pax_global_header00006660000000000000000000000064126300442540014512gustar00rootroot0000000000000052 comment=8a67ae78b8b978877670653817005db82f7a1c1b april-ann-0.4.1/000077500000000000000000000000001263004425400133755ustar00rootroot00000000000000april-ann-0.4.1/.dir-locals.el000066400000000000000000000001711263004425400160250ustar00rootroot00000000000000( (nil . ( (c-basic-offset . 2) (tab-width . 8) (indent-tabs-mode . nil) ) ) ) april-ann-0.4.1/.gitignore000066400000000000000000000011471263004425400153700ustar00rootroot00000000000000gmon.out .dir-locals.el april_tools .april-ann*pc # ignores any shell script ########################## *.sh # Auxiliary include file # ########################## lua5.2-deb-multiarch.h # Building dirs # ################# build_* bin dep_graph.dot include lib doxygen_doc # Emacs backups # ################# *~ \#*\# .\#* # Vim swap # *.swp # OS generated files # ###################### .DS_Store .DS_Store? ._* .Spotlight-V100 .Trashes Icon? ehthumbs.db Thumbs.db # Emacs Clang autocompletion # ############################## .clang-completion-error # Global tags # ############### GPATH GRTAGS GSYMS GTAGS april-ann-0.4.1/.gitmodules000066400000000000000000000001231263004425400155460ustar00rootroot00000000000000[submodule "luapkg"] path = luapkg url = https://github.com/april-org/luapkg.git april-ann-0.4.1/.maketravis.sh000077500000000000000000000027101263004425400161600ustar00rootroot00000000000000#!/bin/bash . configure.sh UNAME=$(uname) if [[ $UNAME == "Linux" ]]; then if [[ $CC == gcc ]]; then if [[ $TEST_OMP == "yes" ]]; then ## echo "**** GCC RELEASE-ATLAS ****" && ## make release-atlas && echo "**** GCC TEST-DEBUG-ATLAS ****" && make test-debug-atlas else ## echo "**** GCC RELEASE-NO-OMP ****" && ## make release-no-omp && echo "**** GCC TEST-DEBUG-NO-OMP ****" && make test-debug-no-omp fi elif [[ $CC == clang ]]; then if [[ $TEST_OMP == "no" ]]; then ## echo "**** CLANG RELEASE-NO-OMP ****" && ## make release-no-omp && echo "**** CLANG TEST-DEBUG-NO-OMP ****" && make test-debug-no-omp else echo "Unable to run OMP test with clang" exit 10 fi else echo "Unknown variable CC=$CC" exit 10 fi elif [[ $UNAME == "Darwin" ]]; then if [[ $CC == clang ]]; then if [[ $TEST_OMP == "no" ]]; then ## echo "**** CLANG RELEASE-HOMEBREW ****" && ## make release-macosx && echo "**** CLANG TEST-DEBUG-HOMEBREW ****" && make test-debug-homebrew else echo "Unable to run OMP test with clang" exit 10 fi else echo "Unknown variable CC=$CC" exit 10 fi else echo "Unknown UNAME=$UNAME" exit 10 fi april-ann-0.4.1/.travis.yml000066400000000000000000000006431263004425400155110ustar00rootroot00000000000000env: global: - OMP_NUM_THREADS=2 matrix: - TEST_OMP=yes - TEST_OMP=no matrix: exclude: - os: osx compiler: gcc - os: osx env: TEST_OMP=yes - os: linux compiler: clang env: TEST_OMP=yes branches: only: - master - devel before_install: - ./DEPENDENCIES-INSTALLER.sh language: cpp script: ./.maketravis.sh compiler: - gcc - clang os: - linux - osx april-ann-0.4.1/AUTHORS.txt000066400000000000000000000002431263004425400152620ustar00rootroot00000000000000In this project has been worked: - Salvador España Boquera - Jorge Gorbe Moya - Adrián Palacios Corella - Joan Pastor Pellicer - Francisco Zamora Martínez april-ann-0.4.1/CHANGELIST.md000066400000000000000000000536061263004425400153520ustar00rootroot00000000000000ChangeList ========== Master branch release --------------------- ### Unstable changes ### API Changes ### Bugs fixed ### C/C++ ### Other v0.4.1 ------ ### Unstable changes - Improved serialize/deserialize functions, reimplemented all the serialization procedure. - Added exceptions support to LuaPkg and APRIL-ANN, allowing to capture C++ errors into Lua code. - Added `set` class. - Added `series` class. - Added `data_frame` class, similar to Python Pandas DataFrame. - Serialization and deserilization have been updated with more robust and reusable API, implemented in `util.serialize()` and `util.deserialize()` functions. - Added `matrix.ext.broadcast` utility (similar to broadcast in numpy). - Added `ProbablisitcMatrixANNComponent`, which allow to implement probabilistic mixtures of posteriors and/or likelihoods. ### API Changes - Added batch normalization ANN component. - Allowing `matrix.join` to add new axis. - Added methods `prod()`, `cumsum()` and `cumprod()` at `matrix` classes. - Added methods `count_eq()` and `count_neq()` at `matrix` classes. - Serializable objects API have been augmented with methods `ctor_name()` and `ctor_params()` in Lua, refered to `luaCtorName()` and `luaCtorParams()` in C++. - Added `cast.to` to dynamic cast C++ objects pushed into Lua, allowing to convert base class objects into any of its derived classes. - Added `matrix.sparse` as valid values for targets in `ann.loss.mse` and `ann.loss.cross_entropy`. - Changed `matrix` metamethods `__index` and `__newindex`, allowing to use `matrix` objects with standard Lua `operator[]`. - Added `matrix.masked_fill` and `matrix.masked_copy` matrix. - Added `matrix.indexed_fill` and `matrix.indexed_copy` matrix. - Added `ann.components.probabilistic_matrix`, and its corresponding specializations `ann.components.left_probabilistic_matrix` and `ann.components.right_probabilistic_matrix`. - Added operator[] in the right side of matrix operations. - Added `ann.components.transpose`. - Added `max_gradients_norm` in `traianble.supervised_trainer`, to avoid gradients exploding. - Added `ann.components.actf.sparse_logistic` a logistic activation function with sparsity penalty. - Simplified `math.add`, `math.sub`, ... and other math extensions for reductions, their original behavior can be emulated by using `bind` function. - Added `bind` function to freeze any positional argument of any Lua function. - Function `stats.boot` uses `multiple_unpack` to allow a table of sizes and the generation of multiple index matrices. - Added `multiple_unpack` Lua function. - Added `__tostring` metamethod to numeric memory blocks in Lua. - Added `dataset.token.sparse_matrix`, a dataset which allow to traverse by rows a sparse matrix instance. - Added `matrix.sparse.builders.dok`, a builder which uses the Dictionary-of-Keys format to construct a sparse matrix from *scratch*. - Added method `data` to numeric matrix classes. - Added methods `values`, `indices`, `first_index` to sparse matrix class. ### Bugs fixed - Fixed bugs when reading bad formed CSV files. - Fixed bugs at statistical distributions. - FloatRGB bug solved on equal (+=, -=, ...) operators. This bug affected ImageRGB operations such as resize. - Solved problems when chaining methods in Lua, some objects end to be garbage collected. - Improved support of strings in auto-completion (rlcompleter package). - Solved bug at `SparseMatrix` when reading it from a file. - Solved bug in `Image::rotate90_cw` methods. - Solved bug in `SparseMatrix::toDense()` method. ### C/C++ - Better `LuaTable` accessors, using `[]` operator. - Implementation of matrix `__index`, `__newindex` and `__call` metamethods in C++. - Implementation of `matProd()`, `matCumSum()` and `matCumProd()` functions. - Implementation of `matCountEq()` and `matCountNeq()` functions for `Matrix`. - Updated `matrix_ext_operations.h` to change API of matrix operations. All functions have been overloaded to accept an **in-place** operation and another version which receives a destination matrix. - Adding iterators to language models. - Added `MatrixScalarMap2` which receives as `input2` a `SparaseMatrix` instance. This functions needs to be generalized to work with CPU and CUDA. - The method `SparseMatrix::fromDenseMatrix()` uses a `DOKBuilder` object to build the sparse matrix. - The conversion of a `Matrix` into a `SparseMatrix` has been changed from a constructor overload to the static method `SparseMatrix::fromDenseMatrix()`. ### Other - Added support for [IPyLua](https://github.com/pakozm/IPyLua). - Optimized matrix access for confusion matrix. - Minor changes in `class.lua`. - Improved binding to avoid multiple object copies when pushing C++ objects. - Added Git commit hash and compilation time. v0.4.0 ------ ### Unstable changes - Added `matrix.op.repmat` function. - Added `matrix.ext.iterate` iterator. - Added statistical distributions in `stats.dist`. - Added `matrix.ext.convolution` and `matrix.ext.real_fftwh`. - Added `Matrix::convolution` method. It is in experimental stage, please, be advice to use them by your own risk. - Because of the changes in `Image`, several classes in package `imaging` has been reviewed, consistent tests are necessary to merge with master branch. ### API Changes - Removed major order differentiation in `matrix`. - `tokens.matrix` **automatically** wraps `matrix` instances, from Lua to C++. - `matrix` **automatically** unwraps `tokens.matrix` instances, from C++ to Lua. - Added new methods to `AprilMath::Limits` class. - Added `metrics.roc` for ROC computation. - Added new `class` behavior taken from [Lua OOP-iter](https://github.com/pakozm/lua-oop-iter), in order to introduce more modularity in APRIL-ANN. - New `april_doc` and `april_set_doc` API, works with values instead of strings. - Added `table.values`, `table.ivalues`, `table.keys` and `table.ikeys` iterators. - `matrix.dict` could store sparse and dense float matrices. - Added `matrix.cholesky(...)` method. ### Bugs fixed - Solved bug at `matrix:max()` and `matrix:min()` methods. - Removed memory leak at `SelectANNComponent::doBackprop()` method. - Solved bug at `CopyANNComponent::doBackprop()` method, incorrect behavior for multi-dimensional matrices. - Solved bug at `ZCAWhiteningANNComponent::doBackprop()` method was wrong. - Solved bug in `stats.boot()` function, it wasn't correctly updated to new `class` functions. - Solve bug in `trainable.supervised_trainer`, problem with smooth_gradients flag. - Solved bug in trainable.lua `train_holdout:execute()` method, the pocket algorithm wasn't work with negative loss functions. - Solved bug at class.lua, inifite loop when calling `class.is_a()`. - Solved bug at autoencoder training. - Solved bug in ROC computation. - CUDA is working, time performance of convolutions needs a review. - Solved bug in `constString` extract numeric methods which returns `false` when the extraction procedure ends up to the character after the last valid number. - Solved bug at `Matrix::div` and `SparseMatrix::div` methods. ### C/C++ - Added `LuaTable` class to allow access of Lua tables from C++ code. - Added TAR support in C/C++, allowing to use streams as the standard I/O objects in APRIL-ANN. - Added `basics` namespace which stores almost all C/C++ code in `basics` packages. - Simplified read/write of matrices using the new `StreamInterface` objects. - Added new `StreamInterface` for input/output operations, with specializations for C files, C strings, Lua strings, GZIP files, ZIP files. Other specializations are easier to implement in the future. - Added statistical distribution classes. - Removed C stack trace in ERROR_PRINT and ERROR_EXIT when compiling without debug. - `Image` class code has been reviewed to be more coherent with current `Matrix` class implementation. ### Other v0.3.1 ------ ### Unstable changes - Added `clustering` and `knn` algorithms. - Added `ann.components.zca_whitening` and `ann.components.pca_whitening` classes. - Added `stats.zca_whitening` and `stats.pca_whitening` functions. - Added packages `autodiff` and `autodiff.ann`, with automatic differentiation algorithms. - Added `ann.optimizer.quickprop` algorithm, but stills untested. - Gradients smoothing, based on weights sharing and `bunch_size`, is applied by `trainable.supervised_trainer` objects, not by the `optimizer`. - Added `ann.components.dropout` class. - Added `ann.autoencoders.ae` class, in order to factorize the SDAE code. - Solved problems with CUDA compilation, but it stills not working because an error during cuMemAlloc. - Class interest_points and layout algorithms (still in development). - Added the geometry c++ class for working in to lines and point geometry. ### API Changes - Modified bootstrapping API in order to be similar with R: `stats.boot()` and `stats.boot.ci()`. - Added `ann.optimizer.asgd` for Averaged SGD optimization. - Added `trainable.qlearning_trainer` for reinforcement learning tasks. - Enhanced `util.serialize` and `util.deserialize` to accept functions as argument, allowing to serialize/deserialize over general streams. - Added `iscallable(...)` function. - Added `utest` package, for unit testing. - Added methods to `matrix` which work with sparse matrices. - Added class `matrix.sparse`. - Added method `m:toTabStream(file or gzfile)` to `matrix`. - Added operations `math.log1p` and `math.logadd`. - Added operator `%` to Lua `string` metatable, allowing to do Python-like string formatting, and map-like substitutions. - Added index matrix for min/max operations in `matrix` objects. - Added `serialize` and `deserialize` Lua functions, in `util` package. ### Bugs fixed - Solved bug which makes to load unitialized weight matrices when loading old trainable.supervised_trainer (without `matrix.dict` object). - Solved bug at `Matrix::sliding_window` which makes an early end of the iterator when window has an `offset` different of 0. ### C/C++ - Added `-lcblas` option to `build_release.lua` and `build_debug.lua`. - Added sparse CBLAS wrappers, for CUDA (not tested) and standard release. - Added CBLAS wrappers for float, double, and ComplexF types. - Added geometric parametrizer for off-line text preprocessing. - Added dependency with `liblapacke` for PCA when not available MKL or MacOS X. ### Other - Added argument check at `mathcore.block.*` constructors. - Travis is monitoring only master and devel branches, for push and pull-requests. - Added travis compilation and testing platform for pull-requests. v0.3.1-alpha (pre-relase of v0.3.1-beta) ---------------------------------------- ### API Changes - Added `matrix:linspace(a,b)` and `matrix:linspace(a,b,base)`. - `matrix:transpose()` returns a matrix which references the original. Any modification to the tranposed matrix, will be reflected at the original. - `matrix:cmul` method is now **in-place**, so, if you don't want to modify the original matrix, you need to do `m:clone():cmul(...)` instead of `m:cmul(...)`. - `update` property is added to `ann.optimizers.sgd` object in order to compute the momentum. - Optimizers `execute` method receives a functions which computes the loss, the gradient (mandatory). Any other data is **optional**. - Removed dropout code from activation functions. - Deleted options from ANN components. - Added methods `unroll` and `get` to `ann.components.stack` class. - Added `inf` and `sup` limits to Hard-Tanh activation function. - Added `random:to_lua_string()` method. - Moved `ann.loss.__base__` to `ann.loss`. - Moved `ann.components.actf.__base__` to `ann.components.actf`. ### New features - Added Sauvola's binarization method. - Added a normalize handwritting text utilities based on the main areas of the text. - Added `matrix.dict`, a hash set dictionary in C++ binded to Lua, which allows to execute basic math operations and reductions over the whole set of contained matrices. It major purpose is to represent a set of connection weights or gradients in ANNs. - Added `dataset.token.filter`, which allows ANN components as filters. - Added `trainable.train_holdout_validation` class, which replace `trainable.supervised_trainer:train_holdout_validation` method. - Added `trainable.train_wo_validation` class, which replace `trainable.supervised_trainer:train_wo_validation` method. - Added `trainable.dataset_pair_iterator` and `trainable.dataset_multiple_iterator`, useful to iterate over datasets following different traversal schemes: sequential, shuffled, shuffled with replacement, shuffled with distribution. - Added method `precompute_output_size` in ANN components. - Added `ann.optimizer.cg`, Conjugate Gradient algorithm. - Added `ann.optimizer.rprop`, Resilient Prop algorithm. - Added `batch_fmeasure_micro_avg` and `batch_fmeasure_macro_avg` for multi-class FMeasure computation. - Renamed loss function `local_fmeasure` as `batch_fmeasure`, and improved to work with multi-class models. - Added `ann.loss.zero_one` loss function. - Added `DEPENDENCIES-INSTALLER.sh`. - Added syntactic sugar for `matrix:slice(...)` method: `m("1:2","3:4")` or `m({1,2},{3,4})`, like in Matlab or Octave. - Added `matrix.svd` and `matrix.diagonalize`. - Added `stats.pca`, `stats.mean_centered`, `stats.pca_whitening`. ### Bugs fixed - Memory leak due to the GPUMirroredMemoryBlock pool was solved. - Solved bug at `stats.correlation.pearson`. - Solved bug at `trainable` when using `use_dataset`, `train_dataset`, `validate_dataset`, `grad_check_dataset` methods without a `bunch_size` parameter, and with a trainer which has not a `bunch_size` defined at construction. - Stabilization of log-logistic activation function. - Stabilization of training with cross-entropy and multi-class-entropy. - Solved bug when reading using `matrix.fromTabFilename`. The loader failed when the file had empty lines. - Solved bug at `Matrix::select(...)` C++ method. The matrix offset wasn't be added to the resulting matrix offset. - Solved bug at `SlidingWindow::setAtWindow(...)` C++ method. The matrix offset wasn't be added to the computed window position. - Solved bug at `buffered_memory.h`. Such bug introduces an early stop when reading matrices, ignoring the last lines of files. - Solved problem with `rlcompleter`, which didn't work properly when loaded as a Lua module. - Modified `configure.sh` to inform about any error during Lua building. - Loadable modules are working on MacOs X. ### C/C++ code changes - Added `Matrix::random_acces_iterator`, which reduces the access overhead for random access of a `Matrix` object. It retains the memory pointer forcing an update between host and device (GPU) memory. - Generalized `GPUMirroredBlockBase` to allow the reinterpretation of the underlying memory pointer using different types (reinterpret_cast). - Added `MatrixSet` class template, which stores a dictionary of STRING->MATRIX, useful for ANNs and gradient descent purposes. - Added `StochasticANNComponent` which is base class for stochastic components. - Simplified coupling between ANN components, ANN loss functions, introducing automatic binding between MatrixFloat and TokenMatrixFloat. - ANN Components has a pointer to a `MatrixFloat` instead of `ANN::Connections`. - `ANN::Connections` is a static class with helper functions, and it is binded as `ann.connections`. - Old-weights property is removed from ANN connections. - Added automatic conversion between DataSetFloat and DataSetToken in `dataset.token.filter` and `dataset.token.union`. - Added `FunctionInterface` class, in Lua as `functions` class, superclass of ANN components. v0.3.0-beta relase ------------------ ### API Changes - Added `loss` parameter to `trainable.supervised_trainer` methods. - Added `optimizer` parameter to `trainable.supervised_trainer` methods. - Added `ann.optimizer` package, which has the implementation of weight update based on weight gradient. So, the ANN components only compute gradients. This allows to implement different optimization methods (as "Conjugate Gradient", or "Linear Search Brack-Propagation") with the same gradient computation. - Loss functions `ann.loss` API has been changed, now the loss computation is done in two separated steps: - `matrix = loss:compute_loss(output,target)`: which returns a matrix with the loss of every pair of patterns, allowing to perform several loss computations without taken them into account. - `matrix = loss:accum_loss(matrix)`: which accumulates the loss in the internal state of the class. - Added a new version of `loss` function, which computes mean and sample variance of the loss. Besides, the loss computation is done with doubles, being more accurated than before. - `replacement` parameter in SDAE doesn't force `on_the_fly` parameter, they are independent. - SDAE training has been changed in order to allow the use of LUA datasets, - Replaced `cpp_class_binding_extension` by `class_extension` function, adding Lua classes support besides to CPP binded classes. - Modified `class` and `class_instance` functions to be more homogeneous with C++ binding. - Added support for GZipped matrices load and save from C++, so functions `matrix.savefile` and `matrix.loadfile` (and its correspondence for complex numbers, double, int32, and char) were removed. Methods `matrix.fromFilename` and `matrix.toFilename` accept '.gz' extension. ### Packages rename - Changed package `sdae` to `ann.autoencoders`. - Changed package `loss_functions` to `ann.loss`. - Splitted `mathcore` package into `mathcore` and `complex` packages. - Renamed `math` package to `mathcore` to avoid the collision with Lua standard math library. ### New features - APRIL-ANN is deployed as a standalone executable and as a shared library for Lua 5.2. - Modified `lua.h` to incorporate the GIT commit number in the disclaimer. - Added Lua autocompletion when readline is available. - Implemented SignalHandler class in C++. - Added `signal.register` and `signal.receive` functions to Lua. - Added to `matrix` the methods `map`, `contiguous`, `join`, `abs`, `tan`, `atan`, `atanh`, `sinh`, `asin`, `asinh`, `cosh`, `acos`, `acosh`, `fromMMap`, `toMMap`, `div`, `max`, `min`. - Added `iterator` class, which is a wrapper around Lua iterators, but provides a more natural interface with functional programming procedures as `map`, `filter`, `apply`, or `reduce`. - Added methods `iterate`, `field`, `select` to iterator Lua class. - `table.insert` returns the table, which is useful for reduction operations. - Added `table` method to `iterator` class. - Added naive `L1_norm` regularization. - Added `dataset.clamp`. - Added `mathcore.set_mmap_allocation` function, which allows to forces the use of mmap for `matrix` memory allocation. - Added `ann.components.slice`. - Added GS-PCA algorithm for efficient computation of PCA (iterative algorithm), `stats.iterative_pca` Lua function. - Added basic MapReduce implementation in Lua. - Added `stats.correlation.pearson` Lua class. - Added `stats.bootstrap_resampling` function. - Added `math.add`, `math.sub`, `math.mul`, `math.div` functions. - `trainable` and `ann.mlp.all_all` are using `matrix:to_lua_string()` method. - Added method `to_lua_string()` in all matrix types, so the method produce a Lua chunk which is loadable and produce a matrix. - Added serialization to `parallel_foreach`, allowing to produce outputs which could be loaded by the caller process. - Declaration of `luatype` function as global, it wasn't. - Added `iterable_map` and `multiple_ipairs` functions to the Lua utilities. - Added SubAndDivNormalizationDataSet, applies a substraction and a division of the feature vectors. - Added stepDataset. ### Bugs fixed - Solved bug at `luabind_template.cc`, which introduced spurious segmentation faults due to Lua execution of garbage collection in the middle of a `lua_pushClassName`. - Solved bug at glob function. - Solved bug at matrix iterators operator=. - Solved bug at method `matrix::best_span_iterator::setAtWindow`. Becaose of It the method didn't works when the matrix was a sub-matrix (slice) of other matrix. - Solved bugs at Matrix template constructor which affects to `rewrap` lua method, and to select method, which affects to `select` lua method. - Added binarizer::init() to a binded static_constructor, it is needed to execute init() before decode/encode double numbers, because of endianism. - Solved bug at constString when extracting double numbers in binary format. - MacOS compilation problems solved. - Solved problems with CUDA, it is working again. - Dynamic loading of C modules is working now. ### C/C++ code changes - Added BIND_STRING_CONSTANT to luabind, so it is possible to export C string constants to Lua. - Removed warning of clang about unused variables, adding a new macro `UNUSED_VARIABLE(x)` defined in the header `utils/c_src/unused_variable.h`. - Matrix fromString and toString Lua methods have been improved to write/read directly from Lua string buffer, so the memory print has been reduced. - The C++ routines to write and read files is generalized to work with streams, under the BufferedStream template, and it is instantiated to FILE and gzFile formats. - Added sanity check to cross-entropy and multi-class cross-entropy loss functions, to detect the use of non logarithmic outputs. v0.2.1-beta relase ------------------ - matrices with float (matrix), complex numbers (matrixComplex), double (matrixDouble), int32 (matrixInt32), and char (matrixChar). - GZIO is fresh code, a wrapper over ZLIB, binded using LUABIND. - Added LAPACK support, for matrix inversion computation. - Updated Lua class mean_var to follow the method of Knuth. - CUDA compiles, but stills not working :SSSSSS - Solved problems of table.tostring. - Generalization of matrix math operators. - Specialization of math wrappers for float and complex numbers. - Support for MAT-file format (Matlab matrices). - Added mutual_information package. - Added APRIL_EXEC and APRIL_TOOLS_DIR environment variables to configure.sh - Added scripts for NBEST, but not working :SSSSSS - Some memory leaks, and bugs are solved. april-ann-0.4.1/DEPENDENCIES-INSTALLER.sh000077500000000000000000000107441263004425400171230ustar00rootroot00000000000000#!/bin/bash UNAME=$(uname) echo "System: $UNAME" if [ $UNAME = "Linux" ]; then if [ $(which apt-get) ]; then ubuntu_release=$(lsb_release -r | cut -f 2) if [[ $? -ne 0 ]]; then echo "Unable to call lsb_release command. This script only works in Ubuntu" exit 10 fi if [[ $ubuntu_release == "12.04" ]]; then packages="gfortran cmake pkg-config libz-dev libreadline-dev libblas-dev libatlas-dev libatlas-base-dev libpng12-dev libtiff-dev liblua5.2-dev libncurses5 libncurses5-dev liblapack-dev libzip-dev" if ! dpkg -l $packages > /dev/null; then sudo apt-get -qq update sudo apt-get install -qq $packages if ! ldconfig -p | grep liblapacke > /dev/null; then cwd=$(pwd) cd /tmp/ && wget http://www.netlib.org/lapack/lapack-3.5.0.tgz && tar zxvf lapack-3.5.0.tgz && cd lapack-3.5.0 && cmake -DBUILD_SHARED_LIBS=1 -DLAPACKE=1 -DCMAKE_INSTALL_PREFIX=/usr . && make && sudo make install if [[ $? -ne 0 ]]; then echo "Error installing dependencies" exit 10 fi cd $cwd fi fi else packages="gfortran pkg-config libz-dev libreadline-dev libblas-dev libatlas-dev libatlas-base-dev libpng12-dev libtiff-dev liblua5.2-dev libncurses5 libncurses5-dev liblapacke-dev libzip-dev" if ! dpkg -l $packages > /dev/null; then sudo apt-get -qq update sudo apt-get install -qq gfortran pkg-config libz-dev libreadline-dev libblas-dev libatlas-dev libatlas-base-dev libpng12-dev libtiff-dev liblua5.2-dev libncurses5 libncurses5-dev liblapacke-dev libzip-dev if [[ $? -ne 0 ]]; then echo "Error installing dependencies, only works with ubuntu >= 12.04" exit 10 fi fi fi dest=$(tempfile) echo -e '#include "lua5.2-deb-multiarch.h"\nint main() { return 0; }\n' > $dest.c multiarch=lua/include/lua5.2-deb-multiarch.h multiarch2=lua/lua-5.2.2/src/lua5.2-deb-multiarch.h if ! gcc -c $dest.c 2> /dev/null; then echo "Not found lua5.2-deb-multiarch.h, generating a default one in $multiarch, please, check the content" echo -e "#ifndef _LUA_DEB_MULTIARCH_\n#define _LUA_DEB_MULTIARCH_\n#define DEB_HOST_MULTIARCH \""$(arch)"-linux-gnu\"\n#endif" > $multiarch echo -e "#ifndef _LUA_DEB_MULTIARCH_\n#define _LUA_DEB_MULTIARCH_\n#define DEB_HOST_MULTIARCH \""$(arch)"-linux-gnu\"\n#endif" > $multiarch2 fi if [ ! -z $dest ]; then rm -f $dest* rm -f $(basename $dest).o fi else echo "Error, impossible to install dependencies, this script only works with apt-get" exit 10 fi elif [ $UNAME = "Darwin" ]; then if [ $(which port) ]; then if ! sudo port install zlib readline libpng tiff findutils pkgconfig lua libzip; then echo "ERROR INSTALLING DEPENDENCIES USING MACPORTS" exit 10 fi elif [ $(which brew) ]; then brew update # If the packages are installed, brew is returning != 0 error code #if ! brew install lzlib readline libpng libtiff findutils pkgconfig; then # echo "ERROR INSTALLING DEPENDENCIES USING HOMEBREW" # exit 10 #fi brew install lzlib readline libpng libtiff findutils pkgconfig libzip ################################################################### # THIS UGLY HACK IS BECAUSE LUA52 IS NOT AT DEFAULT HOMEBREW REPO # brew tap homebrew/versions # If the packages are installed, brew is returning != 0 error code #if ! brew install lua52; then # echo "ERROR INSTALLING DEPENDENCIES USING HOMEBREW" # exit 10 #fi brew install lua52 brew link lua52 ################################################################### else echo "Error, impossible to install dependencies, this scripts needs MacPorts or Homebrew" exit 10 fi echo "This script will change the default system BSD find by GNU find" echo "BSD find will be renamed as bfind" if [ ! -e /usr/find/bfind ]; then sudo mv /usr/bin/find /usr/bin/bfind else sudo rm -f /usr/bin/find fi sudo ln -s $(which gfind) /usr/bin/find else echo "Error, impossible to install dependencies, not recognized system: $UNAME" exit 10 fi exit 0 april-ann-0.4.1/EXAMPLES/000077500000000000000000000000001263004425400146135ustar00rootroot00000000000000april-ann-0.4.1/EXAMPLES/digits-from-scratch.lua000066400000000000000000000115311263004425400211700ustar00rootroot00000000000000local digits_image = ImageIO.read(string.get_path(arg[0]).."digits.png") local m1 = digits_image:to_grayscale():invert_colors():matrix() -- -- TRAINING -- -- a simple matrix for the desired output local train_input = dataset.matrix(m1, { patternSize = {16,16}, offset = {0,0}, numSteps = {80,10}, stepSize = {16,16}, orderStep = {1,0} }) local m2 = matrix(10,{1,0,0,0,0,0,0,0,0,0}) -- a circular dataset which advances with step -1 local train_output = dataset.matrix(m2, { patternSize = {10}, offset = {0}, numSteps = {800}, stepSize = {-1}, circular = {true} }) -- VALIDATION -- local val_input = dataset.matrix(m1, { patternSize = {16,16}, offset = {1280,0}, numSteps = {20,10}, stepSize = {16,16}, orderStep = {1,0} }) local val_output = dataset.matrix(m2, { patternSize = {10}, offset = {0}, numSteps = {200}, stepSize = {-1}, circular = {true} }) -- local bunch_size = 32 local thenet,cnns = ann.mlp.all_all.generate("256 inputs 128 tanh 10 log_softmax"):build() local weights_random = random(52324) local cnn_array = iterator(pairs(cnns)):enumerate():table() table.sort(cnn_array, function(a,b) return a[1]0 and count) or 1 w:scal( 1.0/math.sqrt(count*bunch_size) ) end return tr_loss,weight_grads,tr_matrix end, cnns) loss:accum_loss(tr_loss,tr_matrix) end local tr,_=loss:get_accum_loss() return tr end -- local validate = function(thenet,data,loss) loss:reset() for input,target in trainable.dataset_pair_iterator(data) do thenet:reset() local out = thenet:forward(input) loss:accum_loss(loss:compute_loss(out,target)) end local va,_=loss:get_accum_loss() return va end -- local clock = util.stopwatch() clock:go() print("# Epoch Training Validation") local stopping_criterion = trainable.stopping_criteria.make_max_epochs_wo_imp_relative(2) local train_func = trainable.train_holdout_validation{ min_epochs = 100, max_epochs = 1000, stopping_criterion = stopping_criterion } while train_func:execute(function() local tr_loss = train(thenet,training_data,loss,opt) local va_loss = validate(thenet,validation_data,loss) return thenet,tr_loss,va_loss end) do print(train_func:get_state_string()) local state = train_func:get_state_table() if state.current_epoch == state.best_epoch then train_func:save("jjj.lua", "binary", { optimizer = opt, loss = loss, weights = cnns, shuffle = shuffle }) end end clock:stop() local cpu,wall = clock:read() local num_epochs = train_func:get_state_table().current_epoch printf("# Wall total time: %.3f per epoch: %.3f\n", wall, wall/num_epochs) printf("# CPU total time: %.3f per epoch: %.3f\n", cpu, cpu/num_epochs) april-ann-0.4.1/EXAMPLES/digits-prob-mat.lua000066400000000000000000000066641263004425400203340ustar00rootroot00000000000000 -- forces CUDA when available mathcore.set_use_cuda_default(util.is_cuda_available()) -- digits_image = ImageIO.read(string.get_path(arg[0]).."digits.png") m1 = digits_image:to_grayscale():invert_colors():matrix() -- TRAINING -- -- a simple matrix for the desired output train_input = dataset.matrix(m1, { patternSize = {16,16}, offset = {0,0}, numSteps = {80,10}, stepSize = {16,16}, orderStep = {1,0} }) m2 = matrix(10,{1,0,0,0,0,0,0,0,0,0}) -- a circular dataset which advances with step -1 train_output = dataset.matrix(m2, { patternSize = {10}, offset = {0}, numSteps = {800}, stepSize = {-1}, circular = {true} }) -- VALIDATION -- val_input = dataset.matrix(m1, { patternSize = {16,16}, offset = {1280,0}, numSteps = {20,10}, stepSize = {16,16}, orderStep = {1,0} }) val_output = dataset.matrix(m2, { patternSize = {10}, offset = {0}, numSteps = {200}, stepSize = {-1}, circular = {true} }) bunch_size = 256 thenet = ann.mlp.all_all.generate("256 inputs 128 tanh 128 tanh 10 softmax") thenet:push( ann.components.left_probabilistic_matrix{ input=10, output=10, weights="wN", name="wN" } ) trainer = trainable.supervised_trainer(thenet, ann.loss.non_paired_multi_class_cross_entropy(), bunch_size, ann.optimizer.adadelta()) trainer:build() -- trainer:set_option("weight_decay", 0.0001) trainer:set_layerwise_option("wN", "learning_rate", 200.0) trainer:set_layerwise_option("wN", "weight_decay", 0.0) -- we avoid weight_decay in bias trainer:set_layerwise_option("b.", "weight_decay", 0.0) trainer:randomize_weights{ random = random(52324), use_fanin = true, use_fanout = true, inf = -1, sup = 1, } training_data = { input_dataset = train_input, output_dataset = train_output, shuffle = random(25234), } validation_data = { input_dataset = val_input, output_dataset = val_output, } clock = util.stopwatch() clock:go() print("# Epoch Training Validation") stopping_criterion = trainable.stopping_criteria.make_max_epochs_wo_imp_relative(2) train_func = trainable.train_holdout_validation{ min_epochs = 100, max_epochs = 1000, stopping_criterion = stopping_criterion } while train_func:execute(function() local tr = trainer:train_dataset(training_data) local va = trainer:validate_dataset(validation_data) return trainer,tr,va end) do print(train_func:get_state_string(), trainer:norm2("wN")) end local wN = trainer:weights("wN") wN:toTabFilename("wN") print(wN) local wN = thenet:get(thenet:size()):get_normalized_weights() iterator(matrix.ext.iterate(wN, 2)):select(2): apply(bind(wN.adjust_range, nil, 0, 1)) ImageIO.write(Image(wN), "jaja.png") best = train_func:get_state_table().best clock:stop() cpu,wall = clock:read() num_epochs = train_func:get_state_table().current_epoch local val_error,val_variance=best:validate_dataset{ input_dataset = val_input, output_dataset = val_output, loss = ann.loss.zero_one(), } printf("# Wall total time: %.3f per epoch: %.3f\n", wall, wall/num_epochs) printf("# CPU total time: %.3f per epoch: %.3f\n", cpu, cpu/num_epochs) printf("# Validation error: %f +- %f\n", val_error, val_variance) april-ann-0.4.1/EXAMPLES/digits.lua000066400000000000000000000057521263004425400166120ustar00rootroot00000000000000 -- forces CUDA when available mathcore.set_use_cuda_default(util.is_cuda_available()) -- digits_image = ImageIO.read(string.get_path(arg[0]).."digits.png") m1 = digits_image:to_grayscale():invert_colors():matrix() -- TRAINING -- -- a simple matrix for the desired output train_input = dataset.matrix(m1, { patternSize = {16,16}, offset = {0,0}, numSteps = {80,10}, stepSize = {16,16}, orderStep = {1,0} }) m2 = matrix(10,{1,0,0,0,0,0,0,0,0,0}) -- a circular dataset which advances with step -1 train_output = dataset.matrix(m2, { patternSize = {10}, offset = {0}, numSteps = {800}, stepSize = {-1}, circular = {true} }) -- VALIDATION -- val_input = dataset.matrix(m1, { patternSize = {16,16}, offset = {1280,0}, numSteps = {20,10}, stepSize = {16,16}, orderStep = {1,0} }) val_output = dataset.matrix(m2, { patternSize = {10}, offset = {0}, numSteps = {200}, stepSize = {-1}, circular = {true} }) bunch_size = 256 thenet = ann.mlp.all_all.generate("256 inputs 1024 tanh 1024 tanh 10 log_softmax") trainer = trainable.supervised_trainer(thenet, ann.loss.multi_class_cross_entropy(), bunch_size) trainer:build() -- trainer:set_option("learning_rate", 0.02) trainer:set_option("momentum", 0.1) trainer:set_option("weight_decay", 1e-04) trainer:set_option("L1_norm", 1e-05) -- we avoid weight_decay in bias trainer:set_layerwise_option("b.", "weight_decay", 0) trainer:set_layerwise_option("b.", "L1_norm", 0) trainer:randomize_weights{ random = random(52324), use_fanin = true, use_fanout = true, inf = -1, sup = 1, } training_data = { input_dataset = train_input, output_dataset = train_output, shuffle = random(25234), } validation_data = { input_dataset = val_input, output_dataset = val_output, } clock = util.stopwatch() clock:go() print("# Epoch Training Validation") stopping_criterion = trainable.stopping_criteria.make_max_epochs_wo_imp_relative(2) train_func = trainable.train_holdout_validation{ min_epochs = 100, max_epochs = 1000, stopping_criterion = stopping_criterion } while train_func:execute(function() local tr = trainer:train_dataset(training_data) local va = trainer:validate_dataset(validation_data) return trainer,tr,va end) do print(train_func:get_state_string()) end best = train_func:get_state_table().best clock:stop() cpu,wall = clock:read() num_epochs = train_func:get_state_table().current_epoch local val_error,val_variance=best:validate_dataset{ input_dataset = val_input, output_dataset = val_output, loss = ann.loss.zero_one(), } printf("# Wall total time: %.3f per epoch: %.3f\n", wall, wall/num_epochs) printf("# CPU total time: %.3f per epoch: %.3f\n", cpu, cpu/num_epochs) printf("# Validation error: %f +- %f\n", val_error, val_variance) april-ann-0.4.1/EXAMPLES/digits.png000066400000000000000000000605771263004425400166230ustar00rootroot00000000000000PNG  IHDR@0IaFIDATxڥۖ亪DgUe"f W|N@ vss>ߋ1g@Bm~)ѹ2?':S@&&~|̶OӐR/%ڥOO(KU+`& "r՟zzT_Zo|bjL| X2?ڱZYj_@Up_6CMʇNKwH'HL#$B([6ڈ|so|q[%q;L4{fҊojg;Wri^Y1k0?ro}@`= dV@/ dM&|ˇ{_qStuG[9p˾v[tw6rRv sZ`rxBS ։Q+2nUzQ oH=Od_pXs"R502|=!Ny_| "7 /5Rݲ { x\gטo*;esΩ3%O.8a7-yf,1jan[k~0B,S,*!7@9 iia@>*Jxs] I $N7@QFm9 Ͷ-$xߎQQ4yPVs<^.jP  6s ~B%Eչ P0? )mDp|+Wpi$vY~ 艕[UN@逞,9ic ]xEQQ/٣i?hG))(/Ebd,#Ahmp. 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IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. =============================================================================== april-ann-0.4.1/README.md000066400000000000000000000432131263004425400146570ustar00rootroot00000000000000APRIL-ANN ========= [![Build Status](https://travis-ci.org/pakozm/april-ann.png?branch=master)](https://travis-ci.org/pakozm/april-ann) Travis CI (master branch) [![Build Status](https://travis-ci.org/pakozm/april-ann.png?branch=devel)](https://travis-ci.org/pakozm/april-ann) Travis CI (devel branch) User documentation ------------------ Follow [wiki](https://github.com/pakozm/april-ann/wiki) for user documentation. Tutorials --------- Tutorials are available at [april-ann-tutorials](https://github.com/april-org/april-ann-tutorials) repository. Contributions ------------- Contributions are wellcome. Only pull requests to `devel` branch will be accepted, so avoid to create pull requests to `master`. A Travis CI instance will check that your request passes all tests. For Lua unit testing use the package `basics/utest`, and for C++ unit testing the package `basics/gtest`. At the end of this document there are information about Doxygen documentation which can be useful for C/C++ developing. For Lua developing use the wiki. It is possible to make a pull request directly to `master` branch for bug or memory leak solving. Dependencies and basic setup ---------------------------- Clone the repository and enter to it: ``` $ git clone https://github.com/pakozm/april-ann.git $ cd april-ann ``` The first time you want to run APRIL-ANN, you need to install dependencies in Linux (via apt-get) and in MacOS X (via MacPorts/Homebrew). There is an automatic shellscript which covers majorly Ubuntu (other Debian based distributions can be supported) and MacOS X systems. You just need to run: ```$ ./DEPENDENCIES-INSTALLER.sh``` ### Requirements, installed by previous script Requires the following libraries. Versions are only orientative, it could work with older and newer versions whenver the API was compatible. - GNU C++ compiler (g++): v 4.7.2 - Only in Linux systems: Lua 5.2 headers to tell APRIL-ANN the default system path for Lua modules (`lua5.2-deb-multiarch.h` header). - BLAS implementation: ATLAS (v. 3), Intel MKL (v. 10.3.6), MacOS Accelerate Framework - Threads posix (pthread) - Readline (libreadline) - OpenMP - LAPACK library, offered by liblapack_atlas, mkl_lapack, or MacOS Accelerate Framework - LAPACKE library when compiling with ATLAS The following libreries are recommended, but optional, you will need to remove its package from the path `profile_build_scripts/package_list.lua`: - [OPTIONAL] libpng: if you want to open PNG images, package `libpng`. - [OPTIONAL] libtiff: if you want to open TIFF images, package `libtiff`. - [OPTIONAL] libz: support for open of GZIPPED files, package `gzio`. - [OPTIONAL] libzip: support for open ZIP packages, package `zip`. For perform computation on GPU, this optional library, which has an specific make target: - [OPTIONAL] CUDA and CUBLAS: release 4.2.6. Compilation ----------- First, it is mandatory to configure the repo PATH and other stuff. This step is needed every time you start a session, and before compilation: ```$ . configure.sh``` Second, you can compile the APRIL-ANN version which you need. We have developed compiling files for using different libraries. The most simple compilation way is ```$ make``` and it would detect automatically your platform (Darwin or Linux) and your target SUFIX (mkl, atlas, macports or homebrew). The automatic targets are: - **release** automatic platform and sufix detection target (the same as `make` without any argument). - **debug** automatic platform and sufix detection target for debug version. - **test** automatic platform and sufix detection target for test-debug version. There are available more targets, just depending in your particular system installation you can execute them by using `$ make TARGET`: - **release-mkl** needs of MKL library installed at `/opt/MKL` as prefix. - **release-atlas** needs of OMP and ATLAS library. - **release-no-omp** needs ATLAS library. - **release-cuda-mkl** needs CUDA and MKL installed at `/opt/MKL` as prefix. - **release-macports** needs Mac OS X with MacPorts and Accelerate Framework. - **release-homebrew** needs Mac OS X with Homebrew and Accelerate Framework. Besides this targets, it is possible to compile for debug replacing release string with **debug** string, and for testing replacing release by **test-debug**. The makefile has the following variables which can be forced by the user: - **PREFIX** indicates the prefix for libraries and binaries. In Linux it is `/usr`, in Darwin it depends on MacPorts (`/opt/local`) or Homebrew (`/usr/local`). - **LIB** indicates shared library install directory, by default it is `$(PREFIX)/lib` - **INCLUDE** indicates header sources install directory, by default it is `$(PREFIX)/include/april-ann` - **LUALIB** indicates where Lua library modules are installed, by default it is `$(PREFIX)/lib/lua/5.2` - **LUAMOD** indicates where Lua code modules are installed, by default it is `$(PREFIX)/share/lua/5.2` and there will be created `april_tools` folder with a copy of the content of repository's `tools` folder. - **BIN** indicates where you want to install binary files, by default it is `$(PREFIX)/bin` Each of this targets will need a little configuration depending on your library installation. For example, in order to compile with MKL, the file `profile_build_scripts/build_mkl_release.lua` contains the following sections (among others): ``` global_flags = { debug="no", use_lstrip = "no", use_readline="yes", optimization = "yes", platform = "unix", extra_flags={ -- For Intel MKL :) "-DUSE_MKL", "-I/opt/MKL/include", -------------------- "-march=native", "-msse", "-DNDEBUG", }, extra_libs={ "-lpthread", -- For Intel MKL :) "-L/opt/MKL/lib", "-lmkl_intel_lp64", "-Wl,--start-group", "-lmkl_intel_thread", "-lmkl_core", "-Wl,--end-group", "-liomp5" }, }, ``` You need to especify the `-I` option to the compiler, and all the extra_libs stuff related with MKL. Exists one build file for each possible target: `build_release.lua`, `build_debug.lua`, `build_mkl_release.lua`, `build_mkl_debug.lua`, ... and so on. The binary will be generated at `bin/april-ann`, which incorporates the Lua 5.2 interpreter and works without any dependency in Lua. Besides, a shared library and a Lua module will be generated at `lib/libapril-ann.so` and `lib/aprilann.so`, so it is possible to use `require` from Lua to load APRIL-ANN in a standard Lua 5.2 interpreter. In order to require `aprilann` module it is required the installation of both libraries in their corresponding place in your system. Normally this can be done executing `$ sudo make install`. **NOTE** that loading `april-ann` as a Lua 5.2 module, you need to have the `.so` library in the `package.cpath` or LUA_CPATH. It is possible to install it in your system defaults following next section. ENJOY! Installation ------------ The installation is done executing: ``` $ sudo make install ``` This procedure copies the binary to system location in `/usr` (or in `/opt/local` for Mac OS X via MacPorts). The shared library is copied to Lua default directory, in order to load it by using `require` function. *If you are using a non default installation (a custom one), please copy the `.so` files manually to your `package.cpath` or LUA_CPATH*. Use --- - You can execute the standalone binary: ``` $ april-ann APRIL-ANN v0.2.1-beta COMMIT 920 Copyright (C) 2012-2013 DSIC-UPV, CEU-UCH This program comes with ABSOLUTELY NO WARRANTY; for details see LICENSE.txt. This is free software, and you are welcome to redistribute it under certain conditions; see LICENSE.txt for details. Lua 5.2.2 Copyright (C) 1994-2013 Lua.org, PUC-Rio > print "Hello World!" Hello World! ``` - It is possible to use APRIL-ANN as a Lua module, loading only the packages which you need (i.e. `require("aprilann.matrix")`), or loading the full library (`require("aprilann")`). **Be careful**, the APRIL-ANN modules doesn't follow Lua guidelines and have lateral effects because of the declaration of tables, functions, and other values at the GLOBALs Lua table. Before using APRIL-ANN as a Lua module you need to install it into your system (currently only available for Linux systems) by executing `$ sudo make install`. ``` $ lua Lua 5.2.2 Copyright (C) 1994-2013 Lua.org, PUC-Rio > require "aprilann.matrix" > require "aprilann" APRIL-ANN v0.2.1-beta COMMIT 920 Copyright (C) 2012-2013 DSIC-UPV, CEU-UCH This program comes with ABSOLUTELY NO WARRANTY; for details see LICENSE.txt. This is free software, and you are welcome to redistribute it under certain conditions; see LICENSE.txt for details. > print "Hello World!" Hello World! ``` Citation -------- If you are interested in use this software, please cite correctly the source. In academic publications you can use this bibitem: ```bibtex @misc{aprilann, Author = {Francisco Zamora-Mart\'inez and Salvador Espa{\~n}a-Boquera and Jorge Gorbe-Moya and Joan Pastor-Pellicer and Adri\'an Palacios-Corella}, Note = {{https://github.com/pakozm/april-ann}}, Title = {{APRIL-ANN toolkit, A Pattern Recognizer In Lua with Artificial Neural Networks}}, Year = {2013}} ``` Publications ------------ List of research papers which uses this tool: - Joan Pastor-Pellicer, Salvador España-Boquera, Francisco Zamora-Martínez, M. Zeshan Afzal, M.J. Castro-Bleda. [Insights on the Use of Convolutional Neural Networks for Document Image Binarization](http://link.springer.com/chapter/10.1007/978-3-319-19222-2_10), *IWANN*, *Advances in Computational Intelligence*, pages 115-126, 2015. - Joan Pastor-Pellicer, Salvador España-Boquera, Francisco Zamora-Martínez, María José Castro-Bleda. [Handwriting Normalization by Zone Estimation using HMM/ANNs](http://people.sabanciuniv.edu/berrin/cs581/Papers/icfhr2014/data/4334a633.pdf), *ICFHR*, pages 633-638, 2014. - Francisco Zamora-Martínez, Pablo Romeu, Paloma Botella-Rocamora, and Juan Pardo. [On-line learning of indoor temperature forecasting models towards energy efficiency](http://dx.doi.org/10.1016/j.enbuild.2014.04.034), *Energy and Buildings*, 83:162-172, 2014. - Francisco Zamora-Martínez, Pablo Romeu, Paloma Botella-Rocamora, and Juan Pardo. [Towards Energy Efficiency: Forecasting Indoor Temperature via Multivariate Analysis](http://www.mdpi.com/1996-1073/6/9/4639). *Energies*, 6(9):4639-4659, 2013. - Pablo Romeu, Francisco Zamora-Martinez, Paloma Botella, and Juan Pardo. [Time-Series Forecasting of Indoor Temperature Using Pre-trained Deep Neural Networks](http://dx.doi.org/10.1007/978-3-642-40728-4_57). In *ICANN*, pages 451-458. 2013. - Joan Pastor-Pellicer, Francisco Zamora-Martinez, Salvador España-Boquera, and M.J. Castro-Bleda. [F-Measure as the error function to train Neural Networks](http://dx.doi.org/10.1007/978-3-642-38679-4). In *Advances in Computational Intelligence, IWANN, part I*, LNCS, pages 376-384. Springer, 2013. - F. Zamora-Martínez, Pablo Romeu, Juan Pardo, and Daniel Tormo. [Some empirical evaluations of a temperature forecasting module based on Artificial Neural Networks for a domotic home environment](http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0004133502060211). In *IC3K - KDIR*, pages 206-211, 2012. Our ancient ANN implementation in the former APRIL tookit was published here: - S. España-Boquera, F. Zamora-Martinez, M.J. Castro-Bleda, J. Gorbe-Moya. [Efficient BP algorithms for general feedforward neural networks](http://link.springer.com/chapter/10.1007%2F978-3-540-73053-8_33#page-1). In *IWINAC*, pages 327-336, 2007. Other projects using it ----------------------- Competition participations and other projects where APRIL-ANN has been used: - [Kaggle American Epilepsy Society Seizure Prediction Challenge](https://www.kaggle.com/c/seizure-prediction), system ESAI-CEU-UCH positioned as 4th in the leaderboard. [Download from GitHub](https://github.com/ESAI-CEU-UCH/kaggle-epilepsy) the code to run this system. Packages -------- APRIL-ANN is compiled following a package system. In the directory packages you could find a tree of directory entries. Leaves in the tree are directories which contain file "package.lua". The "package.lua" defines requirements, dependencies, libraries, and other stuff needed by the corresponding package. Each package could contain this directories: - c_src: source files (.h, .cc, .c, .cpp, .cu, and others). - binding: binding files (.lua.cc), a kind of templatized file which generates the glue code between C/C++ and Lua. - lua_src: lua source files which define functions, tables, and pseudo-classes in Lua. - doc: doxygen documentation additional files. - test: examples and files for testing. At root directory exists a file named "package_list.lua". It is a Lua table with the name of packages that you want to compile. If you don't want or don't have libpng, or libtiff, or other library, you could erase the package name from this list to avoid its compilation. Includes these sources ---------------------- - Lua virtual machine 5.2.2: http://www.lua.org/ - Luiz's lstrip for Lua 5.1, adapted to compile with Lua 5.2.2: http://www.tecgraf.puc-rio.br/~lhf/ftp/lua/5.1/lstrip.tar.gz - MersenneTwister: http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html - Median filter from Simon Perreault: http://nomis80.org/ctmf.html - RuningStat class for efficient and stable computation of mean and variance: http://www.johndcook.com/standard_deviation.html - Mike Pall's advanced readline patch for Lua: http://smbolton.com/lua.html#readline - Google C++ Testing Framework: https://code.google.com/p/googletest/ - (Included, but not used) Lua autocompletion rlcompleter release 2, by rthomas: https://github.com/rrthomas/lua-rlcompleter - [Lua base64 encoding](https://github.com/ErnieE5/ee5_base64) developed by Ernie Ewert. Wiki documentation ------------------ - [PDF version](https://rawgithub.com/wiki/pakozm/april-ann/WIKI.pdf) - [HTML one-page](https://rawgithub.com/wiki/pakozm/april-ann/WIKI.html) Doxygen documentation --------------------- The documentation of the devel branch will be mantained as updated as possible in the following links: - [C/C++ developer manual](http://pakozm.hol.es/STUFF/doxygen_doc/developer/html/index.html) - [C/C++ binding manual](http://pakozm.hol.es/STUFF/doxygen_doc/user_refman/html/index.html) However, you can produce the Doxygen documentation of the branch where you are working by using the makefile's `document` target. Please, note that you need to have installed [Doxygen](www.doxygen.org) and [Graphviz](http://www.graphviz.org/). ``` $ make document $ open doxygen_doc/developer/html/index.html ``` The last command can be substituted by you opening the indicated location in your prefered web browser ;) LINUX dependencies installation ------------------------------- Execute: `$ ./DEPENDENCIES-INSTALLER.sh` If your distribution is not supported (currently only Ubuntu has support), then install g++, libatlas-dev, libreadline-dev, libpng-dev, libtiff-dev, libz-dev, libopenmp-dev, libzip-dev, liblua5.2-dev. MAC OS X dependencies installation ---------------------------------- Via MacPorts: - Install [MacPorts](http://www.macports.org/) - Execute `$ ./DEPENDENCIES-INSTALLER.sh` Or via HomeBrew: - Install [Homebrew](http://brew.sh/) - Execute `$ ./DEPENDENCIES-INSTALLER.sh` Building new modules out of APRIL-ANN repository ------------------------------------------------ Find the code base necessary for compilation of new modules at [APRIL-ANN module example](https://github.com/april-org/april-ann-module-example). Currently this option has been tested for Linux systems, despite it can be done in MacOS X. So, for Linux systems, you need to install APRIL-ANN using the following commands (after you have downloaded or cloned the main repository): ``` $ ./DEPENDENCIES-INSTALLER.sh $ make $ sudo make install ``` After that, you need to link your software using `pkg-config` to configure your compiler: ``` $ g++ -fPIC -shared -o YOUR_MODULE_NAME.so *.o $(pkg-config --cflags --libs april-ann) ``` Don't forget to require APRIL-ANN in your C++ code using the following instruction: ```C luaL_requiref(L, "aprilann", luaopen_aprilann, 1); ``` Once you have done this steps, you can load your module into APRIL-ANN using Lua interpreter: ``` $ lua Lua 5.2.2 Copyright (C) 1994-2013 Lua.org, PUC-Rio > your_module = require "YOUR_MODULE_NAME" APRIL-ANN v0.4.0 Copyright (C) 2012-2015 DSIC-UPV, CEU-UCH Compiled at Sat Jul 18 13:45:52 2015, timestamp 1437219952 This program comes with ABSOLUTELY NO WARRANTY; for details see LICENSE.txt. This is free software, and you are welcome to redistribute it under certain conditions; see LICENSE.txt for details. ``` The next C++ code is an example of file which can be loaded as external module for APRIL-ANN: ```C++ // includes all APRIL-ANN dependencies and declares luaopen_aprilann header #include "april-ann.h" using AprilMath::MatrixExt::Initializers::matFill; using AprilUtils::LuaTable; using AprilUtils::SharedPtr; using Basics::MatrixFloat; // exported function example int get(lua_State *L) { SharedPtr m = new MatrixFloat(2, 10, 20); matFill(m.get(), 20.0f); // using LuaTable you can push APRIL-ANN objects in Lua stack (be careful, // not all objects can be pushed) LuaTable::pushInto(L, m.get()); return 1; } // declaration of module opening function extern "C" { int luaopen_example(lua_State *L) { static const luaL_Reg funcs[] = { {"get", get}, {NULL, NULL} }; luaL_requiref(L, "aprilann", luaopen_aprilann, 1); lua_pop(L, 1); luaL_newlib(L, funcs); return 1; } } ``` The module can be loaded using a Lua 5.2 interpreter (for instance, the one deployed with APRIL-ANN, but not the `april-ann` executable command), as indicated above. april-ann-0.4.1/STYLEGUIDE.md000066400000000000000000000116071263004425400154020ustar00rootroot00000000000000# APRIL-ANN source code **style guide** The coding style is not homogeneous becase some code parts are very old. However, for every new and fresh code, this guide will be followed. ## C/C++ style guide Requirements and sugestions: - Use always a namespace where new code will be declared. In this way, the developer documentation will be clearer. - Put public methods and properties in the top of class definitions, then protected stuff and finally private stuff. This allows a better reading of interfaces directly from code. - Use doxygen documentation style like in the example above. - For large code blocks (between { ... }) it is nice to indicate at the closing brace which code is being closed, using a simple comment with //. - **Smart pointers** are being introduced recently. The can be useful to be used in function arguments and in classes properties. In this way, becomes idiomatic the meaning of how the function or the class is being to use the given reference. ### Coding style #### General rules - Indentation: Two spaces indentation. Tabs are not recommended, please, substitute them by spaces. - Namespaces: Namespaces are in UpperCamelCase. - Classes: Class names (and structs) are in UpperCamelCase. - Methods: Method names in lowerCamelCase. - Properties: In lower case with underscore sepparating words. - Variables: In lower case with underscore sepparating words. - Constants: In upper case with underscore sepparating words. - Virtual methods: Always let the `virtual` clause in derived classes, in order to allow the code to indicate it is polymorphic. #### Class declaration and implementation - Separate the code in different files, in order to improve legibility and understanding. If one file requires to implement more than one class, there must be a good reason for it ;) - Unless inline methods, it is better to separate declaration in .h and implementation in .cc or .cu (for C++ or Cuda). - In derived classes write always **virtual** in rewritten methods and *destructors*. #### Examples ```C++ /// A briefly documented stuff, use this style. #define ZERO_CONSTANT 0 /// My namespace whatever. namespace NameSpaceWhatever { /** * @brief Brief documentation for this class. * * Use this style for more complex documentation, allowing to introduce @brief, * @param, @return, @note, @see, among other Doxygen tags. */ class ClassName : public OtherClassName { public: /// Constructor. ClassName(int int_property, float float_property) : OtherClassName(), int_property(int_property), float_property(float_property) { } /// Getter. int getIntProperty() const { return int_property; } /// Getter. float getFloatProperty() const { return float_property; } private: /// An int constant. const int ONE_CONSTANT = 1; /// An int property. int int_property; /// A float property. float float_property; }; // class ClassName /** * @brief A function which adds two values. * * This function adds two values using the awesome add operator. * * @param a - The first value passed by reference. * * @param b - The second value passed by reference. */ template T addTwo(const T &a, const T &b) { // underscored variables T auxiliary = a + b; return auxiliary; } } // namespace NameSpaceWhatever ``` Class derivation: **parent.h** ```C++ /* *LICENSE COMMENT */ #ifndef PARENT_H #define PARENT_H class Parent { public: Parent(); virtual ~Parent(); virtual void method(); }; #endif // PARENT_H ``` **parent.cc** ```C++ #include "parent.h" Parent::Parent() { ... } Parent::~Parent() { ... } void Parent::method() { // Parent class method implementation } ``` **derived.h** ```C++ /* *LICENSE COMMENT */ #ifndef DERIVED_H #define DERIVED_H #include "parent.h" class Derived : public Parent { public: Derived(); virtual ~Derived(); virtual void method(); }; #endif // DERIVED_H ``` **derived.cc** ```C++ #include "derived.h" Derived::Derived() { ... } Derived::~Derived() { ... } void Derived::method() { // Derived class method implementation } ``` ### Useful macros - Unused variables: `#include "unused_variable.h"` and use `UNUSED_VARIABLE` macro. - Ignored results: `#include "ignore_result.h"` and use `IGNORE_RESULT` macro. - Asserts: `#include "april_assert.h"` and use `april_assert` macro. - Error print and exit: `#include "error_print.h"` and use macros `ERROR_PRINT*` and `ERROR_EXIT*`. - Disallow copy constructor and assignment operator: `#include "disallow_class_methods.h"` and use `APRIL_DISALLOW_ASSIGN(type)` or `APRIL_DISALLOW_COPY_AND_ASSIGN(type)` in the private section of your class. ## Lua style guide Prefered always in lower case with underscore sepparating words. ## LuaPkg packages Package names are prefered to be equal to the global Lua table where C/C++ classes and functions are binded, and where Lua code is written. april-ann-0.4.1/TEST/000077500000000000000000000000001263004425400141545ustar00rootroot00000000000000april-ann-0.4.1/TEST/PERFORMANCE/000077500000000000000000000000001263004425400157155ustar00rootroot00000000000000april-ann-0.4.1/TEST/PERFORMANCE/.gitignore000066400000000000000000000001051263004425400177010ustar00rootroot00000000000000# Ignore other results than which has been added previously results* 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0.000001656 size= 10000 1D 0.000006393 0.000006898 size= 100000 1D 0.000058907 0.000058872 size= 1000000 1D 0.000585269 0.000584890 size= 10000000 1D 0.008668083 0.008668741 FILL_1D_TEST_SUBMATRIX size= 10 1D 0.000000933 0.000001118 size= 100 1D 0.000000877 0.000001122 size= 1000 1D 0.000001293 0.000001653 size= 10000 1D 0.000006677 0.000006939 size= 100000 1D 0.000060254 0.000060238 size= 1000000 1D 0.001441225 0.001439803 size= 10000000 1D 0.017837167 0.017813325 FILL_2D_TEST_SUBMATRIX size= 256 2D 0.000011434 0.000003045 size= 1024 2D 0.000014713 0.000003830 size= 4096 2D 0.000026027 0.000006744 size= 16384 2D 0.000026248 0.000006891 size= 65536 2D 0.000061788 0.000015532 size= 262144 2D 0.000198261 0.000049499 size= 1048576 2D 0.009337583 0.002673924 size= 4194304 2D 0.028605000 0.007301271 size= 16777216 2D 0.110925000 0.028888941 size= 67108864 2D 0.451401000 0.116158962 GEMM size= 256 0.000048161 0.000014791 size= 1024 0.000066142 0.000018958 size= 4096 0.000093743 0.000025909 size= 16384 0.000300236 0.000115884 size= 65536 0.001628565 0.000420451 size= 262144 0.013166375 0.003354877 size= 1048576 0.096735000 0.025643468 size= 4194304 0.825518000 0.221151829 GEMV size= 256 0.000004651 0.000004027 size= 1024 0.000003931 0.000004086 size= 4096 0.000004294 0.000004809 size= 16384 0.000005783 0.000006243 size= 65536 0.000011839 0.000012783 size= 262144 0.000039085 0.000039070 size= 1048576 0.000169315 0.000169344 size= 4194304 0.001905811 0.001906831 NORM2_1D_TEST size= 10 1D 0.000000480 0.000000750 size= 100 1D 0.000000479 0.000000765 size= 1000 1D 0.000000754 0.000001024 size= 10000 1D 0.000003509 0.000003926 size= 100000 1D 0.000041349 0.000041332 size= 1000000 1D 0.000427547 0.000427377 size= 10000000 1D 0.004961286 0.004961423 NORM2_1D_TEST_SUBMATRIX size= 10 1D 0.000000502 0.000000741 size= 100 1D 0.000000603 0.000000795 size= 1000 1D 0.000001138 0.000001319 size= 10000 1D 0.000006449 0.000006959 size= 100000 1D 0.000082109 0.000082077 size= 1000000 1D 0.000968404 0.000968530 size= 10000000 1D 0.009666545 0.009686275 NORM2_2D_TEST_SUBMATRIX size= 256 2D 0.000000936 0.000001308 size= 1024 2D 0.000001911 0.000002063 size= 4096 2D 0.000004549 0.000004728 size= 16384 2D 0.000014255 0.000014247 size= 65536 2D 0.000049386 0.000049368 size= 262144 2D 0.000223308 0.000223241 size= 1048576 2D 0.000936710 0.000936954 size= 4194304 2D 0.004112600 0.004109793 size= 16777216 2D 0.015885714 0.015873705 size= 67108864 2D 0.064948500 0.064871430 DOT_1D_TEST size= 10 1D 0.000000767 0.000001072 size= 100 1D 0.000000811 0.000001070 size= 1000 1D 0.000001225 0.000001225 size= 10000 1D 0.000002690 0.000002690 size= 100000 1D 0.000023076 0.000023983 size= 1000000 1D 0.000645503 0.000645367 size= 10000000 1D 0.008193308 0.008185460 DOT_1D_TEST_SUBMATRIX size= 10 1D 0.000000726 0.000001073 size= 100 1D 0.000000911 0.000001165 size= 1000 1D 0.000001685 0.000001952 size= 10000 1D 0.000009650 0.000010029 size= 100000 1D 0.000091942 0.000091882 size= 1000000 1D 0.001856273 0.001852837 size= 10000000 1D 0.017024833 0.017047683 april-ann-0.4.1/TEST/PERFORMANCE/matrix/results_django_v0.4_1851.log000066400000000000000000000370211263004425400241770ustar00rootroot00000000000000# HOST: django # DATE: Fri Sep 5 15:08:42 2014 # VERSION: 0.4 COMMIT 1851 SUM_1D_TEST size= 10 1D 0.000000545 0.000000678 size= 100 1D 0.000000536 0.000000728 size= 1000 1D 0.000001145 0.000001510 size= 10000 1D 0.000009418 0.000009404 size= 100000 1D 0.000087649 0.000087563 size= 1000000 1D 0.000881175 0.000881174 size= 10000000 1D 0.009414818 0.009407824 SUM_2D_TEST size= 256 1D 0.000000702 0.000000870 size= 1024 1D 0.000001378 0.000001543 size= 4096 1D 0.000004215 0.000004212 size= 16384 1D 0.000014372 0.000014936 size= 65536 1D 0.000057490 0.000057444 size= 262144 1D 0.000230165 0.000230170 size= 1048576 1D 0.000924982 0.000925099 size= 4194304 1D 0.004015880 0.004015646 size= 16777216 1D 0.016052714 0.016055005 size= 67108864 1D 0.063566000 0.063516974 SUM_3D_TEST size= 8 1D 0.000000529 0.000000671 size= 64 1D 0.000000527 0.000000695 size= 512 1D 0.000000939 0.000001089 size= 5832 1D 0.000005524 0.000005741 size= 54872 1D 0.000048425 0.000048401 size= 512000 1D 0.000446102 0.000445924 size= 4741632 1D 0.004513870 0.004514000 size= 42875000 1D 0.040571667 0.040617307 SUM_4D_TEST size= 256 1D 0.000000752 0.000000872 size= 625 1D 0.000000993 0.000001191 size= 4096 1D 0.000004283 0.000004281 size= 14641 1D 0.000013488 0.000013484 size= 65536 1D 0.000057954 0.000057930 size= 234256 1D 0.000206950 0.000206818 size= 1048576 1D 0.000911973 0.000911583 size= 4100625 1D 0.003914846 0.003910578 size= 16777216 1D 0.016200857 0.016226292 size= 65610000 1D 0.062559000 0.062607408 SUM_1D_TEST_SUBMATRIX size= 10 1D 0.000000445 0.000000659 size= 100 1D 0.000000569 0.000000751 size= 1000 1D 0.000001520 0.000001519 size= 10000 1D 0.000009491 0.000009486 size= 100000 1D 0.000087594 0.000087549 size= 1000000 1D 0.001035814 0.001036855 size= 10000000 1D 0.011533222 0.011552228 SUM_2D_TEST_SUBMATRIX size= 256 1D 0.000009810 0.000002708 size= 1024 1D 0.000010104 0.000002741 size= 4096 1D 0.000022725 0.000005719 size= 16384 1D 0.000025834 0.000006772 size= 65536 1D 0.000084457 0.000022264 size= 262144 1D 0.000265432 0.000066371 size= 1048576 1D 0.002906914 0.000722660 size= 4194304 1D 0.013225250 0.003472269 size= 16777216 1D 0.055775000 0.018704414 size= 67108864 1D 0.195474000 0.058665991 SUM_3D_TEST_SUBMATRIX size= 8 1D 0.000008519 0.000002437 size= 64 1D 0.000008407 0.000002110 size= 512 1D 0.000013518 0.000003692 size= 5832 1D 0.000048236 0.000012495 size= 54872 1D 0.000300697 0.000081465 size= 512000 1D 0.002309477 0.000582429 size= 4741632 1D 0.014894571 0.003939595 size= 42875000 1D 0.139530000 0.035353184 CLONE_1D_TEST size= 10 1D 0.176919000 0.059628010 size= 100 1D 0.000006231 0.000001834 size= 1000 1D 0.000011822 0.000003683 size= 10000 1D 0.000006667 0.000012962 size= 100000 1D 0.000090461 0.000090435 size= 1000000 1D 0.001205036 0.001204060 size= 10000000 1D 0.012630750 0.012637138 CLONE_1D_TEST_SUBMATRIX size= 10 1D 0.000001018 0.000001261 size= 100 1D 0.000001268 0.000001471 size= 1000 1D 0.000002116 0.000002284 size= 10000 1D 0.000009333 0.000010446 size= 100000 1D 0.000096190 0.000100046 size= 1000000 1D 0.001825364 0.001826490 size= 10000000 1D 0.017478167 0.017410477 CLONE_2D_TEST_SUBMATRIX size= 256 2D 0.000015636 0.000004234 size= 1024 2D 0.000018869 0.000005234 size= 4096 2D 0.000035441 0.000009179 size= 16384 2D 0.000085577 0.000023811 size= 65536 2D 0.000337217 0.000086037 size= 262144 2D 0.001417986 0.000368410 size= 1048576 2D 0.008825000 0.002341847 size= 4194304 2D 0.028737750 0.007230759 size= 16777216 2D 0.114453000 0.028784990 size= 67108864 2D 0.252474000 0.123588085 CLONE+SCAL_1D_TEST size= 10 1D 0.000006622 0.000004871 size= 100 1D 0.000003851 0.000002071 size= 1000 1D 0.000003018 0.000003138 size= 10000 1D 0.000012048 0.000012524 size= 100000 1D 0.000120461 0.000120525 size= 1000000 1D 0.002080429 0.002083555 size= 10000000 1D 0.021313400 0.021297407 CLONE+SCAL_1D_TEST_SUBMATRIX size= 10 1D 0.000001465 0.000001757 size= 100 1D 0.000001863 0.000002011 size= 1000 1D 0.000003155 0.000003160 size= 10000 1D 0.000013000 0.000013005 size= 100000 1D 0.000109306 0.000118034 size= 1000000 1D 0.002571436 0.002571332 size= 10000000 1D 0.025570500 0.025525749 CLONE+SCAL_2D_TEST_SUBMATRIX size= 256 2D 0.000019384 0.000005084 size= 1024 2D 0.000022370 0.000006262 size= 4096 2D 0.000038655 0.000010203 size= 16384 2D 0.000112800 0.000028645 size= 65536 2D 0.000401373 0.000102182 size= 262144 2D 0.001598619 0.000411696 size= 1048576 2D 0.012040556 0.003039440 size= 4194304 2D 0.042305000 0.010716677 size= 16777216 2D 0.160852000 0.042927027 size= 67108864 2D 0.575767000 0.236745834 CLONE+EXP_1D_TEST size= 10 1D 0.000001390 0.000002046 size= 100 1D 0.000002813 0.000003038 size= 1000 1D 0.000013699 0.000013698 size= 10000 1D 0.000118537 0.000118501 size= 100000 1D 0.001137330 0.001137102 size= 1000000 1D 0.012029778 0.012029092 size= 10000000 1D 0.118670000 0.118900061 CLONE+EXP_1D_TEST_SUBMATRIX size= 10 1D 0.000001527 0.000001770 size= 100 1D 0.000002941 0.000003058 size= 1000 1D 0.000013806 0.000013799 size= 10000 1D 0.000118559 0.000118490 size= 100000 1D 0.001145932 0.001146533 size= 1000000 1D 0.012478000 0.012477318 size= 10000000 1D 0.125330000 0.125418901 CLONE+EXP_2D_TEST_SUBMATRIX size= 256 2D 0.000056938 0.000017201 size= 1024 2D 0.000164373 0.000051660 size= 4096 2D 0.000242789 0.000063324 size= 16384 2D 0.000753724 0.000215822 size= 65536 2D 0.003301516 0.000867290 size= 262144 2D 0.013613375 0.003484011 size= 1048576 2D 0.053725500 0.013950586 size= 4194304 2D 0.208148000 0.054101944 size= 16777216 2D 0.712417000 0.213009834 size= 67108864 2D 1.368678000 0.835540056 CLONE+LOG_1D_TEST size= 10 1D 0.000001701 0.000001995 size= 100 1D 0.000002908 0.000003024 size= 1000 1D 0.000014598 0.000015175 size= 10000 1D 0.000147728 0.000147689 size= 100000 1D 0.001463348 0.001464205 size= 1000000 1D 0.015152286 0.015128408 size= 10000000 1D 0.149492000 0.149580956 CLONE+LOG_1D_TEST_SUBMATRIX size= 10 1D 0.000001505 0.000001805 size= 100 1D 0.000002804 0.000003027 size= 1000 1D 0.000015476 0.000015469 size= 10000 1D 0.000145362 0.000145256 size= 100000 1D 0.001477956 0.001478062 size= 1000000 1D 0.015562429 0.015571424 size= 10000000 1D 0.152776000 0.152764082 CLONE+LOG_2D_TEST_SUBMATRIX size= 256 2D 0.000033861 0.000008764 size= 1024 2D 0.000079911 0.000021483 size= 4096 2D 0.000241511 0.000070779 size= 16384 2D 0.000992139 0.000274040 size= 65536 2D 0.004215750 0.001097381 size= 262144 2D 0.016293000 0.004175425 size= 1048576 2D 0.068737500 0.017320991 size= 4194304 2D 0.273620000 0.068548918 size= 16777216 2D 0.669949000 0.264104128 size= 67108864 2D 1.385203000 1.038366795 FILL_1D_TEST size= 10 1D 0.000000782 0.000001062 size= 100 1D 0.000000703 0.000001038 size= 1000 1D 0.000000746 0.000001162 size= 10000 1D 0.000001890 0.000002191 size= 100000 1D 0.000015346 0.000015948 size= 1000000 1D 0.000210827 0.000210823 size= 10000000 1D 0.008632000 0.008621176 FILL_1D_TEST_SUBMATRIX size= 10 1D 0.000000843 0.000001078 size= 100 1D 0.000000721 0.000001066 size= 1000 1D 0.000001159 0.000001435 size= 10000 1D 0.000004214 0.000004547 size= 100000 1D 0.000040455 0.000040440 size= 1000000 1D 0.001587460 0.001587300 size= 10000000 1D 0.017458333 0.017470678 FILL_2D_TEST_SUBMATRIX size= 256 2D 0.000013451 0.000003503 size= 1024 2D 0.000014171 0.000003762 size= 4096 2D 0.000021742 0.000005653 size= 16384 2D 0.000024052 0.000007032 size= 65536 2D 0.000049043 0.000013072 size= 262144 2D 0.000143304 0.000036895 size= 1048576 2D 0.007807923 0.001987549 size= 4194304 2D 0.028697000 0.007253230 size= 16777216 2D 0.108060000 0.029227018 size= 67108864 2D 0.460131000 0.115869999 GEMM size= 256 0.000011148 0.000012974 size= 1024 0.000035270 0.000019701 size= 4096 0.000068175 0.000017502 size= 16384 0.000261847 0.000066671 size= 65536 0.002733000 0.000820172 size= 262144 0.012187333 0.003054990 size= 1048576 0.099543500 0.025988936 size= 4194304 0.783382000 0.197324038 GEMV size= 256 0.000033349 0.000010431 size= 1024 0.000017699 0.000005478 size= 4096 0.000022413 0.000005772 size= 16384 0.000005598 0.000006043 size= 65536 0.000011899 0.000012848 size= 262144 0.000038151 0.000038133 size= 1048576 0.000184957 0.000185050 size= 4194304 0.001853389 0.001854371 NORM2_1D_TEST size= 10 1D 0.000000387 0.000000744 size= 100 1D 0.000000478 0.000000758 size= 1000 1D 0.000000963 0.000001039 size= 10000 1D 0.000003914 0.000004067 size= 100000 1D 0.000041801 0.000041772 size= 1000000 1D 0.000427413 0.000425911 size= 10000000 1D 0.004786429 0.004788717 NORM2_1D_TEST_SUBMATRIX size= 10 1D 0.000000552 0.000000750 size= 100 1D 0.000000522 0.000000793 size= 1000 1D 0.000001043 0.000001334 size= 10000 1D 0.000007072 0.000007067 size= 100000 1D 0.000080133 0.000080091 size= 1000000 1D 0.000938869 0.000939037 size= 10000000 1D 0.009546000 0.009548642 NORM2_2D_TEST_SUBMATRIX size= 256 2D 0.000000919 0.000001359 size= 1024 2D 0.000001997 0.000002234 size= 4096 2D 0.000004464 0.000004817 size= 16384 2D 0.000014297 0.000014291 size= 65536 2D 0.000052083 0.000052074 size= 262144 2D 0.000214944 0.000214983 size= 1048576 2D 0.001065681 0.001066543 size= 4194304 2D 0.004042600 0.004043808 size= 16777216 2D 0.015787000 0.015806437 size= 67108864 2D 0.064251500 0.064244509 DOT_1D_TEST size= 10 1D 0.000000781 0.000001186 size= 100 1D 0.000000867 0.000001213 size= 1000 1D 0.000001059 0.000001312 size= 10000 1D 0.000002214 0.000002831 size= 100000 1D 0.000024598 0.000024587 size= 1000000 1D 0.000756579 0.000754722 size= 10000000 1D 0.008173769 0.008182085 DOT_1D_TEST_SUBMATRIX size= 10 1D 0.000000918 0.000001174 size= 100 1D 0.000000991 0.000001267 size= 1000 1D 0.000001815 0.000002104 size= 10000 1D 0.000010062 0.000010054 size= 100000 1D 0.000092241 0.000092200 size= 1000000 1D 0.001898075 0.001901060 size= 10000000 1D 0.018239667 0.018246492 april-ann-0.4.1/TEST/PERFORMANCE/matrix/test.lua000066400000000000000000000260151263004425400207070ustar00rootroot00000000000000local arg = arg or {} local use_cuda = (table.remove(arg,1)=="true") if util.is_cuda_available() and use_cuda then mathcore.set_use_cuda_default(true) printf("USING CUDA\n\n") end -- local tests_list = table.invert(arg) -- local clock = util.stopwatch() local rnd = random(1234) local T = function(id, func) local id=id:gsub(" ","_") if #arg == 0 or tests_list[id] then print(id) local ok,msg = pcall(func) if not ok then error(msg) end print() end end local measure_process_time = function(func,...) collectgarbage("collect") local it=0 clock:reset() clock:go() repeat local ok,msg = pcall(func,...) if not ok then error(msg) collectgarbage("collect") end it=it+1 until clock:read() > 0.1 clock:stop() local a,b = clock:read() return a/it,b/it end local root = function (N,r,M) if r == 1 then return N,M end local v = math.floor(N^(1/r)) local tbl = iterator(range(1,r)):map(function() return v end):table() if M then table.insert(tbl,M) end return table.unpack(tbl) end T("SUM 1D TEST", function() for i=1,7 do local N = 10^i local m = matrix(N):uniformf(-1,1,rnd) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"1D", measure_process_time(function() m:sum() end)) end end) T("SUM 2D TEST", function() for i=4,13 do local N = 4^i local m = matrix(root(N,2)):uniformf(-1,1,rnd) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"2D", measure_process_time(function() m:sum() end)) end end) T("SUM 3D TEST", function() for i=1,8 do local N = 9^i local m = matrix(root(N,3)):uniformf(-1,1,rnd) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"3D", measure_process_time(function() m:sum() end)) end end) T("SUM 4D TEST", function() for i=4,13 do local N = 4^i local m = matrix(root(N,4)):uniformf(-1,1,rnd) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"4D", measure_process_time(function() m:sum() end)) end end) ----------------------------------------------------------------------------- T("SUM 1D TEST SUBMATRIX", function() for i=1,7 do local N = 10^i local m = matrix(N,2):uniformf(-1,1,rnd):select(2,1) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"1D", measure_process_time(function() m:sum() end)) end end) T("SUM 2D TEST SUBMATRIX", function() for i=4,13 do local N = 4^i local m = matrix(root(N,2,2)):uniformf(-1,1,rnd):select(3,1) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"2D", measure_process_time(function() m:sum() end)) end end) T("SUM 3D TEST SUBMATRIX", function() for i=1,8 do local N = 9^i local m = matrix(root(N,3,2)):uniformf(-1,1,rnd):select(4,1) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"3D", measure_process_time(function() m:sum() end)) end end) ----------------------------------------------------------------------------- T("CLONE 1D TEST", function() for i=1,7 do local N = 10^i local m = matrix(N):uniformf(-1,1,rnd) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"1D", measure_process_time(function() m:clone() end)) end end) ----------------------------------------------------------------------------- T("CLONE 1D TEST SUBMATRIX", function() for i=1,7 do local N = 10^i local m = matrix(N,2):uniformf(-1,1,rnd):select(2,1) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"1D", measure_process_time(function() m:clone() end)) end end) ----------------------------------------------------------------------------- T("CLONE 2D TEST SUBMATRIX", function() for i=4,13 do local N = 4^i local m = matrix(root(N,2,2)):uniformf(-1,1,rnd):select(3,1) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"2D", measure_process_time(function() m:clone() end)) end end) ----------------------------------------------------------------------------- T("CLONE+SCAL 1D TEST", function() for i=1,7 do local N = 10^i local m = matrix(N):uniformf(-1,1,rnd) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"2D", measure_process_time(function() m:clone():scal(10) end)) end end) ----------------------------------------------------------------------------- T("CLONE+SCAL 1D TEST SUBMATRIX", function() for i=1,7 do local N = 10^i local m = matrix(N,2):uniformf(-1,1,rnd):select(2,1) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"1D", measure_process_time(function() m:clone():scal(10) end)) end end) ----------------------------------------------------------------------------- T("CLONE+SCAL 2D TEST SUBMATRIX", function() for i=4,13 do local N = 4^i local m = matrix(root(N,2,2)):uniformf(-1,1,rnd):select(3,1) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"2D", measure_process_time(function() m:clone():scal(10) end)) end end) ----------------------------------------------------------------------------- T("CLONE+EXP 1D TEST", function() for i=1,7 do local N = 10^i local m = matrix(N):uniformf(-1,1,rnd) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"1D", measure_process_time(function() m:clone():exp() end)) end end) ----------------------------------------------------------------------------- T("CLONE+EXP 1D TEST SUBMATRIX", function() for i=1,7 do local N = 10^i local m = matrix(N,2):uniformf(-1,1,rnd):select(2,1) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"1D", measure_process_time(function() m:clone():exp() end)) end end) ----------------------------------------------------------------------------- T("CLONE+EXP 2D TEST SUBMATRIX", function() for i=4,13 do local N = 4^i local m = matrix(root(N,2,2)):uniformf(-1,1,rnd):select(3,1) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"2D", measure_process_time(function() m:clone():exp() end)) end end) ----------------------------------------------------------------------------- T("CLONE+LOG 1D TEST", function() for i=1,7 do local N = 10^i local m = matrix(N):uniformf(-1,1,rnd) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"1D", measure_process_time(function() m:clone():log() end)) end end) ----------------------------------------------------------------------------- T("CLONE+LOG 1D TEST SUBMATRIX", function() for i=1,7 do local N = 10^i local m = matrix(N,2):uniformf(-1,1,rnd):select(2,1) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"1D", measure_process_time(function() m:clone():log() end)) end end) ----------------------------------------------------------------------------- T("CLONE+LOG 2D TEST SUBMATRIX", function() for i=4,13 do local N = 4^i local m = matrix(root(N,2,2)):uniformf(-1,1,rnd):select(3,1) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"2D", measure_process_time(function() m:clone():log() end)) end end) ----------------------------------------------------------------------------- T("FILL 1D TEST", function() for i=1,7 do local N = 10^i local m = matrix(N):uniformf(-1,1,rnd) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"1D", measure_process_time(function() m:fill(10) end)) end end) ----------------------------------------------------------------------------- T("FILL 1D TEST SUBMATRIX", function() for i=1,7 do local N = 10^i local m = matrix(N,2):uniformf(-1,1,rnd):select(2,1) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"1D", measure_process_time(function() m:fill(10) end)) end end) ----------------------------------------------------------------------------- T("FILL 2D TEST SUBMATRIX", function() for i=4,13 do local N = 4^i local m = matrix(root(N,2,2)):uniformf(-1,1,rnd):select(3,1) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"2D", measure_process_time(function() m:fill(10) end)) end end) ----------------------------------------------------------------------------- T("GEMM", function() for i=4,11 do local N = 2^i local a = matrix(N,N):uniformf(-1,1,rnd) local b = matrix(N,N):uniformf(-1,1,rnd) local c = matrix(N,N):uniformf(-1,1,rnd) printf("\tsize=%10d %20.9f %20.9f\n",c:size(), measure_process_time(function() c:gemm{ A=a, B=b, alpha=1.0, beta=1.0 } end)) end end) ----------------------------------------------------------------------------- T("GEMV", function() for i=4,11 do local N = 2^i local a = matrix(N,N):uniformf(-1,1,rnd) local x = matrix(N):uniformf(-1,1,rnd) local y = matrix(N):uniformf(-1,1,rnd) printf("\tsize=%10d %20.9f %20.9f\n",a:size(), measure_process_time(function() y:gemv{ A=a, X=x, alpha=1.0, beta=1.0 } end)) end end) ----------------------------------------------------------------------------- T("NORM2 1D TEST", function() for i=1,7 do local N = 10^i local m = matrix(N):uniformf(-1,1,rnd) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"1D", measure_process_time(function() m:norm2() end)) end end) ----------------------------------------------------------------------------- T("NORM2 1D TEST SUBMATRIX", function() for i=1,7 do local N = 10^i local m = matrix(N,2):uniformf(-1,1,rnd):select(2,1) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"1D", measure_process_time(function() m:norm2() end)) end end) ----------------------------------------------------------------------------- T("NORM2 2D TEST SUBMATRIX", function() for i=4,13 do local N = 4^i local m = matrix(root(N,2,2)):uniformf(-1,1,rnd):select(3,1) printf("\tsize=%10d %s %20.9f %20.9f\n",m:size(),"2D", measure_process_time(function() m:norm2() end)) end end) ----------------------------------------------------------------------------- T("DOT 1D TEST", function() for i=1,7 do local N = 10^i local a = matrix(N):uniformf(-1,1,rnd) local b = matrix(N):uniformf(-1,1,rnd) printf("\tsize=%10d %s %20.9f %20.9f\n",a:size(),"1D", measure_process_time(function() a:dot(b) end)) end end) ----------------------------------------------------------------------------- T("DOT 1D TEST SUBMATRIX", function() for i=1,7 do local N = 10^i local a = matrix(N,2):uniformf(-1,1,rnd):select(2,1) local b = matrix(N,2):uniformf(-1,1,rnd):select(2,1) printf("\tsize=%10d %s %20.9f %20.9f\n",a:size(),"1D", measure_process_time(function() a:dot(b) end)) end end) ----------------------------------------------------------------------------- T("CONVOLUTION 2D TEST", function() for i=4,6 do local N = 6^i local a = matrix(root(N,2)):uniformf(-1,1,rnd) local b = matrix(17,17):uniformf(-1,1,rnd) printf("\tsize=%10d %s %20.9f %20.9f\n",a:size(),"1D", measure_process_time(function() matrix.ext.convolution(a, { kernel=b, D=2 }) end)) end end) april-ann-0.4.1/TEST/PERFORMANCE/register_performance.lua000066400000000000000000000012201263004425400226200ustar00rootroot00000000000000local script = table.remove(arg,1) assert(script, "Needs a performance script as argument") local outfilename = string.format("%sresults_%s_v%d.%d_%d.log", string.get_path(script), (io.popen("hostname", "r"):read("*l")), util.version()) -- 4 CORES util.omp_set_num_threads(4) -- local f = io.open(outfilename, "w") -- change global environment local old_printf = printf local old_print = print printf = function(fmt,...) old_printf(fmt,...) f:write(string.format(fmt,...)) f:flush() end print = function(...) old_print(...) f:write(...) f:write("\n") f:flush() end april_print_script_header(nil,f) assert(loadfile(script))(arg) f:close() april-ann-0.4.1/TEST/cross-entropy-stability/000077500000000000000000000000001263004425400210055ustar00rootroot00000000000000april-ann-0.4.1/TEST/cross-entropy-stability/test.cc000066400000000000000000000010101263004425400222630ustar00rootroot00000000000000#include #define EPSILON 1e-20f #define MULT 1.01f //2.0f int main() { for (float target=EPSILON; target <= 1.0f; target *= MULT) { for (float output=EPSILON; output <= 1.0f; output *= MULT) { float numerator = output - target; float denominator = output * (1.0f - output); float frac = numerator/denominator; float result = frac * denominator; printf ("%g %g => %g - %g = %g \n", output, target, numerator, result, result-numerator); } } return 0; } 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printf("\n") printf("Target: ") for i = 1,10 do printf(" %.2f",desired[i]) end; printf("\n") printf("Output: ") max,imax = resul:max() clasificado = imax for i = 1,10 do printf(" %.2f",resul:get(i)) end; printf("\n") printf("Autor %2d Digito %d\n",autor,digito) printf("MLP clasifica %d %s\n",clasificado,clasificado == digito and ":)" or ":'(") -- printf("\n\nLos valores de las neuronas de las capas ocultas:\n%s\n\n", -- string.join(lared:activation_values(),",")) print("Pulse intro para continuar, una letra e intro para parar") a = io.read('*l') until string.len(a) > 0 end -- datos para entrenar datosentrenar = { input_dataset = train_input, output_dataset = train_output, shuffle = aleat, bunch_size = bunch_size, } datosvalidar = { input_dataset = val_input, output_dataset = val_output, bunch_size = bunch_size, } -- datos para guardar una matriz de salida de la red msalida = matrix(200,10) dsalida = dataset.matrix(msalida, { patternSize={1,10},offset={0,0},numSteps={200,1},stepSize={1,0}}) datosusar = { input_dataset = val_input, output_dataset = dsalida, } totalepocas = 0 function entrenar(epocas) print("Epoch Training Validation") for epoch = 1,epocas do totalepocas = totalepocas+1 errortrain = trainer:train_dataset(datosentrenar) errorval = trainer:validate_dataset(datosvalidar) printf("%4d %.7f %.7f\n", totalepocas,errortrain,errorval) end end function entrenar_reemplazo(epocas,reemplazos) datosentrenar.replacement = reemplazos print("Epoch Training Validation") for epoch = 1,epocas do totalepocas = totalepocas+1 errortrain = trainer:train_dataset(datosentrenar) errorval = trainer:validate_dataset(datosvalidar) printf("%4d %.7f %.7f\n", totalepocas,errortrain,errorval) end datosentrenar.replacement = nil end function menu() --clrscr() printf("-------- ENTRENAMIENTO DIGITOS -------- \n") printf(" 1 - Entrenar epocas\n") printf(" 2 - Entrenar con reemplazo\n") printf(" 3 - Ver resultados\n") printf(" 4 - Salvar red\n") printf(" 5 - Cargar red\n") printf(" 6 - Ver datos\n") printf(" 7 - Clasificar\n") printf(" 8 - Salir\n") printf("Opcion:") opc = tonumber(io.read('*l')) return opc end function ppal() repeat local opc = menu() if opc == 1 then printf("cuantas epocas? ") cuantas = tonumber(io.read('*l')) entrenar(cuantas) print("Pulse intro para continuar") io.read('*l') elseif opc == 2 then printf("cuantos reemplazos? ") reemplazos = tonumber(io.read('*l')) printf("cuantas epocas? ") cuantas = tonumber(io.read('*l')) entrenar_reemplazo(cuantas,reemplazos) print("Pulse intro para continuar") io.read('*l') elseif opc == 3 then ver_resultado() elseif opc == 4 then printf("Salvar la red, nombre: ") filename = io.read('*l') printf("Ascii o binario? (A/B): ") tipoAB = io.read('*l') printf("Guardamos pesos iteracion anterior? (S/N): ") tipoOLD = io.read('*l') if not use_adrian_mlp then mlp.save(trainer, filename, (tipoAB == "A" and "ascii") or "binary", (tipoOLD == "S" and "old") or nil) else ann.mlp.all_all.save(trainer, filename, (tipoAB == "A" and "ascii") or "binary", (tipoOLD == "S" and "old") or nil) end elseif opc == 5 then printf("Cargar la red, nombre: ") filename = io.read('*l') printf('Leemos la red en "%s"\n',filename) print("Antes",trainer) if not use_adrian_mlp then trainer = mlp.load(filename) else trainer = ann.mlp.all_all.load(filename, bunch_size) end print("Despues",trainer) print("Pulse intro para continuar") io.read('*l') elseif opc == 6 then for index=1,train_output:numPatterns() do --clrscr() print"Introduce cualquier cosa ademas de enter parar parar" verdigito(train_input:getPattern(index)) print(table.concat(train_output:getPattern(index),",")) a = io.read('*l') if (string.len(a) > 0) then break end end elseif opc == 7 then -- clasificamos ------------------------------------- local aux_m = matrix(train_input:numPatterns()) local aux_ds = dataset.matrix(aux_m) trainer:classify{ input_dataset = train_input, output_dataset = aux_ds, } local errors = 0 for i=1,aux_ds:numPatterns() do local pat = train_output:getPattern(i) v,p = table.max(pat) if p ~= aux_ds:getPattern(i)[1] then errors = errors + 1 end end print ("ERROR EN TRAINING: ", errors/aux_ds:numPatterns() .. "%", errors) ------------------------------------- local aux_m = matrix(val_input:numPatterns()) local aux_ds = dataset.matrix(aux_m) trainer:classify{ input_dataset = val_input, output_dataset = aux_ds, } local errors = 0 for i=1,aux_ds:numPatterns() do local pat = val_output:getPattern(i) v,p = table.max(pat) if p ~= aux_ds:getPattern(i)[1] then errors = errors + 1 end end print ("ERROR EN VALIDATION: ", errors/aux_ds:numPatterns() .. " %", errors) print("Pulse intro para continuar") io.read('*l') end until opc == 8 end printf("He cargado\n") ppal() april-ann-0.4.1/TEST/digitos/test.lua000066400000000000000000000077411263004425400173110ustar00rootroot00000000000000-- un generador de valores aleatorios... y otros parametros bunch_size = tonumber(arg[1]) or 64 semilla = 1234 weights_random = random(semilla) description = "256 inputs 256 tanh 128 tanh 10 log_softmax" inf = -1 sup = 1 shuffle_random = random(5678) learning_rate = 0.08 momentum = 0.01 weight_decay = 1e-05 max_epochs = 10 -- training and validation errors = { {2.2762842, 2.0276833}, {1.6794761, 1.2444804}, {0.9245928, 0.6157830}, {0.5167769, 0.3807266}, {0.3109381, 0.3248250}, {0.2184281, 0.2167415}, {0.1626369, 0.1783843}, {0.1271410, 0.1495624}, {0.1077118, 0.1718368}, {0.0960633, 0.1591717}, } epsilon = 1e-03 -------------------------------------------------------------- m1 = ImageIO.read(string.get_path(arg[0]) .. "digits.png"):to_grayscale():invert_colors():matrix() train_input = dataset.matrix(m1, { patternSize = {16,16}, offset = {0,0}, numSteps = {80,10}, stepSize = {16,16}, orderStep = {1,0} }) val_input = dataset.matrix(m1, { patternSize = {16,16}, offset = {1280,0}, numSteps = {20,10}, stepSize = {16,16}, orderStep = {1,0} }) -- una matriz pequenya la podemos cargar directamente m2 = matrix(10,{1,0,0,0,0,0,0,0,0,0}) -- ojito con este dataset, fijaros que usa una matriz de dim 1 y talla -- 10 PERO avanza con valor -1 y la considera CIRCULAR en su unica -- dimension train_output = dataset.matrix(m2, { patternSize = {10}, offset = {0}, numSteps = {800}, stepSize = {-1}, circular = {true} }) val_output = dataset.matrix(m2, { patternSize = {10}, offset = {0}, numSteps = {200}, stepSize = {-1}, circular = {true} }) mathcore.set_use_cuda_default(util.is_cuda_available()) thenet = ann.mlp.all_all.generate(description) trainer = trainable.supervised_trainer(thenet, ann.loss.multi_class_cross_entropy(), bunch_size) trainer:build() trainer:set_option("learning_rate", learning_rate) trainer:set_option("momentum", momentum) trainer:set_option("weight_decay", weight_decay) -- bias has weight_decay of ZERO trainer:set_layerwise_option("b.", "weight_decay", 0) trainer:randomize_weights{ random = weights_random, inf = inf, sup = sup, use_fanin = true, } -- datos para entrenar datosentrenar = { input_dataset = train_input, output_dataset = train_output, shuffle = shuffle_random, } datosvalidar = { input_dataset = val_input, output_dataset = val_output, } totalepocas = 0 errorval = trainer:validate_dataset(datosvalidar) -- print("# Initial validation error:", errorval) clock = util.stopwatch() clock:go() -- print("Epoch Training Validation") train_func = trainable.train_holdout_validation{ max_epochs = max_epochs } -- training loop while train_func:execute(function() local tr = trainer:train_dataset(datosentrenar) local va = trainer:validate_dataset(datosvalidar) return trainer,tr,va end) do print(train_func:get_state_string()) if bunch_size == 64 then local epoch,errortrain,errorval,best_epoch = train_func:get_state() if math.abs(errortrain - errors[epoch][1]) > epsilon then error(string.format("Training error %g is not equal enough to ".. "reference error %g", errortrain, errors[epoch][1])) end if math.abs(errorval - errors[epoch][2]) > epsilon then error(string.format("Validation error %g is not equal enough to ".. "reference error %g", errorval, errors[epoch][2])) end end -- if best_epoch == epoch then train_func:save("wop.lua", "binary", {shuffle=datosentrenar.shuffle}) end end clock:stop() cpu,wall = clock:read() printf("Wall total time: %.3f per epoch: %.3f\n", wall, wall/max_epochs) printf("CPU total time: %.3f per epoch: %.3f\n", cpu, cpu/max_epochs) -- print("Test passed! OK!") april-ann-0.4.1/TEST/xor/000077500000000000000000000000001263004425400147645ustar00rootroot00000000000000april-ann-0.4.1/TEST/xor/xor-MLP-dot-product-action-transpose-weights.lua000066400000000000000000000110221263004425400261220ustar00rootroot00000000000000learning_rate = 0.4 momentum = 0.1 weight_decay = 1e-05 semilla = 1234 aleat = random(semilla) bunch_size = tonumber(arg[1]) or 64 delta = 1e-05 initial_result = { 0.18666581809521, 0.16942968964577, 0.17109067738056, 0.14423334598541 } final_result = { 0.0135539099, 0.9875200987, 0.9875199199, 0.0143862367 } m = matrix.fromString[[ 19 ascii 1.0 0.1 0.2 -1.0 0.3 0.4 -0.5 -1.2 1.0 -2.0 4.0 -4.0 0.1 1.1 -1.5 -1.0 2.0 2.0 -1.0 ]] bias0_m = matrix.fromString[[ 2 ascii 1.0 -1.0 ]] bias1_m = matrix.fromString[[ 3 ascii -0.5 -2.0 0.1 ]] bias2_m = matrix.fromString[[ 1 ascii -1.0 ]] w0_m = matrix.fromString[[ 4 ascii 0.1 0.2 0.3 0.4 ]] w1t_m = matrix.fromString[[ 6 ascii -1.2 4.0 1.1 1.0 -4.0 -1.5 ]] w2_m = matrix.fromString[[ 3 ascii 2.0 2.0 -1.0 ]] function show_weights(lared) lared:show_weights() print() local outds = dataset.matrix(matrix(4)) lared:use_dataset{ input_dataset = ds_input, output_dataset = outds } for i = 1,ds_input:numPatterns() do value = lared:calculate(ds_input:getPattern(i))[1] printf("%s\t %s\t %s\n", table.concat(ds_input:getPattern(i),","), value, outds:getPattern(i)[1]) end print() end function check_result(lared, result) local outds = dataset.matrix(matrix(4)) lared:use_dataset{ input_dataset = ds_input, output_dataset = outds } for i = 1,ds_input:numPatterns() do value = lared:calculate(ds_input:getPattern(i))[1] if math.abs(value - result[i]) > delta then error("Incorrect result using bunch_size=1!!! expected " .. value .. " was " .. result[i]) end if math.abs(outds:getPattern(i)[1] - result[i]) > delta then error("Incorrect result using bunch_size=" .. bunch_size .."!!!") end end end ----------------------------------------------------------- lared = ann.mlp{ bunch_size = bunch_size } -- neuron layers i = ann.units.real_cod{ size = 2, ann = lared, type = "inputs" } h0 = ann.units.real_cod{ size = 2, ann = lared, type = "hidden" } h1 = ann.units.real_cod{ size = 3, ann = lared, type = "hidden" } o = ann.units.real_cod{ size = 1, ann = lared, type = "outputs" } -- connection layers b0 = ann.connections.bias{ size = h0:num_neurons(), ann = lared, w = bias0_m } c0 = ann.connections.all_all{ input_size = i:num_neurons(), output_size = h0:num_neurons(), ann = lared, w = w0_m} b1 = ann.connections.bias{ size = h1:num_neurons(), ann = lared, w = bias1_m } c1 = ann.connections.all_all{ input_size = h1:num_neurons(), output_size = h0:num_neurons(), ann = lared, w = w1t_m } b2 = ann.connections.bias{ size = o:num_neurons(), ann = lared, w = bias2_m } c2 = ann.connections.all_all{ input_size = h1:num_neurons(), output_size = o:num_neurons(), ann = lared, w = w2_m } -- first layer actions lared:push_back_all_all_layer{ input = i, output = h0, bias = b0, weights = c0, actfunc = ann.activations.tanh() } -- second layer actions lared:push_back_all_all_layer{ input = h0, output = h1, bias = b1, weights = c1, actfunc = ann.activations.tanh(), transpose = true } -- third layer actions lared:push_back_all_all_layer{ input = h1, output = o, bias = b2, weights = c2, actfunc = ann.activations.logistic() } lared:set_option("learning_rate", learning_rate) lared:set_option("momentum", momentum) lared:set_option("weight_decay", weight_decay) lared2=ann.mlp.all_all.generate{ topology = "2 inputs 2 tanh 3 tanh 1 logistic", w = m, oldw = m, bunch_size = bunch_size, } lared2:set_option("learning_rate", learning_rate) lared2:set_option("momentum", momentum) lared2:set_option("weight_decay", weight_decay) m_xor = matrix.fromString[[ 4 3 ascii 0 0 0 0 1 1 1 0 1 1 1 0 ]] ds_input = dataset.matrix(m_xor,{patternSize={1,2}}) ds_output = dataset.matrix(m_xor,{offset={0,2},patternSize={1,1}}) -------- -- GO -- -------- check_result(lared, initial_result) check_result(lared2, initial_result) data = { input_dataset = ds_input, output_dataset = ds_output, shuffle = random(1234) } data2 = { input_dataset = ds_input, output_dataset = ds_output, shuffle = random(1234) } for i=1,30000 do lared:train_dataset(data) lared2:train_dataset(data2) end check_result(lared, final_result) check_result(lared2, final_result) print("TEST PASSED!") april-ann-0.4.1/TEST/xor/xor-output.log000066400000000000000000026502731263004425400176540ustar00rootroot00000000000000---------------------------------------------- ---------------------------------------------- Initial values 0,0 0.49837177991867 0,1 0.56214302778244 1,0 0.74469667673111 1,1 0.47552713751793 b1 -0.5 -2 w1 -1.2000000476837 1 4 -4 b2 -1 w2 2 2 ---------------------------------------------- -------------------------------------------- After forward of (0,0) 0,0 0.48070278763771 0,1 0.54420828819275 1,0 0.73190540075302 1,1 0.45829811692238 b1 -0.52342361211777 -2.0104651451111 w1 -1.1999880075455 0.99998998641968 3.9999599456787 -3.9999599456787 b2 -1.0498366355896 w2 1.9811645746231 1.9940392971039 After forward of (0,1) 0,0 0.49532616138458 0,1 0.56277918815613 1,0 0.74130284786224 1,1 0.47480425238609 b1 -0.50459259748459 -2.0112915039062 w1 -1.1999747753143 1.0211522579193 3.9999158382416 -3.9996957778931 b2 -1.0095974206924 w2 2.0071609020233 1.9935339689255 After one epoch 0,0 0.49234294891357 0,1 0.55632698535919 1,0 0.74045896530151 1,1 0.46828258037567 b1 -0.50956290960312 -2.008068561554 w1 -1.2079700231552 0.9996030330658 3.997017621994 -4.0048341751099 b2 -1.0173752307892 w2 1.9976183176041 2.0027861595154 After two epochs 0,0 0.4862080514431 0,1 0.55045384168625 1,0 0.73615819215775 1,1 0.46092438697815 b1 -0.5194331407547 -2.0166413784027 w1 -1.2164492607117 0.99959456920624 3.9939501285553 -4.0100154876709 b2 -1.035166144371 w2 1.9955781698227 2.0062191486359 After 30000 epochs 3 0.55150872468948 4 0.54351460933685 5 0.53730577230453 6 0.53248238563538 7 0.52831441164017 8 0.52443826198578 9 0.52069306373596 10 0.5170077085495 11 0.51334953308105 12 0.50970274209976 13 0.50605857372284 14 0.50241208076477 15 0.49875983595848 16 0.4950989484787 17 0.49142742156982 18 0.48774337768555 19 0.48404532670975 20 0.48033195734024 21 0.47660219669342 22 0.47285515069962 23 0.46909016370773 24 0.46530672907829 25 0.46150451898575 26 0.45768341422081 27 0.4538434445858 28 0.44998472929001 29 0.44610768556595 30 0.44221284985542 31 0.43830072879791 32 0.43437215685844 33 0.43042802810669 34 0.42646926641464 35 0.42249715328217 36 0.41851270198822 37 0.4145173728466 38 0.41051250696182 39 0.40649956464767 40 0.40248024463654 41 0.39845591783524 42 0.39442843198776 43 0.39039942622185 44 0.38637065887451 45 0.38234385848045 46 0.37832090258598 47 0.3743035197258 48 0.37029355764389 49 0.36629271507263 50 0.3623029589653 51 0.3583260178566 52 0.35436350107193 53 0.35041731595993 54 0.34648910164833 55 0.34258037805557 56 0.33869287371635 57 0.33482813835144 58 0.33098763227463 59 0.32717284560204 60 0.32338500022888 61 0.31962561607361 62 0.31589576601982 63 0.31219679117203 64 0.30852973461151 65 0.30489563941956 66 0.3012954890728 67 0.29773023724556 68 0.29420065879822 69 0.2907075881958 70 0.2872516810894 71 0.28383359313011 72 0.28045389056206 73 0.27711308002472 74 0.27381163835526 75 0.27054989337921 76 0.26732820272446 77 0.26414680480957 78 0.26100593805313 79 0.25790578126907 80 0.25484639406204 81 0.25182798504829 82 0.24885034561157 83 0.24591353535652 84 0.24301758408546 85 0.24016226828098 86 0.23734751343727 87 0.23457309603691 88 0.23183879256248 89 0.22914445400238 90 0.22648973762989 91 0.22387439012527 92 0.22129802405834 93 0.21876040101051 94 0.21626105904579 95 0.21379971504211 96 0.21137595176697 97 0.20898929238319 98 0.20663940906525 99 0.20432585477829 100 0.20204815268517 101 0.19980582594872 102 0.19759848713875 103 0.1954255849123 104 0.19328671693802 105 0.19118142127991 106 0.189109146595 107 0.18706941604614 108 0.18506181240082 109 0.18308579921722 110 0.1811408996582 111 0.1792266368866 112 0.17734250426292 113 0.17548805475235 114 0.17366275191307 115 0.17186616361141 116 0.17009779810905 117 0.16835719347 118 0.16664382815361 119 0.16495731472969 120 0.16329717636108 121 0.16166287660599 122 0.16005408763885 123 0.15847027301788 124 0.1569110751152 125 0.15537595748901 126 0.15386456251144 127 0.15237647294998 128 0.15091122686863 129 0.14946846663952 130 0.14804776012897 131 0.146648645401 132 0.14527082443237 133 0.1439139097929 134 0.14257743954659 135 0.14126119017601 136 0.13996461033821 137 0.13868749141693 138 0.13742941617966 139 0.13619002699852 140 0.13496898114681 141 0.13376598060131 142 0.13258065283298 143 0.13141274452209 144 0.13026186823845 145 0.12912772595882 146 0.12801004946232 147 0.12690848112106 148 0.12582276761532 149 0.12475257366896 150 0.12369769066572 151 0.12265780568123 152 0.12163262069225 153 0.12062194943428 154 0.11962544173002 155 0.11864284425974 156 0.11767396330833 157 0.11671851575375 158 0.11577631533146 159 0.11484704166651 160 0.11393047869205 161 0.11302645504475 162 0.11213468760252 163 0.11125502735376 164 0.11038722097874 165 0.10953103005886 166 0.10868629813194 167 0.10785280913115 168 0.10703033953905 169 0.10621871054173 170 0.10541772842407 171 0.1046272739768 172 0.10384707152843 173 0.10307698696852 174 0.10231684148312 175 0.1015664935112 176 0.10082571208477 177 0.10009437054396 178 0.099372312426567 179 0.098659366369247 180 0.097955398261547 181 0.097260251641273 182 0.096573725342751 183 0.095895759761333 184 0.095226146280766 185 0.094564788043499 186 0.093911550939083 187 0.093266218900681 188 0.09262877702713 189 0.091999031603336 190 0.091376848518848 191 0.090762168169022 192 0.090154767036438 193 0.089554600417614 194 0.088961526751518 195 0.088375464081764 196 0.087796248495579 197 0.087223805487156 198 0.086658000946045 199 0.08609876781702 200 0.085545964539051 201 0.084999516606331 202 0.08445930480957 203 0.083925247192383 204 0.08339723944664 205 0.082875169813633 206 0.082358978688717 207 0.081848561763763 208 0.081343829631805 209 0.080844670534134 210 0.080351069569588 211 0.079862862825394 212 0.079380020499229 213 0.078902415931225 214 0.078429996967316 215 0.077962718904018 216 0.077500462532043 217 0.077043168246746 218 0.076590731739998 219 0.076143115758896 220 0.075700238347054 221 0.075262024998665 222 0.074828423559666 223 0.074399366974831 224 0.073974758386612 225 0.073554553091526 226 0.073138684034348 227 0.072727106511593 228 0.072319746017456 229 0.071916528046131 230 0.071517422795296 231 0.071122340857983 232 0.070731230080128 233 0.070344045758247 234 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0.00095179217169061 29993 0.00095178582705557 29994 0.00095177965704352 29995 0.00095177354523912 29996 0.00095176772447303 29997 0.00095176172908396 29998 0.0009517555590719 29999 0.0009517494472675 30000 0.00095174321904778 0,0 0.00096295791347527 0,1 0.99906093247472 1,0 0.99906275144406 1,1 0.00096586381043744 b1 -3.8529949188232 -3.9333512783051 w1 -6.9309539794922 6.918788433075 7.0428323745728 -7.0194535255432 b2 -7.5515928268433 w2 15.197933197021 15.170973777771 april-ann-0.4.1/TEST/xor/xor-with-sparse-input.lua000066400000000000000000000061051263004425400217020ustar00rootroot00000000000000learning_rate = 0.4 momentum = 0.1 weight_decay = 1e-05 semilla = 1234 aleat = random(semilla) num_weights = 9 bunch_size = tonumber(arg[1]) or 64 m = matrix.fromString[[ 9 ascii -0.5 -1.2 1.0 -2.0 4.0 -4.0 -1.0 2.0 2.0 ]] function show_weights(trainer, filter) if not filter then filter = function(x) return x end end print() for i = 1,ds_input:numPatterns() do local out = trainer:calculate(ds_input:getPattern(i)):toTable() value = filter(out[1]) --printf("%s\t %s\n", --table.concat(ds_input:getPattern(i),","), --value) print(value) end print() for _,wname in ipairs({ "b1", "w1", "b2", "w2" }) do local w = trainer.weights_table[wname]:copy_to():toTable() print(wname, table.concat(w, " ")) end end function load_initial_weights(weights_table) weights_table["b1"]:load{ w=m, first_pos=0, column_size=3 } weights_table["w1"]:load{ w=m, first_pos=1, column_size=3 } weights_table["b2"]:load{ w=m, first_pos=6, column_size=3 } weights_table["w2"]:load{ w=m, first_pos=7, column_size=3 } end ----------------------------------------------------------- net_component=ann.mlp.all_all.generate("2 inputs 2 logistic 1 logistic") trainer=trainable.supervised_trainer(net_component) trainer:set_option("learning_rate", learning_rate) trainer:set_option("momentum", momentum) trainer:set_option("weight_decay", weight_decay) trainer:build() trainer:set_loss_function(ann.loss.mse(net_component:get_output_size())) load_initial_weights(trainer.weights_table) m_xor = matrix.fromString[[ 4 3 ascii 0 0 0 0 1 1 1 0 1 1 1 0 ]] ds_input = dataset.token.vector(2) ds_output = dataset.token.vector(1) t = tokens.vector.sparse() ds_input:push_back(t) t = tokens.vector.sparse() t:push_back(0, 1.0) ds_input:push_back(t) t = tokens.vector.sparse() t:push_back(1, 1.0) ds_input:push_back(t) t = tokens.vector.sparse() t:push_back(0, 1.0) t:push_back(1, 1.0) ds_input:push_back(t) ------------------------------ t = tokens.matrix( matrix.col_major(1,1,{0.0}) ) ds_output:push_back(t) t = tokens.matrix( matrix.col_major(1,1,{1.0}) ) ds_output:push_back(t) t = tokens.matrix( matrix.col_major(1,1,{1.0}) ) ds_output:push_back(t) t = tokens.matrix( matrix.col_major(1,1,{0.0}) ) ds_output:push_back(t) ----------------------- -- Valores iniciales -- ----------------------- load_initial_weights(trainer.weights_table) data={ input_dataset = ds_input, output_dataset = ds_output, shuffle = aleat, bunch_size = bunch_size } print ("\nAfter one epoch") trainer:train_dataset(data) show_weights(trainer) print ("\nAfter two epochs") trainer:train_dataset(data) show_weights(trainer) net_component:pop() net_component:push( ann.components.actf.log_logistic() ) trainer=trainable.supervised_trainer(net_component) trainer:build() trainer:set_loss_function(ann.loss.cross_entropy(net_component:get_output_size())) load_initial_weights(trainer.weights_table) print ("\nAfter 30000 epochs") for i=3,30000 do print(i, trainer:train_dataset(data)) end show_weights(trainer, math.exp) april-ann-0.4.1/TEST/xor/xor.lua000066400000000000000000000101541263004425400163000ustar00rootroot00000000000000learning_rate = 0.4 momentum = 0.1 weight_decay = 1e-05 semilla = 1234 aleat = random(semilla) num_weights = 9 bunch_size = tonumber(arg[1]) or 64 m = matrix.fromString[[ 9 ascii -0.5 -1.2 1.0 -2.0 4.0 -4.0 -1.0 2.0 2.0 ]] function show_weights(trainer, filter) if not filter then filter = function(x) return x end end print() for i = 1,ds_input:numPatterns() do value = filter(trainer:calculate(ds_input:getPattern(i)):toTable()[1]) printf("%s\t %s\n", table.concat(ds_input:getPattern(i),","), value) end print() for _,wname in ipairs({ "b1", "w1", "b2", "w2" }) do local w = trainer.weights_table[wname]:toTable() print(wname, table.concat(w, " ")) end end function load_initial_weights(weights_table) ann.connections.load(weights_table["b1"], { w=m, first_pos=0, column_size=3 }) ann.connections.load(weights_table["w1"], { w=m, first_pos=1, column_size=3 }) ann.connections.load(weights_table["b2"], { w=m, first_pos=6, column_size=3 }) ann.connections.load(weights_table["w2"], { w=m, first_pos=7, column_size=3 }) end ----------------------------------------------------------- net_component=ann.mlp.all_all.generate("2 inputs 2 logistic 1 logistic") trainer=trainable.supervised_trainer(net_component) trainer:build() trainer:set_option("learning_rate", learning_rate) trainer:set_option("momentum", momentum) trainer:set_option("weight_decay", weight_decay) trainer:set_layerwise_option("b.*", "weight_decay", 0.0) trainer:set_loss_function(ann.loss.mse(net_component:get_output_size())) load_initial_weights(trainer.weights_table) m_xor = matrix.fromString[[ 4 3 ascii 0 0 0 0 1 1 1 0 1 1 1 0 ]] ds_input = dataset.matrix(m_xor,{patternSize={1,2}}) ds_output = dataset.matrix(m_xor,{offset={0,2},patternSize={1,1}}) ds_input1 = dataset.matrix(m_xor,{ patternSize={1,2}, numSteps={1,1}}) ds_output1 = dataset.matrix(m_xor,{ offset={0,2}, patternSize={1,1}, numSteps={1,1}}) ds_input2 = dataset.matrix(m_xor,{ offset={1,0}, patternSize={1,2}, numSteps={1,1}}) ds_output2 = dataset.matrix(m_xor,{ offset={1,2}, patternSize={1,1}, numSteps={1,1}}) if not trainer:grad_check_dataset{ input_dataset = ds_input, output_dataset = ds_output, bunch_size = 4 } then error("Incorrect gradients!!!") end ----------------------- -- Valores iniciales -- ----------------------- print ("----------------------------------------------") print ("----------------------------------------------") print ("Initial values") show_weights(trainer) print ("----------------------------------------------") print ("--------------------------------------------") print ("After forward of (0,0)") data={ input_dataset = ds_input1, output_dataset = ds_output1, shuffle = aleat, bunch_size = bunch_size } trainer:train_dataset(data) show_weights(trainer) print ("\nAfter forward of (0,1)") data={ input_dataset = ds_input2, output_dataset = ds_output2, shuffle = aleat, bunch_size = bunch_size } trainer:train_dataset(data) show_weights(trainer) load_initial_weights(trainer.weights_table) data={ input_dataset = ds_input, output_dataset = ds_output, shuffle = aleat, bunch_size = bunch_size } print ("\nAfter one epoch") trainer:train_dataset(data) show_weights(trainer) print ("\nAfter two epochs") trainer:train_dataset(data) show_weights(trainer) net_component:pop() net_component:push( ann.components.actf.log_logistic() ) trainer=trainable.supervised_trainer(net_component) trainer:build() trainer:set_option("learning_rate", learning_rate) trainer:set_option("momentum", momentum) trainer:set_option("weight_decay", weight_decay) trainer:set_layerwise_option("b.*", "weight_decay", 0.0) trainer:set_loss_function(ann.loss.cross_entropy(net_component:get_output_size())) load_initial_weights(trainer.weights_table) print ("\nAfter 30000 epochs") for i=3,30000 do print(i, trainer:train_dataset(data)) end show_weights(trainer, math.exp) april-ann-0.4.1/clean.sh000077500000000000000000000000311263004425400150100ustar00rootroot00000000000000#!/bin/sh rm -Rf build_* april-ann-0.4.1/configure.sh000077500000000000000000000014451263004425400157210ustar00rootroot00000000000000folder=`ls luapkg` if [ -z "$folder" ]; then echo "Cloning submodules" git submodule init git submodule update fi git submodule foreach git pull origin master if [ -z $APRILANN_CONFIGURED ]; then export APRILANN_CONFIGURED=1 #export LANG="" export PATH="`pwd`"/lua/bin:`pwd`/bin:$PATH #export LUA_PATH="`pwd`""/luapkg/?.lua;?" fi if [ -z $LUA_HISTSIZE ]; then export LUA_HISTSIZE=500 fi if [ -z $LUA_HISTORY ]; then export LUA_HISTORY=~/.lua_history fi export LUA_DIR="`pwd`"/lua/lua-5.2.2 (make -C $LUA_DIR && make -C $LUA_DIR install && make -C "`pwd`"/lua/lstrip) || (echo "Error building Lua!!!" && exit -1) if [ -z $APRIL_EXEC ]; then export APRIL_EXEC=`pwd`/bin/april-ann fi if [ -z $APRIL_TOOLS_DIR ]; then export APRIL_TOOLS_DIR=`pwd`/tools/ fi april-ann-0.4.1/lua/000077500000000000000000000000001263004425400141565ustar00rootroot00000000000000april-ann-0.4.1/lua/.gitignore000066400000000000000000000000241263004425400161420ustar00rootroot00000000000000*.o *.a bin include april-ann-0.4.1/lua/README.txt000066400000000000000000000276431263004425400156700ustar00rootroot000000000000002013/10/13: COPYRIGHT, AUTHORS, and VERSION stuff is out of Lua source tree, it is managed by formiga. 2013/09/17: Modified lua.h to incorporate the commit number diff --git a/lua/lua-5.2.2/src/lua.h b/lua/lua-5.2.2/src/lua.h index c675516..027bc17 100644 --- a/lua/lua-5.2.2/src/lua.h +++ b/lua/lua-5.2.2/src/lua.h @@ -26,10 +26,15 @@ #define LUA_COPYRIGHT LUA_RELEASE " Copyright (C) 1994-2013 Lua.org, PUC-Rio" #define LUA_AUTHORS "R. Ierusalimschy, L. H. de Figueiredo, W. Celes" +#ifndef APRILANN_COMMIT +#define APRILANN_COMMIT UNKNOWN +#endif +#define STRINGFY(X) #X +#define TOSTRING(X) STRINGFY(X) #define APRILANN_VERSION_MAJOR "0" #define APRILANN_VERSION_MINOR "2" #define APRILANN_VERSION_RELEASE "1" -#define APRILANN_RELEASE "April-ANN v" APRILANN_VERSION_MAJOR "." APRILANN_VERSION_MINOR "." APRILANN_VERSION_RELEASE "-beta" +#define APRILANN_RELEASE "April-ANN v" APRILANN_VERSION_MAJOR "." APRILANN_VERSION_MINOR "." APRILANN_VERSION_RELEASE "-beta COMMIT " TOSTRING(APRILANN_COMMIT) #define APRILANN_COPYRIGHT "Copyright (C) 2012-2013 DSIC-UPV, CEU-UCH" #define APRILANN_AUTHORS "F. Zamora-Martinez, S. España-Boquera, J. Gorbe-Moya, J. Pastor & A. Palacios" ------------------------------------------------------------------------------ 2013/09/04: Finally, here is the luaconf.h section for LUA_PATH and LUA_CPATH: #define LUA_CDIR_32 LUA_ROOT "lib/i386-linux-gnu/lua/" LUA_VDIR #define LUA_CDIR_64 LUA_ROOT "lib/x86_64-linux-gnu/lua/" LUA_VDIR #define LUA_PATH_DEFAULT \ LUA_LDIR"?.lua;" LUA_LDIR"?/init.lua;" \ LUA_CDIR"?.lua;" LUA_CDIR"?/init.lua;" "./?.lua" #define LUA_CPATH_DEFAULT \ LUA_CDIR"?.so;" LUA_CDIR"loadall.so;" \ LUA_CDIR_32"?.so;" LUA_CDIR_32"loadall.so;" \ LUA_CDIR_64"?.so;" LUA_CDIR_64"loadall.so;" \ "./?.so;" #endif /* } */ ---------------------------------------------------------------------------- 2013/09/03: Modified luaconf.h: - #define LUA_ROOT "/usr/local/" + #define LUA_ROOT "/usr/" ---------------------------------------------------------------------------- 2013/08/28: Modified Lua makefile, added this: UNAME = `uname` PLAT= DetectOs DetectOs: -@make $(UNAME) Linux: linux Darwin: macosx ---------------------------------------------------------------------------- 2013/06/08: Lua 5.2.2 update - Changes of Lua 5.2.2 diff --git a/lua/lua-5.2.2/src/liolib.c b/lua/lua-5.2.2/src/liolib.c index 3f80db1..d49d1db 100644 --- a/lua/lua-5.2.2/src/liolib.c +++ b/lua/lua-5.2.2/src/liolib.c @@ -46,40 +46,6 @@ /* ** {====================================================== -** lua_popen spawns a new process connected to the current -** one through the file streams. -** ======================================================= -*/ - -#if !defined(lua_popen) /* { */ - -#if defined(LUA_USE_POPEN) /* { */ - -#define lua_popen(L,c,m) ((void)L, fflush(NULL), popen(c,m)) -#define lua_pclose(L,file) ((void)L, pclose(file)) - -#elif defined(LUA_WIN) /* }{ */ - -#define lua_popen(L,c,m) ((void)L, _popen(c,m)) -#define lua_pclose(L,file) ((void)L, _pclose(file)) - - -#else /* }{ */ - -#define lua_popen(L,c,m) ((void)((void)c, m), \ - luaL_error(L, LUA_QL("popen") " not supported"), (FILE*)0) -#define lua_pclose(L,file) ((void)((void)L, file), -1) - - -#endif /* } */ - -#endif /* } */ - -/* }====================================================== */ - - -/* -** {====================================================== ** lua_fseek/lua_ftell: configuration for longer offsets ** ======================================================= */ diff --git a/lua/lua-5.2.2/src/llex.c b/lua/lua-5.2.2/src/llex.c index 1a32e34..877dc34 100644 --- a/lua/lua-5.2.2/src/llex.c +++ b/lua/lua-5.2.2/src/llex.c @@ -33,7 +33,7 @@ /* ORDER RESERVED */ -static const char *const luaX_tokens [] = { +const char *const luaX_tokens [] = { "and", "break", "do", "else", "elseif", "end", "false", "for", "function", "goto", "if", "in", "local", "nil", "not", "or", "repeat", diff --git a/lua/lua-5.2.2/src/lua.h b/lua/lua-5.2.2/src/lua.h index f6fe0d4..c675516 100644 --- a/lua/lua-5.2.2/src/lua.h +++ b/lua/lua-5.2.2/src/lua.h @@ -28,7 +28,7 @@ #define APRILANN_VERSION_MAJOR "0" #define APRILANN_VERSION_MINOR "2" -#define APRILANN_VERSION_RELEASE "0" +#define APRILANN_VERSION_RELEASE "1" #define APRILANN_RELEASE "April-ANN v" APRILANN_VERSION_MAJOR "." APRILANN_VERSION_MINOR "." APRILANN_VERSION_RELEASE "-beta" #define APRILANN_COPYRIGHT "Copyright (C) 2012-2013 DSIC-UPV, CEU-UCH" #define APRILANN_AUTHORS "F. Zamora-Martinez, S. España-Boquera, J. Gorbe-Moya, J. Pastor & A. Palacios" diff --git a/lua/lua-5.2.2/src/lualib.h b/lua/lua-5.2.2/src/lualib.h index 9fd126b..f5977cb 100644 --- a/lua/lua-5.2.2/src/lualib.h +++ b/lua/lua-5.2.2/src/lualib.h @@ -10,6 +10,38 @@ #include "lua.h" +/* +** {====================================================== +** lua_popen spawns a new process connected to the current +** one through the file streams. +** ======================================================= +*/ + +#if !defined(lua_popen) /* { */ + +#if defined(LUA_USE_POPEN) /* { */ + +#define lua_popen(L,c,m) ((void)L, fflush(NULL), popen(c,m)) +#define lua_pclose(L,file) ((void)L, pclose(file)) + +#elif defined(LUA_WIN) /* }{ */ + +#define lua_popen(L,c,m) ((void)L, _popen(c,m)) +#define lua_pclose(L,file) ((void)L, _pclose(file)) + + +#else /* }{ */ + +#define lua_popen(L,c,m) ((void)((void)c, m), \ + luaL_error(L, LUA_QL("popen") " not supported"), (FILE*)0) +#define lua_pclose(L,file) ((void)((void)L, file), -1) + + +#endif /* } */ + +#endif /* } */ + +/* }====================================================== */ LUAMOD_API int (luaopen_base) (lua_State *L); - Changes for compilation of lstrip/lstrip.c with Lua 5.2.2 diff --git a/lua/lstrip/lstrip.c b/lua/lstrip/lstrip.c index 715f3b6..b99fa2b 100644 --- a/lua/lstrip/lstrip.c +++ b/lua/lstrip/lstrip.c @@ -12,6 +12,8 @@ #include #include +#define lua_open() luaL_newstate() + #define LUA_CORE #include "lua.h" @@ -31,6 +33,8 @@ static const char* progname=PROGNAME; /* actual program name */ static int preserve=0; /* preserve line breaks? */ static int dump=0; /* dump instead of stripping? */ +extern const char *const luaX_tokens []; + static void fatal(const char* message) { fprintf(stderr,"%s: %s\n",progname,message); @@ -184,14 +188,24 @@ static void dostrip(LexState *X) } } -Proto *luaY_parser(lua_State *L, ZIO *z, Mbuffer *buff, const char *name) +Closure *luaY_parser(lua_State *L, ZIO *z, Mbuffer *buff, + Dyndata *dyd, const char *name, int firstchar) { LexState X; FuncState F; + Closure *cl = luaF_newLclosure(L, 1); /* create main closure */ + /* anchor closure (to avoid being collected) */ + setclLvalue(L, L->top, cl); + incr_top(L); X.buff=buff; - luaX_setinput(L,&X,z,luaS_new(L,name)); + F.f = cl->l.p = luaF_newproto(L); + F.f->source = luaS_new(L, name); /* create and anchor TString */ + X.buff = buff; + X.dyd = dyd; + dyd->actvar.n = dyd->gt.n = dyd->label.n = 0; + luaX_setinput(L, &X, z, F.f->source, firstchar); X.fs=&F; - X.fs->h=luaH_new(L,0,0); + X.fs->h=luaH_new(L); sethvalue2s(L,L->top,X.fs->h); incr_top(L); if (dump) @@ -200,7 +214,7 @@ Proto *luaY_parser(lua_State *L, ZIO *z, Mbuffer *buff, const char *name) dodump(&X); } else dostrip(&X); - return luaF_newproto(L); + return cl; /* it's on the stack too */ } static void strip(lua_State *L, const char *file) ------------------------------------- -- CHANGES BEFORE LUA 5.2.2 UPDATE -- ------------------------------------- 07/06/2013 diff --git a/lua/lua-5.1.4/src/lua.c b/lua/lua-5.1.4/src/lua.c index a650dbd..164dc12 100644 --- a/lua/lua-5.1.4/src/lua.c +++ b/lua/lua-5.1.4/src/lua.c @@ -110,6 +110,7 @@ static int docall (lua_State *L, int narg, int clear) { static void print_version (void) { l_message(NULL, LUA_RELEASE " " LUA_COPYRIGHT); + l_message(NULL, APRILANN_RELEASE " " APRILANN_COPYRIGHT); } diff --git a/lua/lua-5.1.4/src/lua.h b/lua/lua-5.1.4/src/lua.h index e4bdfd3..8956ab3 100644 --- a/lua/lua-5.1.4/src/lua.h +++ b/lua/lua-5.1.4/src/lua.h @@ -22,6 +22,9 @@ #define LUA_COPYRIGHT "Copyright (C) 1994-2008 Lua.org, PUC-Rio" #define LUA_AUTHORS "R. Ierusalimschy, L. H. de Figueiredo & W. Celes" +#define APRILANN_RELEASE "April-ANN 0.1.1 beta" +#define APRILANN_COPYRIGHT "Copyright (C) 2012-2013 April-ANN" +#define APRILANN_AUTHORS "F. Zamora-Martinez, S. España-Boquera, J. Gorbe-Moya, J. Pastor & A. Palacios" /* mark for precompiled code (`Lua') */ #define LUA_SIGNATURE "\033Lua" ---------------------------------------------------------------------------- 02/06/2013 - lua.c:22 static lua_State *globalL = NULL; + lua.c:22 lua_State *globalL = NULL; 23/04/2007 Aplicar los cambios del parche lua_dist2april.patch --------------------------------------------------- cd lua-.... patch -p1 < ../lua_dist2april.patch El p1 se salta el primer directorio de la ruta en la que se encuentran los ficheros a parchear. Cambios realizados a lua-5.1.2 ------------------------------ Los mismos que a 5.1.1. He creado un parche con ambos cambios para poder aplicarlos comodamente a futuras versiones (al menos de la serie 5.1, supongo). No obstante, sigue siendo necesario especificar las variables PLAT e INSTALL_TOP en el Makefile. Cambios realizados a la version estándar de lua-5.1.1 ----------------------------------------------------- En src/lib/liolib.c, funcion read_chars, cambio para evitar que un read termine interrumpido por seal y se entienda como un EOF - } while (n > 0 && nr == rlen); /* until end of count or eof */ + } while ((n > 0 && nr == rlen) || (ferror(f) && !feof(f) && errno==EINTR)); /* until end of count or eof */ -- En el Makefile poner: PLAT= posix INSTALL_TOP= ../.. de esta manera instala lua en el directorio superior, quedando: luapkg | |- lua | | | |- lua-5.1.1 <- hacer make y make install en este punto | |- lib | |- bin | |- include | \- man | . . . -- Inicializacion de los paquetes en pmain en lua.c. Ya no existe llamada a lua_userinit como la habia en la version anterior. PATCH: --- /home/jgorbe/temp/lua-5.1.1/src/lua.c 2006-06-02 17:34:00.000000000 +0200 +++ lua/lua-5.1.1/src/lua.c 2007-03-15 18:44:51.000000000 +0100 @@ -344,6 +344,9 @@ if (argv[0] && argv[0][0]) progname = argv[0]; lua_gc(L, LUA_GCSTOP, 0); /* stop collector during initialization */ luaL_openlibs(L); /* open libraries */ +#ifdef lua_userinit + lua_userinit(L); /* APRIL: init packages */ +#endif lua_gc(L, LUA_GCRESTART, 0); s->status = handle_luainit(L); if (s->status != 0) return 0; -------------------------------------------------------------------------------- ------------ CAMBIOS DE LA 5.0.3 QUE NO SE HICIERON AL PASAR A 5.1 ------------- -------------------------------------------------------------------------------- En el fichero src/lib/liolib.c: Aadida la funcin 'pclose' para usar con el interprete de Lua. Las lneas aadidas estn mrcadas con comentarios. Buscar 'Formiga' en el comentario. En el fichero luac.c situado en src/luac hemos añadido en la línea 93: antes: else if (IS("-o")) /* output file */ { output=argv[++i]; if (output==NULL || *output==0) usage("`-o' needs argument"); } ahora: else if (IS("-o")) /* output file */ { output=argv[++i]; if (output==NULL || *output==0) usage("`-o' needs argument"); if (IS("-")) output=NULL; } y hemos cambiado la línea 182: antes: FILE* D=fopen(output,"wb"); ahora: FILE* D= (output==NULL) ? stdout : fopen(output,"wb"); de esta manera se permite poner -o - para que saque el bytecode por salida estándar. Hemos cambiado tres líneas en el fichero config: descomentar para que funcione en el MacOS X: POPEN= -DUSE_POPEN=1 descomentar: MYCFLAGS= -O3 -fomit-frame-pointer # -fPIC poner: INSTALL_ROOT= .. de esta manera instala lua en el directorio superior, quedando: luapkg | |- lua | | | |- lua-5.0.2 <- hacer make y make install en este punto | |- lib | |- bin | |- include | \- man | . . . april-ann-0.4.1/lua/include/000077500000000000000000000000001263004425400156015ustar00rootroot00000000000000april-ann-0.4.1/lua/include/.gitignore000066400000000000000000000000001263004425400175570ustar00rootroot00000000000000april-ann-0.4.1/lua/lstrip/000077500000000000000000000000001263004425400154735ustar00rootroot00000000000000april-ann-0.4.1/lua/lstrip/.gitignore000066400000000000000000000000071263004425400174600ustar00rootroot00000000000000lstrip april-ann-0.4.1/lua/lstrip/Makefile000066400000000000000000000015371263004425400171410ustar00rootroot00000000000000# makefile for lstrip # change these to reflect your Lua installation (Lua 5.1!) LUA= $(LUA_DIR) LUAINC= $(LUA)/src LUALIB= $(LUA)/src LUASRC= $(LUA)/src # no need to change anything below here CFLAGS= $(INCS) $(WARN) -O2 $G WARN= -ansi -pedantic -Wall INCS= -I$(LUAINC) -I$(LUASRC) LIBS= -L$(LUALIB) -llua -lm MYNAME= lstrip MYLIB= $(MYNAME) T= $(MYNAME) OBJS= $(MYNAME).o TEST= test.lua LUAEXECDIR = $(LUA_DIR)/../bin all: $T test: $T -rm -f core core.* $T $(TEST) $T: $(OBJS) $(CC) -o $@ $(OBJS) $(LIBS) cp $(MYNAME) $(LUAEXECDIR) clean: -rm -f $(OBJS) core core.* a.out $(MYNAME) # distribution FTP= $(HOME)/public/ftp/lua/5.1 D= $(MYNAME) A= $(MYLIB).tar.gz TOTAR= Makefile,README,$(MYNAME).c,test.lua tar: clean tar zcvf $A -C .. $D/{$(TOTAR)} distr: tar touch -r $A .stamp mv $A $(FTP) diff: clean tar zxf $(FTP)/$A diff $D . # eof april-ann-0.4.1/lua/lstrip/README000066400000000000000000000015011263004425400163500ustar00rootroot00000000000000lstrip compresses Lua programs by removing comments and whitespace, including line breaks. By default, lstrip removes all line breaks. Use "lstrip -p" to preserve some line breaks. Use "lstrip -p -p" to preserve all line breaks. lstrip can also dump the token stream with -d. In this mode, for each token lstrip outputs a line with the line number, the token, and its value, separated by tabs. To try lstrip, just edit Makefile to reflect your installation of Lua and then run make. This will build lstrip and run a simple test. Note that lstrip needs inside information from the Lua private headers and so it needs to be built using a Lua build directory, not just the usual installation directories. This code is hereby placed in the public domain. Please send comments, suggestions, and bug reports to lhf@tecgraf.puc-rio.br . april-ann-0.4.1/lua/lstrip/lstrip.c000066400000000000000000000116061263004425400171600ustar00rootroot00000000000000/* * lstrip.c * compress Lua programs by removing comments and whitespaces, * optionally preserving line breaks (for error messages). * 20 Oct 2006 09:25:34 * Luiz Henrique de Figueiredo * This code is hereby placed in the public domain. */ #include #include #include #include #define lua_open() luaL_newstate() #define LUA_CORE #include "lua.h" #include "lauxlib.h" #include "ldo.h" #include "lfunc.h" #include "llex.h" #include "lobject.h" #include "lparser.h" #include "lstring.h" #include "ltable.h" #include "lzio.h" #define PROGNAME "lstrip" /* default program name */ static const char* progname=PROGNAME; /* actual program name */ static int preserve=0; /* preserve line breaks? */ static int dump=0; /* dump instead of stripping? */ extern const char *const luaX_tokens []; static void fatal(const char* message) { fprintf(stderr,"%s: %s\n",progname,message); exit(EXIT_FAILURE); } static void quote(const TString *ts) { const char *s=getstr(ts); size_t n=ts->tsv.len; int i; printf("\""); for (i=0; i', '='), pair('[', '='), pair('[', '['), pair('~', '='), pair(TK_CONCAT, '.'), pair(TK_CONCAT, TK_CONCAT), pair(TK_CONCAT, TK_DOTS), pair(TK_CONCAT, TK_NUMBER), pair(TK_NAME, TK_NAME), pair(TK_NAME, TK_NUMBER), pair(TK_NUMBER, '.'), pair(TK_NUMBER, TK_CONCAT), pair(TK_NUMBER, TK_DOTS), pair(TK_NUMBER, TK_NAME), pair(TK_NUMBER, TK_NUMBER), 0 }; static int space(int a, int b) { int i,c; if (a>=FIRST_RESERVED && a<=TK_WHILE) a=TK_NAME; if (b>=FIRST_RESERVED && b<=TK_WHILE) b=TK_NAME; c=pair(a,b); for (i=0; clash[i]!=0; i++) if (c==clash[i]) return 1; return 0; } static void dodump(LexState *X) { for (;;) { int t; luaX_next(X); t=X->t.token; printf("%d\t",X->linenumber); if (tt.seminfo.ts); break; case TK_NAME: printf("%s",getstr(X->t.seminfo.ts)); break; case TK_NUMBER: printf("%s",X->buff->buffer); break; } printf("\n"); } } static void dostrip(LexState *X) { int ln=1; int lt=0; for (;;) { int t; luaX_next(X); t=X->t.token; if (preserve) { if (X->linenumber!=ln) { if (preserve>1) while (X->linenumber!=ln++) printf("\n"); else if (lt!=0) printf("\n"); ln=X->linenumber; lt=0; } } if (space(lt,t)) printf(" "); switch (t) { case TK_EOS: return; case TK_STRING: quote(X->t.seminfo.ts); break; case TK_NAME: printf("%s",getstr(X->t.seminfo.ts)); break; case TK_NUMBER: printf("%s",X->buff->buffer); break; default: if (t2) printf("\n"); } } Closure *luaY_parser(lua_State *L, ZIO *z, Mbuffer *buff, Dyndata *dyd, const char *name, int firstchar) { LexState X; FuncState F; Closure *cl = luaF_newLclosure(L, 1); /* create main closure */ /* anchor closure (to avoid being collected) */ setclLvalue(L, L->top, cl); incr_top(L); X.buff=buff; F.f = cl->l.p = luaF_newproto(L); F.f->source = luaS_new(L, name); /* create and anchor TString */ X.buff = buff; X.dyd = dyd; dyd->actvar.n = dyd->gt.n = dyd->label.n = 0; luaX_setinput(L, &X, z, F.f->source, firstchar); X.fs=&F; X.fs->h=luaH_new(L); sethvalue2s(L,L->top,X.fs->h); incr_top(L); if (dump) { printf("0\t\t%s\n",name); dodump(&X); } else dostrip(&X); return cl; /* it's on the stack too */ } static void strip(lua_State *L, const char *file) { if (file!=NULL && strcmp(file,"-")==0) file=NULL; if (luaL_loadfile(L,file)!=0) fatal(lua_tostring(L,-1)); lua_settop(L,0); } int main(int argc, char* argv[]) { lua_State *L=lua_open(); if (argv[0]!=NULL && *argv[0]!=0) progname=argv[0]; if (L==NULL) fatal("not enough memory for state"); while (*++argv!=NULL && strcmp(*argv,"-p")==0) preserve++; --argv; while (*++argv!=NULL && strcmp(*argv,"-d")==0) dump++; if (*argv==NULL) strip(L,NULL); else while (*argv) strip(L,*argv++); lua_close(L); return EXIT_SUCCESS; } april-ann-0.4.1/lua/lstrip/test.lua000066400000000000000000000004621263004425400171570ustar00rootroot00000000000000-- testing lstrip -- this function does nothing -- this is another comment function f(n,...) local s=[[ --header... bye ]] for i=1,n do s = s .. ' ' .. 12 .. " " .. ... end print(">>>", ... .. s, ...) end --[[ Now test it... Not that it means anything... ]] f(1 - -2, "alpha", "beta", "gamma") april-ann-0.4.1/lua/lua-5.2.0-advanced_readline.patch000066400000000000000000000215411263004425400220310ustar00rootroot00000000000000diff -ur lua-5.2.0/src/lua.c lua-5.2.0-patched/src/lua.c --- lua-5.2.0/src/lua.c 2011-12-12 08:34:03.000000000 -0800 +++ lua-5.2.0-patched/src/lua.c 2011-12-21 16:24:29.000000000 -0800 @@ -236,6 +236,261 @@ return report(L, status); } +/* ------------------------------------------------------------------------ */ + +#ifdef LUA_USE_READLINE +/* +** Lua 5.2.0 advanced readline support for the GNU readline and history +** libraries or compatible replacements. +** +** Author: Mike Pall. +** Maintainer: Sean Bolton (sean at smbolton dot com). +** +** Copyright (C) 2004-2006, 2011 Mike Pall. Same license as Lua. See lua.h. +** +** Advanced features: +** - Completion of keywords and global variable names. +** - Recursive and metatable-aware completion of variable names. +** - Context sensitive delimiter completion. +** - Save/restore of the history to/from a file (LUA_HISTORY env variable). +** - Setting a limit for the size of the history (LUA_HISTSIZE env variable). +** - Setting the app name to allow for $if lua ... $endif in ~/.inputrc. +** +** Start lua and try these (replace ~ with the TAB key): +** +** ~~ +** fu~foo() ret~fa~end +** io~~~s~~~o~~~w~"foo\n") +** +** The ~~ are just for demonstration purposes (io~s~o~w~ suffices, of course). +** +** If you are used to zsh/tcsh-style completion support, try adding +** 'TAB: menu-complete' and 'C-d: possible-completions' to your ~/.inputrc. +** +** The patch has been successfully tested with: +** +** GNU readline 2.2.1 (1998-07-17) +** GNU readline 4.0 (1999-02-18) [harmless compiler warning] +** GNU readline 4.3 (2002-07-16) +** GNU readline 5.0 (2004-07-27) +** GNU readline 5.1 (2005-12-07) +** GNU readline 5.2 (2006-10-11) +** GNU readline 6.0 (2009-02-20) +** GNU readline 6.2 (2011-02-13) +** MacOSX libedit 2.11 (2008-07-12) +** NETBSD libedit 2.6.5 (2002-03-25) +** NETBSD libedit 2.6.9 (2004-05-01) +** +** Change Log: +** 2004-2006 Mike Pall - original patch +** 2009/08/24 Sean Bolton - updated for GNU readline version 6 +** 2011/11/15 Sean Bolton - updated for Lua 5.2 +** 2011/12/14 Sean Bolton - fixed segfault when using Mac OS X libedit 2.11 +*/ + +#include + +static char *lua_rl_hist; +static int lua_rl_histsize; + +static lua_State *lua_rl_L; /* User data is not passed to rl callbacks. */ + +/* Reserved keywords. */ +static const char *const lua_rl_keywords[] = { + "and", "break", "do", "else", "elseif", "end", "false", + "for", "function", "goto", "if", "in", "local", "nil", "not", "or", + "repeat", "return", "then", "true", "until", "while", NULL +}; + +static int valididentifier(const char *s) +{ + if (!(isalpha(*s) || *s == '_')) return 0; + for (s++; *s; s++) if (!(isalpha(*s) || isdigit(*s) || *s == '_')) return 0; + return 1; +} + +/* Dynamically resizable match list. */ +typedef struct { + char **list; + size_t idx, allocated, matchlen; +} dmlist; + +/* Add prefix + string + suffix to list and compute common prefix. */ +static int lua_rl_dmadd(dmlist *ml, const char *p, size_t pn, const char *s, + int suf) +{ + char *t = NULL; + + if (ml->idx+1 >= ml->allocated && + !(ml->list = (char**)realloc(ml->list, sizeof(char *)*(ml->allocated += 32)))) + return -1; + + if (s) { + size_t n = strlen(s); + if (!(t = (char *)malloc(sizeof(char)*(pn+n+(suf?2:1))))) return 1; + memcpy(t, p, pn); + memcpy(t+pn, s, n); + n += pn; + t[n] = suf; + if (suf) t[++n] = '\0'; + + if (ml->idx == 0) { + ml->matchlen = n; + } else { + size_t i; + for (i = 0; i < ml->matchlen && i < n && ml->list[1][i] == t[i]; i++) ; + ml->matchlen = i; /* Set matchlen to common prefix. */ + } + } + + ml->list[++ml->idx] = t; + return 0; +} + +/* Get __index field of metatable of object on top of stack. */ +static int lua_rl_getmetaindex(lua_State *L) +{ + if (!lua_getmetatable(L, -1)) { lua_pop(L, 1); return 0; } + lua_pushstring(L, "__index"); + lua_rawget(L, -2); if (lua_isfunction(L, -1)) { lua_pop(L, 1); lua_pushstring(L, "index_table"); lua_rawget(L, -2); } + lua_replace(L, -2); + if (lua_isnil(L, -1) || lua_rawequal(L, -1, -2)) { lua_pop(L, 2); return 0; } + lua_replace(L, -2); + return 1; +} /* 1: obj -- val, 0: obj -- */ + +/* Get field from object on top of stack. Avoid calling metamethods. */ +static int lua_rl_getfield(lua_State *L, const char *s, size_t n) +{ + int i = 20; /* Avoid infinite metatable loops. */ + do { + if (lua_istable(L, -1)) { + lua_pushlstring(L, s, n); + lua_rawget(L, -2); + if (!lua_isnil(L, -1)) { lua_replace(L, -2); return 1; } + lua_pop(L, 1); + } + } while (--i > 0 && lua_rl_getmetaindex(L)); + lua_pop(L, 1); + return 0; +} /* 1: obj -- val, 0: obj -- */ + +/* Completion callback. */ +static char **lua_rl_complete(const char *text, int start, int end) +{ + lua_State *L = lua_rl_L; + dmlist ml; + const char *s; + size_t i, n, dot, loop; + int savetop; + + if (!(text[0] == '\0' || isalpha(text[0]) || text[0] == '_')) return NULL; + + ml.list = NULL; + ml.idx = ml.allocated = ml.matchlen = 0; + + savetop = lua_gettop(L); + lua_pushglobaltable(L); + for (n = (size_t)(end-start), i = dot = 0; i < n; i++) + if (text[i] == '.' || text[i] == ':') { + if (!lua_rl_getfield(L, text+dot, i-dot)) + goto error; /* Invalid prefix. */ + dot = i+1; /* Points to first char after dot/colon. */ + } + + /* Add all matches against keywords if there is no dot/colon. */ + if (dot == 0) + for (i = 0; (s = lua_rl_keywords[i]) != NULL; i++) + if (!strncmp(s, text, n) && lua_rl_dmadd(&ml, NULL, 0, s, ' ')) + goto error; + + /* Add all valid matches from all tables/metatables. */ + loop = 0; /* Avoid infinite metatable loops. */ + lua_pushglobaltable(L); + lua_insert(L, -2); + do { + if (lua_istable(L, -1) && + (loop == 0 || !lua_rawequal(L, -1, -2))) + for (lua_pushnil(L); lua_next(L, -2); lua_pop(L, 1)) + if (lua_type(L, -2) == LUA_TSTRING) { + s = lua_tostring(L, -2); + /* Only match names starting with '_' if explicitly requested. */ + if (!strncmp(s, text+dot, n-dot) && valididentifier(s) && + (*s != '_' || text[dot] == '_')) { + int suf = ' '; /* Default suffix is a space. */ + switch (lua_type(L, -1)) { + case LUA_TTABLE: suf = '\0'; break; /* No way to guess ':', '.' or __call metamethod. */ + case LUA_TFUNCTION: suf = '('; break; + case LUA_TUSERDATA: + if (lua_getmetatable(L, -1)) { lua_pop(L, 1); suf = ':'; } + break; + } + if (lua_rl_dmadd(&ml, text, dot, s, suf)) goto error; + } + } + } while (++loop < 20 && lua_rl_getmetaindex(L)); + lua_pop(L, 1); + + if (ml.idx == 0) { +error: + lua_settop(L, savetop); + return NULL; + } else { + /* list[0] holds the common prefix of all matches (may be ""). */ + /* If there is only one match, list[0] and list[1] will be the same. */ + if (!(ml.list[0] = (char *)malloc(sizeof(char)*(ml.matchlen+1)))) + goto error; + memcpy(ml.list[0], ml.list[1], ml.matchlen); + ml.list[0][ml.matchlen] = '\0'; + /* Add the NULL list terminator. */ + if (lua_rl_dmadd(&ml, NULL, 0, NULL, 0)) goto error; + } + + lua_settop(L, savetop); +#if RL_READLINE_VERSION >= 0x0600 + rl_completion_suppress_append = 1; +#endif + return ml.list; +} + +/* Initialize readline library. */ +static void lua_rl_init(lua_State *L) +{ + char *s; + + lua_rl_L = L; + + /* This allows for $if lua ... $endif in ~/.inputrc. */ + rl_readline_name = (char*)"lua"; + /* Break words at every non-identifier character except '.' and ':'. */ + rl_completer_word_break_characters = + (char*)"\t\r\n !\"#$%&'()*+,-/;<=>?@[\\]^`{|}~"; + rl_completer_quote_characters = (char*)"\"'"; +#if RL_READLINE_VERSION < 0x0600 + rl_completion_append_character = '\0'; +#endif + rl_attempted_completion_function = lua_rl_complete; + rl_initialize(); + + /* Start using history, optionally set history size and load history file. */ + using_history(); + if ((s = getenv("LUA_HISTSIZE")) && + (lua_rl_histsize = atoi(s))) stifle_history(lua_rl_histsize); + if ((lua_rl_hist = getenv("LUA_HISTORY"))) read_history(lua_rl_hist); +} + +/* Finalize readline library. */ +static void lua_rl_exit(lua_State *L) +{ + (void)(L); /* Optionally save history file. */ + if (lua_rl_hist) write_history(lua_rl_hist); +} +#else +#define lua_rl_init(L) ((void)L) +#define lua_rl_exit(L) ((void)L) +#endif + +/* ------------------------------------------------------------------------ */ static const char *get_prompt (lua_State *L, int firstline) { const char *p; @@ -308,6 +563,7 @@ int status; const char *oldprogname = progname; progname = NULL; + lua_rl_init(L); while ((status = loadline(L)) != -1) { if (status == LUA_OK) status = docall(L, 0, LUA_MULTRET); report(L, status); @@ -323,6 +579,7 @@ } lua_settop(L, 0); /* clear stack */ luai_writeline(); + lua_rl_exit(L); progname = oldprogname; } april-ann-0.4.1/lua/lua-5.2.2/000077500000000000000000000000001263004425400154015ustar00rootroot00000000000000april-ann-0.4.1/lua/lua-5.2.2/.gitignore000066400000000000000000000000311263004425400173630ustar00rootroot00000000000000src/*.o src/lua src/luac april-ann-0.4.1/lua/lua-5.2.2/Makefile000066400000000000000000000063571263004425400170540ustar00rootroot00000000000000# Makefile for installing Lua # See doc/readme.html for installation and customization instructions. # == CHANGE THE SETTINGS BELOW TO SUIT YOUR ENVIRONMENT ======================= # Your platform. See PLATS for possible values. UNAME = `uname` PLAT= DetectOS # Where to install. The installation starts in the src and doc directories, # so take care if INSTALL_TOP is not an absolute path. See the local target. # You may want to make INSTALL_LMOD and INSTALL_CMOD consistent with # LUA_ROOT, LUA_LDIR, and LUA_CDIR in luaconf.h. INSTALL_TOP= ../.. INSTALL_BIN= $(INSTALL_TOP)/bin INSTALL_INC= $(INSTALL_TOP)/include INSTALL_LIB= $(INSTALL_TOP)/lib INSTALL_MAN= $(INSTALL_TOP)/man/man1 INSTALL_LMOD= $(INSTALL_TOP)/share/lua/$V INSTALL_CMOD= $(INSTALL_TOP)/lib/lua/$V # How to install. If your install program does not support "-p", then # you may have to run ranlib on the installed liblua.a. INSTALL= install -p INSTALL_EXEC= $(INSTALL) -m 0755 INSTALL_DATA= $(INSTALL) -m 0644 # # If you don't have "install" you can use "cp" instead. # INSTALL= cp -p # INSTALL_EXEC= $(INSTALL) # INSTALL_DATA= $(INSTALL) # Other utilities. MKDIR= mkdir -p RM= rm -f # == END OF USER SETTINGS -- NO NEED TO CHANGE ANYTHING BELOW THIS LINE ======= # Convenience platforms targets. PLATS= DetectOS Darwin Linux aix ansi bsd freebsd generic linux macosx mingw posix solaris # What to install. TO_BIN= lua luac TO_INC= lua.h luaconf.h lualib.h lauxlib.h lua.hpp TO_LIB= liblua.a TO_MAN= lua.1 luac.1 # Lua version and release. V= 5.2 R= $V.1 # Targets start here. all: $(PLAT) $(PLATS) clean: cd src && $(MAKE) $@ test: dummy src/lua -v install: dummy cd src && $(MKDIR) $(INSTALL_BIN) $(INSTALL_INC) $(INSTALL_LIB) $(INSTALL_MAN) $(INSTALL_LMOD) $(INSTALL_CMOD) cd src && $(INSTALL_EXEC) $(TO_BIN) $(INSTALL_BIN) cd src && $(INSTALL_DATA) $(TO_INC) $(INSTALL_INC) cd src && $(INSTALL_DATA) $(TO_LIB) $(INSTALL_LIB) cd doc && $(INSTALL_DATA) $(TO_MAN) $(INSTALL_MAN) uninstall: cd src && cd $(INSTALL_BIN) && $(RM) $(TO_BIN) cd src && cd $(INSTALL_INC) && $(RM) $(TO_INC) cd src && cd $(INSTALL_LIB) && $(RM) $(TO_LIB) cd doc && cd $(INSTALL_MAN) && $(RM) $(TO_MAN) local: $(MAKE) install INSTALL_TOP=../install none: @echo "Please do 'make PLATFORM' where PLATFORM is one of these:" @echo " $(PLATS)" @echo "See doc/readme.html for complete instructions." # make may get confused with test/ and install/ dummy: # echo config parameters echo: @cd src && $(MAKE) -s echo @echo "PLAT= $(PLAT)" @echo "V= $V" @echo "R= $R" @echo "TO_BIN= $(TO_BIN)" @echo "TO_INC= $(TO_INC)" @echo "TO_LIB= $(TO_LIB)" @echo "TO_MAN= $(TO_MAN)" @echo "INSTALL_TOP= $(INSTALL_TOP)" @echo "INSTALL_BIN= $(INSTALL_BIN)" @echo "INSTALL_INC= $(INSTALL_INC)" @echo "INSTALL_LIB= $(INSTALL_LIB)" @echo "INSTALL_MAN= $(INSTALL_MAN)" @echo "INSTALL_LMOD= $(INSTALL_LMOD)" @echo "INSTALL_CMOD= $(INSTALL_CMOD)" @echo "INSTALL_EXEC= $(INSTALL_EXEC)" @echo "INSTALL_DATA= $(INSTALL_DATA)" # echo pkg-config data pc: @echo "version=$R" @echo "prefix=$(INSTALL_TOP)" @echo "libdir=$(INSTALL_LIB)" @echo "includedir=$(INSTALL_INC)" # list targets that do not create files (but not all makes understand .PHONY) .PHONY: all $(PLATS) clean test install local none dummy echo pecho lecho # (end of Makefile) april-ann-0.4.1/lua/lua-5.2.2/README000066400000000000000000000002271263004425400162620ustar00rootroot00000000000000 This is Lua 5.2.2, released on 21 Mar 2013. For installation instructions, license details, and further information about Lua, see doc/readme.html. april-ann-0.4.1/lua/lua-5.2.2/doc/000077500000000000000000000000001263004425400161465ustar00rootroot00000000000000april-ann-0.4.1/lua/lua-5.2.2/doc/contents.html000066400000000000000000000606661263004425400207070ustar00rootroot00000000000000 Lua 5.2 Reference Manual - contents

Lua 5.2 Reference Manual

The reference manual is the official definition of the Lua language. For a complete introduction to Lua programming, see the book Programming in Lua.

start · contents · index

Copyright © 2011–2013 Lua.org, PUC-Rio. Freely available under the terms of the Lua license.

Contents

Index

Lua functions

_G
_VERSION

assert
collectgarbage
dofile
error
getmetatable
ipairs
load
loadfile
next
pairs
pcall
print
rawequal
rawget
rawlen
rawset
require
select
setmetatable
tonumber
tostring
type
xpcall

bit32.arshift
bit32.band
bit32.bnot
bit32.bor
bit32.btest
bit32.bxor
bit32.extract
bit32.lrotate
bit32.lshift
bit32.replace
bit32.rrotate
bit32.rshift

coroutine.create
coroutine.resume
coroutine.running
coroutine.status
coroutine.wrap
coroutine.yield

debug.debug
debug.getuservalue
debug.gethook
debug.getinfo
debug.getlocal
debug.getmetatable
debug.getregistry
debug.getupvalue
debug.setuservalue
debug.sethook
debug.setlocal
debug.setmetatable
debug.setupvalue
debug.traceback
debug.upvalueid
debug.upvaluejoin

file:close
file:flush
file:lines
file:read
file:seek
file:setvbuf
file:write

io.close
io.flush
io.input
io.lines
io.open
io.output
io.popen
io.read
io.stderr
io.stdin
io.stdout
io.tmpfile
io.type
io.write

 

math.abs
math.acos
math.asin
math.atan
math.atan2
math.ceil
math.cos
math.cosh
math.deg
math.exp
math.floor
math.fmod
math.frexp
math.huge
math.ldexp
math.log
math.max
math.min
math.modf
math.pi
math.pow
math.rad
math.random
math.randomseed
math.sin
math.sinh
math.sqrt
math.tan
math.tanh

os.clock
os.date
os.difftime
os.execute
os.exit
os.getenv
os.remove
os.rename
os.setlocale
os.time
os.tmpname

package.config
package.cpath
package.loaded
package.loadlib
package.path
package.preload
package.searchers
package.searchpath

string.byte
string.char
string.dump
string.find
string.format
string.gmatch
string.gsub
string.len
string.lower
string.match
string.rep
string.reverse
string.sub
string.upper

table.concat
table.insert
table.pack
table.remove
table.sort
table.unpack

C API

lua_Alloc
lua_CFunction
lua_Debug
lua_Hook
lua_Integer
lua_Number
lua_Reader
lua_State
lua_Unsigned
lua_Writer

lua_absindex
lua_arith
lua_atpanic
lua_call
lua_callk
lua_checkstack
lua_close
lua_compare
lua_concat
lua_copy
lua_createtable
lua_dump
lua_error
lua_gc
lua_getallocf
lua_getctx
lua_getfield
lua_getglobal
lua_gethook
lua_gethookcount
lua_gethookmask
lua_getinfo
lua_getlocal
lua_getmetatable
lua_getstack
lua_gettable
lua_gettop
lua_getupvalue
lua_getuservalue
lua_insert
lua_isboolean
lua_iscfunction
lua_isfunction
lua_islightuserdata
lua_isnil
lua_isnone
lua_isnoneornil
lua_isnumber
lua_isstring
lua_istable
lua_isthread
lua_isuserdata
lua_len
lua_load
lua_newstate
lua_newtable
lua_newthread
lua_newuserdata
lua_next
lua_pcall
lua_pcallk
lua_pop
lua_pushboolean
lua_pushcclosure
lua_pushcfunction
lua_pushfstring
lua_pushglobaltable
lua_pushinteger
lua_pushlightuserdata
lua_pushliteral
lua_pushlstring
lua_pushnil
lua_pushnumber
lua_pushstring
lua_pushthread
lua_pushunsigned
lua_pushvalue
lua_pushvfstring
lua_rawequal
lua_rawget
lua_rawgeti
lua_rawgetp
lua_rawlen
lua_rawset
lua_rawseti
lua_rawsetp
lua_register
lua_remove
lua_replace
lua_resume
lua_setallocf
lua_setfield
lua_setglobal
lua_sethook
lua_setlocal
lua_setmetatable
lua_settable
lua_settop
lua_setupvalue
lua_setuservalue
lua_status
lua_toboolean
lua_tocfunction
lua_tointeger
lua_tointegerx
lua_tolstring
lua_tonumber
lua_tonumberx
lua_topointer
lua_tostring
lua_tothread
lua_tounsigned
lua_tounsignedx
lua_touserdata
lua_type
lua_typename
lua_upvalueid
lua_upvalueindex
lua_upvaluejoin
lua_version
lua_xmove
lua_yield
lua_yieldk

auxiliary library

luaL_Buffer
luaL_Reg

luaL_addchar
luaL_addlstring
luaL_addsize
luaL_addstring
luaL_addvalue
luaL_argcheck
luaL_argerror
luaL_buffinit
luaL_buffinitsize
luaL_callmeta
luaL_checkany
luaL_checkint
luaL_checkinteger
luaL_checklong
luaL_checklstring
luaL_checknumber
luaL_checkoption
luaL_checkstack
luaL_checkstring
luaL_checktype
luaL_checkudata
luaL_checkunsigned
luaL_checkversion
luaL_dofile
luaL_dostring
luaL_error
luaL_execresult
luaL_fileresult
luaL_getmetafield
luaL_getmetatable
luaL_getsubtable
luaL_gsub
luaL_len
luaL_loadbuffer
luaL_loadbufferx
luaL_loadfile
luaL_loadfilex
luaL_loadstring
luaL_newlib
luaL_newlibtable
luaL_newmetatable
luaL_newstate
luaL_openlibs
luaL_optint
luaL_optinteger
luaL_optlong
luaL_optlstring
luaL_optnumber
luaL_optstring
luaL_optunsigned
luaL_prepbuffer
luaL_prepbuffsize
luaL_pushresult
luaL_pushresultsize
luaL_ref
luaL_requiref
luaL_setfuncs
luaL_setmetatable
luaL_testudata
luaL_tolstring
luaL_traceback
luaL_typename
luaL_unref
luaL_where
Last update: Tue Mar 12 11:22:18 BRT 2013 april-ann-0.4.1/lua/lua-5.2.2/doc/logo.gif000066400000000000000000000102101263004425400175670ustar00rootroot00000000000000GIF87arvz}~ oooqqqvvvzzz !!%%""%%)),,55115511::::??BBDDBBEEJJHHLLMMPPTTQQWWYYZZ\\^^``ccggiijjoollqqvvttyy{{~~‰ËŎƐǒȕʙ˙̟ϡϢѥҩөԭ֯ױױصڻݼ,' H*\ȰÇ#JHŋ3jȱǏ CIɓ(S\ɲ˗0cʜIpִQ:(RJI;HGSSFAPȑA!rC+j D#:S Y:A mSNF1Rg.=2 @ ;5A)s.:)v 0`ϟlnp#rdDD#xЙ 643#LTFyPE+]s2Qk( ;gGΗPfh ( oNr,NiHG0^s& *92;!lX_mwDGU7 DX qIRw5EA&9MdMDHM(އhcYC$#!~8@I$~! $pP |@ c11abRI!``a㠁Y2qkD;Pv}6jǍ0}F^ipZDE ph2+ar&C }t.GEbC |,s69 P( y0DpVft%Af.KH?,nb9"|/GAH"} A#w:p;x5$sE-I";[Xwu85!KV}[A]$ܩepG pYC@ڄkn:m VXf2 BYzD3 ,.zs9PBD\ lf4y",Bscdqf(6J袋@\[$z@@B ˦=5ɢE8H Dk8F{R= ~}Ν `g-1,RBHe-Ms (!{QHm ` AcRf!F &D `Dvd!B07 ,^lأRPIh~ @r)`$ hC@AG"yX mB4i Y(D8& F+1Rh KIH+ @EJ I* #RWDBhD ,6o| m#DxBЪV@$Y B yC$B*$} ZE @asPJoQ| Η?BYeJB8JH,iuJ&9a!r(#D|,9|D'yF)_st$ @2^o'ЯCh>@dz,F!QHB6I( E9E;C\oh2B5+$T}mHCه:VGjM0$8!mhApfBɏ@ m:O<6t}p<1@"t$H "BZ-6lgq,:@|P aF #Q!a'Qi];$}^V_xpmѳq8K`m[@(m`q! B /[mrg&^&qt$ 6g)l ];FpHA(]r Ƃb`QAFkq72-KMΧh xw=XvA@@m‡ƺXZO/ ?xă(+D,d9}Ev XԽIe 0]4y}'W!)] B|Fq D ͧ?s!#F3_ӣ738 N>@8lH q[ JƱ7(hE6,sI7)F0Vp`[%W25fc"8t.Aa!D@i_qeG#UT4PFxE vDa~ R t<"(WAl-[uf$P%~w9W@xwHv{9whV65P\ "ufoDd2g>6-c0(Y< 1"1O*p)ЊPj*25 0% (@BanS{ DN/%Jҍ  (3 b1$X]RP9Z*)~N-#r]NhGpl с^@FY4}b/M !0U|Me=dE$>pM ~rJ-&&@.\ 87{3`%0ds+1Hh22PK3 W0uE)*U))+ @50FtEOKHP@}^ jH0}U`10 k咹EcVUK$A_z`TEΑUɕ4A֓<RrfPGBza"gd62(ayImF"qc("gAyP0i@eESҘYO9b4"}"x@'Pupj`22,*&qٕf%E+]B%f0YJ3f?1,/p?;}XV5Q%H1Z4JmpOP7d=O y;!ӑpeq!F PP-eKfw.lzp`- j`o@EPOv*RzUP uS@Ĩ!IO*PEAO` p\ P 1{:LSPU@QzRʪ#4PG`Nڬ;april-ann-0.4.1/lua/lua-5.2.2/doc/lua.1000066400000000000000000000042341263004425400170140ustar00rootroot00000000000000.\" $Id: lua.man,v 1.13 2011/11/16 17:16:53 lhf Exp $ .TH LUA 1 "$Date: 2011/11/16 17:16:53 $" .SH NAME lua \- Lua interpreter .SH SYNOPSIS .B lua [ .I options ] [ .I script [ .I args ] ] .SH DESCRIPTION .B lua is the standalone Lua interpreter. It loads and executes Lua programs, either in textual source form or in precompiled binary form. (Precompiled binaries are output by .BR luac , the Lua compiler.) .B lua can be used as a batch interpreter and also interactively. .LP The given .I options are handled in order and then the Lua program in file .I script is loaded and executed. The given .I args are available to .I script as strings in a global table named .BR arg . If no options or arguments are given, then .B "\-v \-i" is assumed when the standard input is a terminal; otherwise, .B "\-" is assumed. .LP In interactive mode, .B lua prompts the user, reads lines from the standard input, and executes them as they are read. If a line does not contain a complete statement, then a secondary prompt is displayed and lines are read until a complete statement is formed or a syntax error is found. If a line starts with .BR '=' , then .B lua evaluates and displays the values of the expressions in the remainder of the line. .LP At the very start, before even handling the command line, .B lua checks the contents of the environment variables .B LUA_INIT_5_2 or .BR LUA_INIT , in that order. If the contents is of the form .RI '@ filename ', then .I filename is executed. Otherwise, the string is assumed to be a Lua statement and is executed. .SH OPTIONS .TP .BI \-e " stat" execute statement .IR stat . .TP .B \-i enter interactive mode after executing .IR script . .TP .BI \-l " name" execute the equivalent of .IB name =require(' name ') before executing .IR script . .TP .B \-v show version information. .TP .B \-E ignore environment variables. .TP .B \-\- stop handling options. .TP .B \- stop handling options and execute the standard input as a file. .SH "SEE ALSO" .BR luac (1) .br The documentation at lua.org, especially section 7 of the reference manual. .SH DIAGNOSTICS Error messages should be self explanatory. .SH AUTHORS R. Ierusalimschy, L. H. de Figueiredo, W. Celes .\" EOF april-ann-0.4.1/lua/lua-5.2.2/doc/lua.css000066400000000000000000000024301263004425400174400ustar00rootroot00000000000000body { color: #000000 ; background-color: #FFFFFF ; font-family: Helvetica, Arial, sans-serif ; text-align: justify ; margin-right: 30px ; margin-left: 30px ; } h1, h2, h3, h4 { font-family: Verdana, Geneva, sans-serif ; font-weight: normal ; font-style: italic ; } h2 { padding-top: 0.4em ; padding-bottom: 0.4em ; padding-left: 1em ; padding-right: 1em ; background-color: #E0E0FF ; border-radius: 8px ; } h3 { padding-left: 0.5em ; border-left: solid #E0E0FF 1em ; } table h3 { padding-left: 0px ; border-left: none ; } a:link { color: #000080 ; background-color: inherit ; text-decoration: none ; } a:visited { background-color: inherit ; text-decoration: none ; } a:link:hover, a:visited:hover { color: #000080 ; background-color: #E0E0FF ; } a:link:active, a:visited:active { color: #FF0000 ; } hr { border: 0 ; height: 1px ; color: #a0a0a0 ; background-color: #a0a0a0 ; } :target { background-color: #F8F8F8 ; padding: 8px ; border: solid #a0a0a0 2px ; } .footer { color: gray ; font-size: small ; } input[type=text] { border: solid #a0a0a0 2px ; border-radius: 2em ; -moz-border-radius: 2em ; background-image: url('images/search.png') ; background-repeat: no-repeat; background-position: 4px center ; padding-left: 20px ; height: 2em ; } april-ann-0.4.1/lua/lua-5.2.2/doc/luac.1000066400000000000000000000057771263004425400171740ustar00rootroot00000000000000.\" $Id: luac.man,v 1.29 2011/11/16 13:53:40 lhf Exp $ .TH LUAC 1 "$Date: 2011/11/16 13:53:40 $" .SH NAME luac \- Lua compiler .SH SYNOPSIS .B luac [ .I options ] [ .I filenames ] .SH DESCRIPTION .B luac is the Lua compiler. It translates programs written in the Lua programming language into binary files containing precompiled chunks that can be later loaded and executed. .LP The main advantages of precompiling chunks are: faster loading, protecting source code from accidental user changes, and off-line syntax checking. Precompiling does not imply faster execution because in Lua chunks are always compiled into bytecodes before being executed. .B luac simply allows those bytecodes to be saved in a file for later execution. Precompiled chunks are not necessarily smaller than the corresponding source. The main goal in precompiling is faster loading. .LP In the command line, you can mix text files containing Lua source and binary files containing precompiled chunks. .B luac produces a single output file containing the combined bytecodes for all files given. Executing the combined file is equivalent to executing the given files. By default, the output file is named .BR luac.out , but you can change this with the .B \-o option. .LP Precompiled chunks are .I not portable across different architectures. Moreover, the internal format of precompiled chunks is likely to change when a new version of Lua is released. Make sure you save the source files of all Lua programs that you precompile. .LP .SH OPTIONS .TP .B \-l produce a listing of the compiled bytecode for Lua's virtual machine. Listing bytecodes is useful to learn about Lua's virtual machine. If no files are given, then .B luac loads .B luac.out and lists its contents. Use .B \-l \-l for a full listing. .TP .BI \-o " file" output to .IR file , instead of the default .BR luac.out . (You can use .B "'\-'" for standard output, but not on platforms that open standard output in text mode.) The output file may be one of the given files because all files are loaded before the output file is written. Be careful not to overwrite precious files. .TP .B \-p load files but do not generate any output file. Used mainly for syntax checking and for testing precompiled chunks: corrupted files will probably generate errors when loaded. If no files are given, then .B luac loads .B luac.out and tests its contents. No messages are displayed if the file loads without errors. .TP .B \-s strip debug information before writing the output file. This saves some space in very large chunks, but if errors occur when running a stripped chunk, then the error messages may not contain the full information they usually do. In particular, line numbers and names of local variables are lost. .TP .B \-v show version information. .TP .B \-\- stop handling options. .TP .B \- stop handling options and process standard input. .SH "SEE ALSO" .BR lua (1) .br The documentation at lua.org. .SH DIAGNOSTICS Error messages should be self explanatory. .SH AUTHORS R. Ierusalimschy, L. H. de Figueiredo, W. Celes .\" EOF april-ann-0.4.1/lua/lua-5.2.2/doc/manual.css000066400000000000000000000005541263004425400201410ustar00rootroot00000000000000h3 code { font-family: inherit ; font-size: inherit ; } pre, code { font-size: 12pt ; } span.apii { float: right ; font-family: inherit ; font-style: normal ; font-size: small ; color: gray ; } p+h1, ul+h1 { padding-top: 0.4em ; padding-bottom: 0.4em ; padding-left: 24px ; margin-left: -24px ; background-color: #E0E0FF ; border-radius: 8px ; } april-ann-0.4.1/lua/lua-5.2.2/doc/manual.html000066400000000000000000011262011263004425400203140ustar00rootroot00000000000000 Lua 5.2 Reference Manual

Lua 5.2 Reference Manual

by Roberto Ierusalimschy, Luiz Henrique de Figueiredo, Waldemar Celes

Copyright © 2011–2013 Lua.org, PUC-Rio. Freely available under the terms of the Lua license.

contents · index

1 – Introduction

Lua is an extension programming language designed to support general procedural programming with data description facilities. It also offers good support for object-oriented programming, functional programming, and data-driven programming. Lua is intended to be used as a powerful, lightweight, embeddable scripting language for any program that needs one. Lua is implemented as a library, written in clean C, the common subset of Standard C and C++.

Being an extension language, Lua has no notion of a "main" program: it only works embedded in a host client, called the embedding program or simply the host. The host program can invoke functions to execute a piece of Lua code, can write and read Lua variables, and can register C functions to be called by Lua code. Through the use of C functions, Lua can be augmented to cope with a wide range of different domains, thus creating customized programming languages sharing a syntactical framework. The Lua distribution includes a sample host program called lua, which uses the Lua library to offer a complete, standalone Lua interpreter, for interactive or batch use.

Lua is free software, and is provided as usual with no guarantees, as stated in its license. The implementation described in this manual is available at Lua's official web site, www.lua.org.

Like any other reference manual, this document is dry in places. For a discussion of the decisions behind the design of Lua, see the technical papers available at Lua's web site. For a detailed introduction to programming in Lua, see Roberto's book, Programming in Lua.

2 – Basic Concepts

This section describes the basic concepts of the language.

2.1 – Values and Types

Lua is a dynamically typed language. This means that variables do not have types; only values do. There are no type definitions in the language. All values carry their own type.

All values in Lua are first-class values. This means that all values can be stored in variables, passed as arguments to other functions, and returned as results.

There are eight basic types in Lua: nil, boolean, number, string, function, userdata, thread, and table. Nil is the type of the value nil, whose main property is to be different from any other value; it usually represents the absence of a useful value. Boolean is the type of the values false and true. Both nil and false make a condition false; any other value makes it true. Number represents real (double-precision floating-point) numbers. Operations on numbers follow the same rules of the underlying C implementation, which, in turn, usually follows the IEEE 754 standard. (It is easy to build Lua interpreters that use other internal representations for numbers, such as single-precision floats or long integers; see file luaconf.h.) String represents immutable sequences of bytes. Lua is 8-bit clean: strings can contain any 8-bit value, including embedded zeros ('\0').

Lua can call (and manipulate) functions written in Lua and functions written in C (see §3.4.9).

The type userdata is provided to allow arbitrary C data to be stored in Lua variables. A userdata value is a pointer to a block of raw memory. There are two kinds of userdata: full userdata, where the block of memory is managed by Lua, and light userdata, where the block of memory is managed by the host. Userdata has no predefined operations in Lua, except assignment and identity test. By using metatables, the programmer can define operations for full userdata values (see §2.4). Userdata values cannot be created or modified in Lua, only through the C API. This guarantees the integrity of data owned by the host program.

The type thread represents independent threads of execution and it is used to implement coroutines (see §2.6). Do not confuse Lua threads with operating-system threads. Lua supports coroutines on all systems, even those that do not support threads.

The type table implements associative arrays, that is, arrays that can be indexed not only with numbers, but with any Lua value except nil and NaN (Not a Number, a special numeric value used to represent undefined or unrepresentable results, such as 0/0). Tables can be heterogeneous; that is, they can contain values of all types (except nil). Any key with value nil is not considered part of the table. Conversely, any key that is not part of a table has an associated value nil.

Tables are the sole data structuring mechanism in Lua; they can be used to represent ordinary arrays, sequences, symbol tables, sets, records, graphs, trees, etc. To represent records, Lua uses the field name as an index. The language supports this representation by providing a.name as syntactic sugar for a["name"]. There are several convenient ways to create tables in Lua (see §3.4.8).

We use the term sequence to denote a table where the set of all positive numeric keys is equal to {1..n} for some integer n, which is called the length of the sequence (see §3.4.6).

Like indices, the values of table fields can be of any type. In particular, because functions are first-class values, table fields can contain functions. Thus tables can also carry methods (see §3.4.10).

The indexing of tables follows the definition of raw equality in the language. The expressions a[i] and a[j] denote the same table element if and only if i and j are raw equal (that is, equal without metamethods).

Tables, functions, threads, and (full) userdata values are objects: variables do not actually contain these values, only references to them. Assignment, parameter passing, and function returns always manipulate references to such values; these operations do not imply any kind of copy.

The library function type returns a string describing the type of a given value (see §6.1).

2.2 – Environments and the Global Environment

As will be discussed in §3.2 and §3.3.3, any reference to a global name var is syntactically translated to _ENV.var. Moreover, every chunk is compiled in the scope of an external local variable called _ENV (see §3.3.2), so _ENV itself is never a global name in a chunk.

Despite the existence of this external _ENV variable and the translation of global names, _ENV is a completely regular name. In particular, you can define new variables and parameters with that name. Each reference to a global name uses the _ENV that is visible at that point in the program, following the usual visibility rules of Lua (see §3.5).

Any table used as the value of _ENV is called an environment.

Lua keeps a distinguished environment called the global environment. This value is kept at a special index in the C registry (see §4.5). In Lua, the variable _G is initialized with this same value.

When Lua compiles a chunk, it initializes the value of its _ENV upvalue with the global environment (see load). Therefore, by default, global variables in Lua code refer to entries in the global environment. Moreover, all standard libraries are loaded in the global environment and several functions there operate on that environment. You can use load (or loadfile) to load a chunk with a different environment. (In C, you have to load the chunk and then change the value of its first upvalue.)

If you change the global environment in the registry (through C code or the debug library), all chunks loaded after the change will get the new environment. Previously loaded chunks are not affected, however, as each has its own reference to the environment in its _ENV variable. Moreover, the variable _G (which is stored in the original global environment) is never updated by Lua.

2.3 – Error Handling

Because Lua is an embedded extension language, all Lua actions start from C code in the host program calling a function from the Lua library (see lua_pcall). Whenever an error occurs during the compilation or execution of a Lua chunk, control returns to the host, which can take appropriate measures (such as printing an error message).

Lua code can explicitly generate an error by calling the error function. If you need to catch errors in Lua, you can use pcall or xpcall to call a given function in protected mode.

Whenever there is an error, an error object (also called an error message) is propagated with information about the error. Lua itself only generates errors where the error object is a string, but programs may generate errors with any value for the error object.

When you use xpcall or lua_pcall, you may give a message handler to be called in case of errors. This function is called with the original error message and returns a new error message. It is called before the error unwinds the stack, so that it can gather more information about the error, for instance by inspecting the stack and creating a stack traceback. This message handler is still protected by the protected call; so, an error inside the message handler will call the message handler again. If this loop goes on, Lua breaks it and returns an appropriate message.

2.4 – Metatables and Metamethods

Every value in Lua can have a metatable. This metatable is an ordinary Lua table that defines the behavior of the original value under certain special operations. You can change several aspects of the behavior of operations over a value by setting specific fields in its metatable. For instance, when a non-numeric value is the operand of an addition, Lua checks for a function in the field "__add" of the value's metatable. If it finds one, Lua calls this function to perform the addition.

The keys in a metatable are derived from the event names; the corresponding values are called metamethods. In the previous example, the event is "add" and the metamethod is the function that performs the addition.

You can query the metatable of any value using the getmetatable function.

You can replace the metatable of tables using the setmetatable function. You cannot change the metatable of other types from Lua (except by using the debug library); you must use the C API for that.

Tables and full userdata have individual metatables (although multiple tables and userdata can share their metatables). Values of all other types share one single metatable per type; that is, there is one single metatable for all numbers, one for all strings, etc. By default, a value has no metatable, but the string library sets a metatable for the string type (see §6.4).

A metatable controls how an object behaves in arithmetic operations, order comparisons, concatenation, length operation, and indexing. A metatable also can define a function to be called when a userdata or a table is garbage collected. When Lua performs one of these operations over a value, it checks whether this value has a metatable with the corresponding event. If so, the value associated with that key (the metamethod) controls how Lua will perform the operation.

Metatables control the operations listed next. Each operation is identified by its corresponding name. The key for each operation is a string with its name prefixed by two underscores, '__'; for instance, the key for operation "add" is the string "__add".

The semantics of these operations is better explained by a Lua function describing how the interpreter executes the operation. The code shown here in Lua is only illustrative; the real behavior is hard coded in the interpreter and it is much more efficient than this simulation. All functions used in these descriptions (rawget, tonumber, etc.) are described in §6.1. In particular, to retrieve the metamethod of a given object, we use the expression 

     metatable(obj)[event]

This should be read as 

     rawget(getmetatable(obj) or {}, event)

This means that the access to a metamethod does not invoke other metamethods, and access to objects with no metatables does not fail (it simply results in nil).

For the unary - and # operators, the metamethod is called with a dummy second argument. This extra argument is only to simplify Lua's internals; it may be removed in future versions and therefore it is not present in the following code. (For most uses this extra argument is irrelevant.)

  • "add": the + operation.

    The function getbinhandler below defines how Lua chooses a handler for a binary operation. First, Lua tries the first operand. If its type does not define a handler for the operation, then Lua tries the second operand. 

         function getbinhandler (op1, op2, event)
       return metatable(op1)[event] or metatable(op2)[event]
     end

    By using this function, the behavior of the op1 + op2 is 

         function add_event (op1, op2)
       local o1, o2 = tonumber(op1), tonumber(op2)
       if o1 and o2 then  -- both operands are numeric?
         return o1 + o2   -- '+' here is the primitive 'add'
       else  -- at least one of the operands is not numeric
         local h = getbinhandler(op1, op2, "__add")
         if h then
           -- call the handler with both operands
           return (h(op1, op2))
         else  -- no handler available: default behavior
           error(···)
         end
       end
     end

  • "sub": the - operation. Behavior similar to the "add" operation.
  • "mul": the * operation. Behavior similar to the "add" operation.
  • "div": the / operation. Behavior similar to the "add" operation.
  • "mod": the % operation. Behavior similar to the "add" operation, with the operation o1 - floor(o1/o2)*o2 as the primitive operation.
  • "pow": the ^ (exponentiation) operation. Behavior similar to the "add" operation, with the function pow (from the C math library) as the primitive operation.
  • "unm": the unary - operation. 
         function unm_event (op)
       local o = tonumber(op)
       if o then  -- operand is numeric?
         return -o  -- '-' here is the primitive 'unm'
       else  -- the operand is not numeric.
         -- Try to get a handler from the operand
         local h = metatable(op).__unm
         if h then
           -- call the handler with the operand
           return (h(op))
         else  -- no handler available: default behavior
           error(···)
         end
       end
     end

  • "concat": the .. (concatenation) operation. 
         function concat_event (op1, op2)
       if (type(op1) == "string" or type(op1) == "number") and
          (type(op2) == "string" or type(op2) == "number") then
         return op1 .. op2  -- primitive string concatenation
       else
         local h = getbinhandler(op1, op2, "__concat")
         if h then
           return (h(op1, op2))
         else
           error(···)
         end
       end
     end

  • "len": the # operation. 
         function len_event (op)
       if type(op) == "string" then
         return strlen(op)      -- primitive string length
       else
         local h = metatable(op).__len
         if h then
           return (h(op))       -- call handler with the operand
         elseif type(op) == "table" then
           return #op              -- primitive table length
         else  -- no handler available: error
           error(···)
         end
       end
     end

    See §3.4.6 for a description of the length of a table.

  • "eq": the == operation. The function getequalhandler defines how Lua chooses a metamethod for equality. A metamethod is selected only when both values being compared have the same type and the same metamethod for the selected operation, and the values are either tables or full userdata. 
         function getequalhandler (op1, op2)
       if type(op1) ~= type(op2) or
          (type(op1) ~= "table" and type(op1) ~= "userdata") then
         return nil     -- different values
       end
       local mm1 = metatable(op1).__eq
       local mm2 = metatable(op2).__eq
       if mm1 == mm2 then return mm1 else return nil end
     end

    The "eq" event is defined as follows: 

         function eq_event (op1, op2)
       if op1 == op2 then   -- primitive equal?
         return true   -- values are equal
       end
       -- try metamethod
       local h = getequalhandler(op1, op2)
       if h then
         return not not h(op1, op2)
       else
         return false
       end
     end

    Note that the result is always a boolean.

  • "lt": the < operation. 
         function lt_event (op1, op2)
       if type(op1) == "number" and type(op2) == "number" then
         return op1 < op2   -- numeric comparison
       elseif type(op1) == "string" and type(op2) == "string" then
         return op1 < op2   -- lexicographic comparison
       else
         local h = getbinhandler(op1, op2, "__lt")
         if h then
           return not not h(op1, op2)
         else
           error(···)
         end
       end
     end

    Note that the result is always a boolean.

  • "le": the <= operation. 
         function le_event (op1, op2)
       if type(op1) == "number" and type(op2) == "number" then
         return op1 <= op2   -- numeric comparison
       elseif type(op1) == "string" and type(op2) == "string" then
         return op1 <= op2   -- lexicographic comparison
       else
         local h = getbinhandler(op1, op2, "__le")
         if h then
           return not not h(op1, op2)
         else
           h = getbinhandler(op1, op2, "__lt")
           if h then
             return not h(op2, op1)
           else
             error(···)
           end
         end
       end
     end

    Note that, in the absence of a "le" metamethod, Lua tries the "lt", assuming that a <= b is equivalent to not (b < a).

    As with the other comparison operators, the result is always a boolean.

  • "index": The indexing access table[key]. Note that the metamethod is tried only when key is not present in table. (When table is not a table, no key is ever present, so the metamethod is always tried.) 
         function gettable_event (table, key)
       local h
       if type(table) == "table" then
         local v = rawget(table, key)
         -- if key is present, return raw value
         if v ~= nil then return v end
         h = metatable(table).__index
         if h == nil then return nil end
       else
         h = metatable(table).__index
         if h == nil then
           error(···)
         end
       end
       if type(h) == "function" then
         return (h(table, key))     -- call the handler
       else return h[key]           -- or repeat operation on it
       end
     end

  • "newindex": The indexing assignment table[key] = value. Note that the metamethod is tried only when key is not present in table. 
         function settable_event (table, key, value)
       local h
       if type(table) == "table" then
         local v = rawget(table, key)
         -- if key is present, do raw assignment
         if v ~= nil then rawset(table, key, value); return end
         h = metatable(table).__newindex
         if h == nil then rawset(table, key, value); return end
       else
         h = metatable(table).__newindex
         if h == nil then
           error(···)
         end
       end
       if type(h) == "function" then
         h(table, key,value)           -- call the handler
       else h[key] = value             -- or repeat operation on it
       end
     end

  • "call": called when Lua calls a value. 
         function function_event (func, ...)
       if type(func) == "function" then
         return func(...)   -- primitive call
       else
         local h = metatable(func).__call
         if h then
           return h(func, ...)
         else
           error(···)
         end
       end
     end

2.5 – Garbage Collection

Lua performs automatic memory management. This means that you have to worry neither about allocating memory for new objects nor about freeing it when the objects are no longer needed. Lua manages memory automatically by running a garbage collector to collect all dead objects (that is, objects that are no longer accessible from Lua). All memory used by Lua is subject to automatic management: strings, tables, userdata, functions, threads, internal structures, etc.

Lua implements an incremental mark-and-sweep collector. It uses two numbers to control its garbage-collection cycles: the garbage-collector pause and the garbage-collector step multiplier. Both use percentage points as units (e.g., a value of 100 means an internal value of 1).

The garbage-collector pause controls how long the collector waits before starting a new cycle. Larger values make the collector less aggressive. Values smaller than 100 mean the collector will not wait to start a new cycle. A value of 200 means that the collector waits for the total memory in use to double before starting a new cycle.

The garbage-collector step multiplier controls the relative speed of the collector relative to memory allocation. Larger values make the collector more aggressive but also increase the size of each incremental step. Values smaller than 100 make the collector too slow and can result in the collector never finishing a cycle. The default is 200, which means that the collector runs at "twice" the speed of memory allocation.

If you set the step multiplier to a very large number (larger than 10% of the maximum number of bytes that the program may use), the collector behaves like a stop-the-world collector. If you then set the pause to 200, the collector behaves as in old Lua versions, doing a complete collection every time Lua doubles its memory usage.

You can change these numbers by calling lua_gc in C or collectgarbage in Lua. You can also use these functions to control the collector directly (e.g., stop and restart it).

As an experimental feature in Lua 5.2, you can change the collector's operation mode from incremental to generational. A generational collector assumes that most objects die young, and therefore it traverses only young (recently created) objects. This behavior can reduce the time used by the collector, but also increases memory usage (as old dead objects may accumulate). To mitigate this second problem, from time to time the generational collector performs a full collection. Remember that this is an experimental feature; you are welcome to try it, but check your gains.

2.5.1 – Garbage-Collection Metamethods

You can set garbage-collector metamethods for tables and, using the C API, for full userdata (see §2.4). These metamethods are also called finalizers. Finalizers allow you to coordinate Lua's garbage collection with external resource management (such as closing files, network or database connections, or freeing your own memory).

For an object (table or userdata) to be finalized when collected, you must mark it for finalization. You mark an object for finalization when you set its metatable and the metatable has a field indexed by the string "__gc". Note that if you set a metatable without a __gc field and later create that field in the metatable, the object will not be marked for finalization. However, after an object is marked, you can freely change the __gc field of its metatable.

When a marked object becomes garbage, it is not collected immediately by the garbage collector. Instead, Lua puts it in a list. After the collection, Lua does the equivalent of the following function for each object in that list: 

     function gc_event (obj)
       local h = metatable(obj).__gc
       if type(h) == "function" then
         h(obj)
       end
     end

At the end of each garbage-collection cycle, the finalizers for objects are called in the reverse order that they were marked for collection, among those collected in that cycle; that is, the first finalizer to be called is the one associated with the object marked last in the program. The execution of each finalizer may occur at any point during the execution of the regular code.

Because the object being collected must still be used by the finalizer, it (and other objects accessible only through it) must be resurrected by Lua. Usually, this resurrection is transient, and the object memory is freed in the next garbage-collection cycle. However, if the finalizer stores the object in some global place (e.g., a global variable), then there is a permanent resurrection. In any case, the object memory is freed only when it becomes completely inaccessible; its finalizer will never be called twice.

When you close a state (see lua_close), Lua calls the finalizers of all objects marked for finalization, following the reverse order that they were marked. If any finalizer marks new objects for collection during that phase, these new objects will not be finalized.

2.5.2 – Weak Tables

A weak table is a table whose elements are weak references. A weak reference is ignored by the garbage collector. In other words, if the only references to an object are weak references, then the garbage collector will collect that object.

A weak table can have weak keys, weak values, or both. A table with weak keys allows the collection of its keys, but prevents the collection of its values. A table with both weak keys and weak values allows the collection of both keys and values. In any case, if either the key or the value is collected, the whole pair is removed from the table. The weakness of a table is controlled by the __mode field of its metatable. If the __mode field is a string containing the character 'k', the keys in the table are weak. If __mode contains 'v', the values in the table are weak.

A table with weak keys and strong values is also called an ephemeron table. In an ephemeron table, a value is considered reachable only if its key is reachable. In particular, if the only reference to a key comes through its value, the pair is removed.

Any change in the weakness of a table may take effect only at the next collect cycle. In particular, if you change the weakness to a stronger mode, Lua may still collect some items from that table before the change takes effect.

Only objects that have an explicit construction are removed from weak tables. Values, such as numbers and light C functions, are not subject to garbage collection, and therefore are not removed from weak tables (unless its associated value is collected). Although strings are subject to garbage collection, they do not have an explicit construction, and therefore are not removed from weak tables.

Resurrected objects (that is, objects being finalized and objects accessible only through objects being finalized) have a special behavior in weak tables. They are removed from weak values before running their finalizers, but are removed from weak keys only in the next collection after running their finalizers, when such objects are actually freed. This behavior allows the finalizer to access properties associated with the object through weak tables.

If a weak table is among the resurrected objects in a collection cycle, it may not be properly cleared until the next cycle.

2.6 – Coroutines

Lua supports coroutines, also called collaborative multithreading. A coroutine in Lua represents an independent thread of execution. Unlike threads in multithread systems, however, a coroutine only suspends its execution by explicitly calling a yield function.

You create a coroutine by calling coroutine.create. Its sole argument is a function that is the main function of the coroutine. The create function only creates a new coroutine and returns a handle to it (an object of type thread); it does not start the coroutine.

You execute a coroutine by calling coroutine.resume. When you first call coroutine.resume, passing as its first argument a thread returned by coroutine.create, the coroutine starts its execution, at the first line of its main function. Extra arguments passed to coroutine.resume are passed on to the coroutine main function. After the coroutine starts running, it runs until it terminates or yields.

A coroutine can terminate its execution in two ways: normally, when its main function returns (explicitly or implicitly, after the last instruction); and abnormally, if there is an unprotected error. In the first case, coroutine.resume returns true, plus any values returned by the coroutine main function. In case of errors, coroutine.resume returns false plus an error message.

A coroutine yields by calling coroutine.yield. When a coroutine yields, the corresponding coroutine.resume returns immediately, even if the yield happens inside nested function calls (that is, not in the main function, but in a function directly or indirectly called by the main function). In the case of a yield, coroutine.resume also returns true, plus any values passed to coroutine.yield. The next time you resume the same coroutine, it continues its execution from the point where it yielded, with the call to coroutine.yield returning any extra arguments passed to coroutine.resume.

Like coroutine.create, the coroutine.wrap function also creates a coroutine, but instead of returning the coroutine itself, it returns a function that, when called, resumes the coroutine. Any arguments passed to this function go as extra arguments to coroutine.resume. coroutine.wrap returns all the values returned by coroutine.resume, except the first one (the boolean error code). Unlike coroutine.resume, coroutine.wrap does not catch errors; any error is propagated to the caller.

As an example of how coroutines work, consider the following code: 

     function foo (a)
       print("foo", a)
       return coroutine.yield(2*a)
     end
     
     co = coroutine.create(function (a,b)
           print("co-body", a, b)
           local r = foo(a+1)
           print("co-body", r)
           local r, s = coroutine.yield(a+b, a-b)
           print("co-body", r, s)
           return b, "end"
     end)
     
     print("main", coroutine.resume(co, 1, 10))
     print("main", coroutine.resume(co, "r"))
     print("main", coroutine.resume(co, "x", "y"))
     print("main", coroutine.resume(co, "x", "y"))

When you run it, it produces the following output: 

     co-body 1       10
     foo     2
     main    true    4
     co-body r
     main    true    11      -9
     co-body x       y
     main    true    10      end
     main    false   cannot resume dead coroutine

You can also create and manipulate coroutines through the C API: see functions lua_newthread, lua_resume, and lua_yield.

3 – The Language

This section describes the lexis, the syntax, and the semantics of Lua. In other words, this section describes which tokens are valid, how they can be combined, and what their combinations mean.

Language constructs will be explained using the usual extended BNF notation, in which {a} means 0 or more a's, and [a] means an optional a. Non-terminals are shown like non-terminal, keywords are shown like kword, and other terminal symbols are shown like ‘=’. The complete syntax of Lua can be found in §9 at the end of this manual.

3.1 – Lexical Conventions

Lua is a free-form language. It ignores spaces (including new lines) and comments between lexical elements (tokens), except as delimiters between names and keywords.

Names (also called identifiers) in Lua can be any string of letters, digits, and underscores, not beginning with a digit. Identifiers are used to name variables, table fields, and labels.

The following keywords are reserved and cannot be used as names: 

     and       break     do        else      elseif    end
     false     for       function  goto      if        in
     local     nil       not       or        repeat    return
     then      true      until     while

Lua is a case-sensitive language: and is a reserved word, but And and AND are two different, valid names. As a convention, names starting with an underscore followed by uppercase letters (such as _VERSION) are reserved for variables used by Lua.

The following strings denote other tokens: 

     +     -     *     /     %     ^     #
     ==    ~=    <=    >=    <     >     =
     (     )     {     }     [     ]     ::
     ;     :     ,     .     ..    ...

Literal strings can be delimited by matching single or double quotes, and can contain the following C-like escape sequences: '\a' (bell), '\b' (backspace), '\f' (form feed), '\n' (newline), '\r' (carriage return), '\t' (horizontal tab), '\v' (vertical tab), '\\' (backslash), '\"' (quotation mark [double quote]), and '\'' (apostrophe [single quote]). A backslash followed by a real newline results in a newline in the string. The escape sequence '\z' skips the following span of white-space characters, including line breaks; it is particularly useful to break and indent a long literal string into multiple lines without adding the newlines and spaces into the string contents.

A byte in a literal string can also be specified by its numerical value. This can be done with the escape sequence \xXX, where XX is a sequence of exactly two hexadecimal digits, or with the escape sequence \ddd, where ddd is a sequence of up to three decimal digits. (Note that if a decimal escape is to be followed by a digit, it must be expressed using exactly three digits.) Strings in Lua can contain any 8-bit value, including embedded zeros, which can be specified as '\0'.

Literal strings can also be defined using a long format enclosed by long brackets. We define an opening long bracket of level n as an opening square bracket followed by n equal signs followed by another opening square bracket. So, an opening long bracket of level 0 is written as [[, an opening long bracket of level 1 is written as [=[, and so on. A closing long bracket is defined similarly; for instance, a closing long bracket of level 4 is written as ]====]. A long literal starts with an opening long bracket of any level and ends at the first closing long bracket of the same level. It can contain any text except a closing bracket of the proper level. Literals in this bracketed form can run for several lines, do not interpret any escape sequences, and ignore long brackets of any other level. Any kind of end-of-line sequence (carriage return, newline, carriage return followed by newline, or newline followed by carriage return) is converted to a simple newline.

Any byte in a literal string not explicitly affected by the previous rules represents itself. However, Lua opens files for parsing in text mode, and the system file functions may have problems with some control characters. So, it is safer to represent non-text data as a quoted literal with explicit escape sequences for non-text characters.

For convenience, when the opening long bracket is immediately followed by a newline, the newline is not included in the string. As an example, in a system using ASCII (in which 'a' is coded as 97, newline is coded as 10, and '1' is coded as 49), the five literal strings below denote the same string: 

     a = 'alo\n123"'
     a = "alo\n123\""
     a = '\97lo\10\04923"'
     a = [[alo
     123"]]
     a = [==[
     alo
     123"]==]

A numerical constant can be written with an optional fractional part and an optional decimal exponent, marked by a letter 'e' or 'E'. Lua also accepts hexadecimal constants, which start with 0x or 0X. Hexadecimal constants also accept an optional fractional part plus an optional binary exponent, marked by a letter 'p' or 'P'. Examples of valid numerical constants are 

     3     3.0     3.1416     314.16e-2     0.31416E1
     0xff  0x0.1E  0xA23p-4   0X1.921FB54442D18P+1

A comment starts with a double hyphen (--) anywhere outside a string. If the text immediately after -- is not an opening long bracket, the comment is a short comment, which runs until the end of the line. Otherwise, it is a long comment, which runs until the corresponding closing long bracket. Long comments are frequently used to disable code temporarily.

3.2 – Variables

Variables are places that store values. There are three kinds of variables in Lua: global variables, local variables, and table fields.

A single name can denote a global variable or a local variable (or a function's formal parameter, which is a particular kind of local variable): 

	var ::= Name

Name denotes identifiers, as defined in §3.1.

Any variable name is assumed to be global unless explicitly declared as a local (see §3.3.7). Local variables are lexically scoped: local variables can be freely accessed by functions defined inside their scope (see §3.5).

Before the first assignment to a variable, its value is nil.

Square brackets are used to index a table: 

	var ::= prefixexp ‘[’ exp ‘]’

The meaning of accesses to table fields can be changed via metatables. An access to an indexed variable t[i] is equivalent to a call gettable_event(t,i). (See §2.4 for a complete description of the gettable_event function. This function is not defined or callable in Lua. We use it here only for explanatory purposes.)

The syntax var.Name is just syntactic sugar for var["Name"]: 

	var ::= prefixexp ‘.’ Name

An access to a global variable x is equivalent to _ENV.x. Due to the way that chunks are compiled, _ENV is never a global name (see §2.2).

3.3 – Statements

Lua supports an almost conventional set of statements, similar to those in Pascal or C. This set includes assignments, control structures, function calls, and variable declarations.

3.3.1 – Blocks

A block is a list of statements, which are executed sequentially: 

	block ::= {stat}

Lua has empty statements that allow you to separate statements with semicolons, start a block with a semicolon or write two semicolons in sequence: 

	stat ::= ‘;’

Function calls and assignments can start with an open parenthesis. This possibility leads to an ambiguity in Lua's grammar. Consider the following fragment: 

     a = b + c
     (print or io.write)('done')

The grammar could see it in two ways: 

     a = b + c(print or io.write)('done')
     
     a = b + c; (print or io.write)('done')

The current parser always sees such constructions in the first way, interpreting the open parenthesis as the start of the arguments to a call. To avoid this ambiguity, it is a good practice to always precede with a semicolon statements that start with a parenthesis: 

     ;(print or io.write)('done')

A block can be explicitly delimited to produce a single statement: 

	stat ::= do block end

Explicit blocks are useful to control the scope of variable declarations. Explicit blocks are also sometimes used to add a return statement in the middle of another block (see §3.3.4).

3.3.2 – Chunks

The unit of compilation of Lua is called a chunk. Syntactically, a chunk is simply a block: 

	chunk ::= block

Lua handles a chunk as the body of an anonymous function with a variable number of arguments (see §3.4.10). As such, chunks can define local variables, receive arguments, and return values. Moreover, such anonymous function is compiled as in the scope of an external local variable called _ENV (see §2.2). The resulting function always has _ENV as its only upvalue, even if it does not use that variable.

A chunk can be stored in a file or in a string inside the host program. To execute a chunk, Lua first precompiles the chunk into instructions for a virtual machine, and then it executes the compiled code with an interpreter for the virtual machine.

Chunks can also be precompiled into binary form; see program luac for details. Programs in source and compiled forms are interchangeable; Lua automatically detects the file type and acts accordingly.

3.3.3 – Assignment

Lua allows multiple assignments. Therefore, the syntax for assignment defines a list of variables on the left side and a list of expressions on the right side. The elements in both lists are separated by commas: 

	stat ::= varlist ‘=’ explist
	varlist ::= var {‘,’ var}
	explist ::= exp {‘,’ exp}

Expressions are discussed in §3.4.

Before the assignment, the list of values is adjusted to the length of the list of variables. If there are more values than needed, the excess values are thrown away. If there are fewer values than needed, the list is extended with as many nil's as needed. If the list of expressions ends with a function call, then all values returned by that call enter the list of values, before the adjustment (except when the call is enclosed in parentheses; see §3.4).

The assignment statement first evaluates all its expressions and only then are the assignments performed. Thus the code 

     i = 3
     i, a[i] = i+1, 20

sets a[3] to 20, without affecting a[4] because the i in a[i] is evaluated (to 3) before it is assigned 4. Similarly, the line 

     x, y = y, x

exchanges the values of x and y, and 

     x, y, z = y, z, x

cyclically permutes the values of x, y, and z.

The meaning of assignments to global variables and table fields can be changed via metatables. An assignment to an indexed variable t[i] = val is equivalent to settable_event(t,i,val). (See §2.4 for a complete description of the settable_event function. This function is not defined or callable in Lua. We use it here only for explanatory purposes.)

An assignment to a global variable x = val is equivalent to the assignment _ENV.x = val (see §2.2).

3.3.4 – Control Structures

The control structures if, while, and repeat have the usual meaning and familiar syntax: 

	stat ::= while exp do block end
	stat ::= repeat block until exp
	stat ::= if exp then block {elseif exp then block} [else block] end

Lua also has a for statement, in two flavors (see §3.3.5).

The condition expression of a control structure can return any value. Both false and nil are considered false. All values different from nil and false are considered true (in particular, the number 0 and the empty string are also true).

In the repeat–until loop, the inner block does not end at the until keyword, but only after the condition. So, the condition can refer to local variables declared inside the loop block.

The goto statement transfers the program control to a label. For syntactical reasons, labels in Lua are considered statements too: 

	stat ::= goto Name
	stat ::= label
	label ::= ‘::’ Name ‘::’

A label is visible in the entire block where it is defined, except inside nested blocks where a label with the same name is defined and inside nested functions. A goto may jump to any visible label as long as it does not enter into the scope of a local variable.

Labels and empty statements are called void statements, as they perform no actions.

The break statement terminates the execution of a while, repeat, or for loop, skipping to the next statement after the loop: 

	stat ::= break

A break ends the innermost enclosing loop.

The return statement is used to return values from a function or a chunk (which is a function in disguise). Functions can return more than one value, so the syntax for the return statement is 

	stat ::= return [explist] [‘;’]

The return statement can only be written as the last statement of a block. If it is really necessary to return in the middle of a block, then an explicit inner block can be used, as in the idiom do return end, because now return is the last statement in its (inner) block.

3.3.5 – For Statement

The for statement has two forms: one numeric and one generic.

The numeric for loop repeats a block of code while a control variable runs through an arithmetic progression. It has the following syntax: 

	stat ::= for Name ‘=’ exp ‘,’ exp [‘,’ exp] do block end

The block is repeated for name starting at the value of the first exp, until it passes the second exp by steps of the third exp. More precisely, a for statement like 

     for v = e1, e2, e3 do block end

is equivalent to the code: 

     do
       local var, limit, step = tonumber(e1), tonumber(e2), tonumber(e3)
       if not (var and limit and step) then error() end
       while (step > 0 and var <= limit) or (step <= 0 and var >= limit) do
         local v = var
         block
         var = var + step
       end
     end

Note the following:

  • All three control expressions are evaluated only once, before the loop starts. They must all result in numbers.
  • var, limit, and step are invisible variables. The names shown here are for explanatory purposes only.
  • If the third expression (the step) is absent, then a step of 1 is used.
  • You can use break to exit a for loop.
  • The loop variable v is local to the loop; you cannot use its value after the for ends or is broken. If you need this value, assign it to another variable before breaking or exiting the loop.

The generic for statement works over functions, called iterators. On each iteration, the iterator function is called to produce a new value, stopping when this new value is nil. The generic for loop has the following syntax: 

	stat ::= for namelist in explist do block end
	namelist ::= Name {‘,’ Name}

A for statement like 

     for var_1, ···, var_n in explist do block end

is equivalent to the code: 

     do
       local f, s, var = explist
       while true do
         local var_1, ···, var_n = f(s, var)
         if var_1 == nil then break end
         var = var_1
         block
       end
     end

Note the following:

  • explist is evaluated only once. Its results are an iterator function, a state, and an initial value for the first iterator variable.
  • f, s, and var are invisible variables. The names are here for explanatory purposes only.
  • You can use break to exit a for loop.
  • The loop variables var_i are local to the loop; you cannot use their values after the for ends. If you need these values, then assign them to other variables before breaking or exiting the loop.

3.3.6 – Function Calls as Statements

To allow possible side-effects, function calls can be executed as statements: 

	stat ::= functioncall

In this case, all returned values are thrown away. Function calls are explained in §3.4.9.

3.3.7 – Local Declarations

Local variables can be declared anywhere inside a block. The declaration can include an initial assignment: 

	stat ::= local namelist [‘=’ explist]

If present, an initial assignment has the same semantics of a multiple assignment (see §3.3.3). Otherwise, all variables are initialized with nil.

A chunk is also a block (see §3.3.2), and so local variables can be declared in a chunk outside any explicit block.

The visibility rules for local variables are explained in §3.5.

3.4 – Expressions

The basic expressions in Lua are the following: 

	exp ::= prefixexp
	exp ::= nil | false | true
	exp ::= Number
	exp ::= String
	exp ::= functiondef
	exp ::= tableconstructor
	exp ::= ‘...’
	exp ::= exp binop exp
	exp ::= unop exp
	prefixexp ::= var | functioncall | ‘(’ exp ‘)’

Numbers and literal strings are explained in §3.1; variables are explained in §3.2; function definitions are explained in §3.4.10; function calls are explained in §3.4.9; table constructors are explained in §3.4.8. Vararg expressions, denoted by three dots ('...'), can only be used when directly inside a vararg function; they are explained in §3.4.10.

Binary operators comprise arithmetic operators (see §3.4.1), relational operators (see §3.4.3), logical operators (see §3.4.4), and the concatenation operator (see §3.4.5). Unary operators comprise the unary minus (see §3.4.1), the unary not (see §3.4.4), and the unary length operator (see §3.4.6).

Both function calls and vararg expressions can result in multiple values. If a function call is used as a statement (see §3.3.6), then its return list is adjusted to zero elements, thus discarding all returned values. If an expression is used as the last (or the only) element of a list of expressions, then no adjustment is made (unless the expression is enclosed in parentheses). In all other contexts, Lua adjusts the result list to one element, either discarding all values except the first one or adding a single nil if there are no values.

Here are some examples: 

     f()                -- adjusted to 0 results
     g(f(), x)          -- f() is adjusted to 1 result
     g(x, f())          -- g gets x plus all results from f()
     a,b,c = f(), x     -- f() is adjusted to 1 result (c gets nil)
     a,b = ...          -- a gets the first vararg parameter, b gets
                        -- the second (both a and b can get nil if there
                        -- is no corresponding vararg parameter)
     
     a,b,c = x, f()     -- f() is adjusted to 2 results
     a,b,c = f()        -- f() is adjusted to 3 results
     return f()         -- returns all results from f()
     return ...         -- returns all received vararg parameters
     return x,y,f()     -- returns x, y, and all results from f()
     {f()}              -- creates a list with all results from f()
     {...}              -- creates a list with all vararg parameters
     {f(), nil}         -- f() is adjusted to 1 result

Any expression enclosed in parentheses always results in only one value. Thus, (f(x,y,z)) is always a single value, even if f returns several values. (The value of (f(x,y,z)) is the first value returned by f or nil if f does not return any values.)

3.4.1 – Arithmetic Operators

Lua supports the usual arithmetic operators: the binary + (addition), - (subtraction), * (multiplication), / (division), % (modulo), and ^ (exponentiation); and unary - (mathematical negation). If the operands are numbers, or strings that can be converted to numbers (see §3.4.2), then all operations have the usual meaning. Exponentiation works for any exponent. For instance, x^(-0.5) computes the inverse of the square root of x. Modulo is defined as 

     a % b == a - math.floor(a/b)*b

That is, it is the remainder of a division that rounds the quotient towards minus infinity.

3.4.2 – Coercion

Lua provides automatic conversion between string and number values at run time. Any arithmetic operation applied to a string tries to convert this string to a number, following the rules of the Lua lexer. (The string may have leading and trailing spaces and a sign.) Conversely, whenever a number is used where a string is expected, the number is converted to a string, in a reasonable format. For complete control over how numbers are converted to strings, use the format function from the string library (see string.format).

3.4.3 – Relational Operators

The relational operators in Lua are 

     ==    ~=    <     >     <=    >=

These operators always result in false or true.

Equality (==) first compares the type of its operands. If the types are different, then the result is false. Otherwise, the values of the operands are compared. Numbers and strings are compared in the usual way. Tables, userdata, and threads are compared by reference: two objects are considered equal only if they are the same object. Every time you create a new object (a table, userdata, or thread), this new object is different from any previously existing object. Closures with the same reference are always equal. Closures with any detectable difference (different behavior, different definition) are always different.

You can change the way that Lua compares tables and userdata by using the "eq" metamethod (see §2.4).

The conversion rules of §3.4.2 do not apply to equality comparisons. Thus, "0"==0 evaluates to false, and t[0] and t["0"] denote different entries in a table.

The operator ~= is exactly the negation of equality (==).

The order operators work as follows. If both arguments are numbers, then they are compared as such. Otherwise, if both arguments are strings, then their values are compared according to the current locale. Otherwise, Lua tries to call the "lt" or the "le" metamethod (see §2.4). A comparison a > b is translated to b < a and a >= b is translated to b <= a.

3.4.4 – Logical Operators

The logical operators in Lua are and, or, and not. Like the control structures (see §3.3.4), all logical operators consider both false and nil as false and anything else as true.

The negation operator not always returns false or true. The conjunction operator and returns its first argument if this value is false or nil; otherwise, and returns its second argument. The disjunction operator or returns its first argument if this value is different from nil and false; otherwise, or returns its second argument. Both and and or use short-cut evaluation; that is, the second operand is evaluated only if necessary. Here are some examples: 

     10 or 20            --> 10
     10 or error()       --> 10
     nil or "a"          --> "a"
     nil and 10          --> nil
     false and error()   --> false
     false and nil       --> false
     false or nil        --> nil
     10 and 20           --> 20

(In this manual, --> indicates the result of the preceding expression.)

3.4.5 – Concatenation

The string concatenation operator in Lua is denoted by two dots ('..'). If both operands are strings or numbers, then they are converted to strings according to the rules mentioned in §3.4.2. Otherwise, the __concat metamethod is called (see §2.4).

3.4.6 – The Length Operator

The length operator is denoted by the unary prefix operator #. The length of a string is its number of bytes (that is, the usual meaning of string length when each character is one byte).

A program can modify the behavior of the length operator for any value but strings through the __len metamethod (see §2.4).

Unless a __len metamethod is given, the length of a table t is only defined if the table is a sequence, that is, the set of its positive numeric keys is equal to {1..n} for some integer n. In that case, n is its length. Note that a table like 

     {10, 20, nil, 40}

is not a sequence, because it has the key 4 but does not have the key 3. (So, there is no n such that the set {1..n} is equal to the set of positive numeric keys of that table.) Note, however, that non-numeric keys do not interfere with whether a table is a sequence.

3.4.7 – Precedence

Operator precedence in Lua follows the table below, from lower to higher priority: 

     or
     and
     <     >     <=    >=    ~=    ==
     ..
     +     -
     *     /     %
     not   #     - (unary)
     ^

As usual, you can use parentheses to change the precedences of an expression. The concatenation ('..') and exponentiation ('^') operators are right associative. All other binary operators are left associative.

3.4.8 – Table Constructors

Table constructors are expressions that create tables. Every time a constructor is evaluated, a new table is created. A constructor can be used to create an empty table or to create a table and initialize some of its fields. The general syntax for constructors is 

	tableconstructor ::= ‘{’ [fieldlist] ‘}’
	fieldlist ::= field {fieldsep field} [fieldsep]
	field ::= ‘[’ exp ‘]’ ‘=’ exp | Name ‘=’ exp | exp
	fieldsep ::= ‘,’ | ‘;’

Each field of the form [exp1] = exp2 adds to the new table an entry with key exp1 and value exp2. A field of the form name = exp is equivalent to ["name"] = exp. Finally, fields of the form exp are equivalent to [i] = exp, where i are consecutive numerical integers, starting with 1. Fields in the other formats do not affect this counting. For example, 

     a = { [f(1)] = g; "x", "y"; x = 1, f(x), [30] = 23; 45 }

is equivalent to 

     do
       local t = {}
       t[f(1)] = g
       t[1] = "x"         -- 1st exp
       t[2] = "y"         -- 2nd exp
       t.x = 1            -- t["x"] = 1
       t[3] = f(x)        -- 3rd exp
       t[30] = 23
       t[4] = 45          -- 4th exp
       a = t
     end

If the last field in the list has the form exp and the expression is a function call or a vararg expression, then all values returned by this expression enter the list consecutively (see §3.4.9).

The field list can have an optional trailing separator, as a convenience for machine-generated code.

3.4.9 – Function Calls

A function call in Lua has the following syntax: 

	functioncall ::= prefixexp args

In a function call, first prefixexp and args are evaluated. If the value of prefixexp has type function, then this function is called with the given arguments. Otherwise, the prefixexp "call" metamethod is called, having as first parameter the value of prefixexp, followed by the original call arguments (see §2.4).

The form 

	functioncall ::= prefixexp ‘:’ Name args

can be used to call "methods". A call v:name(args) is syntactic sugar for v.name(v,args), except that v is evaluated only once.

Arguments have the following syntax: 

	args ::= ‘(’ [explist] ‘)’
	args ::= tableconstructor
	args ::= String

All argument expressions are evaluated before the call. A call of the form f{fields} is syntactic sugar for f({fields}); that is, the argument list is a single new table. A call of the form f'string' (or f"string" or f[[string]]) is syntactic sugar for f('string'); that is, the argument list is a single literal string.

A call of the form return functioncall is called a tail call. Lua implements proper tail calls (or proper tail recursion): in a tail call, the called function reuses the stack entry of the calling function. Therefore, there is no limit on the number of nested tail calls that a program can execute. However, a tail call erases any debug information about the calling function. Note that a tail call only happens with a particular syntax, where the return has one single function call as argument; this syntax makes the calling function return exactly the returns of the called function. So, none of the following examples are tail calls: 

     return (f(x))        -- results adjusted to 1
     return 2 * f(x)
     return x, f(x)       -- additional results
     f(x); return         -- results discarded
     return x or f(x)     -- results adjusted to 1

3.4.10 – Function Definitions

The syntax for function definition is 

	functiondef ::= function funcbody
	funcbody ::= ‘(’ [parlist] ‘)’ block end

The following syntactic sugar simplifies function definitions: 

	stat ::= function funcname funcbody
	stat ::= local function Name funcbody
	funcname ::= Name {‘.’ Name} [‘:’ Name]

The statement 

     function f () body end

translates to 

     f = function () body end

The statement 

     function t.a.b.c.f () body end

translates to 

     t.a.b.c.f = function () body end

The statement 

     local function f () body end

translates to 

     local f; f = function () body end

not to 

     local f = function () body end

(This only makes a difference when the body of the function contains references to f.)

A function definition is an executable expression, whose value has type function. When Lua precompiles a chunk, all its function bodies are precompiled too. Then, whenever Lua executes the function definition, the function is instantiated (or closed). This function instance (or closure) is the final value of the expression.

Parameters act as local variables that are initialized with the argument values: 

	parlist ::= namelist [‘,’ ‘...’] | ‘...’

When a function is called, the list of arguments is adjusted to the length of the list of parameters, unless the function is a vararg function, which is indicated by three dots ('...') at the end of its parameter list. A vararg function does not adjust its argument list; instead, it collects all extra arguments and supplies them to the function through a vararg expression, which is also written as three dots. The value of this expression is a list of all actual extra arguments, similar to a function with multiple results. If a vararg expression is used inside another expression or in the middle of a list of expressions, then its return list is adjusted to one element. If the expression is used as the last element of a list of expressions, then no adjustment is made (unless that last expression is enclosed in parentheses).

As an example, consider the following definitions: 

     function f(a, b) end
     function g(a, b, ...) end
     function r() return 1,2,3 end

Then, we have the following mapping from arguments to parameters and to the vararg expression: 

     CALL            PARAMETERS
     
     f(3)             a=3, b=nil
     f(3, 4)          a=3, b=4
     f(3, 4, 5)       a=3, b=4
     f(r(), 10)       a=1, b=10
     f(r())           a=1, b=2
     
     g(3)             a=3, b=nil, ... -->  (nothing)
     g(3, 4)          a=3, b=4,   ... -->  (nothing)
     g(3, 4, 5, 8)    a=3, b=4,   ... -->  5  8
     g(5, r())        a=5, b=1,   ... -->  2  3

Results are returned using the return statement (see §3.3.4). If control reaches the end of a function without encountering a return statement, then the function returns with no results.

There is a system-dependent limit on the number of values that a function may return. This limit is guaranteed to be larger than 1000.

The colon syntax is used for defining methods, that is, functions that have an implicit extra parameter self. Thus, the statement 

     function t.a.b.c:f (params) body end

is syntactic sugar for 

     t.a.b.c.f = function (self, params) body end

3.5 – Visibility Rules

Lua is a lexically scoped language. The scope of a local variable begins at the first statement after its declaration and lasts until the last non-void statement of the innermost block that includes the declaration. Consider the following example: 

     x = 10                -- global variable
     do                    -- new block
       local x = x         -- new 'x', with value 10
       print(x)            --> 10
       x = x+1
       do                  -- another block
         local x = x+1     -- another 'x'
         print(x)          --> 12
       end
       print(x)            --> 11
     end
     print(x)              --> 10  (the global one)

Notice that, in a declaration like local x = x, the new x being declared is not in scope yet, and so the second x refers to the outside variable.

Because of the lexical scoping rules, local variables can be freely accessed by functions defined inside their scope. A local variable used by an inner function is called an upvalue, or external local variable, inside the inner function.

Notice that each execution of a local statement defines new local variables. Consider the following example: 

     a = {}
     local x = 20
     for i=1,10 do
       local y = 0
       a[i] = function () y=y+1; return x+y end
     end

The loop creates ten closures (that is, ten instances of the anonymous function). Each of these closures uses a different y variable, while all of them share the same x.

4 – The Application Program Interface

This section describes the C API for Lua, that is, the set of C functions available to the host program to communicate with Lua. All API functions and related types and constants are declared in the header file lua.h.

Even when we use the term "function", any facility in the API may be provided as a macro instead. Except where stated otherwise, all such macros use each of their arguments exactly once (except for the first argument, which is always a Lua state), and so do not generate any hidden side-effects.

As in most C libraries, the Lua API functions do not check their arguments for validity or consistency. However, you can change this behavior by compiling Lua with the macro LUA_USE_APICHECK defined.

4.1 – The Stack

Lua uses a virtual stack to pass values to and from C. Each element in this stack represents a Lua value (nil, number, string, etc.).

Whenever Lua calls C, the called function gets a new stack, which is independent of previous stacks and of stacks of C functions that are still active. This stack initially contains any arguments to the C function and it is where the C function pushes its results to be returned to the caller (see lua_CFunction).

For convenience, most query operations in the API do not follow a strict stack discipline. Instead, they can refer to any element in the stack by using an index: A positive index represents an absolute stack position (starting at 1); a negative index represents an offset relative to the top of the stack. More specifically, if the stack has n elements, then index 1 represents the first element (that is, the element that was pushed onto the stack first) and index n represents the last element; index -1 also represents the last element (that is, the element at the top) and index -n represents the first element.

4.2 – Stack Size

When you interact with the Lua API, you are responsible for ensuring consistency. In particular, you are responsible for controlling stack overflow. You can use the function lua_checkstack to ensure that the stack has extra slots when pushing new elements.

Whenever Lua calls C, it ensures that the stack has at least LUA_MINSTACK extra slots. LUA_MINSTACK is defined as 20, so that usually you do not have to worry about stack space unless your code has loops pushing elements onto the stack.

When you call a Lua function without a fixed number of results (see lua_call), Lua ensures that the stack has enough size for all results, but it does not ensure any extra space. So, before pushing anything in the stack after such a call you should use lua_checkstack.

4.3 – Valid and Acceptable Indices

Any function in the API that receives stack indices works only with valid indices or acceptable indices.

A valid index is an index that refers to a real position within the stack, that is, its position lies between 1 and the stack top (1 ≤ abs(index) ≤ top). Usually, functions that can modify the value at an index require valid indices.

Unless otherwise noted, any function that accepts valid indices also accepts pseudo-indices, which represent some Lua values that are accessible to C code but which are not in the stack. Pseudo-indices are used to access the registry and the upvalues of a C function (see §4.4).

Functions that do not need a specific stack position, but only a value in the stack (e.g., query functions), can be called with acceptable indices. An acceptable index can be any valid index, including the pseudo-indices, but it also can be any positive index after the stack top within the space allocated for the stack, that is, indices up to the stack size. (Note that 0 is never an acceptable index.) Except when noted otherwise, functions in the API work with acceptable indices.

Acceptable indices serve to avoid extra tests against the stack top when querying the stack. For instance, a C function can query its third argument without the need to first check whether there is a third argument, that is, without the need to check whether 3 is a valid index.

For functions that can be called with acceptable indices, any non-valid index is treated as if it contains a value of a virtual type LUA_TNONE, which behaves like a nil value.

4.4 – C Closures

When a C function is created, it is possible to associate some values with it, thus creating a C closure (see lua_pushcclosure); these values are called upvalues and are accessible to the function whenever it is called.

Whenever a C function is called, its upvalues are located at specific pseudo-indices. These pseudo-indices are produced by the macro lua_upvalueindex. The first value associated with a function is at position lua_upvalueindex(1), and so on. Any access to lua_upvalueindex(n), where n is greater than the number of upvalues of the current function (but not greater than 256), produces an acceptable but invalid index.

4.5 – Registry

Lua provides a registry, a predefined table that can be used by any C code to store whatever Lua values it needs to store. The registry table is always located at pseudo-index LUA_REGISTRYINDEX, which is a valid index. Any C library can store data into this table, but it should take care to choose keys that are different from those used by other libraries, to avoid collisions. Typically, you should use as key a string containing your library name, or a light userdata with the address of a C object in your code, or any Lua object created by your code. As with global names, string keys starting with an underscore followed by uppercase letters are reserved for Lua.

The integer keys in the registry are used by the reference mechanism, implemented by the auxiliary library, and by some predefined values. Therefore, integer keys should not be used for other purposes.

When you create a new Lua state, its registry comes with some predefined values. These predefined values are indexed with integer keys defined as constants in lua.h. The following constants are defined:

  • LUA_RIDX_MAINTHREAD: At this index the registry has the main thread of the state. (The main thread is the one created together with the state.)
  • LUA_RIDX_GLOBALS: At this index the registry has the global environment.

4.6 – Error Handling in C

Internally, Lua uses the C longjmp facility to handle errors. (You can also choose to use exceptions if you compile Lua as C++; search for LUAI_THROW in the source code.) When Lua faces any error (such as a memory allocation error, type errors, syntax errors, and runtime errors) it raises an error; that is, it does a long jump. A protected environment uses setjmp to set a recovery point; any error jumps to the most recent active recovery point.

If an error happens outside any protected environment, Lua calls a panic function (see lua_atpanic) and then calls abort, thus exiting the host application. Your panic function can avoid this exit by never returning (e.g., doing a long jump to your own recovery point outside Lua).

The panic function runs as if it were a message handler (see §2.3); in particular, the error message is at the top of the stack. However, there is no guarantees about stack space. To push anything on the stack, the panic function should first check the available space (see §4.2).

Most functions in the API can throw an error, for instance due to a memory allocation error. The documentation for each function indicates whether it can throw errors.

Inside a C function you can throw an error by calling lua_error.

4.7 – Handling Yields in C

Internally, Lua uses the C longjmp facility to yield a coroutine. Therefore, if a function foo calls an API function and this API function yields (directly or indirectly by calling another function that yields), Lua cannot return to foo any more, because the longjmp removes its frame from the C stack.

To avoid this kind of problem, Lua raises an error whenever it tries to yield across an API call, except for three functions: lua_yieldk, lua_callk, and lua_pcallk. All those functions receive a continuation function (as a parameter called k) to continue execution after a yield.

We need to set some terminology to explain continuations. We have a C function called from Lua which we will call the original function. This original function then calls one of those three functions in the C API, which we will call the callee function, that then yields the current thread. (This can happen when the callee function is lua_yieldk, or when the callee function is either lua_callk or lua_pcallk and the function called by them yields.)

Suppose the running thread yields while executing the callee function. After the thread resumes, it eventually will finish running the callee function. However, the callee function cannot return to the original function, because its frame in the C stack was destroyed by the yield. Instead, Lua calls a continuation function, which was given as an argument to the callee function. As the name implies, the continuation function should continue the task of the original function.

Lua treats the continuation function as if it were the original function. The continuation function receives the same Lua stack from the original function, in the same state it would be if the callee function had returned. (For instance, after a lua_callk the function and its arguments are removed from the stack and replaced by the results from the call.) It also has the same upvalues. Whatever it returns is handled by Lua as if it were the return of the original function.

The only difference in the Lua state between the original function and its continuation is the result of a call to lua_getctx.

4.8 – Functions and Types

Here we list all functions and types from the C API in alphabetical order. Each function has an indicator like this: [-o, +p, x]

The first field, o, is how many elements the function pops from the stack. The second field, p, is how many elements the function pushes onto the stack. (Any function always pushes its results after popping its arguments.) A field in the form x|y means the function can push (or pop) x or y elements, depending on the situation; an interrogation mark '?' means that we cannot know how many elements the function pops/pushes by looking only at its arguments (e.g., they may depend on what is on the stack). The third field, x, tells whether the function may throw errors: '-' means the function never throws any error; 'e' means the function may throw errors; 'v' means the function may throw an error on purpose.

lua_absindex

[-0, +0, –] 

int lua_absindex (lua_State *L, int idx);

Converts the acceptable index idx into an absolute index (that is, one that does not depend on the stack top).

lua_Alloc

typedef void * (*lua_Alloc) (void *ud,
                             void *ptr,
                             size_t osize,
                             size_t nsize);

The type of the memory-allocation function used by Lua states. The allocator function must provide a functionality similar to realloc, but not exactly the same. Its arguments are ud, an opaque pointer passed to lua_newstate; ptr, a pointer to the block being allocated/reallocated/freed; osize, the original size of the block or some code about what is being allocated; nsize, the new size of the block.

When ptr is not NULL, osize is the size of the block pointed by ptr, that is, the size given when it was allocated or reallocated.

When ptr is NULL, osize encodes the kind of object that Lua is allocating. osize is any of LUA_TSTRING, LUA_TTABLE, LUA_TFUNCTION, LUA_TUSERDATA, or LUA_TTHREAD when (and only when) Lua is creating a new object of that type. When osize is some other value, Lua is allocating memory for something else.

Lua assumes the following behavior from the allocator function:

When nsize is zero, the allocator should behave like free and return NULL.

When nsize is not zero, the allocator should behave like realloc. The allocator returns NULL if and only if it cannot fulfill the request. Lua assumes that the allocator never fails when osize >= nsize.

Here is a simple implementation for the allocator function. It is used in the auxiliary library by luaL_newstate. 

     static void *l_alloc (void *ud, void *ptr, size_t osize,
                                                size_t nsize) {
       (void)ud;  (void)osize;  /* not used */
       if (nsize == 0) {
         free(ptr);
         return NULL;
       }
       else
         return realloc(ptr, nsize);
     }

Note that Standard C ensures that free(NULL) has no effect and that realloc(NULL, size) is equivalent to malloc(size). This code assumes that realloc does not fail when shrinking a block. (Although Standard C does not ensure this behavior, it seems to be a safe assumption.)

lua_arith

[-(2|1), +1, e] 

void lua_arith (lua_State *L, int op);

Performs an arithmetic operation over the two values (or one, in the case of negation) at the top of the stack, with the value at the top being the second operand, pops these values, and pushes the result of the operation. The function follows the semantics of the corresponding Lua operator (that is, it may call metamethods).

The value of op must be one of the following constants:

lua_atpanic

[-0, +0, –] 

lua_CFunction lua_atpanic (lua_State *L, lua_CFunction panicf);

Sets a new panic function and returns the old one (see §4.6).

lua_call

[-(nargs+1), +nresults, e] 

void lua_call (lua_State *L, int nargs, int nresults);

Calls a function.

To call a function you must use the following protocol: first, the function to be called is pushed onto the stack; then, the arguments to the function are pushed in direct order; that is, the first argument is pushed first. Finally you call lua_call; nargs is the number of arguments that you pushed onto the stack. All arguments and the function value are popped from the stack when the function is called. The function results are pushed onto the stack when the function returns. The number of results is adjusted to nresults, unless nresults is LUA_MULTRET. In this case, all results from the function are pushed. Lua takes care that the returned values fit into the stack space. The function results are pushed onto the stack in direct order (the first result is pushed first), so that after the call the last result is on the top of the stack.

Any error inside the called function is propagated upwards (with a longjmp).

The following example shows how the host program can do the equivalent to this Lua code: 

     a = f("how", t.x, 14)

Here it is in C: 

     lua_getglobal(L, "f");                  /* function to be called */
     lua_pushstring(L, "how");                        /* 1st argument */
     lua_getglobal(L, "t");                    /* table to be indexed */
     lua_getfield(L, -1, "x");        /* push result of t.x (2nd arg) */
     lua_remove(L, -2);                  /* remove 't' from the stack */
     lua_pushinteger(L, 14);                          /* 3rd argument */
     lua_call(L, 3, 1);     /* call 'f' with 3 arguments and 1 result */
     lua_setglobal(L, "a");                         /* set global 'a' */

Note that the code above is "balanced": at its end, the stack is back to its original configuration. This is considered good programming practice.

lua_callk

[-(nargs + 1), +nresults, e] 

void lua_callk (lua_State *L, int nargs, int nresults, int ctx,
                lua_CFunction k);

This function behaves exactly like lua_call, but allows the called function to yield (see §4.7).

lua_CFunction

typedef int (*lua_CFunction) (lua_State *L);

Type for C functions.

In order to communicate properly with Lua, a C function must use the following protocol, which defines the way parameters and results are passed: a C function receives its arguments from Lua in its stack in direct order (the first argument is pushed first). So, when the function starts, lua_gettop(L) returns the number of arguments received by the function. The first argument (if any) is at index 1 and its last argument is at index lua_gettop(L). To return values to Lua, a C function just pushes them onto the stack, in direct order (the first result is pushed first), and returns the number of results. Any other value in the stack below the results will be properly discarded by Lua. Like a Lua function, a C function called by Lua can also return many results.

As an example, the following function receives a variable number of numerical arguments and returns their average and sum: 

     static int foo (lua_State *L) {
       int n = lua_gettop(L);    /* number of arguments */
       lua_Number sum = 0;
       int i;
       for (i = 1; i <= n; i++) {
         if (!lua_isnumber(L, i)) {
           lua_pushstring(L, "incorrect argument");
           lua_error(L);
         }
         sum += lua_tonumber(L, i);
       }
       lua_pushnumber(L, sum/n);        /* first result */
       lua_pushnumber(L, sum);         /* second result */
       return 2;                   /* number of results */
     }

lua_checkstack

[-0, +0, –] 

int lua_checkstack (lua_State *L, int extra);

Ensures that there are at least extra free stack slots in the stack. It returns false if it cannot fulfill the request, because it would cause the stack to be larger than a fixed maximum size (typically at least a few thousand elements) or because it cannot allocate memory for the new stack size. This function never shrinks the stack; if the stack is already larger than the new size, it is left unchanged.

lua_close

[-0, +0, –] 

void lua_close (lua_State *L);

Destroys all objects in the given Lua state (calling the corresponding garbage-collection metamethods, if any) and frees all dynamic memory used by this state. On several platforms, you may not need to call this function, because all resources are naturally released when the host program ends. On the other hand, long-running programs that create multiple states, such as daemons or web servers, might need to close states as soon as they are not needed.

lua_compare

[-0, +0, e] 

int lua_compare (lua_State *L, int index1, int index2, int op);

Compares two Lua values. Returns 1 if the value at index index1 satisfies op when compared with the value at index index2, following the semantics of the corresponding Lua operator (that is, it may call metamethods). Otherwise returns 0. Also returns 0 if any of the indices is non valid.

The value of op must be one of the following constants:

lua_concat

[-n, +1, e] 

void lua_concat (lua_State *L, int n);

Concatenates the n values at the top of the stack, pops them, and leaves the result at the top. If n is 1, the result is the single value on the stack (that is, the function does nothing); if n is 0, the result is the empty string. Concatenation is performed following the usual semantics of Lua (see §3.4.5).

lua_copy

[-0, +0, –] 

void lua_copy (lua_State *L, int fromidx, int toidx);

Moves the element at index fromidx into the valid index toidx without shifting any element (therefore replacing the value at that position).

lua_createtable

[-0, +1, e] 

void lua_createtable (lua_State *L, int narr, int nrec);

Creates a new empty table and pushes it onto the stack. Parameter narr is a hint for how many elements the table will have as a sequence; parameter nrec is a hint for how many other elements the table will have. Lua may use these hints to preallocate memory for the new table. This pre-allocation is useful for performance when you know in advance how many elements the table will have. Otherwise you can use the function lua_newtable.

lua_dump

[-0, +0, e] 

int lua_dump (lua_State *L, lua_Writer writer, void *data);

Dumps a function as a binary chunk. Receives a Lua function on the top of the stack and produces a binary chunk that, if loaded again, results in a function equivalent to the one dumped. As it produces parts of the chunk, lua_dump calls function writer (see lua_Writer) with the given data to write them.

The value returned is the error code returned by the last call to the writer; 0 means no errors.

This function does not pop the Lua function from the stack.

lua_error

[-1, +0, v] 

int lua_error (lua_State *L);

Generates a Lua error. The error message (which can actually be a Lua value of any type) must be on the stack top. This function does a long jump, and therefore never returns (see luaL_error).

lua_gc

[-0, +0, e] 

int lua_gc (lua_State *L, int what, int data);

Controls the garbage collector.

This function performs several tasks, according to the value of the parameter what:

  • LUA_GCSTOP: stops the garbage collector.
  • LUA_GCRESTART: restarts the garbage collector.
  • LUA_GCCOLLECT: performs a full garbage-collection cycle.
  • LUA_GCCOUNT: returns the current amount of memory (in Kbytes) in use by Lua.
  • LUA_GCCOUNTB: returns the remainder of dividing the current amount of bytes of memory in use by Lua by 1024.
  • LUA_GCSTEP: performs an incremental step of garbage collection. The step "size" is controlled by data (larger values mean more steps) in a non-specified way. If you want to control the step size you must experimentally tune the value of data. The function returns 1 if the step finished a garbage-collection cycle.
  • LUA_GCSETPAUSE: sets data as the new value for the pause of the collector (see §2.5). The function returns the previous value of the pause.
  • LUA_GCSETSTEPMUL: sets data as the new value for the step multiplier of the collector (see §2.5). The function returns the previous value of the step multiplier.
  • LUA_GCISRUNNING: returns a boolean that tells whether the collector is running (i.e., not stopped).
  • LUA_GCGEN: changes the collector to generational mode (see §2.5).
  • LUA_GCINC: changes the collector to incremental mode. This is the default mode.

For more details about these options, see collectgarbage.

lua_getallocf

[-0, +0, –] 

lua_Alloc lua_getallocf (lua_State *L, void **ud);

Returns the memory-allocation function of a given state. If ud is not NULL, Lua stores in *ud the opaque pointer passed to lua_newstate.

lua_getctx

[-0, +0, –] 

int lua_getctx (lua_State *L, int *ctx);

This function is called by a continuation function (see §4.7) to retrieve the status of the thread and a context information.

When called in the original function, lua_getctx always returns LUA_OK and does not change the value of its argument ctx. When called inside a continuation function, lua_getctx returns LUA_YIELD and sets the value of ctx to be the context information (the value passed as the ctx argument to the callee together with the continuation function).

When the callee is lua_pcallk, Lua may also call its continuation function to handle errors during the call. That is, upon an error in the function called by lua_pcallk, Lua may not return to the original function but instead may call the continuation function. In that case, a call to lua_getctx will return the error code (the value that would be returned by lua_pcallk); the value of ctx will be set to the context information, as in the case of a yield.

lua_getfield

[-0, +1, e] 

void lua_getfield (lua_State *L, int index, const char *k);

Pushes onto the stack the value t[k], where t is the value at the given index. As in Lua, this function may trigger a metamethod for the "index" event (see §2.4).

lua_getglobal

[-0, +1, e] 

void lua_getglobal (lua_State *L, const char *name);

Pushes onto the stack the value of the global name.

lua_getmetatable

[-0, +(0|1), –] 

int lua_getmetatable (lua_State *L, int index);

Pushes onto the stack the metatable of the value at the given index. If the value does not have a metatable, the function returns 0 and pushes nothing on the stack.

lua_gettable

[-1, +1, e] 

void lua_gettable (lua_State *L, int index);

Pushes onto the stack the value t[k], where t is the value at the given index and k is the value at the top of the stack.

This function pops the key from the stack (putting the resulting value in its place). As in Lua, this function may trigger a metamethod for the "index" event (see §2.4).

lua_gettop

[-0, +0, –] 

int lua_gettop (lua_State *L);

Returns the index of the top element in the stack. Because indices start at 1, this result is equal to the number of elements in the stack (and so 0 means an empty stack).

lua_getuservalue

[-0, +1, –] 

void lua_getuservalue (lua_State *L, int index);

Pushes onto the stack the Lua value associated with the userdata at the given index. This Lua value must be a table or nil.

lua_insert

[-1, +1, –] 

void lua_insert (lua_State *L, int index);

Moves the top element into the given valid index, shifting up the elements above this index to open space. This function cannot be called with a pseudo-index, because a pseudo-index is not an actual stack position.

lua_Integer

typedef ptrdiff_t lua_Integer;

The type used by the Lua API to represent signed integral values.

By default it is a ptrdiff_t, which is usually the largest signed integral type the machine handles "comfortably".

lua_isboolean

[-0, +0, –] 

int lua_isboolean (lua_State *L, int index);

Returns 1 if the value at the given index is a boolean, and 0 otherwise.

lua_iscfunction

[-0, +0, –] 

int lua_iscfunction (lua_State *L, int index);

Returns 1 if the value at the given index is a C function, and 0 otherwise.

lua_isfunction

[-0, +0, –] 

int lua_isfunction (lua_State *L, int index);

Returns 1 if the value at the given index is a function (either C or Lua), and 0 otherwise.

lua_islightuserdata

[-0, +0, –] 

int lua_islightuserdata (lua_State *L, int index);

Returns 1 if the value at the given index is a light userdata, and 0 otherwise.

lua_isnil

[-0, +0, –] 

int lua_isnil (lua_State *L, int index);

Returns 1 if the value at the given index is nil, and 0 otherwise.

lua_isnone

[-0, +0, –] 

int lua_isnone (lua_State *L, int index);

Returns 1 if the given index is not valid, and 0 otherwise.

lua_isnoneornil

[-0, +0, –] 

int lua_isnoneornil (lua_State *L, int index);

Returns 1 if the given index is not valid or if the value at this index is nil, and 0 otherwise.

lua_isnumber

[-0, +0, –] 

int lua_isnumber (lua_State *L, int index);

Returns 1 if the value at the given index is a number or a string convertible to a number, and 0 otherwise.

lua_isstring

[-0, +0, –] 

int lua_isstring (lua_State *L, int index);

Returns 1 if the value at the given index is a string or a number (which is always convertible to a string), and 0 otherwise.

lua_istable

[-0, +0, –] 

int lua_istable (lua_State *L, int index);

Returns 1 if the value at the given index is a table, and 0 otherwise.

lua_isthread

[-0, +0, –] 

int lua_isthread (lua_State *L, int index);

Returns 1 if the value at the given index is a thread, and 0 otherwise.

lua_isuserdata

[-0, +0, –] 

int lua_isuserdata (lua_State *L, int index);

Returns 1 if the value at the given index is a userdata (either full or light), and 0 otherwise.

lua_len

[-0, +1, e] 

void lua_len (lua_State *L, int index);

Returns the "length" of the value at the given index; it is equivalent to the '#' operator in Lua (see §3.4.6). The result is pushed on the stack.

lua_load

[-0, +1, –] 

int lua_load (lua_State *L,
              lua_Reader reader,
              void *data,
              const char *source,
              const char *mode);

Loads a Lua chunk (without running it). If there are no errors, lua_load pushes the compiled chunk as a Lua function on top of the stack. Otherwise, it pushes an error message.

The return values of lua_load are:

  • LUA_OK: no errors;
  • LUA_ERRSYNTAX: syntax error during precompilation;
  • LUA_ERRMEM: memory allocation error;
  • LUA_ERRGCMM: error while running a __gc metamethod. (This error has no relation with the chunk being loaded. It is generated by the garbage collector.)

The lua_load function uses a user-supplied reader function to read the chunk (see lua_Reader). The data argument is an opaque value passed to the reader function.

The source argument gives a name to the chunk, which is used for error messages and in debug information (see §4.9).

lua_load automatically detects whether the chunk is text or binary and loads it accordingly (see program luac). The string mode works as in function load, with the addition that a NULL value is equivalent to the string "bt".

lua_load uses the stack internally, so the reader function should always leave the stack unmodified when returning.

If the resulting function has one upvalue, this upvalue is set to the value of the global environment stored at index LUA_RIDX_GLOBALS in the registry (see §4.5). When loading main chunks, this upvalue will be the _ENV variable (see §2.2).

lua_newstate

[-0, +0, –] 

lua_State *lua_newstate (lua_Alloc f, void *ud);

Creates a new thread running in a new, independent state. Returns NULL if cannot create the thread or the state (due to lack of memory). The argument f is the allocator function; Lua does all memory allocation for this state through this function. The second argument, ud, is an opaque pointer that Lua passes to the allocator in every call.

lua_newtable

[-0, +1, e] 

void lua_newtable (lua_State *L);

Creates a new empty table and pushes it onto the stack. It is equivalent to lua_createtable(L, 0, 0).

lua_newthread

[-0, +1, e] 

lua_State *lua_newthread (lua_State *L);

Creates a new thread, pushes it on the stack, and returns a pointer to a lua_State that represents this new thread. The new thread returned by this function shares with the original thread its global environment, but has an independent execution stack.

There is no explicit function to close or to destroy a thread. Threads are subject to garbage collection, like any Lua object.

lua_newuserdata

[-0, +1, e] 

void *lua_newuserdata (lua_State *L, size_t size);

This function allocates a new block of memory with the given size, pushes onto the stack a new full userdata with the block address, and returns this address. The host program can freely use this memory.

lua_next

[-1, +(2|0), e] 

int lua_next (lua_State *L, int index);

Pops a key from the stack, and pushes a key–value pair from the table at the given index (the "next" pair after the given key). If there are no more elements in the table, then lua_next returns 0 (and pushes nothing).

A typical traversal looks like this: 

     /* table is in the stack at index 't' */
     lua_pushnil(L);  /* first key */
     while (lua_next(L, t) != 0) {
       /* uses 'key' (at index -2) and 'value' (at index -1) */
       printf("%s - %s\n",
              lua_typename(L, lua_type(L, -2)),
              lua_typename(L, lua_type(L, -1)));
       /* removes 'value'; keeps 'key' for next iteration */
       lua_pop(L, 1);
     }

While traversing a table, do not call lua_tolstring directly on a key, unless you know that the key is actually a string. Recall that lua_tolstring may change the value at the given index; this confuses the next call to lua_next.

See function next for the caveats of modifying the table during its traversal.

lua_Number

typedef double lua_Number;

The type of numbers in Lua. By default, it is double, but that can be changed in luaconf.h. Through this configuration file you can change Lua to operate with another type for numbers (e.g., float or long).

lua_pcall

[-(nargs + 1), +(nresults|1), –] 

int lua_pcall (lua_State *L, int nargs, int nresults, int msgh);

Calls a function in protected mode.

Both nargs and nresults have the same meaning as in lua_call. If there are no errors during the call, lua_pcall behaves exactly like lua_call. However, if there is any error, lua_pcall catches it, pushes a single value on the stack (the error message), and returns an error code. Like lua_call, lua_pcall always removes the function and its arguments from the stack.

If msgh is 0, then the error message returned on the stack is exactly the original error message. Otherwise, msgh is the stack index of a message handler. (In the current implementation, this index cannot be a pseudo-index.) In case of runtime errors, this function will be called with the error message and its return value will be the message returned on the stack by lua_pcall.

Typically, the message handler is used to add more debug information to the error message, such as a stack traceback. Such information cannot be gathered after the return of lua_pcall, since by then the stack has unwound.

The lua_pcall function returns one of the following codes (defined in lua.h):

  • LUA_OK (0): success.
  • LUA_ERRRUN: a runtime error.
  • LUA_ERRMEM: memory allocation error. For such errors, Lua does not call the message handler.
  • LUA_ERRERR: error while running the message handler.
  • LUA_ERRGCMM: error while running a __gc metamethod. (This error typically has no relation with the function being called. It is generated by the garbage collector.)

lua_pcallk

[-(nargs + 1), +(nresults|1), –] 

int lua_pcallk (lua_State *L,
                int nargs,
                int nresults,
                int errfunc,
                int ctx,
                lua_CFunction k);

This function behaves exactly like lua_pcall, but allows the called function to yield (see §4.7).

lua_pop

[-n, +0, –] 

void lua_pop (lua_State *L, int n);

Pops n elements from the stack.

lua_pushboolean

[-0, +1, –] 

void lua_pushboolean (lua_State *L, int b);

Pushes a boolean value with value b onto the stack.

lua_pushcclosure

[-n, +1, e] 

void lua_pushcclosure (lua_State *L, lua_CFunction fn, int n);

Pushes a new C closure onto the stack.

When a C function is created, it is possible to associate some values with it, thus creating a C closure (see §4.4); these values are then accessible to the function whenever it is called. To associate values with a C function, first these values should be pushed onto the stack (when there are multiple values, the first value is pushed first). Then lua_pushcclosure is called to create and push the C function onto the stack, with the argument n telling how many values should be associated with the function. lua_pushcclosure also pops these values from the stack.

The maximum value for n is 255.

When n is zero, this function creates a light C function, which is just a pointer to the C function. In that case, it never throws a memory error.

lua_pushcfunction

[-0, +1, –] 

void lua_pushcfunction (lua_State *L, lua_CFunction f);

Pushes a C function onto the stack. This function receives a pointer to a C function and pushes onto the stack a Lua value of type function that, when called, invokes the corresponding C function.

Any function to be registered in Lua must follow the correct protocol to receive its parameters and return its results (see lua_CFunction).

lua_pushcfunction is defined as a macro: 

     #define lua_pushcfunction(L,f)  lua_pushcclosure(L,f,0)

Note that f is used twice.

lua_pushfstring

[-0, +1, e] 

const char *lua_pushfstring (lua_State *L, const char *fmt, ...);

Pushes onto the stack a formatted string and returns a pointer to this string. It is similar to the ANSI C function sprintf, but has some important differences:

  • You do not have to allocate space for the result: the result is a Lua string and Lua takes care of memory allocation (and deallocation, through garbage collection).
  • The conversion specifiers are quite restricted. There are no flags, widths, or precisions. The conversion specifiers can only be '%%' (inserts a '%' in the string), '%s' (inserts a zero-terminated string, with no size restrictions), '%f' (inserts a lua_Number), '%p' (inserts a pointer as a hexadecimal numeral), '%d' (inserts an int), and '%c' (inserts an int as a byte).

lua_pushglobaltable

[-0, +1, –] 

void lua_pushglobaltable (lua_State *L);

Pushes the global environment onto the stack.

lua_pushinteger

[-0, +1, –] 

void lua_pushinteger (lua_State *L, lua_Integer n);

Pushes a number with value n onto the stack.

lua_pushlightuserdata

[-0, +1, –] 

void lua_pushlightuserdata (lua_State *L, void *p);

Pushes a light userdata onto the stack.

Userdata represent C values in Lua. A light userdata represents a pointer, a void*. It is a value (like a number): you do not create it, it has no individual metatable, and it is not collected (as it was never created). A light userdata is equal to "any" light userdata with the same C address.

lua_pushliteral

[-0, +1, e] 

const char *lua_pushliteral (lua_State *L, const char *s);

This macro is equivalent to lua_pushlstring, but can be used only when s is a literal string. It automatically provides the string length.

lua_pushlstring

[-0, +1, e] 

const char *lua_pushlstring (lua_State *L, const char *s, size_t len);

Pushes the string pointed to by s with size len onto the stack. Lua makes (or reuses) an internal copy of the given string, so the memory at s can be freed or reused immediately after the function returns. The string can contain any binary data, including embedded zeros.

Returns a pointer to the internal copy of the string.

lua_pushnil

[-0, +1, –] 

void lua_pushnil (lua_State *L);

Pushes a nil value onto the stack.

lua_pushnumber

[-0, +1, –] 

void lua_pushnumber (lua_State *L, lua_Number n);

Pushes a number with value n onto the stack.

lua_pushstring

[-0, +1, e] 

const char *lua_pushstring (lua_State *L, const char *s);

Pushes the zero-terminated string pointed to by s onto the stack. Lua makes (or reuses) an internal copy of the given string, so the memory at s can be freed or reused immediately after the function returns.

Returns a pointer to the internal copy of the string.

If s is NULL, pushes nil and returns NULL.

lua_pushthread

[-0, +1, –] 

int lua_pushthread (lua_State *L);

Pushes the thread represented by L onto the stack. Returns 1 if this thread is the main thread of its state.

lua_pushunsigned

[-0, +1, –] 

void lua_pushunsigned (lua_State *L, lua_Unsigned n);

Pushes a number with value n onto the stack.

lua_pushvalue

[-0, +1, –] 

void lua_pushvalue (lua_State *L, int index);

Pushes a copy of the element at the given index onto the stack.

lua_pushvfstring

[-0, +1, e] 

const char *lua_pushvfstring (lua_State *L,
                              const char *fmt,
                              va_list argp);

Equivalent to lua_pushfstring, except that it receives a va_list instead of a variable number of arguments.

lua_rawequal

[-0, +0, –] 

int lua_rawequal (lua_State *L, int index1, int index2);

Returns 1 if the two values in indices index1 and index2 are primitively equal (that is, without calling metamethods). Otherwise returns 0. Also returns 0 if any of the indices are non valid.

lua_rawget

[-1, +1, –] 

void lua_rawget (lua_State *L, int index);

Similar to lua_gettable, but does a raw access (i.e., without metamethods).

lua_rawgeti

[-0, +1, –] 

void lua_rawgeti (lua_State *L, int index, int n);

Pushes onto the stack the value t[n], where t is the table at the given index. The access is raw; that is, it does not invoke metamethods.

lua_rawgetp

[-0, +1, –] 

void lua_rawgetp (lua_State *L, int index, const void *p);

Pushes onto the stack the value t[k], where t is the table at the given index and k is the pointer p represented as a light userdata. The access is raw; that is, it does not invoke metamethods.

lua_rawlen

[-0, +0, –] 

size_t lua_rawlen (lua_State *L, int index);

Returns the raw "length" of the value at the given index: for strings, this is the string length; for tables, this is the result of the length operator ('#') with no metamethods; for userdata, this is the size of the block of memory allocated for the userdata; for other values, it is 0.

lua_rawset

[-2, +0, e] 

void lua_rawset (lua_State *L, int index);

Similar to lua_settable, but does a raw assignment (i.e., without metamethods).

lua_rawseti

[-1, +0, e] 

void lua_rawseti (lua_State *L, int index, int n);

Does the equivalent of t[n] = v, where t is the table at the given index and v is the value at the top of the stack.

This function pops the value from the stack. The assignment is raw; that is, it does not invoke metamethods.

lua_rawsetp

[-1, +0, e] 

void lua_rawsetp (lua_State *L, int index, const void *p);

Does the equivalent of t[k] = v, where t is the table at the given index, k is the pointer p represented as a light userdata, and v is the value at the top of the stack.

This function pops the value from the stack. The assignment is raw; that is, it does not invoke metamethods.

lua_Reader

typedef const char * (*lua_Reader) (lua_State *L,
                                    void *data,
                                    size_t *size);

The reader function used by lua_load. Every time it needs another piece of the chunk, lua_load calls the reader, passing along its data parameter. The reader must return a pointer to a block of memory with a new piece of the chunk and set size to the block size. The block must exist until the reader function is called again. To signal the end of the chunk, the reader must return NULL or set size to zero. The reader function may return pieces of any size greater than zero.

lua_register

[-0, +0, e] 

void lua_register (lua_State *L, const char *name, lua_CFunction f);

Sets the C function f as the new value of global name. It is defined as a macro: 

     #define lua_register(L,n,f) \
            (lua_pushcfunction(L, f), lua_setglobal(L, n))

lua_remove

[-1, +0, –] 

void lua_remove (lua_State *L, int index);

Removes the element at the given valid index, shifting down the elements above this index to fill the gap. This function cannot be called with a pseudo-index, because a pseudo-index is not an actual stack position.

lua_replace

[-1, +0, –] 

void lua_replace (lua_State *L, int index);

Moves the top element into the given valid index without shifting any element (therefore replacing the value at the given index), and then pops the top element.

lua_resume

[-?, +?, –] 

int lua_resume (lua_State *L, lua_State *from, int nargs);

Starts and resumes a coroutine in a given thread.

To start a coroutine, you push onto the thread stack the main function plus any arguments; then you call lua_resume, with nargs being the number of arguments. This call returns when the coroutine suspends or finishes its execution. When it returns, the stack contains all values passed to lua_yield, or all values returned by the body function. lua_resume returns LUA_YIELD if the coroutine yields, LUA_OK if the coroutine finishes its execution without errors, or an error code in case of errors (see lua_pcall).

In case of errors, the stack is not unwound, so you can use the debug API over it. The error message is on the top of the stack.

To resume a coroutine, you remove any results from the last lua_yield, put on its stack only the values to be passed as results from yield, and then call lua_resume.

The parameter from represents the coroutine that is resuming L. If there is no such coroutine, this parameter can be NULL.

lua_setallocf

[-0, +0, –] 

void lua_setallocf (lua_State *L, lua_Alloc f, void *ud);

Changes the allocator function of a given state to f with user data ud.

lua_setfield

[-1, +0, e] 

void lua_setfield (lua_State *L, int index, const char *k);

Does the equivalent to t[k] = v, where t is the value at the given index and v is the value at the top of the stack.

This function pops the value from the stack. As in Lua, this function may trigger a metamethod for the "newindex" event (see §2.4).

lua_setglobal

[-1, +0, e] 

void lua_setglobal (lua_State *L, const char *name);

Pops a value from the stack and sets it as the new value of global name.

lua_setmetatable

[-1, +0, –] 

void lua_setmetatable (lua_State *L, int index);

Pops a table from the stack and sets it as the new metatable for the value at the given index.

lua_settable

[-2, +0, e] 

void lua_settable (lua_State *L, int index);

Does the equivalent to t[k] = v, where t is the value at the given index, v is the value at the top of the stack, and k is the value just below the top.

This function pops both the key and the value from the stack. As in Lua, this function may trigger a metamethod for the "newindex" event (see §2.4).

lua_settop

[-?, +?, –] 

void lua_settop (lua_State *L, int index);

Accepts any index, or 0, and sets the stack top to this index. If the new top is larger than the old one, then the new elements are filled with nil. If index is 0, then all stack elements are removed.

lua_setuservalue

[-1, +0, –] 

void lua_setuservalue (lua_State *L, int index);

Pops a table or nil from the stack and sets it as the new value associated to the userdata at the given index.

lua_State

typedef struct lua_State lua_State;

An opaque structure that points to a thread and indirectly (through the thread) to the whole state of a Lua interpreter. The Lua library is fully reentrant: it has no global variables. All information about a state is accessible through this structure.

A pointer to this structure must be passed as the first argument to every function in the library, except to lua_newstate, which creates a Lua state from scratch.

lua_status

[-0, +0, –] 

int lua_status (lua_State *L);

Returns the status of the thread L.

The status can be 0 (LUA_OK) for a normal thread, an error code if the thread finished the execution of a lua_resume with an error, or LUA_YIELD if the thread is suspended.

You can only call functions in threads with status LUA_OK. You can resume threads with status LUA_OK (to start a new coroutine) or LUA_YIELD (to resume a coroutine).

lua_toboolean

[-0, +0, –] 

int lua_toboolean (lua_State *L, int index);

Converts the Lua value at the given index to a C boolean value (0 or 1). Like all tests in Lua, lua_toboolean returns true for any Lua value different from false and nil; otherwise it returns false. (If you want to accept only actual boolean values, use lua_isboolean to test the value's type.)

lua_tocfunction

[-0, +0, –] 

lua_CFunction lua_tocfunction (lua_State *L, int index);

Converts a value at the given index to a C function. That value must be a C function; otherwise, returns NULL.

lua_tointeger

[-0, +0, –] 

lua_Integer lua_tointeger (lua_State *L, int index);

Equivalent to lua_tointegerx with isnum equal to NULL.

lua_tointegerx

[-0, +0, –] 

lua_Integer lua_tointegerx (lua_State *L, int index, int *isnum);

Converts the Lua value at the given index to the signed integral type lua_Integer. The Lua value must be a number or a string convertible to a number (see §3.4.2); otherwise, lua_tointegerx returns 0.

If the number is not an integer, it is truncated in some non-specified way.

If isnum is not NULL, its referent is assigned a boolean value that indicates whether the operation succeeded.

lua_tolstring

[-0, +0, e] 

const char *lua_tolstring (lua_State *L, int index, size_t *len);

Converts the Lua value at the given index to a C string. If len is not NULL, it also sets *len with the string length. The Lua value must be a string or a number; otherwise, the function returns NULL. If the value is a number, then lua_tolstring also changes the actual value in the stack to a string. (This change confuses lua_next when lua_tolstring is applied to keys during a table traversal.)

lua_tolstring returns a fully aligned pointer to a string inside the Lua state. This string always has a zero ('\0') after its last character (as in C), but can contain other zeros in its body. Because Lua has garbage collection, there is no guarantee that the pointer returned by lua_tolstring will be valid after the corresponding value is removed from the stack.

lua_tonumber

[-0, +0, –] 

lua_Number lua_tonumber (lua_State *L, int index);

Equivalent to lua_tonumberx with isnum equal to NULL.

lua_tonumberx

[-0, +0, –] 

lua_Number lua_tonumberx (lua_State *L, int index, int *isnum);

Converts the Lua value at the given index to the C type lua_Number (see lua_Number). The Lua value must be a number or a string convertible to a number (see §3.4.2); otherwise, lua_tonumberx returns 0.

If isnum is not NULL, its referent is assigned a boolean value that indicates whether the operation succeeded.

lua_topointer

[-0, +0, –] 

const void *lua_topointer (lua_State *L, int index);

Converts the value at the given index to a generic C pointer (void*). The value can be a userdata, a table, a thread, or a function; otherwise, lua_topointer returns NULL. Different objects will give different pointers. There is no way to convert the pointer back to its original value.

Typically this function is used only for debug information.

lua_tostring

[-0, +0, e] 

const char *lua_tostring (lua_State *L, int index);

Equivalent to lua_tolstring with len equal to NULL.

lua_tothread

[-0, +0, –] 

lua_State *lua_tothread (lua_State *L, int index);

Converts the value at the given index to a Lua thread (represented as lua_State*). This value must be a thread; otherwise, the function returns NULL.

lua_tounsigned

[-0, +0, –] 

lua_Unsigned lua_tounsigned (lua_State *L, int index);

Equivalent to lua_tounsignedx with isnum equal to NULL.

lua_tounsignedx

[-0, +0, –] 

lua_Unsigned lua_tounsignedx (lua_State *L, int index, int *isnum);

Converts the Lua value at the given index to the unsigned integral type lua_Unsigned. The Lua value must be a number or a string convertible to a number (see §3.4.2); otherwise, lua_tounsignedx returns 0.

If the number is not an integer, it is truncated in some non-specified way. If the number is outside the range of representable values, it is normalized to the remainder of its division by one more than the maximum representable value.

If isnum is not NULL, its referent is assigned a boolean value that indicates whether the operation succeeded.

lua_touserdata

[-0, +0, –] 

void *lua_touserdata (lua_State *L, int index);

If the value at the given index is a full userdata, returns its block address. If the value is a light userdata, returns its pointer. Otherwise, returns NULL.

lua_type

[-0, +0, –] 

int lua_type (lua_State *L, int index);

Returns the type of the value in the given valid index, or LUA_TNONE for a non-valid (but acceptable) index. The types returned by lua_type are coded by the following constants defined in lua.h: LUA_TNIL, LUA_TNUMBER, LUA_TBOOLEAN, LUA_TSTRING, LUA_TTABLE, LUA_TFUNCTION, LUA_TUSERDATA, LUA_TTHREAD, and LUA_TLIGHTUSERDATA.

lua_typename

[-0, +0, –] 

const char *lua_typename (lua_State *L, int tp);

Returns the name of the type encoded by the value tp, which must be one the values returned by lua_type.

lua_Unsigned

typedef unsigned long lua_Unsigned;

The type used by the Lua API to represent unsigned integral values. It must have at least 32 bits.

By default it is an unsigned int or an unsigned long, whichever can hold 32-bit values.

lua_upvalueindex

[-0, +0, –] 

int lua_upvalueindex (int i);

Returns the pseudo-index that represents the i-th upvalue of the running function (see §4.4).

lua_version

[-0, +0, v] 

const lua_Number *lua_version (lua_State *L);

Returns the address of the version number stored in the Lua core. When called with a valid lua_State, returns the address of the version used to create that state. When called with NULL, returns the address of the version running the call.

lua_Writer

typedef int (*lua_Writer) (lua_State *L,
                           const void* p,
                           size_t sz,
                           void* ud);

The type of the writer function used by lua_dump. Every time it produces another piece of chunk, lua_dump calls the writer, passing along the buffer to be written (p), its size (sz), and the data parameter supplied to lua_dump.

The writer returns an error code: 0 means no errors; any other value means an error and stops lua_dump from calling the writer again.

lua_xmove

[-?, +?, –] 

void lua_xmove (lua_State *from, lua_State *to, int n);

Exchange values between different threads of the same state.

This function pops n values from the stack from, and pushes them onto the stack to.

lua_yield

[-?, +?, –] 

int lua_yield (lua_State *L, int nresults);

This function is equivalent to lua_yieldk, but it has no continuation (see §4.7). Therefore, when the thread resumes, it returns to the function that called the function calling lua_yield.

lua_yieldk

[-?, +?, –] 

int lua_yieldk (lua_State *L, int nresults, int ctx, lua_CFunction k);

Yields a coroutine.

This function should only be called as the return expression of a C function, as follows: 

     return lua_yieldk (L, n, i, k);

When a C function calls lua_yieldk in that way, the running coroutine suspends its execution, and the call to lua_resume that started this coroutine returns. The parameter nresults is the number of values from the stack that are passed as results to lua_resume.

When the coroutine is resumed again, Lua calls the given continuation function k to continue the execution of the C function that yielded (see §4.7). This continuation function receives the same stack from the previous function, with the results removed and replaced by the arguments passed to lua_resume. Moreover, the continuation function may access the value ctx by calling lua_getctx.

4.9 – The Debug Interface

Lua has no built-in debugging facilities. Instead, it offers a special interface by means of functions and hooks. This interface allows the construction of different kinds of debuggers, profilers, and other tools that need "inside information" from the interpreter.

lua_Debug

typedef struct lua_Debug {
  int event;
  const char *name;           /* (n) */
  const char *namewhat;       /* (n) */
  const char *what;           /* (S) */
  const char *source;         /* (S) */
  int currentline;            /* (l) */
  int linedefined;            /* (S) */
  int lastlinedefined;        /* (S) */
  unsigned char nups;         /* (u) number of upvalues */
  unsigned char nparams;      /* (u) number of parameters */
  char isvararg;              /* (u) */
  char istailcall;            /* (t) */
  char short_src[LUA_IDSIZE]; /* (S) */
  /* private part */
  other fields
} lua_Debug;

A structure used to carry different pieces of information about a function or an activation record. lua_getstack fills only the private part of this structure, for later use. To fill the other fields of lua_Debug with useful information, call lua_getinfo.

The fields of lua_Debug have the following meaning:

  • source: the source of the chunk that created the function. If source starts with a '@', it means that the function was defined in a file where the file name follows the '@'. If source starts with a '=', the remainder of its contents describe the source in a user-dependent manner. Otherwise, the function was defined in a string where source is that string.
  • short_src: a "printable" version of source, to be used in error messages.
  • linedefined: the line number where the definition of the function starts.
  • lastlinedefined: the line number where the definition of the function ends.
  • what: the string "Lua" if the function is a Lua function, "C" if it is a C function, "main" if it is the main part of a chunk.
  • currentline: the current line where the given function is executing. When no line information is available, currentline is set to -1.
  • name: a reasonable name for the given function. Because functions in Lua are first-class values, they do not have a fixed name: some functions can be the value of multiple global variables, while others can be stored only in a table field. The lua_getinfo function checks how the function was called to find a suitable name. If it cannot find a name, then name is set to NULL.
  • namewhat: explains the name field. The value of namewhat can be "global", "local", "method", "field", "upvalue", or "" (the empty string), according to how the function was called. (Lua uses the empty string when no other option seems to apply.)
  • istailcall: true if this function invocation was called by a tail call. In this case, the caller of this level is not in the stack.
  • nups: the number of upvalues of the function.
  • nparams: the number of fixed parameters of the function (always 0 for C functions).
  • isvararg: true if the function is a vararg function (always true for C functions).

lua_gethook

[-0, +0, –] 

lua_Hook lua_gethook (lua_State *L);

Returns the current hook function.

lua_gethookcount

[-0, +0, –] 

int lua_gethookcount (lua_State *L);

Returns the current hook count.

lua_gethookmask

[-0, +0, –] 

int lua_gethookmask (lua_State *L);

Returns the current hook mask.

lua_getinfo

[-(0|1), +(0|1|2), e] 

int lua_getinfo (lua_State *L, const char *what, lua_Debug *ar);

Gets information about a specific function or function invocation.

To get information about a function invocation, the parameter ar must be a valid activation record that was filled by a previous call to lua_getstack or given as argument to a hook (see lua_Hook).

To get information about a function you push it onto the stack and start the what string with the character '>'. (In that case, lua_getinfo pops the function from the top of the stack.) For instance, to know in which line a function f was defined, you can write the following code: 

     lua_Debug ar;
     lua_getglobal(L, "f");  /* get global 'f' */
     lua_getinfo(L, ">S", &ar);
     printf("%d\n", ar.linedefined);

Each character in the string what selects some fields of the structure ar to be filled or a value to be pushed on the stack:

  • 'n': fills in the field name and namewhat;
  • 'S': fills in the fields source, short_src, linedefined, lastlinedefined, and what;
  • 'l': fills in the field currentline;
  • 't': fills in the field istailcall;
  • 'u': fills in the fields nups, nparams, and isvararg;
  • 'f': pushes onto the stack the function that is running at the given level;
  • 'L': pushes onto the stack a table whose indices are the numbers of the lines that are valid on the function. (A valid line is a line with some associated code, that is, a line where you can put a break point. Non-valid lines include empty lines and comments.)

This function returns 0 on error (for instance, an invalid option in what).

lua_getlocal

[-0, +(0|1), –] 

const char *lua_getlocal (lua_State *L, lua_Debug *ar, int n);

Gets information about a local variable of a given activation record or a given function.

In the first case, the parameter ar must be a valid activation record that was filled by a previous call to lua_getstack or given as argument to a hook (see lua_Hook). The index n selects which local variable to inspect; see debug.getlocal for details about variable indices and names.

lua_getlocal pushes the variable's value onto the stack and returns its name.

In the second case, ar should be NULL and the function to be inspected must be at the top of the stack. In this case, only parameters of Lua functions are visible (as there is no information about what variables are active) and no values are pushed onto the stack.

Returns NULL (and pushes nothing) when the index is greater than the number of active local variables.

lua_getstack

[-0, +0, –] 

int lua_getstack (lua_State *L, int level, lua_Debug *ar);

Gets information about the interpreter runtime stack.

This function fills parts of a lua_Debug structure with an identification of the activation record of the function executing at a given level. Level 0 is the current running function, whereas level n+1 is the function that has called level n (except for tail calls, which do not count on the stack). When there are no errors, lua_getstack returns 1; when called with a level greater than the stack depth, it returns 0.

lua_getupvalue

[-0, +(0|1), –] 

const char *lua_getupvalue (lua_State *L, int funcindex, int n);

Gets information about a closure's upvalue. (For Lua functions, upvalues are the external local variables that the function uses, and that are consequently included in its closure.) lua_getupvalue gets the index n of an upvalue, pushes the upvalue's value onto the stack, and returns its name. funcindex points to the closure in the stack. (Upvalues have no particular order, as they are active through the whole function. So, they are numbered in an arbitrary order.)

Returns NULL (and pushes nothing) when the index is greater than the number of upvalues. For C functions, this function uses the empty string "" as a name for all upvalues.

lua_Hook

typedef void (*lua_Hook) (lua_State *L, lua_Debug *ar);

Type for debugging hook functions.

Whenever a hook is called, its ar argument has its field event set to the specific event that triggered the hook. Lua identifies these events with the following constants: LUA_HOOKCALL, LUA_HOOKRET, LUA_HOOKTAILCALL, LUA_HOOKLINE, and LUA_HOOKCOUNT. Moreover, for line events, the field currentline is also set. To get the value of any other field in ar, the hook must call lua_getinfo.

For call events, event can be LUA_HOOKCALL, the normal value, or LUA_HOOKTAILCALL, for a tail call; in this case, there will be no corresponding return event.

While Lua is running a hook, it disables other calls to hooks. Therefore, if a hook calls back Lua to execute a function or a chunk, this execution occurs without any calls to hooks.

Hook functions cannot have continuations, that is, they cannot call lua_yieldk, lua_pcallk, or lua_callk with a non-null k.

Hook functions can yield under the following conditions: Only count and line events can yield and they cannot yield any value; to yield a hook function must finish its execution calling lua_yield with nresults equal to zero.

lua_sethook

[-0, +0, –] 

int lua_sethook (lua_State *L, lua_Hook f, int mask, int count);

Sets the debugging hook function.

Argument f is the hook function. mask specifies on which events the hook will be called: it is formed by a bitwise or of the constants LUA_MASKCALL, LUA_MASKRET, LUA_MASKLINE, and LUA_MASKCOUNT. The count argument is only meaningful when the mask includes LUA_MASKCOUNT. For each event, the hook is called as explained below:

  • The call hook: is called when the interpreter calls a function. The hook is called just after Lua enters the new function, before the function gets its arguments.
  • The return hook: is called when the interpreter returns from a function. The hook is called just before Lua leaves the function. There is no standard way to access the values to be returned by the function.
  • The line hook: is called when the interpreter is about to start the execution of a new line of code, or when it jumps back in the code (even to the same line). (This event only happens while Lua is executing a Lua function.)
  • The count hook: is called after the interpreter executes every count instructions. (This event only happens while Lua is executing a Lua function.)

A hook is disabled by setting mask to zero.

lua_setlocal

[-(0|1), +0, –] 

const char *lua_setlocal (lua_State *L, lua_Debug *ar, int n);

Sets the value of a local variable of a given activation record. Parameters ar and n are as in lua_getlocal (see lua_getlocal). lua_setlocal assigns the value at the top of the stack to the variable and returns its name. It also pops the value from the stack.

Returns NULL (and pops nothing) when the index is greater than the number of active local variables.

lua_setupvalue

[-(0|1), +0, –] 

const char *lua_setupvalue (lua_State *L, int funcindex, int n);

Sets the value of a closure's upvalue. It assigns the value at the top of the stack to the upvalue and returns its name. It also pops the value from the stack. Parameters funcindex and n are as in the lua_getupvalue (see lua_getupvalue).

Returns NULL (and pops nothing) when the index is greater than the number of upvalues.

lua_upvalueid

[-0, +0, –] 

void *lua_upvalueid (lua_State *L, int funcindex, int n);

Returns an unique identifier for the upvalue numbered n from the closure at index funcindex. Parameters funcindex and n are as in the lua_getupvalue (see lua_getupvalue) (but n cannot be greater than the number of upvalues).

These unique identifiers allow a program to check whether different closures share upvalues. Lua closures that share an upvalue (that is, that access a same external local variable) will return identical ids for those upvalue indices.

lua_upvaluejoin

[-0, +0, –] 

void lua_upvaluejoin (lua_State *L, int funcindex1, int n1,
                                    int funcindex2, int n2);

Make the n1-th upvalue of the Lua closure at index funcindex1 refer to the n2-th upvalue of the Lua closure at index funcindex2.

5 – The Auxiliary Library

The auxiliary library provides several convenient functions to interface C with Lua. While the basic API provides the primitive functions for all interactions between C and Lua, the auxiliary library provides higher-level functions for some common tasks.

All functions and types from the auxiliary library are defined in header file lauxlib.h and have a prefix luaL_.

All functions in the auxiliary library are built on top of the basic API, and so they provide nothing that cannot be done with that API. Nevertheless, the use of the auxiliary library ensures more consistency to your code.

Several functions in the auxiliary library use internally some extra stack slots. When a function in the auxiliary library uses less than five slots, it does not check the stack size; it simply assumes that there are enough slots.

Several functions in the auxiliary library are used to check C function arguments. Because the error message is formatted for arguments (e.g., "bad argument #1"), you should not use these functions for other stack values.

Functions called luaL_check* always throw an error if the check is not satisfied.

5.1 – Functions and Types

Here we list all functions and types from the auxiliary library in alphabetical order.

luaL_addchar

[-?, +?, e] 

void luaL_addchar (luaL_Buffer *B, char c);

Adds the byte c to the buffer B (see luaL_Buffer).

luaL_addlstring

[-?, +?, e] 

void luaL_addlstring (luaL_Buffer *B, const char *s, size_t l);

Adds the string pointed to by s with length l to the buffer B (see luaL_Buffer). The string can contain embedded zeros.

luaL_addsize

[-?, +?, e] 

void luaL_addsize (luaL_Buffer *B, size_t n);

Adds to the buffer B (see luaL_Buffer) a string of length n previously copied to the buffer area (see luaL_prepbuffer).

luaL_addstring

[-?, +?, e] 

void luaL_addstring (luaL_Buffer *B, const char *s);

Adds the zero-terminated string pointed to by s to the buffer B (see luaL_Buffer). The string cannot contain embedded zeros.

luaL_addvalue

[-1, +?, e] 

void luaL_addvalue (luaL_Buffer *B);

Adds the value at the top of the stack to the buffer B (see luaL_Buffer). Pops the value.

This is the only function on string buffers that can (and must) be called with an extra element on the stack, which is the value to be added to the buffer.

luaL_argcheck

[-0, +0, v] 

void luaL_argcheck (lua_State *L,
                    int cond,
                    int arg,
                    const char *extramsg);

Checks whether cond is true. If not, raises an error with a standard message.

luaL_argerror

[-0, +0, v] 

int luaL_argerror (lua_State *L, int arg, const char *extramsg);

Raises an error with a standard message that includes extramsg as a comment.

This function never returns, but it is an idiom to use it in C functions as return luaL_argerror(args).

luaL_Buffer

typedef struct luaL_Buffer luaL_Buffer;

Type for a string buffer.

A string buffer allows C code to build Lua strings piecemeal. Its pattern of use is as follows:

  • First declare a variable b of type luaL_Buffer.
  • Then initialize it with a call luaL_buffinit(L, &b).
  • Then add string pieces to the buffer calling any of the luaL_add* functions.
  • Finish by calling luaL_pushresult(&b). This call leaves the final string on the top of the stack.

If you know beforehand the total size of the resulting string, you can use the buffer like this:

  • First declare a variable b of type luaL_Buffer.
  • Then initialize it and preallocate a space of size sz with a call luaL_buffinitsize(L, &b, sz).
  • Then copy the string into that space.
  • Finish by calling luaL_pushresultsize(&b, sz), where sz is the total size of the resulting string copied into that space.

During its normal operation, a string buffer uses a variable number of stack slots. So, while using a buffer, you cannot assume that you know where the top of the stack is. You can use the stack between successive calls to buffer operations as long as that use is balanced; that is, when you call a buffer operation, the stack is at the same level it was immediately after the previous buffer operation. (The only exception to this rule is luaL_addvalue.) After calling luaL_pushresult the stack is back to its level when the buffer was initialized, plus the final string on its top.

luaL_buffinit

[-0, +0, –] 

void luaL_buffinit (lua_State *L, luaL_Buffer *B);

Initializes a buffer B. This function does not allocate any space; the buffer must be declared as a variable (see luaL_Buffer).

luaL_buffinitsize

[-?, +?, e] 

char *luaL_buffinitsize (lua_State *L, luaL_Buffer *B, size_t sz);

Equivalent to the sequence luaL_buffinit, luaL_prepbuffsize.

luaL_callmeta

[-0, +(0|1), e] 

int luaL_callmeta (lua_State *L, int obj, const char *e);

Calls a metamethod.

If the object at index obj has a metatable and this metatable has a field e, this function calls this field passing the object as its only argument. In this case this function returns true and pushes onto the stack the value returned by the call. If there is no metatable or no metamethod, this function returns false (without pushing any value on the stack).

luaL_checkany

[-0, +0, v] 

void luaL_checkany (lua_State *L, int arg);

Checks whether the function has an argument of any type (including nil) at position arg.

luaL_checkint

[-0, +0, v] 

int luaL_checkint (lua_State *L, int arg);

Checks whether the function argument arg is a number and returns this number cast to an int.

luaL_checkinteger

[-0, +0, v] 

lua_Integer luaL_checkinteger (lua_State *L, int arg);

Checks whether the function argument arg is a number and returns this number cast to a lua_Integer.

luaL_checklong

[-0, +0, v] 

long luaL_checklong (lua_State *L, int arg);

Checks whether the function argument arg is a number and returns this number cast to a long.

luaL_checklstring

[-0, +0, v] 

const char *luaL_checklstring (lua_State *L, int arg, size_t *l);

Checks whether the function argument arg is a string and returns this string; if l is not NULL fills *l with the string's length.

This function uses lua_tolstring to get its result, so all conversions and caveats of that function apply here.

luaL_checknumber

[-0, +0, v] 

lua_Number luaL_checknumber (lua_State *L, int arg);

Checks whether the function argument arg is a number and returns this number.

luaL_checkoption

[-0, +0, v] 

int luaL_checkoption (lua_State *L,
                      int arg,
                      const char *def,
                      const char *const lst[]);

Checks whether the function argument arg is a string and searches for this string in the array lst (which must be NULL-terminated). Returns the index in the array where the string was found. Raises an error if the argument is not a string or if the string cannot be found.

If def is not NULL, the function uses def as a default value when there is no argument arg or when this argument is nil.

This is a useful function for mapping strings to C enums. (The usual convention in Lua libraries is to use strings instead of numbers to select options.)

luaL_checkstack

[-0, +0, v] 

void luaL_checkstack (lua_State *L, int sz, const char *msg);

Grows the stack size to top + sz elements, raising an error if the stack cannot grow to that size. msg is an additional text to go into the error message (or NULL for no additional text).

luaL_checkstring

[-0, +0, v] 

const char *luaL_checkstring (lua_State *L, int arg);

Checks whether the function argument arg is a string and returns this string.

This function uses lua_tolstring to get its result, so all conversions and caveats of that function apply here.

luaL_checktype

[-0, +0, v] 

void luaL_checktype (lua_State *L, int arg, int t);

Checks whether the function argument arg has type t. See lua_type for the encoding of types for t.

luaL_checkudata

[-0, +0, v] 

void *luaL_checkudata (lua_State *L, int arg, const char *tname);

Checks whether the function argument arg is a userdata of the type tname (see luaL_newmetatable) and returns the userdata address (see lua_touserdata).

luaL_checkunsigned

[-0, +0, v] 

lua_Unsigned luaL_checkunsigned (lua_State *L, int arg);

Checks whether the function argument arg is a number and returns this number cast to a lua_Unsigned.

luaL_checkversion

[-0, +0, –] 

void luaL_checkversion (lua_State *L);

Checks whether the core running the call, the core that created the Lua state, and the code making the call are all using the same version of Lua. Also checks whether the core running the call and the core that created the Lua state are using the same address space.

luaL_dofile

[-0, +?, e] 

int luaL_dofile (lua_State *L, const char *filename);

Loads and runs the given file. It is defined as the following macro: 

     (luaL_loadfile(L, filename) || lua_pcall(L, 0, LUA_MULTRET, 0))

It returns false if there are no errors or true in case of errors.

luaL_dostring

[-0, +?, –] 

int luaL_dostring (lua_State *L, const char *str);

Loads and runs the given string. It is defined as the following macro: 

     (luaL_loadstring(L, str) || lua_pcall(L, 0, LUA_MULTRET, 0))

It returns false if there are no errors or true in case of errors.

luaL_error

[-0, +0, v] 

int luaL_error (lua_State *L, const char *fmt, ...);

Raises an error. The error message format is given by fmt plus any extra arguments, following the same rules of lua_pushfstring. It also adds at the beginning of the message the file name and the line number where the error occurred, if this information is available.

This function never returns, but it is an idiom to use it in C functions as return luaL_error(args).

luaL_execresult

[-0, +3, e] 

int luaL_execresult (lua_State *L, int stat);

This function produces the return values for process-related functions in the standard library (os.execute and io.close).

luaL_fileresult

[-0, +(1|3), e] 

int luaL_fileresult (lua_State *L, int stat, const char *fname);

This function produces the return values for file-related functions in the standard library (io.open, os.rename, file:seek, etc.).

luaL_getmetafield

[-0, +(0|1), e] 

int luaL_getmetafield (lua_State *L, int obj, const char *e);

Pushes onto the stack the field e from the metatable of the object at index obj. If the object does not have a metatable, or if the metatable does not have this field, returns false and pushes nothing.

luaL_getmetatable

[-0, +1, –] 

void luaL_getmetatable (lua_State *L, const char *tname);

Pushes onto the stack the metatable associated with name tname in the registry (see luaL_newmetatable).

luaL_getsubtable

[-0, +1, e] 

int luaL_getsubtable (lua_State *L, int idx, const char *fname);

Ensures that the value t[fname], where t is the value at index idx, is a table, and pushes that table onto the stack. Returns true if it finds a previous table there and false if it creates a new table.

luaL_gsub

[-0, +1, e] 

const char *luaL_gsub (lua_State *L,
                       const char *s,
                       const char *p,
                       const char *r);

Creates a copy of string s by replacing any occurrence of the string p with the string r. Pushes the resulting string on the stack and returns it.

luaL_len

[-0, +0, e] 

int luaL_len (lua_State *L, int index);

Returns the "length" of the value at the given index as a number; it is equivalent to the '#' operator in Lua (see §3.4.6). Raises an error if the result of the operation is not a number. (This case only can happen through metamethods.)

luaL_loadbuffer

[-0, +1, –] 

int luaL_loadbuffer (lua_State *L,
                     const char *buff,
                     size_t sz,
                     const char *name);

Equivalent to luaL_loadbufferx with mode equal to NULL.

luaL_loadbufferx

[-0, +1, –] 

int luaL_loadbufferx (lua_State *L,
                      const char *buff,
                      size_t sz,
                      const char *name,
                      const char *mode);

Loads a buffer as a Lua chunk. This function uses lua_load to load the chunk in the buffer pointed to by buff with size sz.

This function returns the same results as lua_load. name is the chunk name, used for debug information and error messages. The string mode works as in function lua_load.

luaL_loadfile

[-0, +1, e] 

int luaL_loadfile (lua_State *L, const char *filename);

Equivalent to luaL_loadfilex with mode equal to NULL.

luaL_loadfilex

[-0, +1, e] 

int luaL_loadfilex (lua_State *L, const char *filename,
                                            const char *mode);

Loads a file as a Lua chunk. This function uses lua_load to load the chunk in the file named filename. If filename is NULL, then it loads from the standard input. The first line in the file is ignored if it starts with a #.

The string mode works as in function lua_load.

This function returns the same results as lua_load, but it has an extra error code LUA_ERRFILE if it cannot open/read the file or the file has a wrong mode.

As lua_load, this function only loads the chunk; it does not run it.

luaL_loadstring

[-0, +1, –] 

int luaL_loadstring (lua_State *L, const char *s);

Loads a string as a Lua chunk. This function uses lua_load to load the chunk in the zero-terminated string s.

This function returns the same results as lua_load.

Also as lua_load, this function only loads the chunk; it does not run it.

luaL_newlib

[-0, +1, e] 

void luaL_newlib (lua_State *L, const luaL_Reg *l);

Creates a new table and registers there the functions in list l. It is implemented as the following macro: 

     (luaL_newlibtable(L,l), luaL_setfuncs(L,l,0))

luaL_newlibtable

[-0, +1, e] 

void luaL_newlibtable (lua_State *L, const luaL_Reg l[]);

Creates a new table with a size optimized to store all entries in the array l (but does not actually store them). It is intended to be used in conjunction with luaL_setfuncs (see luaL_newlib).

It is implemented as a macro. The array l must be the actual array, not a pointer to it.

luaL_newmetatable

[-0, +1, e] 

int luaL_newmetatable (lua_State *L, const char *tname);

If the registry already has the key tname, returns 0. Otherwise, creates a new table to be used as a metatable for userdata, adds it to the registry with key tname, and returns 1.

In both cases pushes onto the stack the final value associated with tname in the registry.

luaL_newstate

[-0, +0, –] 

lua_State *luaL_newstate (void);

Creates a new Lua state. It calls lua_newstate with an allocator based on the standard C realloc function and then sets a panic function (see §4.6) that prints an error message to the standard error output in case of fatal errors.

Returns the new state, or NULL if there is a memory allocation error.

luaL_openlibs

[-0, +0, e] 

void luaL_openlibs (lua_State *L);

Opens all standard Lua libraries into the given state.

luaL_optint

[-0, +0, v] 

int luaL_optint (lua_State *L, int arg, int d);

If the function argument arg is a number, returns this number cast to an int. If this argument is absent or is nil, returns d. Otherwise, raises an error.

luaL_optinteger

[-0, +0, v] 

lua_Integer luaL_optinteger (lua_State *L,
                             int arg,
                             lua_Integer d);

If the function argument arg is a number, returns this number cast to a lua_Integer. If this argument is absent or is nil, returns d. Otherwise, raises an error.

luaL_optlong

[-0, +0, v] 

long luaL_optlong (lua_State *L, int arg, long d);

If the function argument arg is a number, returns this number cast to a long. If this argument is absent or is nil, returns d. Otherwise, raises an error.

luaL_optlstring

[-0, +0, v] 

const char *luaL_optlstring (lua_State *L,
                             int arg,
                             const char *d,
                             size_t *l);

If the function argument arg is a string, returns this string. If this argument is absent or is nil, returns d. Otherwise, raises an error.

If l is not NULL, fills the position *l with the result's length.

luaL_optnumber

[-0, +0, v] 

lua_Number luaL_optnumber (lua_State *L, int arg, lua_Number d);

If the function argument arg is a number, returns this number. If this argument is absent or is nil, returns d. Otherwise, raises an error.

luaL_optstring

[-0, +0, v] 

const char *luaL_optstring (lua_State *L,
                            int arg,
                            const char *d);

If the function argument arg is a string, returns this string. If this argument is absent or is nil, returns d. Otherwise, raises an error.

luaL_optunsigned

[-0, +0, v] 

lua_Unsigned luaL_optunsigned (lua_State *L,
                               int arg,
                               lua_Unsigned u);

If the function argument arg is a number, returns this number cast to a lua_Unsigned. If this argument is absent or is nil, returns u. Otherwise, raises an error.

luaL_prepbuffer

[-?, +?, e] 

char *luaL_prepbuffer (luaL_Buffer *B);

Equivalent to luaL_prepbuffsize with the predefined size LUAL_BUFFERSIZE.

luaL_prepbuffsize

[-?, +?, e] 

char *luaL_prepbuffsize (luaL_Buffer *B, size_t sz);

Returns an address to a space of size sz where you can copy a string to be added to buffer B (see luaL_Buffer). After copying the string into this space you must call luaL_addsize with the size of the string to actually add it to the buffer.

luaL_pushresult

[-?, +1, e] 

void luaL_pushresult (luaL_Buffer *B);

Finishes the use of buffer B leaving the final string on the top of the stack.

luaL_pushresultsize

[-?, +1, e] 

void luaL_pushresultsize (luaL_Buffer *B, size_t sz);

Equivalent to the sequence luaL_addsize, luaL_pushresult.

luaL_ref

[-1, +0, e] 

int luaL_ref (lua_State *L, int t);

Creates and returns a reference, in the table at index t, for the object at the top of the stack (and pops the object).

A reference is a unique integer key. As long as you do not manually add integer keys into table t, luaL_ref ensures the uniqueness of the key it returns. You can retrieve an object referred by reference r by calling lua_rawgeti(L, t, r). Function luaL_unref frees a reference and its associated object.

If the object at the top of the stack is nil, luaL_ref returns the constant LUA_REFNIL. The constant LUA_NOREF is guaranteed to be different from any reference returned by luaL_ref.

luaL_Reg

typedef struct luaL_Reg {
  const char *name;
  lua_CFunction func;
} luaL_Reg;

Type for arrays of functions to be registered by luaL_setfuncs. name is the function name and func is a pointer to the function. Any array of luaL_Reg must end with an sentinel entry in which both name and func are NULL.

luaL_requiref

[-0, +1, e] 

void luaL_requiref (lua_State *L, const char *modname,
                    lua_CFunction openf, int glb);

Calls function openf with string modname as an argument and sets the call result in package.loaded[modname], as if that function has been called through require.

If glb is true, also stores the result into global modname.

Leaves a copy of that result on the stack.

luaL_setfuncs

[-nup, +0, e] 

void luaL_setfuncs (lua_State *L, const luaL_Reg *l, int nup);

Registers all functions in the array l (see luaL_Reg) into the table on the top of the stack (below optional upvalues, see next).

When nup is not zero, all functions are created sharing nup upvalues, which must be previously pushed on the stack on top of the library table. These values are popped from the stack after the registration.

luaL_setmetatable

[-0, +0, –] 

void luaL_setmetatable (lua_State *L, const char *tname);

Sets the metatable of the object at the top of the stack as the metatable associated with name tname in the registry (see luaL_newmetatable).

luaL_testudata

[-0, +0, e] 

void *luaL_testudata (lua_State *L, int arg, const char *tname);

This function works like luaL_checkudata, except that, when the test fails, it returns NULL instead of throwing an error.

luaL_tolstring

[-0, +1, e] 

const char *luaL_tolstring (lua_State *L, int idx, size_t *len);

Converts any Lua value at the given index to a C string in a reasonable format. The resulting string is pushed onto the stack and also returned by the function. If len is not NULL, the function also sets *len with the string length.

If the value has a metatable with a "__tostring" field, then luaL_tolstring calls the corresponding metamethod with the value as argument, and uses the result of the call as its result.

luaL_traceback

[-0, +1, e] 

void luaL_traceback (lua_State *L, lua_State *L1, const char *msg,
                     int level);

Creates and pushes a traceback of the stack L1. If msg is not NULL it is appended at the beginning of the traceback. The level parameter tells at which level to start the traceback.

luaL_typename

[-0, +0, –] 

const char *luaL_typename (lua_State *L, int index);

Returns the name of the type of the value at the given index.

luaL_unref

[-0, +0, –] 

void luaL_unref (lua_State *L, int t, int ref);

Releases reference ref from the table at index t (see luaL_ref). The entry is removed from the table, so that the referred object can be collected. The reference ref is also freed to be used again.

If ref is LUA_NOREF or LUA_REFNIL, luaL_unref does nothing.

luaL_where

[-0, +1, e] 

void luaL_where (lua_State *L, int lvl);

Pushes onto the stack a string identifying the current position of the control at level lvl in the call stack. Typically this string has the following format: 

     chunkname:currentline:

Level 0 is the running function, level 1 is the function that called the running function, etc.

This function is used to build a prefix for error messages.

6 – Standard Libraries

The standard Lua libraries provide useful functions that are implemented directly through the C API. Some of these functions provide essential services to the language (e.g., type and getmetatable); others provide access to "outside" services (e.g., I/O); and others could be implemented in Lua itself, but are quite useful or have critical performance requirements that deserve an implementation in C (e.g., table.sort).

All libraries are implemented through the official C API and are provided as separate C modules. Currently, Lua has the following standard libraries:

  • basic library (§6.1);
  • coroutine library (§6.2);
  • package library (§6.3);
  • string manipulation (§6.4);
  • table manipulation (§6.5);
  • mathematical functions (§6.6) (sin, log, etc.);
  • bitwise operations (§6.7);
  • input and output (§6.8);
  • operating system facilities (§6.9);
  • debug facilities (§6.10).

Except for the basic and the package libraries, each library provides all its functions as fields of a global table or as methods of its objects.

To have access to these libraries, the C host program should call the luaL_openlibs function, which opens all standard libraries. Alternatively, the host program can open them individually by using luaL_requiref to call luaopen_base (for the basic library), luaopen_package (for the package library), luaopen_coroutine (for the coroutine library), luaopen_string (for the string library), luaopen_table (for the table library), luaopen_math (for the mathematical library), luaopen_bit32 (for the bit library), luaopen_io (for the I/O library), luaopen_os (for the Operating System library), and luaopen_debug (for the debug library). These functions are declared in lualib.h.

6.1 – Basic Functions

The basic library provides core functions to Lua. If you do not include this library in your application, you should check carefully whether you need to provide implementations for some of its facilities.

assert (v [, message])

Issues an error when the value of its argument v is false (i.e., nil or false); otherwise, returns all its arguments. message is an error message; when absent, it defaults to "assertion failed!"

collectgarbage ([opt [, arg]])

This function is a generic interface to the garbage collector. It performs different functions according to its first argument, opt:

  • "collect": performs a full garbage-collection cycle. This is the default option.
  • "stop": stops automatic execution of the garbage collector. The collector will run only when explicitly invoked, until a call to restart it.
  • "restart": restarts automatic execution of the garbage collector.
  • "count": returns the total memory in use by Lua (in Kbytes) and a second value with the total memory in bytes modulo 1024. The first value has a fractional part, so the following equality is always true: 
         k, b = collectgarbage("count")
     assert(k*1024 == math.floor(k)*1024 + b)

    (The second result is useful when Lua is compiled with a non floating-point type for numbers.)

  • "step": performs a garbage-collection step. The step "size" is controlled by arg (larger values mean more steps) in a non-specified way. If you want to control the step size you must experimentally tune the value of arg. Returns true if the step finished a collection cycle.
  • "setpause": sets arg as the new value for the pause of the collector (see §2.5). Returns the previous value for pause.
  • "setstepmul": sets arg as the new value for the step multiplier of the collector (see §2.5). Returns the previous value for step.
  • "isrunning": returns a boolean that tells whether the collector is running (i.e., not stopped).
  • "generational": changes the collector to generational mode. This is an experimental feature (see §2.5).
  • "incremental": changes the collector to incremental mode. This is the default mode.

dofile ([filename])

Opens the named file and executes its contents as a Lua chunk. When called without arguments, dofile executes the contents of the standard input (stdin). Returns all values returned by the chunk. In case of errors, dofile propagates the error to its caller (that is, dofile does not run in protected mode).

error (message [, level])

Terminates the last protected function called and returns message as the error message. Function error never returns.

Usually, error adds some information about the error position at the beginning of the message, if the message is a string. The level argument specifies how to get the error position. With level 1 (the default), the error position is where the error function was called. Level 2 points the error to where the function that called error was called; and so on. Passing a level 0 avoids the addition of error position information to the message.

_G

A global variable (not a function) that holds the global environment (see §2.2). Lua itself does not use this variable; changing its value does not affect any environment, nor vice-versa.

getmetatable (object)

If object does not have a metatable, returns nil. Otherwise, if the object's metatable has a "__metatable" field, returns the associated value. Otherwise, returns the metatable of the given object.

ipairs (t)

If t has a metamethod __ipairs, calls it with t as argument and returns the first three results from the call.

Otherwise, returns three values: an iterator function, the table t, and 0, so that the construction 

     for i,v in ipairs(t) do body end

will iterate over the pairs (1,t[1]), (2,t[2]), ..., up to the first integer key absent from the table.

load (ld [, source [, mode [, env]]])

Loads a chunk.

If ld is a string, the chunk is this string. If ld is a function, load calls it repeatedly to get the chunk pieces. Each call to ld must return a string that concatenates with previous results. A return of an empty string, nil, or no value signals the end of the chunk.

If there are no syntactic errors, returns the compiled chunk as a function; otherwise, returns nil plus the error message.

If the resulting function has upvalues, the first upvalue is set to the value of env, if that parameter is given, or to the value of the global environment. (When you load a main chunk, the resulting function will always have exactly one upvalue, the _ENV variable (see §2.2). When you load a binary chunk created from a function (see string.dump), the resulting function can have arbitrary upvalues.)

source is used as the source of the chunk for error messages and debug information (see §4.9). When absent, it defaults to ld, if ld is a string, or to "=(load)" otherwise.

The string mode controls whether the chunk can be text or binary (that is, a precompiled chunk). It may be the string "b" (only binary chunks), "t" (only text chunks), or "bt" (both binary and text). The default is "bt".

loadfile ([filename [, mode [, env]]])

Similar to load, but gets the chunk from file filename or from the standard input, if no file name is given.

next (table [, index])

Allows a program to traverse all fields of a table. Its first argument is a table and its second argument is an index in this table. next returns the next index of the table and its associated value. When called with nil as its second argument, next returns an initial index and its associated value. When called with the last index, or with nil in an empty table, next returns nil. If the second argument is absent, then it is interpreted as nil. In particular, you can use next(t) to check whether a table is empty.

The order in which the indices are enumerated is not specified, even for numeric indices. (To traverse a table in numeric order, use a numerical for.)

The behavior of next is undefined if, during the traversal, you assign any value to a non-existent field in the table. You may however modify existing fields. In particular, you may clear existing fields.

pairs (t)

If t has a metamethod __pairs, calls it with t as argument and returns the first three results from the call.

Otherwise, returns three values: the next function, the table t, and nil, so that the construction 

     for k,v in pairs(t) do body end

will iterate over all key–value pairs of table t.

See function next for the caveats of modifying the table during its traversal.

pcall (f [, arg1, ···])

Calls function f with the given arguments in protected mode. This means that any error inside f is not propagated; instead, pcall catches the error and returns a status code. Its first result is the status code (a boolean), which is true if the call succeeds without errors. In such case, pcall also returns all results from the call, after this first result. In case of any error, pcall returns false plus the error message.

print (···)

Receives any number of arguments and prints their values to stdout, using the tostring function to convert each argument to a string. print is not intended for formatted output, but only as a quick way to show a value, for instance for debugging. For complete control over the output, use string.format and io.write.

rawequal (v1, v2)

Checks whether v1 is equal to v2, without invoking any metamethod. Returns a boolean.

rawget (table, index)

Gets the real value of table[index], without invoking any metamethod. table must be a table; index may be any value.

rawlen (v)

Returns the length of the object v, which must be a table or a string, without invoking any metamethod. Returns an integer number.

rawset (table, index, value)

Sets the real value of table[index] to value, without invoking any metamethod. table must be a table, index any value different from nil and NaN, and value any Lua value.

This function returns table.

select (index, ···)

If index is a number, returns all arguments after argument number index; a negative number indexes from the end (-1 is the last argument). Otherwise, index must be the string "#", and select returns the total number of extra arguments it received.

setmetatable (table, metatable)

Sets the metatable for the given table. (You cannot change the metatable of other types from Lua, only from C.) If metatable is nil, removes the metatable of the given table. If the original metatable has a "__metatable" field, raises an error.

This function returns table.

tonumber (e [, base])

When called with no base, tonumber tries to convert its argument to a number. If the argument is already a number or a string convertible to a number (see §3.4.2), then tonumber returns this number; otherwise, it returns nil.

When called with base, then e should be a string to be interpreted as an integer numeral in that base. The base may be any integer between 2 and 36, inclusive. In bases above 10, the letter 'A' (in either upper or lower case) represents 10, 'B' represents 11, and so forth, with 'Z' representing 35. If the string e is not a valid numeral in the given base, the function returns nil.

tostring (v)

Receives a value of any type and converts it to a string in a reasonable format. (For complete control of how numbers are converted, use string.format.)

If the metatable of v has a "__tostring" field, then tostring calls the corresponding value with v as argument, and uses the result of the call as its result.

type (v)

Returns the type of its only argument, coded as a string. The possible results of this function are "nil" (a string, not the value nil), "number", "string", "boolean", "table", "function", "thread", and "userdata".

_VERSION

A global variable (not a function) that holds a string containing the current interpreter version. The current contents of this variable is "Lua 5.2".

xpcall (f, msgh [, arg1, ···])

This function is similar to pcall, except that it sets a new message handler msgh.

6.2 – Coroutine Manipulation

The operations related to coroutines comprise a sub-library of the basic library and come inside the table coroutine. See §2.6 for a general description of coroutines.

coroutine.create (f)

Creates a new coroutine, with body f. f must be a Lua function. Returns this new coroutine, an object with type "thread".

coroutine.resume (co [, val1, ···])

Starts or continues the execution of coroutine co. The first time you resume a coroutine, it starts running its body. The values val1, ... are passed as the arguments to the body function. If the coroutine has yielded, resume restarts it; the values val1, ... are passed as the results from the yield.

If the coroutine runs without any errors, resume returns true plus any values passed to yield (if the coroutine yields) or any values returned by the body function (if the coroutine terminates). If there is any error, resume returns false plus the error message.

coroutine.running ()

Returns the running coroutine plus a boolean, true when the running coroutine is the main one.

coroutine.status (co)

Returns the status of coroutine co, as a string: "running", if the coroutine is running (that is, it called status); "suspended", if the coroutine is suspended in a call to yield, or if it has not started running yet; "normal" if the coroutine is active but not running (that is, it has resumed another coroutine); and "dead" if the coroutine has finished its body function, or if it has stopped with an error.

coroutine.wrap (f)

Creates a new coroutine, with body f. f must be a Lua function. Returns a function that resumes the coroutine each time it is called. Any arguments passed to the function behave as the extra arguments to resume. Returns the same values returned by resume, except the first boolean. In case of error, propagates the error.

coroutine.yield (···)

Suspends the execution of the calling coroutine. Any arguments to yield are passed as extra results to resume.

6.3 – Modules

The package library provides basic facilities for loading modules in Lua. It exports one function directly in the global environment: require. Everything else is exported in a table package.

require (modname)

Loads the given module. The function starts by looking into the package.loaded table to determine whether modname is already loaded. If it is, then require returns the value stored at package.loaded[modname]. Otherwise, it tries to find a loader for the module.

To find a loader, require is guided by the package.searchers sequence. By changing this sequence, we can change how require looks for a module. The following explanation is based on the default configuration for package.searchers.

First require queries package.preload[modname]. If it has a value, this value (which should be a function) is the loader. Otherwise require searches for a Lua loader using the path stored in package.path. If that also fails, it searches for a C loader using the path stored in package.cpath. If that also fails, it tries an all-in-one loader (see package.searchers).

Once a loader is found, require calls the loader with two arguments: modname and an extra value dependent on how it got the loader. (If the loader came from a file, this extra value is the file name.) If the loader returns any non-nil value, require assigns the returned value to package.loaded[modname]. If the loader does not return a non-nil value and has not assigned any value to package.loaded[modname], then require assigns true to this entry. In any case, require returns the final value of package.loaded[modname].

If there is any error loading or running the module, or if it cannot find any loader for the module, then require raises an error.

package.config

A string describing some compile-time configurations for packages. This string is a sequence of lines:

  • The first line is the directory separator string. Default is '\' for Windows and '/' for all other systems.
  • The second line is the character that separates templates in a path. Default is ';'.
  • The third line is the string that marks the substitution points in a template. Default is '?'.
  • The fourth line is a string that, in a path in Windows, is replaced by the executable's directory. Default is '!'.
  • The fifth line is a mark to ignore all text before it when building the luaopen_ function name. Default is '-'.

package.cpath

The path used by require to search for a C loader.

Lua initializes the C path package.cpath in the same way it initializes the Lua path package.path, using the environment variable LUA_CPATH_5_2 or the environment variable LUA_CPATH or a default path defined in luaconf.h.

package.loaded

A table used by require to control which modules are already loaded. When you require a module modname and package.loaded[modname] is not false, require simply returns the value stored there.

This variable is only a reference to the real table; assignments to this variable do not change the table used by require.

package.loadlib (libname, funcname)

Dynamically links the host program with the C library libname.

If funcname is "*", then it only links with the library, making the symbols exported by the library available to other dynamically linked libraries. Otherwise, it looks for a function funcname inside the library and returns this function as a C function. So, funcname must follow the lua_CFunction prototype (see lua_CFunction).

This is a low-level function. It completely bypasses the package and module system. Unlike require, it does not perform any path searching and does not automatically adds extensions. libname must be the complete file name of the C library, including if necessary a path and an extension. funcname must be the exact name exported by the C library (which may depend on the C compiler and linker used).

This function is not supported by Standard C. As such, it is only available on some platforms (Windows, Linux, Mac OS X, Solaris, BSD, plus other Unix systems that support the dlfcn standard).

package.path

The path used by require to search for a Lua loader.

At start-up, Lua initializes this variable with the value of the environment variable LUA_PATH_5_2 or the environment variable LUA_PATH or with a default path defined in luaconf.h, if those environment variables are not defined. Any ";;" in the value of the environment variable is replaced by the default path.

package.preload

A table to store loaders for specific modules (see require).

This variable is only a reference to the real table; assignments to this variable do not change the table used by require.

package.searchers

A table used by require to control how to load modules.

Each entry in this table is a searcher function. When looking for a module, require calls each of these searchers in ascending order, with the module name (the argument given to require) as its sole parameter. The function can return another function (the module loader) plus an extra value that will be passed to that loader, or a string explaining why it did not find that module (or nil if it has nothing to say).

Lua initializes this table with four searcher functions.

The first searcher simply looks for a loader in the package.preload table.

The second searcher looks for a loader as a Lua library, using the path stored at package.path. The search is done as described in function package.searchpath.

The third searcher looks for a loader as a C library, using the path given by the variable package.cpath. Again, the search is done as described in function package.searchpath. For instance, if the C path is the string 

     "./?.so;./?.dll;/usr/local/?/init.so"

the searcher for module foo will try to open the files ./foo.so, ./foo.dll, and /usr/local/foo/init.so, in that order. Once it finds a C library, this searcher first uses a dynamic link facility to link the application with the library. Then it tries to find a C function inside the library to be used as the loader. The name of this C function is the string "luaopen_" concatenated with a copy of the module name where each dot is replaced by an underscore. Moreover, if the module name has a hyphen, its prefix up to (and including) the first hyphen is removed. For instance, if the module name is a.v1-b.c, the function name will be luaopen_b_c.

The fourth searcher tries an all-in-one loader. It searches the C path for a library for the root name of the given module. For instance, when requiring a.b.c, it will search for a C library for a. If found, it looks into it for an open function for the submodule; in our example, that would be luaopen_a_b_c. With this facility, a package can pack several C submodules into one single library, with each submodule keeping its original open function.

All searchers except the first one (preload) return as the extra value the file name where the module was found, as returned by package.searchpath. The first searcher returns no extra value.

package.searchpath (name, path [, sep [, rep]])

Searches for the given name in the given path.

A path is a string containing a sequence of templates separated by semicolons. For each template, the function replaces each interrogation mark (if any) in the template with a copy of name wherein all occurrences of sep (a dot, by default) were replaced by rep (the system's directory separator, by default), and then tries to open the resulting file name.

For instance, if the path is the string 

     "./?.lua;./?.lc;/usr/local/?/init.lua"

the search for the name foo.a will try to open the files ./foo/a.lua, ./foo/a.lc, and /usr/local/foo/a/init.lua, in that order.

Returns the resulting name of the first file that it can open in read mode (after closing the file), or nil plus an error message if none succeeds. (This error message lists all file names it tried to open.)

6.4 – String Manipulation

This library provides generic functions for string manipulation, such as finding and extracting substrings, and pattern matching. When indexing a string in Lua, the first character is at position 1 (not at 0, as in C). Indices are allowed to be negative and are interpreted as indexing backwards, from the end of the string. Thus, the last character is at position -1, and so on.

The string library provides all its functions inside the table string. It also sets a metatable for strings where the __index field points to the string table. Therefore, you can use the string functions in object-oriented style. For instance, string.byte(s,i) can be written as s:byte(i).

The string library assumes one-byte character encodings.

string.byte (s [, i [, j]])

Returns the internal numerical codes of the characters s[i], s[i+1], ..., s[j]. The default value for i is 1; the default value for j is i. These indices are corrected following the same rules of function string.sub.

Numerical codes are not necessarily portable across platforms.

string.char (···)

Receives zero or more integers. Returns a string with length equal to the number of arguments, in which each character has the internal numerical code equal to its corresponding argument.

Numerical codes are not necessarily portable across platforms.

string.dump (function)

Returns a string containing a binary representation of the given function, so that a later load on this string returns a copy of the function (but with new upvalues).

string.find (s, pattern [, init [, plain]])

Looks for the first match of pattern in the string s. If it finds a match, then find returns the indices of s where this occurrence starts and ends; otherwise, it returns nil. A third, optional numerical argument init specifies where to start the search; its default value is 1 and can be negative. A value of true as a fourth, optional argument plain turns off the pattern matching facilities, so the function does a plain "find substring" operation, with no characters in pattern being considered magic. Note that if plain is given, then init must be given as well.

If the pattern has captures, then in a successful match the captured values are also returned, after the two indices.

string.format (formatstring, ···)

Returns a formatted version of its variable number of arguments following the description given in its first argument (which must be a string). The format string follows the same rules as the ANSI C function sprintf. The only differences are that the options/modifiers *, h, L, l, n, and p are not supported and that there is an extra option, q. The q option formats a string between double quotes, using escape sequences when necessary to ensure that it can safely be read back by the Lua interpreter. For instance, the call 

     string.format('%q', 'a string with "quotes" and \n new line')

may produce the string: 

     "a string with \"quotes\" and \
      new line"

Options A and a (when available), E, e, f, G, and g all expect a number as argument. Options c, d, i, o, u, X, and x also expect a number, but the range of that number may be limited by the underlying C implementation. For options o, u, X, and x, the number cannot be negative. Option q expects a string; option s expects a string without embedded zeros. If the argument to option s is not a string, it is converted to one following the same rules of tostring.

string.gmatch (s, pattern)

Returns an iterator function that, each time it is called, returns the next captures from pattern over the string s. If pattern specifies no captures, then the whole match is produced in each call.

As an example, the following loop will iterate over all the words from string s, printing one per line: 

     s = "hello world from Lua"
     for w in string.gmatch(s, "%a+") do
       print(w)
     end

The next example collects all pairs key=value from the given string into a table: 

     t = {}
     s = "from=world, to=Lua"
     for k, v in string.gmatch(s, "(%w+)=(%w+)") do
       t[k] = v
     end

For this function, a caret '^' at the start of a pattern does not work as an anchor, as this would prevent the iteration.

string.gsub (s, pattern, repl [, n])

Returns a copy of s in which all (or the first n, if given) occurrences of the pattern have been replaced by a replacement string specified by repl, which can be a string, a table, or a function. gsub also returns, as its second value, the total number of matches that occurred. The name gsub comes from Global SUBstitution.

If repl is a string, then its value is used for replacement. The character % works as an escape character: any sequence in repl of the form %d, with d between 1 and 9, stands for the value of the d-th captured substring. The sequence %0 stands for the whole match. The sequence %% stands for a single %.

If repl is a table, then the table is queried for every match, using the first capture as the key.

If repl is a function, then this function is called every time a match occurs, with all captured substrings passed as arguments, in order.

In any case, if the pattern specifies no captures, then it behaves as if the whole pattern was inside a capture.

If the value returned by the table query or by the function call is a string or a number, then it is used as the replacement string; otherwise, if it is false or nil, then there is no replacement (that is, the original match is kept in the string).

Here are some examples: 

     x = string.gsub("hello world", "(%w+)", "%1 %1")
     --> x="hello hello world world"
     
     x = string.gsub("hello world", "%w+", "%0 %0", 1)
     --> x="hello hello world"
     
     x = string.gsub("hello world from Lua", "(%w+)%s*(%w+)", "%2 %1")
     --> x="world hello Lua from"
     
     x = string.gsub("home = $HOME, user = $USER", "%$(%w+)", os.getenv)
     --> x="home = /home/roberto, user = roberto"
     
     x = string.gsub("4+5 = $return 4+5$", "%$(.-)%$", function (s)
           return load(s)()
         end)
     --> x="4+5 = 9"
     
     local t = {name="lua", version="5.2"}
     x = string.gsub("$name-$version.tar.gz", "%$(%w+)", t)
     --> x="lua-5.2.tar.gz"

string.len (s)

Receives a string and returns its length. The empty string "" has length 0. Embedded zeros are counted, so "a\000bc\000" has length 5.

string.lower (s)

Receives a string and returns a copy of this string with all uppercase letters changed to lowercase. All other characters are left unchanged. The definition of what an uppercase letter is depends on the current locale.

string.match (s, pattern [, init])

Looks for the first match of pattern in the string s. If it finds one, then match returns the captures from the pattern; otherwise it returns nil. If pattern specifies no captures, then the whole match is returned. A third, optional numerical argument init specifies where to start the search; its default value is 1 and can be negative.

string.rep (s, n [, sep])

Returns a string that is the concatenation of n copies of the string s separated by the string sep. The default value for sep is the empty string (that is, no separator).

string.reverse (s)

Returns a string that is the string s reversed.

string.sub (s, i [, j])

Returns the substring of s that starts at i and continues until j; i and j can be negative. If j is absent, then it is assumed to be equal to -1 (which is the same as the string length). In particular, the call string.sub(s,1,j) returns a prefix of s with length j, and string.sub(s, -i) returns a suffix of s with length i.

If, after the translation of negative indices, i is less than 1, it is corrected to 1. If j is greater than the string length, it is corrected to that length. If, after these corrections, i is greater than j, the function returns the empty string.

string.upper (s)

Receives a string and returns a copy of this string with all lowercase letters changed to uppercase. All other characters are left unchanged. The definition of what a lowercase letter is depends on the current locale.

6.4.1 – Patterns

Character Class:

A character class is used to represent a set of characters. The following combinations are allowed in describing a character class:

  • x: (where x is not one of the magic characters ^$()%.[]*+-?) represents the character x itself.
  • .: (a dot) represents all characters.
  • %a: represents all letters.
  • %c: represents all control characters.
  • %d: represents all digits.
  • %g: represents all printable characters except space.
  • %l: represents all lowercase letters.
  • %p: represents all punctuation characters.
  • %s: represents all space characters.
  • %u: represents all uppercase letters.
  • %w: represents all alphanumeric characters.
  • %x: represents all hexadecimal digits.
  • %x: (where x is any non-alphanumeric character) represents the character x. This is the standard way to escape the magic characters. Any punctuation character (even the non magic) can be preceded by a '%' when used to represent itself in a pattern.
  • [set]: represents the class which is the union of all characters in set. A range of characters can be specified by separating the end characters of the range, in ascending order, with a '-', All classes %x described above can also be used as components in set. All other characters in set represent themselves. For example, [%w_] (or [_%w]) represents all alphanumeric characters plus the underscore, [0-7] represents the octal digits, and [0-7%l%-] represents the octal digits plus the lowercase letters plus the '-' character.

    The interaction between ranges and classes is not defined. Therefore, patterns like [%a-z] or [a-%%] have no meaning.

  • [^set]: represents the complement of set, where set is interpreted as above.

For all classes represented by single letters (%a, %c, etc.), the corresponding uppercase letter represents the complement of the class. For instance, %S represents all non-space characters.

The definitions of letter, space, and other character groups depend on the current locale. In particular, the class [a-z] may not be equivalent to %l.

Pattern Item:

A pattern item can be

  • a single character class, which matches any single character in the class;
  • a single character class followed by '*', which matches 0 or more repetitions of characters in the class. These repetition items will always match the longest possible sequence;
  • a single character class followed by '+', which matches 1 or more repetitions of characters in the class. These repetition items will always match the longest possible sequence;
  • a single character class followed by '-', which also matches 0 or more repetitions of characters in the class. Unlike '*', these repetition items will always match the shortest possible sequence;
  • a single character class followed by '?', which matches 0 or 1 occurrence of a character in the class;
  • %n, for n between 1 and 9; such item matches a substring equal to the n-th captured string (see below);
  • %bxy, where x and y are two distinct characters; such item matches strings that start with x, end with y, and where the x and y are balanced. This means that, if one reads the string from left to right, counting +1 for an x and -1 for a y, the ending y is the first y where the count reaches 0. For instance, the item %b() matches expressions with balanced parentheses.
  • %f[set], a frontier pattern; such item matches an empty string at any position such that the next character belongs to set and the previous character does not belong to set. The set set is interpreted as previously described. The beginning and the end of the subject are handled as if they were the character '\0'.

Pattern:

A pattern is a sequence of pattern items. A caret '^' at the beginning of a pattern anchors the match at the beginning of the subject string. A '$' at the end of a pattern anchors the match at the end of the subject string. At other positions, '^' and '$' have no special meaning and represent themselves.

Captures:

A pattern can contain sub-patterns enclosed in parentheses; they describe captures. When a match succeeds, the substrings of the subject string that match captures are stored (captured) for future use. Captures are numbered according to their left parentheses. For instance, in the pattern "(a*(.)%w(%s*))", the part of the string matching "a*(.)%w(%s*)" is stored as the first capture (and therefore has number 1); the character matching "." is captured with number 2, and the part matching "%s*" has number 3.

As a special case, the empty capture () captures the current string position (a number). For instance, if we apply the pattern "()aa()" on the string "flaaap", there will be two captures: 3 and 5.

6.5 – Table Manipulation

This library provides generic functions for table manipulation. It provides all its functions inside the table table.

Remember that, whenever an operation needs the length of a table, the table should be a proper sequence or have a __len metamethod (see §3.4.6). All functions ignore non-numeric keys in tables given as arguments.

For performance reasons, all table accesses (get/set) performed by these functions are raw.

table.concat (list [, sep [, i [, j]]])

Given a list where all elements are strings or numbers, returns the string list[i]..sep..list[i+1] ··· sep..list[j]. The default value for sep is the empty string, the default for i is 1, and the default for j is #list. If i is greater than j, returns the empty string.

table.insert (list, [pos,] value)

Inserts element value at position pos in list, shifting up the elements list[pos], list[pos+1], ···, list[#list]. The default value for pos is #list+1, so that a call table.insert(t,x) inserts x at the end of list t.

table.pack (···)

Returns a new table with all parameters stored into keys 1, 2, etc. and with a field "n" with the total number of parameters. Note that the resulting table may not be a sequence.

table.remove (list [, pos])

Removes from list the element at position pos, returning the value of the removed element. When pos is an integer between 1 and #list, it shifts down the elements list[pos+1], list[pos+2], ···, list[#list] and erases element list[#list]; The index pos can also be 0 when #list is 0, or #list + 1; in those cases, the function erases the element list[pos].

The default value for pos is #list, so that a call table.remove(t) removes the last element of list t.

table.sort (list [, comp])

Sorts list elements in a given order, in-place, from list[1] to list[#list]. If comp is given, then it must be a function that receives two list elements and returns true when the first element must come before the second in the final order (so that not comp(list[i+1],list[i]) will be true after the sort). If comp is not given, then the standard Lua operator < is used instead.

The sort algorithm is not stable; that is, elements considered equal by the given order may have their relative positions changed by the sort.

table.unpack (list [, i [, j]])

Returns the elements from the given table. This function is equivalent to 

     return list[i], list[i+1], ···, list[j]

By default, i is 1 and j is #list.

6.6 – Mathematical Functions

This library is an interface to the standard C math library. It provides all its functions inside the table math.

math.abs (x)

Returns the absolute value of x.

math.acos (x)

Returns the arc cosine of x (in radians).

math.asin (x)

Returns the arc sine of x (in radians).

math.atan (x)

Returns the arc tangent of x (in radians).

math.atan2 (y, x)

Returns the arc tangent of y/x (in radians), but uses the signs of both parameters to find the quadrant of the result. (It also handles correctly the case of x being zero.)

math.ceil (x)

Returns the smallest integer larger than or equal to x.

math.cos (x)

Returns the cosine of x (assumed to be in radians).

math.cosh (x)

Returns the hyperbolic cosine of x.

math.deg (x)

Returns the angle x (given in radians) in degrees.

math.exp (x)

Returns the value ex.

math.floor (x)

Returns the largest integer smaller than or equal to x.

math.fmod (x, y)

Returns the remainder of the division of x by y that rounds the quotient towards zero.

math.frexp (x)

Returns m and e such that x = m2e, e is an integer and the absolute value of m is in the range [0.5, 1) (or zero when x is zero).

math.huge

The value HUGE_VAL, a value larger than or equal to any other numerical value.

math.ldexp (m, e)

Returns m2e (e should be an integer).

math.log (x [, base])

Returns the logarithm of x in the given base. The default for base is e (so that the function returns the natural logarithm of x).

math.max (x, ···)

Returns the maximum value among its arguments.

math.min (x, ···)

Returns the minimum value among its arguments.

math.modf (x)

Returns two numbers, the integral part of x and the fractional part of x.

math.pi

The value of π.

math.pow (x, y)

Returns xy. (You can also use the expression x^y to compute this value.)

math.rad (x)

Returns the angle x (given in degrees) in radians.

math.random ([m [, n]])

This function is an interface to the simple pseudo-random generator function rand provided by Standard C. (No guarantees can be given for its statistical properties.)

When called without arguments, returns a uniform pseudo-random real number in the range [0,1). When called with an integer number m, math.random returns a uniform pseudo-random integer in the range [1, m]. When called with two integer numbers m and n, math.random returns a uniform pseudo-random integer in the range [m, n].

math.randomseed (x)

Sets x as the "seed" for the pseudo-random generator: equal seeds produce equal sequences of numbers.

math.sin (x)

Returns the sine of x (assumed to be in radians).

math.sinh (x)

Returns the hyperbolic sine of x.

math.sqrt (x)

Returns the square root of x. (You can also use the expression x^0.5 to compute this value.)

math.tan (x)

Returns the tangent of x (assumed to be in radians).

math.tanh (x)

Returns the hyperbolic tangent of x.

6.7 – Bitwise Operations

This library provides bitwise operations. It provides all its functions inside the table bit32.

Unless otherwise stated, all functions accept numeric arguments in the range (-251,+251); each argument is normalized to the remainder of its division by 232 and truncated to an integer (in some unspecified way), so that its final value falls in the range [0,232 - 1]. Similarly, all results are in the range [0,232 - 1]. Note that bit32.bnot(0) is 0xFFFFFFFF, which is different from -1.

bit32.arshift (x, disp)

Returns the number x shifted disp bits to the right. The number disp may be any representable integer. Negative displacements shift to the left.

This shift operation is what is called arithmetic shift. Vacant bits on the left are filled with copies of the higher bit of x; vacant bits on the right are filled with zeros. In particular, displacements with absolute values higher than 31 result in zero or 0xFFFFFFFF (all original bits are shifted out).

bit32.band (···)

Returns the bitwise and of its operands.

bit32.bnot (x)

Returns the bitwise negation of x. For any integer x, the following identity holds: 

     assert(bit32.bnot(x) == (-1 - x) % 2^32)

bit32.bor (···)

Returns the bitwise or of its operands.

bit32.btest (···)

Returns a boolean signaling whether the bitwise and of its operands is different from zero.

bit32.bxor (···)

Returns the bitwise exclusive or of its operands.

bit32.extract (n, field [, width])

Returns the unsigned number formed by the bits field to field + width - 1 from n. Bits are numbered from 0 (least significant) to 31 (most significant). All accessed bits must be in the range [0, 31].

The default for width is 1.

bit32.replace (n, v, field [, width])

Returns a copy of n with the bits field to field + width - 1 replaced by the value v. See bit32.extract for details about field and width.

bit32.lrotate (x, disp)

Returns the number x rotated disp bits to the left. The number disp may be any representable integer.

For any valid displacement, the following identity holds: 

     assert(bit32.lrotate(x, disp) == bit32.lrotate(x, disp % 32))

In particular, negative displacements rotate to the right.

bit32.lshift (x, disp)

Returns the number x shifted disp bits to the left. The number disp may be any representable integer. Negative displacements shift to the right. In any direction, vacant bits are filled with zeros. In particular, displacements with absolute values higher than 31 result in zero (all bits are shifted out).

For positive displacements, the following equality holds: 

     assert(bit32.lshift(b, disp) == (b * 2^disp) % 2^32)

bit32.rrotate (x, disp)

Returns the number x rotated disp bits to the right. The number disp may be any representable integer.

For any valid displacement, the following identity holds: 

     assert(bit32.rrotate(x, disp) == bit32.rrotate(x, disp % 32))

In particular, negative displacements rotate to the left.

bit32.rshift (x, disp)

Returns the number x shifted disp bits to the right. The number disp may be any representable integer. Negative displacements shift to the left. In any direction, vacant bits are filled with zeros. In particular, displacements with absolute values higher than 31 result in zero (all bits are shifted out).

For positive displacements, the following equality holds: 

     assert(bit32.rshift(b, disp) == math.floor(b % 2^32 / 2^disp))

This shift operation is what is called logical shift.

6.8 – Input and Output Facilities

The I/O library provides two different styles for file manipulation. The first one uses implicit file descriptors; that is, there are operations to set a default input file and a default output file, and all input/output operations are over these default files. The second style uses explicit file descriptors.

When using implicit file descriptors, all operations are supplied by table io. When using explicit file descriptors, the operation io.open returns a file descriptor and then all operations are supplied as methods of the file descriptor.

The table io also provides three predefined file descriptors with their usual meanings from C: io.stdin, io.stdout, and io.stderr. The I/O library never closes these files.

Unless otherwise stated, all I/O functions return nil on failure (plus an error message as a second result and a system-dependent error code as a third result) and some value different from nil on success. On non-Posix systems, the computation of the error message and error code in case of errors may be not thread safe, because they rely on the global C variable errno.

io.close ([file])

Equivalent to file:close(). Without a file, closes the default output file.

io.flush ()

Equivalent to io.output():flush().

io.input ([file])

When called with a file name, it opens the named file (in text mode), and sets its handle as the default input file. When called with a file handle, it simply sets this file handle as the default input file. When called without parameters, it returns the current default input file.

In case of errors this function raises the error, instead of returning an error code.

io.lines ([filename ···])

Opens the given file name in read mode and returns an iterator function that works like file:lines(···) over the opened file. When the iterator function detects the end of file, it returns nil (to finish the loop) and automatically closes the file.

The call io.lines() (with no file name) is equivalent to io.input():lines(); that is, it iterates over the lines of the default input file. In this case it does not close the file when the loop ends.

In case of errors this function raises the error, instead of returning an error code.

io.open (filename [, mode])

This function opens a file, in the mode specified in the string mode. It returns a new file handle, or, in case of errors, nil plus an error message.

The mode string can be any of the following:

  • "r": read mode (the default);
  • "w": write mode;
  • "a": append mode;
  • "r+": update mode, all previous data is preserved;
  • "w+": update mode, all previous data is erased;
  • "a+": append update mode, previous data is preserved, writing is only allowed at the end of file.

The mode string can also have a 'b' at the end, which is needed in some systems to open the file in binary mode.

io.output ([file])

Similar to io.input, but operates over the default output file.

io.popen (prog [, mode])

This function is system dependent and is not available on all platforms.

Starts program prog in a separated process and returns a file handle that you can use to read data from this program (if mode is "r", the default) or to write data to this program (if mode is "w").

io.read (···)

Equivalent to io.input():read(···).

io.tmpfile ()

Returns a handle for a temporary file. This file is opened in update mode and it is automatically removed when the program ends.

io.type (obj)

Checks whether obj is a valid file handle. Returns the string "file" if obj is an open file handle, "closed file" if obj is a closed file handle, or nil if obj is not a file handle.

io.write (···)

Equivalent to io.output():write(···).

file:close ()

Closes file. Note that files are automatically closed when their handles are garbage collected, but that takes an unpredictable amount of time to happen.

When closing a file handle created with io.popen, file:close returns the same values returned by os.execute.

file:flush ()

Saves any written data to file.

file:lines (···)

Returns an iterator function that, each time it is called, reads the file according to the given formats. When no format is given, uses "*l" as a default. As an example, the construction 

     for c in file:lines(1) do body end

will iterate over all characters of the file, starting at the current position. Unlike io.lines, this function does not close the file when the loop ends.

In case of errors this function raises the error, instead of returning an error code.

file:read (···)

Reads the file file, according to the given formats, which specify what to read. For each format, the function returns a string (or a number) with the characters read, or nil if it cannot read data with the specified format. When called without formats, it uses a default format that reads the next line (see below).

The available formats are

  • "*n": reads a number; this is the only format that returns a number instead of a string.
  • "*a": reads the whole file, starting at the current position. On end of file, it returns the empty string.
  • "*l": reads the next line skipping the end of line, returning nil on end of file. This is the default format.
  • "*L": reads the next line keeping the end of line (if present), returning nil on end of file.
  • number: reads a string with up to this number of bytes, returning nil on end of file. If number is zero, it reads nothing and returns an empty string, or nil on end of file.

file:seek ([whence [, offset]])

Sets and gets the file position, measured from the beginning of the file, to the position given by offset plus a base specified by the string whence, as follows:

  • "set": base is position 0 (beginning of the file);
  • "cur": base is current position;
  • "end": base is end of file;

In case of success, seek returns the final file position, measured in bytes from the beginning of the file. If seek fails, it returns nil, plus a string describing the error.

The default value for whence is "cur", and for offset is 0. Therefore, the call file:seek() returns the current file position, without changing it; the call file:seek("set") sets the position to the beginning of the file (and returns 0); and the call file:seek("end") sets the position to the end of the file, and returns its size.

file:setvbuf (mode [, size])

Sets the buffering mode for an output file. There are three available modes:

  • "no": no buffering; the result of any output operation appears immediately.
  • "full": full buffering; output operation is performed only when the buffer is full or when you explicitly flush the file (see io.flush).
  • "line": line buffering; output is buffered until a newline is output or there is any input from some special files (such as a terminal device).

For the last two cases, size specifies the size of the buffer, in bytes. The default is an appropriate size.

file:write (···)

Writes the value of each of its arguments to file. The arguments must be strings or numbers.

In case of success, this function returns file. Otherwise it returns nil plus a string describing the error.

6.9 – Operating System Facilities

This library is implemented through table os.

os.clock ()

Returns an approximation of the amount in seconds of CPU time used by the program.

os.date ([format [, time]])

Returns a string or a table containing date and time, formatted according to the given string format.

If the time argument is present, this is the time to be formatted (see the os.time function for a description of this value). Otherwise, date formats the current time.

If format starts with '!', then the date is formatted in Coordinated Universal Time. After this optional character, if format is the string "*t", then date returns a table with the following fields: year (four digits), month (1–12), day (1–31), hour (0–23), min (0–59), sec (0–61), wday (weekday, Sunday is 1), yday (day of the year), and isdst (daylight saving flag, a boolean). This last field may be absent if the information is not available.

If format is not "*t", then date returns the date as a string, formatted according to the same rules as the ANSI C function strftime.

When called without arguments, date returns a reasonable date and time representation that depends on the host system and on the current locale (that is, os.date() is equivalent to os.date("%c")).

On non-Posix systems, this function may be not thread safe because of its reliance on C function gmtime and C function localtime.

os.difftime (t2, t1)

Returns the number of seconds from time t1 to time t2. In POSIX, Windows, and some other systems, this value is exactly t2-t1.

os.execute ([command])

This function is equivalent to the ANSI C function system. It passes command to be executed by an operating system shell. Its first result is true if the command terminated successfully, or nil otherwise. After this first result the function returns a string and a number, as follows:

  • "exit": the command terminated normally; the following number is the exit status of the command.
  • "signal": the command was terminated by a signal; the following number is the signal that terminated the command.

When called without a command, os.execute returns a boolean that is true if a shell is available.

os.exit ([code [, close])

Calls the ANSI C function exit to terminate the host program. If code is true, the returned status is EXIT_SUCCESS; if code is false, the returned status is EXIT_FAILURE; if code is a number, the returned status is this number. The default value for code is true.

If the optional second argument close is true, closes the Lua state before exiting.

os.getenv (varname)

Returns the value of the process environment variable varname, or nil if the variable is not defined.

os.remove (filename)

Deletes the file (or empty directory, on POSIX systems) with the given name. If this function fails, it returns nil, plus a string describing the error and the error code.

os.rename (oldname, newname)

Renames file or directory named oldname to newname. If this function fails, it returns nil, plus a string describing the error and the error code.

os.setlocale (locale [, category])

Sets the current locale of the program. locale is a system-dependent string specifying a locale; category is an optional string describing which category to change: "all", "collate", "ctype", "monetary", "numeric", or "time"; the default category is "all". The function returns the name of the new locale, or nil if the request cannot be honored.

If locale is the empty string, the current locale is set to an implementation-defined native locale. If locale is the string "C", the current locale is set to the standard C locale.

When called with nil as the first argument, this function only returns the name of the current locale for the given category.

This function may be not thread safe because of its reliance on C function setlocale.

os.time ([table])

Returns the current time when called without arguments, or a time representing the date and time specified by the given table. This table must have fields year, month, and day, and may have fields hour (default is 12), min (default is 0), sec (default is 0), and isdst (default is nil). For a description of these fields, see the os.date function.

The returned value is a number, whose meaning depends on your system. In POSIX, Windows, and some other systems, this number counts the number of seconds since some given start time (the "epoch"). In other systems, the meaning is not specified, and the number returned by time can be used only as an argument to os.date and os.difftime.

os.tmpname ()

Returns a string with a file name that can be used for a temporary file. The file must be explicitly opened before its use and explicitly removed when no longer needed.

On POSIX systems, this function also creates a file with that name, to avoid security risks. (Someone else might create the file with wrong permissions in the time between getting the name and creating the file.) You still have to open the file to use it and to remove it (even if you do not use it).

When possible, you may prefer to use io.tmpfile, which automatically removes the file when the program ends.

6.10 – The Debug Library

This library provides the functionality of the debug interface (§4.9) to Lua programs. You should exert care when using this library. Several of its functions violate basic assumptions about Lua code (e.g., that variables local to a function cannot be accessed from outside; that userdata metatables cannot be changed by Lua code; that Lua programs do not crash) and therefore can compromise otherwise secure code. Moreover, some functions in this library may be slow.

All functions in this library are provided inside the debug table. All functions that operate over a thread have an optional first argument which is the thread to operate over. The default is always the current thread.

debug.debug ()

Enters an interactive mode with the user, running each string that the user enters. Using simple commands and other debug facilities, the user can inspect global and local variables, change their values, evaluate expressions, and so on. A line containing only the word cont finishes this function, so that the caller continues its execution.

Note that commands for debug.debug are not lexically nested within any function and so have no direct access to local variables.

debug.gethook ([thread])

Returns the current hook settings of the thread, as three values: the current hook function, the current hook mask, and the current hook count (as set by the debug.sethook function).

debug.getinfo ([thread,] f [, what])

Returns a table with information about a function. You can give the function directly or you can give a number as the value of f, which means the function running at level f of the call stack of the given thread: level 0 is the current function (getinfo itself); level 1 is the function that called getinfo (except for tail calls, which do not count on the stack); and so on. If f is a number larger than the number of active functions, then getinfo returns nil.

The returned table can contain all the fields returned by lua_getinfo, with the string what describing which fields to fill in. The default for what is to get all information available, except the table of valid lines. If present, the option 'f' adds a field named func with the function itself. If present, the option 'L' adds a field named activelines with the table of valid lines.

For instance, the expression debug.getinfo(1,"n").name returns a table with a name for the current function, if a reasonable name can be found, and the expression debug.getinfo(print) returns a table with all available information about the print function.

debug.getlocal ([thread,] f, local)

This function returns the name and the value of the local variable with index local of the function at level f of the stack. This function accesses not only explicit local variables, but also parameters, temporaries, etc.

The first parameter or local variable has index 1, and so on, until the last active variable. Negative indices refer to vararg parameters; -1 is the first vararg parameter. The function returns nil if there is no variable with the given index, and raises an error when called with a level out of range. (You can call debug.getinfo to check whether the level is valid.)

Variable names starting with '(' (open parenthesis) represent internal variables (loop control variables, temporaries, varargs, and C function locals).

The parameter f may also be a function. In that case, getlocal returns only the name of function parameters.

debug.getmetatable (value)

Returns the metatable of the given value or nil if it does not have a metatable.

debug.getregistry ()

Returns the registry table (see §4.5).

debug.getupvalue (f, up)

This function returns the name and the value of the upvalue with index up of the function f. The function returns nil if there is no upvalue with the given index.

debug.getuservalue (u)

Returns the Lua value associated to u. If u is not a userdata, returns nil.

debug.sethook ([thread,] hook, mask [, count])

Sets the given function as a hook. The string mask and the number count describe when the hook will be called. The string mask may have the following characters, with the given meaning:

  • 'c': the hook is called every time Lua calls a function;
  • 'r': the hook is called every time Lua returns from a function;
  • 'l': the hook is called every time Lua enters a new line of code.

With a count different from zero, the hook is called after every count instructions.

When called without arguments, debug.sethook turns off the hook.

When the hook is called, its first parameter is a string describing the event that has triggered its call: "call" (or "tail call"), "return", "line", and "count". For line events, the hook also gets the new line number as its second parameter. Inside a hook, you can call getinfo with level 2 to get more information about the running function (level 0 is the getinfo function, and level 1 is the hook function).

debug.setlocal ([thread,] level, local, value)

This function assigns the value value to the local variable with index local of the function at level level of the stack. The function returns nil if there is no local variable with the given index, and raises an error when called with a level out of range. (You can call getinfo to check whether the level is valid.) Otherwise, it returns the name of the local variable.

See debug.getlocal for more information about variable indices and names.

debug.setmetatable (value, table)

Sets the metatable for the given value to the given table (which can be nil). Returns value.

debug.setupvalue (f, up, value)

This function assigns the value value to the upvalue with index up of the function f. The function returns nil if there is no upvalue with the given index. Otherwise, it returns the name of the upvalue.

debug.setuservalue (udata, value)

Sets the given value as the Lua value associated to the given udata. value must be a table or nil; udata must be a full userdata.

Returns udata.

debug.traceback ([thread,] [message [, level]])

If message is present but is neither a string nor nil, this function returns message without further processing. Otherwise, it returns a string with a traceback of the call stack. An optional message string is appended at the beginning of the traceback. An optional level number tells at which level to start the traceback (default is 1, the function calling traceback).

debug.upvalueid (f, n)

Returns an unique identifier (as a light userdata) for the upvalue numbered n from the given function.

These unique identifiers allow a program to check whether different closures share upvalues. Lua closures that share an upvalue (that is, that access a same external local variable) will return identical ids for those upvalue indices.

debug.upvaluejoin (f1, n1, f2, n2)

Make the n1-th upvalue of the Lua closure f1 refer to the n2-th upvalue of the Lua closure f2.

7 – Lua Standalone

Although Lua has been designed as an extension language, to be embedded in a host C program, it is also frequently used as a standalone language. An interpreter for Lua as a standalone language, called simply lua, is provided with the standard distribution. The standalone interpreter includes all standard libraries, including the debug library. Its usage is: 

     lua [options] [script [args]]

The options are:

  • -e stat: executes string stat;
  • -l mod: "requires" mod;
  • -i: enters interactive mode after running script;
  • -v: prints version information;
  • -E: ignores environment variables;
  • --: stops handling options;
  • -: executes stdin as a file and stops handling options.

After handling its options, lua runs the given script, passing to it the given args as string arguments. When called without arguments, lua behaves as lua -v -i when the standard input (stdin) is a terminal, and as lua - otherwise.

When called without option -E, the interpreter checks for an environment variable LUA_INIT_5_2 (or LUA_INIT if it is not defined) before running any argument. If the variable content has the format @filename, then lua executes the file. Otherwise, lua executes the string itself.

When called with option -E, besides ignoring LUA_INIT, Lua also ignores the values of LUA_PATH and LUA_CPATH, setting the values of package.path and package.cpath with the default paths defined in luaconf.h.

All options are handled in order, except -i and -E. For instance, an invocation like 

     $ lua -e'a=1' -e 'print(a)' script.lua

will first set a to 1, then print the value of a, and finally run the file script.lua with no arguments. (Here $ is the shell prompt. Your prompt may be different.)

Before starting to run the script, lua collects all arguments in the command line in a global table called arg. The script name is stored at index 0, the first argument after the script name goes to index 1, and so on. Any arguments before the script name (that is, the interpreter name plus the options) go to negative indices. For instance, in the call 

     $ lua -la b.lua t1 t2

the interpreter first runs the file a.lua, then creates a table 

     arg = { [-2] = "lua", [-1] = "-la",
             [0] = "b.lua",
             [1] = "t1", [2] = "t2" }

and finally runs the file b.lua. The script is called with arg[1], arg[2], ... as arguments; it can also access these arguments with the vararg expression '...'.

In interactive mode, if you write an incomplete statement, the interpreter waits for its completion by issuing a different prompt.

In case of unprotected errors in the script, the interpreter reports the error to the standard error stream. If the error object is a string, the interpreter adds a stack traceback to it. Otherwise, if the error object has a metamethod __tostring, the interpreter calls this metamethod to produce the final message. Finally, if the error object is nil, the interpreter does not report the error.

When finishing normally, the interpreter closes its main Lua state (see lua_close). The script can avoid this step by calling os.exit to terminate.

To allow the use of Lua as a script interpreter in Unix systems, the standalone interpreter skips the first line of a chunk if it starts with #. Therefore, Lua scripts can be made into executable programs by using chmod +x and the #! form, as in 

     #!/usr/local/bin/lua

(Of course, the location of the Lua interpreter may be different in your machine. If lua is in your PATH, then 

     #!/usr/bin/env lua

is a more portable solution.)

8 – Incompatibilities with the Previous Version

Here we list the incompatibilities that you may find when moving a program from Lua 5.1 to Lua 5.2. You can avoid some incompatibilities by compiling Lua with appropriate options (see file luaconf.h). However, all these compatibility options will be removed in the next version of Lua. Similarly, all features marked as deprecated in Lua 5.1 have been removed in Lua 5.2.

8.1 – Changes in the Language

  • The concept of environment changed. Only Lua functions have environments. To set the environment of a Lua function, use the variable _ENV or the function load.

    C functions no longer have environments. Use an upvalue with a shared table if you need to keep shared state among several C functions. (You may use luaL_setfuncs to open a C library with all functions sharing a common upvalue.)

    To manipulate the "environment" of a userdata (which is now called user value), use the new functions lua_getuservalue and lua_setuservalue.

  • Lua identifiers cannot use locale-dependent letters.
  • Doing a step or a full collection in the garbage collector does not restart the collector if it has been stopped.
  • Weak tables with weak keys now perform like ephemeron tables.
  • The event tail return in debug hooks was removed. Instead, tail calls generate a special new event, tail call, so that the debugger can know that there will not be a corresponding return event.
  • Equality between function values has changed. Now, a function definition may not create a new value; it may reuse some previous value if there is no observable difference to the new function.

8.2 – Changes in the Libraries

  • Function module is deprecated. It is easy to set up a module with regular Lua code. Modules are not expected to set global variables.
  • Functions setfenv and getfenv were removed, because of the changes in environments.
  • Function math.log10 is deprecated. Use math.log with 10 as its second argument, instead.
  • Function loadstring is deprecated. Use load instead; it now accepts string arguments and are exactly equivalent to loadstring.
  • Function table.maxn is deprecated. Write it in Lua if you really need it.
  • Function os.execute now returns true when command terminates successfully and nil plus error information otherwise.
  • Function unpack was moved into the table library and therefore must be called as table.unpack.
  • Character class %z in patterns is deprecated, as now patterns may contain '\0' as a regular character.
  • The table package.loaders was renamed package.searchers.
  • Lua does not have bytecode verification anymore. So, all functions that load code (load and loadfile) are potentially insecure when loading untrusted binary data. (Actually, those functions were already insecure because of flaws in the verification algorithm.) When in doubt, use the mode argument of those functions to restrict them to loading textual chunks.
  • The standard paths in the official distribution may change between versions.

8.3 – Changes in the API

  • Pseudoindex LUA_GLOBALSINDEX was removed. You must get the global environment from the registry (see §4.5).
  • Pseudoindex LUA_ENVIRONINDEX and functions lua_getfenv/lua_setfenv were removed, as C functions no longer have environments.
  • Function luaL_register is deprecated. Use luaL_setfuncs so that your module does not create globals. (Modules are not expected to set global variables anymore.)
  • The osize argument to the allocation function may not be zero when creating a new block, that is, when ptr is NULL (see lua_Alloc). Use only the test ptr == NULL to check whether the block is new.
  • Finalizers (__gc metamethods) for userdata are called in the reverse order that they were marked for finalization, not that they were created (see §2.5.1). (Most userdata are marked immediately after they are created.) Moreover, if the metatable does not have a __gc field when set, the finalizer will not be called, even if it is set later.
  • luaL_typerror was removed. Write your own version if you need it.
  • Function lua_cpcall is deprecated. You can simply push the function with lua_pushcfunction and call it with lua_pcall.
  • Functions lua_equal and lua_lessthan are deprecated. Use the new lua_compare with appropriate options instead.
  • Function lua_objlen was renamed lua_rawlen.
  • Function lua_load has an extra parameter, mode. Pass NULL to simulate the old behavior.
  • Function lua_resume has an extra parameter, from. Pass NULL or the thread doing the call.

9 – The Complete Syntax of Lua

Here is the complete syntax of Lua in extended BNF. (It does not describe operator precedences.) 


	chunk ::= block

	block ::= {stat} [retstat]

	stat ::=  ‘;’ | 
		 varlist ‘=’ explist | 
		 functioncall | 
		 label | 
		 break | 
		 goto Name | 
		 do block end | 
		 while exp do block end | 
		 repeat block until exp | 
		 if exp then block {elseif exp then block} [else block] end | 
		 for Name ‘=’ exp ‘,’ exp [‘,’ exp] do block end | 
		 for namelist in explist do block end | 
		 function funcname funcbody | 
		 local function Name funcbody | 
		 local namelist [‘=’ explist] 

	retstat ::= return [explist] [‘;’]

	label ::= ‘::’ Name ‘::’

	funcname ::= Name {‘.’ Name} [‘:’ Name]

	varlist ::= var {‘,’ var}

	var ::=  Name | prefixexp ‘[’ exp ‘]’ | prefixexp ‘.’ Name 

	namelist ::= Name {‘,’ Name}

	explist ::= exp {‘,’ exp}

	exp ::=  nil | false | true | Number | String | ‘...’ | functiondef | 
		 prefixexp | tableconstructor | exp binop exp | unop exp 

	prefixexp ::= var | functioncall | ‘(’ exp ‘)’

	functioncall ::=  prefixexp args | prefixexp ‘:’ Name args 

	args ::=  ‘(’ [explist] ‘)’ | tableconstructor | String 

	functiondef ::= function funcbody

	funcbody ::= ‘(’ [parlist] ‘)’ block end

	parlist ::= namelist [‘,’ ‘...’] | ‘...’

	tableconstructor ::= ‘{’ [fieldlist] ‘}’

	fieldlist ::= field {fieldsep field} [fieldsep]

	field ::= ‘[’ exp ‘]’ ‘=’ exp | Name ‘=’ exp | exp

	fieldsep ::= ‘,’ | ‘;’

	binop ::= ‘+’ | ‘-’ | ‘*’ | ‘/’ | ‘^’ | ‘%’ | ‘..’ | 
		 ‘<’ | ‘<=’ | ‘>’ | ‘>=’ | ‘==’ | ‘~=’ | 
		 and | or

	unop ::= ‘-’ | not | ‘#’

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Lua Welcome to Lua 5.2

about · installation · changes · license · reference manual

About Lua

Lua is a powerful, fast, lightweight, embeddable scripting language developed by a team at PUC-Rio, the Pontifical Catholic University of Rio de Janeiro in Brazil. Lua is free software used in many products and projects around the world.

Lua's official web site provides complete information about Lua, including an executive summary and updated documentation, especially the reference manual, which may differ slightly from the local copy distributed in this package.

Installing Lua

Lua is distributed in source form. You need to build it before using it. Building Lua should be straightforward because Lua is implemented in pure ANSI C and compiles unmodified in all known platforms that have an ANSI C compiler. Lua also compiles unmodified as C++. The instructions given below for building Lua are for Unix-like platforms. See also instructions for other systems and customization options.

If you don't have the time or the inclination to compile Lua yourself, get a binary from LuaBinaries. Try also Lua for Windows, an easy-to-use distribution of Lua that includes many useful libraries.

Building Lua

In most Unix-like platforms, simply do "make" with a suitable target. Here are the details.

  1. Open a terminal window and move to the top-level directory, which is named lua-5.2.2. The Makefile there controls both the build process and the installation process.

  2. Do "make" and see if your platform is listed. The platforms currently supported are:

    aix ansi bsd freebsd generic linux macosx mingw posix solaris

    If your platform is listed, just do "make xxx", where xxx is your platform name.

    If your platform is not listed, try the closest one or posix, generic, ansi, in this order.

  3. The compilation takes only a few moments and produces three files in the src directory: lua (the interpreter), luac (the compiler), and liblua.a (the library).

  4. To check that Lua has been built correctly, do "make test" after building Lua. This will run the interpreter and print its version string.

If you're running Linux and get compilation errors, make sure you have installed the readline development package. If you get link errors after that, then try "make linux MYLIBS=-ltermcap".

Installing Lua

Once you have built Lua, you may want to install it in an official place in your system. In this case, do "make install". The official place and the way to install files are defined in the Makefile. You'll probably need the right permissions to install files.

To build and install Lua in one step, do "make xxx install", where xxx is your platform name.

To install Lua locally, do "make local". This will create a directory install with subdirectories bin, include, lib, man, and install Lua as listed below. To install Lua locally, but in some other directory, do "make install INSTALL_TOP=xxx", where xxx is your chosen directory.

bin:
lua luac
include:
lua.h luaconf.h lualib.h lauxlib.h lua.hpp
lib:
liblua.a
man/man1:
lua.1 luac.1

These are the only directories you need for development. If you only want to run Lua programs, you only need the files in bin and man. The files in include and lib are needed for embedding Lua in C or C++ programs.

Customization

Three kinds of things can be customized by editing a file:

  • Where and how to install Lua — edit Makefile.
  • How to build Lua — edit src/Makefile.
  • Lua features — edit src/luaconf.h.

You don't actually need to edit the Makefiles because you may set the relevant variables in the command line when invoking make. Nevertheless, it's probably best to edit and save the Makefiles to record the changes you need.

On the other hand, if you need to customize some Lua features, you'll need to edit src/luaconf.h before building and installing Lua. The edited file will be the one installed, and it will be used by any Lua clients that you build, to ensure consistency. Further customization is available to experts by editing the Lua sources.

We strongly recommend that you enable dynamic loading in src/luaconf.h. This is done automatically for all platforms listed above that have this feature and also for Windows.

Building Lua on other systems

If you're not using the usual Unix tools, then the instructions for building Lua depend on the compiler you use. You'll need to create projects (or whatever your compiler uses) for building the library, the interpreter, and the compiler, as follows:

library:
lapi.c lcode.c lctype.c ldebug.c ldo.c ldump.c lfunc.c lgc.c llex.c lmem.c lobject.c lopcodes.c lparser.c lstate.c lstring.c ltable.c ltm.c lundump.c lvm.c lzio.c lauxlib.c lbaselib.c lbitlib.c lcorolib.c ldblib.c liolib.c lmathlib.c loslib.c lstrlib.c ltablib.c loadlib.c linit.c
interpreter:
library, lua.c
compiler:
library, luac.c

To use Lua as a library in your own programs you'll need to know how to create and use libraries with your compiler. Moreover, to dynamically load C libraries for Lua you'll need to know how to create dynamic libraries and you'll need to make sure that the Lua API functions are accessible to those dynamic libraries — but don't link the Lua library into each dynamic library. For Unix, we recommend that the Lua library be linked statically into the host program and its symbols exported for dynamic linking; src/Makefile does this for the Lua interpreter. For Windows, we recommend that the Lua library be a DLL.

As mentioned above, you may edit src/luaconf.h to customize some features before building Lua.

Changes since Lua 5.1

Here are the main changes introduced in Lua 5.2. The reference manual lists the incompatibilities that had to be introduced.

Main changes

  • yieldable pcall and metamethods
  • new lexical scheme for globals
  • ephemeron tables
  • new library for bitwise operations
  • light C functions
  • emergency garbage collector
  • goto statement
  • finalizers for tables
Here are the other changes introduced in Lua 5.2:

Language

  • no more fenv for threads or functions
  • tables honor the __len metamethod
  • hex and \z escapes in strings
  • support for hexadecimal floats
  • order metamethods work for different types
  • no more verification of opcode consistency
  • hook event "tail return" replaced by "tail call"
  • empty statement
  • break statement may appear in the middle of a block

Libraries

  • arguments for function called through xpcall
  • optional 'mode' argument to load and loadfile (to control binary x text)
  • optional 'env' argument to load and loadfile (environment for loaded chunk)
  • loadlib may load libraries with global names (RTLD_GLOBAL)
  • new function package.searchpath
  • modules receive their paths when loaded
  • optional base in math.log
  • optional separator in string.rep
  • file:write returns file
  • closing a pipe returns exit status
  • os.exit may close state
  • new metamethods __pairs and __ipairs
  • new option 'isrunning' for collectgarbage and lua_gc
  • frontier patterns
  • \0 in patterns
  • new option *L for io.read
  • options for io.lines
  • debug.getlocal can access function varargs

C API

  • main thread predefined in the registry
  • new functions lua_absindex, lua_arith, lua_compare, lua_copy, lua_len, lua_rawgetp, lua_rawsetp, lua_upvalueid, lua_upvaluejoin, lua_version.
  • new functions luaL_checkversion, luaL_setmetatable, luaL_testudata, luaL_tolstring.
  • lua_pushstring and pushlstring return string
  • nparams and isvararg available in debug API
  • new lua_Unsigned

Implementation

  • max constants per function raised to 226
  • generational mode for garbage collection (experimental)
  • NaN trick (experimental)
  • internal (immutable) version of ctypes
  • simpler implementation for string buffers
  • parser uses much less C-stack space (no more auto arrays)

Lua standalone interpreter

  • new -E option to avoid environment variables
  • handling of non-string error messages

License

[osi certified]

Lua is free software distributed under the terms of the MIT license reproduced below; it may be used for any purpose, including commercial purposes, at absolutely no cost without having to ask us. The only requirement is that if you do use Lua, then you should give us credit by including the appropriate copyright notice somewhere in your product or its documentation. For details, see this.

Copyright © 1994–2013 Lua.org, PUC-Rio.

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Last update: Fri Feb 22 09:24:20 BRT 2013 april-ann-0.4.1/lua/lua-5.2.2/src/000077500000000000000000000000001263004425400161705ustar00rootroot00000000000000april-ann-0.4.1/lua/lua-5.2.2/src/Makefile000066400000000000000000000143341263004425400176350ustar00rootroot00000000000000# Makefile for building Lua # See ../doc/readme.html for installation and customization instructions. # == CHANGE THE SETTINGS BELOW TO SUIT YOUR ENVIRONMENT ======================= # Your platform. See PLATS for possible values. UNAME = `uname` PLAT= DetectOS CC= gcc CFLAGS= -O2 -Wall -DLUA_COMPAT_ALL $(SYSCFLAGS) $(MYCFLAGS) LDFLAGS= $(SYSLDFLAGS) $(MYLDFLAGS) LIBS= -lm $(SYSLIBS) $(MYLIBS) AR= ar rcu RANLIB= ranlib RM= rm -f SYSCFLAGS= SYSLDFLAGS= SYSLIBS= MYCFLAGS= MYLDFLAGS= MYLIBS= MYOBJS= # == END OF USER SETTINGS -- NO NEED TO CHANGE ANYTHING BELOW THIS LINE ======= PLATS= DetectOS Darwin Linux aix ansi bsd freebsd generic linux macosx mingw posix solaris LUA_A= liblua.a CORE_O= lapi.o lcode.o lctype.o ldebug.o ldo.o ldump.o lfunc.o lgc.o llex.o \ lmem.o lobject.o lopcodes.o lparser.o lstate.o lstring.o ltable.o \ ltm.o lundump.o lvm.o lzio.o LIB_O= lauxlib.o lbaselib.o lbitlib.o lcorolib.o ldblib.o liolib.o \ lmathlib.o loslib.o lstrlib.o ltablib.o loadlib.o linit.o BASE_O= $(CORE_O) $(LIB_O) $(MYOBJS) LUA_T= lua LUA_O= lua.o LUAC_T= luac LUAC_O= luac.o ALL_O= $(BASE_O) $(LUA_O) $(LUAC_O) ALL_T= $(LUA_A) $(LUA_T) $(LUAC_T) ALL_A= $(LUA_A) # Targets start here. DetectOS: @make $(UNAME) Linux: linux Darwin: macosx default: $(PLAT) all: $(ALL_T) o: $(ALL_O) a: $(ALL_A) $(LUA_A): $(BASE_O) $(AR) $@ $(BASE_O) $(RANLIB) $@ $(LUA_T): $(LUA_O) $(LUA_A) $(CC) -o $@ $(LDFLAGS) $(LUA_O) $(LUA_A) $(LIBS) $(LUAC_T): $(LUAC_O) $(LUA_A) $(CC) -o $@ $(LDFLAGS) $(LUAC_O) $(LUA_A) $(LIBS) clean: $(RM) $(ALL_T) $(ALL_O) depend: @$(CC) $(CFLAGS) -MM l*.c echo: @echo "PLAT= $(PLAT)" @echo "CC= $(CC)" @echo "CFLAGS= $(CFLAGS)" @echo "LDFLAGS= $(SYSLDFLAGS)" @echo "LIBS= $(LIBS)" @echo "AR= $(AR)" @echo "RANLIB= $(RANLIB)" @echo "RM= $(RM)" # Convenience targets for popular platforms ALL= all none: @echo "Please do 'make PLATFORM' where PLATFORM is one of these:" @echo " $(PLATS)" aix: $(MAKE) $(ALL) CC="xlc" CFLAGS="-O2 -DLUA_USE_POSIX -DLUA_USE_DLOPEN" SYSLIBS="-ldl" SYSLDFLAGS="-brtl -bexpall" ansi: $(MAKE) $(ALL) SYSCFLAGS="-DLUA_ANSI" bsd: $(MAKE) $(ALL) SYSCFLAGS="-DLUA_USE_POSIX -DLUA_USE_DLOPEN" SYSLIBS="-Wl,-E" freebsd: $(MAKE) $(ALL) SYSCFLAGS="-DLUA_USE_LINUX" SYSLIBS="-Wl,-E -lreadline" generic: $(ALL) linux: $(MAKE) $(ALL) SYSCFLAGS="-DLUA_USE_LINUX" SYSLIBS="-Wl,-E -ldl -lreadline" macosx: $(MAKE) $(ALL) SYSCFLAGS="-DLUA_USE_MACOSX" SYSLIBS="-ldl -lreadline" mingw: $(MAKE) "LUA_A=lua52.dll" "LUA_T=lua.exe" \ "AR=$(CC) -shared -o" "RANLIB=strip --strip-unneeded" \ "SYSCFLAGS=-DLUA_BUILD_AS_DLL" "SYSLIBS=" "SYSLDFLAGS=-s" lua.exe $(MAKE) "LUAC_T=luac.exe" luac.exe posix: $(MAKE) $(ALL) SYSCFLAGS="-DLUA_USE_POSIX" SYSLIBS="-lreadline" solaris: $(MAKE) $(ALL) SYSCFLAGS="-DLUA_USE_POSIX -DLUA_USE_DLOPEN" SYSLIBS="-ldl" # list targets that do not create files (but not all makes understand .PHONY) .PHONY: all $(PLATS) default o a clean depend echo none # DO NOT DELETE lapi.o: lapi.c lua.h luaconf.h lapi.h llimits.h lstate.h lobject.h ltm.h \ lzio.h lmem.h ldebug.h ldo.h lfunc.h lgc.h lstring.h ltable.h lundump.h \ lvm.h lauxlib.o: lauxlib.c lua.h luaconf.h lauxlib.h lbaselib.o: lbaselib.c lua.h luaconf.h lauxlib.h lualib.h lbitlib.o: lbitlib.c lua.h luaconf.h lauxlib.h lualib.h lcode.o: lcode.c lua.h luaconf.h lcode.h llex.h lobject.h llimits.h \ lzio.h lmem.h lopcodes.h lparser.h ldebug.h lstate.h ltm.h ldo.h lgc.h \ lstring.h ltable.h lvm.h lcorolib.o: lcorolib.c lua.h luaconf.h lauxlib.h lualib.h lctype.o: lctype.c lctype.h lua.h luaconf.h llimits.h ldblib.o: ldblib.c lua.h luaconf.h lauxlib.h lualib.h ldebug.o: ldebug.c lua.h luaconf.h lapi.h llimits.h lstate.h lobject.h \ ltm.h lzio.h lmem.h lcode.h llex.h lopcodes.h lparser.h ldebug.h ldo.h \ lfunc.h lstring.h lgc.h ltable.h lvm.h ldo.o: ldo.c lua.h luaconf.h lapi.h llimits.h lstate.h lobject.h ltm.h \ lzio.h lmem.h ldebug.h ldo.h lfunc.h lgc.h lopcodes.h lparser.h \ lstring.h ltable.h lundump.h lvm.h ldump.o: ldump.c lua.h luaconf.h lobject.h llimits.h lstate.h ltm.h \ lzio.h lmem.h lundump.h lfunc.o: lfunc.c lua.h luaconf.h lfunc.h lobject.h llimits.h lgc.h \ lstate.h ltm.h lzio.h lmem.h lgc.o: lgc.c lua.h luaconf.h ldebug.h lstate.h lobject.h llimits.h ltm.h \ lzio.h lmem.h ldo.h lfunc.h lgc.h lstring.h ltable.h linit.o: linit.c lua.h luaconf.h lualib.h lauxlib.h liolib.o: liolib.c lua.h luaconf.h lauxlib.h lualib.h llex.o: llex.c lua.h luaconf.h lctype.h llimits.h ldo.h lobject.h \ lstate.h ltm.h lzio.h lmem.h llex.h lparser.h lstring.h lgc.h ltable.h lmathlib.o: lmathlib.c lua.h luaconf.h lauxlib.h lualib.h lmem.o: lmem.c lua.h luaconf.h ldebug.h lstate.h lobject.h llimits.h \ ltm.h lzio.h lmem.h ldo.h lgc.h loadlib.o: loadlib.c lua.h luaconf.h lauxlib.h lualib.h lobject.o: lobject.c lua.h luaconf.h lctype.h llimits.h ldebug.h lstate.h \ lobject.h ltm.h lzio.h lmem.h ldo.h lstring.h lgc.h lvm.h lopcodes.o: lopcodes.c lopcodes.h llimits.h lua.h luaconf.h loslib.o: loslib.c lua.h luaconf.h lauxlib.h lualib.h lparser.o: lparser.c lua.h luaconf.h lcode.h llex.h lobject.h llimits.h \ lzio.h lmem.h lopcodes.h lparser.h ldebug.h lstate.h ltm.h ldo.h lfunc.h \ lstring.h lgc.h ltable.h lstate.o: lstate.c lua.h luaconf.h lapi.h llimits.h lstate.h lobject.h \ ltm.h lzio.h lmem.h ldebug.h ldo.h lfunc.h lgc.h llex.h lstring.h \ ltable.h lstring.o: lstring.c lua.h luaconf.h lmem.h llimits.h lobject.h lstate.h \ ltm.h lzio.h lstring.h lgc.h lstrlib.o: lstrlib.c lua.h luaconf.h lauxlib.h lualib.h ltable.o: ltable.c lua.h luaconf.h ldebug.h lstate.h lobject.h llimits.h \ ltm.h lzio.h lmem.h ldo.h lgc.h lstring.h ltable.h lvm.h ltablib.o: ltablib.c lua.h luaconf.h lauxlib.h lualib.h ltm.o: ltm.c lua.h luaconf.h lobject.h llimits.h lstate.h ltm.h lzio.h \ lmem.h lstring.h lgc.h ltable.h lua.o: lua.c lua.h luaconf.h lauxlib.h lualib.h luac.o: luac.c lua.h luaconf.h lauxlib.h lobject.h llimits.h lstate.h \ ltm.h lzio.h lmem.h lundump.h ldebug.h lopcodes.h lundump.o: lundump.c lua.h luaconf.h ldebug.h lstate.h lobject.h \ llimits.h ltm.h lzio.h lmem.h ldo.h lfunc.h lstring.h lgc.h lundump.h lvm.o: lvm.c lua.h luaconf.h ldebug.h lstate.h lobject.h llimits.h ltm.h \ lzio.h lmem.h ldo.h lfunc.h lgc.h lopcodes.h lstring.h ltable.h lvm.h lzio.o: lzio.c lua.h luaconf.h llimits.h lmem.h lstate.h lobject.h ltm.h \ lzio.h april-ann-0.4.1/lua/lua-5.2.2/src/lapi.c000066400000000000000000000723221263004425400172670ustar00rootroot00000000000000/* ** $Id: lapi.c,v 2.171 2013/03/16 21:10:18 roberto Exp $ ** Lua API ** See Copyright Notice in lua.h */ #include #include #define lapi_c #define LUA_CORE #include "lua.h" #include "lapi.h" #include "ldebug.h" #include "ldo.h" #include "lfunc.h" #include "lgc.h" #include "lmem.h" #include "lobject.h" #include "lstate.h" #include "lstring.h" #include "ltable.h" #include "ltm.h" #include "lundump.h" #include "lvm.h" const char lua_ident[] = "$LuaVersion: " LUA_COPYRIGHT " $" "$LuaAuthors: " LUA_AUTHORS " $"; /* value at a non-valid index */ #define NONVALIDVALUE cast(TValue *, luaO_nilobject) /* corresponding test */ #define isvalid(o) ((o) != luaO_nilobject) /* test for pseudo index */ #define ispseudo(i) ((i) <= LUA_REGISTRYINDEX) /* test for valid but not pseudo index */ #define isstackindex(i, o) (isvalid(o) && !ispseudo(i)) #define api_checkvalidindex(L, o) api_check(L, isvalid(o), "invalid index") #define api_checkstackindex(L, i, o) \ api_check(L, isstackindex(i, o), "index not in the stack") static TValue *index2addr (lua_State *L, int idx) { CallInfo *ci = L->ci; if (idx > 0) { TValue *o = ci->func + idx; api_check(L, idx <= ci->top - (ci->func + 1), "unacceptable index"); if (o >= L->top) return NONVALIDVALUE; else return o; } else if (!ispseudo(idx)) { /* negative index */ api_check(L, idx != 0 && -idx <= L->top - (ci->func + 1), "invalid index"); return L->top + idx; } else if (idx == LUA_REGISTRYINDEX) return &G(L)->l_registry; else { /* upvalues */ idx = LUA_REGISTRYINDEX - idx; api_check(L, idx <= MAXUPVAL + 1, "upvalue index too large"); if (ttislcf(ci->func)) /* light C function? */ return NONVALIDVALUE; /* it has no upvalues */ else { CClosure *func = clCvalue(ci->func); return (idx <= func->nupvalues) ? &func->upvalue[idx-1] : NONVALIDVALUE; } } } /* ** to be called by 'lua_checkstack' in protected mode, to grow stack ** capturing memory errors */ static void growstack (lua_State *L, void *ud) { int size = *(int *)ud; luaD_growstack(L, size); } LUA_API int lua_checkstack (lua_State *L, int size) { int res; CallInfo *ci = L->ci; lua_lock(L); if (L->stack_last - L->top > size) /* stack large enough? */ res = 1; /* yes; check is OK */ else { /* no; need to grow stack */ int inuse = cast_int(L->top - L->stack) + EXTRA_STACK; if (inuse > LUAI_MAXSTACK - size) /* can grow without overflow? */ res = 0; /* no */ else /* try to grow stack */ res = (luaD_rawrunprotected(L, &growstack, &size) == LUA_OK); } if (res && ci->top < L->top + size) ci->top = L->top + size; /* adjust frame top */ lua_unlock(L); return res; } LUA_API void lua_xmove (lua_State *from, lua_State *to, int n) { int i; if (from == to) return; lua_lock(to); api_checknelems(from, n); api_check(from, G(from) == G(to), "moving among independent states"); api_check(from, to->ci->top - to->top >= n, "not enough elements to move"); from->top -= n; for (i = 0; i < n; i++) { setobj2s(to, to->top++, from->top + i); } lua_unlock(to); } LUA_API lua_CFunction lua_atpanic (lua_State *L, lua_CFunction panicf) { lua_CFunction old; lua_lock(L); old = G(L)->panic; G(L)->panic = panicf; lua_unlock(L); return old; } LUA_API const lua_Number *lua_version (lua_State *L) { static const lua_Number version = LUA_VERSION_NUM; if (L == NULL) return &version; else return G(L)->version; } /* ** basic stack manipulation */ /* ** convert an acceptable stack index into an absolute index */ LUA_API int lua_absindex (lua_State *L, int idx) { return (idx > 0 || ispseudo(idx)) ? idx : cast_int(L->top - L->ci->func + idx); } LUA_API int lua_gettop (lua_State *L) { return cast_int(L->top - (L->ci->func + 1)); } LUA_API void lua_settop (lua_State *L, int idx) { StkId func = L->ci->func; lua_lock(L); if (idx >= 0) { api_check(L, idx <= L->stack_last - (func + 1), "new top too large"); while (L->top < (func + 1) + idx) setnilvalue(L->top++); L->top = (func + 1) + idx; } else { api_check(L, -(idx+1) <= (L->top - (func + 1)), "invalid new top"); L->top += idx+1; /* `subtract' index (index is negative) */ } lua_unlock(L); } LUA_API void lua_remove (lua_State *L, int idx) { StkId p; lua_lock(L); p = index2addr(L, idx); api_checkstackindex(L, idx, p); while (++p < L->top) setobjs2s(L, p-1, p); L->top--; lua_unlock(L); } LUA_API void lua_insert (lua_State *L, int idx) { StkId p; StkId q; lua_lock(L); p = index2addr(L, idx); api_checkstackindex(L, idx, p); for (q = L->top; q > p; q--) /* use L->top as a temporary */ setobjs2s(L, q, q - 1); setobjs2s(L, p, L->top); lua_unlock(L); } static void moveto (lua_State *L, TValue *fr, int idx) { TValue *to = index2addr(L, idx); api_checkvalidindex(L, to); setobj(L, to, fr); if (idx < LUA_REGISTRYINDEX) /* function upvalue? */ luaC_barrier(L, clCvalue(L->ci->func), fr); /* LUA_REGISTRYINDEX does not need gc barrier (collector revisits it before finishing collection) */ } LUA_API void lua_replace (lua_State *L, int idx) { lua_lock(L); api_checknelems(L, 1); moveto(L, L->top - 1, idx); L->top--; lua_unlock(L); } LUA_API void lua_copy (lua_State *L, int fromidx, int toidx) { TValue *fr; lua_lock(L); fr = index2addr(L, fromidx); moveto(L, fr, toidx); lua_unlock(L); } LUA_API void lua_pushvalue (lua_State *L, int idx) { lua_lock(L); setobj2s(L, L->top, index2addr(L, idx)); api_incr_top(L); lua_unlock(L); } /* ** access functions (stack -> C) */ LUA_API int lua_type (lua_State *L, int idx) { StkId o = index2addr(L, idx); return (isvalid(o) ? ttypenv(o) : LUA_TNONE); } LUA_API const char *lua_typename (lua_State *L, int t) { UNUSED(L); return ttypename(t); } LUA_API int lua_iscfunction (lua_State *L, int idx) { StkId o = index2addr(L, idx); return (ttislcf(o) || (ttisCclosure(o))); } LUA_API int lua_isnumber (lua_State *L, int idx) { TValue n; const TValue *o = index2addr(L, idx); return tonumber(o, &n); } LUA_API int lua_isstring (lua_State *L, int idx) { int t = lua_type(L, idx); return (t == LUA_TSTRING || t == LUA_TNUMBER); } LUA_API int lua_isuserdata (lua_State *L, int idx) { const TValue *o = index2addr(L, idx); return (ttisuserdata(o) || ttislightuserdata(o)); } LUA_API int lua_rawequal (lua_State *L, int index1, int index2) { StkId o1 = index2addr(L, index1); StkId o2 = index2addr(L, index2); return (isvalid(o1) && isvalid(o2)) ? luaV_rawequalobj(o1, o2) : 0; } LUA_API void lua_arith (lua_State *L, int op) { StkId o1; /* 1st operand */ StkId o2; /* 2nd operand */ lua_lock(L); if (op != LUA_OPUNM) /* all other operations expect two operands */ api_checknelems(L, 2); else { /* for unary minus, add fake 2nd operand */ api_checknelems(L, 1); setobjs2s(L, L->top, L->top - 1); L->top++; } o1 = L->top - 2; o2 = L->top - 1; if (ttisnumber(o1) && ttisnumber(o2)) { setnvalue(o1, luaO_arith(op, nvalue(o1), nvalue(o2))); } else luaV_arith(L, o1, o1, o2, cast(TMS, op - LUA_OPADD + TM_ADD)); L->top--; lua_unlock(L); } LUA_API int lua_compare (lua_State *L, int index1, int index2, int op) { StkId o1, o2; int i = 0; lua_lock(L); /* may call tag method */ o1 = index2addr(L, index1); o2 = index2addr(L, index2); if (isvalid(o1) && isvalid(o2)) { switch (op) { case LUA_OPEQ: i = equalobj(L, o1, o2); break; case LUA_OPLT: i = luaV_lessthan(L, o1, o2); break; case LUA_OPLE: i = luaV_lessequal(L, o1, o2); break; default: api_check(L, 0, "invalid option"); } } lua_unlock(L); return i; } LUA_API lua_Number lua_tonumberx (lua_State *L, int idx, int *isnum) { TValue n; const TValue *o = index2addr(L, idx); if (tonumber(o, &n)) { if (isnum) *isnum = 1; return nvalue(o); } else { if (isnum) *isnum = 0; return 0; } } LUA_API lua_Integer lua_tointegerx (lua_State *L, int idx, int *isnum) { TValue n; const TValue *o = index2addr(L, idx); if (tonumber(o, &n)) { lua_Integer res; lua_Number num = nvalue(o); lua_number2integer(res, num); if (isnum) *isnum = 1; return res; } else { if (isnum) *isnum = 0; return 0; } } LUA_API lua_Unsigned lua_tounsignedx (lua_State *L, int idx, int *isnum) { TValue n; const TValue *o = index2addr(L, idx); if (tonumber(o, &n)) { lua_Unsigned res; lua_Number num = nvalue(o); lua_number2unsigned(res, num); if (isnum) *isnum = 1; return res; } else { if (isnum) *isnum = 0; return 0; } } LUA_API int lua_toboolean (lua_State *L, int idx) { const TValue *o = index2addr(L, idx); return !l_isfalse(o); } LUA_API const char *lua_tolstring (lua_State *L, int idx, size_t *len) { StkId o = index2addr(L, idx); if (!ttisstring(o)) { lua_lock(L); /* `luaV_tostring' may create a new string */ if (!luaV_tostring(L, o)) { /* conversion failed? */ if (len != NULL) *len = 0; lua_unlock(L); return NULL; } luaC_checkGC(L); o = index2addr(L, idx); /* previous call may reallocate the stack */ lua_unlock(L); } if (len != NULL) *len = tsvalue(o)->len; return svalue(o); } LUA_API size_t lua_rawlen (lua_State *L, int idx) { StkId o = index2addr(L, idx); switch (ttypenv(o)) { case LUA_TSTRING: return tsvalue(o)->len; case LUA_TUSERDATA: return uvalue(o)->len; case LUA_TTABLE: return luaH_getn(hvalue(o)); default: return 0; } } LUA_API lua_CFunction lua_tocfunction (lua_State *L, int idx) { StkId o = index2addr(L, idx); if (ttislcf(o)) return fvalue(o); else if (ttisCclosure(o)) return clCvalue(o)->f; else return NULL; /* not a C function */ } LUA_API void *lua_touserdata (lua_State *L, int idx) { StkId o = index2addr(L, idx); switch (ttypenv(o)) { case LUA_TUSERDATA: return (rawuvalue(o) + 1); case LUA_TLIGHTUSERDATA: return pvalue(o); default: return NULL; } } LUA_API lua_State *lua_tothread (lua_State *L, int idx) { StkId o = index2addr(L, idx); return (!ttisthread(o)) ? NULL : thvalue(o); } LUA_API const void *lua_topointer (lua_State *L, int idx) { StkId o = index2addr(L, idx); switch (ttype(o)) { case LUA_TTABLE: return hvalue(o); case LUA_TLCL: return clLvalue(o); case LUA_TCCL: return clCvalue(o); case LUA_TLCF: return cast(void *, cast(size_t, fvalue(o))); case LUA_TTHREAD: return thvalue(o); case LUA_TUSERDATA: case LUA_TLIGHTUSERDATA: return lua_touserdata(L, idx); default: return NULL; } } /* ** push functions (C -> stack) */ LUA_API void lua_pushnil (lua_State *L) { lua_lock(L); setnilvalue(L->top); api_incr_top(L); lua_unlock(L); } LUA_API void lua_pushnumber (lua_State *L, lua_Number n) { lua_lock(L); setnvalue(L->top, n); luai_checknum(L, L->top, luaG_runerror(L, "C API - attempt to push a signaling NaN")); api_incr_top(L); lua_unlock(L); } LUA_API void lua_pushinteger (lua_State *L, lua_Integer n) { lua_lock(L); setnvalue(L->top, cast_num(n)); api_incr_top(L); lua_unlock(L); } LUA_API void lua_pushunsigned (lua_State *L, lua_Unsigned u) { lua_Number n; lua_lock(L); n = lua_unsigned2number(u); setnvalue(L->top, n); api_incr_top(L); lua_unlock(L); } LUA_API const char *lua_pushlstring (lua_State *L, const char *s, size_t len) { TString *ts; lua_lock(L); luaC_checkGC(L); ts = luaS_newlstr(L, s, len); setsvalue2s(L, L->top, ts); api_incr_top(L); lua_unlock(L); return getstr(ts); } LUA_API const char *lua_pushstring (lua_State *L, const char *s) { if (s == NULL) { lua_pushnil(L); return NULL; } else { TString *ts; lua_lock(L); luaC_checkGC(L); ts = luaS_new(L, s); setsvalue2s(L, L->top, ts); api_incr_top(L); lua_unlock(L); return getstr(ts); } } LUA_API const char *lua_pushvfstring (lua_State *L, const char *fmt, va_list argp) { const char *ret; lua_lock(L); luaC_checkGC(L); ret = luaO_pushvfstring(L, fmt, argp); lua_unlock(L); return ret; } LUA_API const char *lua_pushfstring (lua_State *L, const char *fmt, ...) { const char *ret; va_list argp; lua_lock(L); luaC_checkGC(L); va_start(argp, fmt); ret = luaO_pushvfstring(L, fmt, argp); va_end(argp); lua_unlock(L); return ret; } LUA_API void lua_pushcclosure (lua_State *L, lua_CFunction fn, int n) { lua_lock(L); if (n == 0) { setfvalue(L->top, fn); } else { Closure *cl; api_checknelems(L, n); api_check(L, n <= MAXUPVAL, "upvalue index too large"); luaC_checkGC(L); cl = luaF_newCclosure(L, n); cl->c.f = fn; L->top -= n; while (n--) setobj2n(L, &cl->c.upvalue[n], L->top + n); setclCvalue(L, L->top, cl); } api_incr_top(L); lua_unlock(L); } LUA_API void lua_pushboolean (lua_State *L, int b) { lua_lock(L); setbvalue(L->top, (b != 0)); /* ensure that true is 1 */ api_incr_top(L); lua_unlock(L); } LUA_API void lua_pushlightuserdata (lua_State *L, void *p) { lua_lock(L); setpvalue(L->top, p); api_incr_top(L); lua_unlock(L); } LUA_API int lua_pushthread (lua_State *L) { lua_lock(L); setthvalue(L, L->top, L); api_incr_top(L); lua_unlock(L); return (G(L)->mainthread == L); } /* ** get functions (Lua -> stack) */ LUA_API void lua_getglobal (lua_State *L, const char *var) { Table *reg = hvalue(&G(L)->l_registry); const TValue *gt; /* global table */ lua_lock(L); gt = luaH_getint(reg, LUA_RIDX_GLOBALS); setsvalue2s(L, L->top++, luaS_new(L, var)); luaV_gettable(L, gt, L->top - 1, L->top - 1); lua_unlock(L); } LUA_API void lua_gettable (lua_State *L, int idx) { StkId t; lua_lock(L); t = index2addr(L, idx); luaV_gettable(L, t, L->top - 1, L->top - 1); lua_unlock(L); } LUA_API void lua_getfield (lua_State *L, int idx, const char *k) { StkId t; lua_lock(L); t = index2addr(L, idx); setsvalue2s(L, L->top, luaS_new(L, k)); api_incr_top(L); luaV_gettable(L, t, L->top - 1, L->top - 1); lua_unlock(L); } LUA_API void lua_rawget (lua_State *L, int idx) { StkId t; lua_lock(L); t = index2addr(L, idx); api_check(L, ttistable(t), "table expected"); setobj2s(L, L->top - 1, luaH_get(hvalue(t), L->top - 1)); lua_unlock(L); } LUA_API void lua_rawgeti (lua_State *L, int idx, int n) { StkId t; lua_lock(L); t = index2addr(L, idx); api_check(L, ttistable(t), "table expected"); setobj2s(L, L->top, luaH_getint(hvalue(t), n)); api_incr_top(L); lua_unlock(L); } LUA_API void lua_rawgetp (lua_State *L, int idx, const void *p) { StkId t; TValue k; lua_lock(L); t = index2addr(L, idx); api_check(L, ttistable(t), "table expected"); setpvalue(&k, cast(void *, p)); setobj2s(L, L->top, luaH_get(hvalue(t), &k)); api_incr_top(L); lua_unlock(L); } LUA_API void lua_createtable (lua_State *L, int narray, int nrec) { Table *t; lua_lock(L); luaC_checkGC(L); t = luaH_new(L); sethvalue(L, L->top, t); api_incr_top(L); if (narray > 0 || nrec > 0) luaH_resize(L, t, narray, nrec); lua_unlock(L); } LUA_API int lua_getmetatable (lua_State *L, int objindex) { const TValue *obj; Table *mt = NULL; int res; lua_lock(L); obj = index2addr(L, objindex); switch (ttypenv(obj)) { case LUA_TTABLE: mt = hvalue(obj)->metatable; break; case LUA_TUSERDATA: mt = uvalue(obj)->metatable; break; default: mt = G(L)->mt[ttypenv(obj)]; break; } if (mt == NULL) res = 0; else { sethvalue(L, L->top, mt); api_incr_top(L); res = 1; } lua_unlock(L); return res; } LUA_API void lua_getuservalue (lua_State *L, int idx) { StkId o; lua_lock(L); o = index2addr(L, idx); api_check(L, ttisuserdata(o), "userdata expected"); if (uvalue(o)->env) { sethvalue(L, L->top, uvalue(o)->env); } else setnilvalue(L->top); api_incr_top(L); lua_unlock(L); } /* ** set functions (stack -> Lua) */ LUA_API void lua_setglobal (lua_State *L, const char *var) { Table *reg = hvalue(&G(L)->l_registry); const TValue *gt; /* global table */ lua_lock(L); api_checknelems(L, 1); gt = luaH_getint(reg, LUA_RIDX_GLOBALS); setsvalue2s(L, L->top++, luaS_new(L, var)); luaV_settable(L, gt, L->top - 1, L->top - 2); L->top -= 2; /* pop value and key */ lua_unlock(L); } LUA_API void lua_settable (lua_State *L, int idx) { StkId t; lua_lock(L); api_checknelems(L, 2); t = index2addr(L, idx); luaV_settable(L, t, L->top - 2, L->top - 1); L->top -= 2; /* pop index and value */ lua_unlock(L); } LUA_API void lua_setfield (lua_State *L, int idx, const char *k) { StkId t; lua_lock(L); api_checknelems(L, 1); t = index2addr(L, idx); setsvalue2s(L, L->top++, luaS_new(L, k)); luaV_settable(L, t, L->top - 1, L->top - 2); L->top -= 2; /* pop value and key */ lua_unlock(L); } LUA_API void lua_rawset (lua_State *L, int idx) { StkId t; lua_lock(L); api_checknelems(L, 2); t = index2addr(L, idx); api_check(L, ttistable(t), "table expected"); setobj2t(L, luaH_set(L, hvalue(t), L->top-2), L->top-1); invalidateTMcache(hvalue(t)); luaC_barrierback(L, gcvalue(t), L->top-1); L->top -= 2; lua_unlock(L); } LUA_API void lua_rawseti (lua_State *L, int idx, int n) { StkId t; lua_lock(L); api_checknelems(L, 1); t = index2addr(L, idx); api_check(L, ttistable(t), "table expected"); luaH_setint(L, hvalue(t), n, L->top - 1); luaC_barrierback(L, gcvalue(t), L->top-1); L->top--; lua_unlock(L); } LUA_API void lua_rawsetp (lua_State *L, int idx, const void *p) { StkId t; TValue k; lua_lock(L); api_checknelems(L, 1); t = index2addr(L, idx); api_check(L, ttistable(t), "table expected"); setpvalue(&k, cast(void *, p)); setobj2t(L, luaH_set(L, hvalue(t), &k), L->top - 1); luaC_barrierback(L, gcvalue(t), L->top - 1); L->top--; lua_unlock(L); } LUA_API int lua_setmetatable (lua_State *L, int objindex) { TValue *obj; Table *mt; lua_lock(L); api_checknelems(L, 1); obj = index2addr(L, objindex); if (ttisnil(L->top - 1)) mt = NULL; else { api_check(L, ttistable(L->top - 1), "table expected"); mt = hvalue(L->top - 1); } switch (ttypenv(obj)) { case LUA_TTABLE: { hvalue(obj)->metatable = mt; if (mt) { luaC_objbarrierback(L, gcvalue(obj), mt); luaC_checkfinalizer(L, gcvalue(obj), mt); } break; } case LUA_TUSERDATA: { uvalue(obj)->metatable = mt; if (mt) { luaC_objbarrier(L, rawuvalue(obj), mt); luaC_checkfinalizer(L, gcvalue(obj), mt); } break; } default: { G(L)->mt[ttypenv(obj)] = mt; break; } } L->top--; lua_unlock(L); return 1; } LUA_API void lua_setuservalue (lua_State *L, int idx) { StkId o; lua_lock(L); api_checknelems(L, 1); o = index2addr(L, idx); api_check(L, ttisuserdata(o), "userdata expected"); if (ttisnil(L->top - 1)) uvalue(o)->env = NULL; else { api_check(L, ttistable(L->top - 1), "table expected"); uvalue(o)->env = hvalue(L->top - 1); luaC_objbarrier(L, gcvalue(o), hvalue(L->top - 1)); } L->top--; lua_unlock(L); } /* ** `load' and `call' functions (run Lua code) */ #define checkresults(L,na,nr) \ api_check(L, (nr) == LUA_MULTRET || (L->ci->top - L->top >= (nr) - (na)), \ "results from function overflow current stack size") LUA_API int lua_getctx (lua_State *L, int *ctx) { if (L->ci->callstatus & CIST_YIELDED) { if (ctx) *ctx = L->ci->u.c.ctx; return L->ci->u.c.status; } else return LUA_OK; } LUA_API void lua_callk (lua_State *L, int nargs, int nresults, int ctx, lua_CFunction k) { StkId func; lua_lock(L); api_check(L, k == NULL || !isLua(L->ci), "cannot use continuations inside hooks"); api_checknelems(L, nargs+1); api_check(L, L->status == LUA_OK, "cannot do calls on non-normal thread"); checkresults(L, nargs, nresults); func = L->top - (nargs+1); if (k != NULL && L->nny == 0) { /* need to prepare continuation? */ L->ci->u.c.k = k; /* save continuation */ L->ci->u.c.ctx = ctx; /* save context */ luaD_call(L, func, nresults, 1); /* do the call */ } else /* no continuation or no yieldable */ luaD_call(L, func, nresults, 0); /* just do the call */ adjustresults(L, nresults); lua_unlock(L); } /* ** Execute a protected call. */ struct CallS { /* data to `f_call' */ StkId func; int nresults; }; static void f_call (lua_State *L, void *ud) { struct CallS *c = cast(struct CallS *, ud); luaD_call(L, c->func, c->nresults, 0); } LUA_API int lua_pcallk (lua_State *L, int nargs, int nresults, int errfunc, int ctx, lua_CFunction k) { struct CallS c; int status; ptrdiff_t func; lua_lock(L); api_check(L, k == NULL || !isLua(L->ci), "cannot use continuations inside hooks"); api_checknelems(L, nargs+1); api_check(L, L->status == LUA_OK, "cannot do calls on non-normal thread"); checkresults(L, nargs, nresults); if (errfunc == 0) func = 0; else { StkId o = index2addr(L, errfunc); api_checkstackindex(L, errfunc, o); func = savestack(L, o); } c.func = L->top - (nargs+1); /* function to be called */ if (k == NULL || L->nny > 0) { /* no continuation or no yieldable? */ c.nresults = nresults; /* do a 'conventional' protected call */ status = luaD_pcall(L, f_call, &c, savestack(L, c.func), func); } else { /* prepare continuation (call is already protected by 'resume') */ CallInfo *ci = L->ci; ci->u.c.k = k; /* save continuation */ ci->u.c.ctx = ctx; /* save context */ /* save information for error recovery */ ci->extra = savestack(L, c.func); ci->u.c.old_allowhook = L->allowhook; ci->u.c.old_errfunc = L->errfunc; L->errfunc = func; /* mark that function may do error recovery */ ci->callstatus |= CIST_YPCALL; luaD_call(L, c.func, nresults, 1); /* do the call */ ci->callstatus &= ~CIST_YPCALL; L->errfunc = ci->u.c.old_errfunc; status = LUA_OK; /* if it is here, there were no errors */ } adjustresults(L, nresults); lua_unlock(L); return status; } LUA_API int lua_load (lua_State *L, lua_Reader reader, void *data, const char *chunkname, const char *mode) { ZIO z; int status; lua_lock(L); if (!chunkname) chunkname = "?"; luaZ_init(L, &z, reader, data); status = luaD_protectedparser(L, &z, chunkname, mode); if (status == LUA_OK) { /* no errors? */ LClosure *f = clLvalue(L->top - 1); /* get newly created function */ if (f->nupvalues == 1) { /* does it have one upvalue? */ /* get global table from registry */ Table *reg = hvalue(&G(L)->l_registry); const TValue *gt = luaH_getint(reg, LUA_RIDX_GLOBALS); /* set global table as 1st upvalue of 'f' (may be LUA_ENV) */ setobj(L, f->upvals[0]->v, gt); luaC_barrier(L, f->upvals[0], gt); } } lua_unlock(L); return status; } LUA_API int lua_dump (lua_State *L, lua_Writer writer, void *data) { int status; TValue *o; lua_lock(L); api_checknelems(L, 1); o = L->top - 1; if (isLfunction(o)) status = luaU_dump(L, getproto(o), writer, data, 0); else status = 1; lua_unlock(L); return status; } LUA_API int lua_status (lua_State *L) { return L->status; } /* ** Garbage-collection function */ LUA_API int lua_gc (lua_State *L, int what, int data) { int res = 0; global_State *g; lua_lock(L); g = G(L); switch (what) { case LUA_GCSTOP: { g->gcrunning = 0; break; } case LUA_GCRESTART: { luaE_setdebt(g, 0); g->gcrunning = 1; break; } case LUA_GCCOLLECT: { luaC_fullgc(L, 0); break; } case LUA_GCCOUNT: { /* GC values are expressed in Kbytes: #bytes/2^10 */ res = cast_int(gettotalbytes(g) >> 10); break; } case LUA_GCCOUNTB: { res = cast_int(gettotalbytes(g) & 0x3ff); break; } case LUA_GCSTEP: { if (g->gckind == KGC_GEN) { /* generational mode? */ res = (g->GCestimate == 0); /* true if it will do major collection */ luaC_forcestep(L); /* do a single step */ } else { lu_mem debt = cast(lu_mem, data) * 1024 - GCSTEPSIZE; if (g->gcrunning) debt += g->GCdebt; /* include current debt */ luaE_setdebt(g, debt); luaC_forcestep(L); if (g->gcstate == GCSpause) /* end of cycle? */ res = 1; /* signal it */ } break; } case LUA_GCSETPAUSE: { res = g->gcpause; g->gcpause = data; break; } case LUA_GCSETMAJORINC: { res = g->gcmajorinc; g->gcmajorinc = data; break; } case LUA_GCSETSTEPMUL: { res = g->gcstepmul; g->gcstepmul = data; break; } case LUA_GCISRUNNING: { res = g->gcrunning; break; } case LUA_GCGEN: { /* change collector to generational mode */ luaC_changemode(L, KGC_GEN); break; } case LUA_GCINC: { /* change collector to incremental mode */ luaC_changemode(L, KGC_NORMAL); break; } default: res = -1; /* invalid option */ } lua_unlock(L); return res; } /* ** miscellaneous functions */ LUA_API int lua_error (lua_State *L) { lua_lock(L); api_checknelems(L, 1); luaG_errormsg(L); /* code unreachable; will unlock when control actually leaves the kernel */ return 0; /* to avoid warnings */ } LUA_API int lua_next (lua_State *L, int idx) { StkId t; int more; lua_lock(L); t = index2addr(L, idx); api_check(L, ttistable(t), "table expected"); more = luaH_next(L, hvalue(t), L->top - 1); if (more) { api_incr_top(L); } else /* no more elements */ L->top -= 1; /* remove key */ lua_unlock(L); return more; } LUA_API void lua_concat (lua_State *L, int n) { lua_lock(L); api_checknelems(L, n); if (n >= 2) { luaC_checkGC(L); luaV_concat(L, n); } else if (n == 0) { /* push empty string */ setsvalue2s(L, L->top, luaS_newlstr(L, "", 0)); api_incr_top(L); } /* else n == 1; nothing to do */ lua_unlock(L); } LUA_API void lua_len (lua_State *L, int idx) { StkId t; lua_lock(L); t = index2addr(L, idx); luaV_objlen(L, L->top, t); api_incr_top(L); lua_unlock(L); } LUA_API lua_Alloc lua_getallocf (lua_State *L, void **ud) { lua_Alloc f; lua_lock(L); if (ud) *ud = G(L)->ud; f = G(L)->frealloc; lua_unlock(L); return f; } LUA_API void lua_setallocf (lua_State *L, lua_Alloc f, void *ud) { lua_lock(L); G(L)->ud = ud; G(L)->frealloc = f; lua_unlock(L); } LUA_API void *lua_newuserdata (lua_State *L, size_t size) { Udata *u; lua_lock(L); luaC_checkGC(L); u = luaS_newudata(L, size, NULL); setuvalue(L, L->top, u); api_incr_top(L); lua_unlock(L); return u + 1; } static const char *aux_upvalue (StkId fi, int n, TValue **val, GCObject **owner) { switch (ttype(fi)) { case LUA_TCCL: { /* C closure */ CClosure *f = clCvalue(fi); if (!(1 <= n && n <= f->nupvalues)) return NULL; *val = &f->upvalue[n-1]; if (owner) *owner = obj2gco(f); return ""; } case LUA_TLCL: { /* Lua closure */ LClosure *f = clLvalue(fi); TString *name; Proto *p = f->p; if (!(1 <= n && n <= p->sizeupvalues)) return NULL; *val = f->upvals[n-1]->v; if (owner) *owner = obj2gco(f->upvals[n - 1]); name = p->upvalues[n-1].name; return (name == NULL) ? "" : getstr(name); } default: return NULL; /* not a closure */ } } LUA_API const char *lua_getupvalue (lua_State *L, int funcindex, int n) { const char *name; TValue *val = NULL; /* to avoid warnings */ lua_lock(L); name = aux_upvalue(index2addr(L, funcindex), n, &val, NULL); if (name) { setobj2s(L, L->top, val); api_incr_top(L); } lua_unlock(L); return name; } LUA_API const char *lua_setupvalue (lua_State *L, int funcindex, int n) { const char *name; TValue *val = NULL; /* to avoid warnings */ GCObject *owner = NULL; /* to avoid warnings */ StkId fi; lua_lock(L); fi = index2addr(L, funcindex); api_checknelems(L, 1); name = aux_upvalue(fi, n, &val, &owner); if (name) { L->top--; setobj(L, val, L->top); luaC_barrier(L, owner, L->top); } lua_unlock(L); return name; } static UpVal **getupvalref (lua_State *L, int fidx, int n, LClosure **pf) { LClosure *f; StkId fi = index2addr(L, fidx); api_check(L, ttisLclosure(fi), "Lua function expected"); f = clLvalue(fi); api_check(L, (1 <= n && n <= f->p->sizeupvalues), "invalid upvalue index"); if (pf) *pf = f; return &f->upvals[n - 1]; /* get its upvalue pointer */ } LUA_API void *lua_upvalueid (lua_State *L, int fidx, int n) { StkId fi = index2addr(L, fidx); switch (ttype(fi)) { case LUA_TLCL: { /* lua closure */ return *getupvalref(L, fidx, n, NULL); } case LUA_TCCL: { /* C closure */ CClosure *f = clCvalue(fi); api_check(L, 1 <= n && n <= f->nupvalues, "invalid upvalue index"); return &f->upvalue[n - 1]; } default: { api_check(L, 0, "closure expected"); return NULL; } } } LUA_API void lua_upvaluejoin (lua_State *L, int fidx1, int n1, int fidx2, int n2) { LClosure *f1; UpVal **up1 = getupvalref(L, fidx1, n1, &f1); UpVal **up2 = getupvalref(L, fidx2, n2, NULL); *up1 = *up2; luaC_objbarrier(L, f1, *up2); } april-ann-0.4.1/lua/lua-5.2.2/src/lapi.h000066400000000000000000000010351263004425400172650ustar00rootroot00000000000000/* ** $Id: lapi.h,v 2.7 2009/11/27 15:37:59 roberto Exp $ ** Auxiliary functions from Lua API ** See Copyright Notice in lua.h */ #ifndef lapi_h #define lapi_h #include "llimits.h" #include "lstate.h" #define api_incr_top(L) {L->top++; api_check(L, L->top <= L->ci->top, \ "stack overflow");} #define adjustresults(L,nres) \ { if ((nres) == LUA_MULTRET && L->ci->top < L->top) L->ci->top = L->top; } #define api_checknelems(L,n) api_check(L, (n) < (L->top - L->ci->func), \ "not enough elements in the stack") #endif april-ann-0.4.1/lua/lua-5.2.2/src/lauxlib.c000066400000000000000000000656211263004425400200060ustar00rootroot00000000000000/* ** $Id: lauxlib.c,v 1.248 2013/03/21 13:54:57 roberto Exp $ ** Auxiliary functions for building Lua libraries ** See Copyright Notice in lua.h */ #include #include #include #include #include /* This file uses only the official API of Lua. ** Any function declared here could be written as an application function. */ #define lauxlib_c #define LUA_LIB #include "lua.h" #include "lauxlib.h" /* ** {====================================================== ** Traceback ** ======================================================= */ #define LEVELS1 12 /* size of the first part of the stack */ #define LEVELS2 10 /* size of the second part of the stack */ /* ** search for 'objidx' in table at index -1. ** return 1 + string at top if find a good name. */ static int findfield (lua_State *L, int objidx, int level) { if (level == 0 || !lua_istable(L, -1)) return 0; /* not found */ lua_pushnil(L); /* start 'next' loop */ while (lua_next(L, -2)) { /* for each pair in table */ if (lua_type(L, -2) == LUA_TSTRING) { /* ignore non-string keys */ if (lua_rawequal(L, objidx, -1)) { /* found object? */ lua_pop(L, 1); /* remove value (but keep name) */ return 1; } else if (findfield(L, objidx, level - 1)) { /* try recursively */ lua_remove(L, -2); /* remove table (but keep name) */ lua_pushliteral(L, "."); lua_insert(L, -2); /* place '.' between the two names */ lua_concat(L, 3); return 1; } } lua_pop(L, 1); /* remove value */ } return 0; /* not found */ } static int pushglobalfuncname (lua_State *L, lua_Debug *ar) { int top = lua_gettop(L); lua_getinfo(L, "f", ar); /* push function */ lua_pushglobaltable(L); if (findfield(L, top + 1, 2)) { lua_copy(L, -1, top + 1); /* move name to proper place */ lua_pop(L, 2); /* remove pushed values */ return 1; } else { lua_settop(L, top); /* remove function and global table */ return 0; } } static void pushfuncname (lua_State *L, lua_Debug *ar) { if (*ar->namewhat != '\0') /* is there a name? */ lua_pushfstring(L, "function " LUA_QS, ar->name); else if (*ar->what == 'm') /* main? */ lua_pushliteral(L, "main chunk"); else if (*ar->what == 'C') { if (pushglobalfuncname(L, ar)) { lua_pushfstring(L, "function " LUA_QS, lua_tostring(L, -1)); lua_remove(L, -2); /* remove name */ } else lua_pushliteral(L, "?"); } else lua_pushfstring(L, "function <%s:%d>", ar->short_src, ar->linedefined); } static int countlevels (lua_State *L) { lua_Debug ar; int li = 1, le = 1; /* find an upper bound */ while (lua_getstack(L, le, &ar)) { li = le; le *= 2; } /* do a binary search */ while (li < le) { int m = (li + le)/2; if (lua_getstack(L, m, &ar)) li = m + 1; else le = m; } return le - 1; } LUALIB_API void luaL_traceback (lua_State *L, lua_State *L1, const char *msg, int level) { lua_Debug ar; int top = lua_gettop(L); int numlevels = countlevels(L1); int mark = (numlevels > LEVELS1 + LEVELS2) ? LEVELS1 : 0; if (msg) lua_pushfstring(L, "%s\n", msg); lua_pushliteral(L, "stack traceback:"); while (lua_getstack(L1, level++, &ar)) { if (level == mark) { /* too many levels? */ lua_pushliteral(L, "\n\t..."); /* add a '...' */ level = numlevels - LEVELS2; /* and skip to last ones */ } else { lua_getinfo(L1, "Slnt", &ar); lua_pushfstring(L, "\n\t%s:", ar.short_src); if (ar.currentline > 0) lua_pushfstring(L, "%d:", ar.currentline); lua_pushliteral(L, " in "); pushfuncname(L, &ar); if (ar.istailcall) lua_pushliteral(L, "\n\t(...tail calls...)"); lua_concat(L, lua_gettop(L) - top); } } lua_concat(L, lua_gettop(L) - top); } /* }====================================================== */ /* ** {====================================================== ** Error-report functions ** ======================================================= */ LUALIB_API int luaL_argerror (lua_State *L, int narg, const char *extramsg) { lua_Debug ar; if (!lua_getstack(L, 0, &ar)) /* no stack frame? */ return luaL_error(L, "bad argument #%d (%s)", narg, extramsg); lua_getinfo(L, "n", &ar); if (strcmp(ar.namewhat, "method") == 0) { narg--; /* do not count `self' */ if (narg == 0) /* error is in the self argument itself? */ return luaL_error(L, "calling " LUA_QS " on bad self (%s)", ar.name, extramsg); } if (ar.name == NULL) ar.name = (pushglobalfuncname(L, &ar)) ? lua_tostring(L, -1) : "?"; return luaL_error(L, "bad argument #%d to " LUA_QS " (%s)", narg, ar.name, extramsg); } static int typeerror (lua_State *L, int narg, const char *tname) { const char *msg = lua_pushfstring(L, "%s expected, got %s", tname, luaL_typename(L, narg)); return luaL_argerror(L, narg, msg); } static void tag_error (lua_State *L, int narg, int tag) { typeerror(L, narg, lua_typename(L, tag)); } LUALIB_API void luaL_where (lua_State *L, int level) { lua_Debug ar; if (lua_getstack(L, level, &ar)) { /* check function at level */ lua_getinfo(L, "Sl", &ar); /* get info about it */ if (ar.currentline > 0) { /* is there info? */ lua_pushfstring(L, "%s:%d: ", ar.short_src, ar.currentline); return; } } lua_pushliteral(L, ""); /* else, no information available... */ } LUALIB_API int luaL_error (lua_State *L, const char *fmt, ...) { va_list argp; va_start(argp, fmt); luaL_where(L, 1); lua_pushvfstring(L, fmt, argp); va_end(argp); lua_concat(L, 2); return lua_error(L); } LUALIB_API int luaL_fileresult (lua_State *L, int stat, const char *fname) { int en = errno; /* calls to Lua API may change this value */ if (stat) { lua_pushboolean(L, 1); return 1; } else { lua_pushnil(L); if (fname) lua_pushfstring(L, "%s: %s", fname, strerror(en)); else lua_pushstring(L, strerror(en)); lua_pushinteger(L, en); return 3; } } #if !defined(inspectstat) /* { */ #if defined(LUA_USE_POSIX) #include /* ** use appropriate macros to interpret 'pclose' return status */ #define inspectstat(stat,what) \ if (WIFEXITED(stat)) { stat = WEXITSTATUS(stat); } \ else if (WIFSIGNALED(stat)) { stat = WTERMSIG(stat); what = "signal"; } #else #define inspectstat(stat,what) /* no op */ #endif #endif /* } */ LUALIB_API int luaL_execresult (lua_State *L, int stat) { const char *what = "exit"; /* type of termination */ if (stat == -1) /* error? */ return luaL_fileresult(L, 0, NULL); else { inspectstat(stat, what); /* interpret result */ if (*what == 'e' && stat == 0) /* successful termination? */ lua_pushboolean(L, 1); else lua_pushnil(L); lua_pushstring(L, what); lua_pushinteger(L, stat); return 3; /* return true/nil,what,code */ } } /* }====================================================== */ /* ** {====================================================== ** Userdata's metatable manipulation ** ======================================================= */ LUALIB_API int luaL_newmetatable (lua_State *L, const char *tname) { luaL_getmetatable(L, tname); /* try to get metatable */ if (!lua_isnil(L, -1)) /* name already in use? */ return 0; /* leave previous value on top, but return 0 */ lua_pop(L, 1); lua_newtable(L); /* create metatable */ lua_pushvalue(L, -1); lua_setfield(L, LUA_REGISTRYINDEX, tname); /* registry.name = metatable */ return 1; } LUALIB_API void luaL_setmetatable (lua_State *L, const char *tname) { luaL_getmetatable(L, tname); lua_setmetatable(L, -2); } LUALIB_API void *luaL_testudata (lua_State *L, int ud, const char *tname) { void *p = lua_touserdata(L, ud); if (p != NULL) { /* value is a userdata? */ if (lua_getmetatable(L, ud)) { /* does it have a metatable? */ luaL_getmetatable(L, tname); /* get correct metatable */ if (!lua_rawequal(L, -1, -2)) /* not the same? */ p = NULL; /* value is a userdata with wrong metatable */ lua_pop(L, 2); /* remove both metatables */ return p; } } return NULL; /* value is not a userdata with a metatable */ } LUALIB_API void *luaL_checkudata (lua_State *L, int ud, const char *tname) { void *p = luaL_testudata(L, ud, tname); if (p == NULL) typeerror(L, ud, tname); return p; } /* }====================================================== */ /* ** {====================================================== ** Argument check functions ** ======================================================= */ LUALIB_API int luaL_checkoption (lua_State *L, int narg, const char *def, const char *const lst[]) { const char *name = (def) ? luaL_optstring(L, narg, def) : luaL_checkstring(L, narg); int i; for (i=0; lst[i]; i++) if (strcmp(lst[i], name) == 0) return i; return luaL_argerror(L, narg, lua_pushfstring(L, "invalid option " LUA_QS, name)); } LUALIB_API void luaL_checkstack (lua_State *L, int space, const char *msg) { /* keep some extra space to run error routines, if needed */ const int extra = LUA_MINSTACK; if (!lua_checkstack(L, space + extra)) { if (msg) luaL_error(L, "stack overflow (%s)", msg); else luaL_error(L, "stack overflow"); } } LUALIB_API void luaL_checktype (lua_State *L, int narg, int t) { if (lua_type(L, narg) != t) tag_error(L, narg, t); } LUALIB_API void luaL_checkany (lua_State *L, int narg) { if (lua_type(L, narg) == LUA_TNONE) luaL_argerror(L, narg, "value expected"); } LUALIB_API const char *luaL_checklstring (lua_State *L, int narg, size_t *len) { const char *s = lua_tolstring(L, narg, len); if (!s) tag_error(L, narg, LUA_TSTRING); return s; } LUALIB_API const char *luaL_optlstring (lua_State *L, int narg, const char *def, size_t *len) { if (lua_isnoneornil(L, narg)) { if (len) *len = (def ? strlen(def) : 0); return def; } else return luaL_checklstring(L, narg, len); } LUALIB_API lua_Number luaL_checknumber (lua_State *L, int narg) { int isnum; lua_Number d = lua_tonumberx(L, narg, &isnum); if (!isnum) tag_error(L, narg, LUA_TNUMBER); return d; } LUALIB_API lua_Number luaL_optnumber (lua_State *L, int narg, lua_Number def) { return luaL_opt(L, luaL_checknumber, narg, def); } LUALIB_API lua_Integer luaL_checkinteger (lua_State *L, int narg) { int isnum; lua_Integer d = lua_tointegerx(L, narg, &isnum); if (!isnum) tag_error(L, narg, LUA_TNUMBER); return d; } LUALIB_API lua_Unsigned luaL_checkunsigned (lua_State *L, int narg) { int isnum; lua_Unsigned d = lua_tounsignedx(L, narg, &isnum); if (!isnum) tag_error(L, narg, LUA_TNUMBER); return d; } LUALIB_API lua_Integer luaL_optinteger (lua_State *L, int narg, lua_Integer def) { return luaL_opt(L, luaL_checkinteger, narg, def); } LUALIB_API lua_Unsigned luaL_optunsigned (lua_State *L, int narg, lua_Unsigned def) { return luaL_opt(L, luaL_checkunsigned, narg, def); } /* }====================================================== */ /* ** {====================================================== ** Generic Buffer manipulation ** ======================================================= */ /* ** check whether buffer is using a userdata on the stack as a temporary ** buffer */ #define buffonstack(B) ((B)->b != (B)->initb) /* ** returns a pointer to a free area with at least 'sz' bytes */ LUALIB_API char *luaL_prepbuffsize (luaL_Buffer *B, size_t sz) { lua_State *L = B->L; if (B->size - B->n < sz) { /* not enough space? */ char *newbuff; size_t newsize = B->size * 2; /* double buffer size */ if (newsize - B->n < sz) /* not big enough? */ newsize = B->n + sz; if (newsize < B->n || newsize - B->n < sz) luaL_error(L, "buffer too large"); /* create larger buffer */ newbuff = (char *)lua_newuserdata(L, newsize * sizeof(char)); /* move content to new buffer */ memcpy(newbuff, B->b, B->n * sizeof(char)); if (buffonstack(B)) lua_remove(L, -2); /* remove old buffer */ B->b = newbuff; B->size = newsize; } return &B->b[B->n]; } LUALIB_API void luaL_addlstring (luaL_Buffer *B, const char *s, size_t l) { char *b = luaL_prepbuffsize(B, l); memcpy(b, s, l * sizeof(char)); luaL_addsize(B, l); } LUALIB_API void luaL_addstring (luaL_Buffer *B, const char *s) { luaL_addlstring(B, s, strlen(s)); } LUALIB_API void luaL_pushresult (luaL_Buffer *B) { lua_State *L = B->L; lua_pushlstring(L, B->b, B->n); if (buffonstack(B)) lua_remove(L, -2); /* remove old buffer */ } LUALIB_API void luaL_pushresultsize (luaL_Buffer *B, size_t sz) { luaL_addsize(B, sz); luaL_pushresult(B); } LUALIB_API void luaL_addvalue (luaL_Buffer *B) { lua_State *L = B->L; size_t l; const char *s = lua_tolstring(L, -1, &l); if (buffonstack(B)) lua_insert(L, -2); /* put value below buffer */ luaL_addlstring(B, s, l); lua_remove(L, (buffonstack(B)) ? -2 : -1); /* remove value */ } LUALIB_API void luaL_buffinit (lua_State *L, luaL_Buffer *B) { B->L = L; B->b = B->initb; B->n = 0; B->size = LUAL_BUFFERSIZE; } LUALIB_API char *luaL_buffinitsize (lua_State *L, luaL_Buffer *B, size_t sz) { luaL_buffinit(L, B); return luaL_prepbuffsize(B, sz); } /* }====================================================== */ /* ** {====================================================== ** Reference system ** ======================================================= */ /* index of free-list header */ #define freelist 0 LUALIB_API int luaL_ref (lua_State *L, int t) { int ref; if (lua_isnil(L, -1)) { lua_pop(L, 1); /* remove from stack */ return LUA_REFNIL; /* `nil' has a unique fixed reference */ } t = lua_absindex(L, t); lua_rawgeti(L, t, freelist); /* get first free element */ ref = (int)lua_tointeger(L, -1); /* ref = t[freelist] */ lua_pop(L, 1); /* remove it from stack */ if (ref != 0) { /* any free element? */ lua_rawgeti(L, t, ref); /* remove it from list */ lua_rawseti(L, t, freelist); /* (t[freelist] = t[ref]) */ } else /* no free elements */ ref = (int)lua_rawlen(L, t) + 1; /* get a new reference */ lua_rawseti(L, t, ref); return ref; } LUALIB_API void luaL_unref (lua_State *L, int t, int ref) { if (ref >= 0) { t = lua_absindex(L, t); lua_rawgeti(L, t, freelist); lua_rawseti(L, t, ref); /* t[ref] = t[freelist] */ lua_pushinteger(L, ref); lua_rawseti(L, t, freelist); /* t[freelist] = ref */ } } /* }====================================================== */ /* ** {====================================================== ** Load functions ** ======================================================= */ typedef struct LoadF { int n; /* number of pre-read characters */ FILE *f; /* file being read */ char buff[LUAL_BUFFERSIZE]; /* area for reading file */ } LoadF; static const char *getF (lua_State *L, void *ud, size_t *size) { LoadF *lf = (LoadF *)ud; (void)L; /* not used */ if (lf->n > 0) { /* are there pre-read characters to be read? */ *size = lf->n; /* return them (chars already in buffer) */ lf->n = 0; /* no more pre-read characters */ } else { /* read a block from file */ /* 'fread' can return > 0 *and* set the EOF flag. If next call to 'getF' called 'fread', it might still wait for user input. The next check avoids this problem. */ if (feof(lf->f)) return NULL; *size = fread(lf->buff, 1, sizeof(lf->buff), lf->f); /* read block */ } return lf->buff; } static int errfile (lua_State *L, const char *what, int fnameindex) { const char *serr = strerror(errno); const char *filename = lua_tostring(L, fnameindex) + 1; lua_pushfstring(L, "cannot %s %s: %s", what, filename, serr); lua_remove(L, fnameindex); return LUA_ERRFILE; } static int skipBOM (LoadF *lf) { const char *p = "\xEF\xBB\xBF"; /* Utf8 BOM mark */ int c; lf->n = 0; do { c = getc(lf->f); if (c == EOF || c != *(const unsigned char *)p++) return c; lf->buff[lf->n++] = c; /* to be read by the parser */ } while (*p != '\0'); lf->n = 0; /* prefix matched; discard it */ return getc(lf->f); /* return next character */ } /* ** reads the first character of file 'f' and skips an optional BOM mark ** in its beginning plus its first line if it starts with '#'. Returns ** true if it skipped the first line. In any case, '*cp' has the ** first "valid" character of the file (after the optional BOM and ** a first-line comment). */ static int skipcomment (LoadF *lf, int *cp) { int c = *cp = skipBOM(lf); if (c == '#') { /* first line is a comment (Unix exec. file)? */ do { /* skip first line */ c = getc(lf->f); } while (c != EOF && c != '\n') ; *cp = getc(lf->f); /* skip end-of-line, if present */ return 1; /* there was a comment */ } else return 0; /* no comment */ } LUALIB_API int luaL_loadfilex (lua_State *L, const char *filename, const char *mode) { LoadF lf; int status, readstatus; int c; int fnameindex = lua_gettop(L) + 1; /* index of filename on the stack */ if (filename == NULL) { lua_pushliteral(L, "=stdin"); lf.f = stdin; } else { lua_pushfstring(L, "@%s", filename); lf.f = fopen(filename, "r"); if (lf.f == NULL) return errfile(L, "open", fnameindex); } if (skipcomment(&lf, &c)) /* read initial portion */ lf.buff[lf.n++] = '\n'; /* add line to correct line numbers */ if (c == LUA_SIGNATURE[0] && filename) { /* binary file? */ lf.f = freopen(filename, "rb", lf.f); /* reopen in binary mode */ if (lf.f == NULL) return errfile(L, "reopen", fnameindex); skipcomment(&lf, &c); /* re-read initial portion */ } if (c != EOF) lf.buff[lf.n++] = c; /* 'c' is the first character of the stream */ status = lua_load(L, getF, &lf, lua_tostring(L, -1), mode); readstatus = ferror(lf.f); if (filename) fclose(lf.f); /* close file (even in case of errors) */ if (readstatus) { lua_settop(L, fnameindex); /* ignore results from `lua_load' */ return errfile(L, "read", fnameindex); } lua_remove(L, fnameindex); return status; } typedef struct LoadS { const char *s; size_t size; } LoadS; static const char *getS (lua_State *L, void *ud, size_t *size) { LoadS *ls = (LoadS *)ud; (void)L; /* not used */ if (ls->size == 0) return NULL; *size = ls->size; ls->size = 0; return ls->s; } LUALIB_API int luaL_loadbufferx (lua_State *L, const char *buff, size_t size, const char *name, const char *mode) { LoadS ls; ls.s = buff; ls.size = size; return lua_load(L, getS, &ls, name, mode); } LUALIB_API int luaL_loadstring (lua_State *L, const char *s) { return luaL_loadbuffer(L, s, strlen(s), s); } /* }====================================================== */ LUALIB_API int luaL_getmetafield (lua_State *L, int obj, const char *event) { if (!lua_getmetatable(L, obj)) /* no metatable? */ return 0; lua_pushstring(L, event); lua_rawget(L, -2); if (lua_isnil(L, -1)) { lua_pop(L, 2); /* remove metatable and metafield */ return 0; } else { lua_remove(L, -2); /* remove only metatable */ return 1; } } LUALIB_API int luaL_callmeta (lua_State *L, int obj, const char *event) { obj = lua_absindex(L, obj); if (!luaL_getmetafield(L, obj, event)) /* no metafield? */ return 0; lua_pushvalue(L, obj); lua_call(L, 1, 1); return 1; } LUALIB_API int luaL_len (lua_State *L, int idx) { int l; int isnum; lua_len(L, idx); l = (int)lua_tointegerx(L, -1, &isnum); if (!isnum) luaL_error(L, "object length is not a number"); lua_pop(L, 1); /* remove object */ return l; } LUALIB_API const char *luaL_tolstring (lua_State *L, int idx, size_t *len) { if (!luaL_callmeta(L, idx, "__tostring")) { /* no metafield? */ switch (lua_type(L, idx)) { case LUA_TNUMBER: case LUA_TSTRING: lua_pushvalue(L, idx); break; case LUA_TBOOLEAN: lua_pushstring(L, (lua_toboolean(L, idx) ? "true" : "false")); break; case LUA_TNIL: lua_pushliteral(L, "nil"); break; default: lua_pushfstring(L, "%s: %p", luaL_typename(L, idx), lua_topointer(L, idx)); break; } } return lua_tolstring(L, -1, len); } /* ** {====================================================== ** Compatibility with 5.1 module functions ** ======================================================= */ #if defined(LUA_COMPAT_MODULE) static const char *luaL_findtable (lua_State *L, int idx, const char *fname, int szhint) { const char *e; if (idx) lua_pushvalue(L, idx); do { e = strchr(fname, '.'); if (e == NULL) e = fname + strlen(fname); lua_pushlstring(L, fname, e - fname); lua_rawget(L, -2); if (lua_isnil(L, -1)) { /* no such field? */ lua_pop(L, 1); /* remove this nil */ lua_createtable(L, 0, (*e == '.' ? 1 : szhint)); /* new table for field */ lua_pushlstring(L, fname, e - fname); lua_pushvalue(L, -2); lua_settable(L, -4); /* set new table into field */ } else if (!lua_istable(L, -1)) { /* field has a non-table value? */ lua_pop(L, 2); /* remove table and value */ return fname; /* return problematic part of the name */ } lua_remove(L, -2); /* remove previous table */ fname = e + 1; } while (*e == '.'); return NULL; } /* ** Count number of elements in a luaL_Reg list. */ static int libsize (const luaL_Reg *l) { int size = 0; for (; l && l->name; l++) size++; return size; } /* ** Find or create a module table with a given name. The function ** first looks at the _LOADED table and, if that fails, try a ** global variable with that name. In any case, leaves on the stack ** the module table. */ LUALIB_API void luaL_pushmodule (lua_State *L, const char *modname, int sizehint) { luaL_findtable(L, LUA_REGISTRYINDEX, "_LOADED", 1); /* get _LOADED table */ lua_getfield(L, -1, modname); /* get _LOADED[modname] */ if (!lua_istable(L, -1)) { /* not found? */ lua_pop(L, 1); /* remove previous result */ /* try global variable (and create one if it does not exist) */ lua_pushglobaltable(L); if (luaL_findtable(L, 0, modname, sizehint) != NULL) luaL_error(L, "name conflict for module " LUA_QS, modname); lua_pushvalue(L, -1); lua_setfield(L, -3, modname); /* _LOADED[modname] = new table */ } lua_remove(L, -2); /* remove _LOADED table */ } LUALIB_API void luaL_openlib (lua_State *L, const char *libname, const luaL_Reg *l, int nup) { luaL_checkversion(L); if (libname) { luaL_pushmodule(L, libname, libsize(l)); /* get/create library table */ lua_insert(L, -(nup + 1)); /* move library table to below upvalues */ } if (l) luaL_setfuncs(L, l, nup); else lua_pop(L, nup); /* remove upvalues */ } #endif /* }====================================================== */ /* ** set functions from list 'l' into table at top - 'nup'; each ** function gets the 'nup' elements at the top as upvalues. ** Returns with only the table at the stack. */ LUALIB_API void luaL_setfuncs (lua_State *L, const luaL_Reg *l, int nup) { luaL_checkversion(L); luaL_checkstack(L, nup, "too many upvalues"); for (; l->name != NULL; l++) { /* fill the table with given functions */ int i; for (i = 0; i < nup; i++) /* copy upvalues to the top */ lua_pushvalue(L, -nup); lua_pushcclosure(L, l->func, nup); /* closure with those upvalues */ lua_setfield(L, -(nup + 2), l->name); } lua_pop(L, nup); /* remove upvalues */ } /* ** ensure that stack[idx][fname] has a table and push that table ** into the stack */ LUALIB_API int luaL_getsubtable (lua_State *L, int idx, const char *fname) { lua_getfield(L, idx, fname); if (lua_istable(L, -1)) return 1; /* table already there */ else { lua_pop(L, 1); /* remove previous result */ idx = lua_absindex(L, idx); lua_newtable(L); lua_pushvalue(L, -1); /* copy to be left at top */ lua_setfield(L, idx, fname); /* assign new table to field */ return 0; /* false, because did not find table there */ } } /* ** stripped-down 'require'. Calls 'openf' to open a module, ** registers the result in 'package.loaded' table and, if 'glb' ** is true, also registers the result in the global table. ** Leaves resulting module on the top. */ LUALIB_API void luaL_requiref (lua_State *L, const char *modname, lua_CFunction openf, int glb) { lua_pushcfunction(L, openf); lua_pushstring(L, modname); /* argument to open function */ lua_call(L, 1, 1); /* open module */ luaL_getsubtable(L, LUA_REGISTRYINDEX, "_LOADED"); lua_pushvalue(L, -2); /* make copy of module (call result) */ lua_setfield(L, -2, modname); /* _LOADED[modname] = module */ lua_pop(L, 1); /* remove _LOADED table */ if (glb) { lua_pushvalue(L, -1); /* copy of 'mod' */ lua_setglobal(L, modname); /* _G[modname] = module */ } } LUALIB_API const char *luaL_gsub (lua_State *L, const char *s, const char *p, const char *r) { const char *wild; size_t l = strlen(p); luaL_Buffer b; luaL_buffinit(L, &b); while ((wild = strstr(s, p)) != NULL) { luaL_addlstring(&b, s, wild - s); /* push prefix */ luaL_addstring(&b, r); /* push replacement in place of pattern */ s = wild + l; /* continue after `p' */ } luaL_addstring(&b, s); /* push last suffix */ luaL_pushresult(&b); return lua_tostring(L, -1); } static void *l_alloc (void *ud, void *ptr, size_t osize, size_t nsize) { (void)ud; (void)osize; /* not used */ if (nsize == 0) { free(ptr); return NULL; } else return realloc(ptr, nsize); } static int panic (lua_State *L) { luai_writestringerror("PANIC: unprotected error in call to Lua API (%s)\n", lua_tostring(L, -1)); return 0; /* return to Lua to abort */ } LUALIB_API lua_State *luaL_newstate (void) { lua_State *L = lua_newstate(l_alloc, NULL); if (L) lua_atpanic(L, &panic); return L; } LUALIB_API void luaL_checkversion_ (lua_State *L, lua_Number ver) { const lua_Number *v = lua_version(L); if (v != lua_version(NULL)) luaL_error(L, "multiple Lua VMs detected"); else if (*v != ver) luaL_error(L, "version mismatch: app. needs %f, Lua core provides %f", ver, *v); /* check conversions number -> integer types */ lua_pushnumber(L, -(lua_Number)0x1234); if (lua_tointeger(L, -1) != -0x1234 || lua_tounsigned(L, -1) != (lua_Unsigned)-0x1234) luaL_error(L, "bad conversion number->int;" " must recompile Lua with proper settings"); lua_pop(L, 1); } april-ann-0.4.1/lua/lua-5.2.2/src/lauxlib.h000066400000000000000000000162541263004425400200110ustar00rootroot00000000000000/* ** $Id: lauxlib.h,v 1.120 2011/11/29 15:55:08 roberto Exp $ ** Auxiliary functions for building Lua libraries ** See Copyright Notice in lua.h */ #ifndef lauxlib_h #define lauxlib_h #include #include #include "lua.h" /* extra error code for `luaL_load' */ #define LUA_ERRFILE (LUA_ERRERR+1) typedef struct luaL_Reg { const char *name; lua_CFunction func; } luaL_Reg; LUALIB_API void (luaL_checkversion_) (lua_State *L, lua_Number ver); #define luaL_checkversion(L) luaL_checkversion_(L, LUA_VERSION_NUM) LUALIB_API int (luaL_getmetafield) (lua_State *L, int obj, const char *e); LUALIB_API int (luaL_callmeta) (lua_State *L, int obj, const char *e); LUALIB_API const char *(luaL_tolstring) (lua_State *L, int idx, size_t *len); LUALIB_API int (luaL_argerror) (lua_State *L, int numarg, const char *extramsg); LUALIB_API const char *(luaL_checklstring) (lua_State *L, int numArg, size_t *l); LUALIB_API const char *(luaL_optlstring) (lua_State *L, int numArg, const char *def, size_t *l); LUALIB_API lua_Number (luaL_checknumber) (lua_State *L, int numArg); LUALIB_API lua_Number (luaL_optnumber) (lua_State *L, int nArg, lua_Number def); LUALIB_API lua_Integer (luaL_checkinteger) (lua_State *L, int numArg); LUALIB_API lua_Integer (luaL_optinteger) (lua_State *L, int nArg, lua_Integer def); LUALIB_API lua_Unsigned (luaL_checkunsigned) (lua_State *L, int numArg); LUALIB_API lua_Unsigned (luaL_optunsigned) (lua_State *L, int numArg, lua_Unsigned def); LUALIB_API void (luaL_checkstack) (lua_State *L, int sz, const char *msg); LUALIB_API void (luaL_checktype) (lua_State *L, int narg, int t); LUALIB_API void (luaL_checkany) (lua_State *L, int narg); LUALIB_API int (luaL_newmetatable) (lua_State *L, const char *tname); LUALIB_API void (luaL_setmetatable) (lua_State *L, const char *tname); LUALIB_API void *(luaL_testudata) (lua_State *L, int ud, const char *tname); LUALIB_API void *(luaL_checkudata) (lua_State *L, int ud, const char *tname); LUALIB_API void (luaL_where) (lua_State *L, int lvl); LUALIB_API int (luaL_error) (lua_State *L, const char *fmt, ...); LUALIB_API int (luaL_checkoption) (lua_State *L, int narg, const char *def, const char *const lst[]); LUALIB_API int (luaL_fileresult) (lua_State *L, int stat, const char *fname); LUALIB_API int (luaL_execresult) (lua_State *L, int stat); /* pre-defined references */ #define LUA_NOREF (-2) #define LUA_REFNIL (-1) LUALIB_API int (luaL_ref) (lua_State *L, int t); LUALIB_API void (luaL_unref) (lua_State *L, int t, int ref); LUALIB_API int (luaL_loadfilex) (lua_State *L, const char *filename, const char *mode); #define luaL_loadfile(L,f) luaL_loadfilex(L,f,NULL) LUALIB_API int (luaL_loadbufferx) (lua_State *L, const char *buff, size_t sz, const char *name, const char *mode); LUALIB_API int (luaL_loadstring) (lua_State *L, const char *s); LUALIB_API lua_State *(luaL_newstate) (void); LUALIB_API int (luaL_len) (lua_State *L, int idx); LUALIB_API const char *(luaL_gsub) (lua_State *L, const char *s, const char *p, const char *r); LUALIB_API void (luaL_setfuncs) (lua_State *L, const luaL_Reg *l, int nup); LUALIB_API int (luaL_getsubtable) (lua_State *L, int idx, const char *fname); LUALIB_API void (luaL_traceback) (lua_State *L, lua_State *L1, const char *msg, int level); LUALIB_API void (luaL_requiref) (lua_State *L, const char *modname, lua_CFunction openf, int glb); /* ** =============================================================== ** some useful macros ** =============================================================== */ #define luaL_newlibtable(L,l) \ lua_createtable(L, 0, sizeof(l)/sizeof((l)[0]) - 1) #define luaL_newlib(L,l) (luaL_newlibtable(L,l), luaL_setfuncs(L,l,0)) #define luaL_argcheck(L, cond,numarg,extramsg) \ ((void)((cond) || luaL_argerror(L, (numarg), (extramsg)))) #define luaL_checkstring(L,n) (luaL_checklstring(L, (n), NULL)) #define luaL_optstring(L,n,d) (luaL_optlstring(L, (n), (d), NULL)) #define luaL_checkint(L,n) ((int)luaL_checkinteger(L, (n))) #define luaL_optint(L,n,d) ((int)luaL_optinteger(L, (n), (d))) #define luaL_checklong(L,n) ((long)luaL_checkinteger(L, (n))) #define luaL_optlong(L,n,d) ((long)luaL_optinteger(L, (n), (d))) #define luaL_typename(L,i) lua_typename(L, lua_type(L,(i))) #define luaL_dofile(L, fn) \ (luaL_loadfile(L, fn) || lua_pcall(L, 0, LUA_MULTRET, 0)) #define luaL_dostring(L, s) \ (luaL_loadstring(L, s) || lua_pcall(L, 0, LUA_MULTRET, 0)) #define luaL_getmetatable(L,n) (lua_getfield(L, LUA_REGISTRYINDEX, (n))) #define luaL_opt(L,f,n,d) (lua_isnoneornil(L,(n)) ? (d) : f(L,(n))) #define luaL_loadbuffer(L,s,sz,n) luaL_loadbufferx(L,s,sz,n,NULL) /* ** {====================================================== ** Generic Buffer manipulation ** ======================================================= */ typedef struct luaL_Buffer { char *b; /* buffer address */ size_t size; /* buffer size */ size_t n; /* number of characters in buffer */ lua_State *L; char initb[LUAL_BUFFERSIZE]; /* initial buffer */ } luaL_Buffer; #define luaL_addchar(B,c) \ ((void)((B)->n < (B)->size || luaL_prepbuffsize((B), 1)), \ ((B)->b[(B)->n++] = (c))) #define luaL_addsize(B,s) ((B)->n += (s)) LUALIB_API void (luaL_buffinit) (lua_State *L, luaL_Buffer *B); LUALIB_API char *(luaL_prepbuffsize) (luaL_Buffer *B, size_t sz); LUALIB_API void (luaL_addlstring) (luaL_Buffer *B, const char *s, size_t l); LUALIB_API void (luaL_addstring) (luaL_Buffer *B, const char *s); LUALIB_API void (luaL_addvalue) (luaL_Buffer *B); LUALIB_API void (luaL_pushresult) (luaL_Buffer *B); LUALIB_API void (luaL_pushresultsize) (luaL_Buffer *B, size_t sz); LUALIB_API char *(luaL_buffinitsize) (lua_State *L, luaL_Buffer *B, size_t sz); #define luaL_prepbuffer(B) luaL_prepbuffsize(B, LUAL_BUFFERSIZE) /* }====================================================== */ /* ** {====================================================== ** File handles for IO library ** ======================================================= */ /* ** A file handle is a userdata with metatable 'LUA_FILEHANDLE' and ** initial structure 'luaL_Stream' (it may contain other fields ** after that initial structure). */ #define LUA_FILEHANDLE "FILE*" typedef struct luaL_Stream { FILE *f; /* stream (NULL for incompletely created streams) */ lua_CFunction closef; /* to close stream (NULL for closed streams) */ } luaL_Stream; /* }====================================================== */ /* compatibility with old module system */ #if defined(LUA_COMPAT_MODULE) LUALIB_API void (luaL_pushmodule) (lua_State *L, const char *modname, int sizehint); LUALIB_API void (luaL_openlib) (lua_State *L, const char *libname, const luaL_Reg *l, int nup); #define luaL_register(L,n,l) (luaL_openlib(L,(n),(l),0)) #endif #endif april-ann-0.4.1/lua/lua-5.2.2/src/lbaselib.c000066400000000000000000000277711263004425400201270ustar00rootroot00000000000000/* ** $Id: lbaselib.c,v 1.276 2013/02/21 13:44:53 roberto Exp $ ** Basic library ** See Copyright Notice in lua.h */ #include #include #include #include #define lbaselib_c #define LUA_LIB #include "lua.h" #include "lauxlib.h" #include "lualib.h" static int luaB_print (lua_State *L) { int n = lua_gettop(L); /* number of arguments */ int i; lua_getglobal(L, "tostring"); for (i=1; i<=n; i++) { const char *s; size_t l; lua_pushvalue(L, -1); /* function to be called */ lua_pushvalue(L, i); /* value to print */ lua_call(L, 1, 1); s = lua_tolstring(L, -1, &l); /* get result */ if (s == NULL) return luaL_error(L, LUA_QL("tostring") " must return a string to " LUA_QL("print")); if (i>1) luai_writestring("\t", 1); luai_writestring(s, l); lua_pop(L, 1); /* pop result */ } luai_writeline(); return 0; } #define SPACECHARS " \f\n\r\t\v" static int luaB_tonumber (lua_State *L) { if (lua_isnoneornil(L, 2)) { /* standard conversion */ int isnum; lua_Number n = lua_tonumberx(L, 1, &isnum); if (isnum) { lua_pushnumber(L, n); return 1; } /* else not a number; must be something */ luaL_checkany(L, 1); } else { size_t l; const char *s = luaL_checklstring(L, 1, &l); const char *e = s + l; /* end point for 's' */ int base = luaL_checkint(L, 2); int neg = 0; luaL_argcheck(L, 2 <= base && base <= 36, 2, "base out of range"); s += strspn(s, SPACECHARS); /* skip initial spaces */ if (*s == '-') { s++; neg = 1; } /* handle signal */ else if (*s == '+') s++; if (isalnum((unsigned char)*s)) { lua_Number n = 0; do { int digit = (isdigit((unsigned char)*s)) ? *s - '0' : toupper((unsigned char)*s) - 'A' + 10; if (digit >= base) break; /* invalid numeral; force a fail */ n = n * (lua_Number)base + (lua_Number)digit; s++; } while (isalnum((unsigned char)*s)); s += strspn(s, SPACECHARS); /* skip trailing spaces */ if (s == e) { /* no invalid trailing characters? */ lua_pushnumber(L, (neg) ? -n : n); return 1; } /* else not a number */ } /* else not a number */ } lua_pushnil(L); /* not a number */ return 1; } static int luaB_error (lua_State *L) { int level = luaL_optint(L, 2, 1); lua_settop(L, 1); if (lua_isstring(L, 1) && level > 0) { /* add extra information? */ luaL_where(L, level); lua_pushvalue(L, 1); lua_concat(L, 2); } return lua_error(L); } static int luaB_getmetatable (lua_State *L) { luaL_checkany(L, 1); if (!lua_getmetatable(L, 1)) { lua_pushnil(L); return 1; /* no metatable */ } luaL_getmetafield(L, 1, "__metatable"); return 1; /* returns either __metatable field (if present) or metatable */ } static int luaB_setmetatable (lua_State *L) { int t = lua_type(L, 2); luaL_checktype(L, 1, LUA_TTABLE); luaL_argcheck(L, t == LUA_TNIL || t == LUA_TTABLE, 2, "nil or table expected"); if (luaL_getmetafield(L, 1, "__metatable")) return luaL_error(L, "cannot change a protected metatable"); lua_settop(L, 2); lua_setmetatable(L, 1); return 1; } static int luaB_rawequal (lua_State *L) { luaL_checkany(L, 1); luaL_checkany(L, 2); lua_pushboolean(L, lua_rawequal(L, 1, 2)); return 1; } static int luaB_rawlen (lua_State *L) { int t = lua_type(L, 1); luaL_argcheck(L, t == LUA_TTABLE || t == LUA_TSTRING, 1, "table or string expected"); lua_pushinteger(L, lua_rawlen(L, 1)); return 1; } static int luaB_rawget (lua_State *L) { luaL_checktype(L, 1, LUA_TTABLE); luaL_checkany(L, 2); lua_settop(L, 2); lua_rawget(L, 1); return 1; } static int luaB_rawset (lua_State *L) { luaL_checktype(L, 1, LUA_TTABLE); luaL_checkany(L, 2); luaL_checkany(L, 3); lua_settop(L, 3); lua_rawset(L, 1); return 1; } static int luaB_collectgarbage (lua_State *L) { static const char *const opts[] = {"stop", "restart", "collect", "count", "step", "setpause", "setstepmul", "setmajorinc", "isrunning", "generational", "incremental", NULL}; static const int optsnum[] = {LUA_GCSTOP, LUA_GCRESTART, LUA_GCCOLLECT, LUA_GCCOUNT, LUA_GCSTEP, LUA_GCSETPAUSE, LUA_GCSETSTEPMUL, LUA_GCSETMAJORINC, LUA_GCISRUNNING, LUA_GCGEN, LUA_GCINC}; int o = optsnum[luaL_checkoption(L, 1, "collect", opts)]; int ex = luaL_optint(L, 2, 0); int res = lua_gc(L, o, ex); switch (o) { case LUA_GCCOUNT: { int b = lua_gc(L, LUA_GCCOUNTB, 0); lua_pushnumber(L, res + ((lua_Number)b/1024)); lua_pushinteger(L, b); return 2; } case LUA_GCSTEP: case LUA_GCISRUNNING: { lua_pushboolean(L, res); return 1; } default: { lua_pushinteger(L, res); return 1; } } } static int luaB_type (lua_State *L) { luaL_checkany(L, 1); lua_pushstring(L, luaL_typename(L, 1)); return 1; } static int pairsmeta (lua_State *L, const char *method, int iszero, lua_CFunction iter) { if (!luaL_getmetafield(L, 1, method)) { /* no metamethod? */ luaL_checktype(L, 1, LUA_TTABLE); /* argument must be a table */ lua_pushcfunction(L, iter); /* will return generator, */ lua_pushvalue(L, 1); /* state, */ if (iszero) lua_pushinteger(L, 0); /* and initial value */ else lua_pushnil(L); } else { lua_pushvalue(L, 1); /* argument 'self' to metamethod */ lua_call(L, 1, 3); /* get 3 values from metamethod */ } return 3; } static int luaB_next (lua_State *L) { luaL_checktype(L, 1, LUA_TTABLE); lua_settop(L, 2); /* create a 2nd argument if there isn't one */ if (lua_next(L, 1)) return 2; else { lua_pushnil(L); return 1; } } static int luaB_pairs (lua_State *L) { return pairsmeta(L, "__pairs", 0, luaB_next); } static int ipairsaux (lua_State *L) { int i = luaL_checkint(L, 2); luaL_checktype(L, 1, LUA_TTABLE); i++; /* next value */ lua_pushinteger(L, i); lua_rawgeti(L, 1, i); return (lua_isnil(L, -1)) ? 1 : 2; } static int luaB_ipairs (lua_State *L) { return pairsmeta(L, "__ipairs", 1, ipairsaux); } static int load_aux (lua_State *L, int status, int envidx) { if (status == LUA_OK) { if (envidx != 0) { /* 'env' parameter? */ lua_pushvalue(L, envidx); /* environment for loaded function */ if (!lua_setupvalue(L, -2, 1)) /* set it as 1st upvalue */ lua_pop(L, 1); /* remove 'env' if not used by previous call */ } return 1; } else { /* error (message is on top of the stack) */ lua_pushnil(L); lua_insert(L, -2); /* put before error message */ return 2; /* return nil plus error message */ } } static int luaB_loadfile (lua_State *L) { const char *fname = luaL_optstring(L, 1, NULL); const char *mode = luaL_optstring(L, 2, NULL); int env = (!lua_isnone(L, 3) ? 3 : 0); /* 'env' index or 0 if no 'env' */ int status = luaL_loadfilex(L, fname, mode); return load_aux(L, status, env); } /* ** {====================================================== ** Generic Read function ** ======================================================= */ /* ** reserved slot, above all arguments, to hold a copy of the returned ** string to avoid it being collected while parsed. 'load' has four ** optional arguments (chunk, source name, mode, and environment). */ #define RESERVEDSLOT 5 /* ** Reader for generic `load' function: `lua_load' uses the ** stack for internal stuff, so the reader cannot change the ** stack top. Instead, it keeps its resulting string in a ** reserved slot inside the stack. */ static const char *generic_reader (lua_State *L, void *ud, size_t *size) { (void)(ud); /* not used */ luaL_checkstack(L, 2, "too many nested functions"); lua_pushvalue(L, 1); /* get function */ lua_call(L, 0, 1); /* call it */ if (lua_isnil(L, -1)) { lua_pop(L, 1); /* pop result */ *size = 0; return NULL; } else if (!lua_isstring(L, -1)) luaL_error(L, "reader function must return a string"); lua_replace(L, RESERVEDSLOT); /* save string in reserved slot */ return lua_tolstring(L, RESERVEDSLOT, size); } static int luaB_load (lua_State *L) { int status; size_t l; const char *s = lua_tolstring(L, 1, &l); const char *mode = luaL_optstring(L, 3, "bt"); int env = (!lua_isnone(L, 4) ? 4 : 0); /* 'env' index or 0 if no 'env' */ if (s != NULL) { /* loading a string? */ const char *chunkname = luaL_optstring(L, 2, s); status = luaL_loadbufferx(L, s, l, chunkname, mode); } else { /* loading from a reader function */ const char *chunkname = luaL_optstring(L, 2, "=(load)"); luaL_checktype(L, 1, LUA_TFUNCTION); lua_settop(L, RESERVEDSLOT); /* create reserved slot */ status = lua_load(L, generic_reader, NULL, chunkname, mode); } return load_aux(L, status, env); } /* }====================================================== */ static int dofilecont (lua_State *L) { return lua_gettop(L) - 1; } static int luaB_dofile (lua_State *L) { const char *fname = luaL_optstring(L, 1, NULL); lua_settop(L, 1); if (luaL_loadfile(L, fname) != LUA_OK) return lua_error(L); lua_callk(L, 0, LUA_MULTRET, 0, dofilecont); return dofilecont(L); } static int luaB_assert (lua_State *L) { if (!lua_toboolean(L, 1)) return luaL_error(L, "%s", luaL_optstring(L, 2, "assertion failed!")); return lua_gettop(L); } static int luaB_select (lua_State *L) { int n = lua_gettop(L); if (lua_type(L, 1) == LUA_TSTRING && *lua_tostring(L, 1) == '#') { lua_pushinteger(L, n-1); return 1; } else { int i = luaL_checkint(L, 1); if (i < 0) i = n + i; else if (i > n) i = n; luaL_argcheck(L, 1 <= i, 1, "index out of range"); return n - i; } } static int finishpcall (lua_State *L, int status) { if (!lua_checkstack(L, 1)) { /* no space for extra boolean? */ lua_settop(L, 0); /* create space for return values */ lua_pushboolean(L, 0); lua_pushstring(L, "stack overflow"); return 2; /* return false, msg */ } lua_pushboolean(L, status); /* first result (status) */ lua_replace(L, 1); /* put first result in first slot */ return lua_gettop(L); } static int pcallcont (lua_State *L) { int status = lua_getctx(L, NULL); return finishpcall(L, (status == LUA_YIELD)); } static int luaB_pcall (lua_State *L) { int status; luaL_checkany(L, 1); lua_pushnil(L); lua_insert(L, 1); /* create space for status result */ status = lua_pcallk(L, lua_gettop(L) - 2, LUA_MULTRET, 0, 0, pcallcont); return finishpcall(L, (status == LUA_OK)); } static int luaB_xpcall (lua_State *L) { int status; int n = lua_gettop(L); luaL_argcheck(L, n >= 2, 2, "value expected"); lua_pushvalue(L, 1); /* exchange function... */ lua_copy(L, 2, 1); /* ...and error handler */ lua_replace(L, 2); status = lua_pcallk(L, n - 2, LUA_MULTRET, 1, 0, pcallcont); return finishpcall(L, (status == LUA_OK)); } static int luaB_tostring (lua_State *L) { luaL_checkany(L, 1); luaL_tolstring(L, 1, NULL); return 1; } static const luaL_Reg base_funcs[] = { {"assert", luaB_assert}, {"collectgarbage", luaB_collectgarbage}, {"dofile", luaB_dofile}, {"error", luaB_error}, {"getmetatable", luaB_getmetatable}, {"ipairs", luaB_ipairs}, {"loadfile", luaB_loadfile}, {"load", luaB_load}, #if defined(LUA_COMPAT_LOADSTRING) {"loadstring", luaB_load}, #endif {"next", luaB_next}, {"pairs", luaB_pairs}, {"pcall", luaB_pcall}, {"print", luaB_print}, {"rawequal", luaB_rawequal}, {"rawlen", luaB_rawlen}, {"rawget", luaB_rawget}, {"rawset", luaB_rawset}, {"select", luaB_select}, {"setmetatable", luaB_setmetatable}, {"tonumber", luaB_tonumber}, {"tostring", luaB_tostring}, {"type", luaB_type}, {"xpcall", luaB_xpcall}, {NULL, NULL} }; LUAMOD_API int luaopen_base (lua_State *L) { /* set global _G */ lua_pushglobaltable(L); lua_pushglobaltable(L); lua_setfield(L, -2, "_G"); /* open lib into global table */ luaL_setfuncs(L, base_funcs, 0); lua_pushliteral(L, LUA_VERSION); lua_setfield(L, -2, "_VERSION"); /* set global _VERSION */ return 1; } april-ann-0.4.1/lua/lua-5.2.2/src/lbitlib.c000066400000000000000000000103141263004425400177540ustar00rootroot00000000000000/* ** $Id: lbitlib.c,v 1.18 2013/03/19 13:19:12 roberto Exp $ ** Standard library for bitwise operations ** See Copyright Notice in lua.h */ #define lbitlib_c #define LUA_LIB #include "lua.h" #include "lauxlib.h" #include "lualib.h" /* number of bits to consider in a number */ #if !defined(LUA_NBITS) #define LUA_NBITS 32 #endif #define ALLONES (~(((~(lua_Unsigned)0) << (LUA_NBITS - 1)) << 1)) /* macro to trim extra bits */ #define trim(x) ((x) & ALLONES) /* builds a number with 'n' ones (1 <= n <= LUA_NBITS) */ #define mask(n) (~((ALLONES << 1) << ((n) - 1))) typedef lua_Unsigned b_uint; static b_uint andaux (lua_State *L) { int i, n = lua_gettop(L); b_uint r = ~(b_uint)0; for (i = 1; i <= n; i++) r &= luaL_checkunsigned(L, i); return trim(r); } static int b_and (lua_State *L) { b_uint r = andaux(L); lua_pushunsigned(L, r); return 1; } static int b_test (lua_State *L) { b_uint r = andaux(L); lua_pushboolean(L, r != 0); return 1; } static int b_or (lua_State *L) { int i, n = lua_gettop(L); b_uint r = 0; for (i = 1; i <= n; i++) r |= luaL_checkunsigned(L, i); lua_pushunsigned(L, trim(r)); return 1; } static int b_xor (lua_State *L) { int i, n = lua_gettop(L); b_uint r = 0; for (i = 1; i <= n; i++) r ^= luaL_checkunsigned(L, i); lua_pushunsigned(L, trim(r)); return 1; } static int b_not (lua_State *L) { b_uint r = ~luaL_checkunsigned(L, 1); lua_pushunsigned(L, trim(r)); return 1; } static int b_shift (lua_State *L, b_uint r, int i) { if (i < 0) { /* shift right? */ i = -i; r = trim(r); if (i >= LUA_NBITS) r = 0; else r >>= i; } else { /* shift left */ if (i >= LUA_NBITS) r = 0; else r <<= i; r = trim(r); } lua_pushunsigned(L, r); return 1; } static int b_lshift (lua_State *L) { return b_shift(L, luaL_checkunsigned(L, 1), luaL_checkint(L, 2)); } static int b_rshift (lua_State *L) { return b_shift(L, luaL_checkunsigned(L, 1), -luaL_checkint(L, 2)); } static int b_arshift (lua_State *L) { b_uint r = luaL_checkunsigned(L, 1); int i = luaL_checkint(L, 2); if (i < 0 || !(r & ((b_uint)1 << (LUA_NBITS - 1)))) return b_shift(L, r, -i); else { /* arithmetic shift for 'negative' number */ if (i >= LUA_NBITS) r = ALLONES; else r = trim((r >> i) | ~(~(b_uint)0 >> i)); /* add signal bit */ lua_pushunsigned(L, r); return 1; } } static int b_rot (lua_State *L, int i) { b_uint r = luaL_checkunsigned(L, 1); i &= (LUA_NBITS - 1); /* i = i % NBITS */ r = trim(r); r = (r << i) | (r >> (LUA_NBITS - i)); lua_pushunsigned(L, trim(r)); return 1; } static int b_lrot (lua_State *L) { return b_rot(L, luaL_checkint(L, 2)); } static int b_rrot (lua_State *L) { return b_rot(L, -luaL_checkint(L, 2)); } /* ** get field and width arguments for field-manipulation functions, ** checking whether they are valid. ** ('luaL_error' called without 'return' to avoid later warnings about ** 'width' being used uninitialized.) */ static int fieldargs (lua_State *L, int farg, int *width) { int f = luaL_checkint(L, farg); int w = luaL_optint(L, farg + 1, 1); luaL_argcheck(L, 0 <= f, farg, "field cannot be negative"); luaL_argcheck(L, 0 < w, farg + 1, "width must be positive"); if (f + w > LUA_NBITS) luaL_error(L, "trying to access non-existent bits"); *width = w; return f; } static int b_extract (lua_State *L) { int w; b_uint r = luaL_checkunsigned(L, 1); int f = fieldargs(L, 2, &w); r = (r >> f) & mask(w); lua_pushunsigned(L, r); return 1; } static int b_replace (lua_State *L) { int w; b_uint r = luaL_checkunsigned(L, 1); b_uint v = luaL_checkunsigned(L, 2); int f = fieldargs(L, 3, &w); int m = mask(w); v &= m; /* erase bits outside given width */ r = (r & ~(m << f)) | (v << f); lua_pushunsigned(L, r); return 1; } static const luaL_Reg bitlib[] = { {"arshift", b_arshift}, {"band", b_and}, {"bnot", b_not}, {"bor", b_or}, {"bxor", b_xor}, {"btest", b_test}, {"extract", b_extract}, {"lrotate", b_lrot}, {"lshift", b_lshift}, {"replace", b_replace}, {"rrotate", b_rrot}, {"rshift", b_rshift}, {NULL, NULL} }; LUAMOD_API int luaopen_bit32 (lua_State *L) { luaL_newlib(L, bitlib); return 1; } april-ann-0.4.1/lua/lua-5.2.2/src/lcode.c000066400000000000000000000536001263004425400174260ustar00rootroot00000000000000/* ** $Id: lcode.c,v 2.62 2012/08/16 17:34:28 roberto Exp $ ** Code generator for Lua ** See Copyright Notice in lua.h */ #include #define lcode_c #define LUA_CORE #include "lua.h" #include "lcode.h" #include "ldebug.h" #include "ldo.h" #include "lgc.h" #include "llex.h" #include "lmem.h" #include "lobject.h" #include "lopcodes.h" #include "lparser.h" #include "lstring.h" #include "ltable.h" #include "lvm.h" #define hasjumps(e) ((e)->t != (e)->f) static int isnumeral(expdesc *e) { return (e->k == VKNUM && e->t == NO_JUMP && e->f == NO_JUMP); } void luaK_nil (FuncState *fs, int from, int n) { Instruction *previous; int l = from + n - 1; /* last register to set nil */ if (fs->pc > fs->lasttarget) { /* no jumps to current position? */ previous = &fs->f->code[fs->pc-1]; if (GET_OPCODE(*previous) == OP_LOADNIL) { int pfrom = GETARG_A(*previous); int pl = pfrom + GETARG_B(*previous); if ((pfrom <= from && from <= pl + 1) || (from <= pfrom && pfrom <= l + 1)) { /* can connect both? */ if (pfrom < from) from = pfrom; /* from = min(from, pfrom) */ if (pl > l) l = pl; /* l = max(l, pl) */ SETARG_A(*previous, from); SETARG_B(*previous, l - from); return; } } /* else go through */ } luaK_codeABC(fs, OP_LOADNIL, from, n - 1, 0); /* else no optimization */ } int luaK_jump (FuncState *fs) { int jpc = fs->jpc; /* save list of jumps to here */ int j; fs->jpc = NO_JUMP; j = luaK_codeAsBx(fs, OP_JMP, 0, NO_JUMP); luaK_concat(fs, &j, jpc); /* keep them on hold */ return j; } void luaK_ret (FuncState *fs, int first, int nret) { luaK_codeABC(fs, OP_RETURN, first, nret+1, 0); } static int condjump (FuncState *fs, OpCode op, int A, int B, int C) { luaK_codeABC(fs, op, A, B, C); return luaK_jump(fs); } static void fixjump (FuncState *fs, int pc, int dest) { Instruction *jmp = &fs->f->code[pc]; int offset = dest-(pc+1); lua_assert(dest != NO_JUMP); if (abs(offset) > MAXARG_sBx) luaX_syntaxerror(fs->ls, "control structure too long"); SETARG_sBx(*jmp, offset); } /* ** returns current `pc' and marks it as a jump target (to avoid wrong ** optimizations with consecutive instructions not in the same basic block). */ int luaK_getlabel (FuncState *fs) { fs->lasttarget = fs->pc; return fs->pc; } static int getjump (FuncState *fs, int pc) { int offset = GETARG_sBx(fs->f->code[pc]); if (offset == NO_JUMP) /* point to itself represents end of list */ return NO_JUMP; /* end of list */ else return (pc+1)+offset; /* turn offset into absolute position */ } static Instruction *getjumpcontrol (FuncState *fs, int pc) { Instruction *pi = &fs->f->code[pc]; if (pc >= 1 && testTMode(GET_OPCODE(*(pi-1)))) return pi-1; else return pi; } /* ** check whether list has any jump that do not produce a value ** (or produce an inverted value) */ static int need_value (FuncState *fs, int list) { for (; list != NO_JUMP; list = getjump(fs, list)) { Instruction i = *getjumpcontrol(fs, list); if (GET_OPCODE(i) != OP_TESTSET) return 1; } return 0; /* not found */ } static int patchtestreg (FuncState *fs, int node, int reg) { Instruction *i = getjumpcontrol(fs, node); if (GET_OPCODE(*i) != OP_TESTSET) return 0; /* cannot patch other instructions */ if (reg != NO_REG && reg != GETARG_B(*i)) SETARG_A(*i, reg); else /* no register to put value or register already has the value */ *i = CREATE_ABC(OP_TEST, GETARG_B(*i), 0, GETARG_C(*i)); return 1; } static void removevalues (FuncState *fs, int list) { for (; list != NO_JUMP; list = getjump(fs, list)) patchtestreg(fs, list, NO_REG); } static void patchlistaux (FuncState *fs, int list, int vtarget, int reg, int dtarget) { while (list != NO_JUMP) { int next = getjump(fs, list); if (patchtestreg(fs, list, reg)) fixjump(fs, list, vtarget); else fixjump(fs, list, dtarget); /* jump to default target */ list = next; } } static void dischargejpc (FuncState *fs) { patchlistaux(fs, fs->jpc, fs->pc, NO_REG, fs->pc); fs->jpc = NO_JUMP; } void luaK_patchlist (FuncState *fs, int list, int target) { if (target == fs->pc) luaK_patchtohere(fs, list); else { lua_assert(target < fs->pc); patchlistaux(fs, list, target, NO_REG, target); } } LUAI_FUNC void luaK_patchclose (FuncState *fs, int list, int level) { level++; /* argument is +1 to reserve 0 as non-op */ while (list != NO_JUMP) { int next = getjump(fs, list); lua_assert(GET_OPCODE(fs->f->code[list]) == OP_JMP && (GETARG_A(fs->f->code[list]) == 0 || GETARG_A(fs->f->code[list]) >= level)); SETARG_A(fs->f->code[list], level); list = next; } } void luaK_patchtohere (FuncState *fs, int list) { luaK_getlabel(fs); luaK_concat(fs, &fs->jpc, list); } void luaK_concat (FuncState *fs, int *l1, int l2) { if (l2 == NO_JUMP) return; else if (*l1 == NO_JUMP) *l1 = l2; else { int list = *l1; int next; while ((next = getjump(fs, list)) != NO_JUMP) /* find last element */ list = next; fixjump(fs, list, l2); } } static int luaK_code (FuncState *fs, Instruction i) { Proto *f = fs->f; dischargejpc(fs); /* `pc' will change */ /* put new instruction in code array */ luaM_growvector(fs->ls->L, f->code, fs->pc, f->sizecode, Instruction, MAX_INT, "opcodes"); f->code[fs->pc] = i; /* save corresponding line information */ luaM_growvector(fs->ls->L, f->lineinfo, fs->pc, f->sizelineinfo, int, MAX_INT, "opcodes"); f->lineinfo[fs->pc] = fs->ls->lastline; return fs->pc++; } int luaK_codeABC (FuncState *fs, OpCode o, int a, int b, int c) { lua_assert(getOpMode(o) == iABC); lua_assert(getBMode(o) != OpArgN || b == 0); lua_assert(getCMode(o) != OpArgN || c == 0); lua_assert(a <= MAXARG_A && b <= MAXARG_B && c <= MAXARG_C); return luaK_code(fs, CREATE_ABC(o, a, b, c)); } int luaK_codeABx (FuncState *fs, OpCode o, int a, unsigned int bc) { lua_assert(getOpMode(o) == iABx || getOpMode(o) == iAsBx); lua_assert(getCMode(o) == OpArgN); lua_assert(a <= MAXARG_A && bc <= MAXARG_Bx); return luaK_code(fs, CREATE_ABx(o, a, bc)); } static int codeextraarg (FuncState *fs, int a) { lua_assert(a <= MAXARG_Ax); return luaK_code(fs, CREATE_Ax(OP_EXTRAARG, a)); } int luaK_codek (FuncState *fs, int reg, int k) { if (k <= MAXARG_Bx) return luaK_codeABx(fs, OP_LOADK, reg, k); else { int p = luaK_codeABx(fs, OP_LOADKX, reg, 0); codeextraarg(fs, k); return p; } } void luaK_checkstack (FuncState *fs, int n) { int newstack = fs->freereg + n; if (newstack > fs->f->maxstacksize) { if (newstack >= MAXSTACK) luaX_syntaxerror(fs->ls, "function or expression too complex"); fs->f->maxstacksize = cast_byte(newstack); } } void luaK_reserveregs (FuncState *fs, int n) { luaK_checkstack(fs, n); fs->freereg += n; } static void freereg (FuncState *fs, int reg) { if (!ISK(reg) && reg >= fs->nactvar) { fs->freereg--; lua_assert(reg == fs->freereg); } } static void freeexp (FuncState *fs, expdesc *e) { if (e->k == VNONRELOC) freereg(fs, e->u.info); } static int addk (FuncState *fs, TValue *key, TValue *v) { lua_State *L = fs->ls->L; TValue *idx = luaH_set(L, fs->h, key); Proto *f = fs->f; int k, oldsize; if (ttisnumber(idx)) { lua_Number n = nvalue(idx); lua_number2int(k, n); if (luaV_rawequalobj(&f->k[k], v)) return k; /* else may be a collision (e.g., between 0.0 and "\0\0\0\0\0\0\0\0"); go through and create a new entry for this value */ } /* constant not found; create a new entry */ oldsize = f->sizek; k = fs->nk; /* numerical value does not need GC barrier; table has no metatable, so it does not need to invalidate cache */ setnvalue(idx, cast_num(k)); luaM_growvector(L, f->k, k, f->sizek, TValue, MAXARG_Ax, "constants"); while (oldsize < f->sizek) setnilvalue(&f->k[oldsize++]); setobj(L, &f->k[k], v); fs->nk++; luaC_barrier(L, f, v); return k; } int luaK_stringK (FuncState *fs, TString *s) { TValue o; setsvalue(fs->ls->L, &o, s); return addk(fs, &o, &o); } int luaK_numberK (FuncState *fs, lua_Number r) { int n; lua_State *L = fs->ls->L; TValue o; setnvalue(&o, r); if (r == 0 || luai_numisnan(NULL, r)) { /* handle -0 and NaN */ /* use raw representation as key to avoid numeric problems */ setsvalue(L, L->top++, luaS_newlstr(L, (char *)&r, sizeof(r))); n = addk(fs, L->top - 1, &o); L->top--; } else n = addk(fs, &o, &o); /* regular case */ return n; } static int boolK (FuncState *fs, int b) { TValue o; setbvalue(&o, b); return addk(fs, &o, &o); } static int nilK (FuncState *fs) { TValue k, v; setnilvalue(&v); /* cannot use nil as key; instead use table itself to represent nil */ sethvalue(fs->ls->L, &k, fs->h); return addk(fs, &k, &v); } void luaK_setreturns (FuncState *fs, expdesc *e, int nresults) { if (e->k == VCALL) { /* expression is an open function call? */ SETARG_C(getcode(fs, e), nresults+1); } else if (e->k == VVARARG) { SETARG_B(getcode(fs, e), nresults+1); SETARG_A(getcode(fs, e), fs->freereg); luaK_reserveregs(fs, 1); } } void luaK_setoneret (FuncState *fs, expdesc *e) { if (e->k == VCALL) { /* expression is an open function call? */ e->k = VNONRELOC; e->u.info = GETARG_A(getcode(fs, e)); } else if (e->k == VVARARG) { SETARG_B(getcode(fs, e), 2); e->k = VRELOCABLE; /* can relocate its simple result */ } } void luaK_dischargevars (FuncState *fs, expdesc *e) { switch (e->k) { case VLOCAL: { e->k = VNONRELOC; break; } case VUPVAL: { e->u.info = luaK_codeABC(fs, OP_GETUPVAL, 0, e->u.info, 0); e->k = VRELOCABLE; break; } case VINDEXED: { OpCode op = OP_GETTABUP; /* assume 't' is in an upvalue */ freereg(fs, e->u.ind.idx); if (e->u.ind.vt == VLOCAL) { /* 't' is in a register? */ freereg(fs, e->u.ind.t); op = OP_GETTABLE; } e->u.info = luaK_codeABC(fs, op, 0, e->u.ind.t, e->u.ind.idx); e->k = VRELOCABLE; break; } case VVARARG: case VCALL: { luaK_setoneret(fs, e); break; } default: break; /* there is one value available (somewhere) */ } } static int code_label (FuncState *fs, int A, int b, int jump) { luaK_getlabel(fs); /* those instructions may be jump targets */ return luaK_codeABC(fs, OP_LOADBOOL, A, b, jump); } static void discharge2reg (FuncState *fs, expdesc *e, int reg) { luaK_dischargevars(fs, e); switch (e->k) { case VNIL: { luaK_nil(fs, reg, 1); break; } case VFALSE: case VTRUE: { luaK_codeABC(fs, OP_LOADBOOL, reg, e->k == VTRUE, 0); break; } case VK: { luaK_codek(fs, reg, e->u.info); break; } case VKNUM: { luaK_codek(fs, reg, luaK_numberK(fs, e->u.nval)); break; } case VRELOCABLE: { Instruction *pc = &getcode(fs, e); SETARG_A(*pc, reg); break; } case VNONRELOC: { if (reg != e->u.info) luaK_codeABC(fs, OP_MOVE, reg, e->u.info, 0); break; } default: { lua_assert(e->k == VVOID || e->k == VJMP); return; /* nothing to do... */ } } e->u.info = reg; e->k = VNONRELOC; } static void discharge2anyreg (FuncState *fs, expdesc *e) { if (e->k != VNONRELOC) { luaK_reserveregs(fs, 1); discharge2reg(fs, e, fs->freereg-1); } } static void exp2reg (FuncState *fs, expdesc *e, int reg) { discharge2reg(fs, e, reg); if (e->k == VJMP) luaK_concat(fs, &e->t, e->u.info); /* put this jump in `t' list */ if (hasjumps(e)) { int final; /* position after whole expression */ int p_f = NO_JUMP; /* position of an eventual LOAD false */ int p_t = NO_JUMP; /* position of an eventual LOAD true */ if (need_value(fs, e->t) || need_value(fs, e->f)) { int fj = (e->k == VJMP) ? NO_JUMP : luaK_jump(fs); p_f = code_label(fs, reg, 0, 1); p_t = code_label(fs, reg, 1, 0); luaK_patchtohere(fs, fj); } final = luaK_getlabel(fs); patchlistaux(fs, e->f, final, reg, p_f); patchlistaux(fs, e->t, final, reg, p_t); } e->f = e->t = NO_JUMP; e->u.info = reg; e->k = VNONRELOC; } void luaK_exp2nextreg (FuncState *fs, expdesc *e) { luaK_dischargevars(fs, e); freeexp(fs, e); luaK_reserveregs(fs, 1); exp2reg(fs, e, fs->freereg - 1); } int luaK_exp2anyreg (FuncState *fs, expdesc *e) { luaK_dischargevars(fs, e); if (e->k == VNONRELOC) { if (!hasjumps(e)) return e->u.info; /* exp is already in a register */ if (e->u.info >= fs->nactvar) { /* reg. is not a local? */ exp2reg(fs, e, e->u.info); /* put value on it */ return e->u.info; } } luaK_exp2nextreg(fs, e); /* default */ return e->u.info; } void luaK_exp2anyregup (FuncState *fs, expdesc *e) { if (e->k != VUPVAL || hasjumps(e)) luaK_exp2anyreg(fs, e); } void luaK_exp2val (FuncState *fs, expdesc *e) { if (hasjumps(e)) luaK_exp2anyreg(fs, e); else luaK_dischargevars(fs, e); } int luaK_exp2RK (FuncState *fs, expdesc *e) { luaK_exp2val(fs, e); switch (e->k) { case VTRUE: case VFALSE: case VNIL: { if (fs->nk <= MAXINDEXRK) { /* constant fits in RK operand? */ e->u.info = (e->k == VNIL) ? nilK(fs) : boolK(fs, (e->k == VTRUE)); e->k = VK; return RKASK(e->u.info); } else break; } case VKNUM: { e->u.info = luaK_numberK(fs, e->u.nval); e->k = VK; /* go through */ } case VK: { if (e->u.info <= MAXINDEXRK) /* constant fits in argC? */ return RKASK(e->u.info); else break; } default: break; } /* not a constant in the right range: put it in a register */ return luaK_exp2anyreg(fs, e); } void luaK_storevar (FuncState *fs, expdesc *var, expdesc *ex) { switch (var->k) { case VLOCAL: { freeexp(fs, ex); exp2reg(fs, ex, var->u.info); return; } case VUPVAL: { int e = luaK_exp2anyreg(fs, ex); luaK_codeABC(fs, OP_SETUPVAL, e, var->u.info, 0); break; } case VINDEXED: { OpCode op = (var->u.ind.vt == VLOCAL) ? OP_SETTABLE : OP_SETTABUP; int e = luaK_exp2RK(fs, ex); luaK_codeABC(fs, op, var->u.ind.t, var->u.ind.idx, e); break; } default: { lua_assert(0); /* invalid var kind to store */ break; } } freeexp(fs, ex); } void luaK_self (FuncState *fs, expdesc *e, expdesc *key) { int ereg; luaK_exp2anyreg(fs, e); ereg = e->u.info; /* register where 'e' was placed */ freeexp(fs, e); e->u.info = fs->freereg; /* base register for op_self */ e->k = VNONRELOC; luaK_reserveregs(fs, 2); /* function and 'self' produced by op_self */ luaK_codeABC(fs, OP_SELF, e->u.info, ereg, luaK_exp2RK(fs, key)); freeexp(fs, key); } static void invertjump (FuncState *fs, expdesc *e) { Instruction *pc = getjumpcontrol(fs, e->u.info); lua_assert(testTMode(GET_OPCODE(*pc)) && GET_OPCODE(*pc) != OP_TESTSET && GET_OPCODE(*pc) != OP_TEST); SETARG_A(*pc, !(GETARG_A(*pc))); } static int jumponcond (FuncState *fs, expdesc *e, int cond) { if (e->k == VRELOCABLE) { Instruction ie = getcode(fs, e); if (GET_OPCODE(ie) == OP_NOT) { fs->pc--; /* remove previous OP_NOT */ return condjump(fs, OP_TEST, GETARG_B(ie), 0, !cond); } /* else go through */ } discharge2anyreg(fs, e); freeexp(fs, e); return condjump(fs, OP_TESTSET, NO_REG, e->u.info, cond); } void luaK_goiftrue (FuncState *fs, expdesc *e) { int pc; /* pc of last jump */ luaK_dischargevars(fs, e); switch (e->k) { case VJMP: { invertjump(fs, e); pc = e->u.info; break; } case VK: case VKNUM: case VTRUE: { pc = NO_JUMP; /* always true; do nothing */ break; } default: { pc = jumponcond(fs, e, 0); break; } } luaK_concat(fs, &e->f, pc); /* insert last jump in `f' list */ luaK_patchtohere(fs, e->t); e->t = NO_JUMP; } void luaK_goiffalse (FuncState *fs, expdesc *e) { int pc; /* pc of last jump */ luaK_dischargevars(fs, e); switch (e->k) { case VJMP: { pc = e->u.info; break; } case VNIL: case VFALSE: { pc = NO_JUMP; /* always false; do nothing */ break; } default: { pc = jumponcond(fs, e, 1); break; } } luaK_concat(fs, &e->t, pc); /* insert last jump in `t' list */ luaK_patchtohere(fs, e->f); e->f = NO_JUMP; } static void codenot (FuncState *fs, expdesc *e) { luaK_dischargevars(fs, e); switch (e->k) { case VNIL: case VFALSE: { e->k = VTRUE; break; } case VK: case VKNUM: case VTRUE: { e->k = VFALSE; break; } case VJMP: { invertjump(fs, e); break; } case VRELOCABLE: case VNONRELOC: { discharge2anyreg(fs, e); freeexp(fs, e); e->u.info = luaK_codeABC(fs, OP_NOT, 0, e->u.info, 0); e->k = VRELOCABLE; break; } default: { lua_assert(0); /* cannot happen */ break; } } /* interchange true and false lists */ { int temp = e->f; e->f = e->t; e->t = temp; } removevalues(fs, e->f); removevalues(fs, e->t); } void luaK_indexed (FuncState *fs, expdesc *t, expdesc *k) { lua_assert(!hasjumps(t)); t->u.ind.t = t->u.info; t->u.ind.idx = luaK_exp2RK(fs, k); t->u.ind.vt = (t->k == VUPVAL) ? VUPVAL : check_exp(vkisinreg(t->k), VLOCAL); t->k = VINDEXED; } static int constfolding (OpCode op, expdesc *e1, expdesc *e2) { lua_Number r; if (!isnumeral(e1) || !isnumeral(e2)) return 0; if ((op == OP_DIV || op == OP_MOD) && e2->u.nval == 0) return 0; /* do not attempt to divide by 0 */ r = luaO_arith(op - OP_ADD + LUA_OPADD, e1->u.nval, e2->u.nval); e1->u.nval = r; return 1; } static void codearith (FuncState *fs, OpCode op, expdesc *e1, expdesc *e2, int line) { if (constfolding(op, e1, e2)) return; else { int o2 = (op != OP_UNM && op != OP_LEN) ? luaK_exp2RK(fs, e2) : 0; int o1 = luaK_exp2RK(fs, e1); if (o1 > o2) { freeexp(fs, e1); freeexp(fs, e2); } else { freeexp(fs, e2); freeexp(fs, e1); } e1->u.info = luaK_codeABC(fs, op, 0, o1, o2); e1->k = VRELOCABLE; luaK_fixline(fs, line); } } static void codecomp (FuncState *fs, OpCode op, int cond, expdesc *e1, expdesc *e2) { int o1 = luaK_exp2RK(fs, e1); int o2 = luaK_exp2RK(fs, e2); freeexp(fs, e2); freeexp(fs, e1); if (cond == 0 && op != OP_EQ) { int temp; /* exchange args to replace by `<' or `<=' */ temp = o1; o1 = o2; o2 = temp; /* o1 <==> o2 */ cond = 1; } e1->u.info = condjump(fs, op, cond, o1, o2); e1->k = VJMP; } void luaK_prefix (FuncState *fs, UnOpr op, expdesc *e, int line) { expdesc e2; e2.t = e2.f = NO_JUMP; e2.k = VKNUM; e2.u.nval = 0; switch (op) { case OPR_MINUS: { if (isnumeral(e)) /* minus constant? */ e->u.nval = luai_numunm(NULL, e->u.nval); /* fold it */ else { luaK_exp2anyreg(fs, e); codearith(fs, OP_UNM, e, &e2, line); } break; } case OPR_NOT: codenot(fs, e); break; case OPR_LEN: { luaK_exp2anyreg(fs, e); /* cannot operate on constants */ codearith(fs, OP_LEN, e, &e2, line); break; } default: lua_assert(0); } } void luaK_infix (FuncState *fs, BinOpr op, expdesc *v) { switch (op) { case OPR_AND: { luaK_goiftrue(fs, v); break; } case OPR_OR: { luaK_goiffalse(fs, v); break; } case OPR_CONCAT: { luaK_exp2nextreg(fs, v); /* operand must be on the `stack' */ break; } case OPR_ADD: case OPR_SUB: case OPR_MUL: case OPR_DIV: case OPR_MOD: case OPR_POW: { if (!isnumeral(v)) luaK_exp2RK(fs, v); break; } default: { luaK_exp2RK(fs, v); break; } } } void luaK_posfix (FuncState *fs, BinOpr op, expdesc *e1, expdesc *e2, int line) { switch (op) { case OPR_AND: { lua_assert(e1->t == NO_JUMP); /* list must be closed */ luaK_dischargevars(fs, e2); luaK_concat(fs, &e2->f, e1->f); *e1 = *e2; break; } case OPR_OR: { lua_assert(e1->f == NO_JUMP); /* list must be closed */ luaK_dischargevars(fs, e2); luaK_concat(fs, &e2->t, e1->t); *e1 = *e2; break; } case OPR_CONCAT: { luaK_exp2val(fs, e2); if (e2->k == VRELOCABLE && GET_OPCODE(getcode(fs, e2)) == OP_CONCAT) { lua_assert(e1->u.info == GETARG_B(getcode(fs, e2))-1); freeexp(fs, e1); SETARG_B(getcode(fs, e2), e1->u.info); e1->k = VRELOCABLE; e1->u.info = e2->u.info; } else { luaK_exp2nextreg(fs, e2); /* operand must be on the 'stack' */ codearith(fs, OP_CONCAT, e1, e2, line); } break; } case OPR_ADD: case OPR_SUB: case OPR_MUL: case OPR_DIV: case OPR_MOD: case OPR_POW: { codearith(fs, cast(OpCode, op - OPR_ADD + OP_ADD), e1, e2, line); break; } case OPR_EQ: case OPR_LT: case OPR_LE: { codecomp(fs, cast(OpCode, op - OPR_EQ + OP_EQ), 1, e1, e2); break; } case OPR_NE: case OPR_GT: case OPR_GE: { codecomp(fs, cast(OpCode, op - OPR_NE + OP_EQ), 0, e1, e2); break; } default: lua_assert(0); } } void luaK_fixline (FuncState *fs, int line) { fs->f->lineinfo[fs->pc - 1] = line; } void luaK_setlist (FuncState *fs, int base, int nelems, int tostore) { int c = (nelems - 1)/LFIELDS_PER_FLUSH + 1; int b = (tostore == LUA_MULTRET) ? 0 : tostore; lua_assert(tostore != 0); if (c <= MAXARG_C) luaK_codeABC(fs, OP_SETLIST, base, b, c); else if (c <= MAXARG_Ax) { luaK_codeABC(fs, OP_SETLIST, base, b, 0); codeextraarg(fs, c); } else luaX_syntaxerror(fs->ls, "constructor too long"); fs->freereg = base + 1; /* free registers with list values */ } april-ann-0.4.1/lua/lua-5.2.2/src/lcode.h000066400000000000000000000060541263004425400174340ustar00rootroot00000000000000/* ** $Id: lcode.h,v 1.58 2011/08/30 16:26:41 roberto Exp $ ** Code generator for Lua ** See Copyright Notice in lua.h */ #ifndef lcode_h #define lcode_h #include "llex.h" #include "lobject.h" #include "lopcodes.h" #include "lparser.h" /* ** Marks the end of a patch list. It is an invalid value both as an absolute ** address, and as a list link (would link an element to itself). */ #define NO_JUMP (-1) /* ** grep "ORDER OPR" if you change these enums (ORDER OP) */ typedef enum BinOpr { OPR_ADD, OPR_SUB, OPR_MUL, OPR_DIV, OPR_MOD, OPR_POW, OPR_CONCAT, OPR_EQ, OPR_LT, OPR_LE, OPR_NE, OPR_GT, OPR_GE, OPR_AND, OPR_OR, OPR_NOBINOPR } BinOpr; typedef enum UnOpr { OPR_MINUS, OPR_NOT, OPR_LEN, OPR_NOUNOPR } UnOpr; #define getcode(fs,e) ((fs)->f->code[(e)->u.info]) #define luaK_codeAsBx(fs,o,A,sBx) luaK_codeABx(fs,o,A,(sBx)+MAXARG_sBx) #define luaK_setmultret(fs,e) luaK_setreturns(fs, e, LUA_MULTRET) #define luaK_jumpto(fs,t) luaK_patchlist(fs, luaK_jump(fs), t) LUAI_FUNC int luaK_codeABx (FuncState *fs, OpCode o, int A, unsigned int Bx); LUAI_FUNC int luaK_codeABC (FuncState *fs, OpCode o, int A, int B, int C); LUAI_FUNC int luaK_codek (FuncState *fs, int reg, int k); LUAI_FUNC void luaK_fixline (FuncState *fs, int line); LUAI_FUNC void luaK_nil (FuncState *fs, int from, int n); LUAI_FUNC void luaK_reserveregs (FuncState *fs, int n); LUAI_FUNC void luaK_checkstack (FuncState *fs, int n); LUAI_FUNC int luaK_stringK (FuncState *fs, TString *s); LUAI_FUNC int luaK_numberK (FuncState *fs, lua_Number r); LUAI_FUNC void luaK_dischargevars (FuncState *fs, expdesc *e); LUAI_FUNC int luaK_exp2anyreg (FuncState *fs, expdesc *e); LUAI_FUNC void luaK_exp2anyregup (FuncState *fs, expdesc *e); LUAI_FUNC void luaK_exp2nextreg (FuncState *fs, expdesc *e); LUAI_FUNC void luaK_exp2val (FuncState *fs, expdesc *e); LUAI_FUNC int luaK_exp2RK (FuncState *fs, expdesc *e); LUAI_FUNC void luaK_self (FuncState *fs, expdesc *e, expdesc *key); LUAI_FUNC void luaK_indexed (FuncState *fs, expdesc *t, expdesc *k); LUAI_FUNC void luaK_goiftrue (FuncState *fs, expdesc *e); LUAI_FUNC void luaK_goiffalse (FuncState *fs, expdesc *e); LUAI_FUNC void luaK_storevar (FuncState *fs, expdesc *var, expdesc *e); LUAI_FUNC void luaK_setreturns (FuncState *fs, expdesc *e, int nresults); LUAI_FUNC void luaK_setoneret (FuncState *fs, expdesc *e); LUAI_FUNC int luaK_jump (FuncState *fs); LUAI_FUNC void luaK_ret (FuncState *fs, int first, int nret); LUAI_FUNC void luaK_patchlist (FuncState *fs, int list, int target); LUAI_FUNC void luaK_patchtohere (FuncState *fs, int list); LUAI_FUNC void luaK_patchclose (FuncState *fs, int list, int level); LUAI_FUNC void luaK_concat (FuncState *fs, int *l1, int l2); LUAI_FUNC int luaK_getlabel (FuncState *fs); LUAI_FUNC void luaK_prefix (FuncState *fs, UnOpr op, expdesc *v, int line); LUAI_FUNC void luaK_infix (FuncState *fs, BinOpr op, expdesc *v); LUAI_FUNC void luaK_posfix (FuncState *fs, BinOpr op, expdesc *v1, expdesc *v2, int line); LUAI_FUNC void luaK_setlist (FuncState *fs, int base, int nelems, int tostore); #endif april-ann-0.4.1/lua/lua-5.2.2/src/lcorolib.c000066400000000000000000000067631263004425400201550ustar00rootroot00000000000000/* ** $Id: lcorolib.c,v 1.5 2013/02/21 13:44:53 roberto Exp $ ** Coroutine Library ** See Copyright Notice in lua.h */ #include #define lcorolib_c #define LUA_LIB #include "lua.h" #include "lauxlib.h" #include "lualib.h" static int auxresume (lua_State *L, lua_State *co, int narg) { int status; if (!lua_checkstack(co, narg)) { lua_pushliteral(L, "too many arguments to resume"); return -1; /* error flag */ } if (lua_status(co) == LUA_OK && lua_gettop(co) == 0) { lua_pushliteral(L, "cannot resume dead coroutine"); return -1; /* error flag */ } lua_xmove(L, co, narg); status = lua_resume(co, L, narg); if (status == LUA_OK || status == LUA_YIELD) { int nres = lua_gettop(co); if (!lua_checkstack(L, nres + 1)) { lua_pop(co, nres); /* remove results anyway */ lua_pushliteral(L, "too many results to resume"); return -1; /* error flag */ } lua_xmove(co, L, nres); /* move yielded values */ return nres; } else { lua_xmove(co, L, 1); /* move error message */ return -1; /* error flag */ } } static int luaB_coresume (lua_State *L) { lua_State *co = lua_tothread(L, 1); int r; luaL_argcheck(L, co, 1, "coroutine expected"); r = auxresume(L, co, lua_gettop(L) - 1); if (r < 0) { lua_pushboolean(L, 0); lua_insert(L, -2); return 2; /* return false + error message */ } else { lua_pushboolean(L, 1); lua_insert(L, -(r + 1)); return r + 1; /* return true + `resume' returns */ } } static int luaB_auxwrap (lua_State *L) { lua_State *co = lua_tothread(L, lua_upvalueindex(1)); int r = auxresume(L, co, lua_gettop(L)); if (r < 0) { if (lua_isstring(L, -1)) { /* error object is a string? */ luaL_where(L, 1); /* add extra info */ lua_insert(L, -2); lua_concat(L, 2); } return lua_error(L); /* propagate error */ } return r; } static int luaB_cocreate (lua_State *L) { lua_State *NL; luaL_checktype(L, 1, LUA_TFUNCTION); NL = lua_newthread(L); lua_pushvalue(L, 1); /* move function to top */ lua_xmove(L, NL, 1); /* move function from L to NL */ return 1; } static int luaB_cowrap (lua_State *L) { luaB_cocreate(L); lua_pushcclosure(L, luaB_auxwrap, 1); return 1; } static int luaB_yield (lua_State *L) { return lua_yield(L, lua_gettop(L)); } static int luaB_costatus (lua_State *L) { lua_State *co = lua_tothread(L, 1); luaL_argcheck(L, co, 1, "coroutine expected"); if (L == co) lua_pushliteral(L, "running"); else { switch (lua_status(co)) { case LUA_YIELD: lua_pushliteral(L, "suspended"); break; case LUA_OK: { lua_Debug ar; if (lua_getstack(co, 0, &ar) > 0) /* does it have frames? */ lua_pushliteral(L, "normal"); /* it is running */ else if (lua_gettop(co) == 0) lua_pushliteral(L, "dead"); else lua_pushliteral(L, "suspended"); /* initial state */ break; } default: /* some error occurred */ lua_pushliteral(L, "dead"); break; } } return 1; } static int luaB_corunning (lua_State *L) { int ismain = lua_pushthread(L); lua_pushboolean(L, ismain); return 2; } static const luaL_Reg co_funcs[] = { {"create", luaB_cocreate}, {"resume", luaB_coresume}, {"running", luaB_corunning}, {"status", luaB_costatus}, {"wrap", luaB_cowrap}, {"yield", luaB_yield}, {NULL, NULL} }; LUAMOD_API int luaopen_coroutine (lua_State *L) { luaL_newlib(L, co_funcs); return 1; } april-ann-0.4.1/lua/lua-5.2.2/src/lctype.c000066400000000000000000000043671263004425400176460ustar00rootroot00000000000000/* ** $Id: lctype.c,v 1.11 2011/10/03 16:19:23 roberto Exp $ ** 'ctype' functions for Lua ** See Copyright Notice in lua.h */ #define lctype_c #define LUA_CORE #include "lctype.h" #if !LUA_USE_CTYPE /* { */ #include LUAI_DDEF const lu_byte luai_ctype_[UCHAR_MAX + 2] = { 0x00, /* EOZ */ 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, /* 0. */ 0x00, 0x08, 0x08, 0x08, 0x08, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, /* 1. */ 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0c, 0x04, 0x04, 0x04, 0x04, 0x04, 0x04, 0x04, /* 2. */ 0x04, 0x04, 0x04, 0x04, 0x04, 0x04, 0x04, 0x04, 0x16, 0x16, 0x16, 0x16, 0x16, 0x16, 0x16, 0x16, /* 3. */ 0x16, 0x16, 0x04, 0x04, 0x04, 0x04, 0x04, 0x04, 0x04, 0x15, 0x15, 0x15, 0x15, 0x15, 0x15, 0x05, /* 4. */ 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, /* 5. */ 0x05, 0x05, 0x05, 0x04, 0x04, 0x04, 0x04, 0x05, 0x04, 0x15, 0x15, 0x15, 0x15, 0x15, 0x15, 0x05, /* 6. */ 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, 0x05, /* 7. */ 0x05, 0x05, 0x05, 0x04, 0x04, 0x04, 0x04, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, /* 8. */ 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, /* 9. */ 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, /* a. */ 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, /* b. */ 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, /* c. */ 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, /* d. */ 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, /* e. */ 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, /* f. */ 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, }; #endif /* } */ april-ann-0.4.1/lua/lua-5.2.2/src/lctype.h000066400000000000000000000034551263004425400176500ustar00rootroot00000000000000/* ** $Id: lctype.h,v 1.12 2011/07/15 12:50:29 roberto Exp $ ** 'ctype' functions for Lua ** See Copyright Notice in lua.h */ #ifndef lctype_h #define lctype_h #include "lua.h" /* ** WARNING: the functions defined here do not necessarily correspond ** to the similar functions in the standard C ctype.h. They are ** optimized for the specific needs of Lua */ #if !defined(LUA_USE_CTYPE) #if 'A' == 65 && '0' == 48 /* ASCII case: can use its own tables; faster and fixed */ #define LUA_USE_CTYPE 0 #else /* must use standard C ctype */ #define LUA_USE_CTYPE 1 #endif #endif #if !LUA_USE_CTYPE /* { */ #include #include "llimits.h" #define ALPHABIT 0 #define DIGITBIT 1 #define PRINTBIT 2 #define SPACEBIT 3 #define XDIGITBIT 4 #define MASK(B) (1 << (B)) /* ** add 1 to char to allow index -1 (EOZ) */ #define testprop(c,p) (luai_ctype_[(c)+1] & (p)) /* ** 'lalpha' (Lua alphabetic) and 'lalnum' (Lua alphanumeric) both include '_' */ #define lislalpha(c) testprop(c, MASK(ALPHABIT)) #define lislalnum(c) testprop(c, (MASK(ALPHABIT) | MASK(DIGITBIT))) #define lisdigit(c) testprop(c, MASK(DIGITBIT)) #define lisspace(c) testprop(c, MASK(SPACEBIT)) #define lisprint(c) testprop(c, MASK(PRINTBIT)) #define lisxdigit(c) testprop(c, MASK(XDIGITBIT)) /* ** this 'ltolower' only works for alphabetic characters */ #define ltolower(c) ((c) | ('A' ^ 'a')) /* two more entries for 0 and -1 (EOZ) */ LUAI_DDEC const lu_byte luai_ctype_[UCHAR_MAX + 2]; #else /* }{ */ /* ** use standard C ctypes */ #include #define lislalpha(c) (isalpha(c) || (c) == '_') #define lislalnum(c) (isalnum(c) || (c) == '_') #define lisdigit(c) (isdigit(c)) #define lisspace(c) (isspace(c)) #define lisprint(c) (isprint(c)) #define lisxdigit(c) (isxdigit(c)) #define ltolower(c) (tolower(c)) #endif /* } */ #endif april-ann-0.4.1/lua/lua-5.2.2/src/ldblib.c000066400000000000000000000235351263004425400175740ustar00rootroot00000000000000/* ** $Id: ldblib.c,v 1.132 2012/01/19 20:14:44 roberto Exp $ ** Interface from Lua to its debug API ** See Copyright Notice in lua.h */ #include #include #include #define ldblib_c #define LUA_LIB #include "lua.h" #include "lauxlib.h" #include "lualib.h" #define HOOKKEY "_HKEY" static int db_getregistry (lua_State *L) { lua_pushvalue(L, LUA_REGISTRYINDEX); return 1; } static int db_getmetatable (lua_State *L) { luaL_checkany(L, 1); if (!lua_getmetatable(L, 1)) { lua_pushnil(L); /* no metatable */ } return 1; } static int db_setmetatable (lua_State *L) { int t = lua_type(L, 2); luaL_argcheck(L, t == LUA_TNIL || t == LUA_TTABLE, 2, "nil or table expected"); lua_settop(L, 2); lua_setmetatable(L, 1); return 1; /* return 1st argument */ } static int db_getuservalue (lua_State *L) { if (lua_type(L, 1) != LUA_TUSERDATA) lua_pushnil(L); else lua_getuservalue(L, 1); return 1; } static int db_setuservalue (lua_State *L) { if (lua_type(L, 1) == LUA_TLIGHTUSERDATA) luaL_argerror(L, 1, "full userdata expected, got light userdata"); luaL_checktype(L, 1, LUA_TUSERDATA); if (!lua_isnoneornil(L, 2)) luaL_checktype(L, 2, LUA_TTABLE); lua_settop(L, 2); lua_setuservalue(L, 1); return 1; } static void settabss (lua_State *L, const char *i, const char *v) { lua_pushstring(L, v); lua_setfield(L, -2, i); } static void settabsi (lua_State *L, const char *i, int v) { lua_pushinteger(L, v); lua_setfield(L, -2, i); } static void settabsb (lua_State *L, const char *i, int v) { lua_pushboolean(L, v); lua_setfield(L, -2, i); } static lua_State *getthread (lua_State *L, int *arg) { if (lua_isthread(L, 1)) { *arg = 1; return lua_tothread(L, 1); } else { *arg = 0; return L; } } static void treatstackoption (lua_State *L, lua_State *L1, const char *fname) { if (L == L1) { lua_pushvalue(L, -2); lua_remove(L, -3); } else lua_xmove(L1, L, 1); lua_setfield(L, -2, fname); } static int db_getinfo (lua_State *L) { lua_Debug ar; int arg; lua_State *L1 = getthread(L, &arg); const char *options = luaL_optstring(L, arg+2, "flnStu"); if (lua_isnumber(L, arg+1)) { if (!lua_getstack(L1, (int)lua_tointeger(L, arg+1), &ar)) { lua_pushnil(L); /* level out of range */ return 1; } } else if (lua_isfunction(L, arg+1)) { lua_pushfstring(L, ">%s", options); options = lua_tostring(L, -1); lua_pushvalue(L, arg+1); lua_xmove(L, L1, 1); } else return luaL_argerror(L, arg+1, "function or level expected"); if (!lua_getinfo(L1, options, &ar)) return luaL_argerror(L, arg+2, "invalid option"); lua_createtable(L, 0, 2); if (strchr(options, 'S')) { settabss(L, "source", ar.source); settabss(L, "short_src", ar.short_src); settabsi(L, "linedefined", ar.linedefined); settabsi(L, "lastlinedefined", ar.lastlinedefined); settabss(L, "what", ar.what); } if (strchr(options, 'l')) settabsi(L, "currentline", ar.currentline); if (strchr(options, 'u')) { settabsi(L, "nups", ar.nups); settabsi(L, "nparams", ar.nparams); settabsb(L, "isvararg", ar.isvararg); } if (strchr(options, 'n')) { settabss(L, "name", ar.name); settabss(L, "namewhat", ar.namewhat); } if (strchr(options, 't')) settabsb(L, "istailcall", ar.istailcall); if (strchr(options, 'L')) treatstackoption(L, L1, "activelines"); if (strchr(options, 'f')) treatstackoption(L, L1, "func"); return 1; /* return table */ } static int db_getlocal (lua_State *L) { int arg; lua_State *L1 = getthread(L, &arg); lua_Debug ar; const char *name; int nvar = luaL_checkint(L, arg+2); /* local-variable index */ if (lua_isfunction(L, arg + 1)) { /* function argument? */ lua_pushvalue(L, arg + 1); /* push function */ lua_pushstring(L, lua_getlocal(L, NULL, nvar)); /* push local name */ return 1; } else { /* stack-level argument */ if (!lua_getstack(L1, luaL_checkint(L, arg+1), &ar)) /* out of range? */ return luaL_argerror(L, arg+1, "level out of range"); name = lua_getlocal(L1, &ar, nvar); if (name) { lua_xmove(L1, L, 1); /* push local value */ lua_pushstring(L, name); /* push name */ lua_pushvalue(L, -2); /* re-order */ return 2; } else { lua_pushnil(L); /* no name (nor value) */ return 1; } } } static int db_setlocal (lua_State *L) { int arg; lua_State *L1 = getthread(L, &arg); lua_Debug ar; if (!lua_getstack(L1, luaL_checkint(L, arg+1), &ar)) /* out of range? */ return luaL_argerror(L, arg+1, "level out of range"); luaL_checkany(L, arg+3); lua_settop(L, arg+3); lua_xmove(L, L1, 1); lua_pushstring(L, lua_setlocal(L1, &ar, luaL_checkint(L, arg+2))); return 1; } static int auxupvalue (lua_State *L, int get) { const char *name; int n = luaL_checkint(L, 2); luaL_checktype(L, 1, LUA_TFUNCTION); name = get ? lua_getupvalue(L, 1, n) : lua_setupvalue(L, 1, n); if (name == NULL) return 0; lua_pushstring(L, name); lua_insert(L, -(get+1)); return get + 1; } static int db_getupvalue (lua_State *L) { return auxupvalue(L, 1); } static int db_setupvalue (lua_State *L) { luaL_checkany(L, 3); return auxupvalue(L, 0); } static int checkupval (lua_State *L, int argf, int argnup) { lua_Debug ar; int nup = luaL_checkint(L, argnup); luaL_checktype(L, argf, LUA_TFUNCTION); lua_pushvalue(L, argf); lua_getinfo(L, ">u", &ar); luaL_argcheck(L, 1 <= nup && nup <= ar.nups, argnup, "invalid upvalue index"); return nup; } static int db_upvalueid (lua_State *L) { int n = checkupval(L, 1, 2); lua_pushlightuserdata(L, lua_upvalueid(L, 1, n)); return 1; } static int db_upvaluejoin (lua_State *L) { int n1 = checkupval(L, 1, 2); int n2 = checkupval(L, 3, 4); luaL_argcheck(L, !lua_iscfunction(L, 1), 1, "Lua function expected"); luaL_argcheck(L, !lua_iscfunction(L, 3), 3, "Lua function expected"); lua_upvaluejoin(L, 1, n1, 3, n2); return 0; } #define gethooktable(L) luaL_getsubtable(L, LUA_REGISTRYINDEX, HOOKKEY) static void hookf (lua_State *L, lua_Debug *ar) { static const char *const hooknames[] = {"call", "return", "line", "count", "tail call"}; gethooktable(L); lua_pushthread(L); lua_rawget(L, -2); if (lua_isfunction(L, -1)) { lua_pushstring(L, hooknames[(int)ar->event]); if (ar->currentline >= 0) lua_pushinteger(L, ar->currentline); else lua_pushnil(L); lua_assert(lua_getinfo(L, "lS", ar)); lua_call(L, 2, 0); } } static int makemask (const char *smask, int count) { int mask = 0; if (strchr(smask, 'c')) mask |= LUA_MASKCALL; if (strchr(smask, 'r')) mask |= LUA_MASKRET; if (strchr(smask, 'l')) mask |= LUA_MASKLINE; if (count > 0) mask |= LUA_MASKCOUNT; return mask; } static char *unmakemask (int mask, char *smask) { int i = 0; if (mask & LUA_MASKCALL) smask[i++] = 'c'; if (mask & LUA_MASKRET) smask[i++] = 'r'; if (mask & LUA_MASKLINE) smask[i++] = 'l'; smask[i] = '\0'; return smask; } static int db_sethook (lua_State *L) { int arg, mask, count; lua_Hook func; lua_State *L1 = getthread(L, &arg); if (lua_isnoneornil(L, arg+1)) { lua_settop(L, arg+1); func = NULL; mask = 0; count = 0; /* turn off hooks */ } else { const char *smask = luaL_checkstring(L, arg+2); luaL_checktype(L, arg+1, LUA_TFUNCTION); count = luaL_optint(L, arg+3, 0); func = hookf; mask = makemask(smask, count); } if (gethooktable(L) == 0) { /* creating hook table? */ lua_pushstring(L, "k"); lua_setfield(L, -2, "__mode"); /** hooktable.__mode = "k" */ lua_pushvalue(L, -1); lua_setmetatable(L, -2); /* setmetatable(hooktable) = hooktable */ } lua_pushthread(L1); lua_xmove(L1, L, 1); lua_pushvalue(L, arg+1); lua_rawset(L, -3); /* set new hook */ lua_sethook(L1, func, mask, count); /* set hooks */ return 0; } static int db_gethook (lua_State *L) { int arg; lua_State *L1 = getthread(L, &arg); char buff[5]; int mask = lua_gethookmask(L1); lua_Hook hook = lua_gethook(L1); if (hook != NULL && hook != hookf) /* external hook? */ lua_pushliteral(L, "external hook"); else { gethooktable(L); lua_pushthread(L1); lua_xmove(L1, L, 1); lua_rawget(L, -2); /* get hook */ lua_remove(L, -2); /* remove hook table */ } lua_pushstring(L, unmakemask(mask, buff)); lua_pushinteger(L, lua_gethookcount(L1)); return 3; } static int db_debug (lua_State *L) { for (;;) { char buffer[250]; luai_writestringerror("%s", "lua_debug> "); if (fgets(buffer, sizeof(buffer), stdin) == 0 || strcmp(buffer, "cont\n") == 0) return 0; if (luaL_loadbuffer(L, buffer, strlen(buffer), "=(debug command)") || lua_pcall(L, 0, 0, 0)) luai_writestringerror("%s\n", lua_tostring(L, -1)); lua_settop(L, 0); /* remove eventual returns */ } } static int db_traceback (lua_State *L) { int arg; lua_State *L1 = getthread(L, &arg); const char *msg = lua_tostring(L, arg + 1); if (msg == NULL && !lua_isnoneornil(L, arg + 1)) /* non-string 'msg'? */ lua_pushvalue(L, arg + 1); /* return it untouched */ else { int level = luaL_optint(L, arg + 2, (L == L1) ? 1 : 0); luaL_traceback(L, L1, msg, level); } return 1; } static const luaL_Reg dblib[] = { {"debug", db_debug}, {"getuservalue", db_getuservalue}, {"gethook", db_gethook}, {"getinfo", db_getinfo}, {"getlocal", db_getlocal}, {"getregistry", db_getregistry}, {"getmetatable", db_getmetatable}, {"getupvalue", db_getupvalue}, {"upvaluejoin", db_upvaluejoin}, {"upvalueid", db_upvalueid}, {"setuservalue", db_setuservalue}, {"sethook", db_sethook}, {"setlocal", db_setlocal}, {"setmetatable", db_setmetatable}, {"setupvalue", db_setupvalue}, {"traceback", db_traceback}, {NULL, NULL} }; LUAMOD_API int luaopen_debug (lua_State *L) { luaL_newlib(L, dblib); return 1; } april-ann-0.4.1/lua/lua-5.2.2/src/ldebug.c000066400000000000000000000363351263004425400176100ustar00rootroot00000000000000/* ** $Id: ldebug.c,v 2.90 2012/08/16 17:34:28 roberto Exp $ ** Debug Interface ** See Copyright Notice in lua.h */ #include #include #include #define ldebug_c #define LUA_CORE #include "lua.h" #include "lapi.h" #include "lcode.h" #include "ldebug.h" #include "ldo.h" #include "lfunc.h" #include "lobject.h" #include "lopcodes.h" #include "lstate.h" #include "lstring.h" #include "ltable.h" #include "ltm.h" #include "lvm.h" #define noLuaClosure(f) ((f) == NULL || (f)->c.tt == LUA_TCCL) static const char *getfuncname (lua_State *L, CallInfo *ci, const char **name); static int currentpc (CallInfo *ci) { lua_assert(isLua(ci)); return pcRel(ci->u.l.savedpc, ci_func(ci)->p); } static int currentline (CallInfo *ci) { return getfuncline(ci_func(ci)->p, currentpc(ci)); } /* ** this function can be called asynchronous (e.g. during a signal) */ LUA_API int lua_sethook (lua_State *L, lua_Hook func, int mask, int count) { if (func == NULL || mask == 0) { /* turn off hooks? */ mask = 0; func = NULL; } if (isLua(L->ci)) L->oldpc = L->ci->u.l.savedpc; L->hook = func; L->basehookcount = count; resethookcount(L); L->hookmask = cast_byte(mask); return 1; } LUA_API lua_Hook lua_gethook (lua_State *L) { return L->hook; } LUA_API int lua_gethookmask (lua_State *L) { return L->hookmask; } LUA_API int lua_gethookcount (lua_State *L) { return L->basehookcount; } LUA_API int lua_getstack (lua_State *L, int level, lua_Debug *ar) { int status; CallInfo *ci; if (level < 0) return 0; /* invalid (negative) level */ lua_lock(L); for (ci = L->ci; level > 0 && ci != &L->base_ci; ci = ci->previous) level--; if (level == 0 && ci != &L->base_ci) { /* level found? */ status = 1; ar->i_ci = ci; } else status = 0; /* no such level */ lua_unlock(L); return status; } static const char *upvalname (Proto *p, int uv) { TString *s = check_exp(uv < p->sizeupvalues, p->upvalues[uv].name); if (s == NULL) return "?"; else return getstr(s); } static const char *findvararg (CallInfo *ci, int n, StkId *pos) { int nparams = clLvalue(ci->func)->p->numparams; if (n >= ci->u.l.base - ci->func - nparams) return NULL; /* no such vararg */ else { *pos = ci->func + nparams + n; return "(*vararg)"; /* generic name for any vararg */ } } static const char *findlocal (lua_State *L, CallInfo *ci, int n, StkId *pos) { const char *name = NULL; StkId base; if (isLua(ci)) { if (n < 0) /* access to vararg values? */ return findvararg(ci, -n, pos); else { base = ci->u.l.base; name = luaF_getlocalname(ci_func(ci)->p, n, currentpc(ci)); } } else base = ci->func + 1; if (name == NULL) { /* no 'standard' name? */ StkId limit = (ci == L->ci) ? L->top : ci->next->func; if (limit - base >= n && n > 0) /* is 'n' inside 'ci' stack? */ name = "(*temporary)"; /* generic name for any valid slot */ else return NULL; /* no name */ } *pos = base + (n - 1); return name; } LUA_API const char *lua_getlocal (lua_State *L, const lua_Debug *ar, int n) { const char *name; lua_lock(L); if (ar == NULL) { /* information about non-active function? */ if (!isLfunction(L->top - 1)) /* not a Lua function? */ name = NULL; else /* consider live variables at function start (parameters) */ name = luaF_getlocalname(clLvalue(L->top - 1)->p, n, 0); } else { /* active function; get information through 'ar' */ StkId pos = 0; /* to avoid warnings */ name = findlocal(L, ar->i_ci, n, &pos); if (name) { setobj2s(L, L->top, pos); api_incr_top(L); } } lua_unlock(L); return name; } LUA_API const char *lua_setlocal (lua_State *L, const lua_Debug *ar, int n) { StkId pos = 0; /* to avoid warnings */ const char *name = findlocal(L, ar->i_ci, n, &pos); lua_lock(L); if (name) setobjs2s(L, pos, L->top - 1); L->top--; /* pop value */ lua_unlock(L); return name; } static void funcinfo (lua_Debug *ar, Closure *cl) { if (noLuaClosure(cl)) { ar->source = "=[C]"; ar->linedefined = -1; ar->lastlinedefined = -1; ar->what = "C"; } else { Proto *p = cl->l.p; ar->source = p->source ? getstr(p->source) : "=?"; ar->linedefined = p->linedefined; ar->lastlinedefined = p->lastlinedefined; ar->what = (ar->linedefined == 0) ? "main" : "Lua"; } luaO_chunkid(ar->short_src, ar->source, LUA_IDSIZE); } static void collectvalidlines (lua_State *L, Closure *f) { if (noLuaClosure(f)) { setnilvalue(L->top); api_incr_top(L); } else { int i; TValue v; int *lineinfo = f->l.p->lineinfo; Table *t = luaH_new(L); /* new table to store active lines */ sethvalue(L, L->top, t); /* push it on stack */ api_incr_top(L); setbvalue(&v, 1); /* boolean 'true' to be the value of all indices */ for (i = 0; i < f->l.p->sizelineinfo; i++) /* for all lines with code */ luaH_setint(L, t, lineinfo[i], &v); /* table[line] = true */ } } static int auxgetinfo (lua_State *L, const char *what, lua_Debug *ar, Closure *f, CallInfo *ci) { int status = 1; for (; *what; what++) { switch (*what) { case 'S': { funcinfo(ar, f); break; } case 'l': { ar->currentline = (ci && isLua(ci)) ? currentline(ci) : -1; break; } case 'u': { ar->nups = (f == NULL) ? 0 : f->c.nupvalues; if (noLuaClosure(f)) { ar->isvararg = 1; ar->nparams = 0; } else { ar->isvararg = f->l.p->is_vararg; ar->nparams = f->l.p->numparams; } break; } case 't': { ar->istailcall = (ci) ? ci->callstatus & CIST_TAIL : 0; break; } case 'n': { /* calling function is a known Lua function? */ if (ci && !(ci->callstatus & CIST_TAIL) && isLua(ci->previous)) ar->namewhat = getfuncname(L, ci->previous, &ar->name); else ar->namewhat = NULL; if (ar->namewhat == NULL) { ar->namewhat = ""; /* not found */ ar->name = NULL; } break; } case 'L': case 'f': /* handled by lua_getinfo */ break; default: status = 0; /* invalid option */ } } return status; } LUA_API int lua_getinfo (lua_State *L, const char *what, lua_Debug *ar) { int status; Closure *cl; CallInfo *ci; StkId func; lua_lock(L); if (*what == '>') { ci = NULL; func = L->top - 1; api_check(L, ttisfunction(func), "function expected"); what++; /* skip the '>' */ L->top--; /* pop function */ } else { ci = ar->i_ci; func = ci->func; lua_assert(ttisfunction(ci->func)); } cl = ttisclosure(func) ? clvalue(func) : NULL; status = auxgetinfo(L, what, ar, cl, ci); if (strchr(what, 'f')) { setobjs2s(L, L->top, func); api_incr_top(L); } if (strchr(what, 'L')) collectvalidlines(L, cl); lua_unlock(L); return status; } /* ** {====================================================== ** Symbolic Execution ** ======================================================= */ static const char *getobjname (Proto *p, int lastpc, int reg, const char **name); /* ** find a "name" for the RK value 'c' */ static void kname (Proto *p, int pc, int c, const char **name) { if (ISK(c)) { /* is 'c' a constant? */ TValue *kvalue = &p->k[INDEXK(c)]; if (ttisstring(kvalue)) { /* literal constant? */ *name = svalue(kvalue); /* it is its own name */ return; } /* else no reasonable name found */ } else { /* 'c' is a register */ const char *what = getobjname(p, pc, c, name); /* search for 'c' */ if (what && *what == 'c') { /* found a constant name? */ return; /* 'name' already filled */ } /* else no reasonable name found */ } *name = "?"; /* no reasonable name found */ } /* ** try to find last instruction before 'lastpc' that modified register 'reg' */ static int findsetreg (Proto *p, int lastpc, int reg) { int pc; int setreg = -1; /* keep last instruction that changed 'reg' */ for (pc = 0; pc < lastpc; pc++) { Instruction i = p->code[pc]; OpCode op = GET_OPCODE(i); int a = GETARG_A(i); switch (op) { case OP_LOADNIL: { int b = GETARG_B(i); if (a <= reg && reg <= a + b) /* set registers from 'a' to 'a+b' */ setreg = pc; break; } case OP_TFORCALL: { if (reg >= a + 2) setreg = pc; /* affect all regs above its base */ break; } case OP_CALL: case OP_TAILCALL: { if (reg >= a) setreg = pc; /* affect all registers above base */ break; } case OP_JMP: { int b = GETARG_sBx(i); int dest = pc + 1 + b; /* jump is forward and do not skip `lastpc'? */ if (pc < dest && dest <= lastpc) pc += b; /* do the jump */ break; } case OP_TEST: { if (reg == a) setreg = pc; /* jumped code can change 'a' */ break; } default: if (testAMode(op) && reg == a) /* any instruction that set A */ setreg = pc; break; } } return setreg; } static const char *getobjname (Proto *p, int lastpc, int reg, const char **name) { int pc; *name = luaF_getlocalname(p, reg + 1, lastpc); if (*name) /* is a local? */ return "local"; /* else try symbolic execution */ pc = findsetreg(p, lastpc, reg); if (pc != -1) { /* could find instruction? */ Instruction i = p->code[pc]; OpCode op = GET_OPCODE(i); switch (op) { case OP_MOVE: { int b = GETARG_B(i); /* move from 'b' to 'a' */ if (b < GETARG_A(i)) return getobjname(p, pc, b, name); /* get name for 'b' */ break; } case OP_GETTABUP: case OP_GETTABLE: { int k = GETARG_C(i); /* key index */ int t = GETARG_B(i); /* table index */ const char *vn = (op == OP_GETTABLE) /* name of indexed variable */ ? luaF_getlocalname(p, t + 1, pc) : upvalname(p, t); kname(p, pc, k, name); return (vn && strcmp(vn, LUA_ENV) == 0) ? "global" : "field"; } case OP_GETUPVAL: { *name = upvalname(p, GETARG_B(i)); return "upvalue"; } case OP_LOADK: case OP_LOADKX: { int b = (op == OP_LOADK) ? GETARG_Bx(i) : GETARG_Ax(p->code[pc + 1]); if (ttisstring(&p->k[b])) { *name = svalue(&p->k[b]); return "constant"; } break; } case OP_SELF: { int k = GETARG_C(i); /* key index */ kname(p, pc, k, name); return "method"; } default: break; /* go through to return NULL */ } } return NULL; /* could not find reasonable name */ } static const char *getfuncname (lua_State *L, CallInfo *ci, const char **name) { TMS tm; Proto *p = ci_func(ci)->p; /* calling function */ int pc = currentpc(ci); /* calling instruction index */ Instruction i = p->code[pc]; /* calling instruction */ switch (GET_OPCODE(i)) { case OP_CALL: case OP_TAILCALL: /* get function name */ return getobjname(p, pc, GETARG_A(i), name); case OP_TFORCALL: { /* for iterator */ *name = "for iterator"; return "for iterator"; } /* all other instructions can call only through metamethods */ case OP_SELF: case OP_GETTABUP: case OP_GETTABLE: tm = TM_INDEX; break; case OP_SETTABUP: case OP_SETTABLE: tm = TM_NEWINDEX; break; case OP_EQ: tm = TM_EQ; break; case OP_ADD: tm = TM_ADD; break; case OP_SUB: tm = TM_SUB; break; case OP_MUL: tm = TM_MUL; break; case OP_DIV: tm = TM_DIV; break; case OP_MOD: tm = TM_MOD; break; case OP_POW: tm = TM_POW; break; case OP_UNM: tm = TM_UNM; break; case OP_LEN: tm = TM_LEN; break; case OP_LT: tm = TM_LT; break; case OP_LE: tm = TM_LE; break; case OP_CONCAT: tm = TM_CONCAT; break; default: return NULL; /* else no useful name can be found */ } *name = getstr(G(L)->tmname[tm]); return "metamethod"; } /* }====================================================== */ /* ** only ANSI way to check whether a pointer points to an array ** (used only for error messages, so efficiency is not a big concern) */ static int isinstack (CallInfo *ci, const TValue *o) { StkId p; for (p = ci->u.l.base; p < ci->top; p++) if (o == p) return 1; return 0; } static const char *getupvalname (CallInfo *ci, const TValue *o, const char **name) { LClosure *c = ci_func(ci); int i; for (i = 0; i < c->nupvalues; i++) { if (c->upvals[i]->v == o) { *name = upvalname(c->p, i); return "upvalue"; } } return NULL; } l_noret luaG_typeerror (lua_State *L, const TValue *o, const char *op) { CallInfo *ci = L->ci; const char *name = NULL; const char *t = objtypename(o); const char *kind = NULL; if (isLua(ci)) { kind = getupvalname(ci, o, &name); /* check whether 'o' is an upvalue */ if (!kind && isinstack(ci, o)) /* no? try a register */ kind = getobjname(ci_func(ci)->p, currentpc(ci), cast_int(o - ci->u.l.base), &name); } if (kind) luaG_runerror(L, "attempt to %s %s " LUA_QS " (a %s value)", op, kind, name, t); else luaG_runerror(L, "attempt to %s a %s value", op, t); } l_noret luaG_concaterror (lua_State *L, StkId p1, StkId p2) { if (ttisstring(p1) || ttisnumber(p1)) p1 = p2; lua_assert(!ttisstring(p1) && !ttisnumber(p2)); luaG_typeerror(L, p1, "concatenate"); } l_noret luaG_aritherror (lua_State *L, const TValue *p1, const TValue *p2) { TValue temp; if (luaV_tonumber(p1, &temp) == NULL) p2 = p1; /* first operand is wrong */ luaG_typeerror(L, p2, "perform arithmetic on"); } l_noret luaG_ordererror (lua_State *L, const TValue *p1, const TValue *p2) { const char *t1 = objtypename(p1); const char *t2 = objtypename(p2); if (t1 == t2) luaG_runerror(L, "attempt to compare two %s values", t1); else luaG_runerror(L, "attempt to compare %s with %s", t1, t2); } static void addinfo (lua_State *L, const char *msg) { CallInfo *ci = L->ci; if (isLua(ci)) { /* is Lua code? */ char buff[LUA_IDSIZE]; /* add file:line information */ int line = currentline(ci); TString *src = ci_func(ci)->p->source; if (src) luaO_chunkid(buff, getstr(src), LUA_IDSIZE); else { /* no source available; use "?" instead */ buff[0] = '?'; buff[1] = '\0'; } luaO_pushfstring(L, "%s:%d: %s", buff, line, msg); } } l_noret luaG_errormsg (lua_State *L) { if (L->errfunc != 0) { /* is there an error handling function? */ StkId errfunc = restorestack(L, L->errfunc); if (!ttisfunction(errfunc)) luaD_throw(L, LUA_ERRERR); setobjs2s(L, L->top, L->top - 1); /* move argument */ setobjs2s(L, L->top - 1, errfunc); /* push function */ L->top++; luaD_call(L, L->top - 2, 1, 0); /* call it */ } luaD_throw(L, LUA_ERRRUN); } l_noret luaG_runerror (lua_State *L, const char *fmt, ...) { va_list argp; va_start(argp, fmt); addinfo(L, luaO_pushvfstring(L, fmt, argp)); va_end(argp); luaG_errormsg(L); } april-ann-0.4.1/lua/lua-5.2.2/src/ldebug.h000066400000000000000000000020731263004425400176050ustar00rootroot00000000000000/* ** $Id: ldebug.h,v 2.7 2011/10/07 20:45:19 roberto Exp $ ** Auxiliary functions from Debug Interface module ** See Copyright Notice in lua.h */ #ifndef ldebug_h #define ldebug_h #include "lstate.h" #define pcRel(pc, p) (cast(int, (pc) - (p)->code) - 1) #define getfuncline(f,pc) (((f)->lineinfo) ? (f)->lineinfo[pc] : 0) #define resethookcount(L) (L->hookcount = L->basehookcount) /* Active Lua function (given call info) */ #define ci_func(ci) (clLvalue((ci)->func)) LUAI_FUNC l_noret luaG_typeerror (lua_State *L, const TValue *o, const char *opname); LUAI_FUNC l_noret luaG_concaterror (lua_State *L, StkId p1, StkId p2); LUAI_FUNC l_noret luaG_aritherror (lua_State *L, const TValue *p1, const TValue *p2); LUAI_FUNC l_noret luaG_ordererror (lua_State *L, const TValue *p1, const TValue *p2); LUAI_FUNC l_noret luaG_runerror (lua_State *L, const char *fmt, ...); LUAI_FUNC l_noret luaG_errormsg (lua_State *L); #endif april-ann-0.4.1/lua/lua-5.2.2/src/ldo.c000066400000000000000000000500251263004425400171140ustar00rootroot00000000000000/* ** $Id: ldo.c,v 2.108 2012/10/01 14:05:04 roberto Exp $ ** Stack and Call structure of Lua ** See Copyright Notice in lua.h */ #include #include #include #define ldo_c #define LUA_CORE #include "lua.h" #include "lapi.h" #include "ldebug.h" #include "ldo.h" #include "lfunc.h" #include "lgc.h" #include "lmem.h" #include "lobject.h" #include "lopcodes.h" #include "lparser.h" #include "lstate.h" #include "lstring.h" #include "ltable.h" #include "ltm.h" #include "lundump.h" #include "lvm.h" #include "lzio.h" /* ** {====================================================== ** Error-recovery functions ** ======================================================= */ /* ** LUAI_THROW/LUAI_TRY define how Lua does exception handling. By ** default, Lua handles errors with exceptions when compiling as ** C++ code, with _longjmp/_setjmp when asked to use them, and with ** longjmp/setjmp otherwise. */ #if !defined(LUAI_THROW) #if defined(__cplusplus) && !defined(LUA_USE_LONGJMP) /* C++ exceptions */ #define LUAI_THROW(L,c) throw(c) #define LUAI_TRY(L,c,a) \ try { a } catch(...) { if ((c)->status == 0) (c)->status = -1; } #define luai_jmpbuf int /* dummy variable */ #elif defined(LUA_USE_ULONGJMP) /* in Unix, try _longjmp/_setjmp (more efficient) */ #define LUAI_THROW(L,c) _longjmp((c)->b, 1) #define LUAI_TRY(L,c,a) if (_setjmp((c)->b) == 0) { a } #define luai_jmpbuf jmp_buf #else /* default handling with long jumps */ #define LUAI_THROW(L,c) longjmp((c)->b, 1) #define LUAI_TRY(L,c,a) if (setjmp((c)->b) == 0) { a } #define luai_jmpbuf jmp_buf #endif #endif /* chain list of long jump buffers */ struct lua_longjmp { struct lua_longjmp *previous; luai_jmpbuf b; volatile int status; /* error code */ }; static void seterrorobj (lua_State *L, int errcode, StkId oldtop) { switch (errcode) { case LUA_ERRMEM: { /* memory error? */ setsvalue2s(L, oldtop, G(L)->memerrmsg); /* reuse preregistered msg. */ break; } case LUA_ERRERR: { setsvalue2s(L, oldtop, luaS_newliteral(L, "error in error handling")); break; } default: { setobjs2s(L, oldtop, L->top - 1); /* error message on current top */ break; } } L->top = oldtop + 1; } l_noret luaD_throw (lua_State *L, int errcode) { if (L->errorJmp) { /* thread has an error handler? */ L->errorJmp->status = errcode; /* set status */ LUAI_THROW(L, L->errorJmp); /* jump to it */ } else { /* thread has no error handler */ L->status = cast_byte(errcode); /* mark it as dead */ if (G(L)->mainthread->errorJmp) { /* main thread has a handler? */ setobjs2s(L, G(L)->mainthread->top++, L->top - 1); /* copy error obj. */ luaD_throw(G(L)->mainthread, errcode); /* re-throw in main thread */ } else { /* no handler at all; abort */ if (G(L)->panic) { /* panic function? */ lua_unlock(L); G(L)->panic(L); /* call it (last chance to jump out) */ } abort(); } } } int luaD_rawrunprotected (lua_State *L, Pfunc f, void *ud) { unsigned short oldnCcalls = L->nCcalls; struct lua_longjmp lj; lj.status = LUA_OK; lj.previous = L->errorJmp; /* chain new error handler */ L->errorJmp = &lj; LUAI_TRY(L, &lj, (*f)(L, ud); ); L->errorJmp = lj.previous; /* restore old error handler */ L->nCcalls = oldnCcalls; return lj.status; } /* }====================================================== */ static void correctstack (lua_State *L, TValue *oldstack) { CallInfo *ci; GCObject *up; L->top = (L->top - oldstack) + L->stack; for (up = L->openupval; up != NULL; up = up->gch.next) gco2uv(up)->v = (gco2uv(up)->v - oldstack) + L->stack; for (ci = L->ci; ci != NULL; ci = ci->previous) { ci->top = (ci->top - oldstack) + L->stack; ci->func = (ci->func - oldstack) + L->stack; if (isLua(ci)) ci->u.l.base = (ci->u.l.base - oldstack) + L->stack; } } /* some space for error handling */ #define ERRORSTACKSIZE (LUAI_MAXSTACK + 200) void luaD_reallocstack (lua_State *L, int newsize) { TValue *oldstack = L->stack; int lim = L->stacksize; lua_assert(newsize <= LUAI_MAXSTACK || newsize == ERRORSTACKSIZE); lua_assert(L->stack_last - L->stack == L->stacksize - EXTRA_STACK); luaM_reallocvector(L, L->stack, L->stacksize, newsize, TValue); for (; lim < newsize; lim++) setnilvalue(L->stack + lim); /* erase new segment */ L->stacksize = newsize; L->stack_last = L->stack + newsize - EXTRA_STACK; correctstack(L, oldstack); } void luaD_growstack (lua_State *L, int n) { int size = L->stacksize; if (size > LUAI_MAXSTACK) /* error after extra size? */ luaD_throw(L, LUA_ERRERR); else { int needed = cast_int(L->top - L->stack) + n + EXTRA_STACK; int newsize = 2 * size; if (newsize > LUAI_MAXSTACK) newsize = LUAI_MAXSTACK; if (newsize < needed) newsize = needed; if (newsize > LUAI_MAXSTACK) { /* stack overflow? */ luaD_reallocstack(L, ERRORSTACKSIZE); luaG_runerror(L, "stack overflow"); } else luaD_reallocstack(L, newsize); } } static int stackinuse (lua_State *L) { CallInfo *ci; StkId lim = L->top; for (ci = L->ci; ci != NULL; ci = ci->previous) { lua_assert(ci->top <= L->stack_last); if (lim < ci->top) lim = ci->top; } return cast_int(lim - L->stack) + 1; /* part of stack in use */ } void luaD_shrinkstack (lua_State *L) { int inuse = stackinuse(L); int goodsize = inuse + (inuse / 8) + 2*EXTRA_STACK; if (goodsize > LUAI_MAXSTACK) goodsize = LUAI_MAXSTACK; if (inuse > LUAI_MAXSTACK || /* handling stack overflow? */ goodsize >= L->stacksize) /* would grow instead of shrink? */ condmovestack(L); /* don't change stack (change only for debugging) */ else luaD_reallocstack(L, goodsize); /* shrink it */ } void luaD_hook (lua_State *L, int event, int line) { lua_Hook hook = L->hook; if (hook && L->allowhook) { CallInfo *ci = L->ci; ptrdiff_t top = savestack(L, L->top); ptrdiff_t ci_top = savestack(L, ci->top); lua_Debug ar; ar.event = event; ar.currentline = line; ar.i_ci = ci; luaD_checkstack(L, LUA_MINSTACK); /* ensure minimum stack size */ ci->top = L->top + LUA_MINSTACK; lua_assert(ci->top <= L->stack_last); L->allowhook = 0; /* cannot call hooks inside a hook */ ci->callstatus |= CIST_HOOKED; lua_unlock(L); (*hook)(L, &ar); lua_lock(L); lua_assert(!L->allowhook); L->allowhook = 1; ci->top = restorestack(L, ci_top); L->top = restorestack(L, top); ci->callstatus &= ~CIST_HOOKED; } } static void callhook (lua_State *L, CallInfo *ci) { int hook = LUA_HOOKCALL; ci->u.l.savedpc++; /* hooks assume 'pc' is already incremented */ if (isLua(ci->previous) && GET_OPCODE(*(ci->previous->u.l.savedpc - 1)) == OP_TAILCALL) { ci->callstatus |= CIST_TAIL; hook = LUA_HOOKTAILCALL; } luaD_hook(L, hook, -1); ci->u.l.savedpc--; /* correct 'pc' */ } static StkId adjust_varargs (lua_State *L, Proto *p, int actual) { int i; int nfixargs = p->numparams; StkId base, fixed; lua_assert(actual >= nfixargs); /* move fixed parameters to final position */ fixed = L->top - actual; /* first fixed argument */ base = L->top; /* final position of first argument */ for (i=0; itop++, fixed + i); setnilvalue(fixed + i); } return base; } static StkId tryfuncTM (lua_State *L, StkId func) { const TValue *tm = luaT_gettmbyobj(L, func, TM_CALL); StkId p; ptrdiff_t funcr = savestack(L, func); if (!ttisfunction(tm)) luaG_typeerror(L, func, "call"); /* Open a hole inside the stack at `func' */ for (p = L->top; p > func; p--) setobjs2s(L, p, p-1); incr_top(L); func = restorestack(L, funcr); /* previous call may change stack */ setobj2s(L, func, tm); /* tag method is the new function to be called */ return func; } #define next_ci(L) (L->ci = (L->ci->next ? L->ci->next : luaE_extendCI(L))) /* ** returns true if function has been executed (C function) */ int luaD_precall (lua_State *L, StkId func, int nresults) { lua_CFunction f; CallInfo *ci; int n; /* number of arguments (Lua) or returns (C) */ ptrdiff_t funcr = savestack(L, func); switch (ttype(func)) { case LUA_TLCF: /* light C function */ f = fvalue(func); goto Cfunc; case LUA_TCCL: { /* C closure */ f = clCvalue(func)->f; Cfunc: luaD_checkstack(L, LUA_MINSTACK); /* ensure minimum stack size */ ci = next_ci(L); /* now 'enter' new function */ ci->nresults = nresults; ci->func = restorestack(L, funcr); ci->top = L->top + LUA_MINSTACK; lua_assert(ci->top <= L->stack_last); ci->callstatus = 0; luaC_checkGC(L); /* stack grow uses memory */ if (L->hookmask & LUA_MASKCALL) luaD_hook(L, LUA_HOOKCALL, -1); lua_unlock(L); n = (*f)(L); /* do the actual call */ lua_lock(L); api_checknelems(L, n); luaD_poscall(L, L->top - n); return 1; } case LUA_TLCL: { /* Lua function: prepare its call */ StkId base; Proto *p = clLvalue(func)->p; luaD_checkstack(L, p->maxstacksize); func = restorestack(L, funcr); n = cast_int(L->top - func) - 1; /* number of real arguments */ for (; n < p->numparams; n++) setnilvalue(L->top++); /* complete missing arguments */ base = (!p->is_vararg) ? func + 1 : adjust_varargs(L, p, n); ci = next_ci(L); /* now 'enter' new function */ ci->nresults = nresults; ci->func = func; ci->u.l.base = base; ci->top = base + p->maxstacksize; lua_assert(ci->top <= L->stack_last); ci->u.l.savedpc = p->code; /* starting point */ ci->callstatus = CIST_LUA; L->top = ci->top; luaC_checkGC(L); /* stack grow uses memory */ if (L->hookmask & LUA_MASKCALL) callhook(L, ci); return 0; } default: { /* not a function */ func = tryfuncTM(L, func); /* retry with 'function' tag method */ return luaD_precall(L, func, nresults); /* now it must be a function */ } } } int luaD_poscall (lua_State *L, StkId firstResult) { StkId res; int wanted, i; CallInfo *ci = L->ci; if (L->hookmask & (LUA_MASKRET | LUA_MASKLINE)) { if (L->hookmask & LUA_MASKRET) { ptrdiff_t fr = savestack(L, firstResult); /* hook may change stack */ luaD_hook(L, LUA_HOOKRET, -1); firstResult = restorestack(L, fr); } L->oldpc = ci->previous->u.l.savedpc; /* 'oldpc' for caller function */ } res = ci->func; /* res == final position of 1st result */ wanted = ci->nresults; L->ci = ci = ci->previous; /* back to caller */ /* move results to correct place */ for (i = wanted; i != 0 && firstResult < L->top; i--) setobjs2s(L, res++, firstResult++); while (i-- > 0) setnilvalue(res++); L->top = res; return (wanted - LUA_MULTRET); /* 0 iff wanted == LUA_MULTRET */ } /* ** Call a function (C or Lua). The function to be called is at *func. ** The arguments are on the stack, right after the function. ** When returns, all the results are on the stack, starting at the original ** function position. */ void luaD_call (lua_State *L, StkId func, int nResults, int allowyield) { if (++L->nCcalls >= LUAI_MAXCCALLS) { if (L->nCcalls == LUAI_MAXCCALLS) luaG_runerror(L, "C stack overflow"); else if (L->nCcalls >= (LUAI_MAXCCALLS + (LUAI_MAXCCALLS>>3))) luaD_throw(L, LUA_ERRERR); /* error while handing stack error */ } if (!allowyield) L->nny++; if (!luaD_precall(L, func, nResults)) /* is a Lua function? */ luaV_execute(L); /* call it */ if (!allowyield) L->nny--; L->nCcalls--; } static void finishCcall (lua_State *L) { CallInfo *ci = L->ci; int n; lua_assert(ci->u.c.k != NULL); /* must have a continuation */ lua_assert(L->nny == 0); if (ci->callstatus & CIST_YPCALL) { /* was inside a pcall? */ ci->callstatus &= ~CIST_YPCALL; /* finish 'lua_pcall' */ L->errfunc = ci->u.c.old_errfunc; } /* finish 'lua_callk'/'lua_pcall' */ adjustresults(L, ci->nresults); /* call continuation function */ if (!(ci->callstatus & CIST_STAT)) /* no call status? */ ci->u.c.status = LUA_YIELD; /* 'default' status */ lua_assert(ci->u.c.status != LUA_OK); ci->callstatus = (ci->callstatus & ~(CIST_YPCALL | CIST_STAT)) | CIST_YIELDED; lua_unlock(L); n = (*ci->u.c.k)(L); lua_lock(L); api_checknelems(L, n); /* finish 'luaD_precall' */ luaD_poscall(L, L->top - n); } static void unroll (lua_State *L, void *ud) { UNUSED(ud); for (;;) { if (L->ci == &L->base_ci) /* stack is empty? */ return; /* coroutine finished normally */ if (!isLua(L->ci)) /* C function? */ finishCcall(L); else { /* Lua function */ luaV_finishOp(L); /* finish interrupted instruction */ luaV_execute(L); /* execute down to higher C 'boundary' */ } } } /* ** check whether thread has a suspended protected call */ static CallInfo *findpcall (lua_State *L) { CallInfo *ci; for (ci = L->ci; ci != NULL; ci = ci->previous) { /* search for a pcall */ if (ci->callstatus & CIST_YPCALL) return ci; } return NULL; /* no pending pcall */ } static int recover (lua_State *L, int status) { StkId oldtop; CallInfo *ci = findpcall(L); if (ci == NULL) return 0; /* no recovery point */ /* "finish" luaD_pcall */ oldtop = restorestack(L, ci->extra); luaF_close(L, oldtop); seterrorobj(L, status, oldtop); L->ci = ci; L->allowhook = ci->u.c.old_allowhook; L->nny = 0; /* should be zero to be yieldable */ luaD_shrinkstack(L); L->errfunc = ci->u.c.old_errfunc; ci->callstatus |= CIST_STAT; /* call has error status */ ci->u.c.status = status; /* (here it is) */ return 1; /* continue running the coroutine */ } /* ** signal an error in the call to 'resume', not in the execution of the ** coroutine itself. (Such errors should not be handled by any coroutine ** error handler and should not kill the coroutine.) */ static l_noret resume_error (lua_State *L, const char *msg, StkId firstArg) { L->top = firstArg; /* remove args from the stack */ setsvalue2s(L, L->top, luaS_new(L, msg)); /* push error message */ api_incr_top(L); luaD_throw(L, -1); /* jump back to 'lua_resume' */ } /* ** do the work for 'lua_resume' in protected mode */ static void resume (lua_State *L, void *ud) { int nCcalls = L->nCcalls; StkId firstArg = cast(StkId, ud); CallInfo *ci = L->ci; if (nCcalls >= LUAI_MAXCCALLS) resume_error(L, "C stack overflow", firstArg); if (L->status == LUA_OK) { /* may be starting a coroutine */ if (ci != &L->base_ci) /* not in base level? */ resume_error(L, "cannot resume non-suspended coroutine", firstArg); /* coroutine is in base level; start running it */ if (!luaD_precall(L, firstArg - 1, LUA_MULTRET)) /* Lua function? */ luaV_execute(L); /* call it */ } else if (L->status != LUA_YIELD) resume_error(L, "cannot resume dead coroutine", firstArg); else { /* resuming from previous yield */ L->status = LUA_OK; ci->func = restorestack(L, ci->extra); if (isLua(ci)) /* yielded inside a hook? */ luaV_execute(L); /* just continue running Lua code */ else { /* 'common' yield */ if (ci->u.c.k != NULL) { /* does it have a continuation? */ int n; ci->u.c.status = LUA_YIELD; /* 'default' status */ ci->callstatus |= CIST_YIELDED; lua_unlock(L); n = (*ci->u.c.k)(L); /* call continuation */ lua_lock(L); api_checknelems(L, n); firstArg = L->top - n; /* yield results come from continuation */ } luaD_poscall(L, firstArg); /* finish 'luaD_precall' */ } unroll(L, NULL); } lua_assert(nCcalls == L->nCcalls); } LUA_API int lua_resume (lua_State *L, lua_State *from, int nargs) { int status; lua_lock(L); luai_userstateresume(L, nargs); L->nCcalls = (from) ? from->nCcalls + 1 : 1; L->nny = 0; /* allow yields */ api_checknelems(L, (L->status == LUA_OK) ? nargs + 1 : nargs); status = luaD_rawrunprotected(L, resume, L->top - nargs); if (status == -1) /* error calling 'lua_resume'? */ status = LUA_ERRRUN; else { /* yield or regular error */ while (status != LUA_OK && status != LUA_YIELD) { /* error? */ if (recover(L, status)) /* recover point? */ status = luaD_rawrunprotected(L, unroll, NULL); /* run continuation */ else { /* unrecoverable error */ L->status = cast_byte(status); /* mark thread as `dead' */ seterrorobj(L, status, L->top); L->ci->top = L->top; break; } } lua_assert(status == L->status); } L->nny = 1; /* do not allow yields */ L->nCcalls--; lua_assert(L->nCcalls == ((from) ? from->nCcalls : 0)); lua_unlock(L); return status; } LUA_API int lua_yieldk (lua_State *L, int nresults, int ctx, lua_CFunction k) { CallInfo *ci = L->ci; luai_userstateyield(L, nresults); lua_lock(L); api_checknelems(L, nresults); if (L->nny > 0) { if (L != G(L)->mainthread) luaG_runerror(L, "attempt to yield across a C-call boundary"); else luaG_runerror(L, "attempt to yield from outside a coroutine"); } L->status = LUA_YIELD; ci->extra = savestack(L, ci->func); /* save current 'func' */ if (isLua(ci)) { /* inside a hook? */ api_check(L, k == NULL, "hooks cannot continue after yielding"); } else { if ((ci->u.c.k = k) != NULL) /* is there a continuation? */ ci->u.c.ctx = ctx; /* save context */ ci->func = L->top - nresults - 1; /* protect stack below results */ luaD_throw(L, LUA_YIELD); } lua_assert(ci->callstatus & CIST_HOOKED); /* must be inside a hook */ lua_unlock(L); return 0; /* return to 'luaD_hook' */ } int luaD_pcall (lua_State *L, Pfunc func, void *u, ptrdiff_t old_top, ptrdiff_t ef) { int status; CallInfo *old_ci = L->ci; lu_byte old_allowhooks = L->allowhook; unsigned short old_nny = L->nny; ptrdiff_t old_errfunc = L->errfunc; L->errfunc = ef; status = luaD_rawrunprotected(L, func, u); if (status != LUA_OK) { /* an error occurred? */ StkId oldtop = restorestack(L, old_top); luaF_close(L, oldtop); /* close possible pending closures */ seterrorobj(L, status, oldtop); L->ci = old_ci; L->allowhook = old_allowhooks; L->nny = old_nny; luaD_shrinkstack(L); } L->errfunc = old_errfunc; return status; } /* ** Execute a protected parser. */ struct SParser { /* data to `f_parser' */ ZIO *z; Mbuffer buff; /* dynamic structure used by the scanner */ Dyndata dyd; /* dynamic structures used by the parser */ const char *mode; const char *name; }; static void checkmode (lua_State *L, const char *mode, const char *x) { if (mode && strchr(mode, x[0]) == NULL) { luaO_pushfstring(L, "attempt to load a %s chunk (mode is " LUA_QS ")", x, mode); luaD_throw(L, LUA_ERRSYNTAX); } } static void f_parser (lua_State *L, void *ud) { int i; Closure *cl; struct SParser *p = cast(struct SParser *, ud); int c = zgetc(p->z); /* read first character */ if (c == LUA_SIGNATURE[0]) { checkmode(L, p->mode, "binary"); cl = luaU_undump(L, p->z, &p->buff, p->name); } else { checkmode(L, p->mode, "text"); cl = luaY_parser(L, p->z, &p->buff, &p->dyd, p->name, c); } lua_assert(cl->l.nupvalues == cl->l.p->sizeupvalues); for (i = 0; i < cl->l.nupvalues; i++) { /* initialize upvalues */ UpVal *up = luaF_newupval(L); cl->l.upvals[i] = up; luaC_objbarrier(L, cl, up); } } int luaD_protectedparser (lua_State *L, ZIO *z, const char *name, const char *mode) { struct SParser p; int status; L->nny++; /* cannot yield during parsing */ p.z = z; p.name = name; p.mode = mode; p.dyd.actvar.arr = NULL; p.dyd.actvar.size = 0; p.dyd.gt.arr = NULL; p.dyd.gt.size = 0; p.dyd.label.arr = NULL; p.dyd.label.size = 0; luaZ_initbuffer(L, &p.buff); status = luaD_pcall(L, f_parser, &p, savestack(L, L->top), L->errfunc); luaZ_freebuffer(L, &p.buff); luaM_freearray(L, p.dyd.actvar.arr, p.dyd.actvar.size); luaM_freearray(L, p.dyd.gt.arr, p.dyd.gt.size); luaM_freearray(L, p.dyd.label.arr, p.dyd.label.size); L->nny--; return status; } april-ann-0.4.1/lua/lua-5.2.2/src/ldo.h000066400000000000000000000027671263004425400171330ustar00rootroot00000000000000/* ** $Id: ldo.h,v 2.20 2011/11/29 15:55:08 roberto Exp $ ** Stack and Call structure of Lua ** See Copyright Notice in lua.h */ #ifndef ldo_h #define ldo_h #include "lobject.h" #include "lstate.h" #include "lzio.h" #define luaD_checkstack(L,n) if (L->stack_last - L->top <= (n)) \ luaD_growstack(L, n); else condmovestack(L); #define incr_top(L) {L->top++; luaD_checkstack(L,0);} #define savestack(L,p) ((char *)(p) - (char *)L->stack) #define restorestack(L,n) ((TValue *)((char *)L->stack + (n))) /* type of protected functions, to be ran by `runprotected' */ typedef void (*Pfunc) (lua_State *L, void *ud); LUAI_FUNC int luaD_protectedparser (lua_State *L, ZIO *z, const char *name, const char *mode); LUAI_FUNC void luaD_hook (lua_State *L, int event, int line); LUAI_FUNC int luaD_precall (lua_State *L, StkId func, int nresults); LUAI_FUNC void luaD_call (lua_State *L, StkId func, int nResults, int allowyield); LUAI_FUNC int luaD_pcall (lua_State *L, Pfunc func, void *u, ptrdiff_t oldtop, ptrdiff_t ef); LUAI_FUNC int luaD_poscall (lua_State *L, StkId firstResult); LUAI_FUNC void luaD_reallocstack (lua_State *L, int newsize); LUAI_FUNC void luaD_growstack (lua_State *L, int n); LUAI_FUNC void luaD_shrinkstack (lua_State *L); LUAI_FUNC l_noret luaD_throw (lua_State *L, int errcode); LUAI_FUNC int luaD_rawrunprotected (lua_State *L, Pfunc f, void *ud); #endif april-ann-0.4.1/lua/lua-5.2.2/src/ldump.c000066400000000000000000000062211263004425400174560ustar00rootroot00000000000000/* ** $Id: ldump.c,v 2.17 2012/01/23 23:02:10 roberto Exp $ ** save precompiled Lua chunks ** See Copyright Notice in lua.h */ #include #define ldump_c #define LUA_CORE #include "lua.h" #include "lobject.h" #include "lstate.h" #include "lundump.h" typedef struct { lua_State* L; lua_Writer writer; void* data; int strip; int status; } DumpState; #define DumpMem(b,n,size,D) DumpBlock(b,(n)*(size),D) #define DumpVar(x,D) DumpMem(&x,1,sizeof(x),D) static void DumpBlock(const void* b, size_t size, DumpState* D) { if (D->status==0) { lua_unlock(D->L); D->status=(*D->writer)(D->L,b,size,D->data); lua_lock(D->L); } } static void DumpChar(int y, DumpState* D) { char x=(char)y; DumpVar(x,D); } static void DumpInt(int x, DumpState* D) { DumpVar(x,D); } static void DumpNumber(lua_Number x, DumpState* D) { DumpVar(x,D); } static void DumpVector(const void* b, int n, size_t size, DumpState* D) { DumpInt(n,D); DumpMem(b,n,size,D); } static void DumpString(const TString* s, DumpState* D) { if (s==NULL) { size_t size=0; DumpVar(size,D); } else { size_t size=s->tsv.len+1; /* include trailing '\0' */ DumpVar(size,D); DumpBlock(getstr(s),size*sizeof(char),D); } } #define DumpCode(f,D) DumpVector(f->code,f->sizecode,sizeof(Instruction),D) static void DumpFunction(const Proto* f, DumpState* D); static void DumpConstants(const Proto* f, DumpState* D) { int i,n=f->sizek; DumpInt(n,D); for (i=0; ik[i]; DumpChar(ttypenv(o),D); switch (ttypenv(o)) { case LUA_TNIL: break; case LUA_TBOOLEAN: DumpChar(bvalue(o),D); break; case LUA_TNUMBER: DumpNumber(nvalue(o),D); break; case LUA_TSTRING: DumpString(rawtsvalue(o),D); break; default: lua_assert(0); } } n=f->sizep; DumpInt(n,D); for (i=0; ip[i],D); } static void DumpUpvalues(const Proto* f, DumpState* D) { int i,n=f->sizeupvalues; DumpInt(n,D); for (i=0; iupvalues[i].instack,D); DumpChar(f->upvalues[i].idx,D); } } static void DumpDebug(const Proto* f, DumpState* D) { int i,n; DumpString((D->strip) ? NULL : f->source,D); n= (D->strip) ? 0 : f->sizelineinfo; DumpVector(f->lineinfo,n,sizeof(int),D); n= (D->strip) ? 0 : f->sizelocvars; DumpInt(n,D); for (i=0; ilocvars[i].varname,D); DumpInt(f->locvars[i].startpc,D); DumpInt(f->locvars[i].endpc,D); } n= (D->strip) ? 0 : f->sizeupvalues; DumpInt(n,D); for (i=0; iupvalues[i].name,D); } static void DumpFunction(const Proto* f, DumpState* D) { DumpInt(f->linedefined,D); DumpInt(f->lastlinedefined,D); DumpChar(f->numparams,D); DumpChar(f->is_vararg,D); DumpChar(f->maxstacksize,D); DumpCode(f,D); DumpConstants(f,D); DumpUpvalues(f,D); DumpDebug(f,D); } static void DumpHeader(DumpState* D) { lu_byte h[LUAC_HEADERSIZE]; luaU_header(h); DumpBlock(h,LUAC_HEADERSIZE,D); } /* ** dump Lua function as precompiled chunk */ int luaU_dump (lua_State* L, const Proto* f, lua_Writer w, void* data, int strip) { DumpState D; D.L=L; D.writer=w; D.data=data; D.strip=strip; D.status=0; DumpHeader(&D); DumpFunction(f,&D); return D.status; } april-ann-0.4.1/lua/lua-5.2.2/src/lfunc.c000066400000000000000000000102521263004425400174430ustar00rootroot00000000000000/* ** $Id: lfunc.c,v 2.30 2012/10/03 12:36:46 roberto Exp $ ** Auxiliary functions to manipulate prototypes and closures ** See Copyright Notice in lua.h */ #include #define lfunc_c #define LUA_CORE #include "lua.h" #include "lfunc.h" #include "lgc.h" #include "lmem.h" #include "lobject.h" #include "lstate.h" Closure *luaF_newCclosure (lua_State *L, int n) { Closure *c = &luaC_newobj(L, LUA_TCCL, sizeCclosure(n), NULL, 0)->cl; c->c.nupvalues = cast_byte(n); return c; } Closure *luaF_newLclosure (lua_State *L, int n) { Closure *c = &luaC_newobj(L, LUA_TLCL, sizeLclosure(n), NULL, 0)->cl; c->l.p = NULL; c->l.nupvalues = cast_byte(n); while (n--) c->l.upvals[n] = NULL; return c; } UpVal *luaF_newupval (lua_State *L) { UpVal *uv = &luaC_newobj(L, LUA_TUPVAL, sizeof(UpVal), NULL, 0)->uv; uv->v = &uv->u.value; setnilvalue(uv->v); return uv; } UpVal *luaF_findupval (lua_State *L, StkId level) { global_State *g = G(L); GCObject **pp = &L->openupval; UpVal *p; UpVal *uv; while (*pp != NULL && (p = gco2uv(*pp))->v >= level) { GCObject *o = obj2gco(p); lua_assert(p->v != &p->u.value); lua_assert(!isold(o) || isold(obj2gco(L))); if (p->v == level) { /* found a corresponding upvalue? */ if (isdead(g, o)) /* is it dead? */ changewhite(o); /* resurrect it */ return p; } pp = &p->next; } /* not found: create a new one */ uv = &luaC_newobj(L, LUA_TUPVAL, sizeof(UpVal), pp, 0)->uv; uv->v = level; /* current value lives in the stack */ uv->u.l.prev = &g->uvhead; /* double link it in `uvhead' list */ uv->u.l.next = g->uvhead.u.l.next; uv->u.l.next->u.l.prev = uv; g->uvhead.u.l.next = uv; lua_assert(uv->u.l.next->u.l.prev == uv && uv->u.l.prev->u.l.next == uv); return uv; } static void unlinkupval (UpVal *uv) { lua_assert(uv->u.l.next->u.l.prev == uv && uv->u.l.prev->u.l.next == uv); uv->u.l.next->u.l.prev = uv->u.l.prev; /* remove from `uvhead' list */ uv->u.l.prev->u.l.next = uv->u.l.next; } void luaF_freeupval (lua_State *L, UpVal *uv) { if (uv->v != &uv->u.value) /* is it open? */ unlinkupval(uv); /* remove from open list */ luaM_free(L, uv); /* free upvalue */ } void luaF_close (lua_State *L, StkId level) { UpVal *uv; global_State *g = G(L); while (L->openupval != NULL && (uv = gco2uv(L->openupval))->v >= level) { GCObject *o = obj2gco(uv); lua_assert(!isblack(o) && uv->v != &uv->u.value); L->openupval = uv->next; /* remove from `open' list */ if (isdead(g, o)) luaF_freeupval(L, uv); /* free upvalue */ else { unlinkupval(uv); /* remove upvalue from 'uvhead' list */ setobj(L, &uv->u.value, uv->v); /* move value to upvalue slot */ uv->v = &uv->u.value; /* now current value lives here */ gch(o)->next = g->allgc; /* link upvalue into 'allgc' list */ g->allgc = o; luaC_checkupvalcolor(g, uv); } } } Proto *luaF_newproto (lua_State *L) { Proto *f = &luaC_newobj(L, LUA_TPROTO, sizeof(Proto), NULL, 0)->p; f->k = NULL; f->sizek = 0; f->p = NULL; f->sizep = 0; f->code = NULL; f->cache = NULL; f->sizecode = 0; f->lineinfo = NULL; f->sizelineinfo = 0; f->upvalues = NULL; f->sizeupvalues = 0; f->numparams = 0; f->is_vararg = 0; f->maxstacksize = 0; f->locvars = NULL; f->sizelocvars = 0; f->linedefined = 0; f->lastlinedefined = 0; f->source = NULL; return f; } void luaF_freeproto (lua_State *L, Proto *f) { luaM_freearray(L, f->code, f->sizecode); luaM_freearray(L, f->p, f->sizep); luaM_freearray(L, f->k, f->sizek); luaM_freearray(L, f->lineinfo, f->sizelineinfo); luaM_freearray(L, f->locvars, f->sizelocvars); luaM_freearray(L, f->upvalues, f->sizeupvalues); luaM_free(L, f); } /* ** Look for n-th local variable at line `line' in function `func'. ** Returns NULL if not found. */ const char *luaF_getlocalname (const Proto *f, int local_number, int pc) { int i; for (i = 0; isizelocvars && f->locvars[i].startpc <= pc; i++) { if (pc < f->locvars[i].endpc) { /* is variable active? */ local_number--; if (local_number == 0) return getstr(f->locvars[i].varname); } } return NULL; /* not found */ } april-ann-0.4.1/lua/lua-5.2.2/src/lfunc.h000066400000000000000000000020211263004425400174430ustar00rootroot00000000000000/* ** $Id: lfunc.h,v 2.8 2012/05/08 13:53:33 roberto Exp $ ** Auxiliary functions to manipulate prototypes and closures ** See Copyright Notice in lua.h */ #ifndef lfunc_h #define lfunc_h #include "lobject.h" #define sizeCclosure(n) (cast(int, sizeof(CClosure)) + \ cast(int, sizeof(TValue)*((n)-1))) #define sizeLclosure(n) (cast(int, sizeof(LClosure)) + \ cast(int, sizeof(TValue *)*((n)-1))) LUAI_FUNC Proto *luaF_newproto (lua_State *L); LUAI_FUNC Closure *luaF_newCclosure (lua_State *L, int nelems); LUAI_FUNC Closure *luaF_newLclosure (lua_State *L, int nelems); LUAI_FUNC UpVal *luaF_newupval (lua_State *L); LUAI_FUNC UpVal *luaF_findupval (lua_State *L, StkId level); LUAI_FUNC void luaF_close (lua_State *L, StkId level); LUAI_FUNC void luaF_freeproto (lua_State *L, Proto *f); LUAI_FUNC void luaF_freeupval (lua_State *L, UpVal *uv); LUAI_FUNC const char *luaF_getlocalname (const Proto *func, int local_number, int pc); #endif april-ann-0.4.1/lua/lua-5.2.2/src/lgc.c000066400000000000000000001112011263004425400170750ustar00rootroot00000000000000/* ** $Id: lgc.c,v 2.140 2013/03/16 21:10:18 roberto Exp $ ** Garbage Collector ** See Copyright Notice in lua.h */ #include #define lgc_c #define LUA_CORE #include "lua.h" #include "ldebug.h" #include "ldo.h" #include "lfunc.h" #include "lgc.h" #include "lmem.h" #include "lobject.h" #include "lstate.h" #include "lstring.h" #include "ltable.h" #include "ltm.h" /* ** cost of sweeping one element (the size of a small object divided ** by some adjust for the sweep speed) */ #define GCSWEEPCOST ((sizeof(TString) + 4) / 4) /* maximum number of elements to sweep in each single step */ #define GCSWEEPMAX (cast_int((GCSTEPSIZE / GCSWEEPCOST) / 4)) /* maximum number of finalizers to call in each GC step */ #define GCFINALIZENUM 4 /* ** macro to adjust 'stepmul': 'stepmul' is actually used like ** 'stepmul / STEPMULADJ' (value chosen by tests) */ #define STEPMULADJ 200 /* ** macro to adjust 'pause': 'pause' is actually used like ** 'pause / PAUSEADJ' (value chosen by tests) */ #define PAUSEADJ 100 /* ** 'makewhite' erases all color bits plus the old bit and then ** sets only the current white bit */ #define maskcolors (~(bit2mask(BLACKBIT, OLDBIT) | WHITEBITS)) #define makewhite(g,x) \ (gch(x)->marked = cast_byte((gch(x)->marked & maskcolors) | luaC_white(g))) #define white2gray(x) resetbits(gch(x)->marked, WHITEBITS) #define black2gray(x) resetbit(gch(x)->marked, BLACKBIT) #define isfinalized(x) testbit(gch(x)->marked, FINALIZEDBIT) #define checkdeadkey(n) lua_assert(!ttisdeadkey(gkey(n)) || ttisnil(gval(n))) #define checkconsistency(obj) \ lua_longassert(!iscollectable(obj) || righttt(obj)) #define markvalue(g,o) { checkconsistency(o); \ if (valiswhite(o)) reallymarkobject(g,gcvalue(o)); } #define markobject(g,t) { if ((t) && iswhite(obj2gco(t))) \ reallymarkobject(g, obj2gco(t)); } static void reallymarkobject (global_State *g, GCObject *o); /* ** {====================================================== ** Generic functions ** ======================================================= */ /* ** one after last element in a hash array */ #define gnodelast(h) gnode(h, cast(size_t, sizenode(h))) /* ** link table 'h' into list pointed by 'p' */ #define linktable(h,p) ((h)->gclist = *(p), *(p) = obj2gco(h)) /* ** if key is not marked, mark its entry as dead (therefore removing it ** from the table) */ static void removeentry (Node *n) { lua_assert(ttisnil(gval(n))); if (valiswhite(gkey(n))) setdeadvalue(gkey(n)); /* unused and unmarked key; remove it */ } /* ** tells whether a key or value can be cleared from a weak ** table. Non-collectable objects are never removed from weak ** tables. Strings behave as `values', so are never removed too. for ** other objects: if really collected, cannot keep them; for objects ** being finalized, keep them in keys, but not in values */ static int iscleared (global_State *g, const TValue *o) { if (!iscollectable(o)) return 0; else if (ttisstring(o)) { markobject(g, rawtsvalue(o)); /* strings are `values', so are never weak */ return 0; } else return iswhite(gcvalue(o)); } /* ** barrier that moves collector forward, that is, mark the white object ** being pointed by a black object. */ void luaC_barrier_ (lua_State *L, GCObject *o, GCObject *v) { global_State *g = G(L); lua_assert(isblack(o) && iswhite(v) && !isdead(g, v) && !isdead(g, o)); lua_assert(g->gcstate != GCSpause); lua_assert(gch(o)->tt != LUA_TTABLE); if (keepinvariantout(g)) /* must keep invariant? */ reallymarkobject(g, v); /* restore invariant */ else { /* sweep phase */ lua_assert(issweepphase(g)); makewhite(g, o); /* mark main obj. as white to avoid other barriers */ } } /* ** barrier that moves collector backward, that is, mark the black object ** pointing to a white object as gray again. (Current implementation ** only works for tables; access to 'gclist' is not uniform across ** different types.) */ void luaC_barrierback_ (lua_State *L, GCObject *o) { global_State *g = G(L); lua_assert(isblack(o) && !isdead(g, o) && gch(o)->tt == LUA_TTABLE); black2gray(o); /* make object gray (again) */ gco2t(o)->gclist = g->grayagain; g->grayagain = o; } /* ** barrier for prototypes. When creating first closure (cache is ** NULL), use a forward barrier; this may be the only closure of the ** prototype (if it is a "regular" function, with a single instance) ** and the prototype may be big, so it is better to avoid traversing ** it again. Otherwise, use a backward barrier, to avoid marking all ** possible instances. */ LUAI_FUNC void luaC_barrierproto_ (lua_State *L, Proto *p, Closure *c) { global_State *g = G(L); lua_assert(isblack(obj2gco(p))); if (p->cache == NULL) { /* first time? */ luaC_objbarrier(L, p, c); } else { /* use a backward barrier */ black2gray(obj2gco(p)); /* make prototype gray (again) */ p->gclist = g->grayagain; g->grayagain = obj2gco(p); } } /* ** check color (and invariants) for an upvalue that was closed, ** i.e., moved into the 'allgc' list */ void luaC_checkupvalcolor (global_State *g, UpVal *uv) { GCObject *o = obj2gco(uv); lua_assert(!isblack(o)); /* open upvalues are never black */ if (isgray(o)) { if (keepinvariant(g)) { resetoldbit(o); /* see MOVE OLD rule */ gray2black(o); /* it is being visited now */ markvalue(g, uv->v); } else { lua_assert(issweepphase(g)); makewhite(g, o); } } } /* ** create a new collectable object (with given type and size) and link ** it to '*list'. 'offset' tells how many bytes to allocate before the ** object itself (used only by states). */ GCObject *luaC_newobj (lua_State *L, int tt, size_t sz, GCObject **list, int offset) { global_State *g = G(L); char *raw = cast(char *, luaM_newobject(L, novariant(tt), sz)); GCObject *o = obj2gco(raw + offset); if (list == NULL) list = &g->allgc; /* standard list for collectable objects */ gch(o)->marked = luaC_white(g); gch(o)->tt = tt; gch(o)->next = *list; *list = o; return o; } /* }====================================================== */ /* ** {====================================================== ** Mark functions ** ======================================================= */ /* ** mark an object. Userdata, strings, and closed upvalues are visited ** and turned black here. Other objects are marked gray and added ** to appropriate list to be visited (and turned black) later. (Open ** upvalues are already linked in 'headuv' list.) */ static void reallymarkobject (global_State *g, GCObject *o) { lu_mem size; white2gray(o); switch (gch(o)->tt) { case LUA_TSHRSTR: case LUA_TLNGSTR: { size = sizestring(gco2ts(o)); break; /* nothing else to mark; make it black */ } case LUA_TUSERDATA: { Table *mt = gco2u(o)->metatable; markobject(g, mt); markobject(g, gco2u(o)->env); size = sizeudata(gco2u(o)); break; } case LUA_TUPVAL: { UpVal *uv = gco2uv(o); markvalue(g, uv->v); if (uv->v != &uv->u.value) /* open? */ return; /* open upvalues remain gray */ size = sizeof(UpVal); break; } case LUA_TLCL: { gco2lcl(o)->gclist = g->gray; g->gray = o; return; } case LUA_TCCL: { gco2ccl(o)->gclist = g->gray; g->gray = o; return; } case LUA_TTABLE: { linktable(gco2t(o), &g->gray); return; } case LUA_TTHREAD: { gco2th(o)->gclist = g->gray; g->gray = o; return; } case LUA_TPROTO: { gco2p(o)->gclist = g->gray; g->gray = o; return; } default: lua_assert(0); return; } gray2black(o); g->GCmemtrav += size; } /* ** mark metamethods for basic types */ static void markmt (global_State *g) { int i; for (i=0; i < LUA_NUMTAGS; i++) markobject(g, g->mt[i]); } /* ** mark all objects in list of being-finalized */ static void markbeingfnz (global_State *g) { GCObject *o; for (o = g->tobefnz; o != NULL; o = gch(o)->next) { makewhite(g, o); reallymarkobject(g, o); } } /* ** mark all values stored in marked open upvalues. (See comment in ** 'lstate.h'.) */ static void remarkupvals (global_State *g) { UpVal *uv; for (uv = g->uvhead.u.l.next; uv != &g->uvhead; uv = uv->u.l.next) { if (isgray(obj2gco(uv))) markvalue(g, uv->v); } } /* ** mark root set and reset all gray lists, to start a new ** incremental (or full) collection */ static void restartcollection (global_State *g) { g->gray = g->grayagain = NULL; g->weak = g->allweak = g->ephemeron = NULL; markobject(g, g->mainthread); markvalue(g, &g->l_registry); markmt(g); markbeingfnz(g); /* mark any finalizing object left from previous cycle */ } /* }====================================================== */ /* ** {====================================================== ** Traverse functions ** ======================================================= */ static void traverseweakvalue (global_State *g, Table *h) { Node *n, *limit = gnodelast(h); /* if there is array part, assume it may have white values (do not traverse it just to check) */ int hasclears = (h->sizearray > 0); for (n = gnode(h, 0); n < limit; n++) { checkdeadkey(n); if (ttisnil(gval(n))) /* entry is empty? */ removeentry(n); /* remove it */ else { lua_assert(!ttisnil(gkey(n))); markvalue(g, gkey(n)); /* mark key */ if (!hasclears && iscleared(g, gval(n))) /* is there a white value? */ hasclears = 1; /* table will have to be cleared */ } } if (hasclears) linktable(h, &g->weak); /* has to be cleared later */ else /* no white values */ linktable(h, &g->grayagain); /* no need to clean */ } static int traverseephemeron (global_State *g, Table *h) { int marked = 0; /* true if an object is marked in this traversal */ int hasclears = 0; /* true if table has white keys */ int prop = 0; /* true if table has entry "white-key -> white-value" */ Node *n, *limit = gnodelast(h); int i; /* traverse array part (numeric keys are 'strong') */ for (i = 0; i < h->sizearray; i++) { if (valiswhite(&h->array[i])) { marked = 1; reallymarkobject(g, gcvalue(&h->array[i])); } } /* traverse hash part */ for (n = gnode(h, 0); n < limit; n++) { checkdeadkey(n); if (ttisnil(gval(n))) /* entry is empty? */ removeentry(n); /* remove it */ else if (iscleared(g, gkey(n))) { /* key is not marked (yet)? */ hasclears = 1; /* table must be cleared */ if (valiswhite(gval(n))) /* value not marked yet? */ prop = 1; /* must propagate again */ } else if (valiswhite(gval(n))) { /* value not marked yet? */ marked = 1; reallymarkobject(g, gcvalue(gval(n))); /* mark it now */ } } if (prop) linktable(h, &g->ephemeron); /* have to propagate again */ else if (hasclears) /* does table have white keys? */ linktable(h, &g->allweak); /* may have to clean white keys */ else /* no white keys */ linktable(h, &g->grayagain); /* no need to clean */ return marked; } static void traversestrongtable (global_State *g, Table *h) { Node *n, *limit = gnodelast(h); int i; for (i = 0; i < h->sizearray; i++) /* traverse array part */ markvalue(g, &h->array[i]); for (n = gnode(h, 0); n < limit; n++) { /* traverse hash part */ checkdeadkey(n); if (ttisnil(gval(n))) /* entry is empty? */ removeentry(n); /* remove it */ else { lua_assert(!ttisnil(gkey(n))); markvalue(g, gkey(n)); /* mark key */ markvalue(g, gval(n)); /* mark value */ } } } static lu_mem traversetable (global_State *g, Table *h) { const char *weakkey, *weakvalue; const TValue *mode = gfasttm(g, h->metatable, TM_MODE); markobject(g, h->metatable); if (mode && ttisstring(mode) && /* is there a weak mode? */ ((weakkey = strchr(svalue(mode), 'k')), (weakvalue = strchr(svalue(mode), 'v')), (weakkey || weakvalue))) { /* is really weak? */ black2gray(obj2gco(h)); /* keep table gray */ if (!weakkey) /* strong keys? */ traverseweakvalue(g, h); else if (!weakvalue) /* strong values? */ traverseephemeron(g, h); else /* all weak */ linktable(h, &g->allweak); /* nothing to traverse now */ } else /* not weak */ traversestrongtable(g, h); return sizeof(Table) + sizeof(TValue) * h->sizearray + sizeof(Node) * cast(size_t, sizenode(h)); } static int traverseproto (global_State *g, Proto *f) { int i; if (f->cache && iswhite(obj2gco(f->cache))) f->cache = NULL; /* allow cache to be collected */ markobject(g, f->source); for (i = 0; i < f->sizek; i++) /* mark literals */ markvalue(g, &f->k[i]); for (i = 0; i < f->sizeupvalues; i++) /* mark upvalue names */ markobject(g, f->upvalues[i].name); for (i = 0; i < f->sizep; i++) /* mark nested protos */ markobject(g, f->p[i]); for (i = 0; i < f->sizelocvars; i++) /* mark local-variable names */ markobject(g, f->locvars[i].varname); return sizeof(Proto) + sizeof(Instruction) * f->sizecode + sizeof(Proto *) * f->sizep + sizeof(TValue) * f->sizek + sizeof(int) * f->sizelineinfo + sizeof(LocVar) * f->sizelocvars + sizeof(Upvaldesc) * f->sizeupvalues; } static lu_mem traverseCclosure (global_State *g, CClosure *cl) { int i; for (i = 0; i < cl->nupvalues; i++) /* mark its upvalues */ markvalue(g, &cl->upvalue[i]); return sizeCclosure(cl->nupvalues); } static lu_mem traverseLclosure (global_State *g, LClosure *cl) { int i; markobject(g, cl->p); /* mark its prototype */ for (i = 0; i < cl->nupvalues; i++) /* mark its upvalues */ markobject(g, cl->upvals[i]); return sizeLclosure(cl->nupvalues); } static lu_mem traversestack (global_State *g, lua_State *th) { StkId o = th->stack; if (o == NULL) return 1; /* stack not completely built yet */ for (; o < th->top; o++) markvalue(g, o); if (g->gcstate == GCSatomic) { /* final traversal? */ StkId lim = th->stack + th->stacksize; /* real end of stack */ for (; o < lim; o++) /* clear not-marked stack slice */ setnilvalue(o); } return sizeof(lua_State) + sizeof(TValue) * th->stacksize; } /* ** traverse one gray object, turning it to black (except for threads, ** which are always gray). */ static void propagatemark (global_State *g) { lu_mem size; GCObject *o = g->gray; lua_assert(isgray(o)); gray2black(o); switch (gch(o)->tt) { case LUA_TTABLE: { Table *h = gco2t(o); g->gray = h->gclist; /* remove from 'gray' list */ size = traversetable(g, h); break; } case LUA_TLCL: { LClosure *cl = gco2lcl(o); g->gray = cl->gclist; /* remove from 'gray' list */ size = traverseLclosure(g, cl); break; } case LUA_TCCL: { CClosure *cl = gco2ccl(o); g->gray = cl->gclist; /* remove from 'gray' list */ size = traverseCclosure(g, cl); break; } case LUA_TTHREAD: { lua_State *th = gco2th(o); g->gray = th->gclist; /* remove from 'gray' list */ th->gclist = g->grayagain; g->grayagain = o; /* insert into 'grayagain' list */ black2gray(o); size = traversestack(g, th); break; } case LUA_TPROTO: { Proto *p = gco2p(o); g->gray = p->gclist; /* remove from 'gray' list */ size = traverseproto(g, p); break; } default: lua_assert(0); return; } g->GCmemtrav += size; } static void propagateall (global_State *g) { while (g->gray) propagatemark(g); } static void propagatelist (global_State *g, GCObject *l) { lua_assert(g->gray == NULL); /* no grays left */ g->gray = l; propagateall(g); /* traverse all elements from 'l' */ } /* ** retraverse all gray lists. Because tables may be reinserted in other ** lists when traversed, traverse the original lists to avoid traversing ** twice the same table (which is not wrong, but inefficient) */ static void retraversegrays (global_State *g) { GCObject *weak = g->weak; /* save original lists */ GCObject *grayagain = g->grayagain; GCObject *ephemeron = g->ephemeron; g->weak = g->grayagain = g->ephemeron = NULL; propagateall(g); /* traverse main gray list */ propagatelist(g, grayagain); propagatelist(g, weak); propagatelist(g, ephemeron); } static void convergeephemerons (global_State *g) { int changed; do { GCObject *w; GCObject *next = g->ephemeron; /* get ephemeron list */ g->ephemeron = NULL; /* tables will return to this list when traversed */ changed = 0; while ((w = next) != NULL) { next = gco2t(w)->gclist; if (traverseephemeron(g, gco2t(w))) { /* traverse marked some value? */ propagateall(g); /* propagate changes */ changed = 1; /* will have to revisit all ephemeron tables */ } } } while (changed); } /* }====================================================== */ /* ** {====================================================== ** Sweep Functions ** ======================================================= */ /* ** clear entries with unmarked keys from all weaktables in list 'l' up ** to element 'f' */ static void clearkeys (global_State *g, GCObject *l, GCObject *f) { for (; l != f; l = gco2t(l)->gclist) { Table *h = gco2t(l); Node *n, *limit = gnodelast(h); for (n = gnode(h, 0); n < limit; n++) { if (!ttisnil(gval(n)) && (iscleared(g, gkey(n)))) { setnilvalue(gval(n)); /* remove value ... */ removeentry(n); /* and remove entry from table */ } } } } /* ** clear entries with unmarked values from all weaktables in list 'l' up ** to element 'f' */ static void clearvalues (global_State *g, GCObject *l, GCObject *f) { for (; l != f; l = gco2t(l)->gclist) { Table *h = gco2t(l); Node *n, *limit = gnodelast(h); int i; for (i = 0; i < h->sizearray; i++) { TValue *o = &h->array[i]; if (iscleared(g, o)) /* value was collected? */ setnilvalue(o); /* remove value */ } for (n = gnode(h, 0); n < limit; n++) { if (!ttisnil(gval(n)) && iscleared(g, gval(n))) { setnilvalue(gval(n)); /* remove value ... */ removeentry(n); /* and remove entry from table */ } } } } static void freeobj (lua_State *L, GCObject *o) { switch (gch(o)->tt) { case LUA_TPROTO: luaF_freeproto(L, gco2p(o)); break; case LUA_TLCL: { luaM_freemem(L, o, sizeLclosure(gco2lcl(o)->nupvalues)); break; } case LUA_TCCL: { luaM_freemem(L, o, sizeCclosure(gco2ccl(o)->nupvalues)); break; } case LUA_TUPVAL: luaF_freeupval(L, gco2uv(o)); break; case LUA_TTABLE: luaH_free(L, gco2t(o)); break; case LUA_TTHREAD: luaE_freethread(L, gco2th(o)); break; case LUA_TUSERDATA: luaM_freemem(L, o, sizeudata(gco2u(o))); break; case LUA_TSHRSTR: G(L)->strt.nuse--; /* go through */ case LUA_TLNGSTR: { luaM_freemem(L, o, sizestring(gco2ts(o))); break; } default: lua_assert(0); } } #define sweepwholelist(L,p) sweeplist(L,p,MAX_LUMEM) static GCObject **sweeplist (lua_State *L, GCObject **p, lu_mem count); /* ** sweep the (open) upvalues of a thread and resize its stack and ** list of call-info structures. */ static void sweepthread (lua_State *L, lua_State *L1) { if (L1->stack == NULL) return; /* stack not completely built yet */ sweepwholelist(L, &L1->openupval); /* sweep open upvalues */ luaE_freeCI(L1); /* free extra CallInfo slots */ /* should not change the stack during an emergency gc cycle */ if (G(L)->gckind != KGC_EMERGENCY) luaD_shrinkstack(L1); } /* ** sweep at most 'count' elements from a list of GCObjects erasing dead ** objects, where a dead (not alive) object is one marked with the "old" ** (non current) white and not fixed. ** In non-generational mode, change all non-dead objects back to white, ** preparing for next collection cycle. ** In generational mode, keep black objects black, and also mark them as ** old; stop when hitting an old object, as all objects after that ** one will be old too. ** When object is a thread, sweep its list of open upvalues too. */ static GCObject **sweeplist (lua_State *L, GCObject **p, lu_mem count) { global_State *g = G(L); int ow = otherwhite(g); int toclear, toset; /* bits to clear and to set in all live objects */ int tostop; /* stop sweep when this is true */ if (isgenerational(g)) { /* generational mode? */ toclear = ~0; /* clear nothing */ toset = bitmask(OLDBIT); /* set the old bit of all surviving objects */ tostop = bitmask(OLDBIT); /* do not sweep old generation */ } else { /* normal mode */ toclear = maskcolors; /* clear all color bits + old bit */ toset = luaC_white(g); /* make object white */ tostop = 0; /* do not stop */ } while (*p != NULL && count-- > 0) { GCObject *curr = *p; int marked = gch(curr)->marked; if (isdeadm(ow, marked)) { /* is 'curr' dead? */ *p = gch(curr)->next; /* remove 'curr' from list */ freeobj(L, curr); /* erase 'curr' */ } else { if (testbits(marked, tostop)) return NULL; /* stop sweeping this list */ if (gch(curr)->tt == LUA_TTHREAD) sweepthread(L, gco2th(curr)); /* sweep thread's upvalues */ /* update marks */ gch(curr)->marked = cast_byte((marked & toclear) | toset); p = &gch(curr)->next; /* go to next element */ } } return (*p == NULL) ? NULL : p; } /* ** sweep a list until a live object (or end of list) */ static GCObject **sweeptolive (lua_State *L, GCObject **p, int *n) { GCObject ** old = p; int i = 0; do { i++; p = sweeplist(L, p, 1); } while (p == old); if (n) *n += i; return p; } /* }====================================================== */ /* ** {====================================================== ** Finalization ** ======================================================= */ static void checkSizes (lua_State *L) { global_State *g = G(L); if (g->gckind != KGC_EMERGENCY) { /* do not change sizes in emergency */ int hs = g->strt.size / 2; /* half the size of the string table */ if (g->strt.nuse < cast(lu_int32, hs)) /* using less than that half? */ luaS_resize(L, hs); /* halve its size */ luaZ_freebuffer(L, &g->buff); /* free concatenation buffer */ } } static GCObject *udata2finalize (global_State *g) { GCObject *o = g->tobefnz; /* get first element */ lua_assert(isfinalized(o)); g->tobefnz = gch(o)->next; /* remove it from 'tobefnz' list */ gch(o)->next = g->allgc; /* return it to 'allgc' list */ g->allgc = o; resetbit(gch(o)->marked, SEPARATED); /* mark that it is not in 'tobefnz' */ lua_assert(!isold(o)); /* see MOVE OLD rule */ if (!keepinvariantout(g)) /* not keeping invariant? */ makewhite(g, o); /* "sweep" object */ return o; } static void dothecall (lua_State *L, void *ud) { UNUSED(ud); luaD_call(L, L->top - 2, 0, 0); } static void GCTM (lua_State *L, int propagateerrors) { global_State *g = G(L); const TValue *tm; TValue v; setgcovalue(L, &v, udata2finalize(g)); tm = luaT_gettmbyobj(L, &v, TM_GC); if (tm != NULL && ttisfunction(tm)) { /* is there a finalizer? */ int status; lu_byte oldah = L->allowhook; int running = g->gcrunning; L->allowhook = 0; /* stop debug hooks during GC metamethod */ g->gcrunning = 0; /* avoid GC steps */ setobj2s(L, L->top, tm); /* push finalizer... */ setobj2s(L, L->top + 1, &v); /* ... and its argument */ L->top += 2; /* and (next line) call the finalizer */ status = luaD_pcall(L, dothecall, NULL, savestack(L, L->top - 2), 0); L->allowhook = oldah; /* restore hooks */ g->gcrunning = running; /* restore state */ if (status != LUA_OK && propagateerrors) { /* error while running __gc? */ if (status == LUA_ERRRUN) { /* is there an error object? */ const char *msg = (ttisstring(L->top - 1)) ? svalue(L->top - 1) : "no message"; luaO_pushfstring(L, "error in __gc metamethod (%s)", msg); status = LUA_ERRGCMM; /* error in __gc metamethod */ } luaD_throw(L, status); /* re-throw error */ } } } /* ** move all unreachable objects (or 'all' objects) that need ** finalization from list 'finobj' to list 'tobefnz' (to be finalized) */ static void separatetobefnz (lua_State *L, int all) { global_State *g = G(L); GCObject **p = &g->finobj; GCObject *curr; GCObject **lastnext = &g->tobefnz; /* find last 'next' field in 'tobefnz' list (to add elements in its end) */ while (*lastnext != NULL) lastnext = &gch(*lastnext)->next; while ((curr = *p) != NULL) { /* traverse all finalizable objects */ lua_assert(!isfinalized(curr)); lua_assert(testbit(gch(curr)->marked, SEPARATED)); if (!(iswhite(curr) || all)) /* not being collected? */ p = &gch(curr)->next; /* don't bother with it */ else { l_setbit(gch(curr)->marked, FINALIZEDBIT); /* won't be finalized again */ *p = gch(curr)->next; /* remove 'curr' from 'finobj' list */ gch(curr)->next = *lastnext; /* link at the end of 'tobefnz' list */ *lastnext = curr; lastnext = &gch(curr)->next; } } } /* ** if object 'o' has a finalizer, remove it from 'allgc' list (must ** search the list to find it) and link it in 'finobj' list. */ void luaC_checkfinalizer (lua_State *L, GCObject *o, Table *mt) { global_State *g = G(L); if (testbit(gch(o)->marked, SEPARATED) || /* obj. is already separated... */ isfinalized(o) || /* ... or is finalized... */ gfasttm(g, mt, TM_GC) == NULL) /* or has no finalizer? */ return; /* nothing to be done */ else { /* move 'o' to 'finobj' list */ GCObject **p; GCheader *ho = gch(o); if (g->sweepgc == &ho->next) { /* avoid removing current sweep object */ lua_assert(issweepphase(g)); g->sweepgc = sweeptolive(L, g->sweepgc, NULL); } /* search for pointer pointing to 'o' */ for (p = &g->allgc; *p != o; p = &gch(*p)->next) { /* empty */ } *p = ho->next; /* remove 'o' from root list */ ho->next = g->finobj; /* link it in list 'finobj' */ g->finobj = o; l_setbit(ho->marked, SEPARATED); /* mark it as such */ if (!keepinvariantout(g)) /* not keeping invariant? */ makewhite(g, o); /* "sweep" object */ else resetoldbit(o); /* see MOVE OLD rule */ } } /* }====================================================== */ /* ** {====================================================== ** GC control ** ======================================================= */ /* ** set a reasonable "time" to wait before starting a new GC cycle; ** cycle will start when memory use hits threshold */ static void setpause (global_State *g, l_mem estimate) { l_mem debt, threshold; estimate = estimate / PAUSEADJ; /* adjust 'estimate' */ threshold = (g->gcpause < MAX_LMEM / estimate) /* overflow? */ ? estimate * g->gcpause /* no overflow */ : MAX_LMEM; /* overflow; truncate to maximum */ debt = -cast(l_mem, threshold - gettotalbytes(g)); luaE_setdebt(g, debt); } #define sweepphases \ (bitmask(GCSsweepstring) | bitmask(GCSsweepudata) | bitmask(GCSsweep)) /* ** enter first sweep phase (strings) and prepare pointers for other ** sweep phases. The calls to 'sweeptolive' make pointers point to an ** object inside the list (instead of to the header), so that the real ** sweep do not need to skip objects created between "now" and the start ** of the real sweep. ** Returns how many objects it swept. */ static int entersweep (lua_State *L) { global_State *g = G(L); int n = 0; g->gcstate = GCSsweepstring; lua_assert(g->sweepgc == NULL && g->sweepfin == NULL); /* prepare to sweep strings, finalizable objects, and regular objects */ g->sweepstrgc = 0; g->sweepfin = sweeptolive(L, &g->finobj, &n); g->sweepgc = sweeptolive(L, &g->allgc, &n); return n; } /* ** change GC mode */ void luaC_changemode (lua_State *L, int mode) { global_State *g = G(L); if (mode == g->gckind) return; /* nothing to change */ if (mode == KGC_GEN) { /* change to generational mode */ /* make sure gray lists are consistent */ luaC_runtilstate(L, bitmask(GCSpropagate)); g->GCestimate = gettotalbytes(g); g->gckind = KGC_GEN; } else { /* change to incremental mode */ /* sweep all objects to turn them back to white (as white has not changed, nothing extra will be collected) */ g->gckind = KGC_NORMAL; entersweep(L); luaC_runtilstate(L, ~sweepphases); } } /* ** call all pending finalizers */ static void callallpendingfinalizers (lua_State *L, int propagateerrors) { global_State *g = G(L); while (g->tobefnz) { resetoldbit(g->tobefnz); GCTM(L, propagateerrors); } } void luaC_freeallobjects (lua_State *L) { global_State *g = G(L); int i; separatetobefnz(L, 1); /* separate all objects with finalizers */ lua_assert(g->finobj == NULL); callallpendingfinalizers(L, 0); g->currentwhite = WHITEBITS; /* this "white" makes all objects look dead */ g->gckind = KGC_NORMAL; sweepwholelist(L, &g->finobj); /* finalizers can create objs. in 'finobj' */ sweepwholelist(L, &g->allgc); for (i = 0; i < g->strt.size; i++) /* free all string lists */ sweepwholelist(L, &g->strt.hash[i]); lua_assert(g->strt.nuse == 0); } static l_mem atomic (lua_State *L) { global_State *g = G(L); l_mem work = -cast(l_mem, g->GCmemtrav); /* start counting work */ GCObject *origweak, *origall; lua_assert(!iswhite(obj2gco(g->mainthread))); markobject(g, L); /* mark running thread */ /* registry and global metatables may be changed by API */ markvalue(g, &g->l_registry); markmt(g); /* mark basic metatables */ /* remark occasional upvalues of (maybe) dead threads */ remarkupvals(g); propagateall(g); /* propagate changes */ work += g->GCmemtrav; /* stop counting (do not (re)count grays) */ /* traverse objects caught by write barrier and by 'remarkupvals' */ retraversegrays(g); work -= g->GCmemtrav; /* restart counting */ convergeephemerons(g); /* at this point, all strongly accessible objects are marked. */ /* clear values from weak tables, before checking finalizers */ clearvalues(g, g->weak, NULL); clearvalues(g, g->allweak, NULL); origweak = g->weak; origall = g->allweak; work += g->GCmemtrav; /* stop counting (objects being finalized) */ separatetobefnz(L, 0); /* separate objects to be finalized */ markbeingfnz(g); /* mark objects that will be finalized */ propagateall(g); /* remark, to propagate `preserveness' */ work -= g->GCmemtrav; /* restart counting */ convergeephemerons(g); /* at this point, all resurrected objects are marked. */ /* remove dead objects from weak tables */ clearkeys(g, g->ephemeron, NULL); /* clear keys from all ephemeron tables */ clearkeys(g, g->allweak, NULL); /* clear keys from all allweak tables */ /* clear values from resurrected weak tables */ clearvalues(g, g->weak, origweak); clearvalues(g, g->allweak, origall); g->currentwhite = cast_byte(otherwhite(g)); /* flip current white */ work += g->GCmemtrav; /* complete counting */ return work; /* estimate of memory marked by 'atomic' */ } static lu_mem singlestep (lua_State *L) { global_State *g = G(L); switch (g->gcstate) { case GCSpause: { /* start to count memory traversed */ g->GCmemtrav = g->strt.size * sizeof(GCObject*); lua_assert(!isgenerational(g)); restartcollection(g); g->gcstate = GCSpropagate; return g->GCmemtrav; } case GCSpropagate: { if (g->gray) { lu_mem oldtrav = g->GCmemtrav; propagatemark(g); return g->GCmemtrav - oldtrav; /* memory traversed in this step */ } else { /* no more `gray' objects */ lu_mem work; int sw; g->gcstate = GCSatomic; /* finish mark phase */ g->GCestimate = g->GCmemtrav; /* save what was counted */; work = atomic(L); /* add what was traversed by 'atomic' */ g->GCestimate += work; /* estimate of total memory traversed */ sw = entersweep(L); return work + sw * GCSWEEPCOST; } } case GCSsweepstring: { int i; for (i = 0; i < GCSWEEPMAX && g->sweepstrgc + i < g->strt.size; i++) sweepwholelist(L, &g->strt.hash[g->sweepstrgc + i]); g->sweepstrgc += i; if (g->sweepstrgc >= g->strt.size) /* no more strings to sweep? */ g->gcstate = GCSsweepudata; return i * GCSWEEPCOST; } case GCSsweepudata: { if (g->sweepfin) { g->sweepfin = sweeplist(L, g->sweepfin, GCSWEEPMAX); return GCSWEEPMAX*GCSWEEPCOST; } else { g->gcstate = GCSsweep; return 0; } } case GCSsweep: { if (g->sweepgc) { g->sweepgc = sweeplist(L, g->sweepgc, GCSWEEPMAX); return GCSWEEPMAX*GCSWEEPCOST; } else { /* sweep main thread */ GCObject *mt = obj2gco(g->mainthread); sweeplist(L, &mt, 1); checkSizes(L); g->gcstate = GCSpause; /* finish collection */ return GCSWEEPCOST; } } default: lua_assert(0); return 0; } } /* ** advances the garbage collector until it reaches a state allowed ** by 'statemask' */ void luaC_runtilstate (lua_State *L, int statesmask) { global_State *g = G(L); while (!testbit(statesmask, g->gcstate)) singlestep(L); } static void generationalcollection (lua_State *L) { global_State *g = G(L); lua_assert(g->gcstate == GCSpropagate); if (g->GCestimate == 0) { /* signal for another major collection? */ luaC_fullgc(L, 0); /* perform a full regular collection */ g->GCestimate = gettotalbytes(g); /* update control */ } else { lu_mem estimate = g->GCestimate; luaC_runtilstate(L, bitmask(GCSpause)); /* run complete (minor) cycle */ g->gcstate = GCSpropagate; /* skip restart */ if (gettotalbytes(g) > (estimate / 100) * g->gcmajorinc) g->GCestimate = 0; /* signal for a major collection */ else g->GCestimate = estimate; /* keep estimate from last major coll. */ } setpause(g, gettotalbytes(g)); lua_assert(g->gcstate == GCSpropagate); } static void incstep (lua_State *L) { global_State *g = G(L); l_mem debt = g->GCdebt; int stepmul = g->gcstepmul; if (stepmul < 40) stepmul = 40; /* avoid ridiculous low values (and 0) */ /* convert debt from Kb to 'work units' (avoid zero debt and overflows) */ debt = (debt / STEPMULADJ) + 1; debt = (debt < MAX_LMEM / stepmul) ? debt * stepmul : MAX_LMEM; do { /* always perform at least one single step */ lu_mem work = singlestep(L); /* do some work */ debt -= work; } while (debt > -GCSTEPSIZE && g->gcstate != GCSpause); if (g->gcstate == GCSpause) setpause(g, g->GCestimate); /* pause until next cycle */ else { debt = (debt / stepmul) * STEPMULADJ; /* convert 'work units' to Kb */ luaE_setdebt(g, debt); } } /* ** performs a basic GC step */ void luaC_forcestep (lua_State *L) { global_State *g = G(L); int i; if (isgenerational(g)) generationalcollection(L); else incstep(L); /* run a few finalizers (or all of them at the end of a collect cycle) */ for (i = 0; g->tobefnz && (i < GCFINALIZENUM || g->gcstate == GCSpause); i++) GCTM(L, 1); /* call one finalizer */ } /* ** performs a basic GC step only if collector is running */ void luaC_step (lua_State *L) { global_State *g = G(L); if (g->gcrunning) luaC_forcestep(L); else luaE_setdebt(g, -GCSTEPSIZE); /* avoid being called too often */ } /* ** performs a full GC cycle; if "isemergency", does not call ** finalizers (which could change stack positions) */ void luaC_fullgc (lua_State *L, int isemergency) { global_State *g = G(L); int origkind = g->gckind; lua_assert(origkind != KGC_EMERGENCY); if (isemergency) /* do not run finalizers during emergency GC */ g->gckind = KGC_EMERGENCY; else { g->gckind = KGC_NORMAL; callallpendingfinalizers(L, 1); } if (keepinvariant(g)) { /* may there be some black objects? */ /* must sweep all objects to turn them back to white (as white has not changed, nothing will be collected) */ entersweep(L); } /* finish any pending sweep phase to start a new cycle */ luaC_runtilstate(L, bitmask(GCSpause)); luaC_runtilstate(L, ~bitmask(GCSpause)); /* start new collection */ luaC_runtilstate(L, bitmask(GCSpause)); /* run entire collection */ if (origkind == KGC_GEN) { /* generational mode? */ /* generational mode must be kept in propagate phase */ luaC_runtilstate(L, bitmask(GCSpropagate)); } g->gckind = origkind; setpause(g, gettotalbytes(g)); if (!isemergency) /* do not run finalizers during emergency GC */ callallpendingfinalizers(L, 1); } /* }====================================================== */ april-ann-0.4.1/lua/lua-5.2.2/src/lgc.h000066400000000000000000000124301263004425400171060ustar00rootroot00000000000000/* ** $Id: lgc.h,v 2.58 2012/09/11 12:53:08 roberto Exp $ ** Garbage Collector ** See Copyright Notice in lua.h */ #ifndef lgc_h #define lgc_h #include "lobject.h" #include "lstate.h" /* ** Collectable objects may have one of three colors: white, which ** means the object is not marked; gray, which means the ** object is marked, but its references may be not marked; and ** black, which means that the object and all its references are marked. ** The main invariant of the garbage collector, while marking objects, ** is that a black object can never point to a white one. Moreover, ** any gray object must be in a "gray list" (gray, grayagain, weak, ** allweak, ephemeron) so that it can be visited again before finishing ** the collection cycle. These lists have no meaning when the invariant ** is not being enforced (e.g., sweep phase). */ /* how much to allocate before next GC step */ #if !defined(GCSTEPSIZE) /* ~100 small strings */ #define GCSTEPSIZE (cast_int(100 * sizeof(TString))) #endif /* ** Possible states of the Garbage Collector */ #define GCSpropagate 0 #define GCSatomic 1 #define GCSsweepstring 2 #define GCSsweepudata 3 #define GCSsweep 4 #define GCSpause 5 #define issweepphase(g) \ (GCSsweepstring <= (g)->gcstate && (g)->gcstate <= GCSsweep) #define isgenerational(g) ((g)->gckind == KGC_GEN) /* ** macros to tell when main invariant (white objects cannot point to black ** ones) must be kept. During a non-generational collection, the sweep ** phase may break the invariant, as objects turned white may point to ** still-black objects. The invariant is restored when sweep ends and ** all objects are white again. During a generational collection, the ** invariant must be kept all times. */ #define keepinvariant(g) (isgenerational(g) || g->gcstate <= GCSatomic) /* ** Outside the collector, the state in generational mode is kept in ** 'propagate', so 'keepinvariant' is always true. */ #define keepinvariantout(g) \ check_exp(g->gcstate == GCSpropagate || !isgenerational(g), \ g->gcstate <= GCSatomic) /* ** some useful bit tricks */ #define resetbits(x,m) ((x) &= cast(lu_byte, ~(m))) #define setbits(x,m) ((x) |= (m)) #define testbits(x,m) ((x) & (m)) #define bitmask(b) (1<<(b)) #define bit2mask(b1,b2) (bitmask(b1) | bitmask(b2)) #define l_setbit(x,b) setbits(x, bitmask(b)) #define resetbit(x,b) resetbits(x, bitmask(b)) #define testbit(x,b) testbits(x, bitmask(b)) /* Layout for bit use in `marked' field: */ #define WHITE0BIT 0 /* object is white (type 0) */ #define WHITE1BIT 1 /* object is white (type 1) */ #define BLACKBIT 2 /* object is black */ #define FINALIZEDBIT 3 /* object has been separated for finalization */ #define SEPARATED 4 /* object is in 'finobj' list or in 'tobefnz' */ #define FIXEDBIT 5 /* object is fixed (should not be collected) */ #define OLDBIT 6 /* object is old (only in generational mode) */ /* bit 7 is currently used by tests (luaL_checkmemory) */ #define WHITEBITS bit2mask(WHITE0BIT, WHITE1BIT) #define iswhite(x) testbits((x)->gch.marked, WHITEBITS) #define isblack(x) testbit((x)->gch.marked, BLACKBIT) #define isgray(x) /* neither white nor black */ \ (!testbits((x)->gch.marked, WHITEBITS | bitmask(BLACKBIT))) #define isold(x) testbit((x)->gch.marked, OLDBIT) /* MOVE OLD rule: whenever an object is moved to the beginning of a GC list, its old bit must be cleared */ #define resetoldbit(o) resetbit((o)->gch.marked, OLDBIT) #define otherwhite(g) (g->currentwhite ^ WHITEBITS) #define isdeadm(ow,m) (!(((m) ^ WHITEBITS) & (ow))) #define isdead(g,v) isdeadm(otherwhite(g), (v)->gch.marked) #define changewhite(x) ((x)->gch.marked ^= WHITEBITS) #define gray2black(x) l_setbit((x)->gch.marked, BLACKBIT) #define valiswhite(x) (iscollectable(x) && iswhite(gcvalue(x))) #define luaC_white(g) cast(lu_byte, (g)->currentwhite & WHITEBITS) #define luaC_condGC(L,c) \ {if (G(L)->GCdebt > 0) {c;}; condchangemem(L);} #define luaC_checkGC(L) luaC_condGC(L, luaC_step(L);) #define luaC_barrier(L,p,v) { if (valiswhite(v) && isblack(obj2gco(p))) \ luaC_barrier_(L,obj2gco(p),gcvalue(v)); } #define luaC_barrierback(L,p,v) { if (valiswhite(v) && isblack(obj2gco(p))) \ luaC_barrierback_(L,p); } #define luaC_objbarrier(L,p,o) \ { if (iswhite(obj2gco(o)) && isblack(obj2gco(p))) \ luaC_barrier_(L,obj2gco(p),obj2gco(o)); } #define luaC_objbarrierback(L,p,o) \ { if (iswhite(obj2gco(o)) && isblack(obj2gco(p))) luaC_barrierback_(L,p); } #define luaC_barrierproto(L,p,c) \ { if (isblack(obj2gco(p))) luaC_barrierproto_(L,p,c); } LUAI_FUNC void luaC_freeallobjects (lua_State *L); LUAI_FUNC void luaC_step (lua_State *L); LUAI_FUNC void luaC_forcestep (lua_State *L); LUAI_FUNC void luaC_runtilstate (lua_State *L, int statesmask); LUAI_FUNC void luaC_fullgc (lua_State *L, int isemergency); LUAI_FUNC GCObject *luaC_newobj (lua_State *L, int tt, size_t sz, GCObject **list, int offset); LUAI_FUNC void luaC_barrier_ (lua_State *L, GCObject *o, GCObject *v); LUAI_FUNC void luaC_barrierback_ (lua_State *L, GCObject *o); LUAI_FUNC void luaC_barrierproto_ (lua_State *L, Proto *p, Closure *c); LUAI_FUNC void luaC_checkfinalizer (lua_State *L, GCObject *o, Table *mt); LUAI_FUNC void luaC_checkupvalcolor (global_State *g, UpVal *uv); LUAI_FUNC void luaC_changemode (lua_State *L, int mode); #endif april-ann-0.4.1/lua/lua-5.2.2/src/linit.c000066400000000000000000000032251263004425400174550ustar00rootroot00000000000000/* ** $Id: linit.c,v 1.32 2011/04/08 19:17:36 roberto Exp $ ** Initialization of libraries for lua.c and other clients ** See Copyright Notice in lua.h */ /* ** If you embed Lua in your program and need to open the standard ** libraries, call luaL_openlibs in your program. If you need a ** different set of libraries, copy this file to your project and edit ** it to suit your needs. */ #define linit_c #define LUA_LIB #include "lua.h" #include "lualib.h" #include "lauxlib.h" /* ** these libs are loaded by lua.c and are readily available to any Lua ** program */ static const luaL_Reg loadedlibs[] = { {"_G", luaopen_base}, {LUA_LOADLIBNAME, luaopen_package}, {LUA_COLIBNAME, luaopen_coroutine}, {LUA_TABLIBNAME, luaopen_table}, {LUA_IOLIBNAME, luaopen_io}, {LUA_OSLIBNAME, luaopen_os}, {LUA_STRLIBNAME, luaopen_string}, {LUA_BITLIBNAME, luaopen_bit32}, {LUA_MATHLIBNAME, luaopen_math}, {LUA_DBLIBNAME, luaopen_debug}, {NULL, NULL} }; /* ** these libs are preloaded and must be required before used */ static const luaL_Reg preloadedlibs[] = { {NULL, NULL} }; LUALIB_API void luaL_openlibs (lua_State *L) { const luaL_Reg *lib; /* call open functions from 'loadedlibs' and set results to global table */ for (lib = loadedlibs; lib->func; lib++) { luaL_requiref(L, lib->name, lib->func, 1); lua_pop(L, 1); /* remove lib */ } /* add open functions from 'preloadedlibs' into 'package.preload' table */ luaL_getsubtable(L, LUA_REGISTRYINDEX, "_PRELOAD"); for (lib = preloadedlibs; lib->func; lib++) { lua_pushcfunction(L, lib->func); lua_setfield(L, -2, lib->name); } lua_pop(L, 1); /* remove _PRELOAD table */ } april-ann-0.4.1/lua/lua-5.2.2/src/liolib.c000066400000000000000000000376221263004425400176200ustar00rootroot00000000000000/* ** $Id: liolib.c,v 2.111 2013/03/21 13:57:27 roberto Exp $ ** Standard I/O (and system) library ** See Copyright Notice in lua.h */ /* ** POSIX idiosyncrasy! ** This definition must come before the inclusion of 'stdio.h'; it ** should not affect non-POSIX systems */ #if !defined(_FILE_OFFSET_BITS) #define _FILE_OFFSET_BITS 64 #endif #include #include #include #include #define liolib_c #define LUA_LIB #include "lua.h" #include "lauxlib.h" #include "lualib.h" #if !defined(lua_checkmode) /* ** Check whether 'mode' matches '[rwa]%+?b?'. ** Change this macro to accept other modes for 'fopen' besides ** the standard ones. */ #define lua_checkmode(mode) \ (*mode != '\0' && strchr("rwa", *(mode++)) != NULL && \ (*mode != '+' || ++mode) && /* skip if char is '+' */ \ (*mode != 'b' || ++mode) && /* skip if char is 'b' */ \ (*mode == '\0')) #endif /* ** {====================================================== ** lua_fseek/lua_ftell: configuration for longer offsets ** ======================================================= */ #if !defined(lua_fseek) /* { */ #if defined(LUA_USE_POSIX) #define l_fseek(f,o,w) fseeko(f,o,w) #define l_ftell(f) ftello(f) #define l_seeknum off_t #elif defined(LUA_WIN) && !defined(_CRTIMP_TYPEINFO) \ && defined(_MSC_VER) && (_MSC_VER >= 1400) /* Windows (but not DDK) and Visual C++ 2005 or higher */ #define l_fseek(f,o,w) _fseeki64(f,o,w) #define l_ftell(f) _ftelli64(f) #define l_seeknum __int64 #else #define l_fseek(f,o,w) fseek(f,o,w) #define l_ftell(f) ftell(f) #define l_seeknum long #endif #endif /* } */ /* }====================================================== */ #define IO_PREFIX "_IO_" #define IO_INPUT (IO_PREFIX "input") #define IO_OUTPUT (IO_PREFIX "output") typedef luaL_Stream LStream; #define tolstream(L) ((LStream *)luaL_checkudata(L, 1, LUA_FILEHANDLE)) #define isclosed(p) ((p)->closef == NULL) static int io_type (lua_State *L) { LStream *p; luaL_checkany(L, 1); p = (LStream *)luaL_testudata(L, 1, LUA_FILEHANDLE); if (p == NULL) lua_pushnil(L); /* not a file */ else if (isclosed(p)) lua_pushliteral(L, "closed file"); else lua_pushliteral(L, "file"); return 1; } static int f_tostring (lua_State *L) { LStream *p = tolstream(L); if (isclosed(p)) lua_pushliteral(L, "file (closed)"); else lua_pushfstring(L, "file (%p)", p->f); return 1; } static FILE *tofile (lua_State *L) { LStream *p = tolstream(L); if (isclosed(p)) luaL_error(L, "attempt to use a closed file"); lua_assert(p->f); return p->f; } /* ** When creating file handles, always creates a `closed' file handle ** before opening the actual file; so, if there is a memory error, the ** file is not left opened. */ static LStream *newprefile (lua_State *L) { LStream *p = (LStream *)lua_newuserdata(L, sizeof(LStream)); p->closef = NULL; /* mark file handle as 'closed' */ luaL_setmetatable(L, LUA_FILEHANDLE); return p; } static int aux_close (lua_State *L) { LStream *p = tolstream(L); lua_CFunction cf = p->closef; p->closef = NULL; /* mark stream as closed */ return (*cf)(L); /* close it */ } static int io_close (lua_State *L) { if (lua_isnone(L, 1)) /* no argument? */ lua_getfield(L, LUA_REGISTRYINDEX, IO_OUTPUT); /* use standard output */ tofile(L); /* make sure argument is an open stream */ return aux_close(L); } static int f_gc (lua_State *L) { LStream *p = tolstream(L); if (!isclosed(p) && p->f != NULL) aux_close(L); /* ignore closed and incompletely open files */ return 0; } /* ** function to close regular files */ static int io_fclose (lua_State *L) { LStream *p = tolstream(L); int res = fclose(p->f); return luaL_fileresult(L, (res == 0), NULL); } static LStream *newfile (lua_State *L) { LStream *p = newprefile(L); p->f = NULL; p->closef = &io_fclose; return p; } static void opencheck (lua_State *L, const char *fname, const char *mode) { LStream *p = newfile(L); p->f = fopen(fname, mode); if (p->f == NULL) luaL_error(L, "cannot open file " LUA_QS " (%s)", fname, strerror(errno)); } static int io_open (lua_State *L) { const char *filename = luaL_checkstring(L, 1); const char *mode = luaL_optstring(L, 2, "r"); LStream *p = newfile(L); const char *md = mode; /* to traverse/check mode */ luaL_argcheck(L, lua_checkmode(md), 2, "invalid mode"); p->f = fopen(filename, mode); return (p->f == NULL) ? luaL_fileresult(L, 0, filename) : 1; } /* ** function to close 'popen' files */ static int io_pclose (lua_State *L) { LStream *p = tolstream(L); return luaL_execresult(L, lua_pclose(L, p->f)); } static int io_popen (lua_State *L) { const char *filename = luaL_checkstring(L, 1); const char *mode = luaL_optstring(L, 2, "r"); LStream *p = newprefile(L); p->f = lua_popen(L, filename, mode); p->closef = &io_pclose; return (p->f == NULL) ? luaL_fileresult(L, 0, filename) : 1; } static int io_tmpfile (lua_State *L) { LStream *p = newfile(L); p->f = tmpfile(); return (p->f == NULL) ? luaL_fileresult(L, 0, NULL) : 1; } static FILE *getiofile (lua_State *L, const char *findex) { LStream *p; lua_getfield(L, LUA_REGISTRYINDEX, findex); p = (LStream *)lua_touserdata(L, -1); if (isclosed(p)) luaL_error(L, "standard %s file is closed", findex + strlen(IO_PREFIX)); return p->f; } static int g_iofile (lua_State *L, const char *f, const char *mode) { if (!lua_isnoneornil(L, 1)) { const char *filename = lua_tostring(L, 1); if (filename) opencheck(L, filename, mode); else { tofile(L); /* check that it's a valid file handle */ lua_pushvalue(L, 1); } lua_setfield(L, LUA_REGISTRYINDEX, f); } /* return current value */ lua_getfield(L, LUA_REGISTRYINDEX, f); return 1; } static int io_input (lua_State *L) { return g_iofile(L, IO_INPUT, "r"); } static int io_output (lua_State *L) { return g_iofile(L, IO_OUTPUT, "w"); } static int io_readline (lua_State *L); static void aux_lines (lua_State *L, int toclose) { int i; int n = lua_gettop(L) - 1; /* number of arguments to read */ /* ensure that arguments will fit here and into 'io_readline' stack */ luaL_argcheck(L, n <= LUA_MINSTACK - 3, LUA_MINSTACK - 3, "too many options"); lua_pushvalue(L, 1); /* file handle */ lua_pushinteger(L, n); /* number of arguments to read */ lua_pushboolean(L, toclose); /* close/not close file when finished */ for (i = 1; i <= n; i++) lua_pushvalue(L, i + 1); /* copy arguments */ lua_pushcclosure(L, io_readline, 3 + n); } static int f_lines (lua_State *L) { tofile(L); /* check that it's a valid file handle */ aux_lines(L, 0); return 1; } static int io_lines (lua_State *L) { int toclose; if (lua_isnone(L, 1)) lua_pushnil(L); /* at least one argument */ if (lua_isnil(L, 1)) { /* no file name? */ lua_getfield(L, LUA_REGISTRYINDEX, IO_INPUT); /* get default input */ lua_replace(L, 1); /* put it at index 1 */ tofile(L); /* check that it's a valid file handle */ toclose = 0; /* do not close it after iteration */ } else { /* open a new file */ const char *filename = luaL_checkstring(L, 1); opencheck(L, filename, "r"); lua_replace(L, 1); /* put file at index 1 */ toclose = 1; /* close it after iteration */ } aux_lines(L, toclose); return 1; } /* ** {====================================================== ** READ ** ======================================================= */ static int read_number (lua_State *L, FILE *f) { lua_Number d; if (fscanf(f, LUA_NUMBER_SCAN, &d) == 1) { lua_pushnumber(L, d); return 1; } else { lua_pushnil(L); /* "result" to be removed */ return 0; /* read fails */ } } static int test_eof (lua_State *L, FILE *f) { int c = getc(f); ungetc(c, f); lua_pushlstring(L, NULL, 0); return (c != EOF); } static int read_line (lua_State *L, FILE *f, int chop) { luaL_Buffer b; luaL_buffinit(L, &b); for (;;) { size_t l; char *p = luaL_prepbuffer(&b); if (fgets(p, LUAL_BUFFERSIZE, f) == NULL) { /* eof? */ luaL_pushresult(&b); /* close buffer */ return (lua_rawlen(L, -1) > 0); /* check whether read something */ } l = strlen(p); if (l == 0 || p[l-1] != '\n') luaL_addsize(&b, l); else { luaL_addsize(&b, l - chop); /* chop 'eol' if needed */ luaL_pushresult(&b); /* close buffer */ return 1; /* read at least an `eol' */ } } } #define MAX_SIZE_T (~(size_t)0) static void read_all (lua_State *L, FILE *f) { size_t rlen = LUAL_BUFFERSIZE; /* how much to read in each cycle */ luaL_Buffer b; luaL_buffinit(L, &b); for (;;) { char *p = luaL_prepbuffsize(&b, rlen); size_t nr = fread(p, sizeof(char), rlen, f); luaL_addsize(&b, nr); if (nr < rlen) break; /* eof? */ else if (rlen <= (MAX_SIZE_T / 4)) /* avoid buffers too large */ rlen *= 2; /* double buffer size at each iteration */ } luaL_pushresult(&b); /* close buffer */ } static int read_chars (lua_State *L, FILE *f, size_t n) { size_t nr; /* number of chars actually read */ char *p; luaL_Buffer b; luaL_buffinit(L, &b); p = luaL_prepbuffsize(&b, n); /* prepare buffer to read whole block */ nr = fread(p, sizeof(char), n, f); /* try to read 'n' chars */ luaL_addsize(&b, nr); luaL_pushresult(&b); /* close buffer */ return (nr > 0); /* true iff read something */ } static int g_read (lua_State *L, FILE *f, int first) { int nargs = lua_gettop(L) - 1; int success; int n; clearerr(f); if (nargs == 0) { /* no arguments? */ success = read_line(L, f, 1); n = first+1; /* to return 1 result */ } else { /* ensure stack space for all results and for auxlib's buffer */ luaL_checkstack(L, nargs+LUA_MINSTACK, "too many arguments"); success = 1; for (n = first; nargs-- && success; n++) { if (lua_type(L, n) == LUA_TNUMBER) { size_t l = (size_t)lua_tointeger(L, n); success = (l == 0) ? test_eof(L, f) : read_chars(L, f, l); } else { const char *p = lua_tostring(L, n); luaL_argcheck(L, p && p[0] == '*', n, "invalid option"); switch (p[1]) { case 'n': /* number */ success = read_number(L, f); break; case 'l': /* line */ success = read_line(L, f, 1); break; case 'L': /* line with end-of-line */ success = read_line(L, f, 0); break; case 'a': /* file */ read_all(L, f); /* read entire file */ success = 1; /* always success */ break; default: return luaL_argerror(L, n, "invalid format"); } } } } if (ferror(f)) return luaL_fileresult(L, 0, NULL); if (!success) { lua_pop(L, 1); /* remove last result */ lua_pushnil(L); /* push nil instead */ } return n - first; } static int io_read (lua_State *L) { return g_read(L, getiofile(L, IO_INPUT), 1); } static int f_read (lua_State *L) { return g_read(L, tofile(L), 2); } static int io_readline (lua_State *L) { LStream *p = (LStream *)lua_touserdata(L, lua_upvalueindex(1)); int i; int n = (int)lua_tointeger(L, lua_upvalueindex(2)); if (isclosed(p)) /* file is already closed? */ return luaL_error(L, "file is already closed"); lua_settop(L , 1); for (i = 1; i <= n; i++) /* push arguments to 'g_read' */ lua_pushvalue(L, lua_upvalueindex(3 + i)); n = g_read(L, p->f, 2); /* 'n' is number of results */ lua_assert(n > 0); /* should return at least a nil */ if (!lua_isnil(L, -n)) /* read at least one value? */ return n; /* return them */ else { /* first result is nil: EOF or error */ if (n > 1) { /* is there error information? */ /* 2nd result is error message */ return luaL_error(L, "%s", lua_tostring(L, -n + 1)); } if (lua_toboolean(L, lua_upvalueindex(3))) { /* generator created file? */ lua_settop(L, 0); lua_pushvalue(L, lua_upvalueindex(1)); aux_close(L); /* close it */ } return 0; } } /* }====================================================== */ static int g_write (lua_State *L, FILE *f, int arg) { int nargs = lua_gettop(L) - arg; int status = 1; for (; nargs--; arg++) { if (lua_type(L, arg) == LUA_TNUMBER) { /* optimization: could be done exactly as for strings */ status = status && fprintf(f, LUA_NUMBER_FMT, lua_tonumber(L, arg)) > 0; } else { size_t l; const char *s = luaL_checklstring(L, arg, &l); status = status && (fwrite(s, sizeof(char), l, f) == l); } } if (status) return 1; /* file handle already on stack top */ else return luaL_fileresult(L, status, NULL); } static int io_write (lua_State *L) { return g_write(L, getiofile(L, IO_OUTPUT), 1); } static int f_write (lua_State *L) { FILE *f = tofile(L); lua_pushvalue(L, 1); /* push file at the stack top (to be returned) */ return g_write(L, f, 2); } static int f_seek (lua_State *L) { static const int mode[] = {SEEK_SET, SEEK_CUR, SEEK_END}; static const char *const modenames[] = {"set", "cur", "end", NULL}; FILE *f = tofile(L); int op = luaL_checkoption(L, 2, "cur", modenames); lua_Number p3 = luaL_optnumber(L, 3, 0); l_seeknum offset = (l_seeknum)p3; luaL_argcheck(L, (lua_Number)offset == p3, 3, "not an integer in proper range"); op = l_fseek(f, offset, mode[op]); if (op) return luaL_fileresult(L, 0, NULL); /* error */ else { lua_pushnumber(L, (lua_Number)l_ftell(f)); return 1; } } static int f_setvbuf (lua_State *L) { static const int mode[] = {_IONBF, _IOFBF, _IOLBF}; static const char *const modenames[] = {"no", "full", "line", NULL}; FILE *f = tofile(L); int op = luaL_checkoption(L, 2, NULL, modenames); lua_Integer sz = luaL_optinteger(L, 3, LUAL_BUFFERSIZE); int res = setvbuf(f, NULL, mode[op], sz); return luaL_fileresult(L, res == 0, NULL); } static int io_flush (lua_State *L) { return luaL_fileresult(L, fflush(getiofile(L, IO_OUTPUT)) == 0, NULL); } static int f_flush (lua_State *L) { return luaL_fileresult(L, fflush(tofile(L)) == 0, NULL); } /* ** functions for 'io' library */ static const luaL_Reg iolib[] = { {"close", io_close}, {"flush", io_flush}, {"input", io_input}, {"lines", io_lines}, {"open", io_open}, {"output", io_output}, {"popen", io_popen}, {"read", io_read}, {"tmpfile", io_tmpfile}, {"type", io_type}, {"write", io_write}, {NULL, NULL} }; /* ** methods for file handles */ static const luaL_Reg flib[] = { {"close", io_close}, {"flush", f_flush}, {"lines", f_lines}, {"read", f_read}, {"seek", f_seek}, {"setvbuf", f_setvbuf}, {"write", f_write}, {"__gc", f_gc}, {"__tostring", f_tostring}, {NULL, NULL} }; static void createmeta (lua_State *L) { luaL_newmetatable(L, LUA_FILEHANDLE); /* create metatable for file handles */ lua_pushvalue(L, -1); /* push metatable */ lua_setfield(L, -2, "__index"); /* metatable.__index = metatable */ luaL_setfuncs(L, flib, 0); /* add file methods to new metatable */ lua_pop(L, 1); /* pop new metatable */ } /* ** function to (not) close the standard files stdin, stdout, and stderr */ static int io_noclose (lua_State *L) { LStream *p = tolstream(L); p->closef = &io_noclose; /* keep file opened */ lua_pushnil(L); lua_pushliteral(L, "cannot close standard file"); return 2; } static void createstdfile (lua_State *L, FILE *f, const char *k, const char *fname) { LStream *p = newprefile(L); p->f = f; p->closef = &io_noclose; if (k != NULL) { lua_pushvalue(L, -1); lua_setfield(L, LUA_REGISTRYINDEX, k); /* add file to registry */ } lua_setfield(L, -2, fname); /* add file to module */ } LUAMOD_API int luaopen_io (lua_State *L) { luaL_newlib(L, iolib); /* new module */ createmeta(L); /* create (and set) default files */ createstdfile(L, stdin, IO_INPUT, "stdin"); createstdfile(L, stdout, IO_OUTPUT, "stdout"); createstdfile(L, stderr, NULL, "stderr"); return 1; } april-ann-0.4.1/lua/lua-5.2.2/src/llex.c000066400000000000000000000355551263004425400173150ustar00rootroot00000000000000/* ** $Id: llex.c,v 2.63 2013/03/16 21:10:18 roberto Exp $ ** Lexical Analyzer ** See Copyright Notice in lua.h */ #include #include #define llex_c #define LUA_CORE #include "lua.h" #include "lctype.h" #include "ldo.h" #include "llex.h" #include "lobject.h" #include "lparser.h" #include "lstate.h" #include "lstring.h" #include "ltable.h" #include "lzio.h" #define next(ls) (ls->current = zgetc(ls->z)) #define currIsNewline(ls) (ls->current == '\n' || ls->current == '\r') /* ORDER RESERVED */ const char *const luaX_tokens [] = { "and", "break", "do", "else", "elseif", "end", "false", "for", "function", "goto", "if", "in", "local", "nil", "not", "or", "repeat", "return", "then", "true", "until", "while", "..", "...", "==", ">=", "<=", "~=", "::", "", "", "", "" }; #define save_and_next(ls) (save(ls, ls->current), next(ls)) static l_noret lexerror (LexState *ls, const char *msg, int token); static void save (LexState *ls, int c) { Mbuffer *b = ls->buff; if (luaZ_bufflen(b) + 1 > luaZ_sizebuffer(b)) { size_t newsize; if (luaZ_sizebuffer(b) >= MAX_SIZET/2) lexerror(ls, "lexical element too long", 0); newsize = luaZ_sizebuffer(b) * 2; luaZ_resizebuffer(ls->L, b, newsize); } b->buffer[luaZ_bufflen(b)++] = cast(char, c); } void luaX_init (lua_State *L) { int i; for (i=0; itsv.extra = cast_byte(i+1); /* reserved word */ } } const char *luaX_token2str (LexState *ls, int token) { if (token < FIRST_RESERVED) { /* single-byte symbols? */ lua_assert(token == cast(unsigned char, token)); return (lisprint(token)) ? luaO_pushfstring(ls->L, LUA_QL("%c"), token) : luaO_pushfstring(ls->L, "char(%d)", token); } else { const char *s = luaX_tokens[token - FIRST_RESERVED]; if (token < TK_EOS) /* fixed format (symbols and reserved words)? */ return luaO_pushfstring(ls->L, LUA_QS, s); else /* names, strings, and numerals */ return s; } } static const char *txtToken (LexState *ls, int token) { switch (token) { case TK_NAME: case TK_STRING: case TK_NUMBER: save(ls, '\0'); return luaO_pushfstring(ls->L, LUA_QS, luaZ_buffer(ls->buff)); default: return luaX_token2str(ls, token); } } static l_noret lexerror (LexState *ls, const char *msg, int token) { char buff[LUA_IDSIZE]; luaO_chunkid(buff, getstr(ls->source), LUA_IDSIZE); msg = luaO_pushfstring(ls->L, "%s:%d: %s", buff, ls->linenumber, msg); if (token) luaO_pushfstring(ls->L, "%s near %s", msg, txtToken(ls, token)); luaD_throw(ls->L, LUA_ERRSYNTAX); } l_noret luaX_syntaxerror (LexState *ls, const char *msg) { lexerror(ls, msg, ls->t.token); } /* ** creates a new string and anchors it in function's table so that ** it will not be collected until the end of the function's compilation ** (by that time it should be anchored in function's prototype) */ TString *luaX_newstring (LexState *ls, const char *str, size_t l) { lua_State *L = ls->L; TValue *o; /* entry for `str' */ TString *ts = luaS_newlstr(L, str, l); /* create new string */ setsvalue2s(L, L->top++, ts); /* temporarily anchor it in stack */ o = luaH_set(L, ls->fs->h, L->top - 1); if (ttisnil(o)) { /* not in use yet? (see 'addK') */ /* boolean value does not need GC barrier; table has no metatable, so it does not need to invalidate cache */ setbvalue(o, 1); /* t[string] = true */ luaC_checkGC(L); } L->top--; /* remove string from stack */ return ts; } /* ** increment line number and skips newline sequence (any of ** \n, \r, \n\r, or \r\n) */ static void inclinenumber (LexState *ls) { int old = ls->current; lua_assert(currIsNewline(ls)); next(ls); /* skip `\n' or `\r' */ if (currIsNewline(ls) && ls->current != old) next(ls); /* skip `\n\r' or `\r\n' */ if (++ls->linenumber >= MAX_INT) luaX_syntaxerror(ls, "chunk has too many lines"); } void luaX_setinput (lua_State *L, LexState *ls, ZIO *z, TString *source, int firstchar) { ls->decpoint = '.'; ls->L = L; ls->current = firstchar; ls->lookahead.token = TK_EOS; /* no look-ahead token */ ls->z = z; ls->fs = NULL; ls->linenumber = 1; ls->lastline = 1; ls->source = source; ls->envn = luaS_new(L, LUA_ENV); /* create env name */ luaS_fix(ls->envn); /* never collect this name */ luaZ_resizebuffer(ls->L, ls->buff, LUA_MINBUFFER); /* initialize buffer */ } /* ** ======================================================= ** LEXICAL ANALYZER ** ======================================================= */ static int check_next (LexState *ls, const char *set) { if (ls->current == '\0' || !strchr(set, ls->current)) return 0; save_and_next(ls); return 1; } /* ** change all characters 'from' in buffer to 'to' */ static void buffreplace (LexState *ls, char from, char to) { size_t n = luaZ_bufflen(ls->buff); char *p = luaZ_buffer(ls->buff); while (n--) if (p[n] == from) p[n] = to; } #if !defined(getlocaledecpoint) #define getlocaledecpoint() (localeconv()->decimal_point[0]) #endif #define buff2d(b,e) luaO_str2d(luaZ_buffer(b), luaZ_bufflen(b) - 1, e) /* ** in case of format error, try to change decimal point separator to ** the one defined in the current locale and check again */ static void trydecpoint (LexState *ls, SemInfo *seminfo) { char old = ls->decpoint; ls->decpoint = getlocaledecpoint(); buffreplace(ls, old, ls->decpoint); /* try new decimal separator */ if (!buff2d(ls->buff, &seminfo->r)) { /* format error with correct decimal point: no more options */ buffreplace(ls, ls->decpoint, '.'); /* undo change (for error message) */ lexerror(ls, "malformed number", TK_NUMBER); } } /* LUA_NUMBER */ /* ** this function is quite liberal in what it accepts, as 'luaO_str2d' ** will reject ill-formed numerals. */ static void read_numeral (LexState *ls, SemInfo *seminfo) { const char *expo = "Ee"; int first = ls->current; lua_assert(lisdigit(ls->current)); save_and_next(ls); if (first == '0' && check_next(ls, "Xx")) /* hexadecimal? */ expo = "Pp"; for (;;) { if (check_next(ls, expo)) /* exponent part? */ check_next(ls, "+-"); /* optional exponent sign */ if (lisxdigit(ls->current) || ls->current == '.') save_and_next(ls); else break; } save(ls, '\0'); buffreplace(ls, '.', ls->decpoint); /* follow locale for decimal point */ if (!buff2d(ls->buff, &seminfo->r)) /* format error? */ trydecpoint(ls, seminfo); /* try to update decimal point separator */ } /* ** skip a sequence '[=*[' or ']=*]' and return its number of '='s or ** -1 if sequence is malformed */ static int skip_sep (LexState *ls) { int count = 0; int s = ls->current; lua_assert(s == '[' || s == ']'); save_and_next(ls); while (ls->current == '=') { save_and_next(ls); count++; } return (ls->current == s) ? count : (-count) - 1; } static void read_long_string (LexState *ls, SemInfo *seminfo, int sep) { save_and_next(ls); /* skip 2nd `[' */ if (currIsNewline(ls)) /* string starts with a newline? */ inclinenumber(ls); /* skip it */ for (;;) { switch (ls->current) { case EOZ: lexerror(ls, (seminfo) ? "unfinished long string" : "unfinished long comment", TK_EOS); break; /* to avoid warnings */ case ']': { if (skip_sep(ls) == sep) { save_and_next(ls); /* skip 2nd `]' */ goto endloop; } break; } case '\n': case '\r': { save(ls, '\n'); inclinenumber(ls); if (!seminfo) luaZ_resetbuffer(ls->buff); /* avoid wasting space */ break; } default: { if (seminfo) save_and_next(ls); else next(ls); } } } endloop: if (seminfo) seminfo->ts = luaX_newstring(ls, luaZ_buffer(ls->buff) + (2 + sep), luaZ_bufflen(ls->buff) - 2*(2 + sep)); } static void escerror (LexState *ls, int *c, int n, const char *msg) { int i; luaZ_resetbuffer(ls->buff); /* prepare error message */ save(ls, '\\'); for (i = 0; i < n && c[i] != EOZ; i++) save(ls, c[i]); lexerror(ls, msg, TK_STRING); } static int readhexaesc (LexState *ls) { int c[3], i; /* keep input for error message */ int r = 0; /* result accumulator */ c[0] = 'x'; /* for error message */ for (i = 1; i < 3; i++) { /* read two hexadecimal digits */ c[i] = next(ls); if (!lisxdigit(c[i])) escerror(ls, c, i + 1, "hexadecimal digit expected"); r = (r << 4) + luaO_hexavalue(c[i]); } return r; } static int readdecesc (LexState *ls) { int c[3], i; int r = 0; /* result accumulator */ for (i = 0; i < 3 && lisdigit(ls->current); i++) { /* read up to 3 digits */ c[i] = ls->current; r = 10*r + c[i] - '0'; next(ls); } if (r > UCHAR_MAX) escerror(ls, c, i, "decimal escape too large"); return r; } static void read_string (LexState *ls, int del, SemInfo *seminfo) { save_and_next(ls); /* keep delimiter (for error messages) */ while (ls->current != del) { switch (ls->current) { case EOZ: lexerror(ls, "unfinished string", TK_EOS); break; /* to avoid warnings */ case '\n': case '\r': lexerror(ls, "unfinished string", TK_STRING); break; /* to avoid warnings */ case '\\': { /* escape sequences */ int c; /* final character to be saved */ next(ls); /* do not save the `\' */ switch (ls->current) { case 'a': c = '\a'; goto read_save; case 'b': c = '\b'; goto read_save; case 'f': c = '\f'; goto read_save; case 'n': c = '\n'; goto read_save; case 'r': c = '\r'; goto read_save; case 't': c = '\t'; goto read_save; case 'v': c = '\v'; goto read_save; case 'x': c = readhexaesc(ls); goto read_save; case '\n': case '\r': inclinenumber(ls); c = '\n'; goto only_save; case '\\': case '\"': case '\'': c = ls->current; goto read_save; case EOZ: goto no_save; /* will raise an error next loop */ case 'z': { /* zap following span of spaces */ next(ls); /* skip the 'z' */ while (lisspace(ls->current)) { if (currIsNewline(ls)) inclinenumber(ls); else next(ls); } goto no_save; } default: { if (!lisdigit(ls->current)) escerror(ls, &ls->current, 1, "invalid escape sequence"); /* digital escape \ddd */ c = readdecesc(ls); goto only_save; } } read_save: next(ls); /* read next character */ only_save: save(ls, c); /* save 'c' */ no_save: break; } default: save_and_next(ls); } } save_and_next(ls); /* skip delimiter */ seminfo->ts = luaX_newstring(ls, luaZ_buffer(ls->buff) + 1, luaZ_bufflen(ls->buff) - 2); } static int llex (LexState *ls, SemInfo *seminfo) { luaZ_resetbuffer(ls->buff); for (;;) { switch (ls->current) { case '\n': case '\r': { /* line breaks */ inclinenumber(ls); break; } case ' ': case '\f': case '\t': case '\v': { /* spaces */ next(ls); break; } case '-': { /* '-' or '--' (comment) */ next(ls); if (ls->current != '-') return '-'; /* else is a comment */ next(ls); if (ls->current == '[') { /* long comment? */ int sep = skip_sep(ls); luaZ_resetbuffer(ls->buff); /* `skip_sep' may dirty the buffer */ if (sep >= 0) { read_long_string(ls, NULL, sep); /* skip long comment */ luaZ_resetbuffer(ls->buff); /* previous call may dirty the buff. */ break; } } /* else short comment */ while (!currIsNewline(ls) && ls->current != EOZ) next(ls); /* skip until end of line (or end of file) */ break; } case '[': { /* long string or simply '[' */ int sep = skip_sep(ls); if (sep >= 0) { read_long_string(ls, seminfo, sep); return TK_STRING; } else if (sep == -1) return '['; else lexerror(ls, "invalid long string delimiter", TK_STRING); } case '=': { next(ls); if (ls->current != '=') return '='; else { next(ls); return TK_EQ; } } case '<': { next(ls); if (ls->current != '=') return '<'; else { next(ls); return TK_LE; } } case '>': { next(ls); if (ls->current != '=') return '>'; else { next(ls); return TK_GE; } } case '~': { next(ls); if (ls->current != '=') return '~'; else { next(ls); return TK_NE; } } case ':': { next(ls); if (ls->current != ':') return ':'; else { next(ls); return TK_DBCOLON; } } case '"': case '\'': { /* short literal strings */ read_string(ls, ls->current, seminfo); return TK_STRING; } case '.': { /* '.', '..', '...', or number */ save_and_next(ls); if (check_next(ls, ".")) { if (check_next(ls, ".")) return TK_DOTS; /* '...' */ else return TK_CONCAT; /* '..' */ } else if (!lisdigit(ls->current)) return '.'; /* else go through */ } case '0': case '1': case '2': case '3': case '4': case '5': case '6': case '7': case '8': case '9': { read_numeral(ls, seminfo); return TK_NUMBER; } case EOZ: { return TK_EOS; } default: { if (lislalpha(ls->current)) { /* identifier or reserved word? */ TString *ts; do { save_and_next(ls); } while (lislalnum(ls->current)); ts = luaX_newstring(ls, luaZ_buffer(ls->buff), luaZ_bufflen(ls->buff)); seminfo->ts = ts; if (isreserved(ts)) /* reserved word? */ return ts->tsv.extra - 1 + FIRST_RESERVED; else { return TK_NAME; } } else { /* single-char tokens (+ - / ...) */ int c = ls->current; next(ls); return c; } } } } } void luaX_next (LexState *ls) { ls->lastline = ls->linenumber; if (ls->lookahead.token != TK_EOS) { /* is there a look-ahead token? */ ls->t = ls->lookahead; /* use this one */ ls->lookahead.token = TK_EOS; /* and discharge it */ } else ls->t.token = llex(ls, &ls->t.seminfo); /* read next token */ } int luaX_lookahead (LexState *ls) { lua_assert(ls->lookahead.token == TK_EOS); ls->lookahead.token = llex(ls, &ls->lookahead.seminfo); return ls->lookahead.token; } april-ann-0.4.1/lua/lua-5.2.2/src/llex.h000066400000000000000000000041561263004425400173130ustar00rootroot00000000000000/* ** $Id: llex.h,v 1.72 2011/11/30 12:43:51 roberto Exp $ ** Lexical Analyzer ** See Copyright Notice in lua.h */ #ifndef llex_h #define llex_h #include "lobject.h" #include "lzio.h" #define FIRST_RESERVED 257 /* * WARNING: if you change the order of this enumeration, * grep "ORDER RESERVED" */ enum RESERVED { /* terminal symbols denoted by reserved words */ TK_AND = FIRST_RESERVED, TK_BREAK, TK_DO, TK_ELSE, TK_ELSEIF, TK_END, TK_FALSE, TK_FOR, TK_FUNCTION, TK_GOTO, TK_IF, TK_IN, TK_LOCAL, TK_NIL, TK_NOT, TK_OR, TK_REPEAT, TK_RETURN, TK_THEN, TK_TRUE, TK_UNTIL, TK_WHILE, /* other terminal symbols */ TK_CONCAT, TK_DOTS, TK_EQ, TK_GE, TK_LE, TK_NE, TK_DBCOLON, TK_EOS, TK_NUMBER, TK_NAME, TK_STRING }; /* number of reserved words */ #define NUM_RESERVED (cast(int, TK_WHILE-FIRST_RESERVED+1)) typedef union { lua_Number r; TString *ts; } SemInfo; /* semantics information */ typedef struct Token { int token; SemInfo seminfo; } Token; /* state of the lexer plus state of the parser when shared by all functions */ typedef struct LexState { int current; /* current character (charint) */ int linenumber; /* input line counter */ int lastline; /* line of last token `consumed' */ Token t; /* current token */ Token lookahead; /* look ahead token */ struct FuncState *fs; /* current function (parser) */ struct lua_State *L; ZIO *z; /* input stream */ Mbuffer *buff; /* buffer for tokens */ struct Dyndata *dyd; /* dynamic structures used by the parser */ TString *source; /* current source name */ TString *envn; /* environment variable name */ char decpoint; /* locale decimal point */ } LexState; LUAI_FUNC void luaX_init (lua_State *L); LUAI_FUNC void luaX_setinput (lua_State *L, LexState *ls, ZIO *z, TString *source, int firstchar); LUAI_FUNC TString *luaX_newstring (LexState *ls, const char *str, size_t l); LUAI_FUNC void luaX_next (LexState *ls); LUAI_FUNC int luaX_lookahead (LexState *ls); LUAI_FUNC l_noret luaX_syntaxerror (LexState *ls, const char *s); LUAI_FUNC const char *luaX_token2str (LexState *ls, int token); #endif april-ann-0.4.1/lua/lua-5.2.2/src/llimits.h000066400000000000000000000165451263004425400200310ustar00rootroot00000000000000/* ** $Id: llimits.h,v 1.103 2013/02/20 14:08:56 roberto Exp $ ** Limits, basic types, and some other `installation-dependent' definitions ** See Copyright Notice in lua.h */ #ifndef llimits_h #define llimits_h #include #include #include "lua.h" typedef unsigned LUA_INT32 lu_int32; typedef LUAI_UMEM lu_mem; typedef LUAI_MEM l_mem; /* chars used as small naturals (so that `char' is reserved for characters) */ typedef unsigned char lu_byte; #define MAX_SIZET ((size_t)(~(size_t)0)-2) #define MAX_LUMEM ((lu_mem)(~(lu_mem)0)-2) #define MAX_LMEM ((l_mem) ((MAX_LUMEM >> 1) - 2)) #define MAX_INT (INT_MAX-2) /* maximum value of an int (-2 for safety) */ /* ** conversion of pointer to integer ** this is for hashing only; there is no problem if the integer ** cannot hold the whole pointer value */ #define IntPoint(p) ((unsigned int)(lu_mem)(p)) /* type to ensure maximum alignment */ #if !defined(LUAI_USER_ALIGNMENT_T) #define LUAI_USER_ALIGNMENT_T union { double u; void *s; long l; } #endif typedef LUAI_USER_ALIGNMENT_T L_Umaxalign; /* result of a `usual argument conversion' over lua_Number */ typedef LUAI_UACNUMBER l_uacNumber; /* internal assertions for in-house debugging */ #if defined(lua_assert) #define check_exp(c,e) (lua_assert(c), (e)) /* to avoid problems with conditions too long */ #define lua_longassert(c) { if (!(c)) lua_assert(0); } #else #define lua_assert(c) ((void)0) #define check_exp(c,e) (e) #define lua_longassert(c) ((void)0) #endif /* ** assertion for checking API calls */ #if !defined(luai_apicheck) #if defined(LUA_USE_APICHECK) #include #define luai_apicheck(L,e) assert(e) #else #define luai_apicheck(L,e) lua_assert(e) #endif #endif #define api_check(l,e,msg) luai_apicheck(l,(e) && msg) #if !defined(UNUSED) #define UNUSED(x) ((void)(x)) /* to avoid warnings */ #endif #define cast(t, exp) ((t)(exp)) #define cast_byte(i) cast(lu_byte, (i)) #define cast_num(i) cast(lua_Number, (i)) #define cast_int(i) cast(int, (i)) #define cast_uchar(i) cast(unsigned char, (i)) /* ** non-return type */ #if defined(__GNUC__) #define l_noret void __attribute__((noreturn)) #elif defined(_MSC_VER) #define l_noret void __declspec(noreturn) #else #define l_noret void #endif /* ** maximum depth for nested C calls and syntactical nested non-terminals ** in a program. (Value must fit in an unsigned short int.) */ #if !defined(LUAI_MAXCCALLS) #define LUAI_MAXCCALLS 200 #endif /* ** maximum number of upvalues in a closure (both C and Lua). (Value ** must fit in an unsigned char.) */ #define MAXUPVAL UCHAR_MAX /* ** type for virtual-machine instructions ** must be an unsigned with (at least) 4 bytes (see details in lopcodes.h) */ typedef lu_int32 Instruction; /* maximum stack for a Lua function */ #define MAXSTACK 250 /* minimum size for the string table (must be power of 2) */ #if !defined(MINSTRTABSIZE) #define MINSTRTABSIZE 32 #endif /* minimum size for string buffer */ #if !defined(LUA_MINBUFFER) #define LUA_MINBUFFER 32 #endif #if !defined(lua_lock) #define lua_lock(L) ((void) 0) #define lua_unlock(L) ((void) 0) #endif #if !defined(luai_threadyield) #define luai_threadyield(L) {lua_unlock(L); lua_lock(L);} #endif /* ** these macros allow user-specific actions on threads when you defined ** LUAI_EXTRASPACE and need to do something extra when a thread is ** created/deleted/resumed/yielded. */ #if !defined(luai_userstateopen) #define luai_userstateopen(L) ((void)L) #endif #if !defined(luai_userstateclose) #define luai_userstateclose(L) ((void)L) #endif #if !defined(luai_userstatethread) #define luai_userstatethread(L,L1) ((void)L) #endif #if !defined(luai_userstatefree) #define luai_userstatefree(L,L1) ((void)L) #endif #if !defined(luai_userstateresume) #define luai_userstateresume(L,n) ((void)L) #endif #if !defined(luai_userstateyield) #define luai_userstateyield(L,n) ((void)L) #endif /* ** lua_number2int is a macro to convert lua_Number to int. ** lua_number2integer is a macro to convert lua_Number to lua_Integer. ** lua_number2unsigned is a macro to convert a lua_Number to a lua_Unsigned. ** lua_unsigned2number is a macro to convert a lua_Unsigned to a lua_Number. ** luai_hashnum is a macro to hash a lua_Number value into an integer. ** The hash must be deterministic and give reasonable values for ** both small and large values (outside the range of integers). */ #if defined(MS_ASMTRICK) || defined(LUA_MSASMTRICK) /* { */ /* trick with Microsoft assembler for X86 */ #define lua_number2int(i,n) __asm {__asm fld n __asm fistp i} #define lua_number2integer(i,n) lua_number2int(i, n) #define lua_number2unsigned(i,n) \ {__int64 l; __asm {__asm fld n __asm fistp l} i = (unsigned int)l;} #elif defined(LUA_IEEE754TRICK) /* }{ */ /* the next trick should work on any machine using IEEE754 with a 32-bit int type */ union luai_Cast { double l_d; LUA_INT32 l_p[2]; }; #if !defined(LUA_IEEEENDIAN) /* { */ #define LUAI_EXTRAIEEE \ static const union luai_Cast ieeeendian = {-(33.0 + 6755399441055744.0)}; #define LUA_IEEEENDIANLOC (ieeeendian.l_p[1] == 33) #else #define LUA_IEEEENDIANLOC LUA_IEEEENDIAN #define LUAI_EXTRAIEEE /* empty */ #endif /* } */ #define lua_number2int32(i,n,t) \ { LUAI_EXTRAIEEE \ volatile union luai_Cast u; u.l_d = (n) + 6755399441055744.0; \ (i) = (t)u.l_p[LUA_IEEEENDIANLOC]; } #define luai_hashnum(i,n) \ { volatile union luai_Cast u; u.l_d = (n) + 1.0; /* avoid -0 */ \ (i) = u.l_p[0]; (i) += u.l_p[1]; } /* add double bits for his hash */ #define lua_number2int(i,n) lua_number2int32(i, n, int) #define lua_number2unsigned(i,n) lua_number2int32(i, n, lua_Unsigned) /* the trick can be expanded to lua_Integer when it is a 32-bit value */ #if defined(LUA_IEEELL) #define lua_number2integer(i,n) lua_number2int32(i, n, lua_Integer) #endif #endif /* } */ /* the following definitions always work, but may be slow */ #if !defined(lua_number2int) #define lua_number2int(i,n) ((i)=(int)(n)) #endif #if !defined(lua_number2integer) #define lua_number2integer(i,n) ((i)=(lua_Integer)(n)) #endif #if !defined(lua_number2unsigned) /* { */ /* the following definition assures proper modulo behavior */ #if defined(LUA_NUMBER_DOUBLE) || defined(LUA_NUMBER_FLOAT) #include #define SUPUNSIGNED ((lua_Number)(~(lua_Unsigned)0) + 1) #define lua_number2unsigned(i,n) \ ((i)=(lua_Unsigned)((n) - floor((n)/SUPUNSIGNED)*SUPUNSIGNED)) #else #define lua_number2unsigned(i,n) ((i)=(lua_Unsigned)(n)) #endif #endif /* } */ #if !defined(lua_unsigned2number) /* on several machines, coercion from unsigned to double is slow, so it may be worth to avoid */ #define lua_unsigned2number(u) \ (((u) <= (lua_Unsigned)INT_MAX) ? (lua_Number)(int)(u) : (lua_Number)(u)) #endif #if defined(ltable_c) && !defined(luai_hashnum) #include #include #define luai_hashnum(i,n) { int e; \ n = l_mathop(frexp)(n, &e) * (lua_Number)(INT_MAX - DBL_MAX_EXP); \ lua_number2int(i, n); i += e; } #endif /* ** macro to control inclusion of some hard tests on stack reallocation */ #if !defined(HARDSTACKTESTS) #define condmovestack(L) ((void)0) #else /* realloc stack keeping its size */ #define condmovestack(L) luaD_reallocstack((L), (L)->stacksize) #endif #if !defined(HARDMEMTESTS) #define condchangemem(L) condmovestack(L) #else #define condchangemem(L) \ ((void)(!(G(L)->gcrunning) || (luaC_fullgc(L, 0), 1))) #endif #endif april-ann-0.4.1/lua/lua-5.2.2/src/lmathlib.c000066400000000000000000000146661263004425400201450ustar00rootroot00000000000000/* ** $Id: lmathlib.c,v 1.83 2013/03/07 18:21:32 roberto Exp $ ** Standard mathematical library ** See Copyright Notice in lua.h */ #include #include #define lmathlib_c #define LUA_LIB #include "lua.h" #include "lauxlib.h" #include "lualib.h" #undef PI #define PI ((lua_Number)(3.1415926535897932384626433832795)) #define RADIANS_PER_DEGREE ((lua_Number)(PI/180.0)) static int math_abs (lua_State *L) { lua_pushnumber(L, l_mathop(fabs)(luaL_checknumber(L, 1))); return 1; } static int math_sin (lua_State *L) { lua_pushnumber(L, l_mathop(sin)(luaL_checknumber(L, 1))); return 1; } static int math_sinh (lua_State *L) { lua_pushnumber(L, l_mathop(sinh)(luaL_checknumber(L, 1))); return 1; } static int math_cos (lua_State *L) { lua_pushnumber(L, l_mathop(cos)(luaL_checknumber(L, 1))); return 1; } static int math_cosh (lua_State *L) { lua_pushnumber(L, l_mathop(cosh)(luaL_checknumber(L, 1))); return 1; } static int math_tan (lua_State *L) { lua_pushnumber(L, l_mathop(tan)(luaL_checknumber(L, 1))); return 1; } static int math_tanh (lua_State *L) { lua_pushnumber(L, l_mathop(tanh)(luaL_checknumber(L, 1))); return 1; } static int math_asin (lua_State *L) { lua_pushnumber(L, l_mathop(asin)(luaL_checknumber(L, 1))); return 1; } static int math_acos (lua_State *L) { lua_pushnumber(L, l_mathop(acos)(luaL_checknumber(L, 1))); return 1; } static int math_atan (lua_State *L) { lua_pushnumber(L, l_mathop(atan)(luaL_checknumber(L, 1))); return 1; } static int math_atan2 (lua_State *L) { lua_pushnumber(L, l_mathop(atan2)(luaL_checknumber(L, 1), luaL_checknumber(L, 2))); return 1; } static int math_ceil (lua_State *L) { lua_pushnumber(L, l_mathop(ceil)(luaL_checknumber(L, 1))); return 1; } static int math_floor (lua_State *L) { lua_pushnumber(L, l_mathop(floor)(luaL_checknumber(L, 1))); return 1; } static int math_fmod (lua_State *L) { lua_pushnumber(L, l_mathop(fmod)(luaL_checknumber(L, 1), luaL_checknumber(L, 2))); return 1; } static int math_modf (lua_State *L) { lua_Number ip; lua_Number fp = l_mathop(modf)(luaL_checknumber(L, 1), &ip); lua_pushnumber(L, ip); lua_pushnumber(L, fp); return 2; } static int math_sqrt (lua_State *L) { lua_pushnumber(L, l_mathop(sqrt)(luaL_checknumber(L, 1))); return 1; } static int math_pow (lua_State *L) { lua_Number x = luaL_checknumber(L, 1); lua_Number y = luaL_checknumber(L, 2); lua_pushnumber(L, l_mathop(pow)(x, y)); return 1; } static int math_log (lua_State *L) { lua_Number x = luaL_checknumber(L, 1); lua_Number res; if (lua_isnoneornil(L, 2)) res = l_mathop(log)(x); else { lua_Number base = luaL_checknumber(L, 2); if (base == (lua_Number)10.0) res = l_mathop(log10)(x); else res = l_mathop(log)(x)/l_mathop(log)(base); } lua_pushnumber(L, res); return 1; } #if defined(LUA_COMPAT_LOG10) static int math_log10 (lua_State *L) { lua_pushnumber(L, l_mathop(log10)(luaL_checknumber(L, 1))); return 1; } #endif static int math_exp (lua_State *L) { lua_pushnumber(L, l_mathop(exp)(luaL_checknumber(L, 1))); return 1; } static int math_deg (lua_State *L) { lua_pushnumber(L, luaL_checknumber(L, 1)/RADIANS_PER_DEGREE); return 1; } static int math_rad (lua_State *L) { lua_pushnumber(L, luaL_checknumber(L, 1)*RADIANS_PER_DEGREE); return 1; } static int math_frexp (lua_State *L) { int e; lua_pushnumber(L, l_mathop(frexp)(luaL_checknumber(L, 1), &e)); lua_pushinteger(L, e); return 2; } static int math_ldexp (lua_State *L) { lua_Number x = luaL_checknumber(L, 1); int ep = luaL_checkint(L, 2); lua_pushnumber(L, l_mathop(ldexp)(x, ep)); return 1; } static int math_min (lua_State *L) { int n = lua_gettop(L); /* number of arguments */ lua_Number dmin = luaL_checknumber(L, 1); int i; for (i=2; i<=n; i++) { lua_Number d = luaL_checknumber(L, i); if (d < dmin) dmin = d; } lua_pushnumber(L, dmin); return 1; } static int math_max (lua_State *L) { int n = lua_gettop(L); /* number of arguments */ lua_Number dmax = luaL_checknumber(L, 1); int i; for (i=2; i<=n; i++) { lua_Number d = luaL_checknumber(L, i); if (d > dmax) dmax = d; } lua_pushnumber(L, dmax); return 1; } static int math_random (lua_State *L) { /* the `%' avoids the (rare) case of r==1, and is needed also because on some systems (SunOS!) `rand()' may return a value larger than RAND_MAX */ lua_Number r = (lua_Number)(rand()%RAND_MAX) / (lua_Number)RAND_MAX; switch (lua_gettop(L)) { /* check number of arguments */ case 0: { /* no arguments */ lua_pushnumber(L, r); /* Number between 0 and 1 */ break; } case 1: { /* only upper limit */ lua_Number u = luaL_checknumber(L, 1); luaL_argcheck(L, (lua_Number)1.0 <= u, 1, "interval is empty"); lua_pushnumber(L, l_mathop(floor)(r*u) + (lua_Number)(1.0)); /* [1, u] */ break; } case 2: { /* lower and upper limits */ lua_Number l = luaL_checknumber(L, 1); lua_Number u = luaL_checknumber(L, 2); luaL_argcheck(L, l <= u, 2, "interval is empty"); lua_pushnumber(L, l_mathop(floor)(r*(u-l+1)) + l); /* [l, u] */ break; } default: return luaL_error(L, "wrong number of arguments"); } return 1; } static int math_randomseed (lua_State *L) { srand(luaL_checkunsigned(L, 1)); (void)rand(); /* discard first value to avoid undesirable correlations */ return 0; } static const luaL_Reg mathlib[] = { {"abs", math_abs}, {"acos", math_acos}, {"asin", math_asin}, {"atan2", math_atan2}, {"atan", math_atan}, {"ceil", math_ceil}, {"cosh", math_cosh}, {"cos", math_cos}, {"deg", math_deg}, {"exp", math_exp}, {"floor", math_floor}, {"fmod", math_fmod}, {"frexp", math_frexp}, {"ldexp", math_ldexp}, #if defined(LUA_COMPAT_LOG10) {"log10", math_log10}, #endif {"log", math_log}, {"max", math_max}, {"min", math_min}, {"modf", math_modf}, {"pow", math_pow}, {"rad", math_rad}, {"random", math_random}, {"randomseed", math_randomseed}, {"sinh", math_sinh}, {"sin", math_sin}, {"sqrt", math_sqrt}, {"tanh", math_tanh}, {"tan", math_tan}, {NULL, NULL} }; /* ** Open math library */ LUAMOD_API int luaopen_math (lua_State *L) { luaL_newlib(L, mathlib); lua_pushnumber(L, PI); lua_setfield(L, -2, "pi"); lua_pushnumber(L, HUGE_VAL); lua_setfield(L, -2, "huge"); return 1; } april-ann-0.4.1/lua/lua-5.2.2/src/lmem.c000066400000000000000000000051261263004425400172720ustar00rootroot00000000000000/* ** $Id: lmem.c,v 1.84 2012/05/23 15:41:53 roberto Exp $ ** Interface to Memory Manager ** See Copyright Notice in lua.h */ #include #define lmem_c #define LUA_CORE #include "lua.h" #include "ldebug.h" #include "ldo.h" #include "lgc.h" #include "lmem.h" #include "lobject.h" #include "lstate.h" /* ** About the realloc function: ** void * frealloc (void *ud, void *ptr, size_t osize, size_t nsize); ** (`osize' is the old size, `nsize' is the new size) ** ** * frealloc(ud, NULL, x, s) creates a new block of size `s' (no ** matter 'x'). ** ** * frealloc(ud, p, x, 0) frees the block `p' ** (in this specific case, frealloc must return NULL); ** particularly, frealloc(ud, NULL, 0, 0) does nothing ** (which is equivalent to free(NULL) in ANSI C) ** ** frealloc returns NULL if it cannot create or reallocate the area ** (any reallocation to an equal or smaller size cannot fail!) */ #define MINSIZEARRAY 4 void *luaM_growaux_ (lua_State *L, void *block, int *size, size_t size_elems, int limit, const char *what) { void *newblock; int newsize; if (*size >= limit/2) { /* cannot double it? */ if (*size >= limit) /* cannot grow even a little? */ luaG_runerror(L, "too many %s (limit is %d)", what, limit); newsize = limit; /* still have at least one free place */ } else { newsize = (*size)*2; if (newsize < MINSIZEARRAY) newsize = MINSIZEARRAY; /* minimum size */ } newblock = luaM_reallocv(L, block, *size, newsize, size_elems); *size = newsize; /* update only when everything else is OK */ return newblock; } l_noret luaM_toobig (lua_State *L) { luaG_runerror(L, "memory allocation error: block too big"); } /* ** generic allocation routine. */ void *luaM_realloc_ (lua_State *L, void *block, size_t osize, size_t nsize) { void *newblock; global_State *g = G(L); size_t realosize = (block) ? osize : 0; lua_assert((realosize == 0) == (block == NULL)); #if defined(HARDMEMTESTS) if (nsize > realosize && g->gcrunning) luaC_fullgc(L, 1); /* force a GC whenever possible */ #endif newblock = (*g->frealloc)(g->ud, block, osize, nsize); if (newblock == NULL && nsize > 0) { api_check(L, nsize > realosize, "realloc cannot fail when shrinking a block"); if (g->gcrunning) { luaC_fullgc(L, 1); /* try to free some memory... */ newblock = (*g->frealloc)(g->ud, block, osize, nsize); /* try again */ } if (newblock == NULL) luaD_throw(L, LUA_ERRMEM); } lua_assert((nsize == 0) == (newblock == NULL)); g->GCdebt = (g->GCdebt + nsize) - realosize; return newblock; } april-ann-0.4.1/lua/lua-5.2.2/src/lmem.h000066400000000000000000000034121263004425400172730ustar00rootroot00000000000000/* ** $Id: lmem.h,v 1.40 2013/02/20 14:08:21 roberto Exp $ ** Interface to Memory Manager ** See Copyright Notice in lua.h */ #ifndef lmem_h #define lmem_h #include #include "llimits.h" #include "lua.h" /* ** This macro avoids the runtime division MAX_SIZET/(e), as 'e' is ** always constant. ** The macro is somewhat complex to avoid warnings: ** +1 avoids warnings of "comparison has constant result"; ** cast to 'void' avoids warnings of "value unused". */ #define luaM_reallocv(L,b,on,n,e) \ (cast(void, \ (cast(size_t, (n)+1) > MAX_SIZET/(e)) ? (luaM_toobig(L), 0) : 0), \ luaM_realloc_(L, (b), (on)*(e), (n)*(e))) #define luaM_freemem(L, b, s) luaM_realloc_(L, (b), (s), 0) #define luaM_free(L, b) luaM_realloc_(L, (b), sizeof(*(b)), 0) #define luaM_freearray(L, b, n) luaM_reallocv(L, (b), n, 0, sizeof((b)[0])) #define luaM_malloc(L,s) luaM_realloc_(L, NULL, 0, (s)) #define luaM_new(L,t) cast(t *, luaM_malloc(L, sizeof(t))) #define luaM_newvector(L,n,t) \ cast(t *, luaM_reallocv(L, NULL, 0, n, sizeof(t))) #define luaM_newobject(L,tag,s) luaM_realloc_(L, NULL, tag, (s)) #define luaM_growvector(L,v,nelems,size,t,limit,e) \ if ((nelems)+1 > (size)) \ ((v)=cast(t *, luaM_growaux_(L,v,&(size),sizeof(t),limit,e))) #define luaM_reallocvector(L, v,oldn,n,t) \ ((v)=cast(t *, luaM_reallocv(L, v, oldn, n, sizeof(t)))) LUAI_FUNC l_noret luaM_toobig (lua_State *L); /* not to be called directly */ LUAI_FUNC void *luaM_realloc_ (lua_State *L, void *block, size_t oldsize, size_t size); LUAI_FUNC void *luaM_growaux_ (lua_State *L, void *block, int *size, size_t size_elem, int limit, const char *what); #endif april-ann-0.4.1/lua/lua-5.2.2/src/loadlib.c000066400000000000000000000517601263004425400177530ustar00rootroot00000000000000/* ** $Id: loadlib.c,v 1.111 2012/05/30 12:33:44 roberto Exp $ ** Dynamic library loader for Lua ** See Copyright Notice in lua.h ** ** This module contains an implementation of loadlib for Unix systems ** that have dlfcn, an implementation for Windows, and a stub for other ** systems. */ /* ** if needed, includes windows header before everything else */ #if defined(_WIN32) #include #endif #include #include #define loadlib_c #define LUA_LIB #include "lua.h" #include "lauxlib.h" #include "lualib.h" /* ** LUA_PATH and LUA_CPATH are the names of the environment ** variables that Lua check to set its paths. */ #if !defined(LUA_PATH) #define LUA_PATH "LUA_PATH" #endif #if !defined(LUA_CPATH) #define LUA_CPATH "LUA_CPATH" #endif #define LUA_PATHSUFFIX "_" LUA_VERSION_MAJOR "_" LUA_VERSION_MINOR #define LUA_PATHVERSION LUA_PATH LUA_PATHSUFFIX #define LUA_CPATHVERSION LUA_CPATH LUA_PATHSUFFIX /* ** LUA_PATH_SEP is the character that separates templates in a path. ** LUA_PATH_MARK is the string that marks the substitution points in a ** template. ** LUA_EXEC_DIR in a Windows path is replaced by the executable's ** directory. ** LUA_IGMARK is a mark to ignore all before it when building the ** luaopen_ function name. */ #if !defined (LUA_PATH_SEP) #define LUA_PATH_SEP ";" #endif #if !defined (LUA_PATH_MARK) #define LUA_PATH_MARK "?" #endif #if !defined (LUA_EXEC_DIR) #define LUA_EXEC_DIR "!" #endif #if !defined (LUA_IGMARK) #define LUA_IGMARK "-" #endif /* ** LUA_CSUBSEP is the character that replaces dots in submodule names ** when searching for a C loader. ** LUA_LSUBSEP is the character that replaces dots in submodule names ** when searching for a Lua loader. */ #if !defined(LUA_CSUBSEP) #define LUA_CSUBSEP LUA_DIRSEP #endif #if !defined(LUA_LSUBSEP) #define LUA_LSUBSEP LUA_DIRSEP #endif /* prefix for open functions in C libraries */ #define LUA_POF "luaopen_" /* separator for open functions in C libraries */ #define LUA_OFSEP "_" /* table (in the registry) that keeps handles for all loaded C libraries */ #define CLIBS "_CLIBS" #define LIB_FAIL "open" /* error codes for ll_loadfunc */ #define ERRLIB 1 #define ERRFUNC 2 #define setprogdir(L) ((void)0) /* ** system-dependent functions */ static void ll_unloadlib (void *lib); static void *ll_load (lua_State *L, const char *path, int seeglb); static lua_CFunction ll_sym (lua_State *L, void *lib, const char *sym); #if defined(LUA_USE_DLOPEN) /* ** {======================================================================== ** This is an implementation of loadlib based on the dlfcn interface. ** The dlfcn interface is available in Linux, SunOS, Solaris, IRIX, FreeBSD, ** NetBSD, AIX 4.2, HPUX 11, and probably most other Unix flavors, at least ** as an emulation layer on top of native functions. ** ========================================================================= */ #include static void ll_unloadlib (void *lib) { dlclose(lib); } static void *ll_load (lua_State *L, const char *path, int seeglb) { void *lib = dlopen(path, RTLD_NOW | (seeglb ? RTLD_GLOBAL : RTLD_LOCAL)); if (lib == NULL) lua_pushstring(L, dlerror()); return lib; } static lua_CFunction ll_sym (lua_State *L, void *lib, const char *sym) { lua_CFunction f = (lua_CFunction)dlsym(lib, sym); if (f == NULL) lua_pushstring(L, dlerror()); return f; } /* }====================================================== */ #elif defined(LUA_DL_DLL) /* ** {====================================================================== ** This is an implementation of loadlib for Windows using native functions. ** ======================================================================= */ #undef setprogdir /* ** optional flags for LoadLibraryEx */ #if !defined(LUA_LLE_FLAGS) #define LUA_LLE_FLAGS 0 #endif static void setprogdir (lua_State *L) { char buff[MAX_PATH + 1]; char *lb; DWORD nsize = sizeof(buff)/sizeof(char); DWORD n = GetModuleFileNameA(NULL, buff, nsize); if (n == 0 || n == nsize || (lb = strrchr(buff, '\\')) == NULL) luaL_error(L, "unable to get ModuleFileName"); else { *lb = '\0'; luaL_gsub(L, lua_tostring(L, -1), LUA_EXEC_DIR, buff); lua_remove(L, -2); /* remove original string */ } } static void pusherror (lua_State *L) { int error = GetLastError(); char buffer[128]; if (FormatMessageA(FORMAT_MESSAGE_IGNORE_INSERTS | FORMAT_MESSAGE_FROM_SYSTEM, NULL, error, 0, buffer, sizeof(buffer)/sizeof(char), NULL)) lua_pushstring(L, buffer); else lua_pushfstring(L, "system error %d\n", error); } static void ll_unloadlib (void *lib) { FreeLibrary((HMODULE)lib); } static void *ll_load (lua_State *L, const char *path, int seeglb) { HMODULE lib = LoadLibraryExA(path, NULL, LUA_LLE_FLAGS); (void)(seeglb); /* not used: symbols are 'global' by default */ if (lib == NULL) pusherror(L); return lib; } static lua_CFunction ll_sym (lua_State *L, void *lib, const char *sym) { lua_CFunction f = (lua_CFunction)GetProcAddress((HMODULE)lib, sym); if (f == NULL) pusherror(L); return f; } /* }====================================================== */ #else /* ** {====================================================== ** Fallback for other systems ** ======================================================= */ #undef LIB_FAIL #define LIB_FAIL "absent" #define DLMSG "dynamic libraries not enabled; check your Lua installation" static void ll_unloadlib (void *lib) { (void)(lib); /* not used */ } static void *ll_load (lua_State *L, const char *path, int seeglb) { (void)(path); (void)(seeglb); /* not used */ lua_pushliteral(L, DLMSG); return NULL; } static lua_CFunction ll_sym (lua_State *L, void *lib, const char *sym) { (void)(lib); (void)(sym); /* not used */ lua_pushliteral(L, DLMSG); return NULL; } /* }====================================================== */ #endif static void *ll_checkclib (lua_State *L, const char *path) { void *plib; lua_getfield(L, LUA_REGISTRYINDEX, CLIBS); lua_getfield(L, -1, path); plib = lua_touserdata(L, -1); /* plib = CLIBS[path] */ lua_pop(L, 2); /* pop CLIBS table and 'plib' */ return plib; } static void ll_addtoclib (lua_State *L, const char *path, void *plib) { lua_getfield(L, LUA_REGISTRYINDEX, CLIBS); lua_pushlightuserdata(L, plib); lua_pushvalue(L, -1); lua_setfield(L, -3, path); /* CLIBS[path] = plib */ lua_rawseti(L, -2, luaL_len(L, -2) + 1); /* CLIBS[#CLIBS + 1] = plib */ lua_pop(L, 1); /* pop CLIBS table */ } /* ** __gc tag method for CLIBS table: calls 'll_unloadlib' for all lib ** handles in list CLIBS */ static int gctm (lua_State *L) { int n = luaL_len(L, 1); for (; n >= 1; n--) { /* for each handle, in reverse order */ lua_rawgeti(L, 1, n); /* get handle CLIBS[n] */ ll_unloadlib(lua_touserdata(L, -1)); lua_pop(L, 1); /* pop handle */ } return 0; } static int ll_loadfunc (lua_State *L, const char *path, const char *sym) { void *reg = ll_checkclib(L, path); /* check loaded C libraries */ if (reg == NULL) { /* must load library? */ reg = ll_load(L, path, *sym == '*'); if (reg == NULL) return ERRLIB; /* unable to load library */ ll_addtoclib(L, path, reg); } if (*sym == '*') { /* loading only library (no function)? */ lua_pushboolean(L, 1); /* return 'true' */ return 0; /* no errors */ } else { lua_CFunction f = ll_sym(L, reg, sym); if (f == NULL) return ERRFUNC; /* unable to find function */ lua_pushcfunction(L, f); /* else create new function */ return 0; /* no errors */ } } static int ll_loadlib (lua_State *L) { const char *path = luaL_checkstring(L, 1); const char *init = luaL_checkstring(L, 2); int stat = ll_loadfunc(L, path, init); if (stat == 0) /* no errors? */ return 1; /* return the loaded function */ else { /* error; error message is on stack top */ lua_pushnil(L); lua_insert(L, -2); lua_pushstring(L, (stat == ERRLIB) ? LIB_FAIL : "init"); return 3; /* return nil, error message, and where */ } } /* ** {====================================================== ** 'require' function ** ======================================================= */ static int readable (const char *filename) { FILE *f = fopen(filename, "r"); /* try to open file */ if (f == NULL) return 0; /* open failed */ fclose(f); return 1; } static const char *pushnexttemplate (lua_State *L, const char *path) { const char *l; while (*path == *LUA_PATH_SEP) path++; /* skip separators */ if (*path == '\0') return NULL; /* no more templates */ l = strchr(path, *LUA_PATH_SEP); /* find next separator */ if (l == NULL) l = path + strlen(path); lua_pushlstring(L, path, l - path); /* template */ return l; } static const char *searchpath (lua_State *L, const char *name, const char *path, const char *sep, const char *dirsep) { luaL_Buffer msg; /* to build error message */ luaL_buffinit(L, &msg); if (*sep != '\0') /* non-empty separator? */ name = luaL_gsub(L, name, sep, dirsep); /* replace it by 'dirsep' */ while ((path = pushnexttemplate(L, path)) != NULL) { const char *filename = luaL_gsub(L, lua_tostring(L, -1), LUA_PATH_MARK, name); lua_remove(L, -2); /* remove path template */ if (readable(filename)) /* does file exist and is readable? */ return filename; /* return that file name */ lua_pushfstring(L, "\n\tno file " LUA_QS, filename); lua_remove(L, -2); /* remove file name */ luaL_addvalue(&msg); /* concatenate error msg. entry */ } luaL_pushresult(&msg); /* create error message */ return NULL; /* not found */ } static int ll_searchpath (lua_State *L) { const char *f = searchpath(L, luaL_checkstring(L, 1), luaL_checkstring(L, 2), luaL_optstring(L, 3, "."), luaL_optstring(L, 4, LUA_DIRSEP)); if (f != NULL) return 1; else { /* error message is on top of the stack */ lua_pushnil(L); lua_insert(L, -2); return 2; /* return nil + error message */ } } static const char *findfile (lua_State *L, const char *name, const char *pname, const char *dirsep) { const char *path; lua_getfield(L, lua_upvalueindex(1), pname); path = lua_tostring(L, -1); if (path == NULL) luaL_error(L, LUA_QL("package.%s") " must be a string", pname); return searchpath(L, name, path, ".", dirsep); } static int checkload (lua_State *L, int stat, const char *filename) { if (stat) { /* module loaded successfully? */ lua_pushstring(L, filename); /* will be 2nd argument to module */ return 2; /* return open function and file name */ } else return luaL_error(L, "error loading module " LUA_QS " from file " LUA_QS ":\n\t%s", lua_tostring(L, 1), filename, lua_tostring(L, -1)); } static int searcher_Lua (lua_State *L) { const char *filename; const char *name = luaL_checkstring(L, 1); filename = findfile(L, name, "path", LUA_LSUBSEP); if (filename == NULL) return 1; /* module not found in this path */ return checkload(L, (luaL_loadfile(L, filename) == LUA_OK), filename); } static int loadfunc (lua_State *L, const char *filename, const char *modname) { const char *funcname; const char *mark; modname = luaL_gsub(L, modname, ".", LUA_OFSEP); mark = strchr(modname, *LUA_IGMARK); if (mark) { int stat; funcname = lua_pushlstring(L, modname, mark - modname); funcname = lua_pushfstring(L, LUA_POF"%s", funcname); stat = ll_loadfunc(L, filename, funcname); if (stat != ERRFUNC) return stat; modname = mark + 1; /* else go ahead and try old-style name */ } funcname = lua_pushfstring(L, LUA_POF"%s", modname); return ll_loadfunc(L, filename, funcname); } static int searcher_C (lua_State *L) { const char *name = luaL_checkstring(L, 1); const char *filename = findfile(L, name, "cpath", LUA_CSUBSEP); if (filename == NULL) return 1; /* module not found in this path */ return checkload(L, (loadfunc(L, filename, name) == 0), filename); } static int searcher_Croot (lua_State *L) { const char *filename; const char *name = luaL_checkstring(L, 1); const char *p = strchr(name, '.'); int stat; if (p == NULL) return 0; /* is root */ lua_pushlstring(L, name, p - name); filename = findfile(L, lua_tostring(L, -1), "cpath", LUA_CSUBSEP); if (filename == NULL) return 1; /* root not found */ if ((stat = loadfunc(L, filename, name)) != 0) { if (stat != ERRFUNC) return checkload(L, 0, filename); /* real error */ else { /* open function not found */ lua_pushfstring(L, "\n\tno module " LUA_QS " in file " LUA_QS, name, filename); return 1; } } lua_pushstring(L, filename); /* will be 2nd argument to module */ return 2; } static int searcher_preload (lua_State *L) { const char *name = luaL_checkstring(L, 1); lua_getfield(L, LUA_REGISTRYINDEX, "_PRELOAD"); lua_getfield(L, -1, name); if (lua_isnil(L, -1)) /* not found? */ lua_pushfstring(L, "\n\tno field package.preload['%s']", name); return 1; } static void findloader (lua_State *L, const char *name) { int i; luaL_Buffer msg; /* to build error message */ luaL_buffinit(L, &msg); lua_getfield(L, lua_upvalueindex(1), "searchers"); /* will be at index 3 */ if (!lua_istable(L, 3)) luaL_error(L, LUA_QL("package.searchers") " must be a table"); /* iterate over available searchers to find a loader */ for (i = 1; ; i++) { lua_rawgeti(L, 3, i); /* get a searcher */ if (lua_isnil(L, -1)) { /* no more searchers? */ lua_pop(L, 1); /* remove nil */ luaL_pushresult(&msg); /* create error message */ luaL_error(L, "module " LUA_QS " not found:%s", name, lua_tostring(L, -1)); } lua_pushstring(L, name); lua_call(L, 1, 2); /* call it */ if (lua_isfunction(L, -2)) /* did it find a loader? */ return; /* module loader found */ else if (lua_isstring(L, -2)) { /* searcher returned error message? */ lua_pop(L, 1); /* remove extra return */ luaL_addvalue(&msg); /* concatenate error message */ } else lua_pop(L, 2); /* remove both returns */ } } static int ll_require (lua_State *L) { const char *name = luaL_checkstring(L, 1); lua_settop(L, 1); /* _LOADED table will be at index 2 */ lua_getfield(L, LUA_REGISTRYINDEX, "_LOADED"); lua_getfield(L, 2, name); /* _LOADED[name] */ if (lua_toboolean(L, -1)) /* is it there? */ return 1; /* package is already loaded */ /* else must load package */ lua_pop(L, 1); /* remove 'getfield' result */ findloader(L, name); lua_pushstring(L, name); /* pass name as argument to module loader */ lua_insert(L, -2); /* name is 1st argument (before search data) */ lua_call(L, 2, 1); /* run loader to load module */ if (!lua_isnil(L, -1)) /* non-nil return? */ lua_setfield(L, 2, name); /* _LOADED[name] = returned value */ lua_getfield(L, 2, name); if (lua_isnil(L, -1)) { /* module did not set a value? */ lua_pushboolean(L, 1); /* use true as result */ lua_pushvalue(L, -1); /* extra copy to be returned */ lua_setfield(L, 2, name); /* _LOADED[name] = true */ } return 1; } /* }====================================================== */ /* ** {====================================================== ** 'module' function ** ======================================================= */ #if defined(LUA_COMPAT_MODULE) /* ** changes the environment variable of calling function */ static void set_env (lua_State *L) { lua_Debug ar; if (lua_getstack(L, 1, &ar) == 0 || lua_getinfo(L, "f", &ar) == 0 || /* get calling function */ lua_iscfunction(L, -1)) luaL_error(L, LUA_QL("module") " not called from a Lua function"); lua_pushvalue(L, -2); /* copy new environment table to top */ lua_setupvalue(L, -2, 1); lua_pop(L, 1); /* remove function */ } static void dooptions (lua_State *L, int n) { int i; for (i = 2; i <= n; i++) { if (lua_isfunction(L, i)) { /* avoid 'calling' extra info. */ lua_pushvalue(L, i); /* get option (a function) */ lua_pushvalue(L, -2); /* module */ lua_call(L, 1, 0); } } } static void modinit (lua_State *L, const char *modname) { const char *dot; lua_pushvalue(L, -1); lua_setfield(L, -2, "_M"); /* module._M = module */ lua_pushstring(L, modname); lua_setfield(L, -2, "_NAME"); dot = strrchr(modname, '.'); /* look for last dot in module name */ if (dot == NULL) dot = modname; else dot++; /* set _PACKAGE as package name (full module name minus last part) */ lua_pushlstring(L, modname, dot - modname); lua_setfield(L, -2, "_PACKAGE"); } static int ll_module (lua_State *L) { const char *modname = luaL_checkstring(L, 1); int lastarg = lua_gettop(L); /* last parameter */ luaL_pushmodule(L, modname, 1); /* get/create module table */ /* check whether table already has a _NAME field */ lua_getfield(L, -1, "_NAME"); if (!lua_isnil(L, -1)) /* is table an initialized module? */ lua_pop(L, 1); else { /* no; initialize it */ lua_pop(L, 1); modinit(L, modname); } lua_pushvalue(L, -1); set_env(L); dooptions(L, lastarg); return 1; } static int ll_seeall (lua_State *L) { luaL_checktype(L, 1, LUA_TTABLE); if (!lua_getmetatable(L, 1)) { lua_createtable(L, 0, 1); /* create new metatable */ lua_pushvalue(L, -1); lua_setmetatable(L, 1); } lua_pushglobaltable(L); lua_setfield(L, -2, "__index"); /* mt.__index = _G */ return 0; } #endif /* }====================================================== */ /* auxiliary mark (for internal use) */ #define AUXMARK "\1" /* ** return registry.LUA_NOENV as a boolean */ static int noenv (lua_State *L) { int b; lua_getfield(L, LUA_REGISTRYINDEX, "LUA_NOENV"); b = lua_toboolean(L, -1); lua_pop(L, 1); /* remove value */ return b; } static void setpath (lua_State *L, const char *fieldname, const char *envname1, const char *envname2, const char *def) { const char *path = getenv(envname1); if (path == NULL) /* no environment variable? */ path = getenv(envname2); /* try alternative name */ if (path == NULL || noenv(L)) /* no environment variable? */ lua_pushstring(L, def); /* use default */ else { /* replace ";;" by ";AUXMARK;" and then AUXMARK by default path */ path = luaL_gsub(L, path, LUA_PATH_SEP LUA_PATH_SEP, LUA_PATH_SEP AUXMARK LUA_PATH_SEP); luaL_gsub(L, path, AUXMARK, def); lua_remove(L, -2); } setprogdir(L); lua_setfield(L, -2, fieldname); } static const luaL_Reg pk_funcs[] = { {"loadlib", ll_loadlib}, {"searchpath", ll_searchpath}, #if defined(LUA_COMPAT_MODULE) {"seeall", ll_seeall}, #endif {NULL, NULL} }; static const luaL_Reg ll_funcs[] = { #if defined(LUA_COMPAT_MODULE) {"module", ll_module}, #endif {"require", ll_require}, {NULL, NULL} }; static void createsearcherstable (lua_State *L) { static const lua_CFunction searchers[] = {searcher_preload, searcher_Lua, searcher_C, searcher_Croot, NULL}; int i; /* create 'searchers' table */ lua_createtable(L, sizeof(searchers)/sizeof(searchers[0]) - 1, 0); /* fill it with pre-defined searchers */ for (i=0; searchers[i] != NULL; i++) { lua_pushvalue(L, -2); /* set 'package' as upvalue for all searchers */ lua_pushcclosure(L, searchers[i], 1); lua_rawseti(L, -2, i+1); } } LUAMOD_API int luaopen_package (lua_State *L) { /* create table CLIBS to keep track of loaded C libraries */ luaL_getsubtable(L, LUA_REGISTRYINDEX, CLIBS); lua_createtable(L, 0, 1); /* metatable for CLIBS */ lua_pushcfunction(L, gctm); lua_setfield(L, -2, "__gc"); /* set finalizer for CLIBS table */ lua_setmetatable(L, -2); /* create `package' table */ luaL_newlib(L, pk_funcs); createsearcherstable(L); #if defined(LUA_COMPAT_LOADERS) lua_pushvalue(L, -1); /* make a copy of 'searchers' table */ lua_setfield(L, -3, "loaders"); /* put it in field `loaders' */ #endif lua_setfield(L, -2, "searchers"); /* put it in field 'searchers' */ /* set field 'path' */ setpath(L, "path", LUA_PATHVERSION, LUA_PATH, LUA_PATH_DEFAULT); /* set field 'cpath' */ setpath(L, "cpath", LUA_CPATHVERSION, LUA_CPATH, LUA_CPATH_DEFAULT); /* store config information */ lua_pushliteral(L, LUA_DIRSEP "\n" LUA_PATH_SEP "\n" LUA_PATH_MARK "\n" LUA_EXEC_DIR "\n" LUA_IGMARK "\n"); lua_setfield(L, -2, "config"); /* set field `loaded' */ luaL_getsubtable(L, LUA_REGISTRYINDEX, "_LOADED"); lua_setfield(L, -2, "loaded"); /* set field `preload' */ luaL_getsubtable(L, LUA_REGISTRYINDEX, "_PRELOAD"); lua_setfield(L, -2, "preload"); lua_pushglobaltable(L); lua_pushvalue(L, -2); /* set 'package' as upvalue for next lib */ luaL_setfuncs(L, ll_funcs, 1); /* open lib into global table */ lua_pop(L, 1); /* pop global table */ return 1; /* return 'package' table */ } april-ann-0.4.1/lua/lua-5.2.2/src/lobject.c000066400000000000000000000173351263004425400177670ustar00rootroot00000000000000/* ** $Id: lobject.c,v 2.58 2013/02/20 14:08:56 roberto Exp $ ** Some generic functions over Lua objects ** See Copyright Notice in lua.h */ #include #include #include #include #define lobject_c #define LUA_CORE #include "lua.h" #include "lctype.h" #include "ldebug.h" #include "ldo.h" #include "lmem.h" #include "lobject.h" #include "lstate.h" #include "lstring.h" #include "lvm.h" LUAI_DDEF const TValue luaO_nilobject_ = {NILCONSTANT}; /* ** converts an integer to a "floating point byte", represented as ** (eeeeexxx), where the real value is (1xxx) * 2^(eeeee - 1) if ** eeeee != 0 and (xxx) otherwise. */ int luaO_int2fb (unsigned int x) { int e = 0; /* exponent */ if (x < 8) return x; while (x >= 0x10) { x = (x+1) >> 1; e++; } return ((e+1) << 3) | (cast_int(x) - 8); } /* converts back */ int luaO_fb2int (int x) { int e = (x >> 3) & 0x1f; if (e == 0) return x; else return ((x & 7) + 8) << (e - 1); } int luaO_ceillog2 (unsigned int x) { static const lu_byte log_2[256] = { 0,1,2,2,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5, 6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6, 7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7, 7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7, 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8, 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8, 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8, 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8 }; int l = 0; x--; while (x >= 256) { l += 8; x >>= 8; } return l + log_2[x]; } lua_Number luaO_arith (int op, lua_Number v1, lua_Number v2) { switch (op) { case LUA_OPADD: return luai_numadd(NULL, v1, v2); case LUA_OPSUB: return luai_numsub(NULL, v1, v2); case LUA_OPMUL: return luai_nummul(NULL, v1, v2); case LUA_OPDIV: return luai_numdiv(NULL, v1, v2); case LUA_OPMOD: return luai_nummod(NULL, v1, v2); case LUA_OPPOW: return luai_numpow(NULL, v1, v2); case LUA_OPUNM: return luai_numunm(NULL, v1); default: lua_assert(0); return 0; } } int luaO_hexavalue (int c) { if (lisdigit(c)) return c - '0'; else return ltolower(c) - 'a' + 10; } #if !defined(lua_strx2number) #include static int isneg (const char **s) { if (**s == '-') { (*s)++; return 1; } else if (**s == '+') (*s)++; return 0; } static lua_Number readhexa (const char **s, lua_Number r, int *count) { for (; lisxdigit(cast_uchar(**s)); (*s)++) { /* read integer part */ r = (r * cast_num(16.0)) + cast_num(luaO_hexavalue(cast_uchar(**s))); (*count)++; } return r; } /* ** convert an hexadecimal numeric string to a number, following ** C99 specification for 'strtod' */ static lua_Number lua_strx2number (const char *s, char **endptr) { lua_Number r = 0.0; int e = 0, i = 0; int neg = 0; /* 1 if number is negative */ *endptr = cast(char *, s); /* nothing is valid yet */ while (lisspace(cast_uchar(*s))) s++; /* skip initial spaces */ neg = isneg(&s); /* check signal */ if (!(*s == '0' && (*(s + 1) == 'x' || *(s + 1) == 'X'))) /* check '0x' */ return 0.0; /* invalid format (no '0x') */ s += 2; /* skip '0x' */ r = readhexa(&s, r, &i); /* read integer part */ if (*s == '.') { s++; /* skip dot */ r = readhexa(&s, r, &e); /* read fractional part */ } if (i == 0 && e == 0) return 0.0; /* invalid format (no digit) */ e *= -4; /* each fractional digit divides value by 2^-4 */ *endptr = cast(char *, s); /* valid up to here */ if (*s == 'p' || *s == 'P') { /* exponent part? */ int exp1 = 0; int neg1; s++; /* skip 'p' */ neg1 = isneg(&s); /* signal */ if (!lisdigit(cast_uchar(*s))) goto ret; /* must have at least one digit */ while (lisdigit(cast_uchar(*s))) /* read exponent */ exp1 = exp1 * 10 + *(s++) - '0'; if (neg1) exp1 = -exp1; e += exp1; } *endptr = cast(char *, s); /* valid up to here */ ret: if (neg) r = -r; return l_mathop(ldexp)(r, e); } #endif int luaO_str2d (const char *s, size_t len, lua_Number *result) { char *endptr; if (strpbrk(s, "nN")) /* reject 'inf' and 'nan' */ return 0; else if (strpbrk(s, "xX")) /* hexa? */ *result = lua_strx2number(s, &endptr); else *result = lua_str2number(s, &endptr); if (endptr == s) return 0; /* nothing recognized */ while (lisspace(cast_uchar(*endptr))) endptr++; return (endptr == s + len); /* OK if no trailing characters */ } static void pushstr (lua_State *L, const char *str, size_t l) { setsvalue2s(L, L->top++, luaS_newlstr(L, str, l)); } /* this function handles only `%d', `%c', %f, %p, and `%s' formats */ const char *luaO_pushvfstring (lua_State *L, const char *fmt, va_list argp) { int n = 0; for (;;) { const char *e = strchr(fmt, '%'); if (e == NULL) break; luaD_checkstack(L, 2); /* fmt + item */ pushstr(L, fmt, e - fmt); switch (*(e+1)) { case 's': { const char *s = va_arg(argp, char *); if (s == NULL) s = "(null)"; pushstr(L, s, strlen(s)); break; } case 'c': { char buff; buff = cast(char, va_arg(argp, int)); pushstr(L, &buff, 1); break; } case 'd': { setnvalue(L->top++, cast_num(va_arg(argp, int))); break; } case 'f': { setnvalue(L->top++, cast_num(va_arg(argp, l_uacNumber))); break; } case 'p': { char buff[4*sizeof(void *) + 8]; /* should be enough space for a `%p' */ int l = sprintf(buff, "%p", va_arg(argp, void *)); pushstr(L, buff, l); break; } case '%': { pushstr(L, "%", 1); break; } default: { luaG_runerror(L, "invalid option " LUA_QL("%%%c") " to " LUA_QL("lua_pushfstring"), *(e + 1)); } } n += 2; fmt = e+2; } luaD_checkstack(L, 1); pushstr(L, fmt, strlen(fmt)); if (n > 0) luaV_concat(L, n + 1); return svalue(L->top - 1); } const char *luaO_pushfstring (lua_State *L, const char *fmt, ...) { const char *msg; va_list argp; va_start(argp, fmt); msg = luaO_pushvfstring(L, fmt, argp); va_end(argp); return msg; } /* number of chars of a literal string without the ending \0 */ #define LL(x) (sizeof(x)/sizeof(char) - 1) #define RETS "..." #define PRE "[string \"" #define POS "\"]" #define addstr(a,b,l) ( memcpy(a,b,(l) * sizeof(char)), a += (l) ) void luaO_chunkid (char *out, const char *source, size_t bufflen) { size_t l = strlen(source); if (*source == '=') { /* 'literal' source */ if (l <= bufflen) /* small enough? */ memcpy(out, source + 1, l * sizeof(char)); else { /* truncate it */ addstr(out, source + 1, bufflen - 1); *out = '\0'; } } else if (*source == '@') { /* file name */ if (l <= bufflen) /* small enough? */ memcpy(out, source + 1, l * sizeof(char)); else { /* add '...' before rest of name */ addstr(out, RETS, LL(RETS)); bufflen -= LL(RETS); memcpy(out, source + 1 + l - bufflen, bufflen * sizeof(char)); } } else { /* string; format as [string "source"] */ const char *nl = strchr(source, '\n'); /* find first new line (if any) */ addstr(out, PRE, LL(PRE)); /* add prefix */ bufflen -= LL(PRE RETS POS) + 1; /* save space for prefix+suffix+'\0' */ if (l < bufflen && nl == NULL) { /* small one-line source? */ addstr(out, source, l); /* keep it */ } else { if (nl != NULL) l = nl - source; /* stop at first newline */ if (l > bufflen) l = bufflen; addstr(out, source, l); addstr(out, RETS, LL(RETS)); } memcpy(out, POS, (LL(POS) + 1) * sizeof(char)); } } april-ann-0.4.1/lua/lua-5.2.2/src/lobject.h000066400000000000000000000351351263004425400177720ustar00rootroot00000000000000/* ** $Id: lobject.h,v 2.71 2012/09/11 18:21:44 roberto Exp $ ** Type definitions for Lua objects ** See Copyright Notice in lua.h */ #ifndef lobject_h #define lobject_h #include #include "llimits.h" #include "lua.h" /* ** Extra tags for non-values */ #define LUA_TPROTO LUA_NUMTAGS #define LUA_TUPVAL (LUA_NUMTAGS+1) #define LUA_TDEADKEY (LUA_NUMTAGS+2) /* ** number of all possible tags (including LUA_TNONE but excluding DEADKEY) */ #define LUA_TOTALTAGS (LUA_TUPVAL+2) /* ** tags for Tagged Values have the following use of bits: ** bits 0-3: actual tag (a LUA_T* value) ** bits 4-5: variant bits ** bit 6: whether value is collectable */ #define VARBITS (3 << 4) /* ** LUA_TFUNCTION variants: ** 0 - Lua function ** 1 - light C function ** 2 - regular C function (closure) */ /* Variant tags for functions */ #define LUA_TLCL (LUA_TFUNCTION | (0 << 4)) /* Lua closure */ #define LUA_TLCF (LUA_TFUNCTION | (1 << 4)) /* light C function */ #define LUA_TCCL (LUA_TFUNCTION | (2 << 4)) /* C closure */ /* Variant tags for strings */ #define LUA_TSHRSTR (LUA_TSTRING | (0 << 4)) /* short strings */ #define LUA_TLNGSTR (LUA_TSTRING | (1 << 4)) /* long strings */ /* Bit mark for collectable types */ #define BIT_ISCOLLECTABLE (1 << 6) /* mark a tag as collectable */ #define ctb(t) ((t) | BIT_ISCOLLECTABLE) /* ** Union of all collectable objects */ typedef union GCObject GCObject; /* ** Common Header for all collectable objects (in macro form, to be ** included in other objects) */ #define CommonHeader GCObject *next; lu_byte tt; lu_byte marked /* ** Common header in struct form */ typedef struct GCheader { CommonHeader; } GCheader; /* ** Union of all Lua values */ typedef union Value Value; #define numfield lua_Number n; /* numbers */ /* ** Tagged Values. This is the basic representation of values in Lua, ** an actual value plus a tag with its type. */ #define TValuefields Value value_; int tt_ typedef struct lua_TValue TValue; /* macro defining a nil value */ #define NILCONSTANT {NULL}, LUA_TNIL #define val_(o) ((o)->value_) #define num_(o) (val_(o).n) /* raw type tag of a TValue */ #define rttype(o) ((o)->tt_) /* tag with no variants (bits 0-3) */ #define novariant(x) ((x) & 0x0F) /* type tag of a TValue (bits 0-3 for tags + variant bits 4-5) */ #define ttype(o) (rttype(o) & 0x3F) /* type tag of a TValue with no variants (bits 0-3) */ #define ttypenv(o) (novariant(rttype(o))) /* Macros to test type */ #define checktag(o,t) (rttype(o) == (t)) #define checktype(o,t) (ttypenv(o) == (t)) #define ttisnumber(o) checktag((o), LUA_TNUMBER) #define ttisnil(o) checktag((o), LUA_TNIL) #define ttisboolean(o) checktag((o), LUA_TBOOLEAN) #define ttislightuserdata(o) checktag((o), LUA_TLIGHTUSERDATA) #define ttisstring(o) checktype((o), LUA_TSTRING) #define ttisshrstring(o) checktag((o), ctb(LUA_TSHRSTR)) #define ttislngstring(o) checktag((o), ctb(LUA_TLNGSTR)) #define ttistable(o) checktag((o), ctb(LUA_TTABLE)) #define ttisfunction(o) checktype(o, LUA_TFUNCTION) #define ttisclosure(o) ((rttype(o) & 0x1F) == LUA_TFUNCTION) #define ttisCclosure(o) checktag((o), ctb(LUA_TCCL)) #define ttisLclosure(o) checktag((o), ctb(LUA_TLCL)) #define ttislcf(o) checktag((o), LUA_TLCF) #define ttisuserdata(o) checktag((o), ctb(LUA_TUSERDATA)) #define ttisthread(o) checktag((o), ctb(LUA_TTHREAD)) #define ttisdeadkey(o) checktag((o), LUA_TDEADKEY) #define ttisequal(o1,o2) (rttype(o1) == rttype(o2)) /* Macros to access values */ #define nvalue(o) check_exp(ttisnumber(o), num_(o)) #define gcvalue(o) check_exp(iscollectable(o), val_(o).gc) #define pvalue(o) check_exp(ttislightuserdata(o), val_(o).p) #define rawtsvalue(o) check_exp(ttisstring(o), &val_(o).gc->ts) #define tsvalue(o) (&rawtsvalue(o)->tsv) #define rawuvalue(o) check_exp(ttisuserdata(o), &val_(o).gc->u) #define uvalue(o) (&rawuvalue(o)->uv) #define clvalue(o) check_exp(ttisclosure(o), &val_(o).gc->cl) #define clLvalue(o) check_exp(ttisLclosure(o), &val_(o).gc->cl.l) #define clCvalue(o) check_exp(ttisCclosure(o), &val_(o).gc->cl.c) #define fvalue(o) check_exp(ttislcf(o), val_(o).f) #define hvalue(o) check_exp(ttistable(o), &val_(o).gc->h) #define bvalue(o) check_exp(ttisboolean(o), val_(o).b) #define thvalue(o) check_exp(ttisthread(o), &val_(o).gc->th) /* a dead value may get the 'gc' field, but cannot access its contents */ #define deadvalue(o) check_exp(ttisdeadkey(o), cast(void *, val_(o).gc)) #define l_isfalse(o) (ttisnil(o) || (ttisboolean(o) && bvalue(o) == 0)) #define iscollectable(o) (rttype(o) & BIT_ISCOLLECTABLE) /* Macros for internal tests */ #define righttt(obj) (ttype(obj) == gcvalue(obj)->gch.tt) #define checkliveness(g,obj) \ lua_longassert(!iscollectable(obj) || \ (righttt(obj) && !isdead(g,gcvalue(obj)))) /* Macros to set values */ #define settt_(o,t) ((o)->tt_=(t)) #define setnvalue(obj,x) \ { TValue *io=(obj); num_(io)=(x); settt_(io, LUA_TNUMBER); } #define setnilvalue(obj) settt_(obj, LUA_TNIL) #define setfvalue(obj,x) \ { TValue *io=(obj); val_(io).f=(x); settt_(io, LUA_TLCF); } #define setpvalue(obj,x) \ { TValue *io=(obj); val_(io).p=(x); settt_(io, LUA_TLIGHTUSERDATA); } #define setbvalue(obj,x) \ { TValue *io=(obj); val_(io).b=(x); settt_(io, LUA_TBOOLEAN); } #define setgcovalue(L,obj,x) \ { TValue *io=(obj); GCObject *i_g=(x); \ val_(io).gc=i_g; settt_(io, ctb(gch(i_g)->tt)); } #define setsvalue(L,obj,x) \ { TValue *io=(obj); \ TString *x_ = (x); \ val_(io).gc=cast(GCObject *, x_); settt_(io, ctb(x_->tsv.tt)); \ checkliveness(G(L),io); } #define setuvalue(L,obj,x) \ { TValue *io=(obj); \ val_(io).gc=cast(GCObject *, (x)); settt_(io, ctb(LUA_TUSERDATA)); \ checkliveness(G(L),io); } #define setthvalue(L,obj,x) \ { TValue *io=(obj); \ val_(io).gc=cast(GCObject *, (x)); settt_(io, ctb(LUA_TTHREAD)); \ checkliveness(G(L),io); } #define setclLvalue(L,obj,x) \ { TValue *io=(obj); \ val_(io).gc=cast(GCObject *, (x)); settt_(io, ctb(LUA_TLCL)); \ checkliveness(G(L),io); } #define setclCvalue(L,obj,x) \ { TValue *io=(obj); \ val_(io).gc=cast(GCObject *, (x)); settt_(io, ctb(LUA_TCCL)); \ checkliveness(G(L),io); } #define sethvalue(L,obj,x) \ { TValue *io=(obj); \ val_(io).gc=cast(GCObject *, (x)); settt_(io, ctb(LUA_TTABLE)); \ checkliveness(G(L),io); } #define setdeadvalue(obj) settt_(obj, LUA_TDEADKEY) #define setobj(L,obj1,obj2) \ { const TValue *io2=(obj2); TValue *io1=(obj1); \ io1->value_ = io2->value_; io1->tt_ = io2->tt_; \ checkliveness(G(L),io1); } /* ** different types of assignments, according to destination */ /* from stack to (same) stack */ #define setobjs2s setobj /* to stack (not from same stack) */ #define setobj2s setobj #define setsvalue2s setsvalue #define sethvalue2s sethvalue #define setptvalue2s setptvalue /* from table to same table */ #define setobjt2t setobj /* to table */ #define setobj2t setobj /* to new object */ #define setobj2n setobj #define setsvalue2n setsvalue /* check whether a number is valid (useful only for NaN trick) */ #define luai_checknum(L,o,c) { /* empty */ } /* ** {====================================================== ** NaN Trick ** ======================================================= */ #if defined(LUA_NANTRICK) /* ** numbers are represented in the 'd_' field. All other values have the ** value (NNMARK | tag) in 'tt__'. A number with such pattern would be ** a "signaled NaN", which is never generated by regular operations by ** the CPU (nor by 'strtod') */ /* allows for external implementation for part of the trick */ #if !defined(NNMARK) /* { */ #if !defined(LUA_IEEEENDIAN) #error option 'LUA_NANTRICK' needs 'LUA_IEEEENDIAN' #endif #define NNMARK 0x7FF7A500 #define NNMASK 0x7FFFFF00 #undef TValuefields #undef NILCONSTANT #if (LUA_IEEEENDIAN == 0) /* { */ /* little endian */ #define TValuefields \ union { struct { Value v__; int tt__; } i; double d__; } u #define NILCONSTANT {{{NULL}, tag2tt(LUA_TNIL)}} /* field-access macros */ #define v_(o) ((o)->u.i.v__) #define d_(o) ((o)->u.d__) #define tt_(o) ((o)->u.i.tt__) #else /* }{ */ /* big endian */ #define TValuefields \ union { struct { int tt__; Value v__; } i; double d__; } u #define NILCONSTANT {{tag2tt(LUA_TNIL), {NULL}}} /* field-access macros */ #define v_(o) ((o)->u.i.v__) #define d_(o) ((o)->u.d__) #define tt_(o) ((o)->u.i.tt__) #endif /* } */ #endif /* } */ /* correspondence with standard representation */ #undef val_ #define val_(o) v_(o) #undef num_ #define num_(o) d_(o) #undef numfield #define numfield /* no such field; numbers are the entire struct */ /* basic check to distinguish numbers from non-numbers */ #undef ttisnumber #define ttisnumber(o) ((tt_(o) & NNMASK) != NNMARK) #define tag2tt(t) (NNMARK | (t)) #undef rttype #define rttype(o) (ttisnumber(o) ? LUA_TNUMBER : tt_(o) & 0xff) #undef settt_ #define settt_(o,t) (tt_(o) = tag2tt(t)) #undef setnvalue #define setnvalue(obj,x) \ { TValue *io_=(obj); num_(io_)=(x); lua_assert(ttisnumber(io_)); } #undef setobj #define setobj(L,obj1,obj2) \ { const TValue *o2_=(obj2); TValue *o1_=(obj1); \ o1_->u = o2_->u; \ checkliveness(G(L),o1_); } /* ** these redefinitions are not mandatory, but these forms are more efficient */ #undef checktag #undef checktype #define checktag(o,t) (tt_(o) == tag2tt(t)) #define checktype(o,t) (ctb(tt_(o) | VARBITS) == ctb(tag2tt(t) | VARBITS)) #undef ttisequal #define ttisequal(o1,o2) \ (ttisnumber(o1) ? ttisnumber(o2) : (tt_(o1) == tt_(o2))) #undef luai_checknum #define luai_checknum(L,o,c) { if (!ttisnumber(o)) c; } #endif /* }====================================================== */ /* ** {====================================================== ** types and prototypes ** ======================================================= */ union Value { GCObject *gc; /* collectable objects */ void *p; /* light userdata */ int b; /* booleans */ lua_CFunction f; /* light C functions */ numfield /* numbers */ }; struct lua_TValue { TValuefields; }; typedef TValue *StkId; /* index to stack elements */ /* ** Header for string value; string bytes follow the end of this structure */ typedef union TString { L_Umaxalign dummy; /* ensures maximum alignment for strings */ struct { CommonHeader; lu_byte extra; /* reserved words for short strings; "has hash" for longs */ unsigned int hash; size_t len; /* number of characters in string */ } tsv; } TString; /* get the actual string (array of bytes) from a TString */ #define getstr(ts) cast(const char *, (ts) + 1) /* get the actual string (array of bytes) from a Lua value */ #define svalue(o) getstr(rawtsvalue(o)) /* ** Header for userdata; memory area follows the end of this structure */ typedef union Udata { L_Umaxalign dummy; /* ensures maximum alignment for `local' udata */ struct { CommonHeader; struct Table *metatable; struct Table *env; size_t len; /* number of bytes */ } uv; } Udata; /* ** Description of an upvalue for function prototypes */ typedef struct Upvaldesc { TString *name; /* upvalue name (for debug information) */ lu_byte instack; /* whether it is in stack */ lu_byte idx; /* index of upvalue (in stack or in outer function's list) */ } Upvaldesc; /* ** Description of a local variable for function prototypes ** (used for debug information) */ typedef struct LocVar { TString *varname; int startpc; /* first point where variable is active */ int endpc; /* first point where variable is dead */ } LocVar; /* ** Function Prototypes */ typedef struct Proto { CommonHeader; TValue *k; /* constants used by the function */ Instruction *code; struct Proto **p; /* functions defined inside the function */ int *lineinfo; /* map from opcodes to source lines (debug information) */ LocVar *locvars; /* information about local variables (debug information) */ Upvaldesc *upvalues; /* upvalue information */ union Closure *cache; /* last created closure with this prototype */ TString *source; /* used for debug information */ int sizeupvalues; /* size of 'upvalues' */ int sizek; /* size of `k' */ int sizecode; int sizelineinfo; int sizep; /* size of `p' */ int sizelocvars; int linedefined; int lastlinedefined; GCObject *gclist; lu_byte numparams; /* number of fixed parameters */ lu_byte is_vararg; lu_byte maxstacksize; /* maximum stack used by this function */ } Proto; /* ** Lua Upvalues */ typedef struct UpVal { CommonHeader; TValue *v; /* points to stack or to its own value */ union { TValue value; /* the value (when closed) */ struct { /* double linked list (when open) */ struct UpVal *prev; struct UpVal *next; } l; } u; } UpVal; /* ** Closures */ #define ClosureHeader \ CommonHeader; lu_byte nupvalues; GCObject *gclist typedef struct CClosure { ClosureHeader; lua_CFunction f; TValue upvalue[1]; /* list of upvalues */ } CClosure; typedef struct LClosure { ClosureHeader; struct Proto *p; UpVal *upvals[1]; /* list of upvalues */ } LClosure; typedef union Closure { CClosure c; LClosure l; } Closure; #define isLfunction(o) ttisLclosure(o) #define getproto(o) (clLvalue(o)->p) /* ** Tables */ typedef union TKey { struct { TValuefields; struct Node *next; /* for chaining */ } nk; TValue tvk; } TKey; typedef struct Node { TValue i_val; TKey i_key; } Node; typedef struct Table { CommonHeader; lu_byte flags; /* 1<

lsizenode)) /* ** (address of) a fixed nil value */ #define luaO_nilobject (&luaO_nilobject_) LUAI_DDEC const TValue luaO_nilobject_; LUAI_FUNC int luaO_int2fb (unsigned int x); LUAI_FUNC int luaO_fb2int (int x); LUAI_FUNC int luaO_ceillog2 (unsigned int x); LUAI_FUNC lua_Number luaO_arith (int op, lua_Number v1, lua_Number v2); LUAI_FUNC int luaO_str2d (const char *s, size_t len, lua_Number *result); LUAI_FUNC int luaO_hexavalue (int c); LUAI_FUNC const char *luaO_pushvfstring (lua_State *L, const char *fmt, va_list argp); LUAI_FUNC const char *luaO_pushfstring (lua_State *L, const char *fmt, ...); LUAI_FUNC void luaO_chunkid (char *out, const char *source, size_t len); #endif april-ann-0.4.1/lua/lua-5.2.2/src/lopcodes.c000066400000000000000000000060001263004425400201400ustar00rootroot00000000000000/* ** $Id: lopcodes.c,v 1.49 2012/05/14 13:34:18 roberto Exp $ ** Opcodes for Lua virtual machine ** See Copyright Notice in lua.h */ #define lopcodes_c #define LUA_CORE #include "lopcodes.h" /* ORDER OP */ LUAI_DDEF const char *const luaP_opnames[NUM_OPCODES+1] = { "MOVE", "LOADK", "LOADKX", "LOADBOOL", "LOADNIL", "GETUPVAL", "GETTABUP", "GETTABLE", "SETTABUP", "SETUPVAL", "SETTABLE", "NEWTABLE", "SELF", "ADD", "SUB", "MUL", "DIV", "MOD", "POW", "UNM", "NOT", "LEN", "CONCAT", "JMP", "EQ", "LT", "LE", "TEST", "TESTSET", "CALL", "TAILCALL", "RETURN", "FORLOOP", "FORPREP", "TFORCALL", "TFORLOOP", "SETLIST", "CLOSURE", "VARARG", "EXTRAARG", NULL }; #define opmode(t,a,b,c,m) (((t)<<7) | ((a)<<6) | ((b)<<4) | ((c)<<2) | (m)) LUAI_DDEF const lu_byte luaP_opmodes[NUM_OPCODES] = { /* T A B C mode opcode */ opmode(0, 1, OpArgR, OpArgN, iABC) /* OP_MOVE */ ,opmode(0, 1, OpArgK, OpArgN, iABx) /* OP_LOADK */ ,opmode(0, 1, OpArgN, OpArgN, iABx) /* OP_LOADKX */ ,opmode(0, 1, OpArgU, OpArgU, iABC) /* OP_LOADBOOL */ ,opmode(0, 1, OpArgU, OpArgN, iABC) /* OP_LOADNIL */ ,opmode(0, 1, OpArgU, OpArgN, iABC) /* OP_GETUPVAL */ ,opmode(0, 1, OpArgU, OpArgK, iABC) /* OP_GETTABUP */ ,opmode(0, 1, OpArgR, OpArgK, iABC) /* OP_GETTABLE */ ,opmode(0, 0, OpArgK, OpArgK, iABC) /* OP_SETTABUP */ ,opmode(0, 0, OpArgU, OpArgN, iABC) /* OP_SETUPVAL */ ,opmode(0, 0, OpArgK, OpArgK, iABC) /* OP_SETTABLE */ ,opmode(0, 1, OpArgU, OpArgU, iABC) /* OP_NEWTABLE */ ,opmode(0, 1, OpArgR, OpArgK, iABC) /* OP_SELF */ ,opmode(0, 1, OpArgK, OpArgK, iABC) /* OP_ADD */ ,opmode(0, 1, OpArgK, OpArgK, iABC) /* OP_SUB */ ,opmode(0, 1, OpArgK, OpArgK, iABC) /* OP_MUL */ ,opmode(0, 1, OpArgK, OpArgK, iABC) /* OP_DIV */ ,opmode(0, 1, OpArgK, OpArgK, iABC) /* OP_MOD */ ,opmode(0, 1, OpArgK, OpArgK, iABC) /* OP_POW */ ,opmode(0, 1, OpArgR, OpArgN, iABC) /* OP_UNM */ ,opmode(0, 1, OpArgR, OpArgN, iABC) /* OP_NOT */ ,opmode(0, 1, OpArgR, OpArgN, iABC) /* OP_LEN */ ,opmode(0, 1, OpArgR, OpArgR, iABC) /* OP_CONCAT */ ,opmode(0, 0, OpArgR, OpArgN, iAsBx) /* OP_JMP */ ,opmode(1, 0, OpArgK, OpArgK, iABC) /* OP_EQ */ ,opmode(1, 0, OpArgK, OpArgK, iABC) /* OP_LT */ ,opmode(1, 0, OpArgK, OpArgK, iABC) /* OP_LE */ ,opmode(1, 0, OpArgN, OpArgU, iABC) /* OP_TEST */ ,opmode(1, 1, OpArgR, OpArgU, iABC) /* OP_TESTSET */ ,opmode(0, 1, OpArgU, OpArgU, iABC) /* OP_CALL */ ,opmode(0, 1, OpArgU, OpArgU, iABC) /* OP_TAILCALL */ ,opmode(0, 0, OpArgU, OpArgN, iABC) /* OP_RETURN */ ,opmode(0, 1, OpArgR, OpArgN, iAsBx) /* OP_FORLOOP */ ,opmode(0, 1, OpArgR, OpArgN, iAsBx) /* OP_FORPREP */ ,opmode(0, 0, OpArgN, OpArgU, iABC) /* OP_TFORCALL */ ,opmode(0, 1, OpArgR, OpArgN, iAsBx) /* OP_TFORLOOP */ ,opmode(0, 0, OpArgU, OpArgU, iABC) /* OP_SETLIST */ ,opmode(0, 1, OpArgU, OpArgN, iABx) /* OP_CLOSURE */ ,opmode(0, 1, OpArgU, OpArgN, iABC) /* OP_VARARG */ ,opmode(0, 0, OpArgU, OpArgU, iAx) /* OP_EXTRAARG */ }; april-ann-0.4.1/lua/lua-5.2.2/src/lopcodes.h000066400000000000000000000204421263004425400201530ustar00rootroot00000000000000/* ** $Id: lopcodes.h,v 1.142 2011/07/15 12:50:29 roberto Exp $ ** Opcodes for Lua virtual machine ** See Copyright Notice in lua.h */ #ifndef lopcodes_h #define lopcodes_h #include "llimits.h" /*=========================================================================== We assume that instructions are unsigned numbers. All instructions have an opcode in the first 6 bits. Instructions can have the following fields: `A' : 8 bits `B' : 9 bits `C' : 9 bits 'Ax' : 26 bits ('A', 'B', and 'C' together) `Bx' : 18 bits (`B' and `C' together) `sBx' : signed Bx A signed argument is represented in excess K; that is, the number value is the unsigned value minus K. K is exactly the maximum value for that argument (so that -max is represented by 0, and +max is represented by 2*max), which is half the maximum for the corresponding unsigned argument. ===========================================================================*/ enum OpMode {iABC, iABx, iAsBx, iAx}; /* basic instruction format */ /* ** size and position of opcode arguments. */ #define SIZE_C 9 #define SIZE_B 9 #define SIZE_Bx (SIZE_C + SIZE_B) #define SIZE_A 8 #define SIZE_Ax (SIZE_C + SIZE_B + SIZE_A) #define SIZE_OP 6 #define POS_OP 0 #define POS_A (POS_OP + SIZE_OP) #define POS_C (POS_A + SIZE_A) #define POS_B (POS_C + SIZE_C) #define POS_Bx POS_C #define POS_Ax POS_A /* ** limits for opcode arguments. ** we use (signed) int to manipulate most arguments, ** so they must fit in LUAI_BITSINT-1 bits (-1 for sign) */ #if SIZE_Bx < LUAI_BITSINT-1 #define MAXARG_Bx ((1<>1) /* `sBx' is signed */ #else #define MAXARG_Bx MAX_INT #define MAXARG_sBx MAX_INT #endif #if SIZE_Ax < LUAI_BITSINT-1 #define MAXARG_Ax ((1<>POS_OP) & MASK1(SIZE_OP,0))) #define SET_OPCODE(i,o) ((i) = (((i)&MASK0(SIZE_OP,POS_OP)) | \ ((cast(Instruction, o)<>pos) & MASK1(size,0))) #define setarg(i,v,pos,size) ((i) = (((i)&MASK0(size,pos)) | \ ((cast(Instruction, v)<= R(A) + 1 */ OP_EQ,/* A B C if ((RK(B) == RK(C)) ~= A) then pc++ */ OP_LT,/* A B C if ((RK(B) < RK(C)) ~= A) then pc++ */ OP_LE,/* A B C if ((RK(B) <= RK(C)) ~= A) then pc++ */ OP_TEST,/* A C if not (R(A) <=> C) then pc++ */ OP_TESTSET,/* A B C if (R(B) <=> C) then R(A) := R(B) else pc++ */ OP_CALL,/* A B C R(A), ... ,R(A+C-2) := R(A)(R(A+1), ... ,R(A+B-1)) */ OP_TAILCALL,/* A B C return R(A)(R(A+1), ... ,R(A+B-1)) */ OP_RETURN,/* A B return R(A), ... ,R(A+B-2) (see note) */ OP_FORLOOP,/* A sBx R(A)+=R(A+2); if R(A) > 4) & 3)) #define getCMode(m) (cast(enum OpArgMask, (luaP_opmodes[m] >> 2) & 3)) #define testAMode(m) (luaP_opmodes[m] & (1 << 6)) #define testTMode(m) (luaP_opmodes[m] & (1 << 7)) LUAI_DDEC const char *const luaP_opnames[NUM_OPCODES+1]; /* opcode names */ /* number of list items to accumulate before a SETLIST instruction */ #define LFIELDS_PER_FLUSH 50 #endif april-ann-0.4.1/lua/lua-5.2.2/src/loslib.c000066400000000000000000000175671263004425400176400ustar00rootroot00000000000000/* ** $Id: loslib.c,v 1.40 2012/10/19 15:54:02 roberto Exp $ ** Standard Operating System library ** See Copyright Notice in lua.h */ #include #include #include #include #include #define loslib_c #define LUA_LIB #include "lua.h" #include "lauxlib.h" #include "lualib.h" /* ** list of valid conversion specifiers for the 'strftime' function */ #if !defined(LUA_STRFTIMEOPTIONS) #if !defined(LUA_USE_POSIX) #define LUA_STRFTIMEOPTIONS { "aAbBcdHIjmMpSUwWxXyYz%", "" } #else #define LUA_STRFTIMEOPTIONS \ { "aAbBcCdDeFgGhHIjmMnprRStTuUVwWxXyYzZ%", "" \ "", "E", "cCxXyY", \ "O", "deHImMSuUVwWy" } #endif #endif /* ** By default, Lua uses tmpnam except when POSIX is available, where it ** uses mkstemp. */ #if defined(LUA_USE_MKSTEMP) #include #define LUA_TMPNAMBUFSIZE 32 #define lua_tmpnam(b,e) { \ strcpy(b, "/tmp/lua_XXXXXX"); \ e = mkstemp(b); \ if (e != -1) close(e); \ e = (e == -1); } #elif !defined(lua_tmpnam) #define LUA_TMPNAMBUFSIZE L_tmpnam #define lua_tmpnam(b,e) { e = (tmpnam(b) == NULL); } #endif /* ** By default, Lua uses gmtime/localtime, except when POSIX is available, ** where it uses gmtime_r/localtime_r */ #if defined(LUA_USE_GMTIME_R) #define l_gmtime(t,r) gmtime_r(t,r) #define l_localtime(t,r) localtime_r(t,r) #elif !defined(l_gmtime) #define l_gmtime(t,r) ((void)r, gmtime(t)) #define l_localtime(t,r) ((void)r, localtime(t)) #endif static int os_execute (lua_State *L) { const char *cmd = luaL_optstring(L, 1, NULL); int stat = system(cmd); if (cmd != NULL) return luaL_execresult(L, stat); else { lua_pushboolean(L, stat); /* true if there is a shell */ return 1; } } static int os_remove (lua_State *L) { const char *filename = luaL_checkstring(L, 1); return luaL_fileresult(L, remove(filename) == 0, filename); } static int os_rename (lua_State *L) { const char *fromname = luaL_checkstring(L, 1); const char *toname = luaL_checkstring(L, 2); return luaL_fileresult(L, rename(fromname, toname) == 0, NULL); } static int os_tmpname (lua_State *L) { char buff[LUA_TMPNAMBUFSIZE]; int err; lua_tmpnam(buff, err); if (err) return luaL_error(L, "unable to generate a unique filename"); lua_pushstring(L, buff); return 1; } static int os_getenv (lua_State *L) { lua_pushstring(L, getenv(luaL_checkstring(L, 1))); /* if NULL push nil */ return 1; } static int os_clock (lua_State *L) { lua_pushnumber(L, ((lua_Number)clock())/(lua_Number)CLOCKS_PER_SEC); return 1; } /* ** {====================================================== ** Time/Date operations ** { year=%Y, month=%m, day=%d, hour=%H, min=%M, sec=%S, ** wday=%w+1, yday=%j, isdst=? } ** ======================================================= */ static void setfield (lua_State *L, const char *key, int value) { lua_pushinteger(L, value); lua_setfield(L, -2, key); } static void setboolfield (lua_State *L, const char *key, int value) { if (value < 0) /* undefined? */ return; /* does not set field */ lua_pushboolean(L, value); lua_setfield(L, -2, key); } static int getboolfield (lua_State *L, const char *key) { int res; lua_getfield(L, -1, key); res = lua_isnil(L, -1) ? -1 : lua_toboolean(L, -1); lua_pop(L, 1); return res; } static int getfield (lua_State *L, const char *key, int d) { int res, isnum; lua_getfield(L, -1, key); res = (int)lua_tointegerx(L, -1, &isnum); if (!isnum) { if (d < 0) return luaL_error(L, "field " LUA_QS " missing in date table", key); res = d; } lua_pop(L, 1); return res; } static const char *checkoption (lua_State *L, const char *conv, char *buff) { static const char *const options[] = LUA_STRFTIMEOPTIONS; unsigned int i; for (i = 0; i < sizeof(options)/sizeof(options[0]); i += 2) { if (*conv != '\0' && strchr(options[i], *conv) != NULL) { buff[1] = *conv; if (*options[i + 1] == '\0') { /* one-char conversion specifier? */ buff[2] = '\0'; /* end buffer */ return conv + 1; } else if (*(conv + 1) != '\0' && strchr(options[i + 1], *(conv + 1)) != NULL) { buff[2] = *(conv + 1); /* valid two-char conversion specifier */ buff[3] = '\0'; /* end buffer */ return conv + 2; } } } luaL_argerror(L, 1, lua_pushfstring(L, "invalid conversion specifier '%%%s'", conv)); return conv; /* to avoid warnings */ } static int os_date (lua_State *L) { const char *s = luaL_optstring(L, 1, "%c"); time_t t = luaL_opt(L, (time_t)luaL_checknumber, 2, time(NULL)); struct tm tmr, *stm; if (*s == '!') { /* UTC? */ stm = l_gmtime(&t, &tmr); s++; /* skip `!' */ } else stm = l_localtime(&t, &tmr); if (stm == NULL) /* invalid date? */ lua_pushnil(L); else if (strcmp(s, "*t") == 0) { lua_createtable(L, 0, 9); /* 9 = number of fields */ setfield(L, "sec", stm->tm_sec); setfield(L, "min", stm->tm_min); setfield(L, "hour", stm->tm_hour); setfield(L, "day", stm->tm_mday); setfield(L, "month", stm->tm_mon+1); setfield(L, "year", stm->tm_year+1900); setfield(L, "wday", stm->tm_wday+1); setfield(L, "yday", stm->tm_yday+1); setboolfield(L, "isdst", stm->tm_isdst); } else { char cc[4]; luaL_Buffer b; cc[0] = '%'; luaL_buffinit(L, &b); while (*s) { if (*s != '%') /* no conversion specifier? */ luaL_addchar(&b, *s++); else { size_t reslen; char buff[200]; /* should be big enough for any conversion result */ s = checkoption(L, s + 1, cc); reslen = strftime(buff, sizeof(buff), cc, stm); luaL_addlstring(&b, buff, reslen); } } luaL_pushresult(&b); } return 1; } static int os_time (lua_State *L) { time_t t; if (lua_isnoneornil(L, 1)) /* called without args? */ t = time(NULL); /* get current time */ else { struct tm ts; luaL_checktype(L, 1, LUA_TTABLE); lua_settop(L, 1); /* make sure table is at the top */ ts.tm_sec = getfield(L, "sec", 0); ts.tm_min = getfield(L, "min", 0); ts.tm_hour = getfield(L, "hour", 12); ts.tm_mday = getfield(L, "day", -1); ts.tm_mon = getfield(L, "month", -1) - 1; ts.tm_year = getfield(L, "year", -1) - 1900; ts.tm_isdst = getboolfield(L, "isdst"); t = mktime(&ts); } if (t == (time_t)(-1)) lua_pushnil(L); else lua_pushnumber(L, (lua_Number)t); return 1; } static int os_difftime (lua_State *L) { lua_pushnumber(L, difftime((time_t)(luaL_checknumber(L, 1)), (time_t)(luaL_optnumber(L, 2, 0)))); return 1; } /* }====================================================== */ static int os_setlocale (lua_State *L) { static const int cat[] = {LC_ALL, LC_COLLATE, LC_CTYPE, LC_MONETARY, LC_NUMERIC, LC_TIME}; static const char *const catnames[] = {"all", "collate", "ctype", "monetary", "numeric", "time", NULL}; const char *l = luaL_optstring(L, 1, NULL); int op = luaL_checkoption(L, 2, "all", catnames); lua_pushstring(L, setlocale(cat[op], l)); return 1; } static int os_exit (lua_State *L) { int status; if (lua_isboolean(L, 1)) status = (lua_toboolean(L, 1) ? EXIT_SUCCESS : EXIT_FAILURE); else status = luaL_optint(L, 1, EXIT_SUCCESS); if (lua_toboolean(L, 2)) lua_close(L); if (L) exit(status); /* 'if' to avoid warnings for unreachable 'return' */ return 0; } static const luaL_Reg syslib[] = { {"clock", os_clock}, {"date", os_date}, {"difftime", os_difftime}, {"execute", os_execute}, {"exit", os_exit}, {"getenv", os_getenv}, {"remove", os_remove}, {"rename", os_rename}, {"setlocale", os_setlocale}, {"time", os_time}, {"tmpname", os_tmpname}, {NULL, NULL} }; /* }====================================================== */ LUAMOD_API int luaopen_os (lua_State *L) { luaL_newlib(L, syslib); return 1; } april-ann-0.4.1/lua/lua-5.2.2/src/lparser.c000066400000000000000000001316211263004425400200100ustar00rootroot00000000000000/* ** $Id: lparser.c,v 2.130 2013/02/06 13:37:39 roberto Exp $ ** Lua Parser ** See Copyright Notice in lua.h */ #include #define lparser_c #define LUA_CORE #include "lua.h" #include "lcode.h" #include "ldebug.h" #include "ldo.h" #include "lfunc.h" #include "llex.h" #include "lmem.h" #include "lobject.h" #include "lopcodes.h" #include "lparser.h" #include "lstate.h" #include "lstring.h" #include "ltable.h" /* maximum number of local variables per function (must be smaller than 250, due to the bytecode format) */ #define MAXVARS 200 #define hasmultret(k) ((k) == VCALL || (k) == VVARARG) /* ** nodes for block list (list of active blocks) */ typedef struct BlockCnt { struct BlockCnt *previous; /* chain */ short firstlabel; /* index of first label in this block */ short firstgoto; /* index of first pending goto in this block */ lu_byte nactvar; /* # active locals outside the block */ lu_byte upval; /* true if some variable in the block is an upvalue */ lu_byte isloop; /* true if `block' is a loop */ } BlockCnt; /* ** prototypes for recursive non-terminal functions */ static void statement (LexState *ls); static void expr (LexState *ls, expdesc *v); static void anchor_token (LexState *ls) { /* last token from outer function must be EOS */ lua_assert(ls->fs != NULL || ls->t.token == TK_EOS); if (ls->t.token == TK_NAME || ls->t.token == TK_STRING) { TString *ts = ls->t.seminfo.ts; luaX_newstring(ls, getstr(ts), ts->tsv.len); } } /* semantic error */ static l_noret semerror (LexState *ls, const char *msg) { ls->t.token = 0; /* remove 'near to' from final message */ luaX_syntaxerror(ls, msg); } static l_noret error_expected (LexState *ls, int token) { luaX_syntaxerror(ls, luaO_pushfstring(ls->L, "%s expected", luaX_token2str(ls, token))); } static l_noret errorlimit (FuncState *fs, int limit, const char *what) { lua_State *L = fs->ls->L; const char *msg; int line = fs->f->linedefined; const char *where = (line == 0) ? "main function" : luaO_pushfstring(L, "function at line %d", line); msg = luaO_pushfstring(L, "too many %s (limit is %d) in %s", what, limit, where); luaX_syntaxerror(fs->ls, msg); } static void checklimit (FuncState *fs, int v, int l, const char *what) { if (v > l) errorlimit(fs, l, what); } static int testnext (LexState *ls, int c) { if (ls->t.token == c) { luaX_next(ls); return 1; } else return 0; } static void check (LexState *ls, int c) { if (ls->t.token != c) error_expected(ls, c); } static void checknext (LexState *ls, int c) { check(ls, c); luaX_next(ls); } #define check_condition(ls,c,msg) { if (!(c)) luaX_syntaxerror(ls, msg); } static void check_match (LexState *ls, int what, int who, int where) { if (!testnext(ls, what)) { if (where == ls->linenumber) error_expected(ls, what); else { luaX_syntaxerror(ls, luaO_pushfstring(ls->L, "%s expected (to close %s at line %d)", luaX_token2str(ls, what), luaX_token2str(ls, who), where)); } } } static TString *str_checkname (LexState *ls) { TString *ts; check(ls, TK_NAME); ts = ls->t.seminfo.ts; luaX_next(ls); return ts; } static void init_exp (expdesc *e, expkind k, int i) { e->f = e->t = NO_JUMP; e->k = k; e->u.info = i; } static void codestring (LexState *ls, expdesc *e, TString *s) { init_exp(e, VK, luaK_stringK(ls->fs, s)); } static void checkname (LexState *ls, expdesc *e) { codestring(ls, e, str_checkname(ls)); } static int registerlocalvar (LexState *ls, TString *varname) { FuncState *fs = ls->fs; Proto *f = fs->f; int oldsize = f->sizelocvars; luaM_growvector(ls->L, f->locvars, fs->nlocvars, f->sizelocvars, LocVar, SHRT_MAX, "local variables"); while (oldsize < f->sizelocvars) f->locvars[oldsize++].varname = NULL; f->locvars[fs->nlocvars].varname = varname; luaC_objbarrier(ls->L, f, varname); return fs->nlocvars++; } static void new_localvar (LexState *ls, TString *name) { FuncState *fs = ls->fs; Dyndata *dyd = ls->dyd; int reg = registerlocalvar(ls, name); checklimit(fs, dyd->actvar.n + 1 - fs->firstlocal, MAXVARS, "local variables"); luaM_growvector(ls->L, dyd->actvar.arr, dyd->actvar.n + 1, dyd->actvar.size, Vardesc, MAX_INT, "local variables"); dyd->actvar.arr[dyd->actvar.n++].idx = cast(short, reg); } static void new_localvarliteral_ (LexState *ls, const char *name, size_t sz) { new_localvar(ls, luaX_newstring(ls, name, sz)); } #define new_localvarliteral(ls,v) \ new_localvarliteral_(ls, "" v, (sizeof(v)/sizeof(char))-1) static LocVar *getlocvar (FuncState *fs, int i) { int idx = fs->ls->dyd->actvar.arr[fs->firstlocal + i].idx; lua_assert(idx < fs->nlocvars); return &fs->f->locvars[idx]; } static void adjustlocalvars (LexState *ls, int nvars) { FuncState *fs = ls->fs; fs->nactvar = cast_byte(fs->nactvar + nvars); for (; nvars; nvars--) { getlocvar(fs, fs->nactvar - nvars)->startpc = fs->pc; } } static void removevars (FuncState *fs, int tolevel) { fs->ls->dyd->actvar.n -= (fs->nactvar - tolevel); while (fs->nactvar > tolevel) getlocvar(fs, --fs->nactvar)->endpc = fs->pc; } static int searchupvalue (FuncState *fs, TString *name) { int i; Upvaldesc *up = fs->f->upvalues; for (i = 0; i < fs->nups; i++) { if (luaS_eqstr(up[i].name, name)) return i; } return -1; /* not found */ } static int newupvalue (FuncState *fs, TString *name, expdesc *v) { Proto *f = fs->f; int oldsize = f->sizeupvalues; checklimit(fs, fs->nups + 1, MAXUPVAL, "upvalues"); luaM_growvector(fs->ls->L, f->upvalues, fs->nups, f->sizeupvalues, Upvaldesc, MAXUPVAL, "upvalues"); while (oldsize < f->sizeupvalues) f->upvalues[oldsize++].name = NULL; f->upvalues[fs->nups].instack = (v->k == VLOCAL); f->upvalues[fs->nups].idx = cast_byte(v->u.info); f->upvalues[fs->nups].name = name; luaC_objbarrier(fs->ls->L, f, name); return fs->nups++; } static int searchvar (FuncState *fs, TString *n) { int i; for (i = cast_int(fs->nactvar) - 1; i >= 0; i--) { if (luaS_eqstr(n, getlocvar(fs, i)->varname)) return i; } return -1; /* not found */ } /* Mark block where variable at given level was defined (to emit close instructions later). */ static void markupval (FuncState *fs, int level) { BlockCnt *bl = fs->bl; while (bl->nactvar > level) bl = bl->previous; bl->upval = 1; } /* Find variable with given name 'n'. If it is an upvalue, add this upvalue into all intermediate functions. */ static int singlevaraux (FuncState *fs, TString *n, expdesc *var, int base) { if (fs == NULL) /* no more levels? */ return VVOID; /* default is global */ else { int v = searchvar(fs, n); /* look up locals at current level */ if (v >= 0) { /* found? */ init_exp(var, VLOCAL, v); /* variable is local */ if (!base) markupval(fs, v); /* local will be used as an upval */ return VLOCAL; } else { /* not found as local at current level; try upvalues */ int idx = searchupvalue(fs, n); /* try existing upvalues */ if (idx < 0) { /* not found? */ if (singlevaraux(fs->prev, n, var, 0) == VVOID) /* try upper levels */ return VVOID; /* not found; is a global */ /* else was LOCAL or UPVAL */ idx = newupvalue(fs, n, var); /* will be a new upvalue */ } init_exp(var, VUPVAL, idx); return VUPVAL; } } } static void singlevar (LexState *ls, expdesc *var) { TString *varname = str_checkname(ls); FuncState *fs = ls->fs; if (singlevaraux(fs, varname, var, 1) == VVOID) { /* global name? */ expdesc key; singlevaraux(fs, ls->envn, var, 1); /* get environment variable */ lua_assert(var->k == VLOCAL || var->k == VUPVAL); codestring(ls, &key, varname); /* key is variable name */ luaK_indexed(fs, var, &key); /* env[varname] */ } } static void adjust_assign (LexState *ls, int nvars, int nexps, expdesc *e) { FuncState *fs = ls->fs; int extra = nvars - nexps; if (hasmultret(e->k)) { extra++; /* includes call itself */ if (extra < 0) extra = 0; luaK_setreturns(fs, e, extra); /* last exp. provides the difference */ if (extra > 1) luaK_reserveregs(fs, extra-1); } else { if (e->k != VVOID) luaK_exp2nextreg(fs, e); /* close last expression */ if (extra > 0) { int reg = fs->freereg; luaK_reserveregs(fs, extra); luaK_nil(fs, reg, extra); } } } static void enterlevel (LexState *ls) { lua_State *L = ls->L; ++L->nCcalls; checklimit(ls->fs, L->nCcalls, LUAI_MAXCCALLS, "C levels"); } #define leavelevel(ls) ((ls)->L->nCcalls--) static void closegoto (LexState *ls, int g, Labeldesc *label) { int i; FuncState *fs = ls->fs; Labellist *gl = &ls->dyd->gt; Labeldesc *gt = &gl->arr[g]; lua_assert(luaS_eqstr(gt->name, label->name)); if (gt->nactvar < label->nactvar) { TString *vname = getlocvar(fs, gt->nactvar)->varname; const char *msg = luaO_pushfstring(ls->L, " at line %d jumps into the scope of local " LUA_QS, getstr(gt->name), gt->line, getstr(vname)); semerror(ls, msg); } luaK_patchlist(fs, gt->pc, label->pc); /* remove goto from pending list */ for (i = g; i < gl->n - 1; i++) gl->arr[i] = gl->arr[i + 1]; gl->n--; } /* ** try to close a goto with existing labels; this solves backward jumps */ static int findlabel (LexState *ls, int g) { int i; BlockCnt *bl = ls->fs->bl; Dyndata *dyd = ls->dyd; Labeldesc *gt = &dyd->gt.arr[g]; /* check labels in current block for a match */ for (i = bl->firstlabel; i < dyd->label.n; i++) { Labeldesc *lb = &dyd->label.arr[i]; if (luaS_eqstr(lb->name, gt->name)) { /* correct label? */ if (gt->nactvar > lb->nactvar && (bl->upval || dyd->label.n > bl->firstlabel)) luaK_patchclose(ls->fs, gt->pc, lb->nactvar); closegoto(ls, g, lb); /* close it */ return 1; } } return 0; /* label not found; cannot close goto */ } static int newlabelentry (LexState *ls, Labellist *l, TString *name, int line, int pc) { int n = l->n; luaM_growvector(ls->L, l->arr, n, l->size, Labeldesc, SHRT_MAX, "labels/gotos"); l->arr[n].name = name; l->arr[n].line = line; l->arr[n].nactvar = ls->fs->nactvar; l->arr[n].pc = pc; l->n++; return n; } /* ** check whether new label 'lb' matches any pending gotos in current ** block; solves forward jumps */ static void findgotos (LexState *ls, Labeldesc *lb) { Labellist *gl = &ls->dyd->gt; int i = ls->fs->bl->firstgoto; while (i < gl->n) { if (luaS_eqstr(gl->arr[i].name, lb->name)) closegoto(ls, i, lb); else i++; } } /* ** "export" pending gotos to outer level, to check them against ** outer labels; if the block being exited has upvalues, and ** the goto exits the scope of any variable (which can be the ** upvalue), close those variables being exited. */ static void movegotosout (FuncState *fs, BlockCnt *bl) { int i = bl->firstgoto; Labellist *gl = &fs->ls->dyd->gt; /* correct pending gotos to current block and try to close it with visible labels */ while (i < gl->n) { Labeldesc *gt = &gl->arr[i]; if (gt->nactvar > bl->nactvar) { if (bl->upval) luaK_patchclose(fs, gt->pc, bl->nactvar); gt->nactvar = bl->nactvar; } if (!findlabel(fs->ls, i)) i++; /* move to next one */ } } static void enterblock (FuncState *fs, BlockCnt *bl, lu_byte isloop) { bl->isloop = isloop; bl->nactvar = fs->nactvar; bl->firstlabel = fs->ls->dyd->label.n; bl->firstgoto = fs->ls->dyd->gt.n; bl->upval = 0; bl->previous = fs->bl; fs->bl = bl; lua_assert(fs->freereg == fs->nactvar); } /* ** create a label named "break" to resolve break statements */ static void breaklabel (LexState *ls) { TString *n = luaS_new(ls->L, "break"); int l = newlabelentry(ls, &ls->dyd->label, n, 0, ls->fs->pc); findgotos(ls, &ls->dyd->label.arr[l]); } /* ** generates an error for an undefined 'goto'; choose appropriate ** message when label name is a reserved word (which can only be 'break') */ static l_noret undefgoto (LexState *ls, Labeldesc *gt) { const char *msg = isreserved(gt->name) ? "<%s> at line %d not inside a loop" : "no visible label " LUA_QS " for at line %d"; msg = luaO_pushfstring(ls->L, msg, getstr(gt->name), gt->line); semerror(ls, msg); } static void leaveblock (FuncState *fs) { BlockCnt *bl = fs->bl; LexState *ls = fs->ls; if (bl->previous && bl->upval) { /* create a 'jump to here' to close upvalues */ int j = luaK_jump(fs); luaK_patchclose(fs, j, bl->nactvar); luaK_patchtohere(fs, j); } if (bl->isloop) breaklabel(ls); /* close pending breaks */ fs->bl = bl->previous; removevars(fs, bl->nactvar); lua_assert(bl->nactvar == fs->nactvar); fs->freereg = fs->nactvar; /* free registers */ ls->dyd->label.n = bl->firstlabel; /* remove local labels */ if (bl->previous) /* inner block? */ movegotosout(fs, bl); /* update pending gotos to outer block */ else if (bl->firstgoto < ls->dyd->gt.n) /* pending gotos in outer block? */ undefgoto(ls, &ls->dyd->gt.arr[bl->firstgoto]); /* error */ } /* ** adds a new prototype into list of prototypes */ static Proto *addprototype (LexState *ls) { Proto *clp; lua_State *L = ls->L; FuncState *fs = ls->fs; Proto *f = fs->f; /* prototype of current function */ if (fs->np >= f->sizep) { int oldsize = f->sizep; luaM_growvector(L, f->p, fs->np, f->sizep, Proto *, MAXARG_Bx, "functions"); while (oldsize < f->sizep) f->p[oldsize++] = NULL; } f->p[fs->np++] = clp = luaF_newproto(L); luaC_objbarrier(L, f, clp); return clp; } /* ** codes instruction to create new closure in parent function. ** The OP_CLOSURE instruction must use the last available register, ** so that, if it invokes the GC, the GC knows which registers ** are in use at that time. */ static void codeclosure (LexState *ls, expdesc *v) { FuncState *fs = ls->fs->prev; init_exp(v, VRELOCABLE, luaK_codeABx(fs, OP_CLOSURE, 0, fs->np - 1)); luaK_exp2nextreg(fs, v); /* fix it at the last register */ } static void open_func (LexState *ls, FuncState *fs, BlockCnt *bl) { lua_State *L = ls->L; Proto *f; fs->prev = ls->fs; /* linked list of funcstates */ fs->ls = ls; ls->fs = fs; fs->pc = 0; fs->lasttarget = 0; fs->jpc = NO_JUMP; fs->freereg = 0; fs->nk = 0; fs->np = 0; fs->nups = 0; fs->nlocvars = 0; fs->nactvar = 0; fs->firstlocal = ls->dyd->actvar.n; fs->bl = NULL; f = fs->f; f->source = ls->source; f->maxstacksize = 2; /* registers 0/1 are always valid */ fs->h = luaH_new(L); /* anchor table of constants (to avoid being collected) */ sethvalue2s(L, L->top, fs->h); incr_top(L); enterblock(fs, bl, 0); } static void close_func (LexState *ls) { lua_State *L = ls->L; FuncState *fs = ls->fs; Proto *f = fs->f; luaK_ret(fs, 0, 0); /* final return */ leaveblock(fs); luaM_reallocvector(L, f->code, f->sizecode, fs->pc, Instruction); f->sizecode = fs->pc; luaM_reallocvector(L, f->lineinfo, f->sizelineinfo, fs->pc, int); f->sizelineinfo = fs->pc; luaM_reallocvector(L, f->k, f->sizek, fs->nk, TValue); f->sizek = fs->nk; luaM_reallocvector(L, f->p, f->sizep, fs->np, Proto *); f->sizep = fs->np; luaM_reallocvector(L, f->locvars, f->sizelocvars, fs->nlocvars, LocVar); f->sizelocvars = fs->nlocvars; luaM_reallocvector(L, f->upvalues, f->sizeupvalues, fs->nups, Upvaldesc); f->sizeupvalues = fs->nups; lua_assert(fs->bl == NULL); ls->fs = fs->prev; /* last token read was anchored in defunct function; must re-anchor it */ anchor_token(ls); L->top--; /* pop table of constants */ luaC_checkGC(L); } /*============================================================*/ /* GRAMMAR RULES */ /*============================================================*/ /* ** check whether current token is in the follow set of a block. ** 'until' closes syntactical blocks, but do not close scope, ** so it handled in separate. */ static int block_follow (LexState *ls, int withuntil) { switch (ls->t.token) { case TK_ELSE: case TK_ELSEIF: case TK_END: case TK_EOS: return 1; case TK_UNTIL: return withuntil; default: return 0; } } static void statlist (LexState *ls) { /* statlist -> { stat [`;'] } */ while (!block_follow(ls, 1)) { if (ls->t.token == TK_RETURN) { statement(ls); return; /* 'return' must be last statement */ } statement(ls); } } static void fieldsel (LexState *ls, expdesc *v) { /* fieldsel -> ['.' | ':'] NAME */ FuncState *fs = ls->fs; expdesc key; luaK_exp2anyregup(fs, v); luaX_next(ls); /* skip the dot or colon */ checkname(ls, &key); luaK_indexed(fs, v, &key); } static void yindex (LexState *ls, expdesc *v) { /* index -> '[' expr ']' */ luaX_next(ls); /* skip the '[' */ expr(ls, v); luaK_exp2val(ls->fs, v); checknext(ls, ']'); } /* ** {====================================================================== ** Rules for Constructors ** ======================================================================= */ struct ConsControl { expdesc v; /* last list item read */ expdesc *t; /* table descriptor */ int nh; /* total number of `record' elements */ int na; /* total number of array elements */ int tostore; /* number of array elements pending to be stored */ }; static void recfield (LexState *ls, struct ConsControl *cc) { /* recfield -> (NAME | `['exp1`]') = exp1 */ FuncState *fs = ls->fs; int reg = ls->fs->freereg; expdesc key, val; int rkkey; if (ls->t.token == TK_NAME) { checklimit(fs, cc->nh, MAX_INT, "items in a constructor"); checkname(ls, &key); } else /* ls->t.token == '[' */ yindex(ls, &key); cc->nh++; checknext(ls, '='); rkkey = luaK_exp2RK(fs, &key); expr(ls, &val); luaK_codeABC(fs, OP_SETTABLE, cc->t->u.info, rkkey, luaK_exp2RK(fs, &val)); fs->freereg = reg; /* free registers */ } static void closelistfield (FuncState *fs, struct ConsControl *cc) { if (cc->v.k == VVOID) return; /* there is no list item */ luaK_exp2nextreg(fs, &cc->v); cc->v.k = VVOID; if (cc->tostore == LFIELDS_PER_FLUSH) { luaK_setlist(fs, cc->t->u.info, cc->na, cc->tostore); /* flush */ cc->tostore = 0; /* no more items pending */ } } static void lastlistfield (FuncState *fs, struct ConsControl *cc) { if (cc->tostore == 0) return; if (hasmultret(cc->v.k)) { luaK_setmultret(fs, &cc->v); luaK_setlist(fs, cc->t->u.info, cc->na, LUA_MULTRET); cc->na--; /* do not count last expression (unknown number of elements) */ } else { if (cc->v.k != VVOID) luaK_exp2nextreg(fs, &cc->v); luaK_setlist(fs, cc->t->u.info, cc->na, cc->tostore); } } static void listfield (LexState *ls, struct ConsControl *cc) { /* listfield -> exp */ expr(ls, &cc->v); checklimit(ls->fs, cc->na, MAX_INT, "items in a constructor"); cc->na++; cc->tostore++; } static void field (LexState *ls, struct ConsControl *cc) { /* field -> listfield | recfield */ switch(ls->t.token) { case TK_NAME: { /* may be 'listfield' or 'recfield' */ if (luaX_lookahead(ls) != '=') /* expression? */ listfield(ls, cc); else recfield(ls, cc); break; } case '[': { recfield(ls, cc); break; } default: { listfield(ls, cc); break; } } } static void constructor (LexState *ls, expdesc *t) { /* constructor -> '{' [ field { sep field } [sep] ] '}' sep -> ',' | ';' */ FuncState *fs = ls->fs; int line = ls->linenumber; int pc = luaK_codeABC(fs, OP_NEWTABLE, 0, 0, 0); struct ConsControl cc; cc.na = cc.nh = cc.tostore = 0; cc.t = t; init_exp(t, VRELOCABLE, pc); init_exp(&cc.v, VVOID, 0); /* no value (yet) */ luaK_exp2nextreg(ls->fs, t); /* fix it at stack top */ checknext(ls, '{'); do { lua_assert(cc.v.k == VVOID || cc.tostore > 0); if (ls->t.token == '}') break; closelistfield(fs, &cc); field(ls, &cc); } while (testnext(ls, ',') || testnext(ls, ';')); check_match(ls, '}', '{', line); lastlistfield(fs, &cc); SETARG_B(fs->f->code[pc], luaO_int2fb(cc.na)); /* set initial array size */ SETARG_C(fs->f->code[pc], luaO_int2fb(cc.nh)); /* set initial table size */ } /* }====================================================================== */ static void parlist (LexState *ls) { /* parlist -> [ param { `,' param } ] */ FuncState *fs = ls->fs; Proto *f = fs->f; int nparams = 0; f->is_vararg = 0; if (ls->t.token != ')') { /* is `parlist' not empty? */ do { switch (ls->t.token) { case TK_NAME: { /* param -> NAME */ new_localvar(ls, str_checkname(ls)); nparams++; break; } case TK_DOTS: { /* param -> `...' */ luaX_next(ls); f->is_vararg = 1; break; } default: luaX_syntaxerror(ls, " or " LUA_QL("...") " expected"); } } while (!f->is_vararg && testnext(ls, ',')); } adjustlocalvars(ls, nparams); f->numparams = cast_byte(fs->nactvar); luaK_reserveregs(fs, fs->nactvar); /* reserve register for parameters */ } static void body (LexState *ls, expdesc *e, int ismethod, int line) { /* body -> `(' parlist `)' block END */ FuncState new_fs; BlockCnt bl; new_fs.f = addprototype(ls); new_fs.f->linedefined = line; open_func(ls, &new_fs, &bl); checknext(ls, '('); if (ismethod) { new_localvarliteral(ls, "self"); /* create 'self' parameter */ adjustlocalvars(ls, 1); } parlist(ls); checknext(ls, ')'); statlist(ls); new_fs.f->lastlinedefined = ls->linenumber; check_match(ls, TK_END, TK_FUNCTION, line); codeclosure(ls, e); close_func(ls); } static int explist (LexState *ls, expdesc *v) { /* explist -> expr { `,' expr } */ int n = 1; /* at least one expression */ expr(ls, v); while (testnext(ls, ',')) { luaK_exp2nextreg(ls->fs, v); expr(ls, v); n++; } return n; } static void funcargs (LexState *ls, expdesc *f, int line) { FuncState *fs = ls->fs; expdesc args; int base, nparams; switch (ls->t.token) { case '(': { /* funcargs -> `(' [ explist ] `)' */ luaX_next(ls); if (ls->t.token == ')') /* arg list is empty? */ args.k = VVOID; else { explist(ls, &args); luaK_setmultret(fs, &args); } check_match(ls, ')', '(', line); break; } case '{': { /* funcargs -> constructor */ constructor(ls, &args); break; } case TK_STRING: { /* funcargs -> STRING */ codestring(ls, &args, ls->t.seminfo.ts); luaX_next(ls); /* must use `seminfo' before `next' */ break; } default: { luaX_syntaxerror(ls, "function arguments expected"); } } lua_assert(f->k == VNONRELOC); base = f->u.info; /* base register for call */ if (hasmultret(args.k)) nparams = LUA_MULTRET; /* open call */ else { if (args.k != VVOID) luaK_exp2nextreg(fs, &args); /* close last argument */ nparams = fs->freereg - (base+1); } init_exp(f, VCALL, luaK_codeABC(fs, OP_CALL, base, nparams+1, 2)); luaK_fixline(fs, line); fs->freereg = base+1; /* call remove function and arguments and leaves (unless changed) one result */ } /* ** {====================================================================== ** Expression parsing ** ======================================================================= */ static void primaryexp (LexState *ls, expdesc *v) { /* primaryexp -> NAME | '(' expr ')' */ switch (ls->t.token) { case '(': { int line = ls->linenumber; luaX_next(ls); expr(ls, v); check_match(ls, ')', '(', line); luaK_dischargevars(ls->fs, v); return; } case TK_NAME: { singlevar(ls, v); return; } default: { luaX_syntaxerror(ls, "unexpected symbol"); } } } static void suffixedexp (LexState *ls, expdesc *v) { /* suffixedexp -> primaryexp { '.' NAME | '[' exp ']' | ':' NAME funcargs | funcargs } */ FuncState *fs = ls->fs; int line = ls->linenumber; primaryexp(ls, v); for (;;) { switch (ls->t.token) { case '.': { /* fieldsel */ fieldsel(ls, v); break; } case '[': { /* `[' exp1 `]' */ expdesc key; luaK_exp2anyregup(fs, v); yindex(ls, &key); luaK_indexed(fs, v, &key); break; } case ':': { /* `:' NAME funcargs */ expdesc key; luaX_next(ls); checkname(ls, &key); luaK_self(fs, v, &key); funcargs(ls, v, line); break; } case '(': case TK_STRING: case '{': { /* funcargs */ luaK_exp2nextreg(fs, v); funcargs(ls, v, line); break; } default: return; } } } static void simpleexp (LexState *ls, expdesc *v) { /* simpleexp -> NUMBER | STRING | NIL | TRUE | FALSE | ... | constructor | FUNCTION body | suffixedexp */ switch (ls->t.token) { case TK_NUMBER: { init_exp(v, VKNUM, 0); v->u.nval = ls->t.seminfo.r; break; } case TK_STRING: { codestring(ls, v, ls->t.seminfo.ts); break; } case TK_NIL: { init_exp(v, VNIL, 0); break; } case TK_TRUE: { init_exp(v, VTRUE, 0); break; } case TK_FALSE: { init_exp(v, VFALSE, 0); break; } case TK_DOTS: { /* vararg */ FuncState *fs = ls->fs; check_condition(ls, fs->f->is_vararg, "cannot use " LUA_QL("...") " outside a vararg function"); init_exp(v, VVARARG, luaK_codeABC(fs, OP_VARARG, 0, 1, 0)); break; } case '{': { /* constructor */ constructor(ls, v); return; } case TK_FUNCTION: { luaX_next(ls); body(ls, v, 0, ls->linenumber); return; } default: { suffixedexp(ls, v); return; } } luaX_next(ls); } static UnOpr getunopr (int op) { switch (op) { case TK_NOT: return OPR_NOT; case '-': return OPR_MINUS; case '#': return OPR_LEN; default: return OPR_NOUNOPR; } } static BinOpr getbinopr (int op) { switch (op) { case '+': return OPR_ADD; case '-': return OPR_SUB; case '*': return OPR_MUL; case '/': return OPR_DIV; case '%': return OPR_MOD; case '^': return OPR_POW; case TK_CONCAT: return OPR_CONCAT; case TK_NE: return OPR_NE; case TK_EQ: return OPR_EQ; case '<': return OPR_LT; case TK_LE: return OPR_LE; case '>': return OPR_GT; case TK_GE: return OPR_GE; case TK_AND: return OPR_AND; case TK_OR: return OPR_OR; default: return OPR_NOBINOPR; } } static const struct { lu_byte left; /* left priority for each binary operator */ lu_byte right; /* right priority */ } priority[] = { /* ORDER OPR */ {6, 6}, {6, 6}, {7, 7}, {7, 7}, {7, 7}, /* `+' `-' `*' `/' `%' */ {10, 9}, {5, 4}, /* ^, .. (right associative) */ {3, 3}, {3, 3}, {3, 3}, /* ==, <, <= */ {3, 3}, {3, 3}, {3, 3}, /* ~=, >, >= */ {2, 2}, {1, 1} /* and, or */ }; #define UNARY_PRIORITY 8 /* priority for unary operators */ /* ** subexpr -> (simpleexp | unop subexpr) { binop subexpr } ** where `binop' is any binary operator with a priority higher than `limit' */ static BinOpr subexpr (LexState *ls, expdesc *v, int limit) { BinOpr op; UnOpr uop; enterlevel(ls); uop = getunopr(ls->t.token); if (uop != OPR_NOUNOPR) { int line = ls->linenumber; luaX_next(ls); subexpr(ls, v, UNARY_PRIORITY); luaK_prefix(ls->fs, uop, v, line); } else simpleexp(ls, v); /* expand while operators have priorities higher than `limit' */ op = getbinopr(ls->t.token); while (op != OPR_NOBINOPR && priority[op].left > limit) { expdesc v2; BinOpr nextop; int line = ls->linenumber; luaX_next(ls); luaK_infix(ls->fs, op, v); /* read sub-expression with higher priority */ nextop = subexpr(ls, &v2, priority[op].right); luaK_posfix(ls->fs, op, v, &v2, line); op = nextop; } leavelevel(ls); return op; /* return first untreated operator */ } static void expr (LexState *ls, expdesc *v) { subexpr(ls, v, 0); } /* }==================================================================== */ /* ** {====================================================================== ** Rules for Statements ** ======================================================================= */ static void block (LexState *ls) { /* block -> statlist */ FuncState *fs = ls->fs; BlockCnt bl; enterblock(fs, &bl, 0); statlist(ls); leaveblock(fs); } /* ** structure to chain all variables in the left-hand side of an ** assignment */ struct LHS_assign { struct LHS_assign *prev; expdesc v; /* variable (global, local, upvalue, or indexed) */ }; /* ** check whether, in an assignment to an upvalue/local variable, the ** upvalue/local variable is begin used in a previous assignment to a ** table. If so, save original upvalue/local value in a safe place and ** use this safe copy in the previous assignment. */ static void check_conflict (LexState *ls, struct LHS_assign *lh, expdesc *v) { FuncState *fs = ls->fs; int extra = fs->freereg; /* eventual position to save local variable */ int conflict = 0; for (; lh; lh = lh->prev) { /* check all previous assignments */ if (lh->v.k == VINDEXED) { /* assigning to a table? */ /* table is the upvalue/local being assigned now? */ if (lh->v.u.ind.vt == v->k && lh->v.u.ind.t == v->u.info) { conflict = 1; lh->v.u.ind.vt = VLOCAL; lh->v.u.ind.t = extra; /* previous assignment will use safe copy */ } /* index is the local being assigned? (index cannot be upvalue) */ if (v->k == VLOCAL && lh->v.u.ind.idx == v->u.info) { conflict = 1; lh->v.u.ind.idx = extra; /* previous assignment will use safe copy */ } } } if (conflict) { /* copy upvalue/local value to a temporary (in position 'extra') */ OpCode op = (v->k == VLOCAL) ? OP_MOVE : OP_GETUPVAL; luaK_codeABC(fs, op, extra, v->u.info, 0); luaK_reserveregs(fs, 1); } } static void assignment (LexState *ls, struct LHS_assign *lh, int nvars) { expdesc e; check_condition(ls, vkisvar(lh->v.k), "syntax error"); if (testnext(ls, ',')) { /* assignment -> ',' suffixedexp assignment */ struct LHS_assign nv; nv.prev = lh; suffixedexp(ls, &nv.v); if (nv.v.k != VINDEXED) check_conflict(ls, lh, &nv.v); checklimit(ls->fs, nvars + ls->L->nCcalls, LUAI_MAXCCALLS, "C levels"); assignment(ls, &nv, nvars+1); } else { /* assignment -> `=' explist */ int nexps; checknext(ls, '='); nexps = explist(ls, &e); if (nexps != nvars) { adjust_assign(ls, nvars, nexps, &e); if (nexps > nvars) ls->fs->freereg -= nexps - nvars; /* remove extra values */ } else { luaK_setoneret(ls->fs, &e); /* close last expression */ luaK_storevar(ls->fs, &lh->v, &e); return; /* avoid default */ } } init_exp(&e, VNONRELOC, ls->fs->freereg-1); /* default assignment */ luaK_storevar(ls->fs, &lh->v, &e); } static int cond (LexState *ls) { /* cond -> exp */ expdesc v; expr(ls, &v); /* read condition */ if (v.k == VNIL) v.k = VFALSE; /* `falses' are all equal here */ luaK_goiftrue(ls->fs, &v); return v.f; } static void gotostat (LexState *ls, int pc) { int line = ls->linenumber; TString *label; int g; if (testnext(ls, TK_GOTO)) label = str_checkname(ls); else { luaX_next(ls); /* skip break */ label = luaS_new(ls->L, "break"); } g = newlabelentry(ls, &ls->dyd->gt, label, line, pc); findlabel(ls, g); /* close it if label already defined */ } /* check for repeated labels on the same block */ static void checkrepeated (FuncState *fs, Labellist *ll, TString *label) { int i; for (i = fs->bl->firstlabel; i < ll->n; i++) { if (luaS_eqstr(label, ll->arr[i].name)) { const char *msg = luaO_pushfstring(fs->ls->L, "label " LUA_QS " already defined on line %d", getstr(label), ll->arr[i].line); semerror(fs->ls, msg); } } } /* skip no-op statements */ static void skipnoopstat (LexState *ls) { while (ls->t.token == ';' || ls->t.token == TK_DBCOLON) statement(ls); } static void labelstat (LexState *ls, TString *label, int line) { /* label -> '::' NAME '::' */ FuncState *fs = ls->fs; Labellist *ll = &ls->dyd->label; int l; /* index of new label being created */ checkrepeated(fs, ll, label); /* check for repeated labels */ checknext(ls, TK_DBCOLON); /* skip double colon */ /* create new entry for this label */ l = newlabelentry(ls, ll, label, line, fs->pc); skipnoopstat(ls); /* skip other no-op statements */ if (block_follow(ls, 0)) { /* label is last no-op statement in the block? */ /* assume that locals are already out of scope */ ll->arr[l].nactvar = fs->bl->nactvar; } findgotos(ls, &ll->arr[l]); } static void whilestat (LexState *ls, int line) { /* whilestat -> WHILE cond DO block END */ FuncState *fs = ls->fs; int whileinit; int condexit; BlockCnt bl; luaX_next(ls); /* skip WHILE */ whileinit = luaK_getlabel(fs); condexit = cond(ls); enterblock(fs, &bl, 1); checknext(ls, TK_DO); block(ls); luaK_jumpto(fs, whileinit); check_match(ls, TK_END, TK_WHILE, line); leaveblock(fs); luaK_patchtohere(fs, condexit); /* false conditions finish the loop */ } static void repeatstat (LexState *ls, int line) { /* repeatstat -> REPEAT block UNTIL cond */ int condexit; FuncState *fs = ls->fs; int repeat_init = luaK_getlabel(fs); BlockCnt bl1, bl2; enterblock(fs, &bl1, 1); /* loop block */ enterblock(fs, &bl2, 0); /* scope block */ luaX_next(ls); /* skip REPEAT */ statlist(ls); check_match(ls, TK_UNTIL, TK_REPEAT, line); condexit = cond(ls); /* read condition (inside scope block) */ if (bl2.upval) /* upvalues? */ luaK_patchclose(fs, condexit, bl2.nactvar); leaveblock(fs); /* finish scope */ luaK_patchlist(fs, condexit, repeat_init); /* close the loop */ leaveblock(fs); /* finish loop */ } static int exp1 (LexState *ls) { expdesc e; int reg; expr(ls, &e); luaK_exp2nextreg(ls->fs, &e); lua_assert(e.k == VNONRELOC); reg = e.u.info; return reg; } static void forbody (LexState *ls, int base, int line, int nvars, int isnum) { /* forbody -> DO block */ BlockCnt bl; FuncState *fs = ls->fs; int prep, endfor; adjustlocalvars(ls, 3); /* control variables */ checknext(ls, TK_DO); prep = isnum ? luaK_codeAsBx(fs, OP_FORPREP, base, NO_JUMP) : luaK_jump(fs); enterblock(fs, &bl, 0); /* scope for declared variables */ adjustlocalvars(ls, nvars); luaK_reserveregs(fs, nvars); block(ls); leaveblock(fs); /* end of scope for declared variables */ luaK_patchtohere(fs, prep); if (isnum) /* numeric for? */ endfor = luaK_codeAsBx(fs, OP_FORLOOP, base, NO_JUMP); else { /* generic for */ luaK_codeABC(fs, OP_TFORCALL, base, 0, nvars); luaK_fixline(fs, line); endfor = luaK_codeAsBx(fs, OP_TFORLOOP, base + 2, NO_JUMP); } luaK_patchlist(fs, endfor, prep + 1); luaK_fixline(fs, line); } static void fornum (LexState *ls, TString *varname, int line) { /* fornum -> NAME = exp1,exp1[,exp1] forbody */ FuncState *fs = ls->fs; int base = fs->freereg; new_localvarliteral(ls, "(for index)"); new_localvarliteral(ls, "(for limit)"); new_localvarliteral(ls, "(for step)"); new_localvar(ls, varname); checknext(ls, '='); exp1(ls); /* initial value */ checknext(ls, ','); exp1(ls); /* limit */ if (testnext(ls, ',')) exp1(ls); /* optional step */ else { /* default step = 1 */ luaK_codek(fs, fs->freereg, luaK_numberK(fs, 1)); luaK_reserveregs(fs, 1); } forbody(ls, base, line, 1, 1); } static void forlist (LexState *ls, TString *indexname) { /* forlist -> NAME {,NAME} IN explist forbody */ FuncState *fs = ls->fs; expdesc e; int nvars = 4; /* gen, state, control, plus at least one declared var */ int line; int base = fs->freereg; /* create control variables */ new_localvarliteral(ls, "(for generator)"); new_localvarliteral(ls, "(for state)"); new_localvarliteral(ls, "(for control)"); /* create declared variables */ new_localvar(ls, indexname); while (testnext(ls, ',')) { new_localvar(ls, str_checkname(ls)); nvars++; } checknext(ls, TK_IN); line = ls->linenumber; adjust_assign(ls, 3, explist(ls, &e), &e); luaK_checkstack(fs, 3); /* extra space to call generator */ forbody(ls, base, line, nvars - 3, 0); } static void forstat (LexState *ls, int line) { /* forstat -> FOR (fornum | forlist) END */ FuncState *fs = ls->fs; TString *varname; BlockCnt bl; enterblock(fs, &bl, 1); /* scope for loop and control variables */ luaX_next(ls); /* skip `for' */ varname = str_checkname(ls); /* first variable name */ switch (ls->t.token) { case '=': fornum(ls, varname, line); break; case ',': case TK_IN: forlist(ls, varname); break; default: luaX_syntaxerror(ls, LUA_QL("=") " or " LUA_QL("in") " expected"); } check_match(ls, TK_END, TK_FOR, line); leaveblock(fs); /* loop scope (`break' jumps to this point) */ } static void test_then_block (LexState *ls, int *escapelist) { /* test_then_block -> [IF | ELSEIF] cond THEN block */ BlockCnt bl; FuncState *fs = ls->fs; expdesc v; int jf; /* instruction to skip 'then' code (if condition is false) */ luaX_next(ls); /* skip IF or ELSEIF */ expr(ls, &v); /* read condition */ checknext(ls, TK_THEN); if (ls->t.token == TK_GOTO || ls->t.token == TK_BREAK) { luaK_goiffalse(ls->fs, &v); /* will jump to label if condition is true */ enterblock(fs, &bl, 0); /* must enter block before 'goto' */ gotostat(ls, v.t); /* handle goto/break */ skipnoopstat(ls); /* skip other no-op statements */ if (block_follow(ls, 0)) { /* 'goto' is the entire block? */ leaveblock(fs); return; /* and that is it */ } else /* must skip over 'then' part if condition is false */ jf = luaK_jump(fs); } else { /* regular case (not goto/break) */ luaK_goiftrue(ls->fs, &v); /* skip over block if condition is false */ enterblock(fs, &bl, 0); jf = v.f; } statlist(ls); /* `then' part */ leaveblock(fs); if (ls->t.token == TK_ELSE || ls->t.token == TK_ELSEIF) /* followed by 'else'/'elseif'? */ luaK_concat(fs, escapelist, luaK_jump(fs)); /* must jump over it */ luaK_patchtohere(fs, jf); } static void ifstat (LexState *ls, int line) { /* ifstat -> IF cond THEN block {ELSEIF cond THEN block} [ELSE block] END */ FuncState *fs = ls->fs; int escapelist = NO_JUMP; /* exit list for finished parts */ test_then_block(ls, &escapelist); /* IF cond THEN block */ while (ls->t.token == TK_ELSEIF) test_then_block(ls, &escapelist); /* ELSEIF cond THEN block */ if (testnext(ls, TK_ELSE)) block(ls); /* `else' part */ check_match(ls, TK_END, TK_IF, line); luaK_patchtohere(fs, escapelist); /* patch escape list to 'if' end */ } static void localfunc (LexState *ls) { expdesc b; FuncState *fs = ls->fs; new_localvar(ls, str_checkname(ls)); /* new local variable */ adjustlocalvars(ls, 1); /* enter its scope */ body(ls, &b, 0, ls->linenumber); /* function created in next register */ /* debug information will only see the variable after this point! */ getlocvar(fs, b.u.info)->startpc = fs->pc; } static void localstat (LexState *ls) { /* stat -> LOCAL NAME {`,' NAME} [`=' explist] */ int nvars = 0; int nexps; expdesc e; do { new_localvar(ls, str_checkname(ls)); nvars++; } while (testnext(ls, ',')); if (testnext(ls, '=')) nexps = explist(ls, &e); else { e.k = VVOID; nexps = 0; } adjust_assign(ls, nvars, nexps, &e); adjustlocalvars(ls, nvars); } static int funcname (LexState *ls, expdesc *v) { /* funcname -> NAME {fieldsel} [`:' NAME] */ int ismethod = 0; singlevar(ls, v); while (ls->t.token == '.') fieldsel(ls, v); if (ls->t.token == ':') { ismethod = 1; fieldsel(ls, v); } return ismethod; } static void funcstat (LexState *ls, int line) { /* funcstat -> FUNCTION funcname body */ int ismethod; expdesc v, b; luaX_next(ls); /* skip FUNCTION */ ismethod = funcname(ls, &v); body(ls, &b, ismethod, line); luaK_storevar(ls->fs, &v, &b); luaK_fixline(ls->fs, line); /* definition `happens' in the first line */ } static void exprstat (LexState *ls) { /* stat -> func | assignment */ FuncState *fs = ls->fs; struct LHS_assign v; suffixedexp(ls, &v.v); if (ls->t.token == '=' || ls->t.token == ',') { /* stat -> assignment ? */ v.prev = NULL; assignment(ls, &v, 1); } else { /* stat -> func */ check_condition(ls, v.v.k == VCALL, "syntax error"); SETARG_C(getcode(fs, &v.v), 1); /* call statement uses no results */ } } static void retstat (LexState *ls) { /* stat -> RETURN [explist] [';'] */ FuncState *fs = ls->fs; expdesc e; int first, nret; /* registers with returned values */ if (block_follow(ls, 1) || ls->t.token == ';') first = nret = 0; /* return no values */ else { nret = explist(ls, &e); /* optional return values */ if (hasmultret(e.k)) { luaK_setmultret(fs, &e); if (e.k == VCALL && nret == 1) { /* tail call? */ SET_OPCODE(getcode(fs,&e), OP_TAILCALL); lua_assert(GETARG_A(getcode(fs,&e)) == fs->nactvar); } first = fs->nactvar; nret = LUA_MULTRET; /* return all values */ } else { if (nret == 1) /* only one single value? */ first = luaK_exp2anyreg(fs, &e); else { luaK_exp2nextreg(fs, &e); /* values must go to the `stack' */ first = fs->nactvar; /* return all `active' values */ lua_assert(nret == fs->freereg - first); } } } luaK_ret(fs, first, nret); testnext(ls, ';'); /* skip optional semicolon */ } static void statement (LexState *ls) { int line = ls->linenumber; /* may be needed for error messages */ enterlevel(ls); switch (ls->t.token) { case ';': { /* stat -> ';' (empty statement) */ luaX_next(ls); /* skip ';' */ break; } case TK_IF: { /* stat -> ifstat */ ifstat(ls, line); break; } case TK_WHILE: { /* stat -> whilestat */ whilestat(ls, line); break; } case TK_DO: { /* stat -> DO block END */ luaX_next(ls); /* skip DO */ block(ls); check_match(ls, TK_END, TK_DO, line); break; } case TK_FOR: { /* stat -> forstat */ forstat(ls, line); break; } case TK_REPEAT: { /* stat -> repeatstat */ repeatstat(ls, line); break; } case TK_FUNCTION: { /* stat -> funcstat */ funcstat(ls, line); break; } case TK_LOCAL: { /* stat -> localstat */ luaX_next(ls); /* skip LOCAL */ if (testnext(ls, TK_FUNCTION)) /* local function? */ localfunc(ls); else localstat(ls); break; } case TK_DBCOLON: { /* stat -> label */ luaX_next(ls); /* skip double colon */ labelstat(ls, str_checkname(ls), line); break; } case TK_RETURN: { /* stat -> retstat */ luaX_next(ls); /* skip RETURN */ retstat(ls); break; } case TK_BREAK: /* stat -> breakstat */ case TK_GOTO: { /* stat -> 'goto' NAME */ gotostat(ls, luaK_jump(ls->fs)); break; } default: { /* stat -> func | assignment */ exprstat(ls); break; } } lua_assert(ls->fs->f->maxstacksize >= ls->fs->freereg && ls->fs->freereg >= ls->fs->nactvar); ls->fs->freereg = ls->fs->nactvar; /* free registers */ leavelevel(ls); } /* }====================================================================== */ /* ** compiles the main function, which is a regular vararg function with an ** upvalue named LUA_ENV */ static void mainfunc (LexState *ls, FuncState *fs) { BlockCnt bl; expdesc v; open_func(ls, fs, &bl); fs->f->is_vararg = 1; /* main function is always vararg */ init_exp(&v, VLOCAL, 0); /* create and... */ newupvalue(fs, ls->envn, &v); /* ...set environment upvalue */ luaX_next(ls); /* read first token */ statlist(ls); /* parse main body */ check(ls, TK_EOS); close_func(ls); } Closure *luaY_parser (lua_State *L, ZIO *z, Mbuffer *buff, Dyndata *dyd, const char *name, int firstchar) { LexState lexstate; FuncState funcstate; Closure *cl = luaF_newLclosure(L, 1); /* create main closure */ /* anchor closure (to avoid being collected) */ setclLvalue(L, L->top, cl); incr_top(L); funcstate.f = cl->l.p = luaF_newproto(L); funcstate.f->source = luaS_new(L, name); /* create and anchor TString */ lexstate.buff = buff; lexstate.dyd = dyd; dyd->actvar.n = dyd->gt.n = dyd->label.n = 0; luaX_setinput(L, &lexstate, z, funcstate.f->source, firstchar); mainfunc(&lexstate, &funcstate); lua_assert(!funcstate.prev && funcstate.nups == 1 && !lexstate.fs); /* all scopes should be correctly finished */ lua_assert(dyd->actvar.n == 0 && dyd->gt.n == 0 && dyd->label.n == 0); return cl; /* it's on the stack too */ } april-ann-0.4.1/lua/lua-5.2.2/src/lparser.h000066400000000000000000000064001263004425400200110ustar00rootroot00000000000000/* ** $Id: lparser.h,v 1.70 2012/05/08 13:53:33 roberto Exp $ ** Lua Parser ** See Copyright Notice in lua.h */ #ifndef lparser_h #define lparser_h #include "llimits.h" #include "lobject.h" #include "lzio.h" /* ** Expression descriptor */ typedef enum { VVOID, /* no value */ VNIL, VTRUE, VFALSE, VK, /* info = index of constant in `k' */ VKNUM, /* nval = numerical value */ VNONRELOC, /* info = result register */ VLOCAL, /* info = local register */ VUPVAL, /* info = index of upvalue in 'upvalues' */ VINDEXED, /* t = table register/upvalue; idx = index R/K */ VJMP, /* info = instruction pc */ VRELOCABLE, /* info = instruction pc */ VCALL, /* info = instruction pc */ VVARARG /* info = instruction pc */ } expkind; #define vkisvar(k) (VLOCAL <= (k) && (k) <= VINDEXED) #define vkisinreg(k) ((k) == VNONRELOC || (k) == VLOCAL) typedef struct expdesc { expkind k; union { struct { /* for indexed variables (VINDEXED) */ short idx; /* index (R/K) */ lu_byte t; /* table (register or upvalue) */ lu_byte vt; /* whether 't' is register (VLOCAL) or upvalue (VUPVAL) */ } ind; int info; /* for generic use */ lua_Number nval; /* for VKNUM */ } u; int t; /* patch list of `exit when true' */ int f; /* patch list of `exit when false' */ } expdesc; /* description of active local variable */ typedef struct Vardesc { short idx; /* variable index in stack */ } Vardesc; /* description of pending goto statements and label statements */ typedef struct Labeldesc { TString *name; /* label identifier */ int pc; /* position in code */ int line; /* line where it appeared */ lu_byte nactvar; /* local level where it appears in current block */ } Labeldesc; /* list of labels or gotos */ typedef struct Labellist { Labeldesc *arr; /* array */ int n; /* number of entries in use */ int size; /* array size */ } Labellist; /* dynamic structures used by the parser */ typedef struct Dyndata { struct { /* list of active local variables */ Vardesc *arr; int n; int size; } actvar; Labellist gt; /* list of pending gotos */ Labellist label; /* list of active labels */ } Dyndata; /* control of blocks */ struct BlockCnt; /* defined in lparser.c */ /* state needed to generate code for a given function */ typedef struct FuncState { Proto *f; /* current function header */ Table *h; /* table to find (and reuse) elements in `k' */ struct FuncState *prev; /* enclosing function */ struct LexState *ls; /* lexical state */ struct BlockCnt *bl; /* chain of current blocks */ int pc; /* next position to code (equivalent to `ncode') */ int lasttarget; /* 'label' of last 'jump label' */ int jpc; /* list of pending jumps to `pc' */ int nk; /* number of elements in `k' */ int np; /* number of elements in `p' */ int firstlocal; /* index of first local var (in Dyndata array) */ short nlocvars; /* number of elements in 'f->locvars' */ lu_byte nactvar; /* number of active local variables */ lu_byte nups; /* number of upvalues */ lu_byte freereg; /* first free register */ } FuncState; LUAI_FUNC Closure *luaY_parser (lua_State *L, ZIO *z, Mbuffer *buff, Dyndata *dyd, const char *name, int firstchar); #endif april-ann-0.4.1/lua/lua-5.2.2/src/lstate.c000066400000000000000000000167341263004425400176430ustar00rootroot00000000000000/* ** $Id: lstate.c,v 2.99 2012/10/02 17:40:53 roberto Exp $ ** Global State ** See Copyright Notice in lua.h */ #include #include #define lstate_c #define LUA_CORE #include "lua.h" #include "lapi.h" #include "ldebug.h" #include "ldo.h" #include "lfunc.h" #include "lgc.h" #include "llex.h" #include "lmem.h" #include "lstate.h" #include "lstring.h" #include "ltable.h" #include "ltm.h" #if !defined(LUAI_GCPAUSE) #define LUAI_GCPAUSE 200 /* 200% */ #endif #if !defined(LUAI_GCMAJOR) #define LUAI_GCMAJOR 200 /* 200% */ #endif #if !defined(LUAI_GCMUL) #define LUAI_GCMUL 200 /* GC runs 'twice the speed' of memory allocation */ #endif #define MEMERRMSG "not enough memory" /* ** a macro to help the creation of a unique random seed when a state is ** created; the seed is used to randomize hashes. */ #if !defined(luai_makeseed) #include #define luai_makeseed() cast(unsigned int, time(NULL)) #endif /* ** thread state + extra space */ typedef struct LX { #if defined(LUAI_EXTRASPACE) char buff[LUAI_EXTRASPACE]; #endif lua_State l; } LX; /* ** Main thread combines a thread state and the global state */ typedef struct LG { LX l; global_State g; } LG; #define fromstate(L) (cast(LX *, cast(lu_byte *, (L)) - offsetof(LX, l))) /* ** Compute an initial seed as random as possible. In ANSI, rely on ** Address Space Layout Randomization (if present) to increase ** randomness.. */ #define addbuff(b,p,e) \ { size_t t = cast(size_t, e); \ memcpy(buff + p, &t, sizeof(t)); p += sizeof(t); } static unsigned int makeseed (lua_State *L) { char buff[4 * sizeof(size_t)]; unsigned int h = luai_makeseed(); int p = 0; addbuff(buff, p, L); /* heap variable */ addbuff(buff, p, &h); /* local variable */ addbuff(buff, p, luaO_nilobject); /* global variable */ addbuff(buff, p, &lua_newstate); /* public function */ lua_assert(p == sizeof(buff)); return luaS_hash(buff, p, h); } /* ** set GCdebt to a new value keeping the value (totalbytes + GCdebt) ** invariant */ void luaE_setdebt (global_State *g, l_mem debt) { g->totalbytes -= (debt - g->GCdebt); g->GCdebt = debt; } CallInfo *luaE_extendCI (lua_State *L) { CallInfo *ci = luaM_new(L, CallInfo); lua_assert(L->ci->next == NULL); L->ci->next = ci; ci->previous = L->ci; ci->next = NULL; return ci; } void luaE_freeCI (lua_State *L) { CallInfo *ci = L->ci; CallInfo *next = ci->next; ci->next = NULL; while ((ci = next) != NULL) { next = ci->next; luaM_free(L, ci); } } static void stack_init (lua_State *L1, lua_State *L) { int i; CallInfo *ci; /* initialize stack array */ L1->stack = luaM_newvector(L, BASIC_STACK_SIZE, TValue); L1->stacksize = BASIC_STACK_SIZE; for (i = 0; i < BASIC_STACK_SIZE; i++) setnilvalue(L1->stack + i); /* erase new stack */ L1->top = L1->stack; L1->stack_last = L1->stack + L1->stacksize - EXTRA_STACK; /* initialize first ci */ ci = &L1->base_ci; ci->next = ci->previous = NULL; ci->callstatus = 0; ci->func = L1->top; setnilvalue(L1->top++); /* 'function' entry for this 'ci' */ ci->top = L1->top + LUA_MINSTACK; L1->ci = ci; } static void freestack (lua_State *L) { if (L->stack == NULL) return; /* stack not completely built yet */ L->ci = &L->base_ci; /* free the entire 'ci' list */ luaE_freeCI(L); luaM_freearray(L, L->stack, L->stacksize); /* free stack array */ } /* ** Create registry table and its predefined values */ static void init_registry (lua_State *L, global_State *g) { TValue mt; /* create registry */ Table *registry = luaH_new(L); sethvalue(L, &g->l_registry, registry); luaH_resize(L, registry, LUA_RIDX_LAST, 0); /* registry[LUA_RIDX_MAINTHREAD] = L */ setthvalue(L, &mt, L); luaH_setint(L, registry, LUA_RIDX_MAINTHREAD, &mt); /* registry[LUA_RIDX_GLOBALS] = table of globals */ sethvalue(L, &mt, luaH_new(L)); luaH_setint(L, registry, LUA_RIDX_GLOBALS, &mt); } /* ** open parts of the state that may cause memory-allocation errors */ static void f_luaopen (lua_State *L, void *ud) { global_State *g = G(L); UNUSED(ud); stack_init(L, L); /* init stack */ init_registry(L, g); luaS_resize(L, MINSTRTABSIZE); /* initial size of string table */ luaT_init(L); luaX_init(L); /* pre-create memory-error message */ g->memerrmsg = luaS_newliteral(L, MEMERRMSG); luaS_fix(g->memerrmsg); /* it should never be collected */ g->gcrunning = 1; /* allow gc */ } /* ** preinitialize a state with consistent values without allocating ** any memory (to avoid errors) */ static void preinit_state (lua_State *L, global_State *g) { G(L) = g; L->stack = NULL; L->ci = NULL; L->stacksize = 0; L->errorJmp = NULL; L->nCcalls = 0; L->hook = NULL; L->hookmask = 0; L->basehookcount = 0; L->allowhook = 1; resethookcount(L); L->openupval = NULL; L->nny = 1; L->status = LUA_OK; L->errfunc = 0; } static void close_state (lua_State *L) { global_State *g = G(L); luaF_close(L, L->stack); /* close all upvalues for this thread */ luaC_freeallobjects(L); /* collect all objects */ luaM_freearray(L, G(L)->strt.hash, G(L)->strt.size); luaZ_freebuffer(L, &g->buff); freestack(L); lua_assert(gettotalbytes(g) == sizeof(LG)); (*g->frealloc)(g->ud, fromstate(L), sizeof(LG), 0); /* free main block */ } LUA_API lua_State *lua_newthread (lua_State *L) { lua_State *L1; lua_lock(L); luaC_checkGC(L); L1 = &luaC_newobj(L, LUA_TTHREAD, sizeof(LX), NULL, offsetof(LX, l))->th; setthvalue(L, L->top, L1); api_incr_top(L); preinit_state(L1, G(L)); L1->hookmask = L->hookmask; L1->basehookcount = L->basehookcount; L1->hook = L->hook; resethookcount(L1); luai_userstatethread(L, L1); stack_init(L1, L); /* init stack */ lua_unlock(L); return L1; } void luaE_freethread (lua_State *L, lua_State *L1) { LX *l = fromstate(L1); luaF_close(L1, L1->stack); /* close all upvalues for this thread */ lua_assert(L1->openupval == NULL); luai_userstatefree(L, L1); freestack(L1); luaM_free(L, l); } LUA_API lua_State *lua_newstate (lua_Alloc f, void *ud) { int i; lua_State *L; global_State *g; LG *l = cast(LG *, (*f)(ud, NULL, LUA_TTHREAD, sizeof(LG))); if (l == NULL) return NULL; L = &l->l.l; g = &l->g; L->next = NULL; L->tt = LUA_TTHREAD; g->currentwhite = bit2mask(WHITE0BIT, FIXEDBIT); L->marked = luaC_white(g); g->gckind = KGC_NORMAL; preinit_state(L, g); g->frealloc = f; g->ud = ud; g->mainthread = L; g->seed = makeseed(L); g->uvhead.u.l.prev = &g->uvhead; g->uvhead.u.l.next = &g->uvhead; g->gcrunning = 0; /* no GC while building state */ g->GCestimate = 0; g->strt.size = 0; g->strt.nuse = 0; g->strt.hash = NULL; setnilvalue(&g->l_registry); luaZ_initbuffer(L, &g->buff); g->panic = NULL; g->version = lua_version(NULL); g->gcstate = GCSpause; g->allgc = NULL; g->finobj = NULL; g->tobefnz = NULL; g->sweepgc = g->sweepfin = NULL; g->gray = g->grayagain = NULL; g->weak = g->ephemeron = g->allweak = NULL; g->totalbytes = sizeof(LG); g->GCdebt = 0; g->gcpause = LUAI_GCPAUSE; g->gcmajorinc = LUAI_GCMAJOR; g->gcstepmul = LUAI_GCMUL; for (i=0; i < LUA_NUMTAGS; i++) g->mt[i] = NULL; if (luaD_rawrunprotected(L, f_luaopen, NULL) != LUA_OK) { /* memory allocation error: free partial state */ close_state(L); L = NULL; } else luai_userstateopen(L); return L; } LUA_API void lua_close (lua_State *L) { L = G(L)->mainthread; /* only the main thread can be closed */ lua_lock(L); luai_userstateclose(L); close_state(L); } april-ann-0.4.1/lua/lua-5.2.2/src/lstate.h000066400000000000000000000165631263004425400176500ustar00rootroot00000000000000/* ** $Id: lstate.h,v 2.82 2012/07/02 13:37:04 roberto Exp $ ** Global State ** See Copyright Notice in lua.h */ #ifndef lstate_h #define lstate_h #include "lua.h" #include "lobject.h" #include "ltm.h" #include "lzio.h" /* ** Some notes about garbage-collected objects: All objects in Lua must ** be kept somehow accessible until being freed. ** ** Lua keeps most objects linked in list g->allgc. The link uses field ** 'next' of the CommonHeader. ** ** Strings are kept in several lists headed by the array g->strt.hash. ** ** Open upvalues are not subject to independent garbage collection. They ** are collected together with their respective threads. Lua keeps a ** double-linked list with all open upvalues (g->uvhead) so that it can ** mark objects referred by them. (They are always gray, so they must ** be remarked in the atomic step. Usually their contents would be marked ** when traversing the respective threads, but the thread may already be ** dead, while the upvalue is still accessible through closures.) ** ** Objects with finalizers are kept in the list g->finobj. ** ** The list g->tobefnz links all objects being finalized. */ struct lua_longjmp; /* defined in ldo.c */ /* extra stack space to handle TM calls and some other extras */ #define EXTRA_STACK 5 #define BASIC_STACK_SIZE (2*LUA_MINSTACK) /* kinds of Garbage Collection */ #define KGC_NORMAL 0 #define KGC_EMERGENCY 1 /* gc was forced by an allocation failure */ #define KGC_GEN 2 /* generational collection */ typedef struct stringtable { GCObject **hash; lu_int32 nuse; /* number of elements */ int size; } stringtable; /* ** information about a call */ typedef struct CallInfo { StkId func; /* function index in the stack */ StkId top; /* top for this function */ struct CallInfo *previous, *next; /* dynamic call link */ short nresults; /* expected number of results from this function */ lu_byte callstatus; ptrdiff_t extra; union { struct { /* only for Lua functions */ StkId base; /* base for this function */ const Instruction *savedpc; } l; struct { /* only for C functions */ int ctx; /* context info. in case of yields */ lua_CFunction k; /* continuation in case of yields */ ptrdiff_t old_errfunc; lu_byte old_allowhook; lu_byte status; } c; } u; } CallInfo; /* ** Bits in CallInfo status */ #define CIST_LUA (1<<0) /* call is running a Lua function */ #define CIST_HOOKED (1<<1) /* call is running a debug hook */ #define CIST_REENTRY (1<<2) /* call is running on same invocation of luaV_execute of previous call */ #define CIST_YIELDED (1<<3) /* call reentered after suspension */ #define CIST_YPCALL (1<<4) /* call is a yieldable protected call */ #define CIST_STAT (1<<5) /* call has an error status (pcall) */ #define CIST_TAIL (1<<6) /* call was tail called */ #define CIST_HOOKYIELD (1<<7) /* last hook called yielded */ #define isLua(ci) ((ci)->callstatus & CIST_LUA) /* ** `global state', shared by all threads of this state */ typedef struct global_State { lua_Alloc frealloc; /* function to reallocate memory */ void *ud; /* auxiliary data to `frealloc' */ lu_mem totalbytes; /* number of bytes currently allocated - GCdebt */ l_mem GCdebt; /* bytes allocated not yet compensated by the collector */ lu_mem GCmemtrav; /* memory traversed by the GC */ lu_mem GCestimate; /* an estimate of the non-garbage memory in use */ stringtable strt; /* hash table for strings */ TValue l_registry; unsigned int seed; /* randomized seed for hashes */ lu_byte currentwhite; lu_byte gcstate; /* state of garbage collector */ lu_byte gckind; /* kind of GC running */ lu_byte gcrunning; /* true if GC is running */ int sweepstrgc; /* position of sweep in `strt' */ GCObject *allgc; /* list of all collectable objects */ GCObject *finobj; /* list of collectable objects with finalizers */ GCObject **sweepgc; /* current position of sweep in list 'allgc' */ GCObject **sweepfin; /* current position of sweep in list 'finobj' */ GCObject *gray; /* list of gray objects */ GCObject *grayagain; /* list of objects to be traversed atomically */ GCObject *weak; /* list of tables with weak values */ GCObject *ephemeron; /* list of ephemeron tables (weak keys) */ GCObject *allweak; /* list of all-weak tables */ GCObject *tobefnz; /* list of userdata to be GC */ UpVal uvhead; /* head of double-linked list of all open upvalues */ Mbuffer buff; /* temporary buffer for string concatenation */ int gcpause; /* size of pause between successive GCs */ int gcmajorinc; /* pause between major collections (only in gen. mode) */ int gcstepmul; /* GC `granularity' */ lua_CFunction panic; /* to be called in unprotected errors */ struct lua_State *mainthread; const lua_Number *version; /* pointer to version number */ TString *memerrmsg; /* memory-error message */ TString *tmname[TM_N]; /* array with tag-method names */ struct Table *mt[LUA_NUMTAGS]; /* metatables for basic types */ } global_State; /* ** `per thread' state */ struct lua_State { CommonHeader; lu_byte status; StkId top; /* first free slot in the stack */ global_State *l_G; CallInfo *ci; /* call info for current function */ const Instruction *oldpc; /* last pc traced */ StkId stack_last; /* last free slot in the stack */ StkId stack; /* stack base */ int stacksize; unsigned short nny; /* number of non-yieldable calls in stack */ unsigned short nCcalls; /* number of nested C calls */ lu_byte hookmask; lu_byte allowhook; int basehookcount; int hookcount; lua_Hook hook; GCObject *openupval; /* list of open upvalues in this stack */ GCObject *gclist; struct lua_longjmp *errorJmp; /* current error recover point */ ptrdiff_t errfunc; /* current error handling function (stack index) */ CallInfo base_ci; /* CallInfo for first level (C calling Lua) */ }; #define G(L) (L->l_G) /* ** Union of all collectable objects */ union GCObject { GCheader gch; /* common header */ union TString ts; union Udata u; union Closure cl; struct Table h; struct Proto p; struct UpVal uv; struct lua_State th; /* thread */ }; #define gch(o) (&(o)->gch) /* macros to convert a GCObject into a specific value */ #define rawgco2ts(o) \ check_exp(novariant((o)->gch.tt) == LUA_TSTRING, &((o)->ts)) #define gco2ts(o) (&rawgco2ts(o)->tsv) #define rawgco2u(o) check_exp((o)->gch.tt == LUA_TUSERDATA, &((o)->u)) #define gco2u(o) (&rawgco2u(o)->uv) #define gco2lcl(o) check_exp((o)->gch.tt == LUA_TLCL, &((o)->cl.l)) #define gco2ccl(o) check_exp((o)->gch.tt == LUA_TCCL, &((o)->cl.c)) #define gco2cl(o) \ check_exp(novariant((o)->gch.tt) == LUA_TFUNCTION, &((o)->cl)) #define gco2t(o) check_exp((o)->gch.tt == LUA_TTABLE, &((o)->h)) #define gco2p(o) check_exp((o)->gch.tt == LUA_TPROTO, &((o)->p)) #define gco2uv(o) check_exp((o)->gch.tt == LUA_TUPVAL, &((o)->uv)) #define gco2th(o) check_exp((o)->gch.tt == LUA_TTHREAD, &((o)->th)) /* macro to convert any Lua object into a GCObject */ #define obj2gco(v) (cast(GCObject *, (v))) /* actual number of total bytes allocated */ #define gettotalbytes(g) ((g)->totalbytes + (g)->GCdebt) LUAI_FUNC void luaE_setdebt (global_State *g, l_mem debt); LUAI_FUNC void luaE_freethread (lua_State *L, lua_State *L1); LUAI_FUNC CallInfo *luaE_extendCI (lua_State *L); LUAI_FUNC void luaE_freeCI (lua_State *L); #endif april-ann-0.4.1/lua/lua-5.2.2/src/lstring.c000066400000000000000000000114441263004425400200220ustar00rootroot00000000000000/* ** $Id: lstring.c,v 2.26 2013/01/08 13:50:10 roberto Exp $ ** String table (keeps all strings handled by Lua) ** See Copyright Notice in lua.h */ #include #define lstring_c #define LUA_CORE #include "lua.h" #include "lmem.h" #include "lobject.h" #include "lstate.h" #include "lstring.h" /* ** Lua will use at most ~(2^LUAI_HASHLIMIT) bytes from a string to ** compute its hash */ #if !defined(LUAI_HASHLIMIT) #define LUAI_HASHLIMIT 5 #endif /* ** equality for long strings */ int luaS_eqlngstr (TString *a, TString *b) { size_t len = a->tsv.len; lua_assert(a->tsv.tt == LUA_TLNGSTR && b->tsv.tt == LUA_TLNGSTR); return (a == b) || /* same instance or... */ ((len == b->tsv.len) && /* equal length and ... */ (memcmp(getstr(a), getstr(b), len) == 0)); /* equal contents */ } /* ** equality for strings */ int luaS_eqstr (TString *a, TString *b) { return (a->tsv.tt == b->tsv.tt) && (a->tsv.tt == LUA_TSHRSTR ? eqshrstr(a, b) : luaS_eqlngstr(a, b)); } unsigned int luaS_hash (const char *str, size_t l, unsigned int seed) { unsigned int h = seed ^ cast(unsigned int, l); size_t l1; size_t step = (l >> LUAI_HASHLIMIT) + 1; for (l1 = l; l1 >= step; l1 -= step) h = h ^ ((h<<5) + (h>>2) + cast_byte(str[l1 - 1])); return h; } /* ** resizes the string table */ void luaS_resize (lua_State *L, int newsize) { int i; stringtable *tb = &G(L)->strt; /* cannot resize while GC is traversing strings */ luaC_runtilstate(L, ~bitmask(GCSsweepstring)); if (newsize > tb->size) { luaM_reallocvector(L, tb->hash, tb->size, newsize, GCObject *); for (i = tb->size; i < newsize; i++) tb->hash[i] = NULL; } /* rehash */ for (i=0; isize; i++) { GCObject *p = tb->hash[i]; tb->hash[i] = NULL; while (p) { /* for each node in the list */ GCObject *next = gch(p)->next; /* save next */ unsigned int h = lmod(gco2ts(p)->hash, newsize); /* new position */ gch(p)->next = tb->hash[h]; /* chain it */ tb->hash[h] = p; resetoldbit(p); /* see MOVE OLD rule */ p = next; } } if (newsize < tb->size) { /* shrinking slice must be empty */ lua_assert(tb->hash[newsize] == NULL && tb->hash[tb->size - 1] == NULL); luaM_reallocvector(L, tb->hash, tb->size, newsize, GCObject *); } tb->size = newsize; } /* ** creates a new string object */ static TString *createstrobj (lua_State *L, const char *str, size_t l, int tag, unsigned int h, GCObject **list) { TString *ts; size_t totalsize; /* total size of TString object */ totalsize = sizeof(TString) + ((l + 1) * sizeof(char)); ts = &luaC_newobj(L, tag, totalsize, list, 0)->ts; ts->tsv.len = l; ts->tsv.hash = h; ts->tsv.extra = 0; memcpy(ts+1, str, l*sizeof(char)); ((char *)(ts+1))[l] = '\0'; /* ending 0 */ return ts; } /* ** creates a new short string, inserting it into string table */ static TString *newshrstr (lua_State *L, const char *str, size_t l, unsigned int h) { GCObject **list; /* (pointer to) list where it will be inserted */ stringtable *tb = &G(L)->strt; TString *s; if (tb->nuse >= cast(lu_int32, tb->size) && tb->size <= MAX_INT/2) luaS_resize(L, tb->size*2); /* too crowded */ list = &tb->hash[lmod(h, tb->size)]; s = createstrobj(L, str, l, LUA_TSHRSTR, h, list); tb->nuse++; return s; } /* ** checks whether short string exists and reuses it or creates a new one */ static TString *internshrstr (lua_State *L, const char *str, size_t l) { GCObject *o; global_State *g = G(L); unsigned int h = luaS_hash(str, l, g->seed); for (o = g->strt.hash[lmod(h, g->strt.size)]; o != NULL; o = gch(o)->next) { TString *ts = rawgco2ts(o); if (h == ts->tsv.hash && l == ts->tsv.len && (memcmp(str, getstr(ts), l * sizeof(char)) == 0)) { if (isdead(G(L), o)) /* string is dead (but was not collected yet)? */ changewhite(o); /* resurrect it */ return ts; } } return newshrstr(L, str, l, h); /* not found; create a new string */ } /* ** new string (with explicit length) */ TString *luaS_newlstr (lua_State *L, const char *str, size_t l) { if (l <= LUAI_MAXSHORTLEN) /* short string? */ return internshrstr(L, str, l); else { if (l + 1 > (MAX_SIZET - sizeof(TString))/sizeof(char)) luaM_toobig(L); return createstrobj(L, str, l, LUA_TLNGSTR, G(L)->seed, NULL); } } /* ** new zero-terminated string */ TString *luaS_new (lua_State *L, const char *str) { return luaS_newlstr(L, str, strlen(str)); } Udata *luaS_newudata (lua_State *L, size_t s, Table *e) { Udata *u; if (s > MAX_SIZET - sizeof(Udata)) luaM_toobig(L); u = &luaC_newobj(L, LUA_TUSERDATA, sizeof(Udata) + s, NULL, 0)->u; u->uv.len = s; u->uv.metatable = NULL; u->uv.env = e; return u; } april-ann-0.4.1/lua/lua-5.2.2/src/lstring.h000066400000000000000000000023641263004425400200300ustar00rootroot00000000000000/* ** $Id: lstring.h,v 1.49 2012/02/01 21:57:15 roberto Exp $ ** String table (keep all strings handled by Lua) ** See Copyright Notice in lua.h */ #ifndef lstring_h #define lstring_h #include "lgc.h" #include "lobject.h" #include "lstate.h" #define sizestring(s) (sizeof(union TString)+((s)->len+1)*sizeof(char)) #define sizeudata(u) (sizeof(union Udata)+(u)->len) #define luaS_newliteral(L, s) (luaS_newlstr(L, "" s, \ (sizeof(s)/sizeof(char))-1)) #define luaS_fix(s) l_setbit((s)->tsv.marked, FIXEDBIT) /* ** test whether a string is a reserved word */ #define isreserved(s) ((s)->tsv.tt == LUA_TSHRSTR && (s)->tsv.extra > 0) /* ** equality for short strings, which are always internalized */ #define eqshrstr(a,b) check_exp((a)->tsv.tt == LUA_TSHRSTR, (a) == (b)) LUAI_FUNC unsigned int luaS_hash (const char *str, size_t l, unsigned int seed); LUAI_FUNC int luaS_eqlngstr (TString *a, TString *b); LUAI_FUNC int luaS_eqstr (TString *a, TString *b); LUAI_FUNC void luaS_resize (lua_State *L, int newsize); LUAI_FUNC Udata *luaS_newudata (lua_State *L, size_t s, Table *e); LUAI_FUNC TString *luaS_newlstr (lua_State *L, const char *str, size_t l); LUAI_FUNC TString *luaS_new (lua_State *L, const char *str); #endif april-ann-0.4.1/lua/lua-5.2.2/src/lstrlib.c000066400000000000000000000672771263004425400200320ustar00rootroot00000000000000/* ** $Id: lstrlib.c,v 1.178 2012/08/14 18:12:34 roberto Exp $ ** Standard library for string operations and pattern-matching ** See Copyright Notice in lua.h */ #include #include #include #include #include #define lstrlib_c #define LUA_LIB #include "lua.h" #include "lauxlib.h" #include "lualib.h" /* ** maximum number of captures that a pattern can do during ** pattern-matching. This limit is arbitrary. */ #if !defined(LUA_MAXCAPTURES) #define LUA_MAXCAPTURES 32 #endif /* macro to `unsign' a character */ #define uchar(c) ((unsigned char)(c)) static int str_len (lua_State *L) { size_t l; luaL_checklstring(L, 1, &l); lua_pushinteger(L, (lua_Integer)l); return 1; } /* translate a relative string position: negative means back from end */ static size_t posrelat (ptrdiff_t pos, size_t len) { if (pos >= 0) return (size_t)pos; else if (0u - (size_t)pos > len) return 0; else return len - ((size_t)-pos) + 1; } static int str_sub (lua_State *L) { size_t l; const char *s = luaL_checklstring(L, 1, &l); size_t start = posrelat(luaL_checkinteger(L, 2), l); size_t end = posrelat(luaL_optinteger(L, 3, -1), l); if (start < 1) start = 1; if (end > l) end = l; if (start <= end) lua_pushlstring(L, s + start - 1, end - start + 1); else lua_pushliteral(L, ""); return 1; } static int str_reverse (lua_State *L) { size_t l, i; luaL_Buffer b; const char *s = luaL_checklstring(L, 1, &l); char *p = luaL_buffinitsize(L, &b, l); for (i = 0; i < l; i++) p[i] = s[l - i - 1]; luaL_pushresultsize(&b, l); return 1; } static int str_lower (lua_State *L) { size_t l; size_t i; luaL_Buffer b; const char *s = luaL_checklstring(L, 1, &l); char *p = luaL_buffinitsize(L, &b, l); for (i=0; i> 1) static int str_rep (lua_State *L) { size_t l, lsep; const char *s = luaL_checklstring(L, 1, &l); int n = luaL_checkint(L, 2); const char *sep = luaL_optlstring(L, 3, "", &lsep); if (n <= 0) lua_pushliteral(L, ""); else if (l + lsep < l || l + lsep >= MAXSIZE / n) /* may overflow? */ return luaL_error(L, "resulting string too large"); else { size_t totallen = n * l + (n - 1) * lsep; luaL_Buffer b; char *p = luaL_buffinitsize(L, &b, totallen); while (n-- > 1) { /* first n-1 copies (followed by separator) */ memcpy(p, s, l * sizeof(char)); p += l; if (lsep > 0) { /* avoid empty 'memcpy' (may be expensive) */ memcpy(p, sep, lsep * sizeof(char)); p += lsep; } } memcpy(p, s, l * sizeof(char)); /* last copy (not followed by separator) */ luaL_pushresultsize(&b, totallen); } return 1; } static int str_byte (lua_State *L) { size_t l; const char *s = luaL_checklstring(L, 1, &l); size_t posi = posrelat(luaL_optinteger(L, 2, 1), l); size_t pose = posrelat(luaL_optinteger(L, 3, posi), l); int n, i; if (posi < 1) posi = 1; if (pose > l) pose = l; if (posi > pose) return 0; /* empty interval; return no values */ n = (int)(pose - posi + 1); if (posi + n <= pose) /* (size_t -> int) overflow? */ return luaL_error(L, "string slice too long"); luaL_checkstack(L, n, "string slice too long"); for (i=0; i= ms->level || ms->capture[l].len == CAP_UNFINISHED) return luaL_error(ms->L, "invalid capture index %%%d", l + 1); return l; } static int capture_to_close (MatchState *ms) { int level = ms->level; for (level--; level>=0; level--) if (ms->capture[level].len == CAP_UNFINISHED) return level; return luaL_error(ms->L, "invalid pattern capture"); } static const char *classend (MatchState *ms, const char *p) { switch (*p++) { case L_ESC: { if (p == ms->p_end) luaL_error(ms->L, "malformed pattern (ends with " LUA_QL("%%") ")"); return p+1; } case '[': { if (*p == '^') p++; do { /* look for a `]' */ if (p == ms->p_end) luaL_error(ms->L, "malformed pattern (missing " LUA_QL("]") ")"); if (*(p++) == L_ESC && p < ms->p_end) p++; /* skip escapes (e.g. `%]') */ } while (*p != ']'); return p+1; } default: { return p; } } } static int match_class (int c, int cl) { int res; switch (tolower(cl)) { case 'a' : res = isalpha(c); break; case 'c' : res = iscntrl(c); break; case 'd' : res = isdigit(c); break; case 'g' : res = isgraph(c); break; case 'l' : res = islower(c); break; case 'p' : res = ispunct(c); break; case 's' : res = isspace(c); break; case 'u' : res = isupper(c); break; case 'w' : res = isalnum(c); break; case 'x' : res = isxdigit(c); break; case 'z' : res = (c == 0); break; /* deprecated option */ default: return (cl == c); } return (islower(cl) ? res : !res); } static int matchbracketclass (int c, const char *p, const char *ec) { int sig = 1; if (*(p+1) == '^') { sig = 0; p++; /* skip the `^' */ } while (++p < ec) { if (*p == L_ESC) { p++; if (match_class(c, uchar(*p))) return sig; } else if ((*(p+1) == '-') && (p+2 < ec)) { p+=2; if (uchar(*(p-2)) <= c && c <= uchar(*p)) return sig; } else if (uchar(*p) == c) return sig; } return !sig; } static int singlematch (MatchState *ms, const char *s, const char *p, const char *ep) { if (s >= ms->src_end) return 0; else { int c = uchar(*s); switch (*p) { case '.': return 1; /* matches any char */ case L_ESC: return match_class(c, uchar(*(p+1))); case '[': return matchbracketclass(c, p, ep-1); default: return (uchar(*p) == c); } } } static const char *matchbalance (MatchState *ms, const char *s, const char *p) { if (p >= ms->p_end - 1) luaL_error(ms->L, "malformed pattern " "(missing arguments to " LUA_QL("%%b") ")"); if (*s != *p) return NULL; else { int b = *p; int e = *(p+1); int cont = 1; while (++s < ms->src_end) { if (*s == e) { if (--cont == 0) return s+1; } else if (*s == b) cont++; } } return NULL; /* string ends out of balance */ } static const char *max_expand (MatchState *ms, const char *s, const char *p, const char *ep) { ptrdiff_t i = 0; /* counts maximum expand for item */ while (singlematch(ms, s + i, p, ep)) i++; /* keeps trying to match with the maximum repetitions */ while (i>=0) { const char *res = match(ms, (s+i), ep+1); if (res) return res; i--; /* else didn't match; reduce 1 repetition to try again */ } return NULL; } static const char *min_expand (MatchState *ms, const char *s, const char *p, const char *ep) { for (;;) { const char *res = match(ms, s, ep+1); if (res != NULL) return res; else if (singlematch(ms, s, p, ep)) s++; /* try with one more repetition */ else return NULL; } } static const char *start_capture (MatchState *ms, const char *s, const char *p, int what) { const char *res; int level = ms->level; if (level >= LUA_MAXCAPTURES) luaL_error(ms->L, "too many captures"); ms->capture[level].init = s; ms->capture[level].len = what; ms->level = level+1; if ((res=match(ms, s, p)) == NULL) /* match failed? */ ms->level--; /* undo capture */ return res; } static const char *end_capture (MatchState *ms, const char *s, const char *p) { int l = capture_to_close(ms); const char *res; ms->capture[l].len = s - ms->capture[l].init; /* close capture */ if ((res = match(ms, s, p)) == NULL) /* match failed? */ ms->capture[l].len = CAP_UNFINISHED; /* undo capture */ return res; } static const char *match_capture (MatchState *ms, const char *s, int l) { size_t len; l = check_capture(ms, l); len = ms->capture[l].len; if ((size_t)(ms->src_end-s) >= len && memcmp(ms->capture[l].init, s, len) == 0) return s+len; else return NULL; } static const char *match (MatchState *ms, const char *s, const char *p) { if (ms->matchdepth-- == 0) luaL_error(ms->L, "pattern too complex"); init: /* using goto's to optimize tail recursion */ if (p != ms->p_end) { /* end of pattern? */ switch (*p) { case '(': { /* start capture */ if (*(p + 1) == ')') /* position capture? */ s = start_capture(ms, s, p + 2, CAP_POSITION); else s = start_capture(ms, s, p + 1, CAP_UNFINISHED); break; } case ')': { /* end capture */ s = end_capture(ms, s, p + 1); break; } case '$': { if ((p + 1) != ms->p_end) /* is the `$' the last char in pattern? */ goto dflt; /* no; go to default */ s = (s == ms->src_end) ? s : NULL; /* check end of string */ break; } case L_ESC: { /* escaped sequences not in the format class[*+?-]? */ switch (*(p + 1)) { case 'b': { /* balanced string? */ s = matchbalance(ms, s, p + 2); if (s != NULL) { p += 4; goto init; /* return match(ms, s, p + 4); */ } /* else fail (s == NULL) */ break; } case 'f': { /* frontier? */ const char *ep; char previous; p += 2; if (*p != '[') luaL_error(ms->L, "missing " LUA_QL("[") " after " LUA_QL("%%f") " in pattern"); ep = classend(ms, p); /* points to what is next */ previous = (s == ms->src_init) ? '\0' : *(s - 1); if (!matchbracketclass(uchar(previous), p, ep - 1) && matchbracketclass(uchar(*s), p, ep - 1)) { p = ep; goto init; /* return match(ms, s, ep); */ } s = NULL; /* match failed */ break; } case '0': case '1': case '2': case '3': case '4': case '5': case '6': case '7': case '8': case '9': { /* capture results (%0-%9)? */ s = match_capture(ms, s, uchar(*(p + 1))); if (s != NULL) { p += 2; goto init; /* return match(ms, s, p + 2) */ } break; } default: goto dflt; } break; } default: dflt: { /* pattern class plus optional suffix */ const char *ep = classend(ms, p); /* points to optional suffix */ /* does not match at least once? */ if (!singlematch(ms, s, p, ep)) { if (*ep == '*' || *ep == '?' || *ep == '-') { /* accept empty? */ p = ep + 1; goto init; /* return match(ms, s, ep + 1); */ } else /* '+' or no suffix */ s = NULL; /* fail */ } else { /* matched once */ switch (*ep) { /* handle optional suffix */ case '?': { /* optional */ const char *res; if ((res = match(ms, s + 1, ep + 1)) != NULL) s = res; else { p = ep + 1; goto init; /* else return match(ms, s, ep + 1); */ } break; } case '+': /* 1 or more repetitions */ s++; /* 1 match already done */ /* go through */ case '*': /* 0 or more repetitions */ s = max_expand(ms, s, p, ep); break; case '-': /* 0 or more repetitions (minimum) */ s = min_expand(ms, s, p, ep); break; default: /* no suffix */ s++; p = ep; goto init; /* return match(ms, s + 1, ep); */ } } break; } } } ms->matchdepth++; return s; } static const char *lmemfind (const char *s1, size_t l1, const char *s2, size_t l2) { if (l2 == 0) return s1; /* empty strings are everywhere */ else if (l2 > l1) return NULL; /* avoids a negative `l1' */ else { const char *init; /* to search for a `*s2' inside `s1' */ l2--; /* 1st char will be checked by `memchr' */ l1 = l1-l2; /* `s2' cannot be found after that */ while (l1 > 0 && (init = (const char *)memchr(s1, *s2, l1)) != NULL) { init++; /* 1st char is already checked */ if (memcmp(init, s2+1, l2) == 0) return init-1; else { /* correct `l1' and `s1' to try again */ l1 -= init-s1; s1 = init; } } return NULL; /* not found */ } } static void push_onecapture (MatchState *ms, int i, const char *s, const char *e) { if (i >= ms->level) { if (i == 0) /* ms->level == 0, too */ lua_pushlstring(ms->L, s, e - s); /* add whole match */ else luaL_error(ms->L, "invalid capture index"); } else { ptrdiff_t l = ms->capture[i].len; if (l == CAP_UNFINISHED) luaL_error(ms->L, "unfinished capture"); if (l == CAP_POSITION) lua_pushinteger(ms->L, ms->capture[i].init - ms->src_init + 1); else lua_pushlstring(ms->L, ms->capture[i].init, l); } } static int push_captures (MatchState *ms, const char *s, const char *e) { int i; int nlevels = (ms->level == 0 && s) ? 1 : ms->level; luaL_checkstack(ms->L, nlevels, "too many captures"); for (i = 0; i < nlevels; i++) push_onecapture(ms, i, s, e); return nlevels; /* number of strings pushed */ } /* check whether pattern has no special characters */ static int nospecials (const char *p, size_t l) { size_t upto = 0; do { if (strpbrk(p + upto, SPECIALS)) return 0; /* pattern has a special character */ upto += strlen(p + upto) + 1; /* may have more after \0 */ } while (upto <= l); return 1; /* no special chars found */ } static int str_find_aux (lua_State *L, int find) { size_t ls, lp; const char *s = luaL_checklstring(L, 1, &ls); const char *p = luaL_checklstring(L, 2, &lp); size_t init = posrelat(luaL_optinteger(L, 3, 1), ls); if (init < 1) init = 1; else if (init > ls + 1) { /* start after string's end? */ lua_pushnil(L); /* cannot find anything */ return 1; } /* explicit request or no special characters? */ if (find && (lua_toboolean(L, 4) || nospecials(p, lp))) { /* do a plain search */ const char *s2 = lmemfind(s + init - 1, ls - init + 1, p, lp); if (s2) { lua_pushinteger(L, s2 - s + 1); lua_pushinteger(L, s2 - s + lp); return 2; } } else { MatchState ms; const char *s1 = s + init - 1; int anchor = (*p == '^'); if (anchor) { p++; lp--; /* skip anchor character */ } ms.L = L; ms.matchdepth = MAXCCALLS; ms.src_init = s; ms.src_end = s + ls; ms.p_end = p + lp; do { const char *res; ms.level = 0; lua_assert(ms.matchdepth == MAXCCALLS); if ((res=match(&ms, s1, p)) != NULL) { if (find) { lua_pushinteger(L, s1 - s + 1); /* start */ lua_pushinteger(L, res - s); /* end */ return push_captures(&ms, NULL, 0) + 2; } else return push_captures(&ms, s1, res); } } while (s1++ < ms.src_end && !anchor); } lua_pushnil(L); /* not found */ return 1; } static int str_find (lua_State *L) { return str_find_aux(L, 1); } static int str_match (lua_State *L) { return str_find_aux(L, 0); } static int gmatch_aux (lua_State *L) { MatchState ms; size_t ls, lp; const char *s = lua_tolstring(L, lua_upvalueindex(1), &ls); const char *p = lua_tolstring(L, lua_upvalueindex(2), &lp); const char *src; ms.L = L; ms.matchdepth = MAXCCALLS; ms.src_init = s; ms.src_end = s+ls; ms.p_end = p + lp; for (src = s + (size_t)lua_tointeger(L, lua_upvalueindex(3)); src <= ms.src_end; src++) { const char *e; ms.level = 0; lua_assert(ms.matchdepth == MAXCCALLS); if ((e = match(&ms, src, p)) != NULL) { lua_Integer newstart = e-s; if (e == src) newstart++; /* empty match? go at least one position */ lua_pushinteger(L, newstart); lua_replace(L, lua_upvalueindex(3)); return push_captures(&ms, src, e); } } return 0; /* not found */ } static int gmatch (lua_State *L) { luaL_checkstring(L, 1); luaL_checkstring(L, 2); lua_settop(L, 2); lua_pushinteger(L, 0); lua_pushcclosure(L, gmatch_aux, 3); return 1; } static void add_s (MatchState *ms, luaL_Buffer *b, const char *s, const char *e) { size_t l, i; const char *news = lua_tolstring(ms->L, 3, &l); for (i = 0; i < l; i++) { if (news[i] != L_ESC) luaL_addchar(b, news[i]); else { i++; /* skip ESC */ if (!isdigit(uchar(news[i]))) { if (news[i] != L_ESC) luaL_error(ms->L, "invalid use of " LUA_QL("%c") " in replacement string", L_ESC); luaL_addchar(b, news[i]); } else if (news[i] == '0') luaL_addlstring(b, s, e - s); else { push_onecapture(ms, news[i] - '1', s, e); luaL_addvalue(b); /* add capture to accumulated result */ } } } } static void add_value (MatchState *ms, luaL_Buffer *b, const char *s, const char *e, int tr) { lua_State *L = ms->L; switch (tr) { case LUA_TFUNCTION: { int n; lua_pushvalue(L, 3); n = push_captures(ms, s, e); lua_call(L, n, 1); break; } case LUA_TTABLE: { push_onecapture(ms, 0, s, e); lua_gettable(L, 3); break; } default: { /* LUA_TNUMBER or LUA_TSTRING */ add_s(ms, b, s, e); return; } } if (!lua_toboolean(L, -1)) { /* nil or false? */ lua_pop(L, 1); lua_pushlstring(L, s, e - s); /* keep original text */ } else if (!lua_isstring(L, -1)) luaL_error(L, "invalid replacement value (a %s)", luaL_typename(L, -1)); luaL_addvalue(b); /* add result to accumulator */ } static int str_gsub (lua_State *L) { size_t srcl, lp; const char *src = luaL_checklstring(L, 1, &srcl); const char *p = luaL_checklstring(L, 2, &lp); int tr = lua_type(L, 3); size_t max_s = luaL_optinteger(L, 4, srcl+1); int anchor = (*p == '^'); size_t n = 0; MatchState ms; luaL_Buffer b; luaL_argcheck(L, tr == LUA_TNUMBER || tr == LUA_TSTRING || tr == LUA_TFUNCTION || tr == LUA_TTABLE, 3, "string/function/table expected"); luaL_buffinit(L, &b); if (anchor) { p++; lp--; /* skip anchor character */ } ms.L = L; ms.matchdepth = MAXCCALLS; ms.src_init = src; ms.src_end = src+srcl; ms.p_end = p + lp; while (n < max_s) { const char *e; ms.level = 0; lua_assert(ms.matchdepth == MAXCCALLS); e = match(&ms, src, p); if (e) { n++; add_value(&ms, &b, src, e, tr); } if (e && e>src) /* non empty match? */ src = e; /* skip it */ else if (src < ms.src_end) luaL_addchar(&b, *src++); else break; if (anchor) break; } luaL_addlstring(&b, src, ms.src_end-src); luaL_pushresult(&b); lua_pushinteger(L, n); /* number of substitutions */ return 2; } /* }====================================================== */ /* ** {====================================================== ** STRING FORMAT ** ======================================================= */ /* ** LUA_INTFRMLEN is the length modifier for integer conversions in ** 'string.format'; LUA_INTFRM_T is the integer type corresponding to ** the previous length */ #if !defined(LUA_INTFRMLEN) /* { */ #if defined(LUA_USE_LONGLONG) #define LUA_INTFRMLEN "ll" #define LUA_INTFRM_T long long #else #define LUA_INTFRMLEN "l" #define LUA_INTFRM_T long #endif #endif /* } */ /* ** LUA_FLTFRMLEN is the length modifier for float conversions in ** 'string.format'; LUA_FLTFRM_T is the float type corresponding to ** the previous length */ #if !defined(LUA_FLTFRMLEN) #define LUA_FLTFRMLEN "" #define LUA_FLTFRM_T double #endif /* maximum size of each formatted item (> len(format('%99.99f', -1e308))) */ #define MAX_ITEM 512 /* valid flags in a format specification */ #define FLAGS "-+ #0" /* ** maximum size of each format specification (such as '%-099.99d') ** (+10 accounts for %99.99x plus margin of error) */ #define MAX_FORMAT (sizeof(FLAGS) + sizeof(LUA_INTFRMLEN) + 10) static void addquoted (lua_State *L, luaL_Buffer *b, int arg) { size_t l; const char *s = luaL_checklstring(L, arg, &l); luaL_addchar(b, '"'); while (l--) { if (*s == '"' || *s == '\\' || *s == '\n') { luaL_addchar(b, '\\'); luaL_addchar(b, *s); } else if (*s == '\0' || iscntrl(uchar(*s))) { char buff[10]; if (!isdigit(uchar(*(s+1)))) sprintf(buff, "\\%d", (int)uchar(*s)); else sprintf(buff, "\\%03d", (int)uchar(*s)); luaL_addstring(b, buff); } else luaL_addchar(b, *s); s++; } luaL_addchar(b, '"'); } static const char *scanformat (lua_State *L, const char *strfrmt, char *form) { const char *p = strfrmt; while (*p != '\0' && strchr(FLAGS, *p) != NULL) p++; /* skip flags */ if ((size_t)(p - strfrmt) >= sizeof(FLAGS)/sizeof(char)) luaL_error(L, "invalid format (repeated flags)"); if (isdigit(uchar(*p))) p++; /* skip width */ if (isdigit(uchar(*p))) p++; /* (2 digits at most) */ if (*p == '.') { p++; if (isdigit(uchar(*p))) p++; /* skip precision */ if (isdigit(uchar(*p))) p++; /* (2 digits at most) */ } if (isdigit(uchar(*p))) luaL_error(L, "invalid format (width or precision too long)"); *(form++) = '%'; memcpy(form, strfrmt, (p - strfrmt + 1) * sizeof(char)); form += p - strfrmt + 1; *form = '\0'; return p; } /* ** add length modifier into formats */ static void addlenmod (char *form, const char *lenmod) { size_t l = strlen(form); size_t lm = strlen(lenmod); char spec = form[l - 1]; strcpy(form + l - 1, lenmod); form[l + lm - 1] = spec; form[l + lm] = '\0'; } static int str_format (lua_State *L) { int top = lua_gettop(L); int arg = 1; size_t sfl; const char *strfrmt = luaL_checklstring(L, arg, &sfl); const char *strfrmt_end = strfrmt+sfl; luaL_Buffer b; luaL_buffinit(L, &b); while (strfrmt < strfrmt_end) { if (*strfrmt != L_ESC) luaL_addchar(&b, *strfrmt++); else if (*++strfrmt == L_ESC) luaL_addchar(&b, *strfrmt++); /* %% */ else { /* format item */ char form[MAX_FORMAT]; /* to store the format (`%...') */ char *buff = luaL_prepbuffsize(&b, MAX_ITEM); /* to put formatted item */ int nb = 0; /* number of bytes in added item */ if (++arg > top) luaL_argerror(L, arg, "no value"); strfrmt = scanformat(L, strfrmt, form); switch (*strfrmt++) { case 'c': { nb = sprintf(buff, form, luaL_checkint(L, arg)); break; } case 'd': case 'i': { lua_Number n = luaL_checknumber(L, arg); LUA_INTFRM_T ni = (LUA_INTFRM_T)n; lua_Number diff = n - (lua_Number)ni; luaL_argcheck(L, -1 < diff && diff < 1, arg, "not a number in proper range"); addlenmod(form, LUA_INTFRMLEN); nb = sprintf(buff, form, ni); break; } case 'o': case 'u': case 'x': case 'X': { lua_Number n = luaL_checknumber(L, arg); unsigned LUA_INTFRM_T ni = (unsigned LUA_INTFRM_T)n; lua_Number diff = n - (lua_Number)ni; luaL_argcheck(L, -1 < diff && diff < 1, arg, "not a non-negative number in proper range"); addlenmod(form, LUA_INTFRMLEN); nb = sprintf(buff, form, ni); break; } case 'e': case 'E': case 'f': #if defined(LUA_USE_AFORMAT) case 'a': case 'A': #endif case 'g': case 'G': { addlenmod(form, LUA_FLTFRMLEN); nb = sprintf(buff, form, (LUA_FLTFRM_T)luaL_checknumber(L, arg)); break; } case 'q': { addquoted(L, &b, arg); break; } case 's': { size_t l; const char *s = luaL_tolstring(L, arg, &l); if (!strchr(form, '.') && l >= 100) { /* no precision and string is too long to be formatted; keep original string */ luaL_addvalue(&b); break; } else { nb = sprintf(buff, form, s); lua_pop(L, 1); /* remove result from 'luaL_tolstring' */ break; } } default: { /* also treat cases `pnLlh' */ return luaL_error(L, "invalid option " LUA_QL("%%%c") " to " LUA_QL("format"), *(strfrmt - 1)); } } luaL_addsize(&b, nb); } } luaL_pushresult(&b); return 1; } /* }====================================================== */ static const luaL_Reg strlib[] = { {"byte", str_byte}, {"char", str_char}, {"dump", str_dump}, {"find", str_find}, {"format", str_format}, {"gmatch", gmatch}, {"gsub", str_gsub}, {"len", str_len}, {"lower", str_lower}, {"match", str_match}, {"rep", str_rep}, {"reverse", str_reverse}, {"sub", str_sub}, {"upper", str_upper}, {NULL, NULL} }; static void createmetatable (lua_State *L) { lua_createtable(L, 0, 1); /* table to be metatable for strings */ lua_pushliteral(L, ""); /* dummy string */ lua_pushvalue(L, -2); /* copy table */ lua_setmetatable(L, -2); /* set table as metatable for strings */ lua_pop(L, 1); /* pop dummy string */ lua_pushvalue(L, -2); /* get string library */ lua_setfield(L, -2, "__index"); /* metatable.__index = string */ lua_pop(L, 1); /* pop metatable */ } /* ** Open string library */ LUAMOD_API int luaopen_string (lua_State *L) { luaL_newlib(L, strlib); createmetatable(L); return 1; } april-ann-0.4.1/lua/lua-5.2.2/src/ltable.c000066400000000000000000000401361263004425400176030ustar00rootroot00000000000000/* ** $Id: ltable.c,v 2.72 2012/09/11 19:37:16 roberto Exp $ ** Lua tables (hash) ** See Copyright Notice in lua.h */ /* ** Implementation of tables (aka arrays, objects, or hash tables). ** Tables keep its elements in two parts: an array part and a hash part. ** Non-negative integer keys are all candidates to be kept in the array ** part. The actual size of the array is the largest `n' such that at ** least half the slots between 0 and n are in use. ** Hash uses a mix of chained scatter table with Brent's variation. ** A main invariant of these tables is that, if an element is not ** in its main position (i.e. the `original' position that its hash gives ** to it), then the colliding element is in its own main position. ** Hence even when the load factor reaches 100%, performance remains good. */ #include #define ltable_c #define LUA_CORE #include "lua.h" #include "ldebug.h" #include "ldo.h" #include "lgc.h" #include "lmem.h" #include "lobject.h" #include "lstate.h" #include "lstring.h" #include "ltable.h" #include "lvm.h" /* ** max size of array part is 2^MAXBITS */ #if LUAI_BITSINT >= 32 #define MAXBITS 30 #else #define MAXBITS (LUAI_BITSINT-2) #endif #define MAXASIZE (1 << MAXBITS) #define hashpow2(t,n) (gnode(t, lmod((n), sizenode(t)))) #define hashstr(t,str) hashpow2(t, (str)->tsv.hash) #define hashboolean(t,p) hashpow2(t, p) /* ** for some types, it is better to avoid modulus by power of 2, as ** they tend to have many 2 factors. */ #define hashmod(t,n) (gnode(t, ((n) % ((sizenode(t)-1)|1)))) #define hashpointer(t,p) hashmod(t, IntPoint(p)) #define dummynode (&dummynode_) #define isdummy(n) ((n) == dummynode) static const Node dummynode_ = { {NILCONSTANT}, /* value */ {{NILCONSTANT, NULL}} /* key */ }; /* ** hash for lua_Numbers */ static Node *hashnum (const Table *t, lua_Number n) { int i; luai_hashnum(i, n); if (i < 0) { if (cast(unsigned int, i) == 0u - i) /* use unsigned to avoid overflows */ i = 0; /* handle INT_MIN */ i = -i; /* must be a positive value */ } return hashmod(t, i); } /* ** returns the `main' position of an element in a table (that is, the index ** of its hash value) */ static Node *mainposition (const Table *t, const TValue *key) { switch (ttype(key)) { case LUA_TNUMBER: return hashnum(t, nvalue(key)); case LUA_TLNGSTR: { TString *s = rawtsvalue(key); if (s->tsv.extra == 0) { /* no hash? */ s->tsv.hash = luaS_hash(getstr(s), s->tsv.len, s->tsv.hash); s->tsv.extra = 1; /* now it has its hash */ } return hashstr(t, rawtsvalue(key)); } case LUA_TSHRSTR: return hashstr(t, rawtsvalue(key)); case LUA_TBOOLEAN: return hashboolean(t, bvalue(key)); case LUA_TLIGHTUSERDATA: return hashpointer(t, pvalue(key)); case LUA_TLCF: return hashpointer(t, fvalue(key)); default: return hashpointer(t, gcvalue(key)); } } /* ** returns the index for `key' if `key' is an appropriate key to live in ** the array part of the table, -1 otherwise. */ static int arrayindex (const TValue *key) { if (ttisnumber(key)) { lua_Number n = nvalue(key); int k; lua_number2int(k, n); if (luai_numeq(cast_num(k), n)) return k; } return -1; /* `key' did not match some condition */ } /* ** returns the index of a `key' for table traversals. First goes all ** elements in the array part, then elements in the hash part. The ** beginning of a traversal is signaled by -1. */ static int findindex (lua_State *L, Table *t, StkId key) { int i; if (ttisnil(key)) return -1; /* first iteration */ i = arrayindex(key); if (0 < i && i <= t->sizearray) /* is `key' inside array part? */ return i-1; /* yes; that's the index (corrected to C) */ else { Node *n = mainposition(t, key); for (;;) { /* check whether `key' is somewhere in the chain */ /* key may be dead already, but it is ok to use it in `next' */ if (luaV_rawequalobj(gkey(n), key) || (ttisdeadkey(gkey(n)) && iscollectable(key) && deadvalue(gkey(n)) == gcvalue(key))) { i = cast_int(n - gnode(t, 0)); /* key index in hash table */ /* hash elements are numbered after array ones */ return i + t->sizearray; } else n = gnext(n); if (n == NULL) luaG_runerror(L, "invalid key to " LUA_QL("next")); /* key not found */ } } } int luaH_next (lua_State *L, Table *t, StkId key) { int i = findindex(L, t, key); /* find original element */ for (i++; i < t->sizearray; i++) { /* try first array part */ if (!ttisnil(&t->array[i])) { /* a non-nil value? */ setnvalue(key, cast_num(i+1)); setobj2s(L, key+1, &t->array[i]); return 1; } } for (i -= t->sizearray; i < sizenode(t); i++) { /* then hash part */ if (!ttisnil(gval(gnode(t, i)))) { /* a non-nil value? */ setobj2s(L, key, gkey(gnode(t, i))); setobj2s(L, key+1, gval(gnode(t, i))); return 1; } } return 0; /* no more elements */ } /* ** {============================================================= ** Rehash ** ============================================================== */ static int computesizes (int nums[], int *narray) { int i; int twotoi; /* 2^i */ int a = 0; /* number of elements smaller than 2^i */ int na = 0; /* number of elements to go to array part */ int n = 0; /* optimal size for array part */ for (i = 0, twotoi = 1; twotoi/2 < *narray; i++, twotoi *= 2) { if (nums[i] > 0) { a += nums[i]; if (a > twotoi/2) { /* more than half elements present? */ n = twotoi; /* optimal size (till now) */ na = a; /* all elements smaller than n will go to array part */ } } if (a == *narray) break; /* all elements already counted */ } *narray = n; lua_assert(*narray/2 <= na && na <= *narray); return na; } static int countint (const TValue *key, int *nums) { int k = arrayindex(key); if (0 < k && k <= MAXASIZE) { /* is `key' an appropriate array index? */ nums[luaO_ceillog2(k)]++; /* count as such */ return 1; } else return 0; } static int numusearray (const Table *t, int *nums) { int lg; int ttlg; /* 2^lg */ int ause = 0; /* summation of `nums' */ int i = 1; /* count to traverse all array keys */ for (lg=0, ttlg=1; lg<=MAXBITS; lg++, ttlg*=2) { /* for each slice */ int lc = 0; /* counter */ int lim = ttlg; if (lim > t->sizearray) { lim = t->sizearray; /* adjust upper limit */ if (i > lim) break; /* no more elements to count */ } /* count elements in range (2^(lg-1), 2^lg] */ for (; i <= lim; i++) { if (!ttisnil(&t->array[i-1])) lc++; } nums[lg] += lc; ause += lc; } return ause; } static int numusehash (const Table *t, int *nums, int *pnasize) { int totaluse = 0; /* total number of elements */ int ause = 0; /* summation of `nums' */ int i = sizenode(t); while (i--) { Node *n = &t->node[i]; if (!ttisnil(gval(n))) { ause += countint(gkey(n), nums); totaluse++; } } *pnasize += ause; return totaluse; } static void setarrayvector (lua_State *L, Table *t, int size) { int i; luaM_reallocvector(L, t->array, t->sizearray, size, TValue); for (i=t->sizearray; iarray[i]); t->sizearray = size; } static void setnodevector (lua_State *L, Table *t, int size) { int lsize; if (size == 0) { /* no elements to hash part? */ t->node = cast(Node *, dummynode); /* use common `dummynode' */ lsize = 0; } else { int i; lsize = luaO_ceillog2(size); if (lsize > MAXBITS) luaG_runerror(L, "table overflow"); size = twoto(lsize); t->node = luaM_newvector(L, size, Node); for (i=0; ilsizenode = cast_byte(lsize); t->lastfree = gnode(t, size); /* all positions are free */ } void luaH_resize (lua_State *L, Table *t, int nasize, int nhsize) { int i; int oldasize = t->sizearray; int oldhsize = t->lsizenode; Node *nold = t->node; /* save old hash ... */ if (nasize > oldasize) /* array part must grow? */ setarrayvector(L, t, nasize); /* create new hash part with appropriate size */ setnodevector(L, t, nhsize); if (nasize < oldasize) { /* array part must shrink? */ t->sizearray = nasize; /* re-insert elements from vanishing slice */ for (i=nasize; iarray[i])) luaH_setint(L, t, i + 1, &t->array[i]); } /* shrink array */ luaM_reallocvector(L, t->array, oldasize, nasize, TValue); } /* re-insert elements from hash part */ for (i = twoto(oldhsize) - 1; i >= 0; i--) { Node *old = nold+i; if (!ttisnil(gval(old))) { /* doesn't need barrier/invalidate cache, as entry was already present in the table */ setobjt2t(L, luaH_set(L, t, gkey(old)), gval(old)); } } if (!isdummy(nold)) luaM_freearray(L, nold, cast(size_t, twoto(oldhsize))); /* free old array */ } void luaH_resizearray (lua_State *L, Table *t, int nasize) { int nsize = isdummy(t->node) ? 0 : sizenode(t); luaH_resize(L, t, nasize, nsize); } static void rehash (lua_State *L, Table *t, const TValue *ek) { int nasize, na; int nums[MAXBITS+1]; /* nums[i] = number of keys with 2^(i-1) < k <= 2^i */ int i; int totaluse; for (i=0; i<=MAXBITS; i++) nums[i] = 0; /* reset counts */ nasize = numusearray(t, nums); /* count keys in array part */ totaluse = nasize; /* all those keys are integer keys */ totaluse += numusehash(t, nums, &nasize); /* count keys in hash part */ /* count extra key */ nasize += countint(ek, nums); totaluse++; /* compute new size for array part */ na = computesizes(nums, &nasize); /* resize the table to new computed sizes */ luaH_resize(L, t, nasize, totaluse - na); } /* ** }============================================================= */ Table *luaH_new (lua_State *L) { Table *t = &luaC_newobj(L, LUA_TTABLE, sizeof(Table), NULL, 0)->h; t->metatable = NULL; t->flags = cast_byte(~0); t->array = NULL; t->sizearray = 0; setnodevector(L, t, 0); return t; } void luaH_free (lua_State *L, Table *t) { if (!isdummy(t->node)) luaM_freearray(L, t->node, cast(size_t, sizenode(t))); luaM_freearray(L, t->array, t->sizearray); luaM_free(L, t); } static Node *getfreepos (Table *t) { while (t->lastfree > t->node) { t->lastfree--; if (ttisnil(gkey(t->lastfree))) return t->lastfree; } return NULL; /* could not find a free place */ } /* ** inserts a new key into a hash table; first, check whether key's main ** position is free. If not, check whether colliding node is in its main ** position or not: if it is not, move colliding node to an empty place and ** put new key in its main position; otherwise (colliding node is in its main ** position), new key goes to an empty position. */ TValue *luaH_newkey (lua_State *L, Table *t, const TValue *key) { Node *mp; if (ttisnil(key)) luaG_runerror(L, "table index is nil"); else if (ttisnumber(key) && luai_numisnan(L, nvalue(key))) luaG_runerror(L, "table index is NaN"); mp = mainposition(t, key); if (!ttisnil(gval(mp)) || isdummy(mp)) { /* main position is taken? */ Node *othern; Node *n = getfreepos(t); /* get a free place */ if (n == NULL) { /* cannot find a free place? */ rehash(L, t, key); /* grow table */ /* whatever called 'newkey' take care of TM cache and GC barrier */ return luaH_set(L, t, key); /* insert key into grown table */ } lua_assert(!isdummy(n)); othern = mainposition(t, gkey(mp)); if (othern != mp) { /* is colliding node out of its main position? */ /* yes; move colliding node into free position */ while (gnext(othern) != mp) othern = gnext(othern); /* find previous */ gnext(othern) = n; /* redo the chain with `n' in place of `mp' */ *n = *mp; /* copy colliding node into free pos. (mp->next also goes) */ gnext(mp) = NULL; /* now `mp' is free */ setnilvalue(gval(mp)); } else { /* colliding node is in its own main position */ /* new node will go into free position */ gnext(n) = gnext(mp); /* chain new position */ gnext(mp) = n; mp = n; } } setobj2t(L, gkey(mp), key); luaC_barrierback(L, obj2gco(t), key); lua_assert(ttisnil(gval(mp))); return gval(mp); } /* ** search function for integers */ const TValue *luaH_getint (Table *t, int key) { /* (1 <= key && key <= t->sizearray) */ if (cast(unsigned int, key-1) < cast(unsigned int, t->sizearray)) return &t->array[key-1]; else { lua_Number nk = cast_num(key); Node *n = hashnum(t, nk); do { /* check whether `key' is somewhere in the chain */ if (ttisnumber(gkey(n)) && luai_numeq(nvalue(gkey(n)), nk)) return gval(n); /* that's it */ else n = gnext(n); } while (n); return luaO_nilobject; } } /* ** search function for short strings */ const TValue *luaH_getstr (Table *t, TString *key) { Node *n = hashstr(t, key); lua_assert(key->tsv.tt == LUA_TSHRSTR); do { /* check whether `key' is somewhere in the chain */ if (ttisshrstring(gkey(n)) && eqshrstr(rawtsvalue(gkey(n)), key)) return gval(n); /* that's it */ else n = gnext(n); } while (n); return luaO_nilobject; } /* ** main search function */ const TValue *luaH_get (Table *t, const TValue *key) { switch (ttype(key)) { case LUA_TSHRSTR: return luaH_getstr(t, rawtsvalue(key)); case LUA_TNIL: return luaO_nilobject; case LUA_TNUMBER: { int k; lua_Number n = nvalue(key); lua_number2int(k, n); if (luai_numeq(cast_num(k), n)) /* index is int? */ return luaH_getint(t, k); /* use specialized version */ /* else go through */ } default: { Node *n = mainposition(t, key); do { /* check whether `key' is somewhere in the chain */ if (luaV_rawequalobj(gkey(n), key)) return gval(n); /* that's it */ else n = gnext(n); } while (n); return luaO_nilobject; } } } /* ** beware: when using this function you probably need to check a GC ** barrier and invalidate the TM cache. */ TValue *luaH_set (lua_State *L, Table *t, const TValue *key) { const TValue *p = luaH_get(t, key); if (p != luaO_nilobject) return cast(TValue *, p); else return luaH_newkey(L, t, key); } void luaH_setint (lua_State *L, Table *t, int key, TValue *value) { const TValue *p = luaH_getint(t, key); TValue *cell; if (p != luaO_nilobject) cell = cast(TValue *, p); else { TValue k; setnvalue(&k, cast_num(key)); cell = luaH_newkey(L, t, &k); } setobj2t(L, cell, value); } static int unbound_search (Table *t, unsigned int j) { unsigned int i = j; /* i is zero or a present index */ j++; /* find `i' and `j' such that i is present and j is not */ while (!ttisnil(luaH_getint(t, j))) { i = j; j *= 2; if (j > cast(unsigned int, MAX_INT)) { /* overflow? */ /* table was built with bad purposes: resort to linear search */ i = 1; while (!ttisnil(luaH_getint(t, i))) i++; return i - 1; } } /* now do a binary search between them */ while (j - i > 1) { unsigned int m = (i+j)/2; if (ttisnil(luaH_getint(t, m))) j = m; else i = m; } return i; } /* ** Try to find a boundary in table `t'. A `boundary' is an integer index ** such that t[i] is non-nil and t[i+1] is nil (and 0 if t[1] is nil). */ int luaH_getn (Table *t) { unsigned int j = t->sizearray; if (j > 0 && ttisnil(&t->array[j - 1])) { /* there is a boundary in the array part: (binary) search for it */ unsigned int i = 0; while (j - i > 1) { unsigned int m = (i+j)/2; if (ttisnil(&t->array[m - 1])) j = m; else i = m; } return i; } /* else must find a boundary in hash part */ else if (isdummy(t->node)) /* hash part is empty? */ return j; /* that is easy... */ else return unbound_search(t, j); } #if defined(LUA_DEBUG) Node *luaH_mainposition (const Table *t, const TValue *key) { return mainposition(t, key); } int luaH_isdummy (Node *n) { return isdummy(n); } #endif april-ann-0.4.1/lua/lua-5.2.2/src/ltable.h000066400000000000000000000023531263004425400176070ustar00rootroot00000000000000/* ** $Id: ltable.h,v 2.16 2011/08/17 20:26:47 roberto Exp $ ** Lua tables (hash) ** See Copyright Notice in lua.h */ #ifndef ltable_h #define ltable_h #include "lobject.h" #define gnode(t,i) (&(t)->node[i]) #define gkey(n) (&(n)->i_key.tvk) #define gval(n) (&(n)->i_val) #define gnext(n) ((n)->i_key.nk.next) #define invalidateTMcache(t) ((t)->flags = 0) LUAI_FUNC const TValue *luaH_getint (Table *t, int key); LUAI_FUNC void luaH_setint (lua_State *L, Table *t, int key, TValue *value); LUAI_FUNC const TValue *luaH_getstr (Table *t, TString *key); LUAI_FUNC const TValue *luaH_get (Table *t, const TValue *key); LUAI_FUNC TValue *luaH_newkey (lua_State *L, Table *t, const TValue *key); LUAI_FUNC TValue *luaH_set (lua_State *L, Table *t, const TValue *key); LUAI_FUNC Table *luaH_new (lua_State *L); LUAI_FUNC void luaH_resize (lua_State *L, Table *t, int nasize, int nhsize); LUAI_FUNC void luaH_resizearray (lua_State *L, Table *t, int nasize); LUAI_FUNC void luaH_free (lua_State *L, Table *t); LUAI_FUNC int luaH_next (lua_State *L, Table *t, StkId key); LUAI_FUNC int luaH_getn (Table *t); #if defined(LUA_DEBUG) LUAI_FUNC Node *luaH_mainposition (const Table *t, const TValue *key); LUAI_FUNC int luaH_isdummy (Node *n); #endif #endif april-ann-0.4.1/lua/lua-5.2.2/src/ltablib.c000066400000000000000000000167711263004425400177610ustar00rootroot00000000000000/* ** $Id: ltablib.c,v 1.65 2013/03/07 18:17:24 roberto Exp $ ** Library for Table Manipulation ** See Copyright Notice in lua.h */ #include #define ltablib_c #define LUA_LIB #include "lua.h" #include "lauxlib.h" #include "lualib.h" #define aux_getn(L,n) (luaL_checktype(L, n, LUA_TTABLE), luaL_len(L, n)) #if defined(LUA_COMPAT_MAXN) static int maxn (lua_State *L) { lua_Number max = 0; luaL_checktype(L, 1, LUA_TTABLE); lua_pushnil(L); /* first key */ while (lua_next(L, 1)) { lua_pop(L, 1); /* remove value */ if (lua_type(L, -1) == LUA_TNUMBER) { lua_Number v = lua_tonumber(L, -1); if (v > max) max = v; } } lua_pushnumber(L, max); return 1; } #endif static int tinsert (lua_State *L) { int e = aux_getn(L, 1) + 1; /* first empty element */ int pos; /* where to insert new element */ switch (lua_gettop(L)) { case 2: { /* called with only 2 arguments */ pos = e; /* insert new element at the end */ break; } case 3: { int i; pos = luaL_checkint(L, 2); /* 2nd argument is the position */ luaL_argcheck(L, 1 <= pos && pos <= e, 2, "position out of bounds"); for (i = e; i > pos; i--) { /* move up elements */ lua_rawgeti(L, 1, i-1); lua_rawseti(L, 1, i); /* t[i] = t[i-1] */ } break; } default: { return luaL_error(L, "wrong number of arguments to " LUA_QL("insert")); } } lua_rawseti(L, 1, pos); /* t[pos] = v */ return 0; } static int tremove (lua_State *L) { int size = aux_getn(L, 1); int pos = luaL_optint(L, 2, size); if (pos != size) /* validate 'pos' if given */ luaL_argcheck(L, 1 <= pos && pos <= size + 1, 1, "position out of bounds"); lua_rawgeti(L, 1, pos); /* result = t[pos] */ for ( ; pos < size; pos++) { lua_rawgeti(L, 1, pos+1); lua_rawseti(L, 1, pos); /* t[pos] = t[pos+1] */ } lua_pushnil(L); lua_rawseti(L, 1, pos); /* t[pos] = nil */ return 1; } static void addfield (lua_State *L, luaL_Buffer *b, int i) { lua_rawgeti(L, 1, i); if (!lua_isstring(L, -1)) luaL_error(L, "invalid value (%s) at index %d in table for " LUA_QL("concat"), luaL_typename(L, -1), i); luaL_addvalue(b); } static int tconcat (lua_State *L) { luaL_Buffer b; size_t lsep; int i, last; const char *sep = luaL_optlstring(L, 2, "", &lsep); luaL_checktype(L, 1, LUA_TTABLE); i = luaL_optint(L, 3, 1); last = luaL_opt(L, luaL_checkint, 4, luaL_len(L, 1)); luaL_buffinit(L, &b); for (; i < last; i++) { addfield(L, &b, i); luaL_addlstring(&b, sep, lsep); } if (i == last) /* add last value (if interval was not empty) */ addfield(L, &b, i); luaL_pushresult(&b); return 1; } /* ** {====================================================== ** Pack/unpack ** ======================================================= */ static int pack (lua_State *L) { int n = lua_gettop(L); /* number of elements to pack */ lua_createtable(L, n, 1); /* create result table */ lua_pushinteger(L, n); lua_setfield(L, -2, "n"); /* t.n = number of elements */ if (n > 0) { /* at least one element? */ int i; lua_pushvalue(L, 1); lua_rawseti(L, -2, 1); /* insert first element */ lua_replace(L, 1); /* move table into index 1 */ for (i = n; i >= 2; i--) /* assign other elements */ lua_rawseti(L, 1, i); } return 1; /* return table */ } static int unpack (lua_State *L) { int i, e, n; luaL_checktype(L, 1, LUA_TTABLE); i = luaL_optint(L, 2, 1); e = luaL_opt(L, luaL_checkint, 3, luaL_len(L, 1)); if (i > e) return 0; /* empty range */ n = e - i + 1; /* number of elements */ if (n <= 0 || !lua_checkstack(L, n)) /* n <= 0 means arith. overflow */ return luaL_error(L, "too many results to unpack"); lua_rawgeti(L, 1, i); /* push arg[i] (avoiding overflow problems) */ while (i++ < e) /* push arg[i + 1...e] */ lua_rawgeti(L, 1, i); return n; } /* }====================================================== */ /* ** {====================================================== ** Quicksort ** (based on `Algorithms in MODULA-3', Robert Sedgewick; ** Addison-Wesley, 1993.) ** ======================================================= */ static void set2 (lua_State *L, int i, int j) { lua_rawseti(L, 1, i); lua_rawseti(L, 1, j); } static int sort_comp (lua_State *L, int a, int b) { if (!lua_isnil(L, 2)) { /* function? */ int res; lua_pushvalue(L, 2); lua_pushvalue(L, a-1); /* -1 to compensate function */ lua_pushvalue(L, b-2); /* -2 to compensate function and `a' */ lua_call(L, 2, 1); res = lua_toboolean(L, -1); lua_pop(L, 1); return res; } else /* a < b? */ return lua_compare(L, a, b, LUA_OPLT); } static void auxsort (lua_State *L, int l, int u) { while (l < u) { /* for tail recursion */ int i, j; /* sort elements a[l], a[(l+u)/2] and a[u] */ lua_rawgeti(L, 1, l); lua_rawgeti(L, 1, u); if (sort_comp(L, -1, -2)) /* a[u] < a[l]? */ set2(L, l, u); /* swap a[l] - a[u] */ else lua_pop(L, 2); if (u-l == 1) break; /* only 2 elements */ i = (l+u)/2; lua_rawgeti(L, 1, i); lua_rawgeti(L, 1, l); if (sort_comp(L, -2, -1)) /* a[i]= P */ while (lua_rawgeti(L, 1, ++i), sort_comp(L, -1, -2)) { if (i>=u) luaL_error(L, "invalid order function for sorting"); lua_pop(L, 1); /* remove a[i] */ } /* repeat --j until a[j] <= P */ while (lua_rawgeti(L, 1, --j), sort_comp(L, -3, -1)) { if (j<=l) luaL_error(L, "invalid order function for sorting"); lua_pop(L, 1); /* remove a[j] */ } if (j #define ltm_c #define LUA_CORE #include "lua.h" #include "lobject.h" #include "lstate.h" #include "lstring.h" #include "ltable.h" #include "ltm.h" static const char udatatypename[] = "userdata"; LUAI_DDEF const char *const luaT_typenames_[LUA_TOTALTAGS] = { "no value", "nil", "boolean", udatatypename, "number", "string", "table", "function", udatatypename, "thread", "proto", "upval" /* these last two cases are used for tests only */ }; void luaT_init (lua_State *L) { static const char *const luaT_eventname[] = { /* ORDER TM */ "__index", "__newindex", "__gc", "__mode", "__len", "__eq", "__add", "__sub", "__mul", "__div", "__mod", "__pow", "__unm", "__lt", "__le", "__concat", "__call" }; int i; for (i=0; itmname[i] = luaS_new(L, luaT_eventname[i]); luaS_fix(G(L)->tmname[i]); /* never collect these names */ } } /* ** function to be used with macro "fasttm": optimized for absence of ** tag methods */ const TValue *luaT_gettm (Table *events, TMS event, TString *ename) { const TValue *tm = luaH_getstr(events, ename); lua_assert(event <= TM_EQ); if (ttisnil(tm)) { /* no tag method? */ events->flags |= cast_byte(1u<metatable; break; case LUA_TUSERDATA: mt = uvalue(o)->metatable; break; default: mt = G(L)->mt[ttypenv(o)]; } return (mt ? luaH_getstr(mt, G(L)->tmname[event]) : luaO_nilobject); } april-ann-0.4.1/lua/lua-5.2.2/src/ltm.h000066400000000000000000000021411263004425400171330ustar00rootroot00000000000000/* ** $Id: ltm.h,v 2.11 2011/02/28 17:32:10 roberto Exp $ ** Tag methods ** See Copyright Notice in lua.h */ #ifndef ltm_h #define ltm_h #include "lobject.h" /* * WARNING: if you change the order of this enumeration, * grep "ORDER TM" */ typedef enum { TM_INDEX, TM_NEWINDEX, TM_GC, TM_MODE, TM_LEN, TM_EQ, /* last tag method with `fast' access */ TM_ADD, TM_SUB, TM_MUL, TM_DIV, TM_MOD, TM_POW, TM_UNM, TM_LT, TM_LE, TM_CONCAT, TM_CALL, TM_N /* number of elements in the enum */ } TMS; #define gfasttm(g,et,e) ((et) == NULL ? NULL : \ ((et)->flags & (1u<<(e))) ? NULL : luaT_gettm(et, e, (g)->tmname[e])) #define fasttm(l,et,e) gfasttm(G(l), et, e) #define ttypename(x) luaT_typenames_[(x) + 1] #define objtypename(x) ttypename(ttypenv(x)) LUAI_DDEC const char *const luaT_typenames_[LUA_TOTALTAGS]; LUAI_FUNC const TValue *luaT_gettm (Table *events, TMS event, TString *ename); LUAI_FUNC const TValue *luaT_gettmbyobj (lua_State *L, const TValue *o, TMS event); LUAI_FUNC void luaT_init (lua_State *L); #endif april-ann-0.4.1/lua/lua-5.2.2/src/lua.c000066400000000000000000000532521263004425400171240ustar00rootroot00000000000000/* ** $Id: lua.c,v 1.206 2012/09/29 20:07:06 roberto Exp $ ** Lua stand-alone interpreter ** See Copyright Notice in lua.h */ #include #include #include #include #define lua_c #include "lua.h" #include "lauxlib.h" #include "lualib.h" #if !defined(LUA_PROMPT) #define LUA_PROMPT "> " #define LUA_PROMPT2 ">> " #endif #if !defined(LUA_PROGNAME) #define LUA_PROGNAME "lua" #endif #if !defined(LUA_MAXINPUT) #define LUA_MAXINPUT 512 #endif #if !defined(LUA_INIT) #define LUA_INIT "LUA_INIT" #endif #define LUA_INITVERSION \ LUA_INIT "_" LUA_VERSION_MAJOR "_" LUA_VERSION_MINOR /* ** lua_stdin_is_tty detects whether the standard input is a 'tty' (that ** is, whether we're running lua interactively). */ #if defined(LUA_USE_ISATTY) #include #define lua_stdin_is_tty() isatty(0) #elif defined(LUA_WIN) #include #include #define lua_stdin_is_tty() _isatty(_fileno(stdin)) #else #define lua_stdin_is_tty() 1 /* assume stdin is a tty */ #endif /* ** lua_readline defines how to show a prompt and then read a line from ** the standard input. ** lua_saveline defines how to "save" a read line in a "history". ** lua_freeline defines how to free a line read by lua_readline. */ #if defined(LUA_USE_READLINE) #include #include #include #define lua_readline(L,b,p) ((void)L, ((b)=readline(p)) != NULL) #define lua_saveline(L,idx) \ if (lua_rawlen(L,idx) > 0) /* non-empty line? */ \ add_history(lua_tostring(L, idx)); /* add it to history */ #define lua_freeline(L,b) ((void)L, free(b)) #elif !defined(lua_readline) #define lua_readline(L,b,p) \ ((void)L, fputs(p, stdout), fflush(stdout), /* show prompt */ \ fgets(b, LUA_MAXINPUT, stdin) != NULL) /* get line */ #define lua_saveline(L,idx) { (void)L; (void)idx; } #define lua_freeline(L,b) { (void)L; (void)b; } #endif lua_State *globalL = NULL; static const char *progname = LUA_PROGNAME; static void lstop (lua_State *L, lua_Debug *ar) { (void)ar; /* unused arg. */ lua_sethook(L, NULL, 0, 0); luaL_error(L, "interrupted!"); } static void laction (int i) { signal(i, SIG_IGN); /* if another SIGINT happens before lstop, ignore it */ lua_sethook(globalL, lstop, LUA_MASKCALL | LUA_MASKRET | LUA_MASKCOUNT, 1); } static void print_usage (const char *badoption) { luai_writestringerror("%s: ", progname); if (badoption[1] == 'e' || badoption[1] == 'l') luai_writestringerror("'%s' needs argument\n", badoption); else luai_writestringerror("unrecognized option '%s'\n", badoption); luai_writestringerror( "usage: %s [options] [script [args]]\n" "Available options are:\n" " -e stat execute string " LUA_QL("stat") "\n" " -i enter interactive mode after executing " LUA_QL("script") "\n" " -l name require library " LUA_QL("name") "\n" " -v show version information\n" " -E ignore environment variables\n" " -- stop handling options\n" " - stop handling options and execute stdin\n" , progname); } static void l_message (const char *pname, const char *msg) { if (pname) luai_writestringerror("%s: ", pname); luai_writestringerror("%s\n", msg); } static int report (lua_State *L, int status) { if (status != LUA_OK && !lua_isnil(L, -1)) { const char *msg = lua_tostring(L, -1); if (msg == NULL) msg = "(error object is not a string)"; l_message(progname, msg); lua_pop(L, 1); /* force a complete garbage collection in case of errors */ lua_gc(L, LUA_GCCOLLECT, 0); } return status; } /* the next function is called unprotected, so it must avoid errors */ static void finalreport (lua_State *L, int status) { if (status != LUA_OK) { const char *msg = (lua_type(L, -1) == LUA_TSTRING) ? lua_tostring(L, -1) : NULL; if (msg == NULL) msg = "(error object is not a string)"; l_message(progname, msg); lua_pop(L, 1); } } static int traceback (lua_State *L) { const char *msg = lua_tostring(L, 1); if (msg) luaL_traceback(L, L, msg, 1); else if (!lua_isnoneornil(L, 1)) { /* is there an error object? */ if (!luaL_callmeta(L, 1, "__tostring")) /* try its 'tostring' metamethod */ lua_pushliteral(L, "(no error message)"); } return 1; } static int docall (lua_State *L, int narg, int nres) { int status; int base = lua_gettop(L) - narg; /* function index */ lua_pushcfunction(L, traceback); /* push traceback function */ lua_insert(L, base); /* put it under chunk and args */ globalL = L; /* to be available to 'laction' */ signal(SIGINT, laction); status = lua_pcall(L, narg, nres, base); signal(SIGINT, SIG_IGN); lua_remove(L, base); /* remove traceback function */ return status; } static void print_version (void) { luai_writestring(LUA_COPYRIGHT, strlen(LUA_COPYRIGHT)); luai_writeline(); } static int getargs (lua_State *L, char **argv, int n) { int narg; int i; int argc = 0; while (argv[argc]) argc++; /* count total number of arguments */ narg = argc - (n + 1); /* number of arguments to the script */ luaL_checkstack(L, narg + 3, "too many arguments to script"); for (i=n+1; i < argc; i++) lua_pushstring(L, argv[i]); lua_createtable(L, narg, n + 1); for (i=0; i < argc; i++) { lua_pushstring(L, argv[i]); lua_rawseti(L, -2, i - n); } return narg; } static int dofile (lua_State *L, const char *name) { int status = luaL_loadfile(L, name); if (status == LUA_OK) status = docall(L, 0, 0); return report(L, status); } static int dostring (lua_State *L, const char *s, const char *name) { int status = luaL_loadbuffer(L, s, strlen(s), name); if (status == LUA_OK) status = docall(L, 0, 0); return report(L, status); } static int dolibrary (lua_State *L, const char *name) { int status; lua_getglobal(L, "require"); lua_pushstring(L, name); status = docall(L, 1, 1); /* call 'require(name)' */ if (status == LUA_OK) lua_setglobal(L, name); /* global[name] = require return */ return report(L, status); } /* ------------------------------------------------------------------------ */ #ifdef LUA_USE_READLINE /* ** Lua 5.2.0 advanced readline support for the GNU readline and history ** libraries or compatible replacements. ** ** Author: Mike Pall. ** Maintainer: Sean Bolton (sean at smbolton dot com). ** ** Copyright (C) 2004-2006, 2011 Mike Pall. Same license as Lua. See lua.h. ** ** Advanced features: ** - Completion of keywords and global variable names. ** - Recursive and metatable-aware completion of variable names. ** - Context sensitive delimiter completion. ** - Save/restore of the history to/from a file (LUA_HISTORY env variable). ** - Setting a limit for the size of the history (LUA_HISTSIZE env variable). ** - Setting the app name to allow for $if lua ... $endif in ~/.inputrc. ** ** Start lua and try these (replace ~ with the TAB key): ** ** ~~ ** fu~foo() ret~fa~end ** io~~~s~~~o~~~w~"foo\n") ** ** The ~~ are just for demonstration purposes (io~s~o~w~ suffices, of course). ** ** If you are used to zsh/tcsh-style completion support, try adding ** 'TAB: menu-complete' and 'C-d: possible-completions' to your ~/.inputrc. ** ** The patch has been successfully tested with: ** ** GNU readline 2.2.1 (1998-07-17) ** GNU readline 4.0 (1999-02-18) [harmless compiler warning] ** GNU readline 4.3 (2002-07-16) ** GNU readline 5.0 (2004-07-27) ** GNU readline 5.1 (2005-12-07) ** GNU readline 5.2 (2006-10-11) ** GNU readline 6.0 (2009-02-20) ** GNU readline 6.2 (2011-02-13) ** MacOSX libedit 2.11 (2008-07-12) ** NETBSD libedit 2.6.5 (2002-03-25) ** NETBSD libedit 2.6.9 (2004-05-01) ** ** Change Log: ** 2004-2006 Mike Pall - original patch ** 2009/08/24 Sean Bolton - updated for GNU readline version 6 ** 2011/11/15 Sean Bolton - updated for Lua 5.2 ** 2011/12/14 Sean Bolton - fixed segfault when using Mac OS X libedit 2.11 */ #include static char *lua_rl_hist; static int lua_rl_histsize; static lua_State *lua_rl_L; /* User data is not passed to rl callbacks. */ /* Reserved keywords. */ static const char *const lua_rl_keywords[] = { "and", "break", "do", "else", "elseif", "end", "false", "for", "function", "goto", "if", "in", "local", "nil", "not", "or", "repeat", "return", "then", "true", "until", "while", NULL }; static int valididentifier(const char *s) { if (!(isalpha(*s) || *s == '_')) return 0; for (s++; *s; s++) if (!(isalpha(*s) || isdigit(*s) || *s == '_')) return 0; return 1; } /* Dynamically resizable match list. */ typedef struct { char **list; size_t idx, allocated, matchlen; } dmlist; /* Add prefix + string + suffix to list and compute common prefix. */ static int lua_rl_dmadd(dmlist *ml, const char *p, size_t pn, const char *s, int suf) { char *t = NULL; if (ml->idx+1 >= ml->allocated && !(ml->list = (char**)realloc(ml->list, sizeof(char *)*(ml->allocated += 32)))) return -1; if (s) { size_t n = strlen(s); if (!(t = (char *)malloc(sizeof(char)*(pn+n+(suf?2:1))))) return 1; memcpy(t, p, pn); memcpy(t+pn, s, n); n += pn; t[n] = suf; if (suf) t[++n] = '\0'; if (ml->idx == 0) { ml->matchlen = n; } else { size_t i; for (i = 0; i < ml->matchlen && i < n && ml->list[1][i] == t[i]; i++) ; ml->matchlen = i; /* Set matchlen to common prefix. */ } } ml->list[++ml->idx] = t; return 0; } /* Get __index field of metatable of object on top of stack. */ static int lua_rl_getmetaindex(lua_State *L) { if (!lua_getmetatable(L, -1)) { lua_pop(L, 1); return 0; } lua_pushstring(L, "__index"); lua_rawget(L, -2); if (lua_isfunction(L, -1)) { lua_pop(L, 1); lua_pushstring(L, "index_table"); lua_rawget(L, -2); } lua_replace(L, -2); if (lua_isnil(L, -1) || lua_rawequal(L, -1, -2)) { lua_pop(L, 2); return 0; } lua_replace(L, -2); return 1; } /* 1: obj -- val, 0: obj -- */ /* Get field from object on top of stack. Avoid calling metamethods. */ static int lua_rl_getfield(lua_State *L, const char *s, size_t n) { int i = 20; /* Avoid infinite metatable loops. */ do { if (lua_istable(L, -1)) { lua_pushlstring(L, s, n); lua_rawget(L, -2); if (!lua_isnil(L, -1)) { lua_replace(L, -2); return 1; } lua_pop(L, 1); } } while (--i > 0 && lua_rl_getmetaindex(L)); lua_pop(L, 1); return 0; } /* 1: obj -- val, 0: obj -- */ /* Completion callback. */ static char **lua_rl_complete(const char *text, int start, int end) { lua_State *L = lua_rl_L; dmlist ml; const char *s; size_t i, n, dot, loop; int savetop; if (!(text[0] == '\0' || isalpha(text[0]) || text[0] == '_')) return NULL; ml.list = NULL; ml.idx = ml.allocated = ml.matchlen = 0; savetop = lua_gettop(L); lua_pushglobaltable(L); for (n = (size_t)(end-start), i = dot = 0; i < n; i++) if (text[i] == '.' || text[i] == ':') { if (!lua_rl_getfield(L, text+dot, i-dot)) goto error; /* Invalid prefix. */ dot = i+1; /* Points to first char after dot/colon. */ } /* Add all matches against keywords if there is no dot/colon. */ if (dot == 0) for (i = 0; (s = lua_rl_keywords[i]) != NULL; i++) if (!strncmp(s, text, n) && lua_rl_dmadd(&ml, NULL, 0, s, ' ')) goto error; /* Add all valid matches from all tables/metatables. */ loop = 0; /* Avoid infinite metatable loops. */ lua_pushglobaltable(L); lua_insert(L, -2); do { if (lua_istable(L, -1) && (loop == 0 || !lua_rawequal(L, -1, -2))) for (lua_pushnil(L); lua_next(L, -2); lua_pop(L, 1)) if (lua_type(L, -2) == LUA_TSTRING) { s = lua_tostring(L, -2); /* Only match names starting with '_' if explicitly requested. */ if (!strncmp(s, text+dot, n-dot) && valididentifier(s) && (*s != '_' || text[dot] == '_')) { int suf = ' '; /* Default suffix is a space. */ switch (lua_type(L, -1)) { case LUA_TTABLE: suf = '\0'; break; /* No way to guess ':'. */ case LUA_TFUNCTION: suf = '('; break; case LUA_TUSERDATA: if (lua_getmetatable(L, -1)) { lua_pop(L, 1); suf = ':'; } break; } if (lua_rl_dmadd(&ml, text, dot, s, suf)) goto error; } } } while (++loop < 20 && lua_rl_getmetaindex(L)); lua_pop(L, 1); if (ml.idx == 0) { error: lua_settop(L, savetop); return NULL; } else { /* list[0] holds the common prefix of all matches (may be ""). */ /* If there is only one match, list[0] and list[1] will be the same. */ if (!(ml.list[0] = (char *)malloc(sizeof(char)*(ml.matchlen+1)))) goto error; memcpy(ml.list[0], ml.list[1], ml.matchlen); ml.list[0][ml.matchlen] = '\0'; /* Add the NULL list terminator. */ if (lua_rl_dmadd(&ml, NULL, 0, NULL, 0)) goto error; } lua_settop(L, savetop); #if RL_READLINE_VERSION >= 0x0600 rl_completion_suppress_append = 1; #endif return ml.list; } /* Initialize readline library. */ static void lua_rl_init(lua_State *L) { char *s; lua_rl_L = L; /* This allows for $if lua ... $endif in ~/.inputrc. */ rl_readline_name = (char*)"lua"; /* Break words at every non-identifier character except '.' and ':'. */ rl_completer_word_break_characters = (char*)"\t\r\n !\"#$%&'()*+,-/;<=>?@[\\]^`{|}~"; rl_completer_quote_characters = (char*)"\"'"; #if RL_READLINE_VERSION < 0x0600 rl_completion_append_character = '\0'; #endif rl_attempted_completion_function = lua_rl_complete; rl_initialize(); /* Start using history, optionally set history size and load history file. */ using_history(); if ((s = getenv("LUA_HISTSIZE")) && (lua_rl_histsize = atoi(s))) stifle_history(lua_rl_histsize); if ((lua_rl_hist = getenv("LUA_HISTORY"))) read_history(lua_rl_hist); } /* Finalize readline library. */ static void lua_rl_exit(lua_State *L) { (void)(L); /* Optionally save history file. */ if (lua_rl_hist) write_history(lua_rl_hist); } #else #define lua_rl_init(L) ((void)L) #define lua_rl_exit(L) ((void)L) #endif /* ------------------------------------------------------------------------ */ static const char *get_prompt (lua_State *L, int firstline) { const char *p; lua_getglobal(L, firstline ? "_PROMPT" : "_PROMPT2"); p = lua_tostring(L, -1); if (p == NULL) p = (firstline ? LUA_PROMPT : LUA_PROMPT2); return p; } /* mark in error messages for incomplete statements */ #define EOFMARK "" #define marklen (sizeof(EOFMARK)/sizeof(char) - 1) static int incomplete (lua_State *L, int status) { if (status == LUA_ERRSYNTAX) { size_t lmsg; const char *msg = lua_tolstring(L, -1, &lmsg); if (lmsg >= marklen && strcmp(msg + lmsg - marklen, EOFMARK) == 0) { lua_pop(L, 1); return 1; } } return 0; /* else... */ } static int pushline (lua_State *L, int firstline) { char buffer[LUA_MAXINPUT]; char *b = buffer; size_t l; const char *prmt = get_prompt(L, firstline); int readstatus = lua_readline(L, b, prmt); lua_pop(L, 1); /* remove result from 'get_prompt' */ if (readstatus == 0) return 0; /* no input */ l = strlen(b); if (l > 0 && b[l-1] == '\n') /* line ends with newline? */ b[l-1] = '\0'; /* remove it */ if (firstline && b[0] == '=') /* first line starts with `=' ? */ lua_pushfstring(L, "return %s", b+1); /* change it to `return' */ else lua_pushstring(L, b); lua_freeline(L, b); return 1; } static int loadline (lua_State *L) { int status; lua_settop(L, 0); if (!pushline(L, 1)) return -1; /* no input */ for (;;) { /* repeat until gets a complete line */ size_t l; const char *line = lua_tolstring(L, 1, &l); status = luaL_loadbuffer(L, line, l, "=stdin"); if (!incomplete(L, status)) break; /* cannot try to add lines? */ if (!pushline(L, 0)) /* no more input? */ return -1; lua_pushliteral(L, "\n"); /* add a new line... */ lua_insert(L, -2); /* ...between the two lines */ lua_concat(L, 3); /* join them */ } lua_saveline(L, 1); lua_remove(L, 1); /* remove line */ return status; } static void dotty (lua_State *L) { int status; const char *oldprogname = progname; progname = NULL; lua_rl_init(L); while ((status = loadline(L)) != -1) { if (status == LUA_OK) status = docall(L, 0, LUA_MULTRET); report(L, status); if (status == LUA_OK && lua_gettop(L) > 0) { /* any result to print? */ luaL_checkstack(L, LUA_MINSTACK, "too many results to print"); lua_getglobal(L, "print"); lua_insert(L, 1); if (lua_pcall(L, lua_gettop(L)-1, 0, 0) != LUA_OK) l_message(progname, lua_pushfstring(L, "error calling " LUA_QL("print") " (%s)", lua_tostring(L, -1))); } } lua_settop(L, 0); /* clear stack */ luai_writeline(); lua_rl_exit(L); progname = oldprogname; } static int handle_script (lua_State *L, char **argv, int n) { int status; const char *fname; int narg = getargs(L, argv, n); /* collect arguments */ lua_setglobal(L, "arg"); fname = argv[n]; if (strcmp(fname, "-") == 0 && strcmp(argv[n-1], "--") != 0) fname = NULL; /* stdin */ status = luaL_loadfile(L, fname); lua_insert(L, -(narg+1)); if (status == LUA_OK) status = docall(L, narg, LUA_MULTRET); else lua_pop(L, narg); return report(L, status); } /* check that argument has no extra characters at the end */ #define noextrachars(x) {if ((x)[2] != '\0') return -1;} /* indices of various argument indicators in array args */ #define has_i 0 /* -i */ #define has_v 1 /* -v */ #define has_e 2 /* -e */ #define has_E 3 /* -E */ #define num_has 4 /* number of 'has_*' */ static int collectargs (char **argv, int *args) { int i; for (i = 1; argv[i] != NULL; i++) { if (argv[i][0] != '-') /* not an option? */ return i; switch (argv[i][1]) { /* option */ case '-': noextrachars(argv[i]); return (argv[i+1] != NULL ? i+1 : 0); case '\0': return i; case 'E': args[has_E] = 1; break; case 'i': noextrachars(argv[i]); args[has_i] = 1; /* go through */ case 'v': noextrachars(argv[i]); args[has_v] = 1; break; case 'e': args[has_e] = 1; /* go through */ case 'l': /* both options need an argument */ if (argv[i][2] == '\0') { /* no concatenated argument? */ i++; /* try next 'argv' */ if (argv[i] == NULL || argv[i][0] == '-') return -(i - 1); /* no next argument or it is another option */ } break; default: /* invalid option; return its index... */ return -i; /* ...as a negative value */ } } return 0; } static int runargs (lua_State *L, char **argv, int n) { int i; for (i = 1; i < n; i++) { lua_assert(argv[i][0] == '-'); switch (argv[i][1]) { /* option */ case 'e': { const char *chunk = argv[i] + 2; if (*chunk == '\0') chunk = argv[++i]; lua_assert(chunk != NULL); if (dostring(L, chunk, "=(command line)") != LUA_OK) return 0; break; } case 'l': { const char *filename = argv[i] + 2; if (*filename == '\0') filename = argv[++i]; lua_assert(filename != NULL); if (dolibrary(L, filename) != LUA_OK) return 0; /* stop if file fails */ break; } default: break; } } return 1; } static int handle_luainit (lua_State *L) { const char *name = "=" LUA_INITVERSION; const char *init = getenv(name + 1); if (init == NULL) { name = "=" LUA_INIT; init = getenv(name + 1); /* try alternative name */ } if (init == NULL) return LUA_OK; else if (init[0] == '@') return dofile(L, init+1); else return dostring(L, init, name); } static int pmain (lua_State *L) { int argc = (int)lua_tointeger(L, 1); char **argv = (char **)lua_touserdata(L, 2); int script; int args[num_has]; args[has_i] = args[has_v] = args[has_e] = args[has_E] = 0; if (argv[0] && argv[0][0]) progname = argv[0]; script = collectargs(argv, args); if (script < 0) { /* invalid arg? */ print_usage(argv[-script]); return 0; } if (args[has_v]) print_version(); if (args[has_E]) { /* option '-E'? */ lua_pushboolean(L, 1); /* signal for libraries to ignore env. vars. */ lua_setfield(L, LUA_REGISTRYINDEX, "LUA_NOENV"); } /* open standard libraries */ luaL_checkversion(L); lua_gc(L, LUA_GCSTOP, 0); /* stop collector during initialization */ luaL_openlibs(L); /* open libraries */ #ifdef lua_userinit lua_userinit(L); /* APRIL: init packages */ #endif lua_gc(L, LUA_GCRESTART, 0); if (!args[has_E] && handle_luainit(L) != LUA_OK) return 0; /* error running LUA_INIT */ /* execute arguments -e and -l */ if (!runargs(L, argv, (script > 0) ? script : argc)) return 0; /* execute main script (if there is one) */ if (script && handle_script(L, argv, script) != LUA_OK) return 0; if (args[has_i]) /* -i option? */ dotty(L); else if (script == 0 && !args[has_e] && !args[has_v]) { /* no arguments? */ if (lua_stdin_is_tty()) { print_version(); dotty(L); } else dofile(L, NULL); /* executes stdin as a file */ } lua_pushboolean(L, 1); /* signal no errors */ return 1; } int main (int argc, char **argv) { int status, result; lua_State *L = luaL_newstate(); /* create state */ if (L == NULL) { l_message(argv[0], "cannot create state: not enough memory"); return EXIT_FAILURE; } signal(SIGINT, SIG_IGN); // ignore SIGINT by default /* call 'pmain' in protected mode */ lua_pushcfunction(L, &pmain); lua_pushinteger(L, argc); /* 1st argument */ lua_pushlightuserdata(L, argv); /* 2nd argument */ status = lua_pcall(L, 2, 1, 0); result = lua_toboolean(L, -1); /* get result */ finalreport(L, status); lua_close(L); return (result && status == LUA_OK) ? EXIT_SUCCESS : EXIT_FAILURE; } april-ann-0.4.1/lua/lua-5.2.2/src/lua.h000066400000000000000000000324351263004425400171310ustar00rootroot00000000000000/* ** $Id: lua.h,v 1.285 2013/03/15 13:04:22 roberto Exp $ ** Lua - A Scripting Language ** Lua.org, PUC-Rio, Brazil (http://www.lua.org) ** See Copyright Notice at the end of this file */ #ifndef lua_h #define lua_h #include #include #include "luaconf.h" #define LUA_VERSION_MAJOR "5" #define LUA_VERSION_MINOR "2" #define LUA_VERSION_NUM 502 #define LUA_VERSION_RELEASE "2" #define LUA_VERSION "Lua " LUA_VERSION_MAJOR "." LUA_VERSION_MINOR #define LUA_RELEASE LUA_VERSION "." LUA_VERSION_RELEASE #define LUA_COPYRIGHT LUA_RELEASE " Copyright (C) 1994-2013 Lua.org, PUC-Rio" #define LUA_AUTHORS "R. Ierusalimschy, L. H. de Figueiredo, W. Celes" /* mark for precompiled code ('Lua') */ #define LUA_SIGNATURE "\033Lua" /* option for multiple returns in 'lua_pcall' and 'lua_call' */ #define LUA_MULTRET (-1) /* ** pseudo-indices */ #define LUA_REGISTRYINDEX LUAI_FIRSTPSEUDOIDX #define lua_upvalueindex(i) (LUA_REGISTRYINDEX - (i)) /* thread status */ #define LUA_OK 0 #define LUA_YIELD 1 #define LUA_ERRRUN 2 #define LUA_ERRSYNTAX 3 #define LUA_ERRMEM 4 #define LUA_ERRGCMM 5 #define LUA_ERRERR 6 typedef struct lua_State lua_State; typedef int (*lua_CFunction) (lua_State *L); /* ** functions that read/write blocks when loading/dumping Lua chunks */ typedef const char * (*lua_Reader) (lua_State *L, void *ud, size_t *sz); typedef int (*lua_Writer) (lua_State *L, const void* p, size_t sz, void* ud); /* ** prototype for memory-allocation functions */ typedef void * (*lua_Alloc) (void *ud, void *ptr, size_t osize, size_t nsize); /* ** basic types */ #define LUA_TNONE (-1) #define LUA_TNIL 0 #define LUA_TBOOLEAN 1 #define LUA_TLIGHTUSERDATA 2 #define LUA_TNUMBER 3 #define LUA_TSTRING 4 #define LUA_TTABLE 5 #define LUA_TFUNCTION 6 #define LUA_TUSERDATA 7 #define LUA_TTHREAD 8 #define LUA_NUMTAGS 9 /* minimum Lua stack available to a C function */ #define LUA_MINSTACK 20 /* predefined values in the registry */ #define LUA_RIDX_MAINTHREAD 1 #define LUA_RIDX_GLOBALS 2 #define LUA_RIDX_LAST LUA_RIDX_GLOBALS /* type of numbers in Lua */ typedef LUA_NUMBER lua_Number; /* type for integer functions */ typedef LUA_INTEGER lua_Integer; /* unsigned integer type */ typedef LUA_UNSIGNED lua_Unsigned; /* ** generic extra include file */ #if defined(LUA_USER_H) #include LUA_USER_H #endif /* ** RCS ident string */ extern const char lua_ident[]; /* ** state manipulation */ LUA_API lua_State *(lua_newstate) (lua_Alloc f, void *ud); LUA_API void (lua_close) (lua_State *L); LUA_API lua_State *(lua_newthread) (lua_State *L); LUA_API lua_CFunction (lua_atpanic) (lua_State *L, lua_CFunction panicf); LUA_API const lua_Number *(lua_version) (lua_State *L); /* ** basic stack manipulation */ LUA_API int (lua_absindex) (lua_State *L, int idx); LUA_API int (lua_gettop) (lua_State *L); LUA_API void (lua_settop) (lua_State *L, int idx); LUA_API void (lua_pushvalue) (lua_State *L, int idx); LUA_API void (lua_remove) (lua_State *L, int idx); LUA_API void (lua_insert) (lua_State *L, int idx); LUA_API void (lua_replace) (lua_State *L, int idx); LUA_API void (lua_copy) (lua_State *L, int fromidx, int toidx); LUA_API int (lua_checkstack) (lua_State *L, int sz); LUA_API void (lua_xmove) (lua_State *from, lua_State *to, int n); /* ** access functions (stack -> C) */ LUA_API int (lua_isnumber) (lua_State *L, int idx); LUA_API int (lua_isstring) (lua_State *L, int idx); LUA_API int (lua_iscfunction) (lua_State *L, int idx); LUA_API int (lua_isuserdata) (lua_State *L, int idx); LUA_API int (lua_type) (lua_State *L, int idx); LUA_API const char *(lua_typename) (lua_State *L, int tp); LUA_API lua_Number (lua_tonumberx) (lua_State *L, int idx, int *isnum); LUA_API lua_Integer (lua_tointegerx) (lua_State *L, int idx, int *isnum); LUA_API lua_Unsigned (lua_tounsignedx) (lua_State *L, int idx, int *isnum); LUA_API int (lua_toboolean) (lua_State *L, int idx); LUA_API const char *(lua_tolstring) (lua_State *L, int idx, size_t *len); LUA_API size_t (lua_rawlen) (lua_State *L, int idx); LUA_API lua_CFunction (lua_tocfunction) (lua_State *L, int idx); LUA_API void *(lua_touserdata) (lua_State *L, int idx); LUA_API lua_State *(lua_tothread) (lua_State *L, int idx); LUA_API const void *(lua_topointer) (lua_State *L, int idx); /* ** Comparison and arithmetic functions */ #define LUA_OPADD 0 /* ORDER TM */ #define LUA_OPSUB 1 #define LUA_OPMUL 2 #define LUA_OPDIV 3 #define LUA_OPMOD 4 #define LUA_OPPOW 5 #define LUA_OPUNM 6 LUA_API void (lua_arith) (lua_State *L, int op); #define LUA_OPEQ 0 #define LUA_OPLT 1 #define LUA_OPLE 2 LUA_API int (lua_rawequal) (lua_State *L, int idx1, int idx2); LUA_API int (lua_compare) (lua_State *L, int idx1, int idx2, int op); /* ** push functions (C -> stack) */ LUA_API void (lua_pushnil) (lua_State *L); LUA_API void (lua_pushnumber) (lua_State *L, lua_Number n); LUA_API void (lua_pushinteger) (lua_State *L, lua_Integer n); LUA_API void (lua_pushunsigned) (lua_State *L, lua_Unsigned n); LUA_API const char *(lua_pushlstring) (lua_State *L, const char *s, size_t l); LUA_API const char *(lua_pushstring) (lua_State *L, const char *s); LUA_API const char *(lua_pushvfstring) (lua_State *L, const char *fmt, va_list argp); LUA_API const char *(lua_pushfstring) (lua_State *L, const char *fmt, ...); LUA_API void (lua_pushcclosure) (lua_State *L, lua_CFunction fn, int n); LUA_API void (lua_pushboolean) (lua_State *L, int b); LUA_API void (lua_pushlightuserdata) (lua_State *L, void *p); LUA_API int (lua_pushthread) (lua_State *L); /* ** get functions (Lua -> stack) */ LUA_API void (lua_getglobal) (lua_State *L, const char *var); LUA_API void (lua_gettable) (lua_State *L, int idx); LUA_API void (lua_getfield) (lua_State *L, int idx, const char *k); LUA_API void (lua_rawget) (lua_State *L, int idx); LUA_API void (lua_rawgeti) (lua_State *L, int idx, int n); LUA_API void (lua_rawgetp) (lua_State *L, int idx, const void *p); LUA_API void (lua_createtable) (lua_State *L, int narr, int nrec); LUA_API void *(lua_newuserdata) (lua_State *L, size_t sz); LUA_API int (lua_getmetatable) (lua_State *L, int objindex); LUA_API void (lua_getuservalue) (lua_State *L, int idx); /* ** set functions (stack -> Lua) */ LUA_API void (lua_setglobal) (lua_State *L, const char *var); LUA_API void (lua_settable) (lua_State *L, int idx); LUA_API void (lua_setfield) (lua_State *L, int idx, const char *k); LUA_API void (lua_rawset) (lua_State *L, int idx); LUA_API void (lua_rawseti) (lua_State *L, int idx, int n); LUA_API void (lua_rawsetp) (lua_State *L, int idx, const void *p); LUA_API int (lua_setmetatable) (lua_State *L, int objindex); LUA_API void (lua_setuservalue) (lua_State *L, int idx); /* ** 'load' and 'call' functions (load and run Lua code) */ LUA_API void (lua_callk) (lua_State *L, int nargs, int nresults, int ctx, lua_CFunction k); #define lua_call(L,n,r) lua_callk(L, (n), (r), 0, NULL) LUA_API int (lua_getctx) (lua_State *L, int *ctx); LUA_API int (lua_pcallk) (lua_State *L, int nargs, int nresults, int errfunc, int ctx, lua_CFunction k); #define lua_pcall(L,n,r,f) lua_pcallk(L, (n), (r), (f), 0, NULL) LUA_API int (lua_load) (lua_State *L, lua_Reader reader, void *dt, const char *chunkname, const char *mode); LUA_API int (lua_dump) (lua_State *L, lua_Writer writer, void *data); /* ** coroutine functions */ LUA_API int (lua_yieldk) (lua_State *L, int nresults, int ctx, lua_CFunction k); #define lua_yield(L,n) lua_yieldk(L, (n), 0, NULL) LUA_API int (lua_resume) (lua_State *L, lua_State *from, int narg); LUA_API int (lua_status) (lua_State *L); /* ** garbage-collection function and options */ #define LUA_GCSTOP 0 #define LUA_GCRESTART 1 #define LUA_GCCOLLECT 2 #define LUA_GCCOUNT 3 #define LUA_GCCOUNTB 4 #define LUA_GCSTEP 5 #define LUA_GCSETPAUSE 6 #define LUA_GCSETSTEPMUL 7 #define LUA_GCSETMAJORINC 8 #define LUA_GCISRUNNING 9 #define LUA_GCGEN 10 #define LUA_GCINC 11 LUA_API int (lua_gc) (lua_State *L, int what, int data); /* ** miscellaneous functions */ LUA_API int (lua_error) (lua_State *L); LUA_API int (lua_next) (lua_State *L, int idx); LUA_API void (lua_concat) (lua_State *L, int n); LUA_API void (lua_len) (lua_State *L, int idx); LUA_API lua_Alloc (lua_getallocf) (lua_State *L, void **ud); LUA_API void (lua_setallocf) (lua_State *L, lua_Alloc f, void *ud); /* ** =============================================================== ** some useful macros ** =============================================================== */ #define lua_tonumber(L,i) lua_tonumberx(L,i,NULL) #define lua_tointeger(L,i) lua_tointegerx(L,i,NULL) #define lua_tounsigned(L,i) lua_tounsignedx(L,i,NULL) #define lua_pop(L,n) lua_settop(L, -(n)-1) #define lua_newtable(L) lua_createtable(L, 0, 0) #define lua_register(L,n,f) (lua_pushcfunction(L, (f)), lua_setglobal(L, (n))) #define lua_pushcfunction(L,f) lua_pushcclosure(L, (f), 0) #define lua_isfunction(L,n) (lua_type(L, (n)) == LUA_TFUNCTION) #define lua_istable(L,n) (lua_type(L, (n)) == LUA_TTABLE) #define lua_islightuserdata(L,n) (lua_type(L, (n)) == LUA_TLIGHTUSERDATA) #define lua_isnil(L,n) (lua_type(L, (n)) == LUA_TNIL) #define lua_isboolean(L,n) (lua_type(L, (n)) == LUA_TBOOLEAN) #define lua_isthread(L,n) (lua_type(L, (n)) == LUA_TTHREAD) #define lua_isnone(L,n) (lua_type(L, (n)) == LUA_TNONE) #define lua_isnoneornil(L, n) (lua_type(L, (n)) <= 0) #define lua_pushliteral(L, s) \ lua_pushlstring(L, "" s, (sizeof(s)/sizeof(char))-1) #define lua_pushglobaltable(L) \ lua_rawgeti(L, LUA_REGISTRYINDEX, LUA_RIDX_GLOBALS) #define lua_tostring(L,i) lua_tolstring(L, (i), NULL) /* ** {====================================================================== ** Debug API ** ======================================================================= */ /* ** Event codes */ #define LUA_HOOKCALL 0 #define LUA_HOOKRET 1 #define LUA_HOOKLINE 2 #define LUA_HOOKCOUNT 3 #define LUA_HOOKTAILCALL 4 /* ** Event masks */ #define LUA_MASKCALL (1 << LUA_HOOKCALL) #define LUA_MASKRET (1 << LUA_HOOKRET) #define LUA_MASKLINE (1 << LUA_HOOKLINE) #define LUA_MASKCOUNT (1 << LUA_HOOKCOUNT) typedef struct lua_Debug lua_Debug; /* activation record */ /* Functions to be called by the debugger in specific events */ typedef void (*lua_Hook) (lua_State *L, lua_Debug *ar); LUA_API int (lua_getstack) (lua_State *L, int level, lua_Debug *ar); LUA_API int (lua_getinfo) (lua_State *L, const char *what, lua_Debug *ar); LUA_API const char *(lua_getlocal) (lua_State *L, const lua_Debug *ar, int n); LUA_API const char *(lua_setlocal) (lua_State *L, const lua_Debug *ar, int n); LUA_API const char *(lua_getupvalue) (lua_State *L, int funcindex, int n); LUA_API const char *(lua_setupvalue) (lua_State *L, int funcindex, int n); LUA_API void *(lua_upvalueid) (lua_State *L, int fidx, int n); LUA_API void (lua_upvaluejoin) (lua_State *L, int fidx1, int n1, int fidx2, int n2); LUA_API int (lua_sethook) (lua_State *L, lua_Hook func, int mask, int count); LUA_API lua_Hook (lua_gethook) (lua_State *L); LUA_API int (lua_gethookmask) (lua_State *L); LUA_API int (lua_gethookcount) (lua_State *L); struct lua_Debug { int event; const char *name; /* (n) */ const char *namewhat; /* (n) 'global', 'local', 'field', 'method' */ const char *what; /* (S) 'Lua', 'C', 'main', 'tail' */ const char *source; /* (S) */ int currentline; /* (l) */ int linedefined; /* (S) */ int lastlinedefined; /* (S) */ unsigned char nups; /* (u) number of upvalues */ unsigned char nparams;/* (u) number of parameters */ char isvararg; /* (u) */ char istailcall; /* (t) */ char short_src[LUA_IDSIZE]; /* (S) */ /* private part */ struct CallInfo *i_ci; /* active function */ }; /* }====================================================================== */ /****************************************************************************** * Copyright (C) 1994-2013 Lua.org, PUC-Rio. * * Permission is hereby granted, free of charge, to any person obtaining * a copy of this software and associated documentation files (the * "Software"), to deal in the Software without restriction, including * without limitation the rights to use, copy, modify, merge, publish, * distribute, sublicense, and/or sell copies of the Software, and to * permit persons to whom the Software is furnished to do so, subject to * the following conditions: * * The above copyright notice and this permission notice shall be * included in all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY * CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, * TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE * SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ******************************************************************************/ #endif april-ann-0.4.1/lua/lua-5.2.2/src/lua.hpp000066400000000000000000000002771263004425400174700ustar00rootroot00000000000000// lua.hpp // Lua header files for C++ // <> not supplied automatically because Lua also compiles as C++ extern "C" { #include "lua.h" #include "lualib.h" #include "lauxlib.h" } april-ann-0.4.1/lua/lua-5.2.2/src/luac.c000066400000000000000000000233521263004425400172650ustar00rootroot00000000000000/* ** $Id: luac.c,v 1.69 2011/11/29 17:46:33 lhf Exp $ ** Lua compiler (saves bytecodes to files; also list bytecodes) ** See Copyright Notice in lua.h */ #include #include #include #include #define luac_c #define LUA_CORE #include "lua.h" #include "lauxlib.h" #include "lobject.h" #include "lstate.h" #include "lundump.h" static void PrintFunction(const Proto* f, int full); #define luaU_print PrintFunction #define PROGNAME "luac" /* default program name */ #define OUTPUT PROGNAME ".out" /* default output file */ static int listing=0; /* list bytecodes? */ static int dumping=1; /* dump bytecodes? */ static int stripping=0; /* strip debug information? */ static char Output[]={ OUTPUT }; /* default output file name */ static const char* output=Output; /* actual output file name */ static const char* progname=PROGNAME; /* actual program name */ static void fatal(const char* message) { fprintf(stderr,"%s: %s\n",progname,message); exit(EXIT_FAILURE); } static void cannot(const char* what) { fprintf(stderr,"%s: cannot %s %s: %s\n",progname,what,output,strerror(errno)); exit(EXIT_FAILURE); } static void usage(const char* message) { if (*message=='-') fprintf(stderr,"%s: unrecognized option " LUA_QS "\n",progname,message); else fprintf(stderr,"%s: %s\n",progname,message); fprintf(stderr, "usage: %s [options] [filenames]\n" "Available options are:\n" " -l list (use -l -l for full listing)\n" " -o name output to file " LUA_QL("name") " (default is \"%s\")\n" " -p parse only\n" " -s strip debug information\n" " -v show version information\n" " -- stop handling options\n" " - stop handling options and process stdin\n" ,progname,Output); exit(EXIT_FAILURE); } #define IS(s) (strcmp(argv[i],s)==0) static int doargs(int argc, char* argv[]) { int i; int version=0; if (argv[0]!=NULL && *argv[0]!=0) progname=argv[0]; for (i=1; itop+(i)) static const Proto* combine(lua_State* L, int n) { if (n==1) return toproto(L,-1); else { Proto* f; int i=n; if (lua_load(L,reader,&i,"=(" PROGNAME ")",NULL)!=LUA_OK) fatal(lua_tostring(L,-1)); f=toproto(L,-1); for (i=0; ip[i]=toproto(L,i-n-1); if (f->p[i]->sizeupvalues>0) f->p[i]->upvalues[0].instack=0; } f->sizelineinfo=0; return f; } } static int writer(lua_State* L, const void* p, size_t size, void* u) { UNUSED(L); return (fwrite(p,size,1,(FILE*)u)!=1) && (size!=0); } static int pmain(lua_State* L) { int argc=(int)lua_tointeger(L,1); char** argv=(char**)lua_touserdata(L,2); const Proto* f; int i; if (!lua_checkstack(L,argc)) fatal("too many input files"); for (i=0; i1); if (dumping) { FILE* D= (output==NULL) ? stdout : fopen(output,"wb"); if (D==NULL) cannot("open"); lua_lock(L); luaU_dump(L,f,writer,D,stripping); lua_unlock(L); if (ferror(D)) cannot("write"); if (fclose(D)) cannot("close"); } return 0; } int main(int argc, char* argv[]) { lua_State* L; int i=doargs(argc,argv); argc-=i; argv+=i; if (argc<=0) usage("no input files given"); L=luaL_newstate(); if (L==NULL) fatal("cannot create state: not enough memory"); lua_pushcfunction(L,&pmain); lua_pushinteger(L,argc); lua_pushlightuserdata(L,argv); if (lua_pcall(L,2,0,0)!=LUA_OK) fatal(lua_tostring(L,-1)); lua_close(L); return EXIT_SUCCESS; } /* ** $Id: print.c,v 1.68 2011/09/30 10:21:20 lhf Exp $ ** print bytecodes ** See Copyright Notice in lua.h */ #include #include #define luac_c #define LUA_CORE #include "ldebug.h" #include "lobject.h" #include "lopcodes.h" #define VOID(p) ((const void*)(p)) static void PrintString(const TString* ts) { const char* s=getstr(ts); size_t i,n=ts->tsv.len; printf("%c",'"'); for (i=0; ik[i]; switch (ttype(o)) { case LUA_TNIL: printf("nil"); break; case LUA_TBOOLEAN: printf(bvalue(o) ? "true" : "false"); break; case LUA_TNUMBER: printf(LUA_NUMBER_FMT,nvalue(o)); break; case LUA_TSTRING: PrintString(rawtsvalue(o)); break; default: /* cannot happen */ printf("? type=%d",ttype(o)); break; } } #define UPVALNAME(x) ((f->upvalues[x].name) ? getstr(f->upvalues[x].name) : "-") #define MYK(x) (-1-(x)) static void PrintCode(const Proto* f) { const Instruction* code=f->code; int pc,n=f->sizecode; for (pc=0; pc0) printf("[%d]\t",line); else printf("[-]\t"); printf("%-9s\t",luaP_opnames[o]); switch (getOpMode(o)) { case iABC: printf("%d",a); if (getBMode(o)!=OpArgN) printf(" %d",ISK(b) ? (MYK(INDEXK(b))) : b); if (getCMode(o)!=OpArgN) printf(" %d",ISK(c) ? (MYK(INDEXK(c))) : c); break; case iABx: printf("%d",a); if (getBMode(o)==OpArgK) printf(" %d",MYK(bx)); if (getBMode(o)==OpArgU) printf(" %d",bx); break; case iAsBx: printf("%d %d",a,sbx); break; case iAx: printf("%d",MYK(ax)); break; } switch (o) { case OP_LOADK: printf("\t; "); PrintConstant(f,bx); break; case OP_GETUPVAL: case OP_SETUPVAL: printf("\t; %s",UPVALNAME(b)); break; case OP_GETTABUP: printf("\t; %s",UPVALNAME(b)); if (ISK(c)) { printf(" "); PrintConstant(f,INDEXK(c)); } break; case OP_SETTABUP: printf("\t; %s",UPVALNAME(a)); if (ISK(b)) { printf(" "); PrintConstant(f,INDEXK(b)); } if (ISK(c)) { printf(" "); PrintConstant(f,INDEXK(c)); } break; case OP_GETTABLE: case OP_SELF: if (ISK(c)) { printf("\t; "); PrintConstant(f,INDEXK(c)); } break; case OP_SETTABLE: case OP_ADD: case OP_SUB: case OP_MUL: case OP_DIV: case OP_POW: case OP_EQ: case OP_LT: case OP_LE: if (ISK(b) || ISK(c)) { printf("\t; "); if (ISK(b)) PrintConstant(f,INDEXK(b)); else printf("-"); printf(" "); if (ISK(c)) PrintConstant(f,INDEXK(c)); else printf("-"); } break; case OP_JMP: case OP_FORLOOP: case OP_FORPREP: case OP_TFORLOOP: printf("\t; to %d",sbx+pc+2); break; case OP_CLOSURE: printf("\t; %p",VOID(f->p[bx])); break; case OP_SETLIST: if (c==0) printf("\t; %d",(int)code[++pc]); else printf("\t; %d",c); break; case OP_EXTRAARG: printf("\t; "); PrintConstant(f,ax); break; default: break; } printf("\n"); } } #define SS(x) ((x==1)?"":"s") #define S(x) (int)(x),SS(x) static void PrintHeader(const Proto* f) { const char* s=f->source ? getstr(f->source) : "=?"; if (*s=='@' || *s=='=') s++; else if (*s==LUA_SIGNATURE[0]) s="(bstring)"; else s="(string)"; printf("\n%s <%s:%d,%d> (%d instruction%s at %p)\n", (f->linedefined==0)?"main":"function",s, f->linedefined,f->lastlinedefined, S(f->sizecode),VOID(f)); printf("%d%s param%s, %d slot%s, %d upvalue%s, ", (int)(f->numparams),f->is_vararg?"+":"",SS(f->numparams), S(f->maxstacksize),S(f->sizeupvalues)); printf("%d local%s, %d constant%s, %d function%s\n", S(f->sizelocvars),S(f->sizek),S(f->sizep)); } static void PrintDebug(const Proto* f) { int i,n; n=f->sizek; printf("constants (%d) for %p:\n",n,VOID(f)); for (i=0; isizelocvars; printf("locals (%d) for %p:\n",n,VOID(f)); for (i=0; ilocvars[i].varname),f->locvars[i].startpc+1,f->locvars[i].endpc+1); } n=f->sizeupvalues; printf("upvalues (%d) for %p:\n",n,VOID(f)); for (i=0; iupvalues[i].instack,f->upvalues[i].idx); } } static void PrintFunction(const Proto* f, int full) { int i,n=f->sizep; PrintHeader(f); PrintCode(f); if (full) PrintDebug(f); for (i=0; ip[i],full); } april-ann-0.4.1/lua/lua-5.2.2/src/luaconf.h000066400000000000000000000400211263004425400177650ustar00rootroot00000000000000/* ** $Id: luaconf.h,v 1.176 2013/03/16 21:10:18 roberto Exp $ ** Configuration file for Lua ** See Copyright Notice in lua.h */ #ifndef lconfig_h #define lconfig_h #include #include /* ** ================================================================== ** Search for "@@" to find all configurable definitions. ** =================================================================== */ /* @@ LUA_ANSI controls the use of non-ansi features. ** CHANGE it (define it) if you want Lua to avoid the use of any ** non-ansi feature or library. */ #if !defined(LUA_ANSI) && defined(__STRICT_ANSI__) #define LUA_ANSI #endif #if !defined(LUA_ANSI) && defined(_WIN32) && !defined(_WIN32_WCE) #define LUA_WIN /* enable goodies for regular Windows platforms */ #endif #if defined(LUA_WIN) #define LUA_DL_DLL #define LUA_USE_AFORMAT /* assume 'printf' handles 'aA' specifiers */ #endif #if defined(LUA_USE_LINUX) #define LUA_USE_POSIX #define LUA_USE_DLOPEN /* needs an extra library: -ldl */ #define LUA_USE_READLINE /* needs some extra libraries */ #define LUA_USE_STRTODHEX /* assume 'strtod' handles hex formats */ #define LUA_USE_AFORMAT /* assume 'printf' handles 'aA' specifiers */ #define LUA_USE_LONGLONG /* assume support for long long */ #endif #if defined(LUA_USE_MACOSX) #define LUA_USE_POSIX #define LUA_USE_DLOPEN /* does not need -ldl */ #define LUA_USE_READLINE /* needs an extra library: -lreadline */ #define LUA_USE_STRTODHEX /* assume 'strtod' handles hex formats */ #define LUA_USE_AFORMAT /* assume 'printf' handles 'aA' specifiers */ #define LUA_USE_LONGLONG /* assume support for long long */ #endif /* @@ LUA_USE_POSIX includes all functionality listed as X/Open System @* Interfaces Extension (XSI). ** CHANGE it (define it) if your system is XSI compatible. */ #if defined(LUA_USE_POSIX) #define LUA_USE_MKSTEMP #define LUA_USE_ISATTY #define LUA_USE_POPEN #define LUA_USE_ULONGJMP #define LUA_USE_GMTIME_R #endif /* @@ LUA_PATH_DEFAULT is the default path that Lua uses to look for @* Lua libraries. @@ LUA_CPATH_DEFAULT is the default path that Lua uses to look for @* C libraries. ** CHANGE them if your machine has a non-conventional directory ** hierarchy or if you want to install your libraries in ** non-conventional directories. */ #if defined(_WIN32) /* { */ /* ** In Windows, any exclamation mark ('!') in the path is replaced by the ** path of the directory of the executable file of the current process. */ #define LUA_LDIR "!\\lua\\" #define LUA_CDIR "!\\" #define LUA_PATH_DEFAULT \ LUA_LDIR"?.lua;" LUA_LDIR"?\\init.lua;" \ LUA_CDIR"?.lua;" LUA_CDIR"?\\init.lua;" ".\\?.lua" #define LUA_CPATH_DEFAULT \ LUA_CDIR"?.dll;" LUA_CDIR"loadall.dll;" ".\\?.dll" #elif __APPLE__ /* }{ */ #define LUA_VDIR LUA_VERSION_MAJOR "." LUA_VERSION_MINOR "/" #define LUA_ROOT "/usr/" #define LUA_LDIR LUA_ROOT "share/lua/" LUA_VDIR #define LUA_CDIR LUA_ROOT "lib/lua/" LUA_VDIR #define LUA_PATH_DEFAULT \ LUA_LDIR"?.lua;" LUA_LDIR"?/init.lua;" \ LUA_CDIR"?.lua;" LUA_CDIR"?/init.lua;" "./?.lua" #define LUA_CPATH_DEFAULT \ LUA_CDIR"?.so;" LUA_CDIR"loadall.so;" \ "./?.so;" #elif __linux /* }{ */ /* This defines DEB_HOST_MULTIARCH */ #include "lua5.2-deb-multiarch.h" #define LUA_VDIR LUA_VERSION_MAJOR "." LUA_VERSION_MINOR "/" #define LUA_ROOT "/usr/local/" #define LUA_ROOT2 "/usr/" #define LUA_LDIR LUA_ROOT "share/lua/" LUA_VDIR #define LUA_LDIR2 LUA_ROOT2 "share/lua/" LUA_VDIR #define LUA_CDIR LUA_ROOT "lib/lua/" LUA_VDIR #define LUA_CDIR2 LUA_ROOT2 "lib/" DEB_HOST_MULTIARCH "/lua/" LUA_VDIR #define LUA_CDIR3 LUA_ROOT2 "lib/lua/" LUA_VDIR #define LUA_PATH_DEFAULT \ LUA_LDIR"?.lua;" LUA_LDIR"?/init.lua;" \ LUA_CDIR"?.lua;" LUA_CDIR"?/init.lua;" "./?.lua;" \ LUA_LDIR2"?.lua;" LUA_LDIR2"?/init.lua;" "./?.lua" #define LUA_CPATH_DEFAULT \ LUA_CDIR"?.so;" LUA_CDIR2"?.so;" \ LUA_CDIR3"?.so;" LUA_CDIR"loadall.so;" "./?.so" #else /* } */ #error "Unknown platform" #endif /* } */ /* @@ LUA_DIRSEP is the directory separator (for submodules). ** CHANGE it if your machine does not use "/" as the directory separator ** and is not Windows. (On Windows Lua automatically uses "\".) */ #if defined(_WIN32) #define LUA_DIRSEP "\\" #else #define LUA_DIRSEP "/" #endif /* @@ LUA_ENV is the name of the variable that holds the current @@ environment, used to access global names. ** CHANGE it if you do not like this name. */ #define LUA_ENV "_ENV" /* @@ LUA_API is a mark for all core API functions. @@ LUALIB_API is a mark for all auxiliary library functions. @@ LUAMOD_API is a mark for all standard library opening functions. ** CHANGE them if you need to define those functions in some special way. ** For instance, if you want to create one Windows DLL with the core and ** the libraries, you may want to use the following definition (define ** LUA_BUILD_AS_DLL to get it). */ #if defined(LUA_BUILD_AS_DLL) /* { */ #if defined(LUA_CORE) || defined(LUA_LIB) /* { */ #define LUA_API __declspec(dllexport) #else /* }{ */ #define LUA_API __declspec(dllimport) #endif /* } */ #else /* }{ */ #define LUA_API extern #endif /* } */ /* more often than not the libs go together with the core */ #define LUALIB_API LUA_API #define LUAMOD_API LUALIB_API /* @@ LUAI_FUNC is a mark for all extern functions that are not to be @* exported to outside modules. @@ LUAI_DDEF and LUAI_DDEC are marks for all extern (const) variables @* that are not to be exported to outside modules (LUAI_DDEF for @* definitions and LUAI_DDEC for declarations). ** CHANGE them if you need to mark them in some special way. Elf/gcc ** (versions 3.2 and later) mark them as "hidden" to optimize access ** when Lua is compiled as a shared library. Not all elf targets support ** this attribute. Unfortunately, gcc does not offer a way to check ** whether the target offers that support, and those without support ** give a warning about it. To avoid these warnings, change to the ** default definition. */ #if defined(__GNUC__) && ((__GNUC__*100 + __GNUC_MINOR__) >= 302) && \ defined(__ELF__) /* { */ #define LUAI_FUNC __attribute__((visibility("hidden"))) extern #define LUAI_DDEC LUAI_FUNC #define LUAI_DDEF /* empty */ #else /* }{ */ #define LUAI_FUNC extern #define LUAI_DDEC extern #define LUAI_DDEF /* empty */ #endif /* } */ /* @@ LUA_QL describes how error messages quote program elements. ** CHANGE it if you want a different appearance. */ #define LUA_QL(x) "'" x "'" #define LUA_QS LUA_QL("%s") /* @@ LUA_IDSIZE gives the maximum size for the description of the source @* of a function in debug information. ** CHANGE it if you want a different size. */ #define LUA_IDSIZE 60 /* @@ luai_writestring/luai_writeline define how 'print' prints its results. ** They are only used in libraries and the stand-alone program. (The #if ** avoids including 'stdio.h' everywhere.) */ #if defined(LUA_LIB) || defined(lua_c) #include #define luai_writestring(s,l) fwrite((s), sizeof(char), (l), stdout) #define luai_writeline() (luai_writestring("\n", 1), fflush(stdout)) #endif /* @@ luai_writestringerror defines how to print error messages. ** (A format string with one argument is enough for Lua...) */ #define luai_writestringerror(s,p) \ (fprintf(stderr, (s), (p)), fflush(stderr)) /* @@ LUAI_MAXSHORTLEN is the maximum length for short strings, that is, ** strings that are internalized. (Cannot be smaller than reserved words ** or tags for metamethods, as these strings must be internalized; ** #("function") = 8, #("__newindex") = 10.) */ #define LUAI_MAXSHORTLEN 40 /* ** {================================================================== ** Compatibility with previous versions ** =================================================================== */ /* @@ LUA_COMPAT_ALL controls all compatibility options. ** You can define it to get all options, or change specific options ** to fit your specific needs. */ #if defined(LUA_COMPAT_ALL) /* { */ /* @@ LUA_COMPAT_UNPACK controls the presence of global 'unpack'. ** You can replace it with 'table.unpack'. */ #define LUA_COMPAT_UNPACK /* @@ LUA_COMPAT_LOADERS controls the presence of table 'package.loaders'. ** You can replace it with 'package.searchers'. */ #define LUA_COMPAT_LOADERS /* @@ macro 'lua_cpcall' emulates deprecated function lua_cpcall. ** You can call your C function directly (with light C functions). */ #define lua_cpcall(L,f,u) \ (lua_pushcfunction(L, (f)), \ lua_pushlightuserdata(L,(u)), \ lua_pcall(L,1,0,0)) /* @@ LUA_COMPAT_LOG10 defines the function 'log10' in the math library. ** You can rewrite 'log10(x)' as 'log(x, 10)'. */ #define LUA_COMPAT_LOG10 /* @@ LUA_COMPAT_LOADSTRING defines the function 'loadstring' in the base ** library. You can rewrite 'loadstring(s)' as 'load(s)'. */ #define LUA_COMPAT_LOADSTRING /* @@ LUA_COMPAT_MAXN defines the function 'maxn' in the table library. */ #define LUA_COMPAT_MAXN /* @@ The following macros supply trivial compatibility for some ** changes in the API. The macros themselves document how to ** change your code to avoid using them. */ #define lua_strlen(L,i) lua_rawlen(L, (i)) #define lua_objlen(L,i) lua_rawlen(L, (i)) #define lua_equal(L,idx1,idx2) lua_compare(L,(idx1),(idx2),LUA_OPEQ) #define lua_lessthan(L,idx1,idx2) lua_compare(L,(idx1),(idx2),LUA_OPLT) /* @@ LUA_COMPAT_MODULE controls compatibility with previous ** module functions 'module' (Lua) and 'luaL_register' (C). */ #define LUA_COMPAT_MODULE #endif /* } */ /* }================================================================== */ /* @@ LUAI_BITSINT defines the number of bits in an int. ** CHANGE here if Lua cannot automatically detect the number of bits of ** your machine. Probably you do not need to change this. */ /* avoid overflows in comparison */ #if INT_MAX-20 < 32760 /* { */ #define LUAI_BITSINT 16 #elif INT_MAX > 2147483640L /* }{ */ /* int has at least 32 bits */ #define LUAI_BITSINT 32 #else /* }{ */ #error "you must define LUA_BITSINT with number of bits in an integer" #endif /* } */ /* @@ LUA_INT32 is an signed integer with exactly 32 bits. @@ LUAI_UMEM is an unsigned integer big enough to count the total @* memory used by Lua. @@ LUAI_MEM is a signed integer big enough to count the total memory @* used by Lua. ** CHANGE here if for some weird reason the default definitions are not ** good enough for your machine. Probably you do not need to change ** this. */ #if LUAI_BITSINT >= 32 /* { */ #define LUA_INT32 int #define LUAI_UMEM size_t #define LUAI_MEM ptrdiff_t #else /* }{ */ /* 16-bit ints */ #define LUA_INT32 long #define LUAI_UMEM unsigned long #define LUAI_MEM long #endif /* } */ /* @@ LUAI_MAXSTACK limits the size of the Lua stack. ** CHANGE it if you need a different limit. This limit is arbitrary; ** its only purpose is to stop Lua to consume unlimited stack ** space (and to reserve some numbers for pseudo-indices). */ #if LUAI_BITSINT >= 32 #define LUAI_MAXSTACK 1000000 #else #define LUAI_MAXSTACK 15000 #endif /* reserve some space for error handling */ #define LUAI_FIRSTPSEUDOIDX (-LUAI_MAXSTACK - 1000) /* @@ LUAL_BUFFERSIZE is the buffer size used by the lauxlib buffer system. ** CHANGE it if it uses too much C-stack space. */ #define LUAL_BUFFERSIZE BUFSIZ /* ** {================================================================== @@ LUA_NUMBER is the type of numbers in Lua. ** CHANGE the following definitions only if you want to build Lua ** with a number type different from double. You may also need to ** change lua_number2int & lua_number2integer. ** =================================================================== */ #define LUA_NUMBER_DOUBLE #define LUA_NUMBER double /* @@ LUAI_UACNUMBER is the result of an 'usual argument conversion' @* over a number. */ #define LUAI_UACNUMBER double /* @@ LUA_NUMBER_SCAN is the format for reading numbers. @@ LUA_NUMBER_FMT is the format for writing numbers. @@ lua_number2str converts a number to a string. @@ LUAI_MAXNUMBER2STR is maximum size of previous conversion. */ #define LUA_NUMBER_SCAN "%lf" #define LUA_NUMBER_FMT "%.14g" #define lua_number2str(s,n) sprintf((s), LUA_NUMBER_FMT, (n)) #define LUAI_MAXNUMBER2STR 32 /* 16 digits, sign, point, and \0 */ /* @@ l_mathop allows the addition of an 'l' or 'f' to all math operations */ #define l_mathop(x) (x) /* @@ lua_str2number converts a decimal numeric string to a number. @@ lua_strx2number converts an hexadecimal numeric string to a number. ** In C99, 'strtod' does both conversions. C89, however, has no function ** to convert floating hexadecimal strings to numbers. For these ** systems, you can leave 'lua_strx2number' undefined and Lua will ** provide its own implementation. */ #define lua_str2number(s,p) strtod((s), (p)) #if defined(LUA_USE_STRTODHEX) #define lua_strx2number(s,p) strtod((s), (p)) #endif /* @@ The luai_num* macros define the primitive operations over numbers. */ /* the following operations need the math library */ #if defined(lobject_c) || defined(lvm_c) #include #define luai_nummod(L,a,b) ((a) - l_mathop(floor)((a)/(b))*(b)) #define luai_numpow(L,a,b) (l_mathop(pow)(a,b)) #endif /* these are quite standard operations */ #if defined(LUA_CORE) #define luai_numadd(L,a,b) ((a)+(b)) #define luai_numsub(L,a,b) ((a)-(b)) #define luai_nummul(L,a,b) ((a)*(b)) #define luai_numdiv(L,a,b) ((a)/(b)) #define luai_numunm(L,a) (-(a)) #define luai_numeq(a,b) ((a)==(b)) #define luai_numlt(L,a,b) ((a)<(b)) #define luai_numle(L,a,b) ((a)<=(b)) #define luai_numisnan(L,a) (!luai_numeq((a), (a))) #endif /* @@ LUA_INTEGER is the integral type used by lua_pushinteger/lua_tointeger. ** CHANGE that if ptrdiff_t is not adequate on your machine. (On most ** machines, ptrdiff_t gives a good choice between int or long.) */ #define LUA_INTEGER ptrdiff_t /* @@ LUA_UNSIGNED is the integral type used by lua_pushunsigned/lua_tounsigned. ** It must have at least 32 bits. */ #define LUA_UNSIGNED unsigned LUA_INT32 /* ** Some tricks with doubles */ #if defined(LUA_NUMBER_DOUBLE) && !defined(LUA_ANSI) /* { */ /* ** The next definitions activate some tricks to speed up the ** conversion from doubles to integer types, mainly to LUA_UNSIGNED. ** @@ LUA_MSASMTRICK uses Microsoft assembler to avoid clashes with a ** DirectX idiosyncrasy. ** @@ LUA_IEEE754TRICK uses a trick that should work on any machine ** using IEEE754 with a 32-bit integer type. ** @@ LUA_IEEELL extends the trick to LUA_INTEGER; should only be ** defined when LUA_INTEGER is a 32-bit integer. ** @@ LUA_IEEEENDIAN is the endianness of doubles in your machine ** (0 for little endian, 1 for big endian); if not defined, Lua will ** check it dynamically for LUA_IEEE754TRICK (but not for LUA_NANTRICK). ** @@ LUA_NANTRICK controls the use of a trick to pack all types into ** a single double value, using NaN values to represent non-number ** values. The trick only works on 32-bit machines (ints and pointers ** are 32-bit values) with numbers represented as IEEE 754-2008 doubles ** with conventional endianess (12345678 or 87654321), in CPUs that do ** not produce signaling NaN values (all NaNs are quiet). */ /* Microsoft compiler on a Pentium (32 bit) ? */ #if defined(LUA_WIN) && defined(_MSC_VER) && defined(_M_IX86) /* { */ #define LUA_MSASMTRICK #define LUA_IEEEENDIAN 0 #define LUA_NANTRICK /* pentium 32 bits? */ #elif defined(__i386__) || defined(__i386) || defined(__X86__) /* }{ */ #define LUA_IEEE754TRICK #define LUA_IEEELL #define LUA_IEEEENDIAN 0 #define LUA_NANTRICK /* pentium 64 bits? */ #elif defined(__x86_64) /* }{ */ #define LUA_IEEE754TRICK #define LUA_IEEEENDIAN 0 #elif defined(__POWERPC__) || defined(__ppc__) /* }{ */ #define LUA_IEEE754TRICK #define LUA_IEEEENDIAN 1 #else /* }{ */ /* assume IEEE754 and a 32-bit integer type */ #define LUA_IEEE754TRICK #endif /* } */ #endif /* } */ /* }================================================================== */ /* =================================================================== */ /* ** Local configuration. You can use this space to add your redefinitions ** without modifying the main part of the file. */ #endif april-ann-0.4.1/lua/lua-5.2.2/src/lualib.h000066400000000000000000000035771263004425400176250ustar00rootroot00000000000000/* ** $Id: lualib.h,v 1.43 2011/12/08 12:11:37 roberto Exp $ ** Lua standard libraries ** See Copyright Notice in lua.h */ #ifndef lualib_h #define lualib_h #include "lua.h" /* ** {====================================================== ** lua_popen spawns a new process connected to the current ** one through the file streams. ** ======================================================= */ #if !defined(lua_popen) /* { */ #if defined(LUA_USE_POPEN) /* { */ #define lua_popen(L,c,m) ((void)L, fflush(NULL), popen(c,m)) #define lua_pclose(L,file) ((void)L, pclose(file)) #elif defined(LUA_WIN) /* }{ */ #define lua_popen(L,c,m) ((void)L, _popen(c,m)) #define lua_pclose(L,file) ((void)L, _pclose(file)) #else /* }{ */ #define lua_popen(L,c,m) ((void)((void)c, m), \ luaL_error(L, LUA_QL("popen") " not supported"), (FILE*)0) #define lua_pclose(L,file) ((void)((void)L, file), -1) #endif /* } */ #endif /* } */ /* }====================================================== */ LUAMOD_API int (luaopen_base) (lua_State *L); #define LUA_COLIBNAME "coroutine" LUAMOD_API int (luaopen_coroutine) (lua_State *L); #define LUA_TABLIBNAME "table" LUAMOD_API int (luaopen_table) (lua_State *L); #define LUA_IOLIBNAME "io" LUAMOD_API int (luaopen_io) (lua_State *L); #define LUA_OSLIBNAME "os" LUAMOD_API int (luaopen_os) (lua_State *L); #define LUA_STRLIBNAME "string" LUAMOD_API int (luaopen_string) (lua_State *L); #define LUA_BITLIBNAME "bit32" LUAMOD_API int (luaopen_bit32) (lua_State *L); #define LUA_MATHLIBNAME "math" LUAMOD_API int (luaopen_math) (lua_State *L); #define LUA_DBLIBNAME "debug" LUAMOD_API int (luaopen_debug) (lua_State *L); #define LUA_LOADLIBNAME "package" LUAMOD_API int (luaopen_package) (lua_State *L); /* open all previous libraries */ LUALIB_API void (luaL_openlibs) (lua_State *L); #if !defined(lua_assert) #define lua_assert(x) ((void)0) #endif #endif april-ann-0.4.1/lua/lua-5.2.2/src/lundump.c000066400000000000000000000127631263004425400200310ustar00rootroot00000000000000/* ** $Id: lundump.c,v 2.22 2012/05/08 13:53:33 roberto Exp $ ** load precompiled Lua chunks ** See Copyright Notice in lua.h */ #include #define lundump_c #define LUA_CORE #include "lua.h" #include "ldebug.h" #include "ldo.h" #include "lfunc.h" #include "lmem.h" #include "lobject.h" #include "lstring.h" #include "lundump.h" #include "lzio.h" typedef struct { lua_State* L; ZIO* Z; Mbuffer* b; const char* name; } LoadState; static l_noret error(LoadState* S, const char* why) { luaO_pushfstring(S->L,"%s: %s precompiled chunk",S->name,why); luaD_throw(S->L,LUA_ERRSYNTAX); } #define LoadMem(S,b,n,size) LoadBlock(S,b,(n)*(size)) #define LoadByte(S) (lu_byte)LoadChar(S) #define LoadVar(S,x) LoadMem(S,&x,1,sizeof(x)) #define LoadVector(S,b,n,size) LoadMem(S,b,n,size) #if !defined(luai_verifycode) #define luai_verifycode(L,b,f) /* empty */ #endif static void LoadBlock(LoadState* S, void* b, size_t size) { if (luaZ_read(S->Z,b,size)!=0) error(S,"truncated"); } static int LoadChar(LoadState* S) { char x; LoadVar(S,x); return x; } static int LoadInt(LoadState* S) { int x; LoadVar(S,x); if (x<0) error(S,"corrupted"); return x; } static lua_Number LoadNumber(LoadState* S) { lua_Number x; LoadVar(S,x); return x; } static TString* LoadString(LoadState* S) { size_t size; LoadVar(S,size); if (size==0) return NULL; else { char* s=luaZ_openspace(S->L,S->b,size); LoadBlock(S,s,size*sizeof(char)); return luaS_newlstr(S->L,s,size-1); /* remove trailing '\0' */ } } static void LoadCode(LoadState* S, Proto* f) { int n=LoadInt(S); f->code=luaM_newvector(S->L,n,Instruction); f->sizecode=n; LoadVector(S,f->code,n,sizeof(Instruction)); } static void LoadFunction(LoadState* S, Proto* f); static void LoadConstants(LoadState* S, Proto* f) { int i,n; n=LoadInt(S); f->k=luaM_newvector(S->L,n,TValue); f->sizek=n; for (i=0; ik[i]); for (i=0; ik[i]; int t=LoadChar(S); switch (t) { case LUA_TNIL: setnilvalue(o); break; case LUA_TBOOLEAN: setbvalue(o,LoadChar(S)); break; case LUA_TNUMBER: setnvalue(o,LoadNumber(S)); break; case LUA_TSTRING: setsvalue2n(S->L,o,LoadString(S)); break; default: lua_assert(0); } } n=LoadInt(S); f->p=luaM_newvector(S->L,n,Proto*); f->sizep=n; for (i=0; ip[i]=NULL; for (i=0; ip[i]=luaF_newproto(S->L); LoadFunction(S,f->p[i]); } } static void LoadUpvalues(LoadState* S, Proto* f) { int i,n; n=LoadInt(S); f->upvalues=luaM_newvector(S->L,n,Upvaldesc); f->sizeupvalues=n; for (i=0; iupvalues[i].name=NULL; for (i=0; iupvalues[i].instack=LoadByte(S); f->upvalues[i].idx=LoadByte(S); } } static void LoadDebug(LoadState* S, Proto* f) { int i,n; f->source=LoadString(S); n=LoadInt(S); f->lineinfo=luaM_newvector(S->L,n,int); f->sizelineinfo=n; LoadVector(S,f->lineinfo,n,sizeof(int)); n=LoadInt(S); f->locvars=luaM_newvector(S->L,n,LocVar); f->sizelocvars=n; for (i=0; ilocvars[i].varname=NULL; for (i=0; ilocvars[i].varname=LoadString(S); f->locvars[i].startpc=LoadInt(S); f->locvars[i].endpc=LoadInt(S); } n=LoadInt(S); for (i=0; iupvalues[i].name=LoadString(S); } static void LoadFunction(LoadState* S, Proto* f) { f->linedefined=LoadInt(S); f->lastlinedefined=LoadInt(S); f->numparams=LoadByte(S); f->is_vararg=LoadByte(S); f->maxstacksize=LoadByte(S); LoadCode(S,f); LoadConstants(S,f); LoadUpvalues(S,f); LoadDebug(S,f); } /* the code below must be consistent with the code in luaU_header */ #define N0 LUAC_HEADERSIZE #define N1 (sizeof(LUA_SIGNATURE)-sizeof(char)) #define N2 N1+2 #define N3 N2+6 static void LoadHeader(LoadState* S) { lu_byte h[LUAC_HEADERSIZE]; lu_byte s[LUAC_HEADERSIZE]; luaU_header(h); memcpy(s,h,sizeof(char)); /* first char already read */ LoadBlock(S,s+sizeof(char),LUAC_HEADERSIZE-sizeof(char)); if (memcmp(h,s,N0)==0) return; if (memcmp(h,s,N1)!=0) error(S,"not a"); if (memcmp(h,s,N2)!=0) error(S,"version mismatch in"); if (memcmp(h,s,N3)!=0) error(S,"incompatible"); else error(S,"corrupted"); } /* ** load precompiled chunk */ Closure* luaU_undump (lua_State* L, ZIO* Z, Mbuffer* buff, const char* name) { LoadState S; Closure* cl; if (*name=='@' || *name=='=') S.name=name+1; else if (*name==LUA_SIGNATURE[0]) S.name="binary string"; else S.name=name; S.L=L; S.Z=Z; S.b=buff; LoadHeader(&S); cl=luaF_newLclosure(L,1); setclLvalue(L,L->top,cl); incr_top(L); cl->l.p=luaF_newproto(L); LoadFunction(&S,cl->l.p); if (cl->l.p->sizeupvalues != 1) { Proto* p=cl->l.p; cl=luaF_newLclosure(L,cl->l.p->sizeupvalues); cl->l.p=p; setclLvalue(L,L->top-1,cl); } luai_verifycode(L,buff,cl->l.p); return cl; } #define MYINT(s) (s[0]-'0') #define VERSION MYINT(LUA_VERSION_MAJOR)*16+MYINT(LUA_VERSION_MINOR) #define FORMAT 0 /* this is the official format */ /* * make header for precompiled chunks * if you change the code below be sure to update LoadHeader and FORMAT above * and LUAC_HEADERSIZE in lundump.h */ void luaU_header (lu_byte* h) { int x=1; memcpy(h,LUA_SIGNATURE,sizeof(LUA_SIGNATURE)-sizeof(char)); h+=sizeof(LUA_SIGNATURE)-sizeof(char); *h++=cast_byte(VERSION); *h++=cast_byte(FORMAT); *h++=cast_byte(*(char*)&x); /* endianness */ *h++=cast_byte(sizeof(int)); *h++=cast_byte(sizeof(size_t)); *h++=cast_byte(sizeof(Instruction)); *h++=cast_byte(sizeof(lua_Number)); *h++=cast_byte(((lua_Number)0.5)==0); /* is lua_Number integral? */ memcpy(h,LUAC_TAIL,sizeof(LUAC_TAIL)-sizeof(char)); } april-ann-0.4.1/lua/lua-5.2.2/src/lundump.h000066400000000000000000000014001263004425400200200ustar00rootroot00000000000000/* ** $Id: lundump.h,v 1.39 2012/05/08 13:53:33 roberto Exp $ ** load precompiled Lua chunks ** See Copyright Notice in lua.h */ #ifndef lundump_h #define lundump_h #include "lobject.h" #include "lzio.h" /* load one chunk; from lundump.c */ LUAI_FUNC Closure* luaU_undump (lua_State* L, ZIO* Z, Mbuffer* buff, const char* name); /* make header; from lundump.c */ LUAI_FUNC void luaU_header (lu_byte* h); /* dump one chunk; from ldump.c */ LUAI_FUNC int luaU_dump (lua_State* L, const Proto* f, lua_Writer w, void* data, int strip); /* data to catch conversion errors */ #define LUAC_TAIL "\x19\x93\r\n\x1a\n" /* size in bytes of header of binary files */ #define LUAC_HEADERSIZE (sizeof(LUA_SIGNATURE)-sizeof(char)+2+6+sizeof(LUAC_TAIL)-sizeof(char)) #endif april-ann-0.4.1/lua/lua-5.2.2/src/lvm.c000066400000000000000000000702461263004425400171430ustar00rootroot00000000000000/* ** $Id: lvm.c,v 2.155 2013/03/16 21:10:18 roberto Exp $ ** Lua virtual machine ** See Copyright Notice in lua.h */ #include #include #include #define lvm_c #define LUA_CORE #include "lua.h" #include "ldebug.h" #include "ldo.h" #include "lfunc.h" #include "lgc.h" #include "lobject.h" #include "lopcodes.h" #include "lstate.h" #include "lstring.h" #include "ltable.h" #include "ltm.h" #include "lvm.h" /* limit for table tag-method chains (to avoid loops) */ #define MAXTAGLOOP 100 const TValue *luaV_tonumber (const TValue *obj, TValue *n) { lua_Number num; if (ttisnumber(obj)) return obj; if (ttisstring(obj) && luaO_str2d(svalue(obj), tsvalue(obj)->len, &num)) { setnvalue(n, num); return n; } else return NULL; } int luaV_tostring (lua_State *L, StkId obj) { if (!ttisnumber(obj)) return 0; else { char s[LUAI_MAXNUMBER2STR]; lua_Number n = nvalue(obj); int l = lua_number2str(s, n); setsvalue2s(L, obj, luaS_newlstr(L, s, l)); return 1; } } static void traceexec (lua_State *L) { CallInfo *ci = L->ci; lu_byte mask = L->hookmask; int counthook = ((mask & LUA_MASKCOUNT) && L->hookcount == 0); if (counthook) resethookcount(L); /* reset count */ if (ci->callstatus & CIST_HOOKYIELD) { /* called hook last time? */ ci->callstatus &= ~CIST_HOOKYIELD; /* erase mark */ return; /* do not call hook again (VM yielded, so it did not move) */ } if (counthook) luaD_hook(L, LUA_HOOKCOUNT, -1); /* call count hook */ if (mask & LUA_MASKLINE) { Proto *p = ci_func(ci)->p; int npc = pcRel(ci->u.l.savedpc, p); int newline = getfuncline(p, npc); if (npc == 0 || /* call linehook when enter a new function, */ ci->u.l.savedpc <= L->oldpc || /* when jump back (loop), or when */ newline != getfuncline(p, pcRel(L->oldpc, p))) /* enter a new line */ luaD_hook(L, LUA_HOOKLINE, newline); /* call line hook */ } L->oldpc = ci->u.l.savedpc; if (L->status == LUA_YIELD) { /* did hook yield? */ if (counthook) L->hookcount = 1; /* undo decrement to zero */ ci->u.l.savedpc--; /* undo increment (resume will increment it again) */ ci->callstatus |= CIST_HOOKYIELD; /* mark that it yielded */ ci->func = L->top - 1; /* protect stack below results */ luaD_throw(L, LUA_YIELD); } } static void callTM (lua_State *L, const TValue *f, const TValue *p1, const TValue *p2, TValue *p3, int hasres) { ptrdiff_t result = savestack(L, p3); setobj2s(L, L->top++, f); /* push function */ setobj2s(L, L->top++, p1); /* 1st argument */ setobj2s(L, L->top++, p2); /* 2nd argument */ if (!hasres) /* no result? 'p3' is third argument */ setobj2s(L, L->top++, p3); /* 3rd argument */ /* metamethod may yield only when called from Lua code */ luaD_call(L, L->top - (4 - hasres), hasres, isLua(L->ci)); if (hasres) { /* if has result, move it to its place */ p3 = restorestack(L, result); setobjs2s(L, p3, --L->top); } } void luaV_gettable (lua_State *L, const TValue *t, TValue *key, StkId val) { int loop; for (loop = 0; loop < MAXTAGLOOP; loop++) { const TValue *tm; if (ttistable(t)) { /* `t' is a table? */ Table *h = hvalue(t); const TValue *res = luaH_get(h, key); /* do a primitive get */ if (!ttisnil(res) || /* result is not nil? */ (tm = fasttm(L, h->metatable, TM_INDEX)) == NULL) { /* or no TM? */ setobj2s(L, val, res); return; } /* else will try the tag method */ } else if (ttisnil(tm = luaT_gettmbyobj(L, t, TM_INDEX))) luaG_typeerror(L, t, "index"); if (ttisfunction(tm)) { callTM(L, tm, t, key, val, 1); return; } t = tm; /* else repeat with 'tm' */ } luaG_runerror(L, "loop in gettable"); } void luaV_settable (lua_State *L, const TValue *t, TValue *key, StkId val) { int loop; for (loop = 0; loop < MAXTAGLOOP; loop++) { const TValue *tm; if (ttistable(t)) { /* `t' is a table? */ Table *h = hvalue(t); TValue *oldval = cast(TValue *, luaH_get(h, key)); /* if previous value is not nil, there must be a previous entry in the table; moreover, a metamethod has no relevance */ if (!ttisnil(oldval) || /* previous value is nil; must check the metamethod */ ((tm = fasttm(L, h->metatable, TM_NEWINDEX)) == NULL && /* no metamethod; is there a previous entry in the table? */ (oldval != luaO_nilobject || /* no previous entry; must create one. (The next test is always true; we only need the assignment.) */ (oldval = luaH_newkey(L, h, key), 1)))) { /* no metamethod and (now) there is an entry with given key */ setobj2t(L, oldval, val); /* assign new value to that entry */ invalidateTMcache(h); luaC_barrierback(L, obj2gco(h), val); return; } /* else will try the metamethod */ } else /* not a table; check metamethod */ if (ttisnil(tm = luaT_gettmbyobj(L, t, TM_NEWINDEX))) luaG_typeerror(L, t, "index"); /* there is a metamethod */ if (ttisfunction(tm)) { callTM(L, tm, t, key, val, 0); return; } t = tm; /* else repeat with 'tm' */ } luaG_runerror(L, "loop in settable"); } static int call_binTM (lua_State *L, const TValue *p1, const TValue *p2, StkId res, TMS event) { const TValue *tm = luaT_gettmbyobj(L, p1, event); /* try first operand */ if (ttisnil(tm)) tm = luaT_gettmbyobj(L, p2, event); /* try second operand */ if (ttisnil(tm)) return 0; callTM(L, tm, p1, p2, res, 1); return 1; } static const TValue *get_equalTM (lua_State *L, Table *mt1, Table *mt2, TMS event) { const TValue *tm1 = fasttm(L, mt1, event); const TValue *tm2; if (tm1 == NULL) return NULL; /* no metamethod */ if (mt1 == mt2) return tm1; /* same metatables => same metamethods */ tm2 = fasttm(L, mt2, event); if (tm2 == NULL) return NULL; /* no metamethod */ if (luaV_rawequalobj(tm1, tm2)) /* same metamethods? */ return tm1; return NULL; } static int call_orderTM (lua_State *L, const TValue *p1, const TValue *p2, TMS event) { if (!call_binTM(L, p1, p2, L->top, event)) return -1; /* no metamethod */ else return !l_isfalse(L->top); } static int l_strcmp (const TString *ls, const TString *rs) { const char *l = getstr(ls); size_t ll = ls->tsv.len; const char *r = getstr(rs); size_t lr = rs->tsv.len; for (;;) { int temp = strcoll(l, r); if (temp != 0) return temp; else { /* strings are equal up to a `\0' */ size_t len = strlen(l); /* index of first `\0' in both strings */ if (len == lr) /* r is finished? */ return (len == ll) ? 0 : 1; else if (len == ll) /* l is finished? */ return -1; /* l is smaller than r (because r is not finished) */ /* both strings longer than `len'; go on comparing (after the `\0') */ len++; l += len; ll -= len; r += len; lr -= len; } } } int luaV_lessthan (lua_State *L, const TValue *l, const TValue *r) { int res; if (ttisnumber(l) && ttisnumber(r)) return luai_numlt(L, nvalue(l), nvalue(r)); else if (ttisstring(l) && ttisstring(r)) return l_strcmp(rawtsvalue(l), rawtsvalue(r)) < 0; else if ((res = call_orderTM(L, l, r, TM_LT)) < 0) luaG_ordererror(L, l, r); return res; } int luaV_lessequal (lua_State *L, const TValue *l, const TValue *r) { int res; if (ttisnumber(l) && ttisnumber(r)) return luai_numle(L, nvalue(l), nvalue(r)); else if (ttisstring(l) && ttisstring(r)) return l_strcmp(rawtsvalue(l), rawtsvalue(r)) <= 0; else if ((res = call_orderTM(L, l, r, TM_LE)) >= 0) /* first try `le' */ return res; else if ((res = call_orderTM(L, r, l, TM_LT)) < 0) /* else try `lt' */ luaG_ordererror(L, l, r); return !res; } /* ** equality of Lua values. L == NULL means raw equality (no metamethods) */ int luaV_equalobj_ (lua_State *L, const TValue *t1, const TValue *t2) { const TValue *tm; lua_assert(ttisequal(t1, t2)); switch (ttype(t1)) { case LUA_TNIL: return 1; case LUA_TNUMBER: return luai_numeq(nvalue(t1), nvalue(t2)); case LUA_TBOOLEAN: return bvalue(t1) == bvalue(t2); /* true must be 1 !! */ case LUA_TLIGHTUSERDATA: return pvalue(t1) == pvalue(t2); case LUA_TLCF: return fvalue(t1) == fvalue(t2); case LUA_TSHRSTR: return eqshrstr(rawtsvalue(t1), rawtsvalue(t2)); case LUA_TLNGSTR: return luaS_eqlngstr(rawtsvalue(t1), rawtsvalue(t2)); case LUA_TUSERDATA: { if (uvalue(t1) == uvalue(t2)) return 1; else if (L == NULL) return 0; tm = get_equalTM(L, uvalue(t1)->metatable, uvalue(t2)->metatable, TM_EQ); break; /* will try TM */ } case LUA_TTABLE: { if (hvalue(t1) == hvalue(t2)) return 1; else if (L == NULL) return 0; tm = get_equalTM(L, hvalue(t1)->metatable, hvalue(t2)->metatable, TM_EQ); break; /* will try TM */ } default: lua_assert(iscollectable(t1)); return gcvalue(t1) == gcvalue(t2); } if (tm == NULL) return 0; /* no TM? */ callTM(L, tm, t1, t2, L->top, 1); /* call TM */ return !l_isfalse(L->top); } void luaV_concat (lua_State *L, int total) { lua_assert(total >= 2); do { StkId top = L->top; int n = 2; /* number of elements handled in this pass (at least 2) */ if (!(ttisstring(top-2) || ttisnumber(top-2)) || !tostring(L, top-1)) { if (!call_binTM(L, top-2, top-1, top-2, TM_CONCAT)) luaG_concaterror(L, top-2, top-1); } else if (tsvalue(top-1)->len == 0) /* second operand is empty? */ (void)tostring(L, top - 2); /* result is first operand */ else if (ttisstring(top-2) && tsvalue(top-2)->len == 0) { setobjs2s(L, top - 2, top - 1); /* result is second op. */ } else { /* at least two non-empty string values; get as many as possible */ size_t tl = tsvalue(top-1)->len; char *buffer; int i; /* collect total length */ for (i = 1; i < total && tostring(L, top-i-1); i++) { size_t l = tsvalue(top-i-1)->len; if (l >= (MAX_SIZET/sizeof(char)) - tl) luaG_runerror(L, "string length overflow"); tl += l; } buffer = luaZ_openspace(L, &G(L)->buff, tl); tl = 0; n = i; do { /* concat all strings */ size_t l = tsvalue(top-i)->len; memcpy(buffer+tl, svalue(top-i), l * sizeof(char)); tl += l; } while (--i > 0); setsvalue2s(L, top-n, luaS_newlstr(L, buffer, tl)); } total -= n-1; /* got 'n' strings to create 1 new */ L->top -= n-1; /* popped 'n' strings and pushed one */ } while (total > 1); /* repeat until only 1 result left */ } void luaV_objlen (lua_State *L, StkId ra, const TValue *rb) { const TValue *tm; switch (ttypenv(rb)) { case LUA_TTABLE: { Table *h = hvalue(rb); tm = fasttm(L, h->metatable, TM_LEN); if (tm) break; /* metamethod? break switch to call it */ setnvalue(ra, cast_num(luaH_getn(h))); /* else primitive len */ return; } case LUA_TSTRING: { setnvalue(ra, cast_num(tsvalue(rb)->len)); return; } default: { /* try metamethod */ tm = luaT_gettmbyobj(L, rb, TM_LEN); if (ttisnil(tm)) /* no metamethod? */ luaG_typeerror(L, rb, "get length of"); break; } } callTM(L, tm, rb, rb, ra, 1); } void luaV_arith (lua_State *L, StkId ra, const TValue *rb, const TValue *rc, TMS op) { TValue tempb, tempc; const TValue *b, *c; if ((b = luaV_tonumber(rb, &tempb)) != NULL && (c = luaV_tonumber(rc, &tempc)) != NULL) { lua_Number res = luaO_arith(op - TM_ADD + LUA_OPADD, nvalue(b), nvalue(c)); setnvalue(ra, res); } else if (!call_binTM(L, rb, rc, ra, op)) luaG_aritherror(L, rb, rc); } /* ** check whether cached closure in prototype 'p' may be reused, that is, ** whether there is a cached closure with the same upvalues needed by ** new closure to be created. */ static Closure *getcached (Proto *p, UpVal **encup, StkId base) { Closure *c = p->cache; if (c != NULL) { /* is there a cached closure? */ int nup = p->sizeupvalues; Upvaldesc *uv = p->upvalues; int i; for (i = 0; i < nup; i++) { /* check whether it has right upvalues */ TValue *v = uv[i].instack ? base + uv[i].idx : encup[uv[i].idx]->v; if (c->l.upvals[i]->v != v) return NULL; /* wrong upvalue; cannot reuse closure */ } } return c; /* return cached closure (or NULL if no cached closure) */ } /* ** create a new Lua closure, push it in the stack, and initialize ** its upvalues. Note that the call to 'luaC_barrierproto' must come ** before the assignment to 'p->cache', as the function needs the ** original value of that field. */ static void pushclosure (lua_State *L, Proto *p, UpVal **encup, StkId base, StkId ra) { int nup = p->sizeupvalues; Upvaldesc *uv = p->upvalues; int i; Closure *ncl = luaF_newLclosure(L, nup); ncl->l.p = p; setclLvalue(L, ra, ncl); /* anchor new closure in stack */ for (i = 0; i < nup; i++) { /* fill in its upvalues */ if (uv[i].instack) /* upvalue refers to local variable? */ ncl->l.upvals[i] = luaF_findupval(L, base + uv[i].idx); else /* get upvalue from enclosing function */ ncl->l.upvals[i] = encup[uv[i].idx]; } luaC_barrierproto(L, p, ncl); p->cache = ncl; /* save it on cache for reuse */ } /* ** finish execution of an opcode interrupted by an yield */ void luaV_finishOp (lua_State *L) { CallInfo *ci = L->ci; StkId base = ci->u.l.base; Instruction inst = *(ci->u.l.savedpc - 1); /* interrupted instruction */ OpCode op = GET_OPCODE(inst); switch (op) { /* finish its execution */ case OP_ADD: case OP_SUB: case OP_MUL: case OP_DIV: case OP_MOD: case OP_POW: case OP_UNM: case OP_LEN: case OP_GETTABUP: case OP_GETTABLE: case OP_SELF: { setobjs2s(L, base + GETARG_A(inst), --L->top); break; } case OP_LE: case OP_LT: case OP_EQ: { int res = !l_isfalse(L->top - 1); L->top--; /* metamethod should not be called when operand is K */ lua_assert(!ISK(GETARG_B(inst))); if (op == OP_LE && /* "<=" using "<" instead? */ ttisnil(luaT_gettmbyobj(L, base + GETARG_B(inst), TM_LE))) res = !res; /* invert result */ lua_assert(GET_OPCODE(*ci->u.l.savedpc) == OP_JMP); if (res != GETARG_A(inst)) /* condition failed? */ ci->u.l.savedpc++; /* skip jump instruction */ break; } case OP_CONCAT: { StkId top = L->top - 1; /* top when 'call_binTM' was called */ int b = GETARG_B(inst); /* first element to concatenate */ int total = cast_int(top - 1 - (base + b)); /* yet to concatenate */ setobj2s(L, top - 2, top); /* put TM result in proper position */ if (total > 1) { /* are there elements to concat? */ L->top = top - 1; /* top is one after last element (at top-2) */ luaV_concat(L, total); /* concat them (may yield again) */ } /* move final result to final position */ setobj2s(L, ci->u.l.base + GETARG_A(inst), L->top - 1); L->top = ci->top; /* restore top */ break; } case OP_TFORCALL: { lua_assert(GET_OPCODE(*ci->u.l.savedpc) == OP_TFORLOOP); L->top = ci->top; /* correct top */ break; } case OP_CALL: { if (GETARG_C(inst) - 1 >= 0) /* nresults >= 0? */ L->top = ci->top; /* adjust results */ break; } case OP_TAILCALL: case OP_SETTABUP: case OP_SETTABLE: break; default: lua_assert(0); } } /* ** some macros for common tasks in `luaV_execute' */ #if !defined luai_runtimecheck #define luai_runtimecheck(L, c) /* void */ #endif #define RA(i) (base+GETARG_A(i)) /* to be used after possible stack reallocation */ #define RB(i) check_exp(getBMode(GET_OPCODE(i)) == OpArgR, base+GETARG_B(i)) #define RC(i) check_exp(getCMode(GET_OPCODE(i)) == OpArgR, base+GETARG_C(i)) #define RKB(i) check_exp(getBMode(GET_OPCODE(i)) == OpArgK, \ ISK(GETARG_B(i)) ? k+INDEXK(GETARG_B(i)) : base+GETARG_B(i)) #define RKC(i) check_exp(getCMode(GET_OPCODE(i)) == OpArgK, \ ISK(GETARG_C(i)) ? k+INDEXK(GETARG_C(i)) : base+GETARG_C(i)) #define KBx(i) \ (k + (GETARG_Bx(i) != 0 ? GETARG_Bx(i) - 1 : GETARG_Ax(*ci->u.l.savedpc++))) /* execute a jump instruction */ #define dojump(ci,i,e) \ { int a = GETARG_A(i); \ if (a > 0) luaF_close(L, ci->u.l.base + a - 1); \ ci->u.l.savedpc += GETARG_sBx(i) + e; } /* for test instructions, execute the jump instruction that follows it */ #define donextjump(ci) { i = *ci->u.l.savedpc; dojump(ci, i, 1); } #define Protect(x) { {x;}; base = ci->u.l.base; } #define checkGC(L,c) \ Protect( luaC_condGC(L,{L->top = (c); /* limit of live values */ \ luaC_step(L); \ L->top = ci->top;}) /* restore top */ \ luai_threadyield(L); ) #define arith_op(op,tm) { \ TValue *rb = RKB(i); \ TValue *rc = RKC(i); \ if (ttisnumber(rb) && ttisnumber(rc)) { \ lua_Number nb = nvalue(rb), nc = nvalue(rc); \ setnvalue(ra, op(L, nb, nc)); \ } \ else { Protect(luaV_arith(L, ra, rb, rc, tm)); } } #define vmdispatch(o) switch(o) #define vmcase(l,b) case l: {b} break; #define vmcasenb(l,b) case l: {b} /* nb = no break */ void luaV_execute (lua_State *L) { CallInfo *ci = L->ci; LClosure *cl; TValue *k; StkId base; newframe: /* reentry point when frame changes (call/return) */ lua_assert(ci == L->ci); cl = clLvalue(ci->func); k = cl->p->k; base = ci->u.l.base; /* main loop of interpreter */ for (;;) { Instruction i = *(ci->u.l.savedpc++); StkId ra; if ((L->hookmask & (LUA_MASKLINE | LUA_MASKCOUNT)) && (--L->hookcount == 0 || L->hookmask & LUA_MASKLINE)) { Protect(traceexec(L)); } /* WARNING: several calls may realloc the stack and invalidate `ra' */ ra = RA(i); lua_assert(base == ci->u.l.base); lua_assert(base <= L->top && L->top < L->stack + L->stacksize); vmdispatch (GET_OPCODE(i)) { vmcase(OP_MOVE, setobjs2s(L, ra, RB(i)); ) vmcase(OP_LOADK, TValue *rb = k + GETARG_Bx(i); setobj2s(L, ra, rb); ) vmcase(OP_LOADKX, TValue *rb; lua_assert(GET_OPCODE(*ci->u.l.savedpc) == OP_EXTRAARG); rb = k + GETARG_Ax(*ci->u.l.savedpc++); setobj2s(L, ra, rb); ) vmcase(OP_LOADBOOL, setbvalue(ra, GETARG_B(i)); if (GETARG_C(i)) ci->u.l.savedpc++; /* skip next instruction (if C) */ ) vmcase(OP_LOADNIL, int b = GETARG_B(i); do { setnilvalue(ra++); } while (b--); ) vmcase(OP_GETUPVAL, int b = GETARG_B(i); setobj2s(L, ra, cl->upvals[b]->v); ) vmcase(OP_GETTABUP, int b = GETARG_B(i); Protect(luaV_gettable(L, cl->upvals[b]->v, RKC(i), ra)); ) vmcase(OP_GETTABLE, Protect(luaV_gettable(L, RB(i), RKC(i), ra)); ) vmcase(OP_SETTABUP, int a = GETARG_A(i); Protect(luaV_settable(L, cl->upvals[a]->v, RKB(i), RKC(i))); ) vmcase(OP_SETUPVAL, UpVal *uv = cl->upvals[GETARG_B(i)]; setobj(L, uv->v, ra); luaC_barrier(L, uv, ra); ) vmcase(OP_SETTABLE, Protect(luaV_settable(L, ra, RKB(i), RKC(i))); ) vmcase(OP_NEWTABLE, int b = GETARG_B(i); int c = GETARG_C(i); Table *t = luaH_new(L); sethvalue(L, ra, t); if (b != 0 || c != 0) luaH_resize(L, t, luaO_fb2int(b), luaO_fb2int(c)); checkGC(L, ra + 1); ) vmcase(OP_SELF, StkId rb = RB(i); setobjs2s(L, ra+1, rb); Protect(luaV_gettable(L, rb, RKC(i), ra)); ) vmcase(OP_ADD, arith_op(luai_numadd, TM_ADD); ) vmcase(OP_SUB, arith_op(luai_numsub, TM_SUB); ) vmcase(OP_MUL, arith_op(luai_nummul, TM_MUL); ) vmcase(OP_DIV, arith_op(luai_numdiv, TM_DIV); ) vmcase(OP_MOD, arith_op(luai_nummod, TM_MOD); ) vmcase(OP_POW, arith_op(luai_numpow, TM_POW); ) vmcase(OP_UNM, TValue *rb = RB(i); if (ttisnumber(rb)) { lua_Number nb = nvalue(rb); setnvalue(ra, luai_numunm(L, nb)); } else { Protect(luaV_arith(L, ra, rb, rb, TM_UNM)); } ) vmcase(OP_NOT, TValue *rb = RB(i); int res = l_isfalse(rb); /* next assignment may change this value */ setbvalue(ra, res); ) vmcase(OP_LEN, Protect(luaV_objlen(L, ra, RB(i))); ) vmcase(OP_CONCAT, int b = GETARG_B(i); int c = GETARG_C(i); StkId rb; L->top = base + c + 1; /* mark the end of concat operands */ Protect(luaV_concat(L, c - b + 1)); ra = RA(i); /* 'luav_concat' may invoke TMs and move the stack */ rb = b + base; setobjs2s(L, ra, rb); checkGC(L, (ra >= rb ? ra + 1 : rb)); L->top = ci->top; /* restore top */ ) vmcase(OP_JMP, dojump(ci, i, 0); ) vmcase(OP_EQ, TValue *rb = RKB(i); TValue *rc = RKC(i); Protect( if (cast_int(equalobj(L, rb, rc)) != GETARG_A(i)) ci->u.l.savedpc++; else donextjump(ci); ) ) vmcase(OP_LT, Protect( if (luaV_lessthan(L, RKB(i), RKC(i)) != GETARG_A(i)) ci->u.l.savedpc++; else donextjump(ci); ) ) vmcase(OP_LE, Protect( if (luaV_lessequal(L, RKB(i), RKC(i)) != GETARG_A(i)) ci->u.l.savedpc++; else donextjump(ci); ) ) vmcase(OP_TEST, if (GETARG_C(i) ? l_isfalse(ra) : !l_isfalse(ra)) ci->u.l.savedpc++; else donextjump(ci); ) vmcase(OP_TESTSET, TValue *rb = RB(i); if (GETARG_C(i) ? l_isfalse(rb) : !l_isfalse(rb)) ci->u.l.savedpc++; else { setobjs2s(L, ra, rb); donextjump(ci); } ) vmcase(OP_CALL, int b = GETARG_B(i); int nresults = GETARG_C(i) - 1; if (b != 0) L->top = ra+b; /* else previous instruction set top */ if (luaD_precall(L, ra, nresults)) { /* C function? */ if (nresults >= 0) L->top = ci->top; /* adjust results */ base = ci->u.l.base; } else { /* Lua function */ ci = L->ci; ci->callstatus |= CIST_REENTRY; goto newframe; /* restart luaV_execute over new Lua function */ } ) vmcase(OP_TAILCALL, int b = GETARG_B(i); if (b != 0) L->top = ra+b; /* else previous instruction set top */ lua_assert(GETARG_C(i) - 1 == LUA_MULTRET); if (luaD_precall(L, ra, LUA_MULTRET)) /* C function? */ base = ci->u.l.base; else { /* tail call: put called frame (n) in place of caller one (o) */ CallInfo *nci = L->ci; /* called frame */ CallInfo *oci = nci->previous; /* caller frame */ StkId nfunc = nci->func; /* called function */ StkId ofunc = oci->func; /* caller function */ /* last stack slot filled by 'precall' */ StkId lim = nci->u.l.base + getproto(nfunc)->numparams; int aux; /* close all upvalues from previous call */ if (cl->p->sizep > 0) luaF_close(L, oci->u.l.base); /* move new frame into old one */ for (aux = 0; nfunc + aux < lim; aux++) setobjs2s(L, ofunc + aux, nfunc + aux); oci->u.l.base = ofunc + (nci->u.l.base - nfunc); /* correct base */ oci->top = L->top = ofunc + (L->top - nfunc); /* correct top */ oci->u.l.savedpc = nci->u.l.savedpc; oci->callstatus |= CIST_TAIL; /* function was tail called */ ci = L->ci = oci; /* remove new frame */ lua_assert(L->top == oci->u.l.base + getproto(ofunc)->maxstacksize); goto newframe; /* restart luaV_execute over new Lua function */ } ) vmcasenb(OP_RETURN, int b = GETARG_B(i); if (b != 0) L->top = ra+b-1; if (cl->p->sizep > 0) luaF_close(L, base); b = luaD_poscall(L, ra); if (!(ci->callstatus & CIST_REENTRY)) /* 'ci' still the called one */ return; /* external invocation: return */ else { /* invocation via reentry: continue execution */ ci = L->ci; if (b) L->top = ci->top; lua_assert(isLua(ci)); lua_assert(GET_OPCODE(*((ci)->u.l.savedpc - 1)) == OP_CALL); goto newframe; /* restart luaV_execute over new Lua function */ } ) vmcase(OP_FORLOOP, lua_Number step = nvalue(ra+2); lua_Number idx = luai_numadd(L, nvalue(ra), step); /* increment index */ lua_Number limit = nvalue(ra+1); if (luai_numlt(L, 0, step) ? luai_numle(L, idx, limit) : luai_numle(L, limit, idx)) { ci->u.l.savedpc += GETARG_sBx(i); /* jump back */ setnvalue(ra, idx); /* update internal index... */ setnvalue(ra+3, idx); /* ...and external index */ } ) vmcase(OP_FORPREP, const TValue *init = ra; const TValue *plimit = ra+1; const TValue *pstep = ra+2; if (!tonumber(init, ra)) luaG_runerror(L, LUA_QL("for") " initial value must be a number"); else if (!tonumber(plimit, ra+1)) luaG_runerror(L, LUA_QL("for") " limit must be a number"); else if (!tonumber(pstep, ra+2)) luaG_runerror(L, LUA_QL("for") " step must be a number"); setnvalue(ra, luai_numsub(L, nvalue(ra), nvalue(pstep))); ci->u.l.savedpc += GETARG_sBx(i); ) vmcasenb(OP_TFORCALL, StkId cb = ra + 3; /* call base */ setobjs2s(L, cb+2, ra+2); setobjs2s(L, cb+1, ra+1); setobjs2s(L, cb, ra); L->top = cb + 3; /* func. + 2 args (state and index) */ Protect(luaD_call(L, cb, GETARG_C(i), 1)); L->top = ci->top; i = *(ci->u.l.savedpc++); /* go to next instruction */ ra = RA(i); lua_assert(GET_OPCODE(i) == OP_TFORLOOP); goto l_tforloop; ) vmcase(OP_TFORLOOP, l_tforloop: if (!ttisnil(ra + 1)) { /* continue loop? */ setobjs2s(L, ra, ra + 1); /* save control variable */ ci->u.l.savedpc += GETARG_sBx(i); /* jump back */ } ) vmcase(OP_SETLIST, int n = GETARG_B(i); int c = GETARG_C(i); int last; Table *h; if (n == 0) n = cast_int(L->top - ra) - 1; if (c == 0) { lua_assert(GET_OPCODE(*ci->u.l.savedpc) == OP_EXTRAARG); c = GETARG_Ax(*ci->u.l.savedpc++); } luai_runtimecheck(L, ttistable(ra)); h = hvalue(ra); last = ((c-1)*LFIELDS_PER_FLUSH) + n; if (last > h->sizearray) /* needs more space? */ luaH_resizearray(L, h, last); /* pre-allocate it at once */ for (; n > 0; n--) { TValue *val = ra+n; luaH_setint(L, h, last--, val); luaC_barrierback(L, obj2gco(h), val); } L->top = ci->top; /* correct top (in case of previous open call) */ ) vmcase(OP_CLOSURE, Proto *p = cl->p->p[GETARG_Bx(i)]; Closure *ncl = getcached(p, cl->upvals, base); /* cached closure */ if (ncl == NULL) /* no match? */ pushclosure(L, p, cl->upvals, base, ra); /* create a new one */ else setclLvalue(L, ra, ncl); /* push cashed closure */ checkGC(L, ra + 1); ) vmcase(OP_VARARG, int b = GETARG_B(i) - 1; int j; int n = cast_int(base - ci->func) - cl->p->numparams - 1; if (b < 0) { /* B == 0? */ b = n; /* get all var. arguments */ Protect(luaD_checkstack(L, n)); ra = RA(i); /* previous call may change the stack */ L->top = ra + n; } for (j = 0; j < b; j++) { if (j < n) { setobjs2s(L, ra + j, base - n + j); } else { setnilvalue(ra + j); } } ) vmcase(OP_EXTRAARG, lua_assert(0); ) } } } april-ann-0.4.1/lua/lua-5.2.2/src/lvm.h000066400000000000000000000027101263004425400171370ustar00rootroot00000000000000/* ** $Id: lvm.h,v 2.18 2013/01/08 14:06:55 roberto Exp $ ** Lua virtual machine ** See Copyright Notice in lua.h */ #ifndef lvm_h #define lvm_h #include "ldo.h" #include "lobject.h" #include "ltm.h" #define tostring(L,o) (ttisstring(o) || (luaV_tostring(L, o))) #define tonumber(o,n) (ttisnumber(o) || (((o) = luaV_tonumber(o,n)) != NULL)) #define equalobj(L,o1,o2) (ttisequal(o1, o2) && luaV_equalobj_(L, o1, o2)) #define luaV_rawequalobj(o1,o2) equalobj(NULL,o1,o2) /* not to called directly */ LUAI_FUNC int luaV_equalobj_ (lua_State *L, const TValue *t1, const TValue *t2); LUAI_FUNC int luaV_lessthan (lua_State *L, const TValue *l, const TValue *r); LUAI_FUNC int luaV_lessequal (lua_State *L, const TValue *l, const TValue *r); LUAI_FUNC const TValue *luaV_tonumber (const TValue *obj, TValue *n); LUAI_FUNC int luaV_tostring (lua_State *L, StkId obj); LUAI_FUNC void luaV_gettable (lua_State *L, const TValue *t, TValue *key, StkId val); LUAI_FUNC void luaV_settable (lua_State *L, const TValue *t, TValue *key, StkId val); LUAI_FUNC void luaV_finishOp (lua_State *L); LUAI_FUNC void luaV_execute (lua_State *L); LUAI_FUNC void luaV_concat (lua_State *L, int total); LUAI_FUNC void luaV_arith (lua_State *L, StkId ra, const TValue *rb, const TValue *rc, TMS op); LUAI_FUNC void luaV_objlen (lua_State *L, StkId ra, const TValue *rb); #endif april-ann-0.4.1/lua/lua-5.2.2/src/lzio.c000066400000000000000000000031251263004425400173120ustar00rootroot00000000000000/* ** $Id: lzio.c,v 1.35 2012/05/14 13:34:18 roberto Exp $ ** Buffered streams ** See Copyright Notice in lua.h */ #include #define lzio_c #define LUA_CORE #include "lua.h" #include "llimits.h" #include "lmem.h" #include "lstate.h" #include "lzio.h" int luaZ_fill (ZIO *z) { size_t size; lua_State *L = z->L; const char *buff; lua_unlock(L); buff = z->reader(L, z->data, &size); lua_lock(L); if (buff == NULL || size == 0) return EOZ; z->n = size - 1; /* discount char being returned */ z->p = buff; return cast_uchar(*(z->p++)); } void luaZ_init (lua_State *L, ZIO *z, lua_Reader reader, void *data) { z->L = L; z->reader = reader; z->data = data; z->n = 0; z->p = NULL; } /* --------------------------------------------------------------- read --- */ size_t luaZ_read (ZIO *z, void *b, size_t n) { while (n) { size_t m; if (z->n == 0) { /* no bytes in buffer? */ if (luaZ_fill(z) == EOZ) /* try to read more */ return n; /* no more input; return number of missing bytes */ else { z->n++; /* luaZ_fill consumed first byte; put it back */ z->p--; } } m = (n <= z->n) ? n : z->n; /* min. between n and z->n */ memcpy(b, z->p, m); z->n -= m; z->p += m; b = (char *)b + m; n -= m; } return 0; } /* ------------------------------------------------------------------------ */ char *luaZ_openspace (lua_State *L, Mbuffer *buff, size_t n) { if (n > buff->buffsize) { if (n < LUA_MINBUFFER) n = LUA_MINBUFFER; luaZ_resizebuffer(L, buff, n); } return buff->buffer; } april-ann-0.4.1/lua/lua-5.2.2/src/lzio.h000066400000000000000000000027121263004425400173200ustar00rootroot00000000000000/* ** $Id: lzio.h,v 1.26 2011/07/15 12:48:03 roberto Exp $ ** Buffered streams ** See Copyright Notice in lua.h */ #ifndef lzio_h #define lzio_h #include "lua.h" #include "lmem.h" #define EOZ (-1) /* end of stream */ typedef struct Zio ZIO; #define zgetc(z) (((z)->n--)>0 ? cast_uchar(*(z)->p++) : luaZ_fill(z)) typedef struct Mbuffer { char *buffer; size_t n; size_t buffsize; } Mbuffer; #define luaZ_initbuffer(L, buff) ((buff)->buffer = NULL, (buff)->buffsize = 0) #define luaZ_buffer(buff) ((buff)->buffer) #define luaZ_sizebuffer(buff) ((buff)->buffsize) #define luaZ_bufflen(buff) ((buff)->n) #define luaZ_resetbuffer(buff) ((buff)->n = 0) #define luaZ_resizebuffer(L, buff, size) \ (luaM_reallocvector(L, (buff)->buffer, (buff)->buffsize, size, char), \ (buff)->buffsize = size) #define luaZ_freebuffer(L, buff) luaZ_resizebuffer(L, buff, 0) LUAI_FUNC char *luaZ_openspace (lua_State *L, Mbuffer *buff, size_t n); LUAI_FUNC void luaZ_init (lua_State *L, ZIO *z, lua_Reader reader, void *data); LUAI_FUNC size_t luaZ_read (ZIO* z, void* b, size_t n); /* read next n bytes */ /* --------- Private Part ------------------ */ struct Zio { size_t n; /* bytes still unread */ const char *p; /* current position in buffer */ lua_Reader reader; /* reader function */ void* data; /* additional data */ lua_State *L; /* Lua state (for reader) */ }; LUAI_FUNC int luaZ_fill (ZIO *z); #endif april-ann-0.4.1/lua/man/000077500000000000000000000000001263004425400147315ustar00rootroot00000000000000april-ann-0.4.1/lua/man/man1/000077500000000000000000000000001263004425400155655ustar00rootroot00000000000000april-ann-0.4.1/lua/man/man1/lua.1000066400000000000000000000042341263004425400164330ustar00rootroot00000000000000.\" $Id: lua.man,v 1.13 2011/11/16 17:16:53 lhf Exp $ .TH LUA 1 "$Date: 2011/11/16 17:16:53 $" .SH NAME lua \- Lua interpreter .SH SYNOPSIS .B lua [ .I options ] [ .I script [ .I args ] ] .SH DESCRIPTION .B lua is the standalone Lua interpreter. It loads and executes Lua programs, either in textual source form or in precompiled binary form. (Precompiled binaries are output by .BR luac , the Lua compiler.) .B lua can be used as a batch interpreter and also interactively. .LP The given .I options are handled in order and then the Lua program in file .I script is loaded and executed. The given .I args are available to .I script as strings in a global table named .BR arg . If no options or arguments are given, then .B "\-v \-i" is assumed when the standard input is a terminal; otherwise, .B "\-" is assumed. .LP In interactive mode, .B lua prompts the user, reads lines from the standard input, and executes them as they are read. If a line does not contain a complete statement, then a secondary prompt is displayed and lines are read until a complete statement is formed or a syntax error is found. If a line starts with .BR '=' , then .B lua evaluates and displays the values of the expressions in the remainder of the line. .LP At the very start, before even handling the command line, .B lua checks the contents of the environment variables .B LUA_INIT_5_2 or .BR LUA_INIT , in that order. If the contents is of the form .RI '@ filename ', then .I filename is executed. Otherwise, the string is assumed to be a Lua statement and is executed. .SH OPTIONS .TP .BI \-e " stat" execute statement .IR stat . .TP .B \-i enter interactive mode after executing .IR script . .TP .BI \-l " name" execute the equivalent of .IB name =require(' name ') before executing .IR script . .TP .B \-v show version information. .TP .B \-E ignore environment variables. .TP .B \-\- stop handling options. .TP .B \- stop handling options and execute the standard input as a file. .SH "SEE ALSO" .BR luac (1) .br The documentation at lua.org, especially section 7 of the reference manual. .SH DIAGNOSTICS Error messages should be self explanatory. .SH AUTHORS R. Ierusalimschy, L. H. de Figueiredo, W. Celes .\" EOF april-ann-0.4.1/lua/man/man1/luac.1000066400000000000000000000057771263004425400166130ustar00rootroot00000000000000.\" $Id: luac.man,v 1.29 2011/11/16 13:53:40 lhf Exp $ .TH LUAC 1 "$Date: 2011/11/16 13:53:40 $" .SH NAME luac \- Lua compiler .SH SYNOPSIS .B luac [ .I options ] [ .I filenames ] .SH DESCRIPTION .B luac is the Lua compiler. It translates programs written in the Lua programming language into binary files containing precompiled chunks that can be later loaded and executed. .LP The main advantages of precompiling chunks are: faster loading, protecting source code from accidental user changes, and off-line syntax checking. Precompiling does not imply faster execution because in Lua chunks are always compiled into bytecodes before being executed. .B luac simply allows those bytecodes to be saved in a file for later execution. Precompiled chunks are not necessarily smaller than the corresponding source. The main goal in precompiling is faster loading. .LP In the command line, you can mix text files containing Lua source and binary files containing precompiled chunks. .B luac produces a single output file containing the combined bytecodes for all files given. Executing the combined file is equivalent to executing the given files. By default, the output file is named .BR luac.out , but you can change this with the .B \-o option. .LP Precompiled chunks are .I not portable across different architectures. Moreover, the internal format of precompiled chunks is likely to change when a new version of Lua is released. Make sure you save the source files of all Lua programs that you precompile. .LP .SH OPTIONS .TP .B \-l produce a listing of the compiled bytecode for Lua's virtual machine. Listing bytecodes is useful to learn about Lua's virtual machine. If no files are given, then .B luac loads .B luac.out and lists its contents. Use .B \-l \-l for a full listing. .TP .BI \-o " file" output to .IR file , instead of the default .BR luac.out . (You can use .B "'\-'" for standard output, but not on platforms that open standard output in text mode.) The output file may be one of the given files because all files are loaded before the output file is written. Be careful not to overwrite precious files. .TP .B \-p load files but do not generate any output file. Used mainly for syntax checking and for testing precompiled chunks: corrupted files will probably generate errors when loaded. If no files are given, then .B luac loads .B luac.out and tests its contents. No messages are displayed if the file loads without errors. .TP .B \-s strip debug information before writing the output file. This saves some space in very large chunks, but if errors occur when running a stripped chunk, then the error messages may not contain the full information they usually do. In particular, line numbers and names of local variables are lost. .TP .B \-v show version information. .TP .B \-\- stop handling options. .TP .B \- stop handling options and process standard input. .SH "SEE ALSO" .BR lua (1) .br The documentation at lua.org. .SH DIAGNOSTICS Error messages should be self explanatory. .SH AUTHORS R. Ierusalimschy, L. H. de Figueiredo, W. Celes .\" EOF april-ann-0.4.1/luapkg/000077500000000000000000000000001263004425400146605ustar00rootroot00000000000000april-ann-0.4.1/makefile000066400000000000000000000151231263004425400150770ustar00rootroot00000000000000LUAVER = 5.2 export PREFIX = /usr UNAME := $(shell uname) LINUX_SUFIX := $(shell ( ldconfig -p 2>/dev/null | grep libmkl_core > /dev/null && echo "mkl" ) || ( ls /opt/MKL/lib/libmkl_core.so 2> /dev/null > /dev/null && echo "mkl" ) || ( ldconfig -p 2>/dev/null | grep libatlas > /dev/null && echo "atlas" ) || echo "") ifeq ("$(UNAME)","Darwin") # homebrew ifneq ("$(wildcard /usr/local/include/lua.h)","") DARWIN_SUFIX = homebrew PREFIX = /usr/local endif # macports ifneq ("$(wildcard /opt/local/include/lua.h)","") DARWIN_SUFIX = macports PREFIX = /opt/local endif endif INCLUDE := $(PREFIX)/include LIB := $(PREFIX)/lib LUALIB := $(PREFIX)/lib/lua/$(LUAVER) LUAMOD := $(PREFIX)/share/lua/$(LUAVER) BIN := $(PREFIX)/bin ALL: auto-release ########################## AUTOMACTIC SECTION ############################ auto-release: @echo "System $(UNAME)" @make system-release-$(UNAME) auto-debug: @echo "System $(UNAME)" @make system-debug-$(UNAME) auto-test-debug: @echo "System $(UNAME)" @make system-test-debug-$(UNAME) # RELEASE system-release-Linux: check_linux_release @echo "Sufix $(LINUX_SUFIX)" @make release-$(LINUX_SUFIX) system-release-Darwin: check_darwin_release @echo "Sufix $(DARWIN_SUFIX)" @make release-$(DARWIN_SUFIX) # DEBUG system-debug-Linux: check_linux_release @echo "Sufix $(LINUX_SUFIX)" @make debug-$(LINUX_SUFIX) system-debug-Darwin: check_darwin_release @echo "Sufix $(DARWIN_SUFIX)" @make debug-$(DARWIN_SUFIX) # TEST-DEBUG system-test-debug-Linux: check_linux_release @echo "Sufix $(LINUX_SUFIX)" @make test-debug-$(LINUX_SUFIX) system-test-debug-Darwin: check_darwin_release @echo "Sufix $(DARWIN_SUFIX)" @make test-debug-$(DARWIN_SUFIX) # CHECK check_linux_release: ifeq ("$(LINUX_SUFIX)", "") @echo "Impossible to detect the proper release!" @exit 1 endif check_darwin_release: ifeq ("$(DARWIN_SUFIX)", "") @echo "Impossible to detect macports or homebrew!" @exit 2 endif ############################################################################# release: auto-release debug: auto-debug test: auto-test-debug document: rm -Rf doxygen_doc build_doc lua profile_build_scripts/build_release_atlas.lua document performance: april-ann TEST/PERFORMANCE/register_performance.lua TEST/PERFORMANCE/matrix/test.lua ############################################################################# # TEST with OMP and ATLAS test-debug-atlas: debug-atlas lua profile_build_scripts/build_debug_atlas.lua test # TEST without OMP and ATLAS test-debug-no-omp: debug-no-omp lua profile_build_scripts/build_debug_no_omp.lua test # TEST for DARWIN MACPORTS test-debug-macports: debug-macports lua profile_build_scripts/build_debug_macports.lua test # TEST for DARWIN HOMEBREW test-debug-homebrew: debug-homebrew lua profile_build_scripts/build_debug_homebrew.lua test # TEST with OMP and MKL test-debug-mkl: debug-mkl lua profile_build_scripts/build_debug_mkl.lua test # TEST with CUDA and MKL test-debug-cuda-mkl: debug-cuda-mkl lua profile_build_scripts/build_debug_cuda_and_mkl.lua test # TEST for raspberry-pi (subset of packages) test-debug-pi: debug-pi lua profile_build_scripts/build_debug_pi.lua test ############################################################################# # RELEASE for DARWIN MACPORTS release-macports: lua profile_build_scripts/build_release_macports.lua # RELEASE for DARWIN HOMEBREW release-homebrew: lua profile_build_scripts/build_release_homebrew.lua # RELEASE with OMP and MKL release-mkl: lua profile_build_scripts/build_release_mkl.lua # RELEASE with OMP and ATLAS release-atlas: lua profile_build_scripts/build_release_atlas.lua # RELEASE with CUDA and MKL release-cuda-mkl: lua profile_build_scripts/build_release_cuda_and_mkl.lua # RELEASE for raspberry-pi (subset of pacakges) release-pi: lua profile_build_scripts/build_release_pi.lua # RELEASE without OMP and ATLAS release-no-omp: lua profile_build_scripts/build_release_no_omp.lua ############################################################################# # DEBUG for DARWIN MACPORTS debug-macports: lua profile_build_scripts/build_debug_macports.lua # DEBUG for DARWIN HOMEBREW debug-homebrew: lua profile_build_scripts/build_debug_homebrew.lua # DEBUG with OMP and MKL debug-mkl: lua profile_build_scripts/build_debug_mkl.lua # DEBUG with OMP and ATLAS debug-atlas: lua profile_build_scripts/build_debug_atlas.lua # DEBUG without OMP and ATLAS debug-no-omp: lua profile_build_scripts/build_debug_no_omp.lua # DEBUG with CUDA and MKL debug-cuda-mkl: lua profile_build_scripts/build_debug_cuda_and_mkl.lua # DEBUG for raspberry-pi (subset of packages) debug-pi: lua profile_build_scripts/build_debug_pi.lua ############################################################################# INCLUDE_NO_WS := $(shell echo "$(INCLUDE)" | sed 's/ //g') LIB_NO_WS := $(shell echo "$(LIB)" | sed 's/ //g') LUALIB_NO_WS := $(shell echo "$(LUALIB)" | sed 's/ //g') LUAMOD_NO_WS := $(shell echo "$(LUAMOD)" | sed 's/ //g') BIN_NO_WS := $(shell echo "$(BIN)" | sed 's/ //g') check-env-vars: ifneq ("$(INCLUDE_NO_WS)","$(INCLUDE)") @echo "Unable to work with whitespaces in PREFIX, INCLUDE, LIB, LUALIB, LUAMOD, BIN env vars" @exit 3 endif ifneq ("$(LIB_NO_WS)","$(LIB)") @echo "Unable to work with whitespaces in PREFIX, INCLUDE, LIB, LUALIB, LUAMOD, BIN env vars" @exit 4 endif ifneq ("$(LUALIB_NO_WS)","$(LUALIB)") @echo "Unable to work with whitespaces in PREFIX, INCLUDE, LIB, LUALIB, LUAMOD, BIN env vars" @exit 5 endif ifneq ("$(LUAMOD_NO_WS)","$(LUAMOD)") @echo "Unable to work with whitespaces in PREFIX, INCLUDE, LIB, LUALIB, LUAMOD, BIN env vars" @exit 6 endif ifneq ("$(BIN_NO_WS)","$(BIN)") @echo "Unable to work with whitespaces in PREFIX, INCLUDE, LIB, LUALIB, LUAMOD, BIN env vars" @exit 7 endif clean: ./clean.sh install: check-env-vars uninstall @mkdir -p $(LUAMOD) @mkdir -p $(LUALIB) rsync -r tools/ $(LUAMOD)/april_tools @mkdir -p $(INCLUDE)/april-ann install -m 444 include/april-ann/* $(INCLUDE)/april-ann install -m 444 include/april-ann.h $(INCLUDE)/april-ann.h install .april-ann.pc $(LIB)/pkgconfig/april-ann.pc install lib/libapril-ann.a $(LIB) install lib/libapril-ann.so $(LIB) install lib/aprilann.so $(LUALIB) install bin/april-ann $(BIN) install lua/bin/lua $(BIN)/lua$(LUAVER)-april uninstall: check-env-vars @rm -Rf $(INCLUDE)/april-ann @rm -Rf $(LUAMOD)/april_tools @rm -f $(INCLUDE)/april-ann.h @rm -f $(LUALIB)/aprilann.so @rm -f $(LIB)/libapril-ann.a @rm -f $(LIB)/libapril-ann.so @rm -f $(LIB)/pkgconfig/april-ann.pc @rm -f $(BIN)/april-ann @rm -f $(BIN)/lua-$(LUAVER)-april ############################################################################## .PHONY: all april-ann-0.4.1/packages/000077500000000000000000000000001263004425400151535ustar00rootroot00000000000000april-ann-0.4.1/packages/ann/000077500000000000000000000000001263004425400157275ustar00rootroot00000000000000april-ann-0.4.1/packages/ann/ann/000077500000000000000000000000001263004425400165035ustar00rootroot00000000000000april-ann-0.4.1/packages/ann/ann/binding/000077500000000000000000000000001263004425400201155ustar00rootroot00000000000000april-ann-0.4.1/packages/ann/ann/binding/bind_ann_base.bak000066400000000000000000000502001263004425400233330ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "bind_activation_function.h" #include "bind_matrix.h" #include "bind_mtrand.h" //BIND_END //BIND_HEADER_H #include "ann.h" #include "connection.h" #include "all_all_connection.h" #include "bias_connection.h" #include "action.h" #include "dot_product_action.h" #include "forward_bias_action.h" #include "activations_action.h" #include "actunit.h" #include "errorfunc.h" #include "bind_trainablesuper.h" #include "bind_function_interface.h" #include "trainsuper.h" using namespace Trainable; using namespace ANN; using namespace Functions; //BIND_END //BIND_LUACLASSNAME TrainableSupervised __trainable__ //BIND_LUACLASSNAME ANNBase ann.__base__ //BIND_CPP_CLASS ANNBase //BIND_SUBCLASS_OF ANNBase TrainableSupervised ////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME ActivationUnits ann.units.__base__ //BIND_LUACLASSNAME RealActivationUnits ann.units.real_cod //BIND_CPP_CLASS ActivationUnits //BIND_CPP_CLASS RealActivationUnits //BIND_SUBCLASS_OF RealActivationUnits ActivationUnits //BIND_CONSTRUCTOR ActivationUnits { LUABIND_ERROR("Abstract class!!!\n"); } //BIND_END //BIND_METHOD ActivationUnits num_neurons { LUABIND_RETURN(uint, obj->numNeurons()); } //BIND_END //BIND_METHOD ActivationUnits set_sparse { bool v; LUABIND_CHECK_ARGN(==,1); LUABIND_GET_PARAMETER(1, bool, v); obj->setSparse(v); } //BIND_END //BIND_METHOD ActivationUnits clone { LUABIND_CHECK_ARGN(>=,1); LUABIND_CHECK_ARGN(<=,2); ANNBase *ann; const char *type; LUABIND_GET_PARAMETER(1, ANNBase, ann); LUABIND_GET_OPTIONAL_PARAMETER(2, string, type, 0); ActivationUnitsType type_enum = HIDDEN_TYPE; if (type == 0) type_enum = obj->getType(); else if (strcmp(type, "inputs") == 0) type_enum = INPUTS_TYPE; else if (strcmp(type, "outputs") == 0) type_enum = OUTPUTS_TYPE; ActivationUnits *units = obj->clone(ann->getConfReference()); units->setType(type_enum); ann->registerActivationUnits(units); if (type_enum == INPUTS_TYPE) ann->registerInput(units); else if (type_enum == OUTPUTS_TYPE) ann->registerOutput(units); LUABIND_RETURN(ActivationUnits, units); } //BIND_END ////////////////////////////////////////////////////////////////// //BIND_CONSTRUCTOR RealActivationUnits //DOC_BEGIN // ann.units.real{ size = ..., ann = ..., type = (inputs, hidden, outputs) } /// Create a real activation units layer /// @param size The number of neurons /// @param ann The ANN which belongs /// @param type The type, could be inputs, hidden, outputs //DOC_END { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "size", "ann", "type", 0); unsigned int size; ANNBase *ann; const char *type; ActivationUnitsType type_enum = HIDDEN_TYPE; LUABIND_GET_TABLE_PARAMETER(1, size, uint, size); LUABIND_GET_TABLE_PARAMETER(1, ann, ANNBase, ann); LUABIND_GET_TABLE_PARAMETER(1, type, string, type); if (strcmp(type, "inputs")!=0 && strcmp(type, "hidden")!=0 && strcmp(type, "outputs")!=0) { LUABIND_FERROR1("Incorrect type '%s'!!\n", type); } if (strcmp(type, "inputs") == 0) type_enum = INPUTS_TYPE; else if (strcmp(type, "outputs") == 0) type_enum = OUTPUTS_TYPE; obj = new RealActivationUnits(size, ann->getConfReference(), type_enum, type_enum != INPUTS_TYPE); ann->registerActivationUnits(obj); if (type_enum == INPUTS_TYPE) ann->registerInput(obj); else if (type_enum == OUTPUTS_TYPE) ann->registerOutput(obj); LUABIND_RETURN(RealActivationUnits, obj); } //BIND_END //////////////////////////////////////////////// //BIND_CONSTRUCTOR ANNBase { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD ANNBase get_num_weights { LUABIND_RETURN(uint, obj->getNumWeights()); } //BIND_END //BIND_METHOD ANNBase release_output { obj->releaseOutput(); } //BIND_END //BIND_METHOD ANNBase register_action { Action *action; LUABIND_GET_PARAMETER(1, Action, action); obj->registerAction(action); LUABIND_RETURN(Action, action); } //BIND_END //BIND_METHOD ANNBase register_input { ActivationUnits *actu; LUABIND_GET_PARAMETER(1, ActivationUnits, actu); obj->registerInput(actu); } //BIND_END //BIND_METHOD ANNBase register_output { ActivationUnits *actu; LUABIND_GET_PARAMETER(1, ActivationUnits, actu); obj->registerOutput(actu); } //BIND_END //BIND_METHOD ANNBase set_use_cuda { bool use_cuda, pinned; LUABIND_GET_PARAMETER(1, bool, use_cuda); LUABIND_GET_OPTIONAL_PARAMETER(2, bool, pinned, true); obj->setUseCuda(use_cuda, pinned); } //BIND_END //BIND_METHOD ANNBase get_layer_connections { unsigned int layer; LUABIND_GET_PARAMETER(1, uint, layer); if (layer < 1) LUABIND_ERROR("First layer is numbered with 1"); LUABIND_RETURN(Connections, obj->getLayerConnections(layer-1)); } //BIND_END //BIND_METHOD ANNBase get_layer_activations { unsigned int layer; LUABIND_GET_PARAMETER(1, uint, layer); if (layer < 1) LUABIND_ERROR("First layer is numbered with 1"); LUABIND_RETURN(ActivationUnits, obj->getLayerActivations(layer-1)); } //BIND_END //BIND_METHOD ANNBase get_action { unsigned int idx; LUABIND_GET_PARAMETER(1, uint, idx); if (idx < 1) LUABIND_ERROR("First action is numbered with 1"); LUABIND_RETURN(Action, obj->getAction(idx-1)); } //BIND_END //BIND_METHOD ANNBase get_layer_connections_size { LUABIND_RETURN(uint, obj->getLayerConnectionsSize()); } //BIND_END //BIND_METHOD ANNBase get_layer_activations_size { LUABIND_RETURN(uint, obj->getLayerActivationsSize()); } //BIND_END //BIND_METHOD ANNBase get_layer_connections_vector { unsigned int sz = obj->getLayerConnectionsSize(); lua_createtable(L, static_cast(sz), 0); for (unsigned int i=0; igetLayerConnections(i); lua_pushConnections(L, cnn); lua_rawseti(L, -2, i+1); } LUABIND_RETURN_FROM_STACK(1); } //BIND_END //BIND_METHOD ANNBase get_layer_activations_vector { unsigned int sz = obj->getLayerActivationsSize(); lua_createtable(L, static_cast(sz), 0); for (unsigned int i=0; igetLayerActivations(i); lua_pushActivationUnits(L, units); lua_rawseti(L, -2, i+1); } LUABIND_RETURN_FROM_STACK(1); } //BIND_END //BIND_METHOD ANNBase weights { MatrixFloat *weights = 0; MatrixFloat *old_weights = 0; unsigned int sz = obj->copyWeightsTo(&weights, &old_weights); LUABIND_RETURN(MatrixFloat, weights); LUABIND_RETURN(MatrixFloat, old_weights); LUABIND_RETURN(uint, sz); } //BIND_END ///////////////////////////////////////////////////// //BIND_LUACLASSNAME Action ann.actions.__base__ //BIND_CPP_CLASS Action //BIND_CONSTRUCTOR Action { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD Action set_option { const char *name; double value; LUABIND_GET_PARAMETER(1, string, name); LUABIND_GET_PARAMETER(2, double, value); obj->setOption(name, value); } //BIND_END //BIND_METHOD Action get_option { const char *name; LUABIND_GET_PARAMETER(1, string, name); LUABIND_RETURN(double, obj->getOption(name)); } //BIND_END //BIND_METHOD Action has_option { const char *name; LUABIND_GET_PARAMETER(1, string, name); LUABIND_RETURN(bool, obj->hasOption(name)); } //BIND_END ////////////////////////////////////////////////////// //BIND_LUACLASSNAME ForwardBiasAction ann.actions.forward_bias //BIND_CPP_CLASS ForwardBiasAction //BIND_SUBCLASS_OF ForwardBiasAction Action //BIND_CONSTRUCTOR ForwardBiasAction { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "ann", "output", "connections", 0); ActivationUnits *output; Connections *conn; ANNBase *ann; LUABIND_GET_TABLE_PARAMETER(1, output, ActivationUnits, output); LUABIND_GET_TABLE_PARAMETER(1, connections, Connections, conn); LUABIND_GET_TABLE_PARAMETER(1, ann, ANNBase, ann); obj = new ForwardBiasAction(ann->getConfReference(), output, conn); ann->registerAction(obj); LUABIND_RETURN(ForwardBiasAction, obj); } //BIND_END ////////////////////////////////////////////////////// //BIND_LUACLASSNAME DotProductAction ann.actions.dot_product //BIND_CPP_CLASS DotProductAction //BIND_SUBCLASS_OF DotProductAction Action //BIND_CONSTRUCTOR DotProductAction { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "ann", "input", "output", "connections", "transpose", 0); ActivationUnits *input; ActivationUnits *output; Connections *conn; ANNBase *ann; bool transpose; LUABIND_GET_TABLE_PARAMETER(1, input, ActivationUnits, input); LUABIND_GET_TABLE_PARAMETER(1, output, ActivationUnits, output); LUABIND_GET_TABLE_PARAMETER(1, connections, Connections, conn); LUABIND_GET_TABLE_PARAMETER(1, ann, ANNBase, ann); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, transpose, bool, transpose, false); obj = new DotProductAction(ann->getConfReference(), input, output, conn, transpose); ann->registerAction(obj); LUABIND_RETURN(DotProductAction, obj); } //BIND_END ////////////////////////////////////////////////////// //BIND_LUACLASSNAME ActivationsAction ann.actions.activations //BIND_CPP_CLASS ActivationsAction //BIND_SUBCLASS_OF ActivationsAction Action //BIND_CONSTRUCTOR ActivationsAction { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "ann", "actfunc", "output", 0); ActivationUnits *output; ActivationFunction *actfunc; ANNBase *ann; LUABIND_GET_TABLE_PARAMETER(1, output, ActivationUnits, output); LUABIND_GET_TABLE_PARAMETER(1, actfunc, ActivationFunction, actfunc); LUABIND_GET_TABLE_PARAMETER(1, ann, ANNBase, ann); obj = new ActivationsAction(ann->getConfReference(), output, actfunc); ann->registerAction(obj); LUABIND_RETURN(ActivationsAction, obj); } //BIND_END ////////////////////////////////////////////////////// //BIND_LUACLASSNAME ErrorFunction ann.error_functions.__base__ //BIND_CPP_CLASS ErrorFunction //BIND_CONSTRUCTOR ErrorFunction { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_LUACLASSNAME MSE ann.error_functions.mse //BIND_CPP_CLASS MSE //BIND_SUBCLASS_OF MSE ErrorFunction //BIND_CONSTRUCTOR MSE { obj = new MSE(); LUABIND_RETURN(MSE, obj); } //BIND_END //BIND_LUACLASSNAME Tanh ann.error_functions.tanh //BIND_CPP_CLASS Tanh //BIND_SUBCLASS_OF Tanh ErrorFunction //BIND_CONSTRUCTOR Tanh { obj = new Tanh(); LUABIND_RETURN(Tanh, obj); } //BIND_END //BIND_LUACLASSNAME CrossEntropy ann.error_functions.cross_entropy //BIND_CPP_CLASS CrossEntropy //BIND_SUBCLASS_OF CrossEntropy ErrorFunction //BIND_CONSTRUCTOR CrossEntropy { obj = new CrossEntropy(); LUABIND_RETURN(CrossEntropy, obj); } //BIND_END //BIND_LUACLASSNAME LogisticCrossEntropy ann.error_functions.logistic_cross_entropy //BIND_CPP_CLASS LogisticCrossEntropy //BIND_SUBCLASS_OF LogisticCrossEntropy ErrorFunction //BIND_CONSTRUCTOR LogisticCrossEntropy { obj = new LogisticCrossEntropy(); LUABIND_RETURN(LogisticCrossEntropy, obj); } //BIND_END //BIND_LUACLASSNAME FullCrossEntropy ann.error_functions.full_cross_entropy //BIND_CPP_CLASS FullCrossEntropy //BIND_SUBCLASS_OF FullCrossEntropy ErrorFunction //BIND_CONSTRUCTOR FullCrossEntropy { obj = new FullCrossEntropy(); LUABIND_RETURN(FullCrossEntropy, obj); } //BIND_END //BIND_LUACLASSNAME FullLogisticCrossEntropy ann.error_functions.full_logistic_cross_entropy //BIND_CPP_CLASS FullLogisticCrossEntropy //BIND_SUBCLASS_OF FullLogisticCrossEntropy ErrorFunction //BIND_CONSTRUCTOR FullLogisticCrossEntropy { obj = new FullLogisticCrossEntropy(); LUABIND_RETURN(FullLogisticCrossEntropy, obj); } //BIND_END //BIND_LUACLASSNAME LocalFMeasure ann.error_functions.local_fmeasure //BIND_CPP_CLASS LocalFMeasure //BIND_SUBCLASS_OF LocalFMeasure ErrorFunction //BIND_CONSTRUCTOR LocalFMeasure { obj = new LocalFMeasure(); LUABIND_RETURN(LocalFMeasure, obj); } //BIND_END /////////////////////////////////////////////////// //BIND_LUACLASSNAME Connections ann.connections.__base__ //BIND_CPP_CLASS Connections //BIND_CONSTRUCTOR Connections { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD Connections clone { LUABIND_CHECK_ARGN(==,1); ANNBase *ann; LUABIND_GET_PARAMETER(1, ANNBase, ann); Connections *cnn = obj->clone(); ann->registerConnections(cnn); LUABIND_RETURN(Connections, cnn); } //BIND_END //BIND_METHOD Connections load { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1,table); check_table_fields(L, 1, "w", "oldw", "first_pos", "column_size", 0); unsigned int first_pos, column_size; MatrixFloat *w, *oldw; LUABIND_GET_TABLE_PARAMETER(1, w, MatrixFloat, w); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, oldw, MatrixFloat, oldw, w); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, first_pos, uint, first_pos, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, column_size, uint, column_size, obj->getNumInputs()); LUABIND_RETURN(uint, obj->loadWeights(w, oldw, first_pos, column_size)); } //BIND_END //BIND_METHOD Connections weights { LUABIND_CHECK_ARGN(<=,1); LUABIND_CHECK_ARGN(>=,0); int nargs; LUABIND_TABLE_GETN(1, nargs); unsigned int first_pos=0, column_size=obj->getNumInputs(); MatrixFloat *w=0, *oldw=0; if (nargs == 1) { LUABIND_CHECK_PARAMETER(1,table); check_table_fields(L, 1, "w", "oldw", "first_pos", "column_size", 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, w, MatrixFloat, w, w); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, oldw, MatrixFloat, oldw, oldw); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, first_pos, uint, first_pos, first_pos); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, column_size, uint, column_size, column_size); } int size = static_cast(obj->size()); if (!w) w = new MatrixFloat(1, first_pos + size); if (!oldw) oldw = new MatrixFloat(1, w->size); if (first_pos + obj->size() > static_cast(w->size) || first_pos + obj->size() > static_cast(oldw->size) ) LUABIND_ERROR("Incorrect matrix size!!\n"); unsigned int sz = obj->copyWeightsTo(w, oldw, first_pos, column_size); LUABIND_RETURN(MatrixFloat, w); LUABIND_RETURN(MatrixFloat, oldw); LUABIND_RETURN(uint, sz); } //BIND_END //BIND_METHOD Connections size { LUABIND_RETURN(uint, obj->size()); } //BIND_END //BIND_METHOD Connections randomize_weights { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "random", "inf", "sup", "use_fanin", 0); MTRand *rnd; float inf, sup; bool use_fanin; LUABIND_GET_TABLE_PARAMETER(1, random, MTRand, rnd); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, inf, float, inf, -1.0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, sup, float, sup, 1.0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, use_fanin, bool, use_fanin, false); obj->randomizeWeights(rnd, inf, sup, use_fanin); } //BIND_END //////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME AllAllConnections ann.connections.all_all //BIND_CPP_CLASS AllAllConnections //BIND_SUBCLASS_OF AllAllConnections Connections //BIND_CONSTRUCTOR AllAllConnections { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "input_size", "output_size", "ann", "w", "oldw", "first_pos", "column_size", 0); MatrixFloat *w, *oldw; unsigned int input_size, output_size, first_pos, column_size; ANNBase *ann; LUABIND_GET_TABLE_PARAMETER(1, input_size, uint, input_size); LUABIND_GET_TABLE_PARAMETER(1, output_size, uint, output_size); LUABIND_GET_TABLE_PARAMETER(1, ann, ANNBase, ann); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, w, MatrixFloat, w, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, oldw, MatrixFloat, oldw, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, first_pos, uint, first_pos, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, column_size, uint, column_size, input_size); if (oldw && !w) LUABIND_ERROR("Parameter w is mandatory with oldw!!!\n"); obj=new AllAllConnections(input_size, output_size); ann->registerConnections(obj); if (w) obj->loadWeights(w, oldw, first_pos, column_size); LUABIND_RETURN(AllAllConnections, obj); } //BIND_END //BIND_LUACLASSNAME BiasConnections ann.connections.bias //BIND_CPP_CLASS BiasConnections //BIND_SUBCLASS_OF BiasConnections Connections //BIND_CONSTRUCTOR BiasConnections { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "size", "ann", "w", "oldw", "first_pos", "column_size", 0); MatrixFloat *w, *oldw; unsigned int size, first_pos, column_size; ANNBase *ann; LUABIND_GET_TABLE_PARAMETER(1, size, uint, size); LUABIND_GET_TABLE_PARAMETER(1, ann, ANNBase, ann); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, w, MatrixFloat, w, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, oldw, MatrixFloat, oldw, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, first_pos, uint, first_pos, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, column_size, uint, column_size, 1); if (oldw && !w) LUABIND_ERROR("Parameter w is mandatory with oldw!!!\n"); obj=new BiasConnections(size); ann->registerConnections(obj); if (w) obj->loadWeights(w, oldw, first_pos, column_size); LUABIND_RETURN(BiasConnections, obj); } //BIND_END ///////////////////////////////////////////////////// //BIND_LUACLASSNAME TimeSeriesErrorFunction ann.time_series_error_functions.__base__ //BIND_CPP_CLASS TimeSeriesErrorFunction //BIND_CONSTRUCTOR TimeSeriesErrorFunction { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD TimeSeriesErrorFunction computeErrorFromTimeSerie { float *outputs; float *target_outputs; unsigned int output_size; LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "outputs", "target_outputs", 0); lua_getfield(L, 1, "outputs"); LUABIND_TABLE_GETN(-1, output_size); outputs = new float[output_size]; LUABIND_TABLE_TO_VECTOR(-1, float, outputs, output_size); lua_pop(L, 1); lua_getfield(L, 1, "target_outputs"); unsigned int aux; LUABIND_TABLE_GETN(-1, aux); if (aux != output_size) LUABIND_ERROR ("outputs and target_outputs sizes are diferent!!!\n"); target_outputs = new float[output_size]; LUABIND_TABLE_TO_VECTOR(-1, float, target_outputs, output_size); lua_pop(L, 1); LUABIND_RETURN(float, obj->computeErrorFromTimeSerie(outputs, target_outputs, output_size)); delete[] outputs; delete[] target_outputs; } //BIND_END //////////////////////////////////////////////////// //BIND_LUACLASSNAME NormalizedRootMSE ann.time_series_error_functions.nrmse //BIND_CPP_CLASS NormalizedRootMSE //BIND_SUBCLASS_OF NormalizedRootMSE TimeSeriesErrorFunction //BIND_CONSTRUCTOR NormalizedRootMSE { obj = new NormalizedRootMSE(); LUABIND_RETURN(NormalizedRootMSE, obj); } //BIND_END //////////////////////////////////////////////////// //BIND_LUACLASSNAME RootMSE ann.time_series_error_functions.rmse //BIND_CPP_CLASS RootMSE //BIND_SUBCLASS_OF RootMSE TimeSeriesErrorFunction //BIND_CONSTRUCTOR RootMSE { obj = new RootMSE(); LUABIND_RETURN(RootMSE, obj); } //BIND_END //////////////////////////////////////////////////// //BIND_LUACLASSNAME AbsoluteError ann.time_series_error_functions.absolute_error //BIND_CPP_CLASS AbsoluteError //BIND_SUBCLASS_OF AbsoluteError TimeSeriesErrorFunction //BIND_CONSTRUCTOR AbsoluteError { obj = new AbsoluteError(); LUABIND_RETURN(AbsoluteError, obj); } //BIND_END april-ann-0.4.1/packages/ann/ann/binding/bind_ann_base.lua.cc000066400000000000000000002107131263004425400237520ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include #include "bind_function_interface.h" #include "bind_matrix.h" #include "bind_sparse_matrix.h" #include "bind_mtrand.h" #include "bind_tokens.h" #include "bind_util.h" #include "table_of_token_codes.h" using namespace AprilUtils; using namespace Basics; namespace ANN { static bool rewrapToAtLeastDim2(AprilUtils::SharedPtr &tk) { if (tk->getTokenCode() == table_of_token_codes::token_matrix) { Basics::TokenMatrixFloat *tk_mat = tk->convertTo(); Basics::MatrixFloat *m = tk_mat->getMatrix(); if (m->getNumDim() == 1) { int dims[2] = { 1, m->getDimSize(0) }; tk.reset( new Basics::TokenMatrixFloat(m->rewrap(dims, 2)) ); return true; } } return false; } static void unwrapToDim1(AprilUtils::SharedPtr &tk) { if (tk->getTokenCode() == table_of_token_codes::token_matrix) { Basics::TokenMatrixFloat *tk_mat = tk->convertTo(); Basics::MatrixFloat *m = tk_mat->getMatrix(); int dim = m->getDimSize(1); Basics::MatrixFloat *new_m = m->rewrap(&dim, 1); tk.reset( new Basics::TokenMatrixFloat(new_m) ); } } } void lua_pushAuxANNComponent(lua_State *L, ANNComponent *value) { if (typeid(*value) == typeid(StackANNComponent)) { lua_pushStackANNComponent(L, (StackANNComponent*)value); } else if (typeid(*value) == typeid(JoinANNComponent)) { lua_pushJoinANNComponent(L, (JoinANNComponent*)value); } else if (dynamic_cast(value)) { lua_pushActivationFunctionANNComponent(L, (ActivationFunctionANNComponent*)value); } else if (dynamic_cast(value)) { lua_pushStochasticANNComponent(L, (StochasticANNComponent*)value); } else if (dynamic_cast(value)) { lua_pushConvolutionANNComponent(L, (ConvolutionANNComponent*)value); } else if (dynamic_cast(value)) { lua_pushRewrapANNComponent(L, (RewrapANNComponent*)value); } else if (dynamic_cast(value)) { lua_pushFlattenANNComponent(L, (FlattenANNComponent*)value); } else if (dynamic_cast(value)) { lua_pushProbabilisticMatrixANNComponent(L, (ProbabilisticMatrixANNComponent*)value); } else { lua_pushANNComponent(L, value); } } IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(ANNComponent); //BIND_END //BIND_HEADER_H #include "activation_function_component.h" #include "ann_component.h" #include "batch_standardization_component.h" #include "bias_component.h" #include "bind_function_interface.h" #include "connection.h" #include "const_component.h" #include "convolution_bias_component.h" #include "convolution_component.h" #include "copy_component.h" #include "dot_product_component.h" #include "dropout_component.h" #include "error_print.h" #include "exp_actf_component.h" #include "flatten_component.h" #include "gaussian_noise_component.h" #include "hardtanh_actf_component.h" #include "hyperplane_component.h" #include "join_component.h" #include "leaky_relu_actf_component.h" #include "linear_actf_component.h" #include "log_actf_component.h" #include "log_logistic_actf_component.h" #include "log_softmax_actf_component.h" #include "logistic_actf_component.h" #include "maxpooling_component.h" #include "mul_component.h" #include "prelu_actf_component.h" #include "probabilistic_matrix_component.h" #include "pca_whitening_component.h" #include "relu_actf_component.h" #include "rewrap_component.h" #include "salt_and_pepper_component.h" #include "select_component.h" #include "sin_actf_component.h" #include "slice_component.h" #include "softmax_actf_component.h" #include "softplus_actf_component.h" #include "softsign_actf_component.h" #include "stack_component.h" #include "tanh_actf_component.h" #include "transpose_component.h" #include "zca_whitening_component.h" using namespace Functions; using namespace ANN; void lua_pushAuxANNComponent(lua_State *L, ANNComponent *value); //BIND_END ///////////////////////////////////////////////////// // Connections // ///////////////////////////////////////////////////// //BIND_FUNCTION ann.connections { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "input", "output", "w", "oldw", "first_pos", "column_size", (const char *)0); Basics::MatrixFloat *w, *oldw; unsigned int input_size, output_size, first_pos, column_size; LUABIND_GET_TABLE_PARAMETER(1, input, uint, input_size); LUABIND_GET_TABLE_PARAMETER(1, output, uint, output_size); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, w, MatrixFloat, w, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, oldw, MatrixFloat, oldw, 0); if (oldw != 0) ERROR_PRINT("oldw field is deprecated\n"); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, first_pos, uint, first_pos, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, column_size, uint, column_size, input_size); // Basics::MatrixFloat *obj; if (w) { obj = w->clone(); } else { obj = Connections::build(input_size, output_size); } LUABIND_RETURN(MatrixFloat, obj); } //BIND_END //BIND_FUNCTION ann.connections.load { LUABIND_CHECK_ARGN(==,2); LUABIND_CHECK_PARAMETER(1,MatrixFloat); LUABIND_CHECK_PARAMETER(2,table); check_table_fields(L, 2, "w", "oldw", "first_pos", "column_size", (const char *)0); unsigned int first_pos, column_size; Basics::MatrixFloat *w, *oldw, *obj; LUABIND_GET_PARAMETER(1, MatrixFloat, obj); LUABIND_GET_TABLE_PARAMETER(2, w, MatrixFloat, w); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(2, oldw, MatrixFloat, oldw, 0); if (oldw != 0) ERROR_PRINT("oldw field is deprecated\n"); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(2, first_pos, uint, first_pos, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(2, column_size, uint, column_size, Connections::getNumInputs(obj)); LUABIND_RETURN(uint, Connections::loadWeights(obj, w, first_pos, column_size)); } //BIND_END //BIND_FUNCTION ann.connections.copy_to { LUABIND_CHECK_ARGN(>=,1); LUABIND_CHECK_ARGN(<=,2); LUABIND_CHECK_PARAMETER(1, MatrixFloat); int argn = lua_gettop(L); Basics::MatrixFloat *w=0, *oldw=0, *obj; LUABIND_GET_PARAMETER(1, MatrixFloat, obj); unsigned int first_pos=0, column_size=Connections::getNumInputs(obj); if (argn == 2) { LUABIND_CHECK_PARAMETER(2,table); check_table_fields(L, 2, "w", "oldw", "first_pos", "column_size", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, w, MatrixFloat, w, w); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, oldw, MatrixFloat, oldw, 0); if (oldw != 0) ERROR_PRINT("oldw field is deprecated\n"); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, first_pos, uint, first_pos, first_pos); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, column_size, uint, column_size, column_size); } int size = static_cast(obj->size()); if (!w) w = new Basics::MatrixFloat(1, first_pos + size); if (first_pos + obj->size() > static_cast(w->size())) LUABIND_ERROR("Incorrect matrix size!!\n"); unsigned int lastpos; lastpos = Connections::copyWeightsTo(obj, w, first_pos, column_size); LUABIND_RETURN(MatrixFloat, w); LUABIND_RETURN(uint, lastpos); } //BIND_END //BIND_FUNCTION ann.connections.get_input_size { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, MatrixFloat); Basics::MatrixFloat *obj; LUABIND_GET_PARAMETER(1, MatrixFloat, obj); LUABIND_RETURN(uint, Connections::getInputSize(obj)); } //BIND_END //BIND_FUNCTION ann.connections.get_output_size { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, MatrixFloat); Basics::MatrixFloat *obj; LUABIND_GET_PARAMETER(1, MatrixFloat, obj); LUABIND_RETURN(uint, Connections::getOutputSize(obj)); } //BIND_END //BIND_FUNCTION ann.connections.randomize_weights { LUABIND_CHECK_ARGN(==, 2); LUABIND_CHECK_PARAMETER(1, MatrixFloat); LUABIND_CHECK_PARAMETER(2, table); check_table_fields(L, 2, "random", "inf", "sup", (const char *)0); Basics::MTRand *rnd; float inf, sup; bool use_fanin; Basics::MatrixFloat *obj; LUABIND_GET_PARAMETER(1, MatrixFloat, obj); LUABIND_GET_TABLE_PARAMETER(2, random, MTRand, rnd); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(2, inf, float, inf, -1.0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(2, sup, float, sup, 1.0); Connections::randomizeWeights(obj, rnd, inf, sup); LUABIND_RETURN(MatrixFloat, obj); } //BIND_END ///////////////////////////////////////////////////// // ANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME FunctionInterface functions //BIND_LUACLASSNAME ANNComponent ann.components.base //BIND_CPP_CLASS ANNComponent //BIND_SUBCLASS_OF ANNComponent FunctionInterface //BIND_CONSTRUCTOR ANNComponent //DOC_BEGIN // base(name) /// Superclass for ann.components objects. It is also a dummy by-pass object (does nothing with input/output data). /// @param name A lua string with the name of the component. //DOC_END { LUABIND_CHECK_ARGN(<=,1); int argn = lua_gettop(L); const char *name = 0; const char *weights = 0; unsigned int size = 0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", "weights", "size", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, weights, string, weights, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, size, uint, size, 0); } obj = new ANNComponent(name, weights, size, size); LUABIND_RETURN(ANNComponent, obj); } //BIND_END //BIND_FUNCTION ann.components.reset_id_counters { ANNComponent::resetIdCounters(); } //BIND_END //BIND_FUNCTION ann.inc_names_id_counter { ANNComponent::incNamesIdCounter(); } //BIND_END //BIND_FUNCTION ann.inc_weights_id_counter { ANNComponent::incWeightsIdCounter(); } //BIND_END //BIND_METHOD ANNComponent get_name { LUABIND_RETURN(string, obj->getName().c_str()); } //BIND_END //BIND_METHOD ANNComponent get_weights_name { LUABIND_RETURN(string, obj->getWeightsName().c_str()); } //BIND_END //BIND_METHOD ANNComponent has_weights_name { LUABIND_RETURN(bool, obj->hasWeightsName()); } //BIND_END //BIND_METHOD ANNComponent get_is_built { LUABIND_RETURN(bool, obj->getIsBuilt()); } //BIND_END //BIND_METHOD ANNComponent debug_info { obj->debugInfo(); } //BIND_END //BIND_METHOD ANNComponent copy_state { LuaTable state; if (lua_istable(L,1)) state = lua_toLuaTable(L,1); obj->copyState(state); LUABIND_RETURN(LuaTable, state); } //BIND_END //BIND_METHOD ANNComponent set_state { LuaTable state(L,1); obj->setState(state); LUABIND_RETURN(AuxANNComponent, obj); } //BIND_END //BIND_METHOD ANNComponent get_input_size { LUABIND_RETURN(uint, obj->getInputSize()); } //BIND_END //BIND_METHOD ANNComponent get_output_size { LUABIND_RETURN(uint, obj->getOutputSize()); } //BIND_END //BIND_METHOD ANNComponent get_input { AprilUtils::SharedPtr aux( obj->getInput() ); LUABIND_RETURN(AuxToken, aux); } //BIND_END //BIND_METHOD ANNComponent get_output { AprilUtils::SharedPtr aux( obj->getOutput() ); LUABIND_RETURN(AuxToken, aux); } //BIND_END //BIND_METHOD ANNComponent get_error_input { AprilUtils::SharedPtr aux( obj->getErrorInput() ); LUABIND_RETURN(AuxToken, aux); } //BIND_END //BIND_METHOD ANNComponent get_error_output { AprilUtils::SharedPtr aux( obj->getErrorOutput() ); LUABIND_RETURN(AuxToken, aux); } //BIND_END //BIND_METHOD ANNComponent precompute_output_size { vector input_size, output_size; int argn = lua_gettop(L); if (argn == 0) input_size.push_back(0); else { int n; LUABIND_TABLE_GETN(1, n); input_size.resize(n); LUABIND_TABLE_TO_VECTOR(1, uint, input_size, n); } obj->precomputeOutputSize(input_size, output_size); LUABIND_FORWARD_CONTAINER_TO_NEW_TABLE(vector, uint, output_size); LUABIND_RETURN_FROM_STACK(-1); } //BIND_END //BIND_METHOD ANNComponent forward { AprilUtils::SharedPtr input; bool during_training; LUABIND_CHECK_ARGN(>=, 1); LUABIND_CHECK_ARGN(<=, 2); LUABIND_GET_PARAMETER(1, AuxToken, input); LUABIND_GET_OPTIONAL_PARAMETER(2, bool, during_training, false); bool rewrapped = rewrapToAtLeastDim2(input); AprilUtils::SharedPtr output( obj->doForward(input.get(), during_training) ); if (rewrapped) unwrapToDim1(output); LUABIND_RETURN(AuxToken, output); } //BIND_END //BIND_METHOD ANNComponent backprop { AprilUtils::SharedPtr input; LUABIND_CHECK_ARGN(==, 1); LUABIND_GET_PARAMETER(1, AuxToken, input); bool rewrapped = rewrapToAtLeastDim2(input); AprilUtils::SharedPtr gradient( obj->doBackprop(input.get()) ); if (!gradient.empty()) { if (rewrapped) unwrapToDim1(gradient); LUABIND_RETURN(AuxToken, gradient); } else LUABIND_RETURN_NIL(); } //BIND_END //BIND_METHOD ANNComponent reset { unsigned int it; LUABIND_GET_OPTIONAL_PARAMETER(1, int, it, 0); obj->reset(it); } //BIND_END //BIND_METHOD ANNComponent compute_gradients { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable weight_grads_dict; if (argn == 1) { weight_grads_dict = AprilUtils::LuaTable(L,1); } // obj->computeAllGradients(weight_grads_dict); LUABIND_RETURN(LuaTable, weight_grads_dict); } //BIND_END //BIND_METHOD ANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(AuxANNComponent, obj->clone(copies)); } //BIND_END //BIND_METHOD ANNComponent set_use_cuda { bool use_cuda; LUABIND_CHECK_ARGN(==, 1); LUABIND_GET_PARAMETER(1, bool, use_cuda); obj->setUseCuda(use_cuda); LUABIND_RETURN(AuxANNComponent, obj); } //BIND_END //BIND_METHOD ANNComponent get_use_cuda { LUABIND_RETURN(bool, obj->getUseCuda()); } //BIND_END //BIND_METHOD ANNComponent build { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); unsigned int input_size=0, output_size=0; AprilUtils::LuaTable weights_dict(L), components_dict(L); if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "input", "output", "weights", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, input, uint, input_size, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, output, uint, output_size, 0); lua_getfield(L, 1, "weights"); if (!lua_isnil(L, -1)) weights_dict = lua_toLuaTable(L,-1); lua_pop(L, 1); } // obj->build(input_size, output_size, weights_dict, components_dict); // LUABIND_RETURN(AuxANNComponent, obj); LUABIND_RETURN(LuaTable, weights_dict); LUABIND_RETURN(LuaTable, components_dict); } //BIND_END //BIND_METHOD ANNComponent copy_weights { AprilUtils::LuaTable weights_dict(L); int argn = lua_gettop(L); if (argn == 1) { weights_dict = lua_toLuaTable(L, 1); } obj->copyWeights(weights_dict); LUABIND_RETURN(LuaTable, weights_dict); } //BIND_END //BIND_METHOD ANNComponent copy_components { AprilUtils::LuaTable components_dict(L); int argn = lua_gettop(L); if (argn == 1) { components_dict = lua_toLuaTable(L, 1); } obj->copyComponents(components_dict); LUABIND_RETURN(LuaTable, components_dict); } //BIND_END //BIND_METHOD ANNComponent get_component { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1,string); const char *name; LUABIND_GET_PARAMETER(1, string, name); string name_string(name); ANNComponent *component = obj->getComponent(name_string); LUABIND_RETURN(AuxANNComponent, component); } //BIND_END //BIND_FUNCTION ann.generate_name { const char *prefix; LUABIND_GET_OPTIONAL_PARAMETER(1, string, prefix, 0); AprilUtils::string name = ANNComponent::generateName(prefix); LUABIND_RETURN(string, name.c_str()); } //BIND_END ///////////////////////////////////////////////////// // DotProductANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME DotProductANNComponent ann.components.dot_product //BIND_CPP_CLASS DotProductANNComponent //BIND_SUBCLASS_OF DotProductANNComponent ANNComponent //BIND_CONSTRUCTOR DotProductANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0, *weights_name=0; unsigned int input_size=0, output_size=0; bool transpose_weights=false; MatrixFloat *matrix = 0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", "weights", "input", "output", "transpose", "matrix", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, weights, string, weights_name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, input, uint, input_size, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, output, uint, output_size, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, transpose, bool, transpose_weights, false); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, matrix, MatrixFloat, matrix, 0); } obj = new DotProductANNComponent(name, weights_name, input_size, output_size, transpose_weights, matrix); LUABIND_RETURN(DotProductANNComponent, obj); } //BIND_END //BIND_METHOD DotProductANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(DotProductANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // ProbabilisticMatrixANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME ProbabilisticMatrixANNComponent ann.components.probabilistic_matrix //BIND_CPP_CLASS ProbabilisticMatrixANNComponent //BIND_SUBCLASS_OF ProbabilisticMatrixANNComponent ANNComponent //BIND_CONSTRUCTOR ProbabilisticMatrixANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0, *weights_name=0, *side_str = 0; unsigned int input_size=0, output_size=0; ProbabilisticMatrixANNComponent::NormalizationSide side; side = ProbabilisticMatrixANNComponent::LEFT; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "side", "name", "weights", "input", "output", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, side, string, side_str, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, weights, string, weights_name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, input, uint, input_size, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, output, uint, output_size, 0); if (side_str != 0) { if (strcmp(side_str, "left")==0) { side = ProbabilisticMatrixANNComponent::LEFT; } else if (strcmp(side_str, "right")==0) { side = ProbabilisticMatrixANNComponent::RIGHT; } else { side = ProbabilisticMatrixANNComponent::LEFT; // avoid compiler warning LUABIND_ERROR("Incorrect side string, expected 'left' or 'right'"); } } // if (side_str != 0) } obj = new ProbabilisticMatrixANNComponent(side, name, weights_name, input_size, output_size); LUABIND_RETURN(ProbabilisticMatrixANNComponent, obj); } //BIND_END //BIND_METHOD ProbabilisticMatrixANNComponent get_normalized_weights { LUABIND_RETURN(MatrixFloat, obj->getNormalizedWeights()); } //BIND_END //BIND_METHOD ProbabilisticMatrixANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(ProbabilisticMatrixANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // BiasANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME BiasANNComponent ann.components.bias //BIND_CPP_CLASS BiasANNComponent //BIND_SUBCLASS_OF BiasANNComponent ANNComponent //BIND_CONSTRUCTOR BiasANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0, *weights_name=0; unsigned int size=0; MatrixFloat *matrix=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", "weights", "size", "matrix", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, size, uint, size, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, weights, string, weights_name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, matrix, MatrixFloat, matrix, 0); } obj = new BiasANNComponent(size, name, weights_name, matrix); LUABIND_RETURN(BiasANNComponent, obj); } //BIND_END //BIND_METHOD BiasANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(BiasANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // MulANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME MulANNComponent ann.components.mul //BIND_CPP_CLASS MulANNComponent //BIND_SUBCLASS_OF MulANNComponent ANNComponent //BIND_CONSTRUCTOR MulANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); bool scalar = false; const char *name=0, *weights_name=0; unsigned int size=0; MatrixFloat *matrix = 0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", "weights", "size", "scalar", "matrix", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, size, uint, size, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, scalar, bool, scalar, scalar); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, weights, string, weights_name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, matrix, MatrixFloat, matrix, 0); } obj = new MulANNComponent(size, scalar, name, weights_name, matrix); LUABIND_RETURN(MulANNComponent, obj); } //BIND_END //BIND_METHOD MulANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(MulANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // BatchStandardizationANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME BatchStandardizationANNComponent ann.components.batch_standardization //BIND_CPP_CLASS BatchStandardizationANNComponent //BIND_SUBCLASS_OF BatchStandardizationANNComponent ANNComponent //BIND_CONSTRUCTOR BatchStandardizationANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; unsigned int size=0; MatrixFloat *mean=0, *inv_std=0; float alpha=0.1, epsilon=1e-05f; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", "size", "alpha", "epsilon", "mean", "inv_std", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, alpha, float, alpha, alpha); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, epsilon, float, epsilon, epsilon); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, size, uint, size, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, mean, MatrixFloat, mean, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, inv_std, MatrixFloat, inv_std, 0); } obj = new BatchStandardizationANNComponent(alpha, epsilon, size, name, mean, inv_std); LUABIND_RETURN(BatchStandardizationANNComponent, obj); } //BIND_END //BIND_METHOD BatchStandardizationANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(BatchStandardizationANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // HyperplaneANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME HyperplaneANNComponent ann.components.hyperplane //BIND_CPP_CLASS HyperplaneANNComponent //BIND_SUBCLASS_OF HyperplaneANNComponent ANNComponent //BIND_CONSTRUCTOR HyperplaneANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; const char *dot_product_name=0, *bias_name=0; const char *dot_product_weights=0, *bias_weights=0; unsigned int input_size=0, output_size=0; bool transpose_weights=false; MatrixFloat *wmatrix=0, *bmatrix=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", "dot_product_name", "bias_name", "dot_product_weights", "bias_weights", "input", "output", "transpose", "wmatrix", "bmatrix", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, dot_product_name, string, dot_product_name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, bias_name, string, bias_name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, dot_product_weights, string, dot_product_weights, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, bias_weights, string, bias_weights, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, input, uint, input_size, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, output, uint, output_size, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, transpose, bool, transpose_weights, false); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, wmatrix, MatrixFloat, wmatrix, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, bmatrix, MatrixFloat, bmatrix, 0); } obj = new HyperplaneANNComponent(name, dot_product_name, bias_name, dot_product_weights, bias_weights, input_size, output_size, transpose_weights, wmatrix, bmatrix); LUABIND_RETURN(HyperplaneANNComponent, obj); } //BIND_END //BIND_METHOD HyperplaneANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(HyperplaneANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // StackANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME StackANNComponent ann.components.stack //BIND_CPP_CLASS StackANNComponent //BIND_SUBCLASS_OF StackANNComponent ANNComponent //BIND_CONSTRUCTOR StackANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); unsigned int input=0, output=0; const char *name=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", "components", "input", "output", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, input, uint, input, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, output, uint, output, 0); } obj = new StackANNComponent(name, input, output); if (argn >= 1) { lua_getfield(L, 1, "components"); if (!lua_isnil(L, -1)) { for (int i=1; i<=luaL_len(L, -1); ++i) { lua_rawgeti(L, -1, i); ANNComponent *c = lua_toANNComponent(L, -1); obj->pushComponent(c); lua_pop(L, 1); } } lua_pop(L, 1); } LUABIND_RETURN(StackANNComponent, obj); } //BIND_END //BIND_METHOD StackANNComponent size { LUABIND_RETURN(uint, obj->size()); } //BIND_END //BIND_METHOD StackANNComponent push { LUABIND_CHECK_ARGN(>=, 1); int argn = lua_gettop(L); for (int i=1; i<=argn; ++i) { LUABIND_CHECK_PARAMETER(i, ANNComponent); ANNComponent *component; LUABIND_GET_PARAMETER(i, ANNComponent, component); obj->pushComponent(component); } LUABIND_RETURN(StackANNComponent, obj); } //BIND_END //BIND_METHOD StackANNComponent unroll { lua_checkstack(L, obj->size()); for (unsigned int i=0; isize(); ++i) { LUABIND_RETURN(AuxANNComponent, obj->getComponentAt(i)); } } //BIND_END //BIND_METHOD StackANNComponent get { LUABIND_CHECK_ARGN(>=,1); int argn = lua_gettop(L); lua_checkstack(L, argn); for (int i=1; i<=argn; ++i) { unsigned int idx = lua_tointeger(L, i); if (idx > obj->size()) LUABIND_FERROR2("Incorrect index, expected <= %d, found %d\n", obj->size(), idx); LUABIND_RETURN(AuxANNComponent, obj->getComponentAt(idx - 1)); } } //BIND_END //BIND_METHOD StackANNComponent top { if (obj->size() > 0) LUABIND_RETURN(AuxANNComponent, obj->topComponent()); } //BIND_END //BIND_METHOD StackANNComponent pop { if (obj->size() > 0) obj->popComponent(); LUABIND_RETURN(StackANNComponent, obj); } //BIND_END //BIND_METHOD StackANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(StackANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END //BIND_METHOD StackANNComponent set_use_cuda { bool use_cuda; LUABIND_CHECK_ARGN(==, 1); LUABIND_GET_PARAMETER(1, bool, use_cuda); obj->setUseCuda(use_cuda); LUABIND_RETURN(StackANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // JoinANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME JoinANNComponent ann.components.join //BIND_CPP_CLASS JoinANNComponent //BIND_SUBCLASS_OF JoinANNComponent ANNComponent //BIND_CONSTRUCTOR JoinANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", "components", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); } obj = new JoinANNComponent(name); if (argn >= 1) { lua_getfield(L, 1, "components"); if (!lua_isnil(L, -1)) { for (int i=1; i<=luaL_len(L, -1); ++i) { lua_rawgeti(L, -1, i); ANNComponent *c = lua_toANNComponent(L, -1); obj->addComponent(c); lua_pop(L, 1); } } lua_pop(L, 1); } LUABIND_RETURN(JoinANNComponent, obj); } //BIND_END //BIND_METHOD JoinANNComponent add { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, ANNComponent); ANNComponent *component; LUABIND_GET_PARAMETER(1, ANNComponent, component); obj->addComponent(component); LUABIND_RETURN(JoinANNComponent, obj); } //BIND_END //BIND_METHOD JoinANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(JoinANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END //BIND_METHOD JoinANNComponent set_use_cuda { bool use_cuda; LUABIND_CHECK_ARGN(==, 1); LUABIND_GET_PARAMETER(1, bool, use_cuda); obj->setUseCuda(use_cuda); LUABIND_RETURN(JoinANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // CopyANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME CopyANNComponent ann.components.copy //BIND_CPP_CLASS CopyANNComponent //BIND_SUBCLASS_OF CopyANNComponent ANNComponent //BIND_CONSTRUCTOR CopyANNComponent { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); int argn = lua_gettop(L); const char *name=0; unsigned int input_size=0, output_size=0, times; check_table_fields(L, 1, "times", "name", "input", "output", (const char *)0); LUABIND_GET_TABLE_PARAMETER(1, times, uint, times); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, input, uint, input_size, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, output, uint, output_size, 0); obj = new CopyANNComponent(times, name, input_size, output_size); LUABIND_RETURN(CopyANNComponent, obj); } //BIND_END //BIND_METHOD CopyANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(CopyANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // SelectANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME SelectANNComponent ann.components.select //BIND_CPP_CLASS SelectANNComponent //BIND_SUBCLASS_OF SelectANNComponent ANNComponent //BIND_CONSTRUCTOR SelectANNComponent { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); const char *name=0; int dimension, index; check_table_fields(L, 1, "name", "dimension", "index", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_PARAMETER(1, dimension, int, dimension); LUABIND_GET_TABLE_PARAMETER(1, index, int, index); obj = new SelectANNComponent(dimension-1, index-1, name); LUABIND_RETURN(SelectANNComponent, obj); } //BIND_END //BIND_METHOD SelectANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(SelectANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // RewrapANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME RewrapANNComponent ann.components.rewrap //BIND_CPP_CLASS RewrapANNComponent //BIND_SUBCLASS_OF RewrapANNComponent ANNComponent //BIND_CONSTRUCTOR RewrapANNComponent { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); const char *name=0; int *size, n; check_table_fields(L, 1, "name", "size", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); lua_getfield(L, 1, "size"); if (!lua_istable(L, -1)) LUABIND_ERROR("Expected a table at field size"); LUABIND_TABLE_GETN(-1, n); size = new int[n]; LUABIND_TABLE_TO_VECTOR(-1, int, size, n); lua_pop(L, 1); obj = new RewrapANNComponent(size, n, name); delete[] size; LUABIND_RETURN(RewrapANNComponent, obj); } //BIND_END //BIND_METHOD RewrapANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(RewrapANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // TransposeANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME TransposeANNComponent ann.components.transpose //BIND_CPP_CLASS TransposeANNComponent //BIND_SUBCLASS_OF TransposeANNComponent ANNComponent //BIND_CONSTRUCTOR TransposeANNComponent { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); const char *name=0; check_table_fields(L, 1, "name", "dims", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); lua_getfield(L, 1, "dims"); AprilUtils::UniquePtr which; if (!lua_isnil(L, -1)) { if (!lua_istable(L, -1)) { LUABIND_ERROR("Expected a table at field dims"); } int n; LUABIND_TABLE_GETN(-1, n); if (n != 2) { LUABIND_ERROR("Needs a dims table field with two elements"); } which = new int[2]; LUABIND_TABLE_TO_VECTOR_SUB1(-1, int, which, n); } lua_pop(L, 1); obj = new TransposeANNComponent(which.get(), name); LUABIND_RETURN(TransposeANNComponent, obj); } //BIND_END //BIND_METHOD TransposeANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(TransposeANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // SliceANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME SliceANNComponent ann.components.slice //BIND_CPP_CLASS SliceANNComponent //BIND_SUBCLASS_OF SliceANNComponent ANNComponent //BIND_CONSTRUCTOR SliceANNComponent { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); const char *name=0; int *size, *pos, n; check_table_fields(L, 1, "name", "pos", "size", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); // lua_getfield(L, 1, "pos"); if (!lua_istable(L, -1)) LUABIND_ERROR("Expected a table at field pos"); LUABIND_TABLE_GETN(-1, n); pos = new int[n]; LUABIND_TABLE_TO_VECTOR_SUB1(-1, int, pos, n); lua_pop(L, 1); // lua_getfield(L, 1, "size"); if (!lua_istable(L, -1)) LUABIND_ERROR("Expected a table at field size"); LUABIND_TABLE_GETN(-1, n); size = new int[n]; LUABIND_TABLE_TO_VECTOR(-1, int, size, n); lua_pop(L, 1); // obj = new SliceANNComponent(pos, size, n, name); delete[] pos; delete[] size; LUABIND_RETURN(SliceANNComponent, obj); } //BIND_END //BIND_METHOD SliceANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(SliceANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // FlattenANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME FlattenANNComponent ann.components.flatten //BIND_CPP_CLASS FlattenANNComponent //BIND_SUBCLASS_OF FlattenANNComponent ANNComponent //BIND_CONSTRUCTOR FlattenANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); } obj = new FlattenANNComponent(name); LUABIND_RETURN(FlattenANNComponent, obj); } //BIND_END //BIND_METHOD FlattenANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(FlattenANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // ConvolutionANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME ConvolutionANNComponent ann.components.convolution //BIND_CPP_CLASS ConvolutionANNComponent //BIND_SUBCLASS_OF ConvolutionANNComponent ANNComponent //BIND_CONSTRUCTOR ConvolutionANNComponent { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); const char *name=0, *weights=0; int *kernel, *step, n, input_planes_dim; MatrixFloat *matrix=0; check_table_fields(L, 1, "name", "weights", "kernel", "input_planes_dim", "step", "n", "matrix", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, input_planes_dim, int, input_planes_dim, -1); if (input_planes_dim > 1) { LUABIND_ERROR("Deprecated property, new version only allowed for input_planes_dim==1\n"); } else if (input_planes_dim == 1) { ERROR_PRINT("Deprecated property, not needed in the new version\n"); } LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, weights, string, weights, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, matrix, MatrixFloat, matrix, 0); LUABIND_GET_TABLE_PARAMETER(1, n, int, n); // lua_getfield(L, 1, "kernel"); if (!lua_istable(L, -1)) LUABIND_ERROR("Expected a table at field 'kernel'"); int size; LUABIND_TABLE_GETN(-1, size); kernel = new int[size]; step = new int[size]; LUABIND_TABLE_TO_VECTOR(-1, int, kernel, size); lua_pop(L, 1); // lua_getfield(L, 1, "step"); if (lua_isnil(L, -1)) { for (int i=0; igetKernelShape(n); LUABIND_VECTOR_TO_NEW_TABLE(int, kernel, n); LUABIND_INCREASE_NUM_RETURNS(1); } //BIND_END //BIND_METHOD ConvolutionANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(ConvolutionANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // ConvolutionBiasANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME ConvolutionBiasANNComponent ann.components.convolution_bias //BIND_CPP_CLASS ConvolutionBiasANNComponent //BIND_SUBCLASS_OF ConvolutionBiasANNComponent ANNComponent //BIND_CONSTRUCTOR ConvolutionBiasANNComponent { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); const char *name=0, *weights=0; int n, ndims; MatrixFloat *matrix=0; check_table_fields(L, 1, "name", "weights", "n", "ndims", "matrix", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, weights, string, weights, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, matrix, MatrixFloat, matrix, 0); LUABIND_GET_TABLE_PARAMETER(1, n, int, n); LUABIND_GET_TABLE_PARAMETER(1, ndims, int, ndims); // obj = new ConvolutionBiasANNComponent(ndims, n, name, weights, matrix); LUABIND_RETURN(ConvolutionBiasANNComponent, obj); } //BIND_END //BIND_METHOD ConvolutionBiasANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(ConvolutionBiasANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // MaxPoolingANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME MaxPoolingANNComponent ann.components.max_pooling //BIND_CPP_CLASS MaxPoolingANNComponent //BIND_SUBCLASS_OF MaxPoolingANNComponent ANNComponent //BIND_CONSTRUCTOR MaxPoolingANNComponent { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); const char *name=0; int *kernel, *step; check_table_fields(L, 1, "name", "kernel", "step", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); // lua_getfield(L, 1, "kernel"); if (!lua_istable(L, -1)) LUABIND_ERROR("Expected a table at field 'kernel'"); int size; LUABIND_TABLE_GETN(-1, size); kernel = new int[size]; step = new int[size]; LUABIND_TABLE_TO_VECTOR(-1, int, kernel, size); lua_pop(L, 1); // lua_getfield(L, 1, "step"); if (lua_isnil(L, -1)) { for (int i=0; i(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME StochasticANNComponent ann.components.stochastic //BIND_CPP_CLASS StochasticANNComponent //BIND_SUBCLASS_OF StochasticANNComponent ANNComponent //BIND_CONSTRUCTOR StochasticANNComponent { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD StochasticANNComponent set_random { Basics::MTRand *random; LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, MTRand); LUABIND_GET_PARAMETER(1, MTRand, random); obj->setRandom(random); LUABIND_RETURN(StochasticANNComponent, obj); } //BIND_END //BIND_METHOD StochasticANNComponent get_random { LUABIND_RETURN(MTRand, obj->getRandom()); } //BIND_END ///////////////////////////////////////////////////// // GaussianNoiseANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME GaussianNoiseANNComponent ann.components.gaussian_noise //BIND_CPP_CLASS GaussianNoiseANNComponent //BIND_SUBCLASS_OF GaussianNoiseANNComponent ANNComponent //BIND_CONSTRUCTOR GaussianNoiseANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; float mean=0.0f, var=0.1f; unsigned int size=0; Basics::MTRand *random=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "size", "random", "mean", "var", "name", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, random, MTRand, random, random); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, mean, float, mean, mean); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, var, float, var, var); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, size, uint, size, size); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, name); } if (!random) random = new Basics::MTRand(); obj = new GaussianNoiseANNComponent(random, mean, var, name, size); LUABIND_RETURN(GaussianNoiseANNComponent, obj); } //BIND_END //BIND_METHOD GaussianNoiseANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(GaussianNoiseANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // SaltAndPepperANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME SaltAndPepperANNComponent ann.components.salt_and_pepper //BIND_CPP_CLASS SaltAndPepperANNComponent //BIND_SUBCLASS_OF SaltAndPepperANNComponent ANNComponent //BIND_CONSTRUCTOR SaltAndPepperANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; float zero=0.0f, one=1.0f, prob=0.2f; unsigned int size=0; Basics::MTRand *random=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "size", "random", "one", "zero", "prob", "name", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, random, MTRand, random, random); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, prob, float, prob, prob); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, zero, float, zero, zero); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, one, float, one, one); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, size, uint, size, size); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, name); } if (!random) random = new Basics::MTRand(); obj = new SaltAndPepperANNComponent(random, zero, one, prob, name, size); LUABIND_RETURN(SaltAndPepperANNComponent, obj); } //BIND_END //BIND_METHOD SaltAndPepperANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(SaltAndPepperANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END //////////////////////////////////////////////////// // DropoutANNComponent // //////////////////////////////////////////////////// //BIND_LUACLASSNAME DropoutANNComponent ann.components.dropout //BIND_CPP_CLASS DropoutANNComponent //BIND_SUBCLASS_OF DropoutANNComponent ANNComponent //BIND_CONSTRUCTOR DropoutANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; float prob=0.5f, value=0.0f; unsigned int size=0; Basics::MTRand *random=0; bool norm = true; // normalize_after_training if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", "size", "prob", "value", "random", "norm", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, name); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, size, uint, size, size); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, value, float, value, value); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, prob, float, prob, prob); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, norm, bool, norm, norm); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, random, MTRand, random, random); } if (!random) random = new Basics::MTRand(); obj = new DropoutANNComponent(random, value, prob, norm, name, size); LUABIND_RETURN(DropoutANNComponent, obj); } //BIND_END //BIND_METHOD SaltAndPepperANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(DropoutANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////////////////////////////// ///////////////////////////////////////////////////// // ActivationFunctionANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME ActivationFunctionANNComponent ann.components.actf //BIND_CPP_CLASS ActivationFunctionANNComponent //BIND_SUBCLASS_OF ActivationFunctionANNComponent ANNComponent //BIND_CONSTRUCTOR ActivationFunctionANNComponent { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD ActivationFunctionANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(ActivationFunctionANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // LogisticActfANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME LogisticActfANNComponent ann.components.actf.logistic //BIND_CPP_CLASS LogisticActfANNComponent //BIND_SUBCLASS_OF LogisticActfANNComponent ActivationFunctionANNComponent //BIND_CONSTRUCTOR LogisticActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); } obj = new LogisticActfANNComponent(name); LUABIND_RETURN(LogisticActfANNComponent, obj); } //BIND_END //BIND_LUACLASSNAME SparseLogisticActfANNComponent ann.components.actf.sparse_logistic //BIND_CPP_CLASS SparseLogisticActfANNComponent //BIND_SUBCLASS_OF SparseLogisticActfANNComponent LogisticActfANNComponent ////BIND_CONSTRUCTOR SparseLogisticActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; float sparsity = 1.0f; float penalty = 0.05f; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", "sparsity", "penalty", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, penalty, float, penalty, 1.0f); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, sparsity, float, sparsity, 0.05f); } obj = new SparseLogisticActfANNComponent(name, penalty, sparsity); LUABIND_RETURN(SparseLogisticActfANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // TanhActfANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME TanhActfANNComponent ann.components.actf.tanh //BIND_CPP_CLASS TanhActfANNComponent //BIND_SUBCLASS_OF TanhActfANNComponent ActivationFunctionANNComponent //BIND_CONSTRUCTOR TanhActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); } obj = new TanhActfANNComponent(name); LUABIND_RETURN(TanhActfANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // SoftsignActfANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME SoftsignActfANNComponent ann.components.actf.softsign //BIND_CPP_CLASS SoftsignActfANNComponent //BIND_SUBCLASS_OF SoftsignActfANNComponent ActivationFunctionANNComponent //BIND_CONSTRUCTOR SoftsignActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); } obj = new SoftsignActfANNComponent(name); LUABIND_RETURN(SoftsignActfANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // LogLogisticActfANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME LogLogisticActfANNComponent ann.components.actf.log_logistic //BIND_CPP_CLASS LogLogisticActfANNComponent //BIND_SUBCLASS_OF LogLogisticActfANNComponent ActivationFunctionANNComponent //BIND_CONSTRUCTOR LogLogisticActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); } obj = new LogLogisticActfANNComponent(name); LUABIND_RETURN(LogLogisticActfANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // SoftmaxActfANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME SoftmaxActfANNComponent ann.components.actf.softmax //BIND_CPP_CLASS SoftmaxActfANNComponent //BIND_SUBCLASS_OF SoftmaxActfANNComponent ActivationFunctionANNComponent //BIND_CONSTRUCTOR SoftmaxActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); } obj = new SoftmaxActfANNComponent(name); LUABIND_RETURN(SoftmaxActfANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // LogSoftmaxActfANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME LogSoftmaxActfANNComponent ann.components.actf.log_softmax //BIND_CPP_CLASS LogSoftmaxActfANNComponent //BIND_SUBCLASS_OF LogSoftmaxActfANNComponent ActivationFunctionANNComponent //BIND_CONSTRUCTOR LogSoftmaxActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); } obj = new LogSoftmaxActfANNComponent(name); LUABIND_RETURN(LogSoftmaxActfANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // SoftplusActfANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME SoftplusActfANNComponent ann.components.actf.softplus //BIND_CPP_CLASS SoftplusActfANNComponent //BIND_SUBCLASS_OF SoftplusActfANNComponent ActivationFunctionANNComponent //BIND_CONSTRUCTOR SoftplusActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); } obj = new SoftplusActfANNComponent(name); LUABIND_RETURN(SoftplusActfANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // ReLUActfANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME ReLUActfANNComponent ann.components.actf.relu //BIND_CPP_CLASS ReLUActfANNComponent //BIND_SUBCLASS_OF ReLUActfANNComponent ActivationFunctionANNComponent //BIND_CONSTRUCTOR ReLUActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); } obj = new ReLUActfANNComponent(name); LUABIND_RETURN(ReLUActfANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // LeakyReLUActfANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME LeakyReLUActfANNComponent ann.components.actf.leaky_relu //BIND_CPP_CLASS LeakyReLUActfANNComponent //BIND_SUBCLASS_OF LeakyReLUActfANNComponent ActivationFunctionANNComponent //BIND_CONSTRUCTOR LeakyReLUActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; float leak=0.01f; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", "leak", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, leak, float, leak, 0.01f); } obj = new LeakyReLUActfANNComponent(leak, name); LUABIND_RETURN(LeakyReLUActfANNComponent, obj); } //BIND_END /////////////////////////////////////////////////////// // PReLUActfANNComponent // /////////////////////////////////////////////////////// //BIND_LUACLASSNAME PReLUActfANNComponent ann.components.actf.prelu //BIND_CPP_CLASS PReLUActfANNComponent //BIND_SUBCLASS_OF PReLUActfANNComponent ActivationFunctionANNComponent //BIND_CONSTRUCTOR PReLUActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0, *weights=0; unsigned int size=0; bool scalar=false; MatrixFloat *matrix=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", "size", "scalar", "weights", "matrix", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, weights, string, weights, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, scalar, bool, scalar, false); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, size, uint, size, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, matrix, MatrixFloat, matrix, 0); } obj = new PReLUActfANNComponent(scalar, size, name, weights, matrix); LUABIND_RETURN(PReLUActfANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // HardtanhActfANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME HardtanhActfANNComponent ann.components.actf.hardtanh //BIND_CPP_CLASS HardtanhActfANNComponent //BIND_SUBCLASS_OF HardtanhActfANNComponent ActivationFunctionANNComponent //BIND_CONSTRUCTOR HardtanhActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; float inf=-1.0f, sup=1.0f; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", "inf", "sup", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, inf, float, inf, -1.0f); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, sup, float, sup, 1.0f); } obj = new HardtanhActfANNComponent(name, inf, sup); LUABIND_RETURN(HardtanhActfANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // SinActfANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME SinActfANNComponent ann.components.actf.sin //BIND_CPP_CLASS SinActfANNComponent //BIND_SUBCLASS_OF SinActfANNComponent ActivationFunctionANNComponent //BIND_CONSTRUCTOR SinActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); } obj = new SinActfANNComponent(name); LUABIND_RETURN(SinActfANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // LogActfANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME LogActfANNComponent ann.components.actf.log //BIND_CPP_CLASS LogActfANNComponent //BIND_SUBCLASS_OF LogActfANNComponent ActivationFunctionANNComponent //BIND_CONSTRUCTOR LogActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); } obj = new LogActfANNComponent(name); LUABIND_RETURN(LogActfANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // ExpActfANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME ExpActfANNComponent ann.components.actf.exp //BIND_CPP_CLASS ExpActfANNComponent //BIND_SUBCLASS_OF ExpActfANNComponent ActivationFunctionANNComponent //BIND_CONSTRUCTOR ExpActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); } obj = new ExpActfANNComponent(name); LUABIND_RETURN(ExpActfANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // LinearActfANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME LinearActfANNComponent ann.components.actf.linear //BIND_CPP_CLASS LinearActfANNComponent //BIND_SUBCLASS_OF LinearActfANNComponent ActivationFunctionANNComponent //BIND_CONSTRUCTOR LinearActfANNComponent { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); const char *name=0; if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "name", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); } obj = new LinearActfANNComponent(name); LUABIND_RETURN(LinearActfANNComponent, obj); } //BIND_END ///////////////////////////////////////////////////// // PCAWhiteningANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME PCAWhiteningANNComponent ann.components.pca_whitening //BIND_CPP_CLASS PCAWhiteningANNComponent //BIND_SUBCLASS_OF PCAWhiteningANNComponent ANNComponent //BIND_CONSTRUCTOR PCAWhiteningANNComponent { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); const char *name=0; float epsilon; int takeN; Basics::MatrixFloat *U; Basics::SparseMatrixFloat *S; check_table_fields(L, 1, "name", "U", "S", "takeN", "epsilon", (const char *)0); LUABIND_GET_TABLE_PARAMETER(1, U, MatrixFloat, U); LUABIND_GET_TABLE_PARAMETER(1, S, SparseMatrixFloat, S); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, takeN, int, takeN, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, epsilon, float, epsilon, 0); // obj = new PCAWhiteningANNComponent(U, S, epsilon, takeN, name); LUABIND_RETURN(PCAWhiteningANNComponent, obj); } //BIND_END //BIND_METHOD PCAWhiteningANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(PCAWhiteningANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ///////////////////////////////////////////////////// // ZCAWhiteningANNComponent // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME ZCAWhiteningANNComponent ann.components.zca_whitening //BIND_CPP_CLASS ZCAWhiteningANNComponent //BIND_SUBCLASS_OF ZCAWhiteningANNComponent ANNComponent //BIND_CONSTRUCTOR ZCAWhiteningANNComponent { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); const char *name=0; float epsilon; int takeN; Basics::MatrixFloat *U; Basics::SparseMatrixFloat *S; check_table_fields(L, 1, "name", "U", "S", "takeN", "epsilon", (const char *)0); LUABIND_GET_TABLE_PARAMETER(1, U, MatrixFloat, U); LUABIND_GET_TABLE_PARAMETER(1, S, SparseMatrixFloat, S); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, takeN, int, takeN, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, epsilon, float, epsilon, 0); // obj = new ZCAWhiteningANNComponent(U, S, epsilon, takeN, name); LUABIND_RETURN(ZCAWhiteningANNComponent, obj); } //BIND_END //BIND_METHOD ZCAWhiteningANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(ZCAWhiteningANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END ////////////////////////////////////////////// // ConstANNComponent // ////////////////////////////////////////////// //BIND_LUACLASSNAME ConstANNComponent ann.components.const //BIND_CPP_CLASS ConstANNComponent //BIND_SUBCLASS_OF ConstANNComponent ANNComponent //BIND_CONSTRUCTOR ConstANNComponent { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); const char *name=0; ANNComponent *component; check_table_fields(L, 1, "name", "component", (const char *)0); LUABIND_GET_TABLE_PARAMETER(1, component, ANNComponent, component); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, name, string, name, 0); // obj = new ConstANNComponent(component, name); LUABIND_RETURN(ConstANNComponent, obj); } //BIND_END //BIND_METHOD ConstANNComponent clone { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); AprilUtils::LuaTable copies; if (argn == 1) { copies = AprilUtils::LuaTable(L,1); } LUABIND_RETURN(ConstANNComponent, dynamic_cast(obj->clone(copies))); } //BIND_END april-ann-0.4.1/packages/ann/ann/c_src/000077500000000000000000000000001263004425400175745ustar00rootroot00000000000000april-ann-0.4.1/packages/ann/ann/c_src/activation_function_component.cc000066400000000000000000000133071263004425400262370ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "activation_function_component.h" #include "unused_variable.h" using namespace Basics; using namespace AprilUtils; using namespace AprilMath; namespace ANN { ActivationFunctionANNComponent::ActivationFunctionANNComponent(const char *name, bool need_flatten) : ANNComponent(name, 0, 0, 0), input(0), output(0), error_input(0), error_output(0), need_flatten(need_flatten) { } ActivationFunctionANNComponent::~ActivationFunctionANNComponent() { if (input) DecRef(input); if (error_input) DecRef(error_input); if (output) DecRef(output); if (error_output) DecRef(error_output); } Token *ActivationFunctionANNComponent::doForward(Token* _input, bool during_training) { UNUSED_VARIABLE(during_training); // error checking if ( (_input == 0) || (_input->getTokenCode() != table_of_token_codes::token_matrix)) ERROR_EXIT1(129,"Incorrect input Token type, expected token_matrix! [%s]\n", name.c_str()); // change current input by new input AssignRef(input,_input->convertTo()); MatrixFloat *input_mat = input->getMatrix(); april_assert(input_mat->getNumDim() >= 2); if (!input_mat->getIsContiguous()) { input_mat = input_mat->clone(); AssignRef(input,new TokenMatrixFloat(input_mat)); } #ifdef USE_CUDA input_mat->setUseCuda(use_cuda); #endif // new output to fit the bunch MatrixFloat *output_mat = input_mat->cloneOnlyDims(); AssignRef(output,new TokenMatrixFloat(output_mat)); // flatten if needed flat_input_mat = input_mat; flat_output_mat = output_mat; if (need_flatten && input_mat->getNumDim() > 2) { int dims[2] = { input_mat->getDimSize(0), input_mat->size() / input_mat->getDimSize(0) }; flat_input_mat = input_mat->rewrap(dims, 2); flat_output_mat = output_mat->rewrap(dims, 2); } // execute apply activations abstract method applyActivation(flat_input_mat.get(), flat_output_mat.get()); return output; } Token *ActivationFunctionANNComponent::doBackprop(Token *_error_input) { // error checking if ( (_error_input == 0) || (_error_input->getTokenCode() != table_of_token_codes::token_matrix)) ERROR_EXIT1(129,"Incorrect input error Token type, expected token_matrix! [%s]\n", name.c_str()); // change current input by new input AssignRef(error_input,_error_input->convertTo()); MatrixFloat *error_input_mat = error_input->getMatrix(); april_assert(error_input_mat->getNumDim() >= 2); if (!error_input_mat->getIsContiguous()) { error_input_mat = error_input_mat->clone(); AssignRef(error_input,new TokenMatrixFloat(error_input_mat)); } #ifdef USE_CUDA error_input_mat->setUseCuda(use_cuda); #endif // new output to fit the bunch MatrixFloat *error_output_mat = error_input_mat->cloneOnlyDims(); AssignRef(error_output,new TokenMatrixFloat(error_output_mat)); if (!error_output_mat->sameDim(input->getMatrix())) ERROR_EXIT1(129, "Different bunches found at doForward and doBackprop [%s]\n", name.c_str()); // flatten if needed flat_error_input_mat = error_input_mat; flat_error_output_mat = error_output_mat; if (need_flatten && error_input_mat->getNumDim() > 2) { int dims[2] = { error_input_mat->getDimSize(0), error_input_mat->size() / error_input_mat->getDimSize(0) }; flat_error_input_mat = error_input_mat->rewrap(dims, 2); flat_error_output_mat = error_output_mat->rewrap(dims, 2); } // apply derivatives at gradients multiplyDerivatives(flat_input_mat.get(), flat_output_mat.get(), flat_error_input_mat.get(), flat_error_output_mat.get()); return error_output; } void ActivationFunctionANNComponent::reset(unsigned int it) { UNUSED_VARIABLE(it); if (input) DecRef(input); if (error_input) DecRef(error_input); if (output) DecRef(output); if (error_output) DecRef(error_output); input = 0; error_input = 0; output = 0; error_output = 0; flat_input_mat.reset(); flat_output_mat.reset(); flat_error_input_mat.reset(); flat_error_output_mat.reset(); } void ActivationFunctionANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); if (input_size == 0) input_size = output_size; if (output_size == 0) output_size = input_size; if (input_size != output_size) ERROR_EXIT3(240, "ActivationFunctionANNComponent input/output " "sizes must be equal (component %s): %d != %d\n", name.c_str(), input_size, output_size); } } // namespace ANN april-ann-0.4.1/packages/ann/ann/c_src/activation_function_component.h000066400000000000000000000107111263004425400260750ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef ACTFCOMPONENT_H #define ACTFCOMPONENT_H #include "ann_component.h" #include "MersenneTwister.h" #include "smart_ptr.h" #include "token_matrix.h" namespace ANN { /** * @brief An abstract class that defines the basic interface that * the activation functions should fulfill. * * This class implements all methods of ANNComponent, and * declare two protected abstract methods: applyActivation() and * multiplyDerivatives(). */ class ActivationFunctionANNComponent : public ANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(ActivationFunctionANNComponent); Basics::TokenMatrixFloat *input, *output, *error_input, *error_output; bool need_flatten; AprilUtils::SharedPtr flat_input_mat; AprilUtils::SharedPtr flat_output_mat; AprilUtils::SharedPtr flat_error_input_mat; AprilUtils::SharedPtr flat_error_output_mat; protected: /** * @brief This method receives two matrices, applies the activation over * the input and stores the result into the output matrix. * * @param[in] input_units - It is a matrix with the input. * @param[out] output_units - It is a matrix where the result must be * stored. Its content should be overwritten. */ virtual void applyActivation(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units) = 0; /** * @brief This method receives four matrices, two input/output with neuron * values before/after activation, and two input/output with * incoming/outgoing error deltas. * * @param[in] input_units - It is the matrix given as input in applyActivation. * @param[in] output_units - It is the matrix given as output at applyActivation. * @param[in] input_errors - It is another matrix with the incoming error deltas. * @param[out] output_errors - It is a matrix where the outgoing error deltas * would be stored. Its content should be overwritten. */ virtual void multiplyDerivatives(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units, Basics::MatrixFloat *input_errors, Basics::MatrixFloat *output_errors) = 0; public: ActivationFunctionANNComponent(const char *name=0, bool need_flatten=false); virtual ~ActivationFunctionANNComponent(); virtual Basics::Token *getInput() { return input; } virtual Basics::Token *getOutput() { return output; } virtual Basics::Token *getErrorInput() { return error_input; } virtual Basics::Token *getErrorOutput() { return error_output; } // virtual void setInput(Basics::Token *tk) { AssignRef(input, tk->convertTo()); } virtual void setOutput(Basics::Token *tk) { AssignRef(output, tk->convertTo()); } virtual void setErrorInput(Basics::Token *tk) { AssignRef(error_input, tk->convertTo()); } virtual void setErrorOutput(Basics::Token *tk) { AssignRef(error_output, tk->convertTo()); } virtual Basics::Token *doForward(Basics::Token* input, bool during_training); virtual Basics::Token *doBackprop(Basics::Token *input_error); virtual void reset(unsigned int it=0); virtual void build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); // virtual const char *luaCtorName() const; // virtual int exportParamsToLua(lua_State *L); }; } #endif // ACTFCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/activation_function_kernels.cu000066400000000000000000000334021263004425400257200ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "activation_function_kernels.h" #include "april_assert.h" #include "cblas_headers.h" #include "cmath_overloads.h" #include "map_matrix.h" #include "reduce_matrix.h" #include "smart_ptr.h" using namespace AprilMath; using namespace AprilMath::MatrixExt; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Operations; using namespace AprilMath::MatrixExt::Reductions; namespace ANN { namespace Kernels { template struct prelu { APRIL_CUDA_EXPORT T operator()(const float &x, const float &w) const { return (x > T(0.0f)) ? (x) : (w*x); } }; template struct prelu_der { APRIL_CUDA_EXPORT T operator()(const float &x, const float &w) const { return (x > T(0.0f)) ? T(1.0f) : (w); } }; void applyHardTanhDerivative(Basics::MatrixFloat *output_errors, const Basics::MatrixFloat *input_units, float inf, float sup) { MatrixScalarMap1(input_units, AprilMath::m_curried_clamp_der(inf, sup), output_errors); } void applyTanh(Basics::MatrixFloat *output, const Basics::MatrixFloat *input) { MatrixScalarMap1(input, AprilMath::Functors::m_antisym_logistic(), output); } void applyTanhDerivative(Basics::MatrixFloat *output_errors, const Basics::MatrixFloat *output_units) { MatrixScalarMap1(output_units, AprilMath::Functors::m_antisym_logistic_der(), output_errors); } void applyLogistic(Basics::MatrixFloat *output, const Basics::MatrixFloat *input) { MatrixScalarMap1(input, AprilMath::Functors::m_logistic(), output); } void applyLogisticDerivative(Basics::MatrixFloat *output_errors, const Basics::MatrixFloat *output_units) { MatrixScalarMap1(output_units, AprilMath::Functors::m_logistic_der(), output_errors); } void applySoftsign(Basics::MatrixFloat *output, const Basics::MatrixFloat *input) { MatrixScalarMap1(input, AprilMath::Functors::m_softsign(), output); } void applySoftsignDerivative(Basics::MatrixFloat *output_errors, const Basics::MatrixFloat *output_units) { MatrixScalarMap1(output_units, AprilMath::Functors::m_softsign_der(), output_errors); } void applySoftplus(Basics::MatrixFloat *output, const Basics::MatrixFloat *input) { MatrixScalarMap1(input, AprilMath::Functors::m_softplus(), output); } void applySoftplusDerivative(Basics::MatrixFloat *output_errors, const Basics::MatrixFloat *input_units) { MatrixScalarMap1(input_units, AprilMath::Functors::m_softplus_der(), output_errors); } void applyReLU(Basics::MatrixFloat *output, const Basics::MatrixFloat *input) { MatrixScalarMap1(input, AprilMath::Functors::m_relu(), output); } void applyReLUDerivative(Basics::MatrixFloat *output_errors, const Basics::MatrixFloat *input_units) { MatrixScalarMap1(input_units, AprilMath::Functors::m_relu_der(), output_errors); } void applyLeakyReLU(Basics::MatrixFloat *output, const Basics::MatrixFloat *input, float leak) { MatrixScalarMap1(input, AprilMath::Functors::m_leaky_relu(leak), output); } void applyLeakyReLUDerivative(Basics::MatrixFloat *output_errors, const Basics::MatrixFloat *input_units, float leak) { MatrixScalarMap1(input_units, AprilMath::Functors::m_leaky_relu_der(leak), output_errors); } void applyPReLU(Basics::MatrixFloat *output, Basics::MatrixFloat *input, const Basics::MatrixFloat *w) { april_assert(w->getDimSize(0) == input->getDimSize(1)); april_assert(w->getDimSize(1) == 1); AprilUtils::SharedPtr input_slice; AprilUtils::SharedPtr output_slice; for (int i=0; igetDimSize(0); ++i) { input_slice = input->select(0, i, input_slice.get()); output_slice = output->select(0, i, output_slice.get()); MatrixScalarMap2(input_slice.get(), w, prelu(), output_slice.get()); } } void applyPReLUDerivative(Basics::MatrixFloat *output_errors, Basics::MatrixFloat *input_units, const Basics::MatrixFloat *w) { april_assert(w->getDimSize(0) == input_units->getDimSize(1)); april_assert(w->getDimSize(1) == 1); AprilUtils::SharedPtr input_slice; AprilUtils::SharedPtr output_slice; for (int i=0; igetDimSize(0); ++i) { input_slice = input_units->select(0, i, input_slice.get()); output_slice = output_errors->select(0, i, output_slice.get()); MatrixScalarMap2(input_slice.get(), w, prelu_der(), output_slice.get()); } } void applyLogLogistic(Basics::MatrixFloat *output, const Basics::MatrixFloat *input) { MatrixScalarMap1(input, AprilMath::Functors::m_log_logistic(), output); } void applySoftmax(Basics::MatrixFloat *output, const Basics::MatrixFloat *input) { unsigned int bunch_size = input->getDimSize(0); unsigned int size = input->getDimSize(1); #ifdef USE_CUDA if (input->getCudaFlag()) { AprilUtils::SharedPtr maximums( matMax(input,1) ); matCopy(output, input); AprilUtils::SharedPtr column; for (unsigned int i=0; iselect(1,i,column.get()); matAxpy(column.get(), -1.0f, maximums.get()); } maximums.reset(); // frees the memory matExp(output); AprilUtils::SharedPtr sums( matSum(output,1) ); // Avoid overhead of division operator inside loop. matDiv(sums.get(), 1.0f); // divide once for (unsigned int i=0; iselect(1,i,column.get()); matCmul(column.get(), sums.get()); // multiply several times } } else { #endif for (unsigned int b = 0; b < bunch_size; ++b) { Basics::MatrixFloat::const_iterator input_it(input->iteratorAt(b,0)); float minimum = *input_it; float maximum = *input_it; ++input_it; for (unsigned int i = 2; i < size; i += 2) { float prev_unit = *input_it; ++input_it; float cur_unit = *input_it; ++input_it; if (prev_unit < cur_unit) { if (prev_unit < minimum) minimum = prev_unit; if (cur_unit > maximum) maximum = cur_unit; } else { if (cur_unit < minimum) minimum = cur_unit; if (prev_unit > maximum) maximum = prev_unit; } } if ((size & 1) == 0) { // si es impar if (*input_it < minimum) minimum = *input_it; if (*input_it > maximum) maximum = *input_it; } if ((maximum - minimum) > 30.0f) minimum = maximum - 30.0f; double addition = 0; input_it = input->iteratorAt(b,0); Basics::MatrixFloat::iterator output_it(output->iteratorAt(b,0)); for (unsigned int i = 0; i < size; i++) { double e = exp(*input_it - minimum); *output_it = e; addition += e; ++input_it; ++output_it; } float ratio = 1.0f/addition; output_it = output->iteratorAt(b,0); for (unsigned int i = 0; i < size; i++) { *output_it *= ratio; ++output_it; } } #ifdef USE_CUDA } #endif } void applyLogSoftmax(Basics::MatrixFloat *output, const Basics::MatrixFloat *input) { unsigned int bunch_size = input->getDimSize(0); unsigned int size = input->getDimSize(1); #ifdef USE_CUDA if (input->getCudaFlag()) { AprilUtils::SharedPtr maximums( matMax(input,1) ); matCopy(output, input); AprilUtils::SharedPtr column; for (unsigned int i=0; iselect(1,i,column.get()); matAxpy(column.get(), -1.0f, maximums.get()); } maximums.reset(); AprilUtils::SharedPtr sums; sums = MatrixScalarReduce1OverDimension (output, // b 1, // dimension for the reduction // This template instantiates an operator like this: // operator()(acc, b) { acc += exp(b); } AprilMath:: make_r_map1(// aux = exp(b) AprilMath::Functors::m_exp(), // acc += aux AprilMath::Functors::r_add() ), AprilMath::Functors::r_add(), 0.0f); matLog(sums.get()); for (unsigned int i=0; iselect(1,i,column.get()); matAxpy(column.get(), -1.0f, sums.get()); } } else { #endif for (unsigned int b = 0; b < bunch_size; ++b) { Basics::MatrixFloat::const_iterator input_it(input->iteratorAt(b,0)); float maximum = *input_it; ++input_it; for (unsigned int i = 2; i < size; i += 2) { float prev_unit = *input_it; ++input_it; float cur_unit = *input_it; ++input_it; if (prev_unit < cur_unit) { if (cur_unit > maximum) maximum = cur_unit; } else { if (prev_unit > maximum) maximum = prev_unit; } } if ((size & 1) == 0) { // si es par if (*input_it > maximum) maximum = *input_it; } input_it = input->iteratorAt(b,0); Basics::MatrixFloat::iterator output_it(output->iteratorAt(b,0)); double addition = 0.0f; for (unsigned int i = 0; i < size; i++) { *output_it = *input_it - maximum; double exp_output = AprilMath::m_exp(static_cast(*output_it)); addition += exp_output; ++input_it; ++output_it; } output_it = output->iteratorAt(b,0); float ratio = static_cast(log(addition)); for (unsigned int i = 0; i < size; i++) { *output_it -= ratio; april_assert(!(*output_it > 0.0f) && "Numerical inestability at log-softmax activation function"); ++output_it; } } #ifdef USE_CUDA } #endif } void applySoftmaxDerivative(Basics::MatrixFloat *output_errors_mat, const Basics::MatrixFloat *input_errors_mat, const Basics::MatrixFloat *output_units_mat) { unsigned int size = output_units_mat->getDimSize(1); AprilUtils::SharedPtr column, sums; sums = MatrixScalarReduce2OverDimension (output_units_mat, // b input_errors_mat, // c 1, // dimension for the reduction // This template instantiates an operator like this: // operator()(acc, b, c) { acc += b * c; } AprilMath:: make_r_map2(// aux = b*c AprilMath::Functors::m_mul(), // acc += aux AprilMath::Functors::r_add() ), AprilMath::Functors::r_add(), 0.0f); matCopy(output_errors_mat, input_errors_mat); for (unsigned int i=0; iselect(1,i,column.get()); matAxpy(column.get(), -1.0f, sums.get()); } matCmul(output_errors_mat, output_units_mat); } } // namespace Kernels } // namespace ANN april-ann-0.4.1/packages/ann/ann/c_src/activation_function_kernels.h000066400000000000000000000072141263004425400255420ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef ACTF_KERNELS_H #define ACTF_KERNELS_H #include "activation_function_kernels.h" #include "matrixFloat.h" namespace ANN { namespace Kernels { void applyHardTanhDerivative(Basics::MatrixFloat *output_errors, const Basics::MatrixFloat *input_units, float inf, float sup); void applyTanh(Basics::MatrixFloat *output, const Basics::MatrixFloat *input); void applyTanhDerivative(Basics::MatrixFloat *output_errors, const Basics::MatrixFloat *output_units); void applyLogistic(Basics::MatrixFloat *output, const Basics::MatrixFloat *input); void applyLogisticDerivative(Basics::MatrixFloat *output_errors, const Basics::MatrixFloat *output_units); void applySoftsign(Basics::MatrixFloat *output, const Basics::MatrixFloat *input); void applySoftsignDerivative(Basics::MatrixFloat *output_errors, const Basics::MatrixFloat *output_units); void applySoftplus(Basics::MatrixFloat *output, const Basics::MatrixFloat *input); void applySoftplusDerivative(Basics::MatrixFloat *output_errors, const Basics::MatrixFloat *input_units); void applyReLU(Basics::MatrixFloat *output, const Basics::MatrixFloat *input); void applyReLUDerivative(Basics::MatrixFloat *output_errors, const Basics::MatrixFloat *input_units); void applyLeakyReLU(Basics::MatrixFloat *output, const Basics::MatrixFloat *input, float leak); void applyLeakyReLUDerivative(Basics::MatrixFloat *output_errors, const Basics::MatrixFloat *input_units, float leak); void applyPReLU(Basics::MatrixFloat *output, Basics::MatrixFloat *input, const Basics::MatrixFloat *w); void applyPReLUDerivative(Basics::MatrixFloat *output_errors, Basics::MatrixFloat *input_units, const Basics::MatrixFloat *w); void applyLogLogistic(Basics::MatrixFloat *output, const Basics::MatrixFloat *input); void applySoftmax(Basics::MatrixFloat *output, const Basics::MatrixFloat *input); void applyLogSoftmax(Basics::MatrixFloat *output, const Basics::MatrixFloat *input); void applySoftmaxDerivative(Basics::MatrixFloat *output_errors, const Basics::MatrixFloat *input_errors, const Basics::MatrixFloat *output_units); } } #endif // ACTF_KERNELS_H april-ann-0.4.1/packages/ann/ann/c_src/ann_component.cc000066400000000000000000000022141263004425400227400ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "ann_component.h" using namespace Basics; using namespace AprilUtils; using namespace AprilMath; namespace ANN { unsigned int ANNComponent::next_name_id = 1; unsigned int ANNComponent::next_weights_id = 1; unsigned int mult(const int *v, int n) { int m = 1; for (int i=0; i #include "connection.h" #include "disallow_class_methods.h" #include "error_print.h" #include "function_interface.h" #include "mystring.h" #include "lua_table.h" #include "token_base.h" #include "token_null.h" #include "matrixFloat.h" #include "unused_variable.h" #include "vector.h" #define ASSERT_MATRIX(m) /** * @brief Maximum size of automatically generated names. * * @see Methods ANN::ANNComponent::generateDefaultWeightsName(), * ANN::ANNComponent::generateDefaultWeightsName(). */ #define MAX_NAME_STR 256 #define INPUT_STR "input" #define OUTPUT_STR "output" #define ERROR_INPUT_STR "error_input" #define ERROR_OUTPUT_STR "error_output" namespace ANN { // forward declaration class ANNComponent; } DECLARE_LUA_TABLE_BIND_SPECIALIZATION(ANN::ANNComponent); /** * @brief All ANN components and other stuff is implemented here. */ namespace ANN { unsigned int mult(const int *v, int n); /** * @brief Virtual class with basic interface and behavior of ANNs. * * @note It is a Referenced class and needs heap allocation. * * An ANN component is the basic module which allows to define Artificial * Neural Networks (ANNs). Its basic interface allows to compute forward step, * back-propagate errors and weight gradients computation. * Some ANNComponent's can contain parameters or weights which depend upon the * final model topology and can be computed by some basic introspection * technique. For this purpose, an ANNComponent can be in two states: * non-built and built. Build method changes this state and allows the * ANNComponent to allocate the necessary resources derived from its * input/output connections. * * Every ANNComponent has a unique name which allows to locate and identify * it. Optionally, a non-unique weights_name is given and allows to locate and * identify the component parameters. ANNComponents which share the same * weights_name will share also the same weight parameters after the build * call. * * ANNComponent's work majorly over Basics::MatrixFloat and * Basics::SparseMatrixFloat classes. Both objects can be put together by * using Basics::Token instances, and the methods defined here receive and * produce always Basics::Token references. */ class ANNComponent : public Functions::FunctionInterface { APRIL_DISALLOW_COPY_AND_ASSIGN(ANNComponent); public: /** * @brief Constructor with names and input/output sizes. * * @param name - The name of this instance. * * @param weights_name - Optional name for the weight parameters. * * @param input_size - Optional input size of the ANNComponent. * * @param output_size - Optional output size of the ANNComponent. * * @note A value of @c weights_name=0 indicates that non parameters are * needed by the ANNComponent. A value @c input_size=0 or @c output_size=0 * indicates that input or output sizes are unknown and tentatively any of * them can be dynamic (different patterns can have different sizes) if the * ANNComponent supports that. */ ANNComponent(const char *name, const char *weights_name=0, unsigned int input_size=0, unsigned int output_size=0) : input_size(input_size), output_size(output_size), use_cuda(AprilMath::GPUMirroredMemoryBlockBase::USE_CUDA_DEFAULT) { if (name) { this->name = AprilUtils::string(name); ++next_name_id; // increase the counter in any case } else { generateDefaultName(); } if (weights_name) this->weights_name = AprilUtils::string(weights_name); } /// Destructor of ANNComponent. virtual ~ANNComponent() { } /// Returns the name of the component. const AprilUtils::string &getName() const { return name; } /** * Returns the name of the component weight parameters. * * @note The weights_name string can be an empty string (NULL string). */ const AprilUtils::string &getWeightsName() const { return weights_name; } /// Indicates if the weights_name string is valid, i.e., it is not empty. bool hasWeightsName() const { return !weights_name.empty(); } /** * @brief Sets @c next_name_id=0 and @c next_weights_id=0. * * ANNComponent implements a basic procedure to produce automatic name * and/or weight_name generation. It uses two counters which are increased * with every automatically generated name. generateDefaultName() and * generateDefaultWeightsName() are the methods available for these * purposes. */ static void resetIdCounters() { next_name_id=0; next_weights_id=0; } /// Increments the ID counter for names static void incNamesIdCounter() { ++next_name_id; } /// Increments the ID counter for weights static void incWeightsIdCounter() { ++next_weights_id; } /// Returns the built state of the ANNComponent. bool getIsBuilt() const { return is_built; } /** * @brief Generates a default name for weight parameters. * * The weights_name is generated with the given prefix. * * @note If not prefix or @c prefix=0 is given, a @c "w" will be used by * default. * * @see Method resetIdCounters(). */ void generateDefaultWeightsName(const char *prefix=0) { char str_id[MAX_NAME_STR+1]; char default_prefix[2] = "w"; if (prefix == 0) prefix = default_prefix; snprintf(str_id, MAX_NAME_STR, "%s%u", prefix, next_weights_id); weights_name = AprilUtils::string(str_id); ++next_weights_id; } // FunctionInterface methods virtual unsigned int getInputSize() const { return input_size; } virtual unsigned int getOutputSize() const { return output_size; } virtual Basics::Token *calculate(Basics::Token *input) { AprilUtils::SharedPtr out( this->doForward(input, false) ); reset(); Basics::Token *ptr = out.release(); ReleaseRef(ptr); return ptr; } ///////////////////////////////////////////// /** * @brief Computes the output size given a vector of dimension sizes. * * @param input_size - A AprilUtils::vector with a list of input dimension * sizes. * * @param[out] output_size - A AprilUtils::vector reference which will * contain the output dimension sizes for the current ANNComponent with the * given @c input_size vector. * * This method is useful to compute output size of convolutional components. * * @note The given @c output_size reference is cleared before appending the * result, i.e., AprilUtils::vector::clear() method is called as first * instruction. * * @note Identity function is implemented by default in the ANNComponent * virtual class. */ virtual void precomputeOutputSize(const AprilUtils::vector &input_size, AprilUtils::vector &output_size) { output_size.clear(); if (getOutputSize()>0) output_size.push_back(getOutputSize()); else if (getInputSize() > 0) output_size.push_back(getInputSize()); else output_size = input_size; } /// Returns a Basics::Token with the last given input. virtual Basics::Token *getInput() { return 0; } /// Returns a Basics::Token with the last produced output. virtual Basics::Token *getOutput() { return 0; } /// Returns a Basics::Token with the last given deltas (error input) virtual Basics::Token *getErrorInput() { return 0; } /// Returns a Basics::Token with the last produced deltas (error output) virtual Basics::Token *getErrorOutput() { return 0; } /// Sets a Basics::Token as the last given input. virtual void setInput(Basics::Token *tk) { ERROR_EXIT(128, "NOT IMPLEMENTED\n"); UNUSED_VARIABLE(tk); } /// Sets a Basics::Token as the last produced output. virtual void setOutput(Basics::Token *tk) { ERROR_EXIT(128, "NOT IMPLEMENTED\n"); UNUSED_VARIABLE(tk); } /// Sets a Basics::Token as the last given deltas (error input) virtual void setErrorInput(Basics::Token *tk) { ERROR_EXIT(128, "NOT IMPLEMENTED\n"); UNUSED_VARIABLE(tk); } /// Sets a Basics::Token as the last produced deltas (error output) virtual void setErrorOutput(Basics::Token *tk) { ERROR_EXIT(128, "NOT IMPLEMENTED\n"); UNUSED_VARIABLE(tk); } /// Sets a Basics::Token as the last given input. virtual void setInput(AprilUtils::SharedPtr tk) { setInput(tk.get()); } /// Sets a Basics::Token as the last produced output. virtual void setOutput(AprilUtils::SharedPtr tk) { setOutput(tk.get()); } /// Sets a Basics::Token as the last given deltas (error input) virtual void setErrorInput(AprilUtils::SharedPtr tk) { setErrorInput(tk.get()); } /// Sets a Basics::Token as the last produced deltas (error output) virtual void setErrorOutput(AprilUtils::SharedPtr tk) { setErrorOutput(tk.get()); } /** * @brief Computes the forward step of the ANNComponent. * * @param input - A Basics::Token with the input given to the ANNComponent. * * @param during_training - A bool which allows to indicate if the * forward step is during training phase or not. Some ANNComponent's need * this information to modify its behavior, e.g., DropoutANNComponent uses * it to implement dropout technique. * * @return A new Basics::Token reference with the forward step result. * * This method executes the set of operations required for each block of * connections when performing the forward step of the Backpropagation * algorithm and returns its output. * * @note Identity function is implemented by default in the ANNComponent * virtual class. */ virtual Basics::Token *doForward(Basics::Token* input, bool during_training) { UNUSED_VARIABLE(during_training); return input; } /** * @brief Computes the back-propagation of delta errors step. * * @param input_error - A Basics::Token with the delta errors of the * ANNComponent outputs. * * @return A Basics::Token reference with the delta errors of the * ANNComponent inputs (@c output_error). * * This method back-propagates error derivatives, i.e., delta * errors. Receives input error gradients, and returns its output error * gradients Basics::Token. * * @note By default the identity function is implemented by ANNComponent * virtual class. */ virtual Basics::Token *doBackprop(Basics::Token *input_error) { return input_error; } /** * @brief Releases the references of Basics::Token acquired at doForward() * and doBackprop() methods. * * This method receives a counter of the number of times it is sequentially * called by optimizers (as conjugate gradient) using the same input/output * patterns. * * @param it - The number of times it has been called sequentially with the * same input/output patterns. * * @note StochasticANNComponent uses the given @c it value to reuse the same * random sequence in every doForward(). A value of @c it=0 changes the * random sequence. */ virtual void reset(unsigned int it=0) { UNUSED_VARIABLE(it); } /** * @brief Computation of gradient of all ANNComponent's is done here. * * @param[in,out] weight_grads_dict - A AprilUtils::LuaTable reference where * gradient matrices will be stored. * * This method traverses all the ANNComponent's using the given * AprilUtils::LuaTable. If hasWeightsName() is true, the method * computeGradients() will be executed. * * @note The @c weight_grads_dict[weights_name] can be an empty reference, * in this case, the called method has the responsability of its proper * initialization. */ virtual void computeAllGradients(AprilUtils::LuaTable &weight_grads_dict){ if (hasWeightsName()) { computeGradients( weights_name.c_str(), weight_grads_dict ); } } /** * @brief Returns a non-built clone of the caller instance. * * @return A new ANNComponent reference in non-built state. * * @note The returned ANNComponent is in non-built state and its weight * parameters are set to an NULL reference. It is needed to call built * method with a proper weight parameters Basics::MatrixFloat. */ virtual ANNComponent *clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); return new ANNComponent(name.c_str(), weights_name.c_str(), input_size, output_size); } /** * @brief Sets the @c use_cuda value. * * @param v - A bool with the desired value for @c use_cuda flag. * * @note Derived classes which rewrite this method must call its parent * method before doing anything. */ virtual void setUseCuda(bool v) { #ifdef USE_CUDA use_cuda = v; #else UNUSED_VARIABLE(v); ERROR_PRINT("WARNING!!! Trying to set use_cuda=true with NON " "cuda compilation\n"); use_cuda = false; // always false in this case #endif } /// Getter for @c use_cuda property. bool getUseCuda() const { return use_cuda; } /** * @brief Method which changes ANNComponent state from non-built to built. * * This method finish the building of ANNComponent's topology and set * weight parameter object pointers. * * @note All derived classes which rewrite this method must call parent * method before doing anything. * * @param _input_size - The input size given to the method. It can be @c * _input_size=0 to indicate that it is unknown or don't care. * * @param _output_size - The output size given to the method. It can be @c * _input_size=0 to indicate that it is unknown or don't care. * * @param[in,out] weights_dict - A reference to AprilUtils::LuaTable where * weight matrices are stored. * * @param[out] components_dict - A AprilUtils::LuaTable of ANNComponent's which * are part of the ANN. * * @note Derived classes must re-implement this method throwing errors if * necessary when input/output sizes have unexpected values, and calling to * the parent method before doing anything. * * @note The @c weights_dict param can contain any Lua or APRIL-ANN type * indexed by @c weights_name property. It can be empty and the derived * class is responsible to initialize it properly. If it is not empty, the * derived class is responsible to check its size and type correctness. */ virtual void build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { UNUSED_VARIABLE(weights_dict); // if (is_built) ERROR_EXIT(128, "Rebuild is forbidden!!!!\n"); is_built = true; //////////////////////////////////////////////////////////////////// ANNComponent *component = components_dict.opt(name.c_str(), 0); if (component != 0 && component != this) { ERROR_EXIT1(102, "Non unique component name found: %s\n", name.c_str()); } else { component = this; components_dict.put(name.c_str(), component); } //////////////////////////////////////////////////////////////////// if (input_size == 0) input_size = _input_size; if (output_size == 0) output_size = _output_size; if (_input_size == 0) _input_size = input_size; if (_output_size == 0) _output_size = output_size; if (_output_size != 0) output_size = _output_size; if (_input_size != 0) input_size = _input_size; if (input_size != _input_size) ERROR_EXIT2(129, "Incorrect input size, expected %d, found %d\n", input_size, _input_size); if (output_size != _output_size) ERROR_EXIT2(129, "Incorrect output size, expected %d, found %d\n", output_size, _output_size); } /// Retrieve state of the component (inputs, outputs, deltas, masks, ...) virtual void copyState(AprilUtils::LuaTable &dict) { // A Lua table will contain the state. AprilUtils::LuaTable state; state.put(INPUT_STR, AprilUtils::SharedPtr(getInput())); state.put(OUTPUT_STR, AprilUtils::SharedPtr(getOutput())); state.put(ERROR_INPUT_STR, AprilUtils::SharedPtr(getErrorInput())); state.put(ERROR_OUTPUT_STR, AprilUtils::SharedPtr(getErrorOutput())); // The state is stored at dict LuaTable argument indexed by the name. dict.put(name, state); } /// Modifies the state of the component virtual void setState(AprilUtils::LuaTable &dict) { AprilUtils::LuaTable state(dict.get(name)); setInput(state.get< AprilUtils::SharedPtr >(INPUT_STR)); setOutput(state.get< AprilUtils::SharedPtr >(OUTPUT_STR)); setErrorInput(state.get< AprilUtils::SharedPtr >(ERROR_INPUT_STR)); setErrorOutput(state.get< AprilUtils::SharedPtr >(ERROR_OUTPUT_STR)); } /// Retrieve matrix weights from ANNComponent's. virtual void copyWeights(AprilUtils::LuaTable &weights_dict) { UNUSED_VARIABLE(weights_dict); } /** * @brief Abstract method to retrieve ANNComponent object. * * @note All derived classes which rewrite this method must call parent * method before doing anything. */ virtual void copyComponents(AprilUtils::LuaTable &components_dict) { components_dict.put(name.c_str(), this); } /// For debug purposes. virtual void debugInfo() { fprintf(stderr, "Component '%s' ('%s') %d inputs %d outputs\n", name.c_str(), !(weights_name.empty())?weights_name.c_str():"(null)", input_size, output_size); } /** * @brief Looks for an ANNComponent given its name. * * @param name - The name of the ANNComponent your are looking for. * * @return An ANNComponent pointer identified by @c name, or a NULL pointer * if the given name doesn't exists. * * @note By default, a leaf component only contains itself, but composed * components need to check itself name and the name of all the contained * components. * * @note All derived classes which rewrite this method must call the parent * method before doing anything. */ virtual ANNComponent *getComponent(AprilUtils::string &name) { if (this->name == name) return this; return 0; } /** * @brief Generates a name. * * The name is generated with the given prefix. * * @note If not prefix or @c prefix=0 is given, a @c "c" will be used by * default. * * @see Method resetIdCounters(). */ static AprilUtils::string generateName(const char *prefix=0) { char default_prefix[2] = "c"; char str_id[MAX_NAME_STR+1]; if (prefix == 0) prefix = default_prefix; snprintf(str_id, MAX_NAME_STR, "%s%u", prefix, next_name_id); AprilUtils::string name = AprilUtils::string(str_id); ++next_name_id; return name; } private: /// A flag which indicates if the ANNComponent has been properly built. bool is_built; /** * @brief Generates a default name for the ANNComponent. * * The name is generated with the given prefix. * * @note If not prefix or @c prefix=0 is given, a @c "c" will be used by * default. * * @see Method resetIdCounters(). */ void generateDefaultName(const char *prefix=0) { name = generateName(prefix); } protected: /// The counter for automatic name generation. static unsigned int next_name_id; /// The counter for automatic weights_name generation. static unsigned int next_weights_id; /// The name which identifies the ANNComponent. AprilUtils::string name; /// The name which identifies the ANNComponent weight parameters. AprilUtils::string weights_name; /// The input size (or domain) of the ANNComponent. unsigned int input_size; /// The output size (or range) of the ANNComponent. unsigned int output_size; /// The @c use_cuda flag. bool use_cuda; /** * @brief Computes the gradient of the weight parameters. * * This method is rewritten only by ANNComponent's which contain trainable * weight matrices, and therefore it is needed to compute its gradients. * * @param weights_name - A string with the corresponding weights name. * * @param weight_grads - A dictionary where to store the gradients. * * @note The default implementation in ANNComponent does nothing. * * @note The given weight_grads reference can be empty, and the derived * class is responsible to initialize it properly, or to check the * correctness of sizes and dimensions. */ virtual void computeGradients(const char *weights_name, AprilUtils::LuaTable &weight_grads) { UNUSED_VARIABLE(weights_name); UNUSED_VARIABLE(weight_grads); } virtual const char *luaCtorName() const { return "ann.components.base"; } // default implementation virtual int exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name; if (!weights_name.empty()) t["weights"] = weights_name; t.pushTable(L); return 1; } }; } // namespace ANN #undef MAX_NAME_STR #endif // ANNCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/batch_standardization_component.cc000066400000000000000000000206641263004425400265340ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "april_assert.h" #include "batch_standardization_component.h" #include "unused_variable.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilMath::MatrixExt::Operations; using namespace AprilMath::MatrixExt::Reductions; using namespace AprilUtils; using namespace Basics; static AprilUtils::SharedPtr computeMean(MatrixFloat *m) { float inv_N = 1.0f/static_cast(m->getDimSize(0)); AprilUtils::SharedPtr mean; mean = matSum(m, 0); matScal(mean.get(), inv_N); return mean; } static void applyCenter(MatrixFloat *m, MatrixFloat *c, float a=-1.0f) { AprilUtils::SharedPtr m_row; for (int i=0; igetDimSize(0); ++i) { m_row = m->select(0, i, m_row.get()); matAxpy(m_row.get(), a, c); } } static void applyScale(MatrixFloat *m, MatrixFloat *s) { AprilUtils::SharedPtr m_row; for (int i=0; igetDimSize(0); ++i) { m_row = m->select(0, i, m_row.get()); matCmul(m_row.get(), s); } } static void applyCenterScale(MatrixFloat *m, MatrixFloat *c, MatrixFloat *s) { AprilUtils::SharedPtr m_row; for (int i=0; igetDimSize(0); ++i) { m_row = m->select(0, i, m_row.get()); matAxpy(m_row.get(), -1.0f, c); matCmul(m_row.get(), s); } } namespace ANN { BatchStandardizationANNComponent:: BatchStandardizationANNComponent(float alpha, float epsilon, unsigned int size, const char *name, MatrixFloat *mean, MatrixFloat *inv_std) : VirtualMatrixANNComponent(name, 0, size, size), alpha(alpha), epsilon(epsilon), running_mean(mean), running_inv_std(inv_std) { setInputContiguousProperty(true); } BatchStandardizationANNComponent::~BatchStandardizationANNComponent() { } MatrixFloat *BatchStandardizationANNComponent:: privateDoForward(MatrixFloat* input, bool during_training) { if (input->getNumDim() < 2) ERROR_EXIT2(128, "A 2-dimensional matrix is expected, found %d. " "[%s]", input->getNumDim(), name.c_str()); if (running_mean.empty()) { ERROR_EXIT1(129, "Not built component %s\n", name.c_str()); } MatrixFloat *output = input->clone(); if (!during_training) { applyCenterScale(output, running_mean.get(), running_inv_std.get()); } // compute running mean and inv_std else { if (input->getDimSize(0) < 2) { ERROR_EXIT(128, "Batch std. needs more than one sample per bunch\n"); } mean = computeMean(output); applyCenter(output, mean.get()); centered = output->clone(); // copy for backprop method // apply square to output matrix matPow(output,2.0f); // compute inverted standard deviation for current batch inv_std = computeMean(output); matScalarAdd(inv_std.get(), epsilon); matSqrt(inv_std.get()); matPow(inv_std.get(), -1.0f); // update running mean and inv_std matrices matScal(running_mean.get(), 1.0f - alpha); matAxpy(running_mean.get(), alpha, mean.get()); matScal(running_inv_std.get(), 1.0f - alpha); matAxpy(running_inv_std.get(), alpha, inv_std.get()); // copy centered into output matrix and apply scale matCopy(output, centered.get()); applyScale(output, inv_std.get()); } return output; } /// In BatchStandardizationANNComponent this method is a multiplication by the weights vector MatrixFloat *BatchStandardizationANNComponent::privateDoBackprop(MatrixFloat *error_input) { if (error_input->getNumDim() < 2) ERROR_EXIT2(128, "A 2-dimensional matrix is expected, found %d. " "[%s]", error_input->getNumDim(), name.c_str()); if (mean.empty()) { ERROR_EXIT1(129, "Requires forward execution [%s]\n",name.c_str()); } // transfer of input to output MatrixFloat *error_output = error_input->clone(); matCmul(error_output, centered.get()); AprilUtils::SharedPtr gmean = computeMean(error_output); AprilUtils::SharedPtr row; for (int i=0; igetDimSize(0); ++i) { row = error_output->select(0, i, row.get()); matCopy(row.get(), gmean.get()); } matCmul(error_output, centered.get()); matScal(error_output, -1.0f); applyScale(error_output, inv_std.get()); applyScale(error_output, inv_std.get()); matAxpy(error_output, 1.0f, error_input); gmean = computeMean(error_input); applyCenterScale(error_output, gmean.get(), inv_std.get()); // return error_output; } void BatchStandardizationANNComponent::privateReset(unsigned int it) { UNUSED_VARIABLE(it); mean.reset(); inv_std.reset(); centered.reset(); } void BatchStandardizationANNComponent::computeGradients(const char *name, AprilUtils::LuaTable &weight_grads_dict) { UNUSED_VARIABLE(name); UNUSED_VARIABLE(weight_grads_dict); } ANNComponent *BatchStandardizationANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); BatchStandardizationANNComponent *component = new BatchStandardizationANNComponent(alpha, epsilon, input_size, name.c_str(), !running_mean.empty() ? running_mean->clone() : 0, !running_inv_std.empty() ? running_inv_std->clone() : 0); return component; } void BatchStandardizationANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); // if (input_size == 0 && output_size == 0) ERROR_EXIT1(141, "Impossible to compute input/output " "sizes for this component [%s]\n", name.c_str()); if (input_size == 0) input_size = output_size; else if (output_size == 0) output_size = input_size; else if (input_size != output_size) ERROR_EXIT1(142, "BatchStandardizationANNComponent input/output sizes must be equal [%s]\n", name.c_str()); //////////////////////////////////////////////////////////////////// if (!running_mean.empty()) { if (running_mean->size() != static_cast(input_size)) { ERROR_EXIT3(256, "Expected size %d, found %d in build [%s]\n", running_mean->size(), input_size, name.c_str()); } } else { running_mean = matZeros(new MatrixFloat(1, input_size)); } if (!running_inv_std.empty()) { if (running_inv_std->size() != static_cast(input_size)) { ERROR_EXIT3(256, "Expected size %d, found %d in build [%s]\n", running_inv_std->size(), input_size, name.c_str()); } } else { running_inv_std = matOnes(new MatrixFloat(1, input_size)); } } const char *BatchStandardizationANNComponent::luaCtorName() const { return "ann.components.batch_standardization"; } int BatchStandardizationANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["alpha"] = alpha; t["epsilon"] = epsilon; t["size"] = input_size; t["name"] = name; t["mean"] = running_mean; t["inv_std"] = running_inv_std; t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/batch_standardization_component.h000066400000000000000000000065741263004425400264020ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef BATCHSTANDARDIZATIONANNCOMPONENT_H #define BATCHSTANDARDIZATIONANNCOMPONENT_H #include "cblas_headers.h" #include "matrix_component.h" #include "connection.h" #include "token_matrix.h" namespace ANN { /** * @brief A component which performs standardization of its given input. * * The standardization uses vectors which are adapted during training and * fixed during evaluation phase. * * @note This component code is based in the paper: * http://arxiv.org/pdf/1502.03167v3.pdf * and the implementation of batchnormalization of Torch: * https://github.com/torch/nn/blob/master/BatchNormalization.lua */ class BatchStandardizationANNComponent : public VirtualMatrixANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(BatchStandardizationANNComponent); float alpha, epsilon; /// Mean value of current batch. AprilUtils::SharedPtr mean; /// Inverse standard deviation of current batch. AprilUtils::SharedPtr inv_std; /// Running mean computed during training to be used at inference stage. AprilUtils::SharedPtr running_mean; /// Running stddev computed during training to be used at inference stage. AprilUtils::SharedPtr running_inv_std; /// Auxiliary matrix. AprilUtils::SharedPtr centered; protected: virtual Basics::MatrixFloat *privateDoForward(Basics::MatrixFloat *input, bool during_training); virtual Basics::MatrixFloat *privateDoBackprop(Basics::MatrixFloat *input_error); virtual void privateReset(unsigned int it=0); virtual void computeGradients(const char *name, AprilUtils::LuaTable &weight_grads_dict); public: BatchStandardizationANNComponent(float alpha=0.1f, float epsilon=1e-05f, unsigned int size=0, const char *name=0, Basics::MatrixFloat *mean=0, Basics::MatrixFloat *inv_std=0); virtual ~BatchStandardizationANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void build(unsigned int input_size, unsigned int output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // BATCHSTANDARDIZATIONANNCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/bias_component.cc000066400000000000000000000160711263004425400231100ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "bias_component.h" #include "unused_variable.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilUtils; using namespace Basics; namespace ANN { BiasANNComponent::BiasANNComponent(unsigned int size, const char *name, const char *weights_name, MatrixFloat *matrix) : VirtualMatrixANNComponent(name, weights_name, size, size), bias_vector(matrix) { setInputContiguousProperty(true); if (weights_name == 0) generateDefaultWeightsName("b"); } BiasANNComponent::~BiasANNComponent() { } MatrixFloat *BiasANNComponent::privateDoForward(MatrixFloat* input, bool during_training) { UNUSED_VARIABLE(during_training); if (input->getNumDim() < 2) ERROR_EXIT2(128, "At 2-dimensional matrix is expected, found %d. " "[%s]", input->getNumDim(), name.c_str()); if (!bias_vector) ERROR_EXIT1(129, "Not built component %s\n", name.c_str()); unsigned int bunch_size = input->getDimSize(0); // linear transfer of input to output MatrixFloat *output = input->clone(); // bias MatrixFloat *bias_ptr = bias_vector.get(); if (bunch_size == 1) { matAxpy(output, 1.0f, bias_ptr); } else { // addition of bias vector at output doAxpyLoop(output_size, 1.0f, bias_ptr->getRawDataAccess(), bias_ptr->getStrideSize(0), 0, output->getRawDataAccess(), output->getStrideSize(1), 0, bunch_size, 0, output->getStrideSize(0), use_cuda); } // return output; } /// In BiasANNComponent this method is a by-pass MatrixFloat *BiasANNComponent::privateDoBackprop(MatrixFloat *error_input) { return error_input; } void BiasANNComponent::privateReset(unsigned int it) { UNUSED_VARIABLE(it); // reset shared counter bias_vector->resetSharedCount(); } void BiasANNComponent::computeGradients(const char *name, AprilUtils::LuaTable &weight_grads_dict) { // count one use of the vector bias_vector->addToSharedCount(); MatrixFloat *grads_mat = weight_grads_dict.opt(name, 0); if (grads_mat == 0) { grads_mat = bias_vector->cloneOnlyDims(); matZeros(grads_mat); weight_grads_dict.put(name, grads_mat); } else if (!grads_mat->sameDim(bias_vector.get())) { ERROR_EXIT(128, "Incorrect weights matrix dimensions\n"); } #ifdef USE_CUDA grads_mat->setUseCuda(use_cuda); #endif MatrixFloat *error_input_mat = getErrorInputMatrix(); unsigned int bunch_size = error_input_mat->getDimSize(0); // bias update: prev_bias[j] = prev_bias[j] + \sum_b norm_learn_rate * ERROR_INPUT[b,j] if (bunch_size == 1) { matAxpy(grads_mat, 1.0f, error_input_mat); } else { doAxpyLoop(output_size, 1.0f, error_input_mat->getRawDataAccess(), error_input_mat->getStrideSize(1), 0, grads_mat->getRawDataAccess(), grads_mat->getStrideSize(0), 0, bunch_size, error_input_mat->getStrideSize(0), 0, use_cuda); } } ANNComponent *BiasANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); BiasANNComponent *component = new BiasANNComponent(input_size, name.c_str(), weights_name.c_str()); return component; } void BiasANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); // if (input_size == 0 && output_size == 0) { ERROR_EXIT1(141, "Impossible to compute input/output " "sizes for this component [%s]\n", name.c_str()); } if (input_size == 0) input_size = output_size; else if (output_size == 0) output_size= input_size; else if (input_size != output_size) { ERROR_EXIT1(142, "BiasANNComponent input/output sizes must be equal [%s]\n", name.c_str()); } unsigned int weights_input_size = 1; unsigned int weights_output_size = output_size; //////////////////////////////////////////////////////////////////// MatrixFloat *w = weights_dict.opt(weights_name, 0); // printf("%s :: %p %p\n", weights_name.c_str(), w, bias_vector); if (w != 0) { bias_vector = w; // printf("COPY OF BIAS FROM HASH %s\n", weights_name.c_str()); if (!Connections::checkInputOutputSizes(bias_vector.get(), weights_input_size, weights_output_size)) ERROR_EXIT3(256,"The weights matrix input/output sizes are not correct, " "expected %d inputs and %d outputs. [%s]\n", weights_input_size, weights_output_size, name.c_str()); } else { if (bias_vector.empty()) { // printf("NEW OF BIAS %s\n", weights_name.c_str()); bias_vector = Connections::build(weights_input_size, weights_output_size); } // else printf("USING PREVIOUS BIAS %s\n", weights_name.c_str()); weights_dict.put(weights_name, bias_vector.get()); } } void BiasANNComponent::copyWeights(AprilUtils::LuaTable &weights_dict) { if (bias_vector.empty()) ERROR_EXIT1(100, "Component not built, impossible execute copyWeights [%s]\n", name.c_str()); MatrixFloat *w = weights_dict.opt(weights_name, 0); if (w != 0 && w != bias_vector.get()) ERROR_EXIT2(101, "Weights dictionary contains %s weights name which is " "not shared with bias_vector attribute [%s]\n", weights_name.c_str(), name.c_str()); else if (w == 0) { weights_dict.put(weights_name, bias_vector.get()); } } const char *BiasANNComponent::luaCtorName() const { return "ann.components.bias"; } int BiasANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name; t["weights"] = weights_name; t["size"] = getOutputSize(); t["matrix"] = bias_vector.get(); t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/bias_component.h000066400000000000000000000044671263004425400227600ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef BIASANNCOMPONENT_H #define BIASANNCOMPONENT_H #include "cblas_headers.h" #include "matrix_component.h" #include "connection.h" #include "token_matrix.h" namespace ANN { /// A component which adds a bias to the given bi-dimensional input matrix. class BiasANNComponent : public VirtualMatrixANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(BiasANNComponent); AprilUtils::SharedPtr bias_vector; protected: virtual Basics::MatrixFloat *privateDoForward(Basics::MatrixFloat *input, bool during_training); virtual Basics::MatrixFloat *privateDoBackprop(Basics::MatrixFloat *input_error); virtual void privateReset(unsigned int it=0); virtual void computeGradients(const char *name, AprilUtils::LuaTable &weight_grads_dict); public: BiasANNComponent(unsigned int size=0, const char *name=0, const char *weights_name=0, Basics::MatrixFloat *matrix=0); virtual ~BiasANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void build(unsigned int input_size, unsigned int output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual void copyWeights(AprilUtils::LuaTable &weights_dict); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // BIASANNCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/component_properties.h000066400000000000000000000040421263004425400242230ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef COMPONENT_PROPERTIES_H #define COMPONENT_PROPERTIES_H #include "disallow_class_methods.h" // Properties for VirtualMatrixANNComponent and MatrixInputSwitchANNComponent #define DEFAULT_INPUT_CONTIGUOUS_PROPERTY false namespace ANN { class ComponentPropertiesAndAsserts { APRIL_DISALLOW_COPY_AND_ASSIGN(ComponentPropertiesAndAsserts); private: // Properties and asserts of input matrices needed by derived classes, and // ensured or asserted by this class. CURRENTLY ONLY ONE PROPERTY /// Contiguous property for input matrices (input and error_input) bool input_contiguous; protected: // Properties and asserts setters. It is recommended to call always this // setters in order to make clear the properties of your class. void setInputContiguousProperty(bool v) { input_contiguous = v; } // Properties and asserts getters. bool getInputContiguousProperty() const { return input_contiguous; } ///////////////////////////////////////////////////////////////////////// ComponentPropertiesAndAsserts() : input_contiguous(DEFAULT_INPUT_CONTIGUOUS_PROPERTY) { } virtual ~ComponentPropertiesAndAsserts() { } }; } #endif // COMPONENT_PROPERTIES_H april-ann-0.4.1/packages/ann/ann/c_src/connection.cc000066400000000000000000000136221263004425400222460ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "buffer_list.h" #include "connection.h" #include "check_floats.h" #include "smart_ptr.h" #include "c_string.h" #include "swap.h" #include "utilMatrixFloat.h" using namespace AprilIO; using namespace AprilMath; using namespace AprilUtils; using namespace Basics; #define MAX_ITERATIONS_RANDOMIZE_LOOP 1000 // generates a random weight, checking number of iterations and weightnearzero #define rnd_weight(rnd, value, dinf, range, weightnearzero) do { \ unsigned int it = 0; \ do { \ (value) = (rnd)->rand((range))+(dinf); \ it++; \ } while (it < MAX_ITERATIONS_RANDOMIZE_LOOP && \ fabs((value)) < (weightnearzero)); \ if (fabs((value)) < (weightnearzero)) \ ERROR_PRINT("# WARNING!!! Detected weightnearzero\n"); \ } while(false); namespace ANN { const double Connections::weightnearzero = 1e-7; MatrixFloat *Connections::build(unsigned int num_inputs, unsigned int num_outputs) { int dims[2] = { static_cast(num_outputs), static_cast(num_inputs) }; MatrixFloat *weights = new MatrixFloat(2, dims); if (weights == 0) ERROR_EXIT(130, "Impossible to allocate memory\n"); return weights; } bool Connections::checkInputOutputSizes(const MatrixFloat *weights, unsigned int input_size, unsigned int output_size) { if (getOutputSize(weights) != output_size) { ERROR_PRINT("Incorrect output size!!!\n"); return false; } if (getInputSize(weights) != input_size) { ERROR_PRINT("Incorrect input size!!!\n"); return false; } return true; } // Crea de forma aleatoria el conjunto de pesos con valores en el // rango [low, high] void Connections::randomizeWeights(MatrixFloat *weights, MTRand *rnd, float low, float high) { double dinf = low; double dsup = high; // assert to avoid nearzero weights if (fabs(dinf) < weightnearzero) dinf = weightnearzero; if (fabs(dsup) < weightnearzero) dsup = -weightnearzero; double range = dsup - dinf; MatrixFloat::iterator w_it(weights->begin()); while(w_it != weights->end()) { rnd_weight(rnd, *w_it, dinf, range, weightnearzero); ++w_it; } } void Connections::randomizeWeightsAtColumn(MatrixFloat *weights, unsigned int col, MTRand *rnd, float low, float high) { double dinf = low; double dsup = high; // assert to avoid nearzero weights april_assert(fabs(dinf) > weightnearzero); april_assert(fabs(dsup) > weightnearzero); double range = dsup - dinf; MatrixFloat::iterator w_it(weights->iteratorAt(col,0)); MatrixFloat::iterator end(weights->iteratorAt(col+1,0)); while(w_it != end) { rnd_weight(rnd, *w_it, dinf, range, weightnearzero); ++w_it; } } unsigned int Connections::loadWeights(MatrixFloat *weights, MatrixFloat *data, unsigned int first_weight_pos, unsigned int column_size) { const unsigned int num_outputs = static_cast(weights->getDimSize(0)); const unsigned int num_inputs = static_cast(weights->getDimSize(1)); const unsigned int total_size = static_cast(weights->size()); unsigned int min_size = (total_size + max(0, (static_cast(column_size-num_inputs)-1))*num_outputs + first_weight_pos); if (min_size > static_cast(data->size())) ERROR_EXIT2(24, "Incorrect matrix size, was %d, expected >= %d\n", data->size(), min_size); if (!data->getIsContiguous()) { ERROR_EXIT(128, "Matrices need to be contiguous\n"); } unsigned int current_w_pos = first_weight_pos; MatrixFloat::iterator w_it(weights->begin()); for (unsigned int j=0; j(weights->getDimSize(0)); const unsigned int num_inputs = static_cast(weights->getDimSize(1)); const unsigned int total_size = static_cast(weights->size()); unsigned int min_size = (total_size + max(0, (static_cast(column_size-num_inputs)-1))*num_outputs + first_weight_pos); if (min_size > static_cast(data->size())) ERROR_EXIT2(24, "Incorrect matrix size, was %d, expected >= %d\n", data->size(), min_size); if (!data->getIsContiguous()) ERROR_EXIT(128, "Matrices need to contiguous\n"); unsigned int current_w_pos = first_weight_pos; MatrixFloat::const_iterator w_it(weights->begin()); for (unsigned int j=0; j #include "aligned_memory.h" #include "swap.h" #include "referenced.h" #include "MersenneTwister.h" #include "matrixFloat.h" #include "error_print.h" #include "maxmin.h" namespace ANN { /// The class Connections is an static class. It is a helper to build, /// initialize, and query matrix instances interpreted as connection weights. class Connections : public Referenced { public: static const double weightnearzero; static Basics::MatrixFloat *build(unsigned int num_inputs, unsigned int num_outputs); // static unsigned int getInputSize(const Basics::MatrixFloat *weights) { return static_cast(weights->getDimSize(1)); } static unsigned int getNumInputs(const Basics::MatrixFloat *weights) { return static_cast(weights->getDimSize(1)); } static unsigned int getOutputSize(const Basics::MatrixFloat *weights) { return static_cast(weights->getDimSize(0)); } static unsigned int getNumOutputs(const Basics::MatrixFloat *weights) { return static_cast(weights->getDimSize(0)); } static bool checkInputOutputSizes(const Basics::MatrixFloat *weights, unsigned int input_size, unsigned int output_size); static void randomizeWeights(Basics::MatrixFloat *weights, Basics::MTRand *rnd, float low, float high); static void randomizeWeightsAtColumn(Basics::MatrixFloat *weights, unsigned int col, Basics::MTRand *rnd, float low, float high); // Carga/guarda los pesos de la matriz data comenzando por la // posicion first_weight_pos. Devuelve la suma del numero de pesos // cargados/salvados y first_weight_pos. En caso de error, // abortara el programa con un ERROR_EXIT static unsigned int loadWeights(Basics::MatrixFloat *weights, Basics::MatrixFloat *data, unsigned int first_weight_pos, unsigned int column_size); static unsigned int copyWeightsTo(Basics::MatrixFloat *weights, Basics::MatrixFloat *data, unsigned int first_weight_pos, unsigned int column_size); }; } #endif april-ann-0.4.1/packages/ann/ann/c_src/const_component.cc000066400000000000000000000052401263004425400233140ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "const_component.h" using Basics::Token; namespace ANN { ConstANNComponent::ConstANNComponent(ANNComponent *component, const char *name) : ANNComponent(name, 0, component->getInputSize(), component->getOutputSize()), component(component) { if (!component->getIsBuilt()) { AprilUtils::LuaTable components_dict; component->build(0, 0, component_weights, components_dict); input_size = component->getInputSize(); output_size = component->getOutputSize(); } else { component->copyWeights(component_weights); } } ConstANNComponent::~ConstANNComponent() { } Token *ConstANNComponent::doForward(Token* _input, bool during_training) { return component->doForward(_input, during_training); } Token *ConstANNComponent::doBackprop(Token *_error_input) { return component->doBackprop(_error_input); } void ConstANNComponent::reset(unsigned int it) { component->reset(it); } ANNComponent *ConstANNComponent::clone(AprilUtils::LuaTable &copies) { ANNComponent *cloned = component->clone(copies); AprilUtils::LuaTable components; cloned->build(0, 0, component_weights, components); return new ConstANNComponent(cloned, name.c_str()); } void ConstANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); } const char *ConstANNComponent::luaCtorName() const { return "ann.components.const"; } int ConstANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name; t["component"] = component; t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/const_component.h000066400000000000000000000052511263004425400231600ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef CONSTCOMPONENT_H #define CONSTCOMPONENT_H #include "ann_component.h" #include "disallow_class_methods.h" #include "smart_ptr.h" namespace ANN { class ConstANNComponent : public ANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(ConstANNComponent); protected: AprilUtils::SharedPtr component; AprilUtils::LuaTable component_weights; public: ConstANNComponent(ANNComponent *component, const char *name); virtual ~ConstANNComponent(); virtual Basics::Token *getInput() { return component->getInput(); } virtual Basics::Token *getOutput() { return component->getOutput(); } virtual Basics::Token *getErrorInput() { return component->getErrorInput(); } virtual Basics::Token *getErrorOutput() { return component->getErrorOutput(); } virtual void setInput(Basics::Token *tk) { component->setInput(tk); } virtual void setOutput(Basics::Token *tk) { component->setOutput(tk); } virtual void setErrorInput(Basics::Token *tk) { component->setErrorInput(tk); } virtual void setErrorOutput(Basics::Token *tk) { component->setErrorOutput(tk); } virtual void copyState(AprilUtils::LuaTable &dict) { component->copyState(dict); } virtual void setState(AprilUtils::LuaTable &dict) { component->setState(dict); } virtual Basics::Token *doForward(Basics::Token* input, bool during_training); virtual Basics::Token *doBackprop(Basics::Token *input_error); virtual void reset(unsigned int it=0); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // CONSTCOMPONENT_H_H april-ann-0.4.1/packages/ann/ann/c_src/convolution_bias_component.cc000066400000000000000000000244211263004425400255450ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "convolution_bias_component.h" #include "token_matrix.h" #include "table_of_token_codes.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilUtils; using namespace Basics; namespace ANN { //////////////////////////////////////////////// // ConvolutionBiasANNComponent implementation // //////////////////////////////////////////////// void ConvolutionBiasANNComponent::initializeArrays(const int *input_dims) { // input_dims[0] => BUNCH SIZE, input_dims[1] => HIDDEN SIZE window_size[0] = input_dims[0]; for (int i=2; i<=num_dims; ++i) window_num_steps[i] = input_dims[i]; } // A method to convert the bias vector of size Nx1 in a matrix of size // BUNCHxK1xK2x...xKM being Ki the kernel size at dimension i MatrixFloat *ConvolutionBiasANNComponent::prepareBiasBunch() { /* FIXME: When the following improvement is set, the performance of the ANN degenerates... if (bias_matrix != 0 && bias_matrix->sameDim(window_size, num_dims + 1)) return bias_matrix; */ // this line converts the bias matrix of Nx1 in a vector of N elements MatrixFloat *bias_vec = bias_vector->select(1,0); IncRef(bias_vec); // the output bias as a 2d matrix of BUNCHxN MatrixFloat *bias_matrix_2d = new MatrixFloat(2, window_size); IncRef(bias_matrix_2d); // first pattern is done out of the loop MatrixFloat *dest = bias_matrix_2d->select(0, 0); IncRef(dest); matCopy(dest,bias_vec); // for the rest of patterns at the bunch for (int b=1; bselect(0, b, dest); matCopy(dest,bias_vec); } DecRef(dest); if (bias_matrix) DecRef(bias_matrix); // reinterpret the output bias matrix of BUNCHxN to fit with the output // sliding window of BUNCHxK1xK2x....xKM where Ki is the kernel size at // dimension i bias_matrix = bias_matrix_2d->rewrap(window_size, num_dims + 1); IncRef(bias_matrix); // free the memory of auxiliary matrices DecRef(bias_matrix_2d); DecRef(bias_vec); return bias_matrix; } ConvolutionBiasANNComponent:: ConvolutionBiasANNComponent(int num_dims, unsigned int num_output_planes, const char *name, const char *bias_name, MatrixFloat *matrix) : VirtualMatrixANNComponent(name, bias_name, 0, 0), bias_vector(matrix), bias_matrix(0), hidden_size(num_output_planes), num_dims(num_dims), window_size(new int[num_dims+1]), window_step(new int[num_dims+1]), window_num_steps(new int[num_dims+1]) { setInputContiguousProperty(true); if (bias_name == 0) generateDefaultWeightsName("b"); window_size[1] = static_cast(hidden_size); window_step[0] = 1; window_step[1] = 1; window_num_steps[0] = 1; window_num_steps[1] = 1; for (int i=2; i<=num_dims; ++i) { window_size[i] = 1; window_step[i] = 1; } if (bias_vector) IncRef(bias_vector); } ConvolutionBiasANNComponent::~ConvolutionBiasANNComponent() { if (bias_vector) DecRef(bias_vector); delete[] window_size; delete[] window_step; delete[] window_num_steps; if (bias_matrix) DecRef(bias_matrix); } MatrixFloat *ConvolutionBiasANNComponent:: privateDoForward(MatrixFloat *input_mat, bool during_training) { UNUSED_VARIABLE(during_training); if (bias_vector == 0) ERROR_EXIT1(129, "Not built component %s\n", name.c_str()); if (input_mat->getNumDim() != num_dims+1) ERROR_EXIT3(129, "Incorrect input matrix numDims, " "expected %d, found %d [%s]\n", num_dims+1, input_mat->getNumDim(), name.c_str()); const int *input_dims = input_mat->getDimPtr(); if (input_dims[1] != static_cast(hidden_size)) ERROR_EXIT3(129,"Incorrect input dim[1] size, found %d, expected %d [%s]\n", input_dims[1], hidden_size, name.c_str()); initializeArrays(input_dims); MatrixFloat *output_mat; output_mat = input_mat->clone(); IncRef(output_mat); MatrixFloat *bias_matrix = prepareBiasBunch(); IncRef(bias_matrix); ///////////////////////////////////////////////////////////////////////// // Prepare sliding windows to compute the convolution MatrixFloat::sliding_window *input_sw = new MatrixFloat::sliding_window(input_mat, window_size, 0, // OFFSET window_step, window_num_steps); MatrixFloat::sliding_window *output_sw = new MatrixFloat::sliding_window(output_mat, window_size, 0, // OFFSET window_step, window_num_steps); number_input_windows = input_sw->numWindows(); // CONVOLUTION OVER number_input_windows MatrixFloat *input_w = input_sw->getMatrix(); MatrixFloat *output_w = output_sw->getMatrix(); IncRef(input_w); IncRef(output_w); while(!input_sw->isEnd() && !output_sw->isEnd()) { input_sw->getMatrix(input_w); output_sw->getMatrix(output_w); // ADD BIAS matAxpy(output_w, 1.0f, bias_matrix); // Next iteration input_sw->next(); output_sw->next(); } // Free memory DecRef(input_w); DecRef(output_w); DecRef(bias_matrix); delete input_sw; delete output_sw; ReleaseRef(output_mat); return output_mat; } MatrixFloat *ConvolutionBiasANNComponent:: privateDoBackprop(MatrixFloat *error_mat) { return error_mat; } void ConvolutionBiasANNComponent::computeGradients(const char *name, AprilUtils::LuaTable &grads_mat_dict) { // reset shared counter bias_vector->addToSharedCount(number_input_windows); MatrixFloat *grads_mat = grads_mat_dict.opt(name, 0); if (grads_mat == 0) { grads_mat = bias_vector->cloneOnlyDims(); matZeros(grads_mat); grads_mat_dict.put(name, grads_mat); } #ifdef USE_CUDA grads_mat->setUseCuda(use_cuda); #endif MatrixFloat *input_error_mat = getErrorInputMatrix(); // Prepare sliding windows to compute the convolution MatrixFloat::sliding_window error_sw(input_error_mat, window_size, 0, // OFFSET window_step, window_num_steps); unsigned int bunch_size = input_error_mat->getDimSize(0); april_assert(error_sw.numWindows() == number_input_windows); MatrixFloat *error_w = error_sw.getMatrix(); IncRef(error_w); while(!error_sw.isEnd()) { error_sw.getMatrix(error_w); // BIAS UPDATE doAxpyLoop(hidden_size, 1.0f, error_w->getRawDataAccess(), error_w->getStrideSize(1), error_w->getOffset(), grads_mat->getRawDataAccess(), grads_mat->getStrideSize(0), 0, bunch_size, error_w->getStrideSize(0), 0, use_cuda); // Next iteration error_sw.next(); } // Free memory DecRef(error_w); } void ConvolutionBiasANNComponent::privateReset(unsigned int it) { UNUSED_VARIABLE(it); // reset shared counter bias_vector->resetSharedCount(); } ANNComponent *ConvolutionBiasANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); ConvolutionBiasANNComponent *component = new ConvolutionBiasANNComponent(num_dims, hidden_size, name.c_str(), weights_name.c_str()); component->input_size = input_size; component->output_size = output_size; return component; } void ConvolutionBiasANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); //////////////////////////////////////////////////////////////////// MatrixFloat *b = weights_dict.opt(weights_name, 0); if (b != 0) { AssignRef(bias_vector, b); if (!Connections::checkInputOutputSizes(bias_vector,1,hidden_size)) ERROR_EXIT2(256,"The bias vector input/output sizes are not correct, " "expected 1x%d [%s]\n", hidden_size, name.c_str()); } else { if (bias_vector == 0) { bias_vector = Connections::build(1, hidden_size); IncRef(bias_vector); } weights_dict.put(weights_name, bias_vector); } } void ConvolutionBiasANNComponent::copyWeights(AprilUtils::LuaTable &weights_dict) { if (bias_vector == 0) ERROR_EXIT1(100, "Component not built, impossible execute copyWeights [%s]\n", name.c_str()); MatrixFloat *b = weights_dict.opt(weights_name, 0); if (b != 0 && b != bias_vector) ERROR_EXIT2(101, "Weights dictionary contains %s bias name which is " "not shared with bias_vector attribute [%s]\n", weights_name.c_str(), name.c_str()); else if (b == 0) { weights_dict.put(weights_name, bias_vector); } } const char *ConvolutionBiasANNComponent::luaCtorName() const { return "ann.components.convolution_bias"; } int ConvolutionBiasANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name; t["weights"] = weights_name; t["n"] = hidden_size; t["ndims"] = num_dims; t["matrix"] = bias_vector; t.pushTable(L); return 1; } ////////////////////////////////////////////////////////////////////////// } april-ann-0.4.1/packages/ann/ann/c_src/convolution_bias_component.h000066400000000000000000000061461263004425400254130ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef CONVOLUTIONBIASANNCOMPONENT_H #define CONVOLUTIONBIASANNCOMPONENT_H #include "token_matrix.h" #include "cblas_headers.h" #include "matrix_component.h" #include "connection.h" namespace ANN { /// A component which adds a convolutional bias given the number of output /// planes. Exists one bias per each output plane. class ConvolutionBiasANNComponent : public VirtualMatrixANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(ConvolutionBiasANNComponent); Basics::MatrixFloat *bias_vector; Basics::MatrixFloat *bias_matrix; // rewrapping of bias_vector matrix to // fits at input window sizes /// The number of convolutions computed during last forward int number_input_windows; // parameters of the convolution bias unsigned int hidden_size; // number of planes int num_dims; int *window_size; int *window_step; int *window_num_steps; void initializeArrays(const int *input_dims); Basics::MatrixFloat *prepareBiasBunch(); protected: virtual void computeGradients(const char *name, AprilUtils::LuaTable &weight_grads_dict); virtual Basics::MatrixFloat *privateDoForward(Basics::MatrixFloat *input, bool during_training); virtual Basics::MatrixFloat *privateDoBackprop(Basics::MatrixFloat *input_error); virtual void privateReset(unsigned int it=0); public: ConvolutionBiasANNComponent(int input_num_dims, unsigned int num_output_planes, // hidden layer size const char *name=0, const char *bias_name=0, Basics::MatrixFloat *matrix=0); virtual ~ConvolutionBiasANNComponent(); virtual void precomputeOutputSize(const AprilUtils::vector &input_size, AprilUtils::vector &output_size) { output_size = input_size; } virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void build(unsigned int input_size, unsigned int output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual void copyWeights(AprilUtils::LuaTable &weights_dict); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // CONVOLUTIONANNCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/convolution_component.cc000066400000000000000000000410471263004425400245520ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "convolution_component.h" #include "token_matrix.h" #include "table_of_token_codes.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilUtils; using namespace Basics; namespace ANN { //////////////////////////////////////////// // ConvolutionANNComponent implementation // //////////////////////////////////////////// void ConvolutionANNComponent::initializeArrays(const int *input_dims) { for (int i=2; i<=input_num_dims; ++i) { output_dims[i] = (input_dims[i] - kernel_dims[i])/kernel_step[i] + 1; input_window_num_steps[i] = output_dims[i]; output_window_num_steps[i] = output_dims[i]; } /* for (int i=1; i<=input_num_dims; ++i) { output_dims[i] = (input_dims[i] - kernel_dims[i])/kernel_step[i] + 1; input_window_num_steps[i] = output_dims[i]; output_window_num_steps[i] = output_dims[i]; } */ // input_dims[0] => BUNCH SIZE // output_dims[0] => BUNCH SIZE, output_dims[1] => HIDDEN LAYER SIZE output_dims[0] = input_dims[0]; output_dims[1] = hidden_size; input_window_size[0] = input_dims[0]; input_window_num_steps[0] = 1; input_window_num_steps[1] = 1; output_window_size[0] = input_dims[0]; // AT CONSTRUCTOR: output_window_size[1] = hidden_size; output_window_num_steps[0] = 1; output_window_num_steps[1] = 1; input_window_rewrap[0] = input_dims[0]; // AT CONSTRUCTOR: input_window_rewrap[1] = kernel_size; output_window_rewrap[0] = input_dims[0]; // AT CONSTRUCTOR: output_window_rewrap[1] = hidden_size; if (input_dims[1] != kernel_dims[1]) ERROR_EXIT3(128, "Input matrix dim 1 must be equals to kernel dim 1, " "input_dims[1]=%d != kernel_dims[1]=%d [%s]\n", input_dims[1], kernel_dims[1], name.c_str()); } ConvolutionANNComponent::ConvolutionANNComponent(int input_num_dims, const int *_kernel_dims, const int *_kernel_step, int num_output_planes, const char *name, const char *weights_name, MatrixFloat *matrix) : VirtualMatrixANNComponent(name, weights_name, 0, 0), weights_matrix(matrix), number_input_windows(0), kernel_size(1), hidden_size(num_output_planes), input_num_dims(input_num_dims), kernel_dims(new int[input_num_dims+1]), kernel_step(new int[input_num_dims+1]), output_dims(new int[input_num_dims+1]), input_window_size(new int[input_num_dims+1]), input_window_num_steps(new int[input_num_dims+1]), input_window_rewrap(new int[2]), output_window_size(new int[input_num_dims+1]), output_window_step(new int[input_num_dims+1]), output_window_num_steps(new int[input_num_dims+1]), output_window_rewrap(new int[2]) { setInputContiguousProperty(true); if (weights_name == 0) generateDefaultWeightsName("w"); kernel_dims[0] = static_cast(hidden_size); kernel_step[0] = 1; output_window_size[0] = 0; output_window_size[1] = static_cast(hidden_size); output_window_step[0] = 1; output_window_step[1] = 1; for(int i=0; i(kernel_size); output_window_rewrap[0] = 0; output_window_rewrap[1] = static_cast(hidden_size); if (weights_matrix) IncRef(weights_matrix); } ConvolutionANNComponent::~ConvolutionANNComponent() { if (weights_matrix) DecRef(weights_matrix); delete[] kernel_dims; delete[] kernel_step; delete[] output_dims; delete[] input_window_size; delete[] input_window_num_steps; delete[] output_window_size; delete[] output_window_step; delete[] output_window_num_steps; delete[] input_window_rewrap; delete[] output_window_rewrap; } MatrixFloat *ConvolutionANNComponent:: privateDoForward(MatrixFloat *input_mat, bool during_training) { UNUSED_VARIABLE(during_training); if (weights_matrix == 0) ERROR_EXIT1(129, "Not built component %s\n", name.c_str()); MatrixFloat *weights_mat = weights_matrix; // error checking if (input_mat->getNumDim() != input_num_dims+1) ERROR_EXIT3(129, "Incorrect input matrix numDims, " "expected %d, found %d [%s]\n", input_num_dims+1, input_mat->getNumDim(), name.c_str()); const int *input_dims = input_mat->getDimPtr(); initializeArrays(input_dims); MatrixFloat *output_mat; output_mat = new MatrixFloat(input_num_dims+1, output_dims); IncRef(output_mat); #ifdef USE_CUDA output_mat->setUseCuda(use_cuda); #endif ///////////////////////////////////////////////////////////////////////// // Prepare sliding windows to compute the convolution MatrixFloat::sliding_window *input_sw = new MatrixFloat::sliding_window(input_mat, input_window_size, 0, // OFFSET kernel_step, input_window_num_steps); MatrixFloat::sliding_window *output_sw = new MatrixFloat::sliding_window(output_mat, output_window_size, 0, // OFFSET output_window_step, output_window_num_steps); number_input_windows = input_sw->numWindows(); // CONVOLUTION OVER number_input_windows MatrixFloat *input_w = input_sw->getMatrix(); MatrixFloat *output_w = output_sw->getMatrix(); IncRef(input_w); IncRef(output_w); while(!input_sw->isEnd() && !output_sw->isEnd()) { // reusing the same MatrixFloat across all the possible windows input_sw->getMatrix(input_w); output_sw->getMatrix(output_w); MatrixFloat *input_flattened = getRewrappedMatrix(input_w, input_window_rewrap, 2, true); MatrixFloat *output_flattened = getRewrappedMatrix(output_w, output_window_rewrap, 2, false); IncRef(input_flattened); IncRef(output_flattened); // COMPUTE MATRIX MULTIPLICATION matGemm(output_flattened, CblasNoTrans, CblasTrans, 1.0f, input_flattened, weights_mat, 0.0f); // COPY TO DESTINATION IF NEEDED if (output_w->getRawDataAccess()!=output_flattened->getRawDataAccess()) { // if output_w and output_flattened are pointing to different data // then the copy is needed, otherwise it isn't MatrixFloat *conv_output_rewrapped; conv_output_rewrapped = output_flattened->rewrap(output_w->getDimPtr(), output_w->getNumDim()); IncRef(conv_output_rewrapped); matCopy(output_w, conv_output_rewrapped); DecRef(conv_output_rewrapped); } // Next iteration input_sw->next(); output_sw->next(); // Free memory DecRef(input_flattened); DecRef(output_flattened); } DecRef(input_w); DecRef(output_w); delete input_sw; delete output_sw; ReleaseRef(output_mat); return output_mat; } MatrixFloat *ConvolutionANNComponent:: privateDoBackprop(MatrixFloat *error_input_mat) { MatrixFloat *weights_mat = weights_matrix; MatrixFloat *output_mat = getOutputMatrix(); MatrixFloat *input_mat = getInputMatrix(); if (!output_mat->sameDim(error_input_mat)) ERROR_EXIT1(129, "Incorrect dimensions at error input matrix [%s]\n", name.c_str()); MatrixFloat *error_output_mat = input_mat->cloneOnlyDims(); IncRef(error_output_mat); // initialization of error_output_mat is needed because of kernel // overlapping matZeros(error_output_mat); // Prepare sliding windows to compute the convolution gradient MatrixFloat::sliding_window *error_output_sw = new MatrixFloat::sliding_window(error_output_mat, input_window_size, 0, // OFFSET kernel_step, input_window_num_steps); MatrixFloat::sliding_window *error_input_sw = new MatrixFloat::sliding_window(error_input_mat, output_window_size, 0, // OFFSET output_window_step, output_window_num_steps); april_assert(error_input_sw->numWindows() == number_input_windows); // CONVOLUTION GRADIENT MatrixFloat *error_input_w = error_input_sw->getMatrix(); MatrixFloat *error_output_w = error_output_sw->getMatrix(); IncRef(error_input_w); IncRef(error_output_w); while(!error_input_sw->isEnd() && !error_output_sw->isEnd()) { // reuse the same MatrixFloat across all possible windows error_input_sw->getMatrix(error_input_w); error_output_sw->getMatrix(error_output_w); MatrixFloat *error_input_flattened = getRewrappedMatrix(error_input_w, output_window_rewrap, 2, true); MatrixFloat *error_output_flattened = getRewrappedMatrix(error_output_w, input_window_rewrap, 2, true); IncRef(error_input_flattened); IncRef(error_output_flattened); // COMPUTE MATRIX MULTIPLICATION matGemm(error_output_flattened, CblasNoTrans, CblasNoTrans, 1.0f, error_input_flattened, weights_mat, 1.0f); // accumulative operation // COPY TO DESTINATION IF NEEDED if (error_output_w->getRawDataAccess()!=error_output_flattened->getRawDataAccess()) { // if error_output_w and error_output_flattened are pointing to // different data then the copy is needed, otherwise it isn't MatrixFloat *conv_error_output_rewrapped; conv_error_output_rewrapped = error_output_flattened->rewrap(error_output_w->getDimPtr(), error_output_w->getNumDim()); IncRef(conv_error_output_rewrapped); // COPY THE RESULT matCopy(error_output_w, conv_error_output_rewrapped); DecRef(conv_error_output_rewrapped); } // Next iteration error_input_sw->next(); error_output_sw->next(); // Free memory DecRef(error_input_flattened); DecRef(error_output_flattened); } DecRef(error_input_w); DecRef(error_output_w); delete error_input_sw; delete error_output_sw; ReleaseRef(error_output_mat); return error_output_mat; } void ConvolutionANNComponent::computeGradients(const char *name, AprilUtils::LuaTable &grads_mat_dict) { weights_matrix->addToSharedCount(number_input_windows); MatrixFloat *grads_mat = grads_mat_dict.opt(name, 0); if (grads_mat == 0) { grads_mat = weights_matrix->cloneOnlyDims(); matZeros(grads_mat); grads_mat_dict.put(name, grads_mat); } #ifdef USE_CUDA grads_mat->setUseCuda(use_cuda); #endif MatrixFloat *input_mat = getInputMatrix(); MatrixFloat *error_input_mat = getErrorInputMatrix(); // Prepare sliding windows to compute the convolution MatrixFloat::sliding_window input_sw(input_mat, input_window_size, 0, // OFFSET kernel_step, input_window_num_steps); MatrixFloat::sliding_window error_input_sw(error_input_mat, output_window_size, 0, // OFFSET output_window_step, output_window_num_steps); MatrixFloat *input_w = input_sw.getMatrix(); MatrixFloat *error_input_w = error_input_sw.getMatrix(); IncRef(input_w); IncRef(error_input_w); while(!input_sw.isEnd() && !error_input_sw.isEnd()) { input_sw.getMatrix(input_w); error_input_sw.getMatrix(error_input_w); MatrixFloat *input_flattened = getRewrappedMatrix(input_w, input_window_rewrap, 2, true); MatrixFloat *error_input_flattened = getRewrappedMatrix(error_input_w, output_window_rewrap, 2, true); IncRef(input_flattened); IncRef(error_input_flattened); // WEIGHTS UPDATE matGemm(grads_mat, CblasTrans, CblasNoTrans, 1.0f, error_input_flattened, // A input_flattened, // B 1.0f); // Next iteration input_sw.next(); error_input_sw.next(); // Free memory DecRef(input_flattened); DecRef(error_input_flattened); } DecRef(input_w); DecRef(error_input_w); } void ConvolutionANNComponent::privateReset(unsigned int it) { UNUSED_VARIABLE(it); weights_matrix->resetSharedCount(); } ANNComponent *ConvolutionANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); ConvolutionANNComponent *component = new ConvolutionANNComponent(input_num_dims, kernel_dims+1, kernel_step+1, hidden_size, name.c_str(), weights_name.c_str()); component->input_size = input_size; component->output_size = output_size; return component; } void ConvolutionANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); // unsigned int weights_input_size = kernel_size; unsigned int weights_output_size = hidden_size; //////////////////////////////////////////////////////////////////// MatrixFloat *w = weights_dict.opt(weights_name.c_str(), 0); // printf("%s :: %p %p\n", weights_name.c_str(), w, weights_matrix); if (w != 0) { // printf("COPY OF WEIGHTS FROM HASH %s\n", weights_name.c_str()); AssignRef(weights_matrix, w); if (!Connections::checkInputOutputSizes(weights_matrix, weights_input_size, weights_output_size)) ERROR_EXIT3(256,"The weights matrix input/output sizes are not correct, " "expected %dx%d [%s]\n", weights_input_size, weights_output_size, name.c_str()); } else { if (weights_matrix == 0) { // printf("NEW OF WEIGHTS %s\n", weights_name.c_str()); weights_matrix = Connections::build(weights_input_size, weights_output_size); IncRef(weights_matrix); } // else printf("USING PREVIOUS WEIGHTS %s\n", weights_name.c_str()); weights_dict.put(weights_name.c_str(), weights_matrix); } } void ConvolutionANNComponent::copyWeights(AprilUtils::LuaTable &weights_dict) { if (weights_matrix == 0) ERROR_EXIT1(100, "Component not built, impossible execute copyWeights [%s]\n", name.c_str()); MatrixFloat *w = weights_dict.opt(weights_name.c_str(), 0); if (w != 0 && w != weights_matrix) ERROR_EXIT2(101, "Weights dictionary contains %s weights name which is " "not shared with weights_matrix attribute [%s]\n", weights_name.c_str(), name.c_str()); else if (w == 0) { weights_dict.put(weights_name.c_str(), weights_matrix); } } const char *ConvolutionANNComponent::luaCtorName() const { return "ann.components.convolution"; } int ConvolutionANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L), kernel(L), step(L); t["name"] = name; t["matrix"] = weights_matrix; t["weights"] = weights_name; t["n"] = hidden_size; t["kernel"] = kernel; t["step"] = step; for (int i=1; i<=input_num_dims; ++i) { kernel[i] = kernel_dims[i]; step[i] = kernel_step[i]; } t.pushTable(L); return 1; } ////////////////////////////////////////////////////////////////////////// } april-ann-0.4.1/packages/ann/ann/c_src/convolution_component.h000066400000000000000000000120471263004425400244120ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef CONVOLUTIONANNCOMPONENT_H #define CONVOLUTIONANNCOMPONENT_H #include "token_matrix.h" #include "cblas_headers.h" #include "matrix_component.h" #include "connection.h" namespace ANN { /// A component which computes a convolutional layer using given kernel size /// and step, and the given number of output planes. class ConvolutionANNComponent : public VirtualMatrixANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(ConvolutionANNComponent); Basics::MatrixFloat *weights_matrix; // parameters of the convolution /// The number of convolutions computed during last forward int number_input_windows; /// The size of one kernel (number of inputs of one hidden neuron) unsigned int kernel_size; /// The number of neurons (number of output planes) const unsigned int hidden_size; /// The number of expected input dimensions without count BUNCH dim (first) const int input_num_dims; /// Size at each dim of the kernel, input_num_dims + 1 int *kernel_dims; /// Step at each dim of the input, input_num_dims + 1 int *kernel_step; /// Size at each dim of the output, input_num_dims + 1 int *output_dims; // first is BUNCH, second is number of output planes) // INPUT SLIDING WINDOW SECTION /// Size of the convolution window, input_num_dims + 1 int *input_window_size; /// Number of steps of the convolution window, input_num_dims + 1 int *input_window_num_steps; /// Translates the input window into a bi-dimensional matrix int *input_window_rewrap; // OUTPUT SLIDING WINDOW SECTION /// Size of the convolution window, input_num_dims + 1 int *output_window_size; /// Step between convolution windows, input_num_dims + 1 int *output_window_step; /// Number of steps of the convolution window, input_num_dims + 1 int *output_window_num_steps; /// Translates the output window into a bi-dimensional matrix int *output_window_rewrap; Basics::MatrixFloat *getRewrappedMatrix(Basics::MatrixFloat *w, const int *rewrap_size, const int N, bool copy) const { Basics::MatrixFloat *w_flattened; if (w->getIsContiguous()) w_flattened = w->rewrap(rewrap_size, N); else { Basics::MatrixFloat *w_clone; if (copy) w_clone = w->clone(); else w_clone = w->cloneOnlyDims(); IncRef(w_clone); w_flattened = w_clone->rewrap(rewrap_size, N); DecRef(w_clone); } return w_flattened; } void initializeArrays(const int *input_dims); protected: virtual void computeGradients(const char *name, AprilUtils::LuaTable &weight_grads_dict); virtual Basics::MatrixFloat *privateDoForward(Basics::MatrixFloat* input, bool during_training); virtual Basics::MatrixFloat *privateDoBackprop(Basics::MatrixFloat *input_error); virtual void privateReset(unsigned int it=0); public: ConvolutionANNComponent(int input_num_dims, const int *_kernel_dims, // input_num_dims const int *_kernel_step, // step int num_output_planes, // hidden layer size const char *name=0, const char *weights_name=0, Basics::MatrixFloat *matrix=0); virtual ~ConvolutionANNComponent(); virtual void precomputeOutputSize(const AprilUtils::vector &input_size, AprilUtils::vector &output_size) { output_size.clear(); output_size.push_back(hidden_size); for (int i=2; i<=input_num_dims; ++i) { output_size.push_back((input_size[i-1]-kernel_dims[i])/kernel_step[i]+1); } } virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void build(unsigned int input_size, unsigned int output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual void copyWeights(AprilUtils::LuaTable &weights_dict); const int *getKernelShape(int &n) const { n = input_num_dims; return kernel_dims + 1; } virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // CONVOLUTIONANNCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/copy_component.cc000066400000000000000000000164371263004425400231520ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "error_print.h" #include "table_of_token_codes.h" #include "token_vector.h" #include "token_matrix.h" #include "copy_component.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilUtils; using namespace Basics; namespace ANN { CopyANNComponent::CopyANNComponent(unsigned int times, const char *name, unsigned int input_size, unsigned int output_size) : ANNComponent(name, 0, input_size, output_size), input(0), error_output(0), output(0), error_input(0), times(times) { if (times < 2) ERROR_EXIT1(128, "CopyANNComponent for less than 2 copies is forbidden [%s]\n", this->name.c_str()); } CopyANNComponent::~CopyANNComponent() { if (input) DecRef(input); if (error_input) DecRef(error_input); if (output) DecRef(output); if (error_output) DecRef(error_output); } Token *CopyANNComponent::doForward(Token* _input, bool during_training) { UNUSED_VARIABLE(during_training); AssignRef(input, _input); switch(input->getTokenCode()) { case table_of_token_codes::token_matrix: { AssignRef(output, new TokenBunchVector(times)); for (unsigned int i=0; iconvertTo(); AssignRef(output, new TokenBunchVector(input_bunch->size())); for (unsigned int i=0; isize(); ++i) { TokenBunchVector *current = new TokenBunchVector(times); (*output)[i] = current; for (unsigned int j=0; jgetTokenCode(), name.c_str()); } return output; } Token *CopyANNComponent::doBackprop(Token *_error_input) { if (_error_input == 0) { if (error_input) { DecRef(error_input); error_input = 0; } if (error_output) { DecRef(error_output); error_output = 0; } return 0; } if (_error_input->getTokenCode() != table_of_token_codes::vector_Tokens) ERROR_EXIT1(128, "Incorrect error input token type, " "expected TokenBunchVector [%s]\n", name.c_str()); AssignRef(error_input, _error_input->convertTo()); if (error_input->size() != times) ERROR_EXIT3(128, "Incorrect error input size, found %d, expected %d [%s]\n", error_input->size(), times, name.c_str()); // the first is only copied AprilUtils::SharedPtr current = (*error_input)[0]; if (current->getTokenCode() != table_of_token_codes::token_matrix) ERROR_EXIT1(128, "Incorrect token type, expected token matrix [%s]\n", name.c_str()); TokenMatrixFloat *current_token; current_token = current->convertTo(); MatrixFloat *current_mat = current_token->getMatrix(); #ifdef USE_CUDA current_mat->setUseCuda(use_cuda); #endif ASSERT_MATRIX(current_mat); unsigned int bunch_size = current_mat->getDimSize(0); // output token MatrixFloat *error_output_mat; switch(input->getTokenCode()) { case table_of_token_codes::token_matrix: { TokenMatrixFloat *aux = input->convertTo(); april_assert(aux != 0); MatrixFloat *input_mat = aux->getMatrix(); if (input_mat->getDimSize(0) != static_cast(bunch_size)) { ERROR_EXIT(128, "Different bunch size between forward and backprop\n"); } error_output_mat = new MatrixFloat(input_mat->getNumDim(), input_mat->getDimPtr()); break; } case table_of_token_codes::vector_Tokens: { int dims[2] = { static_cast(bunch_size), static_cast(input_size) }; error_output_mat = new MatrixFloat(2, dims); break; } default: error_output_mat = 0; ERROR_EXIT2(128, "Incorrect input token type %d [%s]\n", input->getTokenCode(), name.c_str()); } #ifdef USE_CUDA error_output_mat->setUseCuda(use_cuda); #endif TokenMatrixFloat *error_output_token = new TokenMatrixFloat(error_output_mat); AssignRef(error_output, error_output_token); matCopy(error_output_mat, current_mat); // The rest of tokens for (unsigned int i=1; i current = (*error_input)[i]; if (current->getTokenCode() != table_of_token_codes::token_matrix) ERROR_EXIT1(128, "Incorrect token type, expected token matrix [%s]\n", name.c_str()); current_token = current->convertTo(); current_mat = current_token->getMatrix(); #ifdef USE_CUDA current_mat->setUseCuda(use_cuda); #endif ASSERT_MATRIX(current_mat); matAxpy(error_output_mat, 1.0f, current_mat); } return error_output; } void CopyANNComponent::reset(unsigned int it) { UNUSED_VARIABLE(it); if (input) DecRef(input); if (error_input) DecRef(error_input); if (output) DecRef(output); if (error_output) DecRef(error_output); input = 0; error_input = 0; output = 0; error_output = 0; } ANNComponent *CopyANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); CopyANNComponent *copy_component = new CopyANNComponent(times, name.c_str(), input_size, output_size); return copy_component; } void CopyANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); if (output_size == 0) output_size = input_size * times; if (input_size == 0) input_size = output_size / times; if (input_size * times != output_size) ERROR_EXIT3(128, "Incorrect input/output sizes: input=%d output=%d [%s]\n", input_size, output_size, name.c_str()); } const char *CopyANNComponent::luaCtorName() const { return "ann.components.copy"; } int CopyANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name; t["times"] = times; t["input"] = input_size; t["output"] = output_size; t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/copy_component.h000066400000000000000000000055301263004425400230040ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef COPYCOMPONENT_H #define COPYCOMPONENT_H #include "vector.h" #include "ann_component.h" #include "token_vector.h" namespace ANN { /// This component replicates its input a given number of times. class CopyANNComponent : public ANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(CopyANNComponent); AprilUtils::vector components; // Token pointers which contains exactly the same that was received Basics::Token *input, *error_output; // These token are always a TokenBunchVector Basics::TokenBunchVector *output, *error_input; unsigned int times; public: CopyANNComponent(unsigned int times, const char *name=0, unsigned int input_size=0, unsigned int output_size=0); virtual ~CopyANNComponent(); virtual Basics::Token *getInput() { return input; } virtual Basics::Token *getOutput() { return output; } virtual Basics::Token *getErrorInput() { return error_input; } virtual Basics::Token *getErrorOutput() { return error_output; } virtual void setInput(Basics::Token *tk) { AssignRef(input, tk->convertTo()); } virtual void setOutput(Basics::Token *tk) { AssignRef(output, tk->convertTo()); } virtual void setErrorInput(Basics::Token *tk) { AssignRef(error_input, tk->convertTo()); } virtual void setErrorOutput(Basics::Token *tk) { AssignRef(error_output, tk->convertTo()); } virtual Basics::Token *doForward(Basics::Token* input, bool during_training); virtual Basics::Token *doBackprop(Basics::Token *input_error); virtual void reset(unsigned int it=0); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // COPYCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/dot_product_component.cc000066400000000000000000000274211263004425400245210ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "dot_product_component.h" #include "matrixFloat.h" #include "sparse_matrixFloat.h" #include "swap.h" #include "token_base.h" #include "token_matrix.h" #include "table_of_token_codes.h" #include "token_sparse_matrix.h" #include "unused_variable.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilUtils; using namespace Basics; namespace ANN { /////////////////////////////////////////// // DotProductANNComponent implementation // /////////////////////////////////////////// DotProductANNComponent::DotProductANNComponent(const char *name, const char *weights_name, unsigned int input_size, unsigned int output_size, bool transpose_weights, MatrixFloat *matrix) : MatrixInputSwitchANNComponent(name, weights_name, input_size, output_size), weights_matrix(matrix) { setInputContiguousProperty(true); if (weights_name == 0) generateDefaultWeightsName("w"); this->transpose_weights = (transpose_weights) ? CblasTrans : CblasNoTrans; if (weights_matrix) IncRef(weights_matrix); } DotProductANNComponent::~DotProductANNComponent() { if (weights_matrix) DecRef(weights_matrix); } MatrixFloat *DotProductANNComponent:: privateDoDenseForward(MatrixFloat *input_mat, bool during_training) { UNUSED_VARIABLE(during_training); if (input_mat->getNumDim() < 2) ERROR_EXIT2(128, "At 2-dimensional matrix is expected, found %d. " "[%s]", input_mat->getNumDim(), name.c_str()); if (weights_matrix == 0) ERROR_EXIT1(129, "Not built component %s\n", getName().c_str()); MatrixFloat *weights_mat = weights_matrix; unsigned int bunch_size = input_mat->getDimSize(0); // new output to fit the bunch MatrixFloat *output_mat; int dims[2] = { static_cast(bunch_size), static_cast(getOutputSize()) }; output_mat = new MatrixFloat(2, dims); #ifdef USE_CUDA output_mat->setUseCuda(use_cuda); #endif if (bunch_size == 1) { // vector x matrix product matGemv(output_mat, transpose_weights, 1.0f, weights_mat, input_mat, 0.0f); } // if bunch_size==1 else { // matrix x matrix product // C = \alpha op(A) op(B) + \beta C // input * weights = output matGemm(output_mat, CblasNoTrans, NEGATE_CBLAS_TRANSPOSE(transpose_weights), 1.0f, input_mat, weights_mat, 0.0f); } // if bunch_size==1 ... else return output_mat; } MatrixFloat *DotProductANNComponent:: privateDoSparseForward(SparseMatrixFloat *input_mat, bool during_training) { UNUSED_VARIABLE(during_training); unsigned int bunch_size = input_mat->getDimSize(0); MatrixFloat *weights_mat = weights_matrix; // new output to fit the bunch MatrixFloat *output_mat; int dims[2] = {static_cast(bunch_size), static_cast(getOutputSize())}; output_mat = new MatrixFloat(2, dims); #ifdef USE_CUDA output_mat->setUseCuda(use_cuda); #endif matSparseMM(output_mat, CblasNoTrans, NEGATE_CBLAS_TRANSPOSE(transpose_weights), 1.0f, input_mat, weights_mat, 0.0f); return output_mat; } MatrixFloat *DotProductANNComponent:: privateDoDenseBackprop(MatrixFloat *error_input_mat) { // new error output to fit the bunch unsigned int bunch_size = error_input_mat->getDimSize(0); // new output to fit the bunch MatrixFloat *error_output_mat; int dims[2] = { static_cast(bunch_size), static_cast(getInputSize()) }; error_output_mat = new MatrixFloat(2, dims); #ifdef USE_CUDA error_output_mat->setUseCuda(use_cuda); #endif // MatrixFloat *weights_mat = weights_matrix; if (bunch_size > 1) { // C = alpha * A * B + beta * C matGemm(error_output_mat, CblasNoTrans, transpose_weights, 1.0f, error_input_mat, weights_mat, 0.0f); } else { matGemv(error_output_mat, NEGATE_CBLAS_TRANSPOSE(transpose_weights), 1.0f, weights_mat, error_input_mat, 0.0f); } return error_output_mat; } SparseMatrixFloat *DotProductANNComponent:: privateDoSparseBackprop(MatrixFloat *error_input_mat) { UNUSED_VARIABLE(error_input_mat); // If input is sparse, the component needs to be an input of the ANN, // therefore the input is probably SO LARGE, and computing the backprop // will lead in HIGH computational cost ;) Because of this, the components // returns a NULL gradient pointer return 0; } void DotProductANNComponent::privateDenseReset(unsigned int it) { UNUSED_VARIABLE(it); weights_matrix->resetSharedCount(); } void DotProductANNComponent::privateSparseReset(unsigned int it) { UNUSED_VARIABLE(it); weights_matrix->resetSharedCount(); } MatrixFloat *DotProductANNComponent:: initializeComputeGradients(const char *name, AprilUtils::LuaTable &grads_mat_dict) { weights_matrix->addToSharedCount(); MatrixFloat *grads_mat = grads_mat_dict.opt(name, 0); if (grads_mat == 0) { grads_mat = weights_matrix->cloneOnlyDims(); matZeros(grads_mat); grads_mat_dict.put(name, grads_mat); } else if (!grads_mat->sameDim(weights_matrix)) { ERROR_EXIT(128, "Incorrect weights matrix dimensions\n"); } #ifdef USE_CUDA grads_mat->setUseCuda(use_cuda); #endif return grads_mat; } void DotProductANNComponent:: privateDenseComputeGradients(const char *name, AprilUtils::LuaTable & grads_mat_dict) { MatrixFloat *grads_mat = initializeComputeGradients(name, grads_mat_dict); MatrixFloat *error_input_mat; error_input_mat = getErrorInputMatrix(); unsigned int bunch_size = error_input_mat->getDimSize(0); MatrixFloat *input_mat = getInputMatrix(); if (bunch_size > 1) { matGemm(grads_mat, CblasTrans, CblasNoTrans, 1.0f, (transpose_weights == CblasNoTrans)?error_input_mat:input_mat, // A (transpose_weights == CblasNoTrans)?input_mat:error_input_mat, // B 1.0f); } // if bunch_size > 1 ... else else { matGer(grads_mat, 1.0f, (transpose_weights == CblasNoTrans)?error_input_mat:input_mat, (transpose_weights == CblasNoTrans)?input_mat:error_input_mat); } // if bunch_size > 1 ... else } void DotProductANNComponent:: privateSparseComputeGradients(const char *name, AprilUtils::LuaTable & grads_mat_dict) { MatrixFloat *grads_mat = initializeComputeGradients(name, grads_mat_dict); MatrixFloat *error_input_mat; error_input_mat = getErrorInputMatrix(); SparseMatrixFloat *input_mat; input_mat = getSparseInputMatrix(); if (transpose_weights == CblasNoTrans) { AprilUtils::SharedPtr< MatrixFloat > gT(grads_mat->transpose()); matSparseMM(gT.get(), CblasTrans, CblasNoTrans, 1.0f, input_mat, error_input_mat, 1.0f); } else { matSparseMM(grads_mat, CblasTrans, CblasNoTrans, 1.0f, input_mat, error_input_mat, 1.0f); } } ANNComponent *DotProductANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); DotProductANNComponent *component = new DotProductANNComponent(getName().c_str(), getWeightsName().c_str(), getInputSize(), getOutputSize(), (transpose_weights == CblasTrans)); return component; } void DotProductANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { MatrixInputSwitchANNComponent::build(_input_size, _output_size, weights_dict, components_dict); // if (getInputSize() == 0 || getOutputSize() == 0) ERROR_EXIT1(141, "Impossible to compute input/output " "sizes for this component [%s]\n", getName().c_str()); unsigned int weights_input_size = getInputSize(); unsigned int weights_output_size = getOutputSize(); //////////////////////////////////////////////////////////////////// if (transpose_weights == CblasTrans) { swap(weights_input_size, weights_output_size); } MatrixFloat *w = weights_dict.opt(getWeightsName(), 0); // printf("%s :: %p %p\n", weights_name.c_str(), w, weights_matrix); if (w != 0) { // printf("COPY OF WEIGHTS FROM HASH %s\n", weights_name.c_str()); AssignRef(weights_matrix, w); if (!Connections::checkInputOutputSizes(weights_matrix, weights_input_size, weights_output_size)) ERROR_EXIT5(256,"The weights matrix input/output sizes are not correct, " "expected %d and %d, found %d and %d [%s]\n", weights_input_size, weights_output_size, Connections::getInputSize(weights_matrix), Connections::getOutputSize(weights_matrix), getName().c_str()); } else { if (weights_matrix == 0) { // printf("NEW OF WEIGHTS %s\n", weights_name.c_str()); weights_matrix = Connections::build(weights_input_size, weights_output_size); IncRef(weights_matrix); } // else printf("USING PREVIOUS WEIGHTS %s\n", weights_name.c_str()); weights_dict.put(getWeightsName(), weights_matrix); } } void DotProductANNComponent::copyWeights(AprilUtils::LuaTable &weights_dict) { if (weights_matrix == 0) { ERROR_EXIT1(100, "Component not built, impossible execute copyWeights [%s]\n", getName().c_str()); } MatrixFloat *w = weights_dict.opt(getWeightsName(), 0); if (w != 0 && w != weights_matrix) ERROR_EXIT2(101, "Weights dictionary contains %s weights name which is " "not shared with weights_matrix attribute [%s]\n", getWeightsName().c_str(), getName().c_str()); else if (w == 0) { weights_dict.put(getWeightsName(), weights_matrix); } } const char *DotProductANNComponent::luaCtorName() const { return "ann.components.dot_product"; } int DotProductANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = getName(); t["weights"] = getWeightsName(); t["input"] = getInputSize(); t["output"] = getOutputSize(); t["transpose"] = transposed(); t["matrix"] = weights_matrix; t.pushTable(L); return 1; } ////////////////////////////////////////////////////////////////////////// } april-ann-0.4.1/packages/ann/ann/c_src/dot_product_component.h000066400000000000000000000066521263004425400243660ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef DOTPRODUCTANNCOMPONENT_H #define DOTPRODUCTANNCOMPONENT_H #include "token_matrix.h" #include "cblas_headers.h" #include "matrix_input_switch_component.h" #include "connection.h" namespace ANN { /// This components computes, for every I output neuron, the dot product /// between input neurons and the weights of the neuron I. class DotProductANNComponent : public MatrixInputSwitchANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(DotProductANNComponent); Basics::MatrixFloat *weights_matrix; /// learning parameters CBLAS_TRANSPOSE transpose_weights; protected: // from MatrixANNComponentHelper virtual Basics::MatrixFloat *privateDoDenseForward(Basics::MatrixFloat *input, bool during_training); virtual Basics::MatrixFloat *privateDoDenseBackprop(Basics::MatrixFloat *error_input); virtual void privateDenseReset(unsigned int it=0); virtual void privateDenseComputeGradients(const char *name, AprilUtils::LuaTable &grads_mat_dict); // from SparseMatrixANNComponentHelper virtual Basics::MatrixFloat *privateDoSparseForward(Basics::SparseMatrixFloat *input, bool during_training); virtual Basics::SparseMatrixFloat *privateDoSparseBackprop(Basics::MatrixFloat *error_input); virtual void privateSparseReset(unsigned int it=0); virtual void privateSparseComputeGradients(const char *name, AprilUtils::LuaTable &grads_mat_dict); // Basics::MatrixFloat *initializeComputeGradients(const char *name, AprilUtils::LuaTable &grads_mat_dict); public: DotProductANNComponent(const char *name=0, const char *weights_name=0, unsigned int input_size = 0, unsigned int output_size = 0, bool transpose_weights = false, Basics::MatrixFloat *matrix = 0); virtual ~DotProductANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void build(unsigned int input_size, unsigned int output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual void copyWeights(AprilUtils::LuaTable &weights_dict); bool transposed() { return transpose_weights == CblasTrans; } virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // DOTPRODUCTANNCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/dropout_component.cc000066400000000000000000000150531263004425400236650ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "error_print.h" #include "table_of_token_codes.h" #include "dropout_component.h" #include "dropout_kernel.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::Operations; using namespace AprilUtils; using namespace Basics; namespace ANN { DropoutANNComponent::DropoutANNComponent(MTRand *random, float value, float prob, bool normalize_after_training, const char *name, unsigned int size) : StochasticANNComponent(random, name, 0, size, size), input(0), output(0), error_input(0), error_output(0), dropout_mask(0), value(value), prob(prob), normalize_after_training(normalize_after_training), size(size) { } DropoutANNComponent::~DropoutANNComponent() { if (input) DecRef(input); if (error_input) DecRef(error_input); if (output) DecRef(output); if (error_output) DecRef(error_output); if (dropout_mask) DecRef(dropout_mask); } Token *DropoutANNComponent::doForward(Token* _input, bool during_training) { _input = StochasticANNComponent::doForward(_input, during_training); // error checking if ( (_input == 0) || (_input->getTokenCode() != table_of_token_codes::token_matrix)) ERROR_EXIT1(129,"Incorrect input Token type, expected token_matrix! [%s]\n", name.c_str()); // change current input by new input AssignRef(input,_input->convertTo()); if (prob > 0.0f && (during_training || normalize_after_training)) { MatrixFloat *input_mat = input->getMatrix(); #ifdef USE_CUDA input_mat->setUseCuda(use_cuda); #endif // new output to fit the bunch AssignRef(output,new TokenMatrixFloat(input_mat->clone())); MatrixFloat *output_mat = output->getMatrix(); // apply dropout if (during_training) { if (dropout_mask == 0 || dropout_mask->size() != input_mat->size()) { if (dropout_mask) DecRef(dropout_mask); dropout_mask = new MatrixFloat(1, input_mat->size()); IncRef(dropout_mask); } for (MatrixFloat::iterator it(dropout_mask->begin()); it != dropout_mask->end(); ++it) { if (random->rand() < prob) *it = 0.0f; else *it = 1.0f; } // apply mask Kernels::applyDropoutMask(output_mat, dropout_mask, value); } // if during_training else { // if not during_training matScal(output_mat, 1.0f - prob); } } // apply dropout else { AssignRef(output, input); } return output; } Token *DropoutANNComponent::doBackprop(Token *_error_input) { if (dropout_mask && prob > 0.0f) { // error checking if ( (_error_input == 0) || (_error_input->getTokenCode() != table_of_token_codes::token_matrix)) ERROR_EXIT1(129,"Incorrect input error Token type, expected token_matrix! [%s]\n", name.c_str()); // change current input by new input AssignRef(error_input,_error_input); TokenMatrixFloat *error_input_token_matrix = _error_input->convertTo(); MatrixFloat *error_input_mat = error_input_token_matrix->getMatrix(); april_assert(error_input_mat->getNumDim() >= 2); if (!error_input_mat->getIsContiguous()) { error_input_mat = error_input_mat->clone(); AssignRef(error_input,new TokenMatrixFloat(error_input_mat)); } #ifdef USE_CUDA error_input_mat->setUseCuda(use_cuda); #endif MatrixFloat *error_output_mat = error_input_mat->clone(); AssignRef(error_output,new TokenMatrixFloat(error_output_mat)); if (!error_output_mat->sameDim(input->getMatrix())) ERROR_EXIT1(129, "Different bunches found at doForward and doBackprop [%s]\n", name.c_str()); // apply mask Kernels::applyDropoutMask(error_output_mat, dropout_mask, 0.0f); } else { AssignRef(error_input, _error_input); AssignRef(error_output, _error_input); } return error_output; } void DropoutANNComponent::reset(unsigned int it) { StochasticANNComponent::reset(it); if (input) DecRef(input); if (error_input) DecRef(error_input); if (output) DecRef(output); if (error_output) DecRef(error_output); input = 0; error_input = 0; output = 0; error_output = 0; } ANNComponent *DropoutANNComponent::clone(AprilUtils::LuaTable &copies) { MTRand *rng_clone = copies[getRandom()].opt(0); if (rng_clone == 0) { copies[getRandom()] = rng_clone = new MTRand(*getRandom()); } DropoutANNComponent *copy_component = new DropoutANNComponent(rng_clone, value, prob, normalize_after_training, name.c_str(), size); return copy_component; } void DropoutANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); if (input_size == 0) input_size = output_size; if (output_size == 0) output_size = input_size; if (size != 0 && size != input_size) ERROR_EXIT(128, "Size given different from size at input/output\n"); size = input_size; if (input_size != output_size) ERROR_EXIT3(128, "Incorrect input/output sizes: input=%d output=%d [%s]\n", input_size, output_size, name.c_str()); } const char *DropoutANNComponent::luaCtorName() const { return "ann.components.dropout"; } int DropoutANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name; t["size"] = size; t["random"] = random; t["value"] = value; t["prob"] = prob; t["norm"] = normalize_after_training; t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/dropout_component.h000066400000000000000000000072221263004425400235260ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef DROPOUTCOMPONENT_H #define DROPOUTCOMPONENT_H #include "ann_component.h" #include "token_matrix.h" #include "stochastic_component.h" #define MASK_STR "mask" namespace ANN { /// This component adds to the input matrix mask noise, using a given random /// object, the noise probability, and the float value for masked units. The /// matrix size and dimensions are not restricted. class DropoutANNComponent : public StochasticANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(DropoutANNComponent); Basics::TokenMatrixFloat *input, *output; Basics::Token *error_input, *error_output; Basics::MatrixFloat *dropout_mask; float value; float prob; bool normalize_after_training; unsigned int size; public: DropoutANNComponent(Basics::MTRand *random, float value, float prob, bool normalize_after_training=true, const char *name=0, unsigned int size=0); virtual ~DropoutANNComponent(); virtual Basics::Token *getInput() { return input; } virtual Basics::Token *getOutput() { return output; } virtual Basics::Token *getErrorInput() { return error_input; } virtual Basics::Token *getErrorOutput() { return error_output; } virtual void setInput(Basics::Token *tk) { AssignRef(input, tk->convertTo()); } virtual void setOutput(Basics::Token *tk) { AssignRef(output, tk->convertTo()); } virtual void setErrorInput(Basics::Token *tk) { AssignRef(error_input, tk); } virtual void setErrorOutput(Basics::Token *tk) { AssignRef(error_output, tk); } virtual void copyState(AprilUtils::LuaTable &dict) { StochasticANNComponent::copyState(dict); AprilUtils::LuaTable state(dict.get(name)); if (dropout_mask != 0) { state.put(MASK_STR, dropout_mask); } } virtual void setState(AprilUtils::LuaTable &dict) { StochasticANNComponent::setState(dict); AprilUtils::LuaTable state(dict.get(name)); Basics::MatrixFloat *mask = state.opt(MASK_STR, 0); if (mask != 0) { AssignRef(dropout_mask, mask); } } virtual Basics::Token *doForward(Basics::Token* input, bool during_training); virtual Basics::Token *doBackprop(Basics::Token *input_error); virtual void reset(unsigned int it=0); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // DROPOUTCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/dropout_kernel.cu000066400000000000000000000024261263004425400231650ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "cmath_overloads.h" #include "dropout_kernel.h" #include "map_matrix.h" #include "matrixFloat.h" namespace ANN { namespace Kernels { void applyDropoutMask(Basics::MatrixFloat *output, Basics::MatrixFloat *mask, float value) { AprilMath::MatrixExt:: MatrixScalarMap2(output, mask, AprilMath::m_curried_mask(value), output); } } } april-ann-0.4.1/packages/ann/ann/c_src/dropout_kernel.h000066400000000000000000000021501263004425400227770ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef DROPOUT_KERNEL_H #define DROPOUT_KERNEL_H #include "matrixFloat.h" namespace ANN { namespace Kernels { void applyDropoutMask(Basics::MatrixFloat *output, Basics::MatrixFloat *mask, float value); } } #endif // DROPOUT_KERNEL_H april-ann-0.4.1/packages/ann/ann/c_src/exp_actf_component.cc000066400000000000000000000041261263004425400237610ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "cblas_headers.h" #include "exp_actf_component.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Operations; using namespace AprilUtils; using namespace Basics; namespace ANN { ExpActfANNComponent::ExpActfANNComponent(const char *name) : ActivationFunctionANNComponent(name) { } ExpActfANNComponent::~ExpActfANNComponent() { } void ExpActfANNComponent::applyActivation(MatrixFloat *input_units, MatrixFloat *output_units) { matExp(input_units, output_units); } void ExpActfANNComponent::multiplyDerivatives(MatrixFloat *input_units, MatrixFloat *output_units, MatrixFloat *input_errors, MatrixFloat *output_errors) { UNUSED_VARIABLE(input_units); matCopy(output_errors, output_units); matCmul(output_errors, input_errors); } ANNComponent *ExpActfANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); ExpActfANNComponent *obj = new ExpActfANNComponent(name.c_str()); return obj; } const char *ExpActfANNComponent::luaCtorName() const { return "ann.components.actf.exp"; } } april-ann-0.4.1/packages/ann/ann/c_src/exp_actf_component.h000066400000000000000000000034231263004425400236220ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef EXPACTFCOMPONENT_H #define EXPACTFCOMPONENT_H #include "activation_function_component.h" #include "ann_component.h" #include "gpu_mirrored_memory_block.h" namespace ANN { /// A component which computes the Exp activation function. class ExpActfANNComponent : public ActivationFunctionANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(ExpActfANNComponent); protected: virtual void applyActivation(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units); virtual void multiplyDerivatives(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units, Basics::MatrixFloat *input_errors, Basics::MatrixFloat *output_errors); public: ExpActfANNComponent(const char *name); virtual ~ExpActfANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual const char *luaCtorName() const; // virtual int exportParamsToLua(lua_State *L); }; } #endif // EXPACTFCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/flatten_component.cc000066400000000000000000000055671263004425400236370ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "error_print.h" #include "table_of_token_codes.h" #include "token_vector.h" #include "token_matrix.h" #include "flatten_component.h" using namespace Basics; using namespace AprilUtils; using namespace AprilMath; namespace ANN { FlattenANNComponent::FlattenANNComponent(const char *name) : VirtualMatrixANNComponent(name, 0, 0, 0) { setInputContiguousProperty(true); } FlattenANNComponent::~FlattenANNComponent() { } MatrixFloat *FlattenANNComponent:: privateDoForward(MatrixFloat* input_mat, bool during_training) { IncRef(input_mat); UNUSED_VARIABLE(during_training); if (input_mat->getNumDim() < 2) ERROR_EXIT2(128, "At 2-dimensional matrix is expected, found %d. " "[%s]", input_mat->getNumDim(), name.c_str()); flatten_dims[0] = input_mat->getDimSize(0); flatten_dims[1] = input_mat->size() / flatten_dims[0]; MatrixFloat *output_mat = input_mat->rewrap(flatten_dims, 2); DecRef(input_mat); return output_mat; } MatrixFloat *FlattenANNComponent:: privateDoBackprop(MatrixFloat *error_input_mat) { IncRef(error_input_mat); MatrixFloat *error_output_mat; MatrixFloat *input_mat = getInputMatrix(); error_output_mat = error_input_mat->rewrap(input_mat->getDimPtr(), input_mat->getNumDim()); DecRef(error_input_mat); return error_output_mat; } void FlattenANNComponent::privateReset(unsigned int it) { UNUSED_VARIABLE(it); } ANNComponent *FlattenANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); FlattenANNComponent *flatten_component; flatten_component = new FlattenANNComponent(name.c_str()); return flatten_component; } void FlattenANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); } const char *FlattenANNComponent::luaCtorName() const { return "ann.components.flatten"; } } april-ann-0.4.1/packages/ann/ann/c_src/flatten_component.h000066400000000000000000000045751263004425400234770ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef FLATTENCOMPONENT_H #define FLATTENCOMPONENT_H #include "vector.h" #include "matrix_component.h" #include "token_vector.h" #include "token_matrix.h" namespace ANN { /// This component receives a multidimensional input matrix and reinterprets /// its data like to be a bi-dimensional matrix (bunch size X number of /// neurons). class FlattenANNComponent : public VirtualMatrixANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(FlattenANNComponent); int flatten_dims[2]; virtual Basics::MatrixFloat *privateDoForward(Basics::MatrixFloat* input, bool during_training); virtual Basics::MatrixFloat *privateDoBackprop(Basics::MatrixFloat *input_error); virtual void privateReset(unsigned int it=0); public: FlattenANNComponent(const char *name=0); virtual ~FlattenANNComponent(); virtual void precomputeOutputSize(const AprilUtils::vector &input_size, AprilUtils::vector &output_size) { unsigned int sz = 1; for (unsigned int i=0; igetTokenCode() != table_of_token_codes::token_matrix)) ERROR_EXIT1(129,"Incorrect input Token type, expected token_matrix! [%s]\n", name.c_str()); // change current input by new input AssignRef(input,_input->convertTo()); #ifdef USE_CUDA input->getMatrix()->setUseCuda(use_cuda); #endif // new output to fit the bunch AssignRef(output,new TokenMatrixFloat(input->getMatrix()->clone())); // get memory blocks for tokens MatrixFloat *output_mat = output->getMatrix(); MatrixFloat *noise_mat = output_mat->cloneOnlyDims(); for (MatrixFloat::iterator it=noise_mat->begin(); it!=noise_mat->end(); ++it) { *it = random->randNorm(mean, variance); } matAxpy(output_mat, 1.0f, noise_mat); delete noise_mat; return output; } Token *GaussianNoiseANNComponent::doBackprop(Token *_error_input) { AssignRef(error_input, _error_input); AssignRef(error_output, _error_input); return error_output; } void GaussianNoiseANNComponent::reset(unsigned int it) { StochasticANNComponent::reset(it); if (input) DecRef(input); if (error_input) DecRef(error_input); if (output) DecRef(output); if (error_output) DecRef(error_output); input = 0; error_input = 0; output = 0; error_output = 0; } ANNComponent *GaussianNoiseANNComponent::clone(AprilUtils::LuaTable &copies) { MTRand *rng_clone = copies[getRandom()].opt(0); if (rng_clone == 0) { copies[getRandom()] = rng_clone = new MTRand(*getRandom()); } GaussianNoiseANNComponent *copy_component = new GaussianNoiseANNComponent(rng_clone, mean, variance, name.c_str(), input_size); return copy_component; } void GaussianNoiseANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); if (output_size == 0) output_size = input_size; if (input_size == 0) input_size = output_size; if (input_size != output_size) ERROR_EXIT3(128, "Incorrect input/output sizes: input=%d output=%d [%s]\n", input_size, output_size, name.c_str()); } const char *GaussianNoiseANNComponent::luaCtorName() const { return "ann.components.gaussian_noise"; } int GaussianNoiseANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name; t["size"] = input_size; t["random"] = random; t["mean"] = mean; t["var"] = variance; t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/gaussian_noise_component.h000066400000000000000000000055531263004425400250460ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef GAUSSIANNOISECOMPONENT_H #define GAUSSIANNOISECOMPONENT_H #include "ann_component.h" #include "token_matrix.h" #include "stochastic_component.h" namespace ANN { /// A component which adds gaussian noise, with the given mean and variance, /// to the input matrix. The size and dimensions of input matrix are not /// restricted. class GaussianNoiseANNComponent : public StochasticANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(GaussianNoiseANNComponent); Basics::TokenMatrixFloat *input, *output; Basics::Token *error_input, *error_output; float mean, variance; public: GaussianNoiseANNComponent(Basics::MTRand *random, float mean, float variance, const char *name=0, unsigned int size=0); virtual ~GaussianNoiseANNComponent(); virtual Basics::Token *getInput() { return input; } virtual Basics::Token *getOutput() { return output; } virtual Basics::Token *getErrorInput() { return error_input; } virtual Basics::Token *getErrorOutput() { return error_output; } // virtual void setInput(Basics::Token *tk) { AssignRef(input, tk->convertTo()); } virtual void setOutput(Basics::Token *tk) { AssignRef(output, tk->convertTo()); } virtual void setErrorInput(Basics::Token *tk) { AssignRef(error_input, tk); } virtual void setErrorOutput(Basics::Token *tk) { AssignRef(error_output, tk); } virtual Basics::Token *doForward(Basics::Token* input, bool during_training); virtual Basics::Token *doBackprop(Basics::Token *input_error); virtual void reset(unsigned int it=0); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // GAUSSIANNOISECOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/hardtanh_actf_component.cc000066400000000000000000000046631263004425400247640ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "activation_function_kernels.h" #include "hardtanh_actf_component.h" #include "unused_variable.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::Operations; using namespace AprilUtils; using namespace Basics; namespace ANN { HardtanhActfANNComponent::HardtanhActfANNComponent(const char *name, float inf, float sup) : ActivationFunctionANNComponent(name), inf(inf), sup(sup) { } HardtanhActfANNComponent::~HardtanhActfANNComponent() { } void HardtanhActfANNComponent::applyActivation(MatrixFloat *input_units, MatrixFloat *output_units) { matClamp(input_units, inf, sup, output_units); } void HardtanhActfANNComponent::multiplyDerivatives(MatrixFloat *input_units, MatrixFloat *output_units, MatrixFloat *input_errors, MatrixFloat *output_errors) { UNUSED_VARIABLE(output_units); Kernels::applyHardTanhDerivative(output_errors, input_units, inf, sup); matCmul(output_errors, input_errors); } ANNComponent *HardtanhActfANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); HardtanhActfANNComponent *obj = new HardtanhActfANNComponent(name.c_str()); return obj; } const char *HardtanhActfANNComponent::luaCtorName() const { return "ann.components.actf.hardtanh"; } int HardtanhActfANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name; t["inf"] = inf; t["sup"] = sup; t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/hardtanh_actf_component.h000066400000000000000000000036221263004425400246200ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef HARDTANHACTFCOMPONENT_H #define HARDTANHACTFCOMPONENT_H #include "activation_function_component.h" #include "ann_component.h" #include "gpu_mirrored_memory_block.h" namespace ANN { /// Component which computes the HardTanh activation function. It is useful /// for deep ANNs and CNNs. class HardtanhActfANNComponent : public ActivationFunctionANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(HardtanhActfANNComponent); float inf, sup; protected: virtual void applyActivation(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units); virtual void multiplyDerivatives(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units, Basics::MatrixFloat *input_errors, Basics::MatrixFloat *output_errors); public: HardtanhActfANNComponent(const char *name, float inf=-1.0f, float sup=1.0f); virtual ~HardtanhActfANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // HARDTANHACTFCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/hyperplane_component.cc000066400000000000000000000136541263004425400243450ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "hyperplane_component.h" using namespace Basics; using namespace AprilUtils; using namespace AprilMath; namespace ANN { HyperplaneANNComponent::HyperplaneANNComponent(const char *name) : ANNComponent(name, 0, 0, 0), dot_product(), bias() { } HyperplaneANNComponent::HyperplaneANNComponent(const char *name, const char *dot_product_name, const char *bias_name, const char *dot_product_weights_name, const char *bias_weights_name, unsigned int input_size, unsigned int output_size, bool transpose_weights, MatrixFloat *wmatrix, MatrixFloat *bmatrix) : ANNComponent(name, 0, input_size, output_size), dot_product(new DotProductANNComponent(dot_product_name, dot_product_weights_name, input_size, output_size, transpose_weights, wmatrix)), bias(new BiasANNComponent(output_size, bias_name, bias_weights_name, bmatrix)) { IncRef(dot_product); IncRef(bias); } HyperplaneANNComponent::~HyperplaneANNComponent() { if (dot_product != 0) DecRef(dot_product); if (bias != 0) DecRef(bias); } Token *HyperplaneANNComponent::getInput() { return dot_product->getInput(); } Token *HyperplaneANNComponent::getOutput() { return bias->getOutput(); } Token *HyperplaneANNComponent::getErrorInput() { return bias->getErrorInput(); } Token *HyperplaneANNComponent::getErrorOutput() { return dot_product->getErrorOutput(); } Token *HyperplaneANNComponent::doForward(Token* input, bool during_training) { Token *output = dot_product->doForward(input, during_training); output = bias->doForward(output, during_training); return output; } Token *HyperplaneANNComponent::doBackprop(Token *input_error) { Token *output = bias->doBackprop(input_error); output = dot_product->doBackprop(output); return output; } void HyperplaneANNComponent::reset(unsigned int it) { dot_product->reset(it); bias->reset(it); } void HyperplaneANNComponent::computeAllGradients(AprilUtils::LuaTable &weight_grads_dict) { dot_product->computeAllGradients(weight_grads_dict); bias->computeAllGradients(weight_grads_dict); } ANNComponent *HyperplaneANNComponent::clone(AprilUtils::LuaTable &copies) { HyperplaneANNComponent *obj; obj = new HyperplaneANNComponent(name.c_str()); obj->dot_product = dynamic_cast(dot_product->clone(copies)); obj->bias = dynamic_cast(bias->clone(copies)); obj->input_size = input_size; obj->output_size = output_size; IncRef(obj->dot_product); IncRef(obj->bias); return obj; } void HyperplaneANNComponent::setUseCuda(bool v) { ANNComponent::setUseCuda(v); dot_product->setUseCuda(v); bias->setUseCuda(v); } void HyperplaneANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); ////////////////////////////////////////////////////////////// if (input_size == 0 || output_size == 0) ERROR_EXIT1(141, "Impossible to compute input/output " "sizes for this component [%s]\n", name.c_str()); // dot_product->build(input_size, output_size, weights_dict, components_dict); bias->build(output_size, output_size, weights_dict, components_dict); } void HyperplaneANNComponent::copyWeights(AprilUtils::LuaTable &weights_dict) { dot_product->copyWeights(weights_dict); bias->copyWeights(weights_dict); } void HyperplaneANNComponent::copyComponents(AprilUtils::LuaTable &components_dict) { ANNComponent::copyComponents(components_dict); dot_product->copyComponents(components_dict); bias->copyComponents(components_dict); } ANNComponent *HyperplaneANNComponent::getComponent(string &name) { ANNComponent *component = ANNComponent::getComponent(name); if (component == 0) { component = dot_product->getComponent(name); if (component == 0) component = bias->getComponent(name); } return component; } const char *HyperplaneANNComponent::luaCtorName() const { return "ann.components.hyperplane"; } int HyperplaneANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L), weights(L); dot_product->copyWeights(weights); bias->copyWeights(weights); t["name"] = name; t["dot_product_name"] = dot_product->getName(); t["bias_name"] = bias->getName(); t["dot_product_weights"] = dot_product->getWeightsName(); t["bias_weights"] = bias->getWeightsName(); t["input"] = input_size; t["output"] = output_size; t["transpose"] = dot_product->transposed(); t["wmatrix"] = weights[dot_product->getWeightsName()].get(); t["bmatrix"] = weights[bias->getWeightsName()].get(); t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/hyperplane_component.h000066400000000000000000000073041263004425400242020ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef HYPERPLANECOMPONENT_H #define HYPERPLANECOMPONENT_H #include "vector.h" #include "ann_component.h" #include "dot_product_component.h" #include "bias_component.h" namespace ANN { /// This component is an stack of DotProductANNComponent and BiasANNComponent, /// because this two components are used together in almost every ANN. class HyperplaneANNComponent : public ANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(HyperplaneANNComponent); DotProductANNComponent *dot_product; BiasANNComponent *bias; HyperplaneANNComponent(const char *name); public: HyperplaneANNComponent(const char *name, const char *dot_product_name, const char *bias_name, const char *dot_product_weights_name, const char *bias_weights_name, unsigned int input_size=0, unsigned int output_size=0, bool transpose_weights=false, Basics::MatrixFloat *wmatrix=0, Basics::MatrixFloat *bmatrix=0); virtual ~HyperplaneANNComponent(); virtual Basics::Token *getInput(); virtual Basics::Token *getOutput(); virtual Basics::Token *getErrorInput(); virtual Basics::Token *getErrorOutput(); virtual void setInput(Basics::Token *tk) { dot_product->setInput(tk); } virtual void setOutput(Basics::Token *tk) { bias->setOutput(tk); } virtual void setErrorInput(Basics::Token *tk) { bias->setErrorInput(tk); } virtual void setErrorOutput(Basics::Token *tk) { dot_product->setErrorOutput(tk); } virtual void copyState(AprilUtils::LuaTable &dict) { ANNComponent::copyState(dict); dot_product->copyState(dict); bias->copyState(dict); } virtual void setState(AprilUtils::LuaTable &dict) { ANNComponent::setState(dict); dot_product->setState(dict); bias->setState(dict); } virtual Basics::Token *doForward(Basics::Token* input, bool during_training); virtual Basics::Token *doBackprop(Basics::Token *input_error); virtual void reset(unsigned int it=0); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void setUseCuda(bool v); virtual void build(unsigned int input_size, unsigned int output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual void copyWeights(AprilUtils::LuaTable &weights_dict); virtual void copyComponents(AprilUtils::LuaTable &components_dict); virtual ANNComponent *getComponent(AprilUtils::string &name); virtual void computeAllGradients(AprilUtils::LuaTable &weight_grads_dict); virtual void debugInfo() { ANNComponent::debugInfo(); dot_product->debugInfo(); bias->debugInfo(); } virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // HYPERPLANECOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/join_component.cc000066400000000000000000000361261263004425400231340ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "error_print.h" #include "table_of_token_codes.h" #include "join_component.h" #include "token_sparse_matrix.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilUtils; using namespace Basics; namespace ANN { JoinANNComponent::JoinANNComponent(const char *name) : ANNComponent(name, 0, 0, 0), input(0), error_output(0), output(0), error_input(0), input_vector(0), error_input_vector(0), output_vector(0), error_output_vector(0), segmented_input(false) { } JoinANNComponent::~JoinANNComponent() { for (unsigned int i=0; igetTokenCode()) { case table_of_token_codes::token_matrix: { segmented_input = false; TokenMatrixFloat *input_mat_token; input_mat_token = input_token->convertTo(); MatrixFloat *input_mat = input_mat_token->getMatrix(); ASSERT_MATRIX(input_mat); #ifdef USE_CUDA input_mat->setUseCuda(use_cuda); #endif unsigned int mat_pat_size = static_cast(input_mat->getDimSize(1)); april_assert(mat_pat_size==input_size && "Incorrect token matrix size"); int sizes[2] = { input_mat->getDimSize(0), input_mat->getDimSize(1) }; int coords[2] = { 0, 0 }; for (unsigned int i=0; isize(); ++i) { const unsigned int sz = components[i]->getInputSize(); // submatrix at coords with sizes, deep copy of original matrix sizes[1] = sz; MatrixFloat *output_mat = new MatrixFloat(input_mat,coords,sizes,true); #ifdef USE_CUDA output_mat->setUseCuda(use_cuda); #endif coords[1] += sz; TokenMatrixFloat *component_mat_token = new TokenMatrixFloat(output_mat); (*result_vector_token)[i] = component_mat_token; } break; } case table_of_token_codes::token_sparse_matrix: { segmented_input = false; TokenSparseMatrixFloat *input_mat_token; input_mat_token = input_token->convertTo(); SparseMatrixFloat *input_mat = input_mat_token->getMatrix(); ASSERT_MATRIX(input_mat); #ifdef USE_CUDA input_mat->setUseCuda(use_cuda); #endif unsigned int mat_pat_size = static_cast(input_mat->getDimSize(1)); april_assert(mat_pat_size==input_size && "Incorrect token matrix size"); int sizes[2] = { input_mat->getDimSize(0), input_mat->getDimSize(1) }; int coords[2] = { 0, 0 }; for (unsigned int i=0; isize(); ++i) { const unsigned int sz = components[i]->getInputSize(); // submatrix at coords with sizes, deep copy of original matrix sizes[1] = sz; SparseMatrixFloat *output_mat = new SparseMatrixFloat(input_mat,coords,sizes); #ifdef USE_CUDA output_mat->setUseCuda(use_cuda); #endif coords[1] += sz; TokenSparseMatrixFloat *component_mat_token = new TokenSparseMatrixFloat(output_mat); (*result_vector_token)[i] = component_mat_token; } break; } case table_of_token_codes::vector_Tokens: { segmented_input = true; TokenBunchVector *input_vector_token; input_vector_token = input_token->convertTo(); switch((*input_vector_token)[0]->getTokenCode()) { case table_of_token_codes::token_matrix: case table_of_token_codes::token_sparse_matrix: if (result_vector_token->size() != input_vector_token->size()) ERROR_EXIT3(128, "Incorrect number of components at input vector, " "expected %u and found %u [%s]\n", result_vector_token->size(), input_vector_token->size(), name.c_str()); // for each component we assign its matrix for (unsigned int i=0; isize(); ++i) (*result_vector_token)[i] = (*input_vector_token)[i]; break; case table_of_token_codes::vector_Tokens: // for each component we reserve a vector for bunch_size patterns for (unsigned int i=0; isize(); ++i) (*result_vector_token)[i] = new TokenBunchVector(input_vector_token->size()); // for each pattern for (unsigned int b=0; bsize(); ++b) { TokenBunchVector *pattern_token; pattern_token=(*input_vector_token)[b]->convertTo(); if (result_vector_token->size() != pattern_token->size()) ERROR_EXIT3(128, "Incorrect number of components at input vector, " "expected %u and found %u [%s]\n", result_vector_token->size(), pattern_token->size(), name.c_str()); // for each component for (unsigned int i=0; isize(); ++i) { (*(*result_vector_token)[i]->convertTo())[b] = (*pattern_token)[i]; } } break; default: ERROR_EXIT2(128, "Incorrect token type 0x%x [%s]\n", input_vector_token->getTokenCode(), name.c_str()); } break; } default: ERROR_EXIT2(129, "Incorrect token type 0x%x [%s]", input_token->getTokenCode(), name.c_str()); } } void JoinANNComponent::buildErrorInputBunchVector(TokenBunchVector *&vector_token, Token *token) { if (token->getTokenCode() != table_of_token_codes::token_matrix) ERROR_EXIT2(128, "Incorrect token type 0x%x [%s]\n", token->getTokenCode(), name.c_str()); // TokenMatrixFloat *mat_token = token->convertTo(); MatrixFloat *mat = mat_token->getMatrix(); ASSERT_MATRIX(mat); #ifndef USE_CUDA mat->setUseCuda(use_cuda); #endif unsigned int mat_pat_size = static_cast(mat->getDimSize(1)); april_assert(mat_pat_size==output_size && "Incorrect token matrix size"); int sizes[2] = { mat->getDimSize(0), 0 }; int coords[2] = { 0, 0 }; for (unsigned int i=0; isize(); ++i) { const unsigned int sz = components[i]->getOutputSize(); // sub-matrix at coords with sizes sizes[1] = sz; MatrixFloat *component_mat = new MatrixFloat(mat, coords, sizes, true); coords[1] += sz; TokenMatrixFloat *component_mat_token = new TokenMatrixFloat(component_mat); (*vector_token)[i] = component_mat_token; } } TokenMatrixFloat *JoinANNComponent::buildMatrixFloatToken(TokenBunchVector *token, bool is_output) { MatrixFloat *full_mat, *aux_mat; if ((*token)[0]->getTokenCode() != table_of_token_codes::token_matrix) ERROR_EXIT3(128,"Incorrect token type 0x%x at TokenBunchVector pos %d [%s]\n", (*token)[0]->getTokenCode(), 0,name.c_str()); aux_mat = (*token)[0]->convertTo()->getMatrix(); int sizes[2] = { aux_mat->getDimSize(0), (is_output) ? static_cast(output_size) : static_cast(input_size) }; int coords[2] = { 0, 0 }; full_mat = new MatrixFloat(2, sizes); #ifdef USE_CUDA full_mat->setUseCuda(use_cuda); #endif for (unsigned int i=0; isize(); ++i) { if ((*token)[i]->getTokenCode() != table_of_token_codes::token_matrix) ERROR_EXIT2(128, "Incorrect token type 0x%x [%s]\n", (*token)[i]->getTokenCode(), name.c_str()); aux_mat = (*token)[i]->convertTo()->getMatrix(); ASSERT_MATRIX(aux_mat); const unsigned int sz = ( (is_output) ? components[i]->getOutputSize() : components[i]->getInputSize() ); sizes[1] = sz; // Destination data sub-matrix (references original data matrix) MatrixFloat *submat = new MatrixFloat(full_mat, coords, sizes, false); matCopy(submat, aux_mat); delete submat; coords[1] += sz; } return new TokenMatrixFloat(full_mat); } TokenMatrixFloat *JoinANNComponent::buildMatrixFloatToken(Token *token, bool is_output) { if (token->getTokenCode() != table_of_token_codes::vector_Tokens) ERROR_EXIT1(128, "Incorrect output token type [%s]\n", name.c_str()); // TokenBunchVector *vector_token = token->convertTo(); return buildMatrixFloatToken(vector_token, is_output); } Token *JoinANNComponent::doForward(Token* _input, bool during_training) { AssignRef(input, _input); // INFO: will be possible to put this method inside next loop, but seems // more simpler a decoupled code buildInputBunchVector(input_vector, _input); for (unsigned int i=0; idoForward((*input_vector)[i].get(), during_training); // INFO: will be possible to put this method inside previous loop, but seems // more simpler a decoupled code AssignRef(output, buildMatrixFloatToken(output_vector, true)); // return output; } Token *JoinANNComponent::doBackprop(Token *_error_input) { if (_error_input == 0) { if (error_input) { DecRef(error_input); error_input = 0; } if (error_output) { DecRef(error_output); error_output = 0; } return 0; } if (_error_input->getTokenCode() != table_of_token_codes::token_matrix) ERROR_EXIT1(128, "Incorrect error input token type [%s]\n", name.c_str()); AssignRef(error_input, _error_input->convertTo()); // INFO: will be possible to put this method inside previous loop, but seems // more simpler a decoupled code buildErrorInputBunchVector(error_input_vector, _error_input); for (unsigned int i=0; idoBackprop((*error_input_vector)[i].get()); // error_output_vector has the gradients of each component stored as // array. Depending on the received input, this vector would be returned as // it is, or gradients will be stored as a TokenMatrixFloat joining all // array positions. if (segmented_input) AssignRef(error_output, error_output_vector); // INFO: will be possible to put this method inside previous loop, but // seems more simpler a decoupled code else AssignRef(error_output, buildMatrixFloatToken(error_output_vector, false)); return error_output; } void JoinANNComponent::reset(unsigned int it) { if (input) DecRef(input); if (error_input) DecRef(error_input); if (output) DecRef(output); if (error_output) DecRef(error_output); input = 0; error_input = 0; output = 0; error_output = 0; for (unsigned int i=0; ireset(it); } void JoinANNComponent::computeAllGradients(AprilUtils::LuaTable &weight_grads_dict) { for (unsigned int c=0; ccomputeAllGradients(weight_grads_dict); } } ANNComponent *JoinANNComponent::clone(AprilUtils::LuaTable &copies) { JoinANNComponent *join_component = new JoinANNComponent(name.c_str()); for (unsigned int i=0; iaddComponent(components[i]->clone(copies)); join_component->input_size = input_size; join_component->output_size = output_size; return join_component; } void JoinANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); // if (components.size() == 0) ERROR_EXIT1(128, "JoinANNComponent needs one or more components, " "use addComponent method [%s]\n", name.c_str()); unsigned int computed_input_size = 0, computed_output_size = 0; AssignRef(input_vector, new TokenBunchVector(components.size())); AssignRef(output_vector, new TokenBunchVector(components.size())); AssignRef(error_input_vector, new TokenBunchVector(components.size())); AssignRef(error_output_vector, new TokenBunchVector(components.size())); for (unsigned int i=0; ibuild(0, 0, weights_dict, components_dict); computed_input_size += components[i]->getInputSize(); computed_output_size += components[i]->getOutputSize(); (*input_vector)[i] = 0; (*output_vector)[i] = 0; (*error_input_vector)[i] = 0; (*error_output_vector)[i] = 0; } if (input_size == 0) input_size = computed_input_size; if (output_size == 0) output_size = computed_output_size; if (input_size != computed_input_size) ERROR_EXIT3(128, "Incorrect input sizes, components inputs sum %d but " "expected %d [%s]\n", computed_input_size, input_size, name.c_str()); if (output_size != computed_output_size) ERROR_EXIT3(128, "Incorrect output sizes, components outputs sum %d but " "expected %d [%s]\n", computed_output_size, output_size, name.c_str()); } void JoinANNComponent::setUseCuda(bool v) { ANNComponent::setUseCuda(v); for (unsigned int c=0; csetUseCuda(v); } void JoinANNComponent::copyWeights(AprilUtils::LuaTable &weights_dict) { for (unsigned int i=0; icopyWeights(weights_dict); } void JoinANNComponent::copyComponents(AprilUtils::LuaTable &components_dict) { ANNComponent::copyComponents(components_dict); for (unsigned int i=0; icopyComponents(components_dict); } ANNComponent *JoinANNComponent::getComponent(string &name) { ANNComponent *c = ANNComponent::getComponent(name); for (unsigned int i=0; igetComponent(name); return c; } const char *JoinANNComponent::luaCtorName() const { return "ann.components.join"; } int JoinANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L), c(L); t["name"] = name; t["components"] = c; for (unsigned int i=0; i components; // Token pointers which contains exactly the same that was received Basics::Token *input, *error_output; // This token is always a MatrixFloat Basics::TokenMatrixFloat *output, *error_input; // Auxiliar Token pointers to prepare data from and for contained components Basics::TokenBunchVector *input_vector, *error_input_vector; Basics::TokenBunchVector *output_vector, *error_output_vector; bool segmented_input; // private auxiliar methods void buildInputBunchVector(Basics::TokenBunchVector *&vector_token, Basics::Token *token); void buildErrorInputBunchVector(Basics::TokenBunchVector *&vector_token, Basics::Token *token); Basics::TokenMatrixFloat *buildMatrixFloatToken(Basics::TokenBunchVector *token, bool is_output); Basics::TokenMatrixFloat *buildMatrixFloatToken(Basics::Token *token, bool is_output); public: JoinANNComponent(const char *name=0); virtual ~JoinANNComponent(); void addComponent(ANNComponent *component); virtual Basics::Token *getInput() { return input; } virtual Basics::Token *getOutput() { return output; } virtual Basics::Token *getErrorInput() { return error_input; } virtual Basics::Token *getErrorOutput() { return error_output; } // virtual void setInput(Basics::Token *tk) { AssignRef(input, tk); } virtual void setOutput(Basics::Token *tk) { AssignRef(output, tk->convertTo()); } virtual void setErrorInput(Basics::Token *tk) { AssignRef(error_input, tk->convertTo()); } virtual void setErrorOutput(Basics::Token *tk) { AssignRef(error_output, tk); } virtual void copyState(AprilUtils::LuaTable &dict) { ANNComponent::copyState(dict); for (unsigned int i=0; icopyState(dict); } } virtual void setState(AprilUtils::LuaTable &dict) { ANNComponent::setState(dict); for (unsigned int i=0; isetState(dict); } } virtual void precomputeOutputSize(const AprilUtils::vector &input_size, AprilUtils::vector &output_size) { UNUSED_VARIABLE(input_size); UNUSED_VARIABLE(output_size); ERROR_EXIT(128, "Impossible to precomputeOutputSize in JoinANNComponent\n"); } virtual Basics::Token *doForward(Basics::Token* input, bool during_training); virtual Basics::Token *doBackprop(Basics::Token *input_error); virtual void reset(unsigned int it=0); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void setUseCuda(bool v); virtual void build(unsigned int input_size, unsigned int output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual void copyWeights(AprilUtils::LuaTable &weights_dict); virtual void copyComponents(AprilUtils::LuaTable &components_dict); virtual ANNComponent *getComponent(AprilUtils::string &name); virtual void computeAllGradients(AprilUtils::LuaTable &weight_grads_dict); virtual void debugInfo() { ANNComponent::debugInfo(); for (unsigned int i=0; idebugInfo(); } virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // JOINCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/leaky_relu_actf_component.cc000066400000000000000000000051331263004425400253200ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2015, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "activation_function_kernels.h" #include "cblas_headers.h" #include "leaky_relu_actf_component.h" #include "unused_variable.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::Operations; using namespace AprilUtils; using namespace Basics; namespace ANN { LeakyReLUActfANNComponent::LeakyReLUActfANNComponent(float leak, const char *name) : ActivationFunctionANNComponent(name), leak(leak) { } LeakyReLUActfANNComponent::~LeakyReLUActfANNComponent() { } void LeakyReLUActfANNComponent::applyActivation(MatrixFloat *input_units, MatrixFloat *output_units) { Kernels::applyLeakyReLU(output_units, input_units, leak); } void LeakyReLUActfANNComponent::multiplyDerivatives(MatrixFloat *input_units, MatrixFloat *output_units, MatrixFloat *input_errors, MatrixFloat *output_errors) { UNUSED_VARIABLE(output_units); Kernels::applyLeakyReLUDerivative(output_errors, input_units, leak); matCmul(output_errors, input_errors); } ANNComponent *LeakyReLUActfANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); LeakyReLUActfANNComponent *obj = new LeakyReLUActfANNComponent(leak, name.c_str()); return obj; } const char *LeakyReLUActfANNComponent::luaCtorName() const { return "ann.components.actf.leaky_relu"; } int LeakyReLUActfANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name; t["leak"] = leak; t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/leaky_relu_actf_component.h000066400000000000000000000035571263004425400251720ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2015, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LEAKYRELUACTFCOMPONENT_H #define LEAKYRELUACTFCOMPONENT_H #include "activation_function_component.h" #include "ann_component.h" #include "gpu_mirrored_memory_block.h" namespace ANN { /// Component for the Leaky ReLU activation function. class LeakyReLUActfANNComponent : public ActivationFunctionANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(LeakyReLUActfANNComponent); float leak; protected: virtual void applyActivation(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units); virtual void multiplyDerivatives(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units, Basics::MatrixFloat *input_errors, Basics::MatrixFloat *output_errors); public: LeakyReLUActfANNComponent(float leak=0.01f, const char *name=0); virtual ~LeakyReLUActfANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // LEAKYRELUACTFCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/linear_actf_component.cc000066400000000000000000000040021263004425400244300ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "cblas_headers.h" #include "linear_actf_component.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilUtils; using namespace Basics; namespace ANN { LinearActfANNComponent::LinearActfANNComponent(const char *name) : ActivationFunctionANNComponent(name) { } LinearActfANNComponent::~LinearActfANNComponent() { } void LinearActfANNComponent::applyActivation(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units) { matCopy(output_units, input_units); } void LinearActfANNComponent::multiplyDerivatives(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units, Basics::MatrixFloat *input_errors, Basics::MatrixFloat *output_errors) { UNUSED_VARIABLE(input_units); UNUSED_VARIABLE(output_units); matCopy(output_errors, input_errors); } ANNComponent *LinearActfANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); LinearActfANNComponent *obj = new LinearActfANNComponent(name.c_str()); return obj; } const char *LinearActfANNComponent::luaCtorName() const { return "ann.components.actf.linear"; } } april-ann-0.4.1/packages/ann/ann/c_src/linear_actf_component.h000066400000000000000000000034521263004425400243020ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LINEARACTFCOMPONENT_H #define LINEARACTFCOMPONENT_H #include "activation_function_component.h" #include "ann_component.h" #include "gpu_mirrored_memory_block.h" namespace ANN { /// This component implements the linear activation function. class LinearActfANNComponent : public ActivationFunctionANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(LinearActfANNComponent); protected: virtual void applyActivation(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units); virtual void multiplyDerivatives(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units, Basics::MatrixFloat *input_errors, Basics::MatrixFloat *output_errors); public: LinearActfANNComponent(const char *name); virtual ~LinearActfANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual const char *luaCtorName() const; // virtual int exportParamsToLua(lua_State *L); }; } #endif // LINEARACTFCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/log_actf_component.cc000066400000000000000000000040571263004425400237510ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "cblas_headers.h" #include "log_actf_component.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::Operations; using namespace AprilUtils; using namespace Basics; namespace ANN { LogActfANNComponent::LogActfANNComponent(const char *name) : ActivationFunctionANNComponent(name) { } LogActfANNComponent::~LogActfANNComponent() { } void LogActfANNComponent::applyActivation(MatrixFloat *input_units, MatrixFloat *output_units) { matLog(input_units, output_units); } void LogActfANNComponent::multiplyDerivatives(MatrixFloat *input_units, MatrixFloat *output_units, MatrixFloat *input_errors, MatrixFloat *output_errors) { UNUSED_VARIABLE(output_units); matDiv(input_units, 1.0f, output_errors); matCmul(output_errors, input_errors); } ANNComponent *LogActfANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); LogActfANNComponent *obj = new LogActfANNComponent(name.c_str()); return obj; } const char *LogActfANNComponent::luaCtorName() const { return "ann.components.actf.log"; } } april-ann-0.4.1/packages/ann/ann/c_src/log_actf_component.h000066400000000000000000000034231263004425400236070ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LOGACTFCOMPONENT_H #define LOGACTFCOMPONENT_H #include "activation_function_component.h" #include "ann_component.h" #include "gpu_mirrored_memory_block.h" namespace ANN { /// A component which computes the Log activation function. class LogActfANNComponent : public ActivationFunctionANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(LogActfANNComponent); protected: virtual void applyActivation(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units); virtual void multiplyDerivatives(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units, Basics::MatrixFloat *input_errors, Basics::MatrixFloat *output_errors); public: LogActfANNComponent(const char *name); virtual ~LogActfANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual const char *luaCtorName() const; // virtual int exportParamsToLua(lua_State *L); }; } #endif // LOGACTFCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/log_logistic_actf_component.cc000066400000000000000000000044531263004425400256460ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "activation_function_kernels.h" #include "cblas_headers.h" #include "log_logistic_actf_component.h" #include "unused_variable.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Operations; using namespace AprilUtils; using namespace Basics; namespace ANN { LogLogisticActfANNComponent::LogLogisticActfANNComponent(const char *name) : ActivationFunctionANNComponent(name) { } LogLogisticActfANNComponent::~LogLogisticActfANNComponent() { } void LogLogisticActfANNComponent::applyActivation(MatrixFloat *input_units, MatrixFloat *output_units) { Kernels::applyLogLogistic(output_units, input_units); } void LogLogisticActfANNComponent::multiplyDerivatives(MatrixFloat *input_units, MatrixFloat *output_units, MatrixFloat *input_errors, MatrixFloat *output_errors) { UNUSED_VARIABLE(input_units); UNUSED_VARIABLE(output_units); // This activation function derivative is cancelled by cross-entropy // derivative. It must be used with cross entropy loss function. matCopy(output_errors, input_errors); } ANNComponent *LogLogisticActfANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); LogLogisticActfANNComponent *obj = new LogLogisticActfANNComponent(name.c_str()); return obj; } const char *LogLogisticActfANNComponent::luaCtorName() const { return "ann.components.actf.log_logistic"; } } april-ann-0.4.1/packages/ann/ann/c_src/log_logistic_actf_component.h000066400000000000000000000037311263004425400255060ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LOGLOGISTICACTFCOMPONENT_H #define LOGLOGISTICACTFCOMPONENT_H #include "activation_function_component.h" #include "ann_component.h" #include "gpu_mirrored_memory_block.h" namespace ANN { /// This component implements the LogLogistic activation function. This /// activation only works with CrossEntropy LossFunction (and viceversa). class LogLogisticActfANNComponent : public ActivationFunctionANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(LogLogisticActfANNComponent); protected: virtual void applyActivation(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units); virtual void multiplyDerivatives(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units, Basics::MatrixFloat *input_errors, Basics::MatrixFloat *output_errors); public: LogLogisticActfANNComponent(const char *name); virtual ~LogLogisticActfANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual const char *luaCtorName() const; // virtual int exportParamsToLua(lua_State *L); }; } #endif // LOGLOGISTICACTFCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/log_softmax_actf_component.cc000066400000000000000000000043331263004425400255070ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "activation_function_kernels.h" #include "cblas_headers.h" #include "log_softmax_actf_component.h" #include "unused_variable.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilUtils; using namespace Basics; namespace ANN { LogSoftmaxActfANNComponent::LogSoftmaxActfANNComponent(const char *name) : ActivationFunctionANNComponent(name) { } LogSoftmaxActfANNComponent::~LogSoftmaxActfANNComponent() { } void LogSoftmaxActfANNComponent:: applyActivation(MatrixFloat *input_units, MatrixFloat *output_units) { Kernels::applyLogSoftmax(output_units, input_units); } void LogSoftmaxActfANNComponent:: multiplyDerivatives(MatrixFloat *input_units, MatrixFloat *output_units, MatrixFloat *input_errors, MatrixFloat *output_errors) { UNUSED_VARIABLE(input_units); UNUSED_VARIABLE(output_units); // This activation function derivative is cancelled by cross-entropy // derivative. It only could be used with cross entropy loss function. matCopy(output_errors, input_errors); } ANNComponent *LogSoftmaxActfANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); LogSoftmaxActfANNComponent *obj = new LogSoftmaxActfANNComponent(name.c_str()); return obj; } const char *LogSoftmaxActfANNComponent::luaCtorName() const { return "ann.components.actf.log_softmax"; } } april-ann-0.4.1/packages/ann/ann/c_src/log_softmax_actf_component.h000066400000000000000000000037411263004425400253530ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LOGSOFTMAXACTFCOMPONENT_H #define LOGSOFTMAXACTFCOMPONENT_H #include "activation_function_component.h" #include "ann_component.h" #include "gpu_mirrored_memory_block.h" namespace ANN { /// This component implements the LogSoftmax activation function. This /// activation only works with MultiClassCrossEntropy LossFunction (and /// viceversa). class LogSoftmaxActfANNComponent : public ActivationFunctionANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(LogSoftmaxActfANNComponent); protected: virtual void applyActivation(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units); virtual void multiplyDerivatives(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units, Basics::MatrixFloat *input_errors, Basics::MatrixFloat *output_errors); public: LogSoftmaxActfANNComponent(const char *name); virtual ~LogSoftmaxActfANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual const char *luaCtorName() const; // virtual int exportParamsToLua(lua_State *L); }; } #endif // LOGSOFTMAXACTFCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/logistic_actf_component.cc000066400000000000000000000115231263004425400250010ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "activation_function_kernels.h" #include "cblas_headers.h" #include "cmath_overloads.h" #include "logistic_actf_component.h" #include "unused_variable.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Operations; using namespace AprilMath::MatrixExt::Reductions; using namespace AprilUtils; using namespace Basics; namespace ANN { LogisticActfANNComponent::LogisticActfANNComponent(const char *name) : ActivationFunctionANNComponent(name) { } LogisticActfANNComponent::~LogisticActfANNComponent() { } void LogisticActfANNComponent::applyActivation(MatrixFloat *input_units, MatrixFloat *output_units) { Kernels::applyLogistic(output_units, input_units); } void LogisticActfANNComponent::multiplyDerivatives(MatrixFloat *input_units, MatrixFloat *output_units, MatrixFloat *input_errors, MatrixFloat *output_errors) { UNUSED_VARIABLE(input_units); Kernels::applyLogisticDerivative(output_errors, output_units); matCmul(output_errors, input_errors); } ANNComponent *LogisticActfANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); LogisticActfANNComponent *obj = new LogisticActfANNComponent(name.c_str()); return obj; } const char *LogisticActfANNComponent::luaCtorName() const { return "ann.components.actf.logistic"; } /////////////////////////////////////////////////////////////////////// SparseLogisticActfANNComponent:: SparseLogisticActfANNComponent(const char *name, float beta, float target_avg_act) : LogisticActfANNComponent(name) { this->beta = beta; this->target_avg_act = target_avg_act; } SparseLogisticActfANNComponent::~SparseLogisticActfANNComponent() { } ANNComponent *SparseLogisticActfANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); SparseLogisticActfANNComponent *obj = new SparseLogisticActfANNComponent(name.c_str(), beta, target_avg_act); return obj; } void SparseLogisticActfANNComponent::multiplyDerivatives(MatrixFloat *input_units, MatrixFloat *output_units, MatrixFloat *input_errors, MatrixFloat *output_errors) { UNUSED_VARIABLE(input_units); const float INV_DIM0 = 1.0f/static_cast(output_units->getDimSize(0)); const float EPS = AprilMath::Limits::epsilon(); // Computing average activations MatrixFloat *current_avg = matSum(output_units, 0); matScal(current_avg, INV_DIM0); // -p/\hat{p} MatrixFloat *sparse_gradients = current_avg->clone(); matClamp(sparse_gradients, EPS, 1.0f); matDiv(sparse_gradients, -target_avg_act); // (1-p)/(1-\hat{p}) MatrixFloat *aux = current_avg; // reusing current_avg matComplement(aux); matClamp(aux, EPS, 1.0f); matDiv(aux, (1.0f-target_avg_act)); // -p/\hat{p} + (1-p)/(1-\hat{p} = sparse_gradients + aux matAxpy(sparse_gradients, 1.0f, aux); // FIXME: Do we need to normalize by the bunch size? // matScal(sparse_gradients, INV_DIM0); // Unfold MatrixFloat *sparse_errors = input_errors->clone(); MatrixFloat *row = 0; for (int i = 0; i < output_units->getDimSize(0); ++i) { row = sparse_errors->select(0, i, row); matAxpy(row , beta, sparse_gradients); } delete row; Kernels::applyLogisticDerivative(output_errors, output_units); matCmul(output_errors, sparse_errors); delete aux; delete sparse_gradients; delete sparse_errors; } const char *SparseLogisticActfANNComponent::luaCtorName() const { return "ann.components.actf.sparse_logistic"; } int SparseLogisticActfANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name; t["penalty"] = beta; t["sparsity"] = target_avg_act; t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/logistic_actf_component.h000066400000000000000000000056231263004425400246470ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LOGISTICACTFCOMPONENT_H #define LOGISTICACTFCOMPONENT_H #include "activation_function_component.h" #include "ann_component.h" #include "gpu_mirrored_memory_block.h" namespace ANN { /// This component implements the logistic activation function. class LogisticActfANNComponent : public ActivationFunctionANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(LogisticActfANNComponent); protected: virtual void applyActivation(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units); virtual void multiplyDerivatives(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units, Basics::MatrixFloat *input_errors, Basics::MatrixFloat *output_errors); public: LogisticActfANNComponent(const char *name); virtual ~LogisticActfANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual const char *luaCtorName() const; // virtual int exportParamsToLua(lua_State *L); }; /** * @brief Implementation of logistic activation function with sparsity * penalty. * * @note The computation is based on Andrew Ng Stanford lecture: * https://web.stanford.edu/class/cs294a/sparseAutoencoder_2011new.pdf */ class SparseLogisticActfANNComponent: public LogisticActfANNComponent { private: float beta; ///< Weight of sparsity penalty term. float target_avg_act; ///< Desired level of sparsity. protected: virtual void multiplyDerivatives(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units, Basics::MatrixFloat *input_errors, Basics::MatrixFloat *output_errors); public: SparseLogisticActfANNComponent(const char *name, float beta, float target_avg_act); virtual ~SparseLogisticActfANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // LOGISTICACTFCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/matrix_component.cc000066400000000000000000000126401263004425400234740ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "matrix_component.h" #include "token_sparse_matrix.h" #include "unused_variable.h" using namespace Basics; using namespace AprilUtils; using namespace AprilMath; namespace ANN { VirtualMatrixANNComponent:: VirtualMatrixANNComponent(const char *name, const char *weights_name, unsigned int input_size, unsigned int output_size) : ANNComponent(name, weights_name, input_size, output_size), ComponentPropertiesAndAsserts(), input(0), output(0), error_input(0), error_output(0) { } VirtualMatrixANNComponent::~VirtualMatrixANNComponent() { if (input) DecRef(input); if (error_input) DecRef(error_input); if (output) DecRef(output); if (error_output) DecRef(error_output); } Token *VirtualMatrixANNComponent::doForward(Token* _input, bool during_training) { // error checking if (_input == 0) ERROR_EXIT1(129,"Incorrect input Token type, expected token_matrix! [%s]\n", name.c_str()); MatrixFloat *input_mat; switch( _input->getTokenCode() ) { case table_of_token_codes::token_matrix: { // change current input by new input AssignRef(input,_input->convertTo()); input_mat = input->getMatrix(); break; } case table_of_token_codes::token_sparse_matrix: { // compute dense matrix from sparse TokenSparseMatrixFloat *sparse_token; sparse_token = _input->convertTo(); input_mat = sparse_token->getMatrix()->toDense(); AssignRef(input, new TokenMatrixFloat(input_mat)); #ifndef NDEBUG ERROR_PRINT1("Sparse to dense matrix transformation is expensive [%s]\n", name.c_str()); #endif break; } default: input_mat = 0; ERROR_EXIT1(129,"Incorrect input Token type, expected token_matrix! [%s]\n", name.c_str()); } #ifdef USE_CUDA input_mat->setUseCuda(use_cuda); #endif ASSERT_MATRIX(input_mat); april_assert(input_size == 0 || input_mat->size()/input_mat->getDimSize(0) == static_cast(input_size)); if (getInputContiguousProperty() && !input_mat->getIsContiguous()) { input_mat = input_mat->clone(); AssignRef(input,new TokenMatrixFloat(input_mat)); } ///////////////////////// // FORWARD COMPUTATION // MatrixFloat *output_mat = privateDoForward(input_mat, during_training); ///////////////////////// april_assert(output_size == 0 || output_mat == 0 || output_mat->size()/output_mat->getDimSize(0) == static_cast(output_size)); AssignRef(output,new TokenMatrixFloat(output_mat)); return output; } Token *VirtualMatrixANNComponent::doBackprop(Token *_error_input) { if ( (_error_input == 0) || (_error_input->getTokenCode() != table_of_token_codes::token_matrix)) ERROR_EXIT1(129,"Incorrect input error Token type, expected token_matrix! [%s]\n", name.c_str()); // change current input by new input AssignRef(error_input,_error_input->convertTo()); MatrixFloat *error_input_mat = error_input->getMatrix(); #ifdef USE_CUDA error_input_mat->setUseCuda(use_cuda); #endif ASSERT_MATRIX(error_input_mat); april_assert(output_size == 0 || error_input_mat->size()/error_input_mat->getDimSize(0) == static_cast(output_size)); if (getInputContiguousProperty() && !error_input_mat->getIsContiguous()) { error_input_mat = error_input_mat->clone(); AssignRef(error_input,new TokenMatrixFloat(error_input_mat)); } if (! error_input_mat->sameDim(output->getMatrix()) ) { ERROR_EXIT1(129, "Different matrix sizes found at doForward and " "doBackprop [%s]\n", name.c_str()); } ////////////////////////// // BACKPROP COMPUTATION // MatrixFloat *error_output_mat = privateDoBackprop(error_input_mat); ////////////////////////// april_assert(input_size==0 || error_output_mat == 0 || error_output_mat->size()/error_output_mat->getDimSize(0) == static_cast(input_size)); if (error_input_mat != 0) { AssignRef(error_output, new TokenMatrixFloat(error_output_mat)); } else { if (error_output) DecRef(error_output); error_output = 0; } return error_output; } void VirtualMatrixANNComponent::reset(unsigned int it) { if (input) DecRef(input); if (error_input) DecRef(error_input); if (output) DecRef(output); if (error_output) DecRef(error_output); input = 0; error_input = 0; output = 0; error_output = 0; // reset shared counter privateReset(it); } } april-ann-0.4.1/packages/ann/ann/c_src/matrix_component.h000066400000000000000000000113101263004425400233270ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIXANNCOMPONENT_H #define MATRIXANNCOMPONENT_H #include "ann_component.h" #include "cblas_headers.h" #include "component_properties.h" #include "connection.h" #include "token_matrix.h" namespace ANN { /** * An abstract component which defines basic interface for components which * expect matrices and produce matrices. */ class VirtualMatrixANNComponent : public ANNComponent, public ComponentPropertiesAndAsserts { APRIL_DISALLOW_COPY_AND_ASSIGN(VirtualMatrixANNComponent); Basics::TokenMatrixFloat *input, *output, *error_input, *error_output; protected: // Auxiliary methods Basics::MatrixFloat *getInputMatrix() { return input->getMatrix(); } Basics::MatrixFloat *getOutputMatrix() { return output->getMatrix(); } Basics::MatrixFloat *getErrorInputMatrix() { return error_input->getMatrix(); } Basics::MatrixFloat *getErrorOutputMatrix() { return error_output->getMatrix(); } // Abstract methods /** * Forward computation using MatrixFloat input/output * * @param input - The MatrixFloat received as input. * @param during_training - Indicates if it is training or not. * @return A MatrixFloat with the forward computation result. */ virtual Basics::MatrixFloat *privateDoForward(Basics::MatrixFloat *input, bool during_training) = 0; /** * Backprop computation using MatrixFloat input/output * * @param input_error - The MatrixFloat received as input_error. * @return A MatrixFloat with the backprop computation result. */ virtual Basics::MatrixFloat *privateDoBackprop(Basics::MatrixFloat *input_error) = 0; /** * Reset of intermediate data * * @param it - Current iteration of optimization algorithm. */ virtual void privateReset(unsigned int it=0) = 0; // virtual void computeGradients(AprilUtils::SharedPtr &grad_mat) = 0; public: VirtualMatrixANNComponent(const char *name, const char *weights_name, unsigned int input_size, unsigned int output_size); virtual ~VirtualMatrixANNComponent(); virtual Basics::Token *getInput() { return input; } virtual Basics::Token *getOutput() { return output; } virtual Basics::Token *getErrorInput() { return error_input; } virtual Basics::Token *getErrorOutput() { return error_output; } // virtual void setInput(Basics::Token *tk) { AssignRef(input, tk->convertTo()); } virtual void setOutput(Basics::Token *tk) { AssignRef(output, tk->convertTo()); } virtual void setErrorInput(Basics::Token *tk) { AssignRef(error_input, tk->convertTo()); } virtual void setErrorOutput(Basics::Token *tk) { AssignRef(error_output, tk->convertTo()); } /** * If a TokenSparseMatrixFloat is given as input, it will be converted to * TokenMatrixFloat by calling toDense method of SparseMatrixFloat. */ virtual Basics::Token *doForward(Basics::Token* input, bool during_training); virtual Basics::Token *doBackprop(Basics::Token *input_error); virtual void reset(unsigned int it=0); // The following methods are not implemented, derived classes had to // // virtual ANNComponent *clone(AprilUtils::LuaTable &copies) = 0; /* virtual void build(unsigned int input_size, unsigned int output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) = 0; */ // virtual void copyWeights(AprilUtils::LuaTable &weights_dict) = 0; // virtual const char *luaCtorName() const; // virtual int exportParamsToLua(lua_State *L); }; } #endif // MATRIXANNCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/matrix_input_switch_component.cc000066400000000000000000000242641263004425400263010ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "error_print.h" #include "matrix_input_switch_component.h" #include "unused_variable.h" using namespace Basics; using namespace AprilUtils; using namespace AprilMath; namespace ANN { MatrixInputSwitchANNComponent:: MatrixInputSwitchANNComponent(const char *name, const char *weights_name, unsigned int input_size, unsigned int output_size) : ANNComponent(name, weights_name, input_size, output_size), ComponentPropertiesAndAsserts(), input(0), output(0), error_input(0), error_output(0), sparse_input(0), sparse_error_output(0), is_sparse_input(false) { } MatrixInputSwitchANNComponent::~MatrixInputSwitchANNComponent() { if (input) DecRef(input); if (output) DecRef(output); if (error_input) DecRef(error_input); if (error_output) DecRef(error_output); if (sparse_input) DecRef(sparse_input); if (sparse_error_output) DecRef(sparse_error_output); } Token *MatrixInputSwitchANNComponent::doDenseForward(Token *_input, bool during_training) { // error checking if (_input == 0) ERROR_EXIT1(129,"Incorrect input Token type, expected token_matrix! [%s]\n", name.c_str()); MatrixFloat *input_mat; if (_input->getTokenCode() != table_of_token_codes::token_matrix) ERROR_EXIT1(129,"Incorrect input Token type, expected token_matrix! [%s]\n", name.c_str()); // change current input by new input AssignRef(input,_input->convertTo()); input_mat = input->getMatrix(); #ifdef USE_CUDA input_mat->setUseCuda(use_cuda); #endif ASSERT_MATRIX(input_mat); april_assert(input_size == 0 || input_mat->size()/input_mat->getDimSize(0) == static_cast(input_size)); if (getInputContiguousProperty() && !input_mat->getIsContiguous()) { input_mat = input_mat->clone(); AssignRef(input,new TokenMatrixFloat(input_mat)); } ///////////////////////// // FORWARD COMPUTATION // MatrixFloat *output_mat = privateDoDenseForward(input_mat, during_training); ///////////////////////// april_assert(output_size == 0 || output_mat == 0 || output_mat->size()/output_mat->getDimSize(0) == static_cast(output_size)); AssignRef(output,new TokenMatrixFloat(output_mat)); return output; } Token *MatrixInputSwitchANNComponent::doSparseForward(Token *_input, bool during_training) { // error checking if (_input == 0) ERROR_EXIT1(129,"Incorrect input Token type, expected token_sparse_matrix! [%s]\n", name.c_str()); if (_input->getTokenCode() != table_of_token_codes::token_sparse_matrix) { ERROR_EXIT1(129,"Incorrect input Token type, expected token_matrix! [%s]\n", name.c_str()); } // change current input by new input AssignRef(sparse_input, _input->convertTo()); SparseMatrixFloat *input_mat = sparse_input->getMatrix(); #ifdef USE_CUDA input_mat->setUseCuda(use_cuda); #endif if (input_mat->getSparseFormat() != CSR_FORMAT) { ERROR_EXIT(128, "Sparse matrix must be in csr format\n"); } april_assert(input_size == 0 || input_mat->size()/input_mat->getDimSize(0) == static_cast(input_size)); ///////////////////////// // FORWARD COMPUTATION // MatrixFloat *output_mat = privateDoSparseForward(input_mat,during_training); ///////////////////////// april_assert(output_size == 0 || output_mat == 0 || output_mat->size()/output_mat->getDimSize(0) == static_cast(output_size)); AssignRef(output,new TokenMatrixFloat(output_mat)); return output; } Token *MatrixInputSwitchANNComponent::doDenseBackprop(Token *_error_input) { if ( (_error_input == 0) || (_error_input->getTokenCode() != table_of_token_codes::token_matrix)) ERROR_EXIT1(129,"Incorrect input error Token type, expected token_matrix! [%s]\n", name.c_str()); // change current input by new input AssignRef(error_input,_error_input->convertTo()); MatrixFloat *error_input_mat = error_input->getMatrix(); #ifdef USE_CUDA error_input_mat->setUseCuda(use_cuda); #endif ASSERT_MATRIX(error_input_mat); april_assert(output_size == 0 || error_input_mat->size()/error_input_mat->getDimSize(0) == static_cast(output_size)); if (getInputContiguousProperty() && !error_input_mat->getIsContiguous()) { error_input_mat = error_input_mat->clone(); AssignRef(error_input,new TokenMatrixFloat(error_input_mat)); } if (! error_input_mat->sameDim(output->getMatrix()) ) ERROR_EXIT1(129, "Different matrix sizes found at doForward and " "doBackprop [%s]\n", name.c_str()); ////////////////////////// // BACKPROP COMPUTATION // MatrixFloat *error_output_mat = privateDoDenseBackprop(error_input_mat); ////////////////////////// april_assert(input_size==0 || error_output_mat == 0 || error_output_mat->size()/error_output_mat->getDimSize(0) == static_cast(input_size)); if (error_output_mat != 0) { AssignRef(error_output, new TokenMatrixFloat(error_output_mat)); } else { if (error_output) DecRef(error_output); error_output = 0; } return error_output; } Token *MatrixInputSwitchANNComponent::doSparseBackprop(Token *_error_input) { if ( (_error_input == 0) || (_error_input->getTokenCode() != table_of_token_codes::token_matrix)) ERROR_EXIT1(129,"Incorrect input error Token type, expected token_matrix! [%s]\n", name.c_str()); // change current input by new input AssignRef(error_input,_error_input->convertTo()); MatrixFloat *error_input_mat = error_input->getMatrix(); #ifdef USE_CUDA error_input_mat->setUseCuda(use_cuda); #endif ASSERT_MATRIX(error_input_mat); april_assert(output_size == 0 || error_input_mat->size()/error_input_mat->getDimSize(0) == static_cast(output_size)); if (getInputContiguousProperty() && !error_input_mat->getIsContiguous()) { error_input_mat = error_input_mat->clone(); AssignRef(error_input,new TokenMatrixFloat(error_input_mat)); } if (! error_input_mat->sameDim(output->getMatrix()) ) ERROR_EXIT1(129, "Different matrix sizes found at doForward " "and doBackprop [%s]\n", name.c_str()); ////////////////////////// // BACKPROP COMPUTATION // SparseMatrixFloat *error_output_mat; error_output_mat = privateDoSparseBackprop(error_input_mat); ////////////////////////// april_assert(input_size==0 || error_output_mat == 0 || error_output_mat->size()/error_output_mat->getDimSize(0) == static_cast(input_size)); if (error_output_mat != 0) AssignRef(sparse_error_output, new TokenSparseMatrixFloat(error_output_mat)); else if (sparse_error_output) { if (sparse_error_output) DecRef(sparse_error_output); sparse_error_output = 0; } return sparse_error_output; } ///////////////////////////////////////////////////////////////////////////// Token *MatrixInputSwitchANNComponent::doForward(Token* _input, bool during_training) { Token *output; // error checking if (_input == 0) ERROR_EXIT1(129,"Incorrect input Token type, expected token_matrix or token_sparse_matrix! [%s]\n", getName().c_str()); switch( _input->getTokenCode() ) { case table_of_token_codes::token_matrix: { is_sparse_input = false; output = doDenseForward(_input, during_training); break; } case table_of_token_codes::token_sparse_matrix: { is_sparse_input = true; output = doSparseForward(_input, during_training); break; } default: output = 0; ERROR_EXIT1(129,"Incorrect input Token type, expected token_matrix or token_sparse_matrix! [%s]\n", getName().c_str()); } return output; } Token *MatrixInputSwitchANNComponent::doBackprop(Token *_error_input) { Token *error_output; if ( (_error_input == 0) || (_error_input->getTokenCode() != table_of_token_codes::token_matrix)) ERROR_EXIT1(129,"Incorrect input error Token type, expected token_matrix! [%s]\n", getName().c_str()); if (!is_sparse_input) { error_output = doDenseBackprop(_error_input); } else { error_output = doSparseBackprop(_error_input); } return error_output; } void MatrixInputSwitchANNComponent::reset(unsigned int it) { if (input) DecRef(input); if (output) DecRef(output); if (error_input) DecRef(error_input); if (error_output) DecRef(error_output); if (sparse_input) DecRef(sparse_input); if (sparse_error_output) DecRef(sparse_error_output); input = 0; output = 0; error_input = 0; error_output = 0; sparse_input = 0; sparse_error_output = 0; if (!is_sparse_input) privateDenseReset(it); else privateSparseReset(it); } void MatrixInputSwitchANNComponent::computeGradients(const char *name, AprilUtils::LuaTable &weight_grads_dict) { if (!is_sparse_input) privateDenseComputeGradients(name, weight_grads_dict); else privateSparseComputeGradients(name, weight_grads_dict); } } april-ann-0.4.1/packages/ann/ann/c_src/matrix_input_switch_component.h000066400000000000000000000150441263004425400261370ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIXINPUTSWITCHANNCOMPONENT_H #define MATRIXINPUTSWITCHANNCOMPONENT_H #include "ann_component.h" #include "april_assert.h" #include "cblas_headers.h" #include "component_properties.h" #include "sparse_matrixFloat.h" #include "token_matrix.h" #include "token_sparse_matrix.h" namespace ANN { /** * An abstract component which defines basic interface for components which * receives sparse or dense matrix and produce dense matrix. */ class MatrixInputSwitchANNComponent : public ANNComponent, public ComponentPropertiesAndAsserts { APRIL_DISALLOW_COPY_AND_ASSIGN(MatrixInputSwitchANNComponent); Basics::TokenMatrixFloat *input, *output, *error_input, *error_output; Basics::TokenSparseMatrixFloat *sparse_input, *sparse_error_output; bool is_sparse_input; // Auxiliary methods Basics::Token *doDenseForward(Basics::Token *_input, bool during_training); Basics::Token *doSparseForward(Basics::Token *_input, bool during_training); Basics::Token *doDenseBackprop(Basics::Token *_error_input); Basics::Token *doSparseBackprop(Basics::Token *_error_input); protected: // Auxiliary methods Basics::MatrixFloat *getInputMatrix() { april_assert(!is_sparse_input); return input->getMatrix(); } Basics::SparseMatrixFloat *getSparseInputMatrix() { april_assert(is_sparse_input); return sparse_input->getMatrix(); } Basics::MatrixFloat *getOutputMatrix() { return output->getMatrix(); } Basics::MatrixFloat *getErrorInputMatrix() { return error_input->getMatrix(); } Basics::MatrixFloat *getErrorOutputMatrix() { april_assert(!is_sparse_input); return error_output->getMatrix(); } Basics::SparseMatrixFloat *getSparseErrorOutputMatrix() { april_assert(is_sparse_input); return sparse_error_output->getMatrix(); } virtual void computeGradients(const char *name, AprilUtils::LuaTable &weight_grads_dict); // Abstract methods virtual Basics::MatrixFloat *privateDoDenseForward(Basics::MatrixFloat *input, bool during_training) = 0; virtual Basics::MatrixFloat *privateDoDenseBackprop(Basics::MatrixFloat *input_error) = 0; virtual void privateDenseReset(unsigned int it=0) = 0; virtual void privateDenseComputeGradients(const char *name, AprilUtils::LuaTable &weight_grads_dict) = 0; virtual Basics::MatrixFloat *privateDoSparseForward(Basics::SparseMatrixFloat *input, bool during_training) = 0; virtual Basics::SparseMatrixFloat *privateDoSparseBackprop(Basics::MatrixFloat *input_error) = 0; virtual void privateSparseReset(unsigned int it=0) = 0; virtual void privateSparseComputeGradients(const char *name, AprilUtils::LuaTable &weight_grads_dict) = 0; public: MatrixInputSwitchANNComponent(const char *name, const char *weights_name, unsigned int input_size, unsigned int output_size); virtual ~MatrixInputSwitchANNComponent(); virtual Basics::Token *getInput() { if (!is_sparse_input) return input; else return sparse_input; } virtual Basics::Token *getOutput() { return output; } virtual Basics::Token *getErrorInput() { return error_input; } virtual Basics::Token *getErrorOutput() { if (!is_sparse_input) return error_output; else return sparse_error_output; } // virtual void setInput(Basics::Token *tk) { switch(tk->getTokenCode()) { case Basics::table_of_token_codes::token_matrix: AssignRef(input, tk->convertTo()); is_sparse_input = false; break; case Basics::table_of_token_codes::token_sparse_matrix: AssignRef(sparse_input, tk->convertTo()); is_sparse_input = true; break; default: AssignRef(input, (Basics::TokenMatrixFloat*)0); AssignRef(sparse_input, (Basics::TokenSparseMatrixFloat*)0); } } virtual void setOutput(Basics::Token *tk) { AssignRef(output, tk->convertTo()); } virtual void setErrorInput(Basics::Token *tk) { AssignRef(error_input, tk->convertTo()); } virtual void setErrorOutput(Basics::Token *tk) { switch(tk->getTokenCode()) { case Basics::table_of_token_codes::token_matrix: AssignRef(error_output, tk->convertTo()); is_sparse_input = false; break; case Basics::table_of_token_codes::token_sparse_matrix: AssignRef(sparse_error_output, tk->convertTo()); is_sparse_input = true; break; default: AssignRef(error_output, (Basics::TokenMatrixFloat*)0); AssignRef(sparse_error_output, (Basics::TokenSparseMatrixFloat*)0); } } virtual Basics::Token *doForward(Basics::Token* input, bool during_training); virtual Basics::Token *doBackprop(Basics::Token *input_error); virtual void reset(unsigned int it=0); // // The following methods are not implemented, derived classes had to // // virtual ANNComponent *clone(AprilUtils::LuaTable &copies) = 0; /* virtual void build(unsigned int input_size, unsigned int output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) = 0; */ // virtual void copyWeights(AprilUtils::LuaTable &weights_dict) = 0; // virtual const char *luaCtorName() const; // virtual int exportParamsToLua(lua_State *L); }; } #endif // MATRIXINPUTSWITCHANNCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/maxpooling_component.cc000066400000000000000000000255201263004425400243460ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "maxpooling_component.h" #include "swap.h" #include "token_matrix.h" #include "table_of_token_codes.h" #include "unused_variable.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilMath::MatrixExt::Reductions; using namespace AprilUtils; using namespace Basics; using AprilUtils::swap; namespace ANN { /////////////////////////////////////////// // MaxPoolingANNComponent implementation // /////////////////////////////////////////// void MaxPoolingANNComponent::initializeArrays(const int *input_dims) { // input_dims[0] => BUNCH SIZE // output_dims[0] => BUNCH SIZE, output_dims[1] => HIDDEN LAYER SIZE output_dims[0] = input_dims[0]; input_window_size[0] = input_dims[0]; input_window_num_steps[0] = 1; output_window_size[0] = input_dims[0]; output_window_num_steps[0] = 1; input_window_rewrap[0] = input_dims[0]; output_window_rewrap[0] = input_dims[0]; for (int i=1; i<=input_num_dims; ++i) { if (kernel_dims[i] == 0) { output_dims[i] = 1; input_window_size[i] = input_dims[i]; input_window_num_steps[i] = output_dims[i]; output_window_num_steps[i] = output_dims[i]; } else { output_dims[i] = (input_dims[i] - kernel_dims[i])/kernel_step[i] + 1; input_window_size[i] = kernel_dims[i]; input_window_num_steps[i] = output_dims[i]; output_window_num_steps[i] = output_dims[i]; } } } MaxPoolingANNComponent::MaxPoolingANNComponent(int input_num_dims, const int *_kernel_dims, const int *_kernel_step, const char *name) : VirtualMatrixANNComponent(name, 0, 0, 0), argmax_raw_pos(0), number_input_windows(0), kernel_size(1), input_num_dims(input_num_dims), kernel_dims(new int[input_num_dims+1]), kernel_step(new int[input_num_dims+1]), output_dims(new int[input_num_dims+1]), input_window_size(new int[input_num_dims+1]), input_window_num_steps(new int[input_num_dims+1]), input_window_order_step(new int[input_num_dims+1]), input_window_rewrap(new int[2]), output_window_size(new int[input_num_dims+1]), output_window_step(new int[input_num_dims+1]), output_window_num_steps(new int[input_num_dims+1]), output_window_order_step(new int[input_num_dims+1]), output_window_rewrap(new int[2]) { // setInputContiguousProperty(true); input_window_order_step[0] = 0; output_window_size[0] = 0; output_window_order_step[0] = 0; output_window_step[0] = 1; kernel_step[0] = 1; kernel_dims[0] = 1; for(int i=0; i(kernel_size); output_window_rewrap[0] = 0; output_window_rewrap[1] = 1; } MaxPoolingANNComponent::~MaxPoolingANNComponent() { if (argmax_raw_pos) DecRef(argmax_raw_pos); delete[] kernel_dims; delete[] kernel_step; delete[] output_dims; delete[] input_window_size; delete[] input_window_num_steps; delete[] input_window_order_step; delete[] output_window_size; delete[] output_window_step; delete[] output_window_num_steps; delete[] output_window_order_step; delete[] input_window_rewrap; delete[] output_window_rewrap; } MatrixFloat *MaxPoolingANNComponent:: privateDoForward(MatrixFloat *input_mat, bool during_training) { IncRef(input_mat); if (input_mat->getNumDim() != input_num_dims+1) ERROR_EXIT3(129, "Incorrect input matrix numDims, " "expected %d, found %d [%s]\n", input_num_dims+1, input_mat->getNumDim(), name.c_str()); if (!input_mat->getIsContiguous()) { AssignRef(input_mat, input_mat->clone()); } const int *input_dims = input_mat->getDimPtr(); initializeArrays(input_dims); MatrixFloat *output_mat; output_mat = new MatrixFloat(input_num_dims+1, output_dims); IncRef(output_mat); #ifdef USE_CUDA output_mat->setUseCuda(use_cuda); #endif ///////////////////////////////////////////////////////////////////////// float *aux = input_mat->getRawDataAccess()->getPPALForReadAndWrite(); UNUSED_VARIABLE(aux); ///////////////////////////////////////////////////////////////////////// // Prepare sliding windows to compute the convolution MatrixFloat::sliding_window *input_sw = new MatrixFloat::sliding_window(input_mat, input_window_size, 0, // OFFSET kernel_step, input_window_num_steps, input_window_order_step); MatrixFloat::sliding_window *output_sw = new MatrixFloat::sliding_window(output_mat, output_window_size, 0, // OFFSET output_window_step, output_window_num_steps, output_window_order_step); number_input_windows = input_sw->numWindows(); april_assert(number_input_windows == output_sw->numWindows()); if (during_training) AssignRef(argmax_raw_pos, new Int32GPUMirroredMemoryBlock(input_mat->getDimSize(0)* output_sw->numWindows())); else if (argmax_raw_pos) { DecRef(argmax_raw_pos); argmax_raw_pos = 0; } int k=0; // CONVOLUTION OVER number_input_windows MatrixFloat *input_w = input_sw->getMatrix(); MatrixFloat *output_w = output_sw->getMatrix(); IncRef(input_w); IncRef(output_w); while(!input_sw->isEnd() && !output_sw->isEnd()) { input_sw->getMatrix(input_w); output_sw->getMatrix(output_w); MatrixFloat *max_sel_dim = matMaxSelDim(input_w, 0, argmax_raw_pos, k); IncRef(max_sel_dim); MatrixFloat *max_sel_dim_rewrapped; max_sel_dim_rewrapped = max_sel_dim->rewrap(output_w->getDimPtr(), output_w->getNumDim()); IncRef(max_sel_dim_rewrapped); matCopy(output_w, max_sel_dim_rewrapped); // Next iteration input_sw->next(); output_sw->next(); // Free memory DecRef(max_sel_dim_rewrapped); DecRef(max_sel_dim); k += input_mat->getDimSize(0); } DecRef(input_w); DecRef(output_w); DecRef(input_mat); delete input_sw; delete output_sw; ReleaseRef(output_mat); return output_mat; } MatrixFloat *MaxPoolingANNComponent:: privateDoBackprop(MatrixFloat *error_input_mat) { MatrixFloat *input_mat = getInputMatrix(); MatrixFloat *error_output_mat = input_mat->cloneOnlyDims(); IncRef(error_output_mat); matZeros(error_output_mat); // Prepare sliding windows to compute the convolution gradient MatrixFloat::sliding_window *error_output_sw = new MatrixFloat::sliding_window(error_output_mat, input_window_size, 0, // OFFSET kernel_step, input_window_num_steps, input_window_order_step); MatrixFloat::sliding_window *error_input_sw = new MatrixFloat::sliding_window(error_input_mat, output_window_size, 0, // OFFSET output_window_step, output_window_num_steps, output_window_order_step); april_assert(argmax_raw_pos != 0); april_assert(static_cast(argmax_raw_pos->getSize()) == error_input_mat->size()); april_assert(error_output_sw->numWindows() == error_input_sw->numWindows()); const int *argmax_ints = argmax_raw_pos->getPPALForRead(); // float *error_output_ptr = error_output_mat->getRawDataAccess()->getPPALForReadAndWrite(); // CONVOLUTION GRADIENT MatrixFloat *error_input_w = error_input_sw->getMatrix(); IncRef(error_input_w); while(!error_input_sw->isEnd()) { error_input_sw->getMatrix(error_input_w); for (MatrixFloat::const_iterator it(error_input_w->begin()); it!=error_input_w->end(); ++it, ++argmax_ints) { (*error_output_mat)[*argmax_ints] += *it; /* int jaja[4]; error_output_w->computeCoords(*argmax_ints, jaja); printf ("ERROR_OUTPUT-W["); for (int i=0; i<4; ++i) printf (" %d", jaja[i]); printf(" ] :: %d => %g\n", *argmax_ints, *it); error_output_mat->computeCoords(*argmax_ints, jaja); printf ("ERROR_OUTPUT-M["); for (int i=0; i<4; ++i) printf (" %d", jaja[i]); printf(" ] :: %d => %g\n", *argmax_ints, *it); */ } // Next iteration error_input_sw->next(); } // Free memory DecRef(error_input_w); delete error_input_sw; delete error_output_sw; ReleaseRef(error_output_mat); return error_output_mat; } void MaxPoolingANNComponent::privateReset(unsigned int it) { UNUSED_VARIABLE(it); if (argmax_raw_pos) DecRef(argmax_raw_pos); argmax_raw_pos = 0; } ANNComponent *MaxPoolingANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); MaxPoolingANNComponent *component = new MaxPoolingANNComponent(input_num_dims, kernel_dims+1, kernel_step+1, name.c_str()); component->input_size = input_size; component->output_size = output_size; return component; } const char *MaxPoolingANNComponent::luaCtorName() const { return "ann.components.max_pooling"; } int MaxPoolingANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L), kernel(L), step(L); t["name"] = name; t["kernel"] = kernel; t["step"] = step; for (int i=1; i<=input_num_dims; ++i) { kernel[i] = kernel_dims[i]; step[i] = kernel_step[i]; } t.pushTable(L); return 1; } ////////////////////////////////////////////////////////////////////////// } april-ann-0.4.1/packages/ann/ann/c_src/maxpooling_component.h000066400000000000000000000110161263004425400242030ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MAXPOOLINGANNCOMPONENT_H #define MAXPOOLINGANNCOMPONENT_H #include "token_matrix.h" #include "cblas_headers.h" #include "matrix_component.h" #include "connection.h" #include "gpu_mirrored_memory_block.h" namespace ANN { /// This component implements the Max-Pooling operation of convolutional /// neural networks (CNNs). It is configured with a given kernel size and /// kernel step, and outputs the maximum value of each possible window at /// input matrix. class MaxPoolingANNComponent : public VirtualMatrixANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(MaxPoolingANNComponent); AprilMath::Int32GPUMirroredMemoryBlock *argmax_raw_pos; // parameters of the convolution /// The number of convolutions computed during last forward int number_input_windows; /// The size of one kernel unsigned int kernel_size; /// The number of expected input dimensions without count BUNCH dim (first) const int input_num_dims; /// Size at each dim of the kernel, input_num_dims + 1 int *kernel_dims; /// Step at each dim of the input, input_num_dims + 1 int *kernel_step; /// Size at each dim of the output, input_num_dims + 1 int *output_dims; // first is BUNCH // INPUT SLIDING WINDOW SECTION /// Size of the convolution window, input_num_dims + 1 int *input_window_size; /// Number of steps of the convolution window, input_num_dims + 1 int *input_window_num_steps; /// Order for traversing the input data int *input_window_order_step; /// Translates the input window into a bi-dimensional matrix int *input_window_rewrap; // OUTPUT SLIDING WINDOW SECTION /// Size of the convolution window, input_num_dims + 1 int *output_window_size; /// Step between convolution windows, input_num_dims + 1 int *output_window_step; /// Number of steps of the convolution window, input_num_dims + 1 int *output_window_num_steps; /// Order for traversing the input data int *output_window_order_step; /// Translates the output window into a bi-dimensional matrix int *output_window_rewrap; Basics::MatrixFloat *getRewrappedMatrix(Basics::MatrixFloat *w, const int *rewrap_size, const int N) const { Basics::MatrixFloat *w_flattened; if (w->getIsContiguous()) w_flattened = w->rewrap(rewrap_size, N); else { Basics::MatrixFloat *w_clone = w->clone(); IncRef(w_clone); w_flattened = w_clone->rewrap(rewrap_size, N); DecRef(w_clone); } return w_flattened; } void initializeArrays(const int *input_dims); virtual Basics::MatrixFloat *privateDoForward(Basics::MatrixFloat* input, bool during_training); virtual Basics::MatrixFloat *privateDoBackprop(Basics::MatrixFloat *input_error); virtual void privateReset(unsigned int it=0); public: MaxPoolingANNComponent(int input_num_dims, const int *_kernel_dims, // input_num_dims const int *_kernel_step, const char *name=0); virtual ~MaxPoolingANNComponent(); virtual void precomputeOutputSize(const AprilUtils::vector &input_size, AprilUtils::vector &output_size) { output_size.clear(); for (int i=1; i<=input_num_dims; ++i) { if (kernel_dims[i] == 0) { output_size.push_back(1); } else { output_size.push_back((input_size[i-1]-kernel_dims[i])/kernel_step[i]+1); } } } virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // MAXPOOLINGANNCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/mul_component.cc000066400000000000000000000173621263004425400227730ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "april_assert.h" #include "mul_component.h" #include "unused_variable.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilMath::MatrixExt::Operations; using namespace AprilMath::MatrixExt::Reductions; using namespace AprilUtils; using namespace Basics; namespace ANN { MulANNComponent::MulANNComponent(unsigned int size, bool scalar, const char *name, const char *weights_name, MatrixFloat *matrix) : VirtualMatrixANNComponent(name, weights_name, size, size), scalar(scalar), mul_vector(matrix) { setInputContiguousProperty(true); if (weights_name == 0) generateDefaultWeightsName("m"); } MulANNComponent::~MulANNComponent() { } void MulANNComponent::applyCmul(MatrixFloat *dest, MatrixFloat *w) { if (w->size() == 1) { matScal(dest, *(w->begin())); } else { if (dest->size() == w->size()) { matCmul(dest, w); } else { april_assert(dest->size() > w->size()); // addition of mul vector at output AprilUtils::SharedPtr dest_slice; for (int i=0; igetDimSize(0); ++i) { dest_slice = dest->select(0, i, dest_slice.get()); matCmul(dest_slice.get(), w); } } } } MatrixFloat *MulANNComponent::privateDoForward(MatrixFloat* input, bool during_training) { UNUSED_VARIABLE(during_training); if (input->getNumDim() < 2) ERROR_EXIT2(128, "A 2-dimensional matrix is expected, found %d. " "[%s]", input->getNumDim(), name.c_str()); if (mul_vector.empty()) ERROR_EXIT1(129, "Not built component %s\n", name.c_str()); // transfer of input to output MatrixFloat *output = input->clone(); applyCmul(output, mul_vector.get()); // return output; } /// In MulANNComponent this method is a multiplication by the weights vector MatrixFloat *MulANNComponent::privateDoBackprop(MatrixFloat *error_input) { if (error_input->getNumDim() < 2) ERROR_EXIT2(128, "A 2-dimensional matrix is expected, found %d. " "[%s]", error_input->getNumDim(), name.c_str()); if (mul_vector.empty()) ERROR_EXIT1(129, "Not built component %s\n", name.c_str()); // transfer of input to output MatrixFloat *error_output = error_input->clone(); applyCmul(error_output, mul_vector.get()); // return error_output; } void MulANNComponent::privateReset(unsigned int it) { UNUSED_VARIABLE(it); // reset scalar counter mul_vector->resetSharedCount(); } void MulANNComponent::computeGradients(const char *name, AprilUtils::LuaTable &weight_grads_dict) { // count one use of the vector mul_vector->addToSharedCount(); MatrixFloat *grads_mat = weight_grads_dict.opt(name, 0); if (grads_mat == 0) { grads_mat = mul_vector->cloneOnlyDims(); matZeros(grads_mat); weight_grads_dict.put(name, grads_mat); } else if (!grads_mat->sameDim(mul_vector.get())) { ERROR_EXIT(128, "Incorrect weights matrix dimensions\n"); } #ifdef USE_CUDA grads_mat->setUseCuda(use_cuda); #endif MatrixFloat *error_input_mat = getErrorInputMatrix(); AprilUtils::SharedPtr aux = error_input_mat->clone(); MatrixFloat *input_mat = getInputMatrix(); applyCmul(aux.get(), input_mat); if (scalar) { *(grads_mat->begin()) = matSum(aux.get()); } else { AprilUtils::SharedPtr grads_mat_row; int dims[2] = { 1, aux->getDimSize(1) }; grads_mat_row = grads_mat->rewrap(dims, 2); matSum(aux.get(), 0, grads_mat_row.get()); } } ANNComponent *MulANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); MulANNComponent *component = new MulANNComponent(input_size, scalar, name.c_str(), weights_name.c_str()); return component; } void MulANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); // if (!scalar && input_size == 0 && output_size == 0) ERROR_EXIT1(141, "Impossible to compute input/output " "sizes for this component [%s]\n", name.c_str()); if (input_size == 0) input_size = output_size; else if (output_size == 0) output_size= input_size; else if (input_size != output_size) ERROR_EXIT1(142, "MulANNComponent input/output sizes must be equal [%s]\n", name.c_str()); //////////////////////////////////////////////////////////////////// MatrixFloat *w = weights_dict.opt(weights_name, 0); // printf("%s :: %p %p\n", weights_name.c_str(), w, mul_vector); if (w != 0) { mul_vector = w; // printf("COPY OF MUL FROM HASH %s\n", weights_name.c_str()); if (w->getNumDim() != 1) { ERROR_EXIT1(256, "Needs a one dimensional matrix [%s]\n", name.c_str()); } if (!scalar && w->getDimSize(0) != static_cast(input_size)) { ERROR_EXIT2(256, "Needs a one dimensional matrix with size %d [%s]\n", input_size, name.c_str()); } } else { if (mul_vector.empty()) { if (scalar) mul_vector = new MatrixFloat(1, 1); else mul_vector = new MatrixFloat(1, input_size); } weights_dict.put(weights_name, mul_vector.get()); } } void MulANNComponent::copyWeights(AprilUtils::LuaTable &weights_dict) { if (!mul_vector) ERROR_EXIT1(100, "Component not built, impossible execute copyWeights [%s]\n", name.c_str()); MatrixFloat *w = weights_dict.opt(weights_name, 0); if (w != 0 && w != mul_vector.get()) ERROR_EXIT2(101, "Weights dictionary contains %s weights name which is " "not shared with mul_vector attribute [%s]\n", weights_name.c_str(), name.c_str()); else if (w == 0) { weights_dict.put(weights_name, mul_vector.get()); } } const char *MulANNComponent::luaCtorName() const { return "ann.components.mul"; } int MulANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["size"] = input_size; t["scalar"] = scalar; t["name"] = name; t["weights"] = weights_name; t["matrix"] = mul_vector.get(); t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/mul_component.h000066400000000000000000000055411263004425400226310ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MULANNCOMPONENT_H #define MULANNCOMPONENT_H #include "cblas_headers.h" #include "matrix_component.h" #include "connection.h" #include "token_matrix.h" namespace ANN { /** * @brief A component which mul the given bi-dimensional input matrix by an * scalar or cmul by a vector. * * The component can be configured in two modes: scalar and non-scalar. Mode * is configured at construction, giving a boolean @c scalar=false by default. * In case of @c scalar=true the component performs multiplication of input * matrix by a learnable scalar value. In case of @ scalar=false, the * component computes multiplication of input matrix by a learnable vector. */ class MulANNComponent : public VirtualMatrixANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(MulANNComponent); bool scalar; AprilUtils::SharedPtr mul_vector; protected: virtual Basics::MatrixFloat *privateDoForward(Basics::MatrixFloat *input, bool during_training); virtual Basics::MatrixFloat *privateDoBackprop(Basics::MatrixFloat *input_error); virtual void privateReset(unsigned int it=0); virtual void computeGradients(const char *name, AprilUtils::LuaTable &weight_grads_dict); void applyCmul(Basics::MatrixFloat *dest, Basics::MatrixFloat *w); public: MulANNComponent(unsigned int size=0, bool scalar=false, const char *name=0, const char *weights_name=0, Basics::MatrixFloat *matrix=0); virtual ~MulANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void build(unsigned int input_size, unsigned int output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual void copyWeights(AprilUtils::LuaTable &weights_dict); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // MULANNCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/pca_whitening_component.cc000066400000000000000000000106121263004425400250040ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "error_print.h" #include "pca_whitening_component.h" #include "table_of_token_codes.h" #include "token_vector.h" #include "token_matrix.h" #include "unused_variable.h" #include "utilMatrixFloat.h" using namespace AprilIO; using namespace AprilMath; using namespace AprilMath::MatrixExt::Operations; using namespace AprilUtils; using namespace Basics; #define WEIGHTS_NAME "U_S_epsilon" namespace ANN { PCAWhiteningANNComponent::PCAWhiteningANNComponent(MatrixFloat *U, SparseMatrixFloat *S, float epsilon, unsigned int takeN, const char *name) : ANNComponent(name, 0, static_cast(U->getDimSize(0)), (takeN==0)?(static_cast(S->getDimSize(0))):(takeN)), U(U), S(S), epsilon(epsilon), dot_product_encoder(0, WEIGHTS_NAME, getInputSize(), getOutputSize(), true), takeN(takeN) { if (U->getNumDim() != 2) ERROR_EXIT(128, "Needs a bi-dimensional matrix as U argument\n"); if ( !S->isDiagonal() ) ERROR_EXIT(128, "Needs a sparse diagonal matrix as S argument\n"); if (static_cast(takeN) > S->getDimSize(0)) ERROR_EXIT(128, "Taking more components than size of S matrix\n"); if (takeN != 0) { int coords[2] = { 0,0 }; int sizes[2] = { U->getDimSize(0), static_cast(takeN) }; U_S_epsilon = new MatrixFloat(this->U, coords, sizes, true); } else U_S_epsilon = this->U->clone(); IncRef(this->U); IncRef(this->S); IncRef(U_S_epsilon); // regularization MatrixFloat *aux_mat = 0; SparseMatrixFloat::const_iterator Sit(this->S->begin()); for (int i=0; igetDimSize(1); ++i, ++Sit) { april_assert(Sit != this->S->end()); aux_mat = U_S_epsilon->select(1, i, aux_mat); matScal(aux_mat, 1/sqrtf( (*Sit) + epsilon ) ); } delete aux_mat; // matrix_set.put(WEIGHTS_NAME, U_S_epsilon); AprilUtils::LuaTable components_dict; dot_product_encoder.build(0, 0, matrix_set, components_dict); // avoid problems with DecRef in LuaTable IncRef(&dot_product_encoder); } PCAWhiteningANNComponent::~PCAWhiteningANNComponent() { DecRef(U); DecRef(S); DecRef(U_S_epsilon); } Token *PCAWhiteningANNComponent::doForward(Token* _input, bool during_training) { return dot_product_encoder.doForward(_input, during_training); } Token *PCAWhiteningANNComponent::doBackprop(Token *_error_input) { return dot_product_encoder.doBackprop(_error_input); } void PCAWhiteningANNComponent::reset(unsigned int it) { dot_product_encoder.reset(it); } ANNComponent *PCAWhiteningANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); PCAWhiteningANNComponent *component = new PCAWhiteningANNComponent(U, S, epsilon, takeN, name.c_str()); return component; } void PCAWhiteningANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { // TODO: CHECK INPUT OUTPUT SIZES UNUSED_VARIABLE(_input_size); UNUSED_VARIABLE(_output_size); UNUSED_VARIABLE(weights_dict); UNUSED_VARIABLE(components_dict); } const char *PCAWhiteningANNComponent::luaCtorName() const { return "ann.components.pca_whitening"; } int PCAWhiteningANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name.c_str(); t["U"] = U; t["S"] = S; t["epsilon"] = epsilon; t["takeN"] = takeN; t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/pca_whitening_component.h000066400000000000000000000063221263004425400246510ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef PCAWHITENINGCOMPONENT_H #define PCAWHITENINGCOMPONENT_H #include "sparse_matrixFloat.h" #include "matrixFloat.h" #include "vector.h" #include "ann_component.h" #include "token_vector.h" #include "token_matrix.h" #include "dot_product_component.h" namespace ANN { class PCAWhiteningANNComponent : public ANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(PCAWhiteningANNComponent); protected: Basics::MatrixFloat *U; //< bi-dimensional Basics::SparseMatrixFloat *S; //< sparse diagonal matrix in CSR Basics::MatrixFloat *U_S_epsilon; //< matrix for dot_product_component float epsilon; //< regularization DotProductANNComponent dot_product_encoder; //< Applies the transformation AprilUtils::LuaTable matrix_set; //< Auxiliary for dot_product_encoder build unsigned int takeN; public: PCAWhiteningANNComponent(Basics::MatrixFloat *U, Basics::SparseMatrixFloat *S, float epsilon=0.0f, unsigned int takeN=0, const char *name=0); virtual ~PCAWhiteningANNComponent(); virtual Basics::Token *getInput() { return dot_product_encoder.getInput(); } virtual Basics::Token *getOutput() { return dot_product_encoder.getOutput(); } virtual Basics::Token *getErrorInput() { return dot_product_encoder.getErrorInput(); } virtual Basics::Token *getErrorOutput() { return dot_product_encoder.getErrorOutput(); } // virtual void setInput(Basics::Token *tk) { dot_product_encoder.setInput(tk); } virtual void setOutput(Basics::Token *tk) { dot_product_encoder.setOutput(tk); } virtual void setErrorInput(Basics::Token *tk) { dot_product_encoder.setErrorInput(tk); } virtual void setErrorOutput(Basics::Token *tk) { dot_product_encoder.setErrorOutput(tk); } virtual Basics::Token *doForward(Basics::Token* input, bool during_training); virtual Basics::Token *doBackprop(Basics::Token *input_error); virtual void reset(unsigned int it=0); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); unsigned int getTakeN() const { return takeN; } virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // PCAWHITENINGCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/prelu_actf_component.cc000066400000000000000000000145031263004425400243140ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2015, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "activation_function_kernels.h" #include "cblas_headers.h" #include "error_print.h" #include "prelu_actf_component.h" #include "unused_variable.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Boolean; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilMath::MatrixExt::Misc; using namespace AprilMath::MatrixExt::Operations; using namespace AprilMath::MatrixExt::Reductions; using namespace AprilUtils; using namespace Basics; namespace ANN { PReLUActfANNComponent::PReLUActfANNComponent(bool scalar, unsigned int size, const char *name, const char *weights_name, MatrixFloat *matrix) : ActivationFunctionANNComponent(name), weights(matrix), size(size), scalar(scalar) { if (weights_name) { this->weights_name = string(weights_name); } else { generateDefaultWeightsName("a"); } } PReLUActfANNComponent::~PReLUActfANNComponent() { } void PReLUActfANNComponent::applyActivation(MatrixFloat *input_units, MatrixFloat *output_units) { if (scalar) { Kernels::applyLeakyReLU(output_units, input_units, (*weights)(0,0)); } else { Kernels::applyPReLU(output_units, input_units, weights.get()); } } void PReLUActfANNComponent::multiplyDerivatives(MatrixFloat *input_units, MatrixFloat *output_units, MatrixFloat *input_errors, MatrixFloat *output_errors) { UNUSED_VARIABLE(output_units); if (scalar) { Kernels::applyLeakyReLUDerivative(output_errors, input_units, (*weights)(0,0)); } else { Kernels::applyPReLUDerivative(output_errors, input_units, weights.get()); } matCmul(output_errors, input_errors); } void PReLUActfANNComponent::computeGradients(const char *weights_name, AprilUtils::LuaTable &weight_grads) { weights->addToSharedCount(); MatrixFloat *grads_mat = weight_grads.opt(weights_name, 0); if (grads_mat == 0) { grads_mat = weights->cloneOnlyDims(); matZeros(grads_mat); weight_grads.put(weights_name, grads_mat); } else if (!grads_mat->sameDim(weights.get())) { ERROR_EXIT(128, "Incorrect weights matrix dimensions\n"); } #ifdef USE_CUDA grads_mat->setUseCuda(use_cuda); #endif MatrixFloat *input = getInput()->convertTo()->getMatrix(); MatrixFloat *error = getErrorInput()->convertTo()->getMatrix(); // AprilUtils::SharedPtr lt_zero; lt_zero = new MatrixBool(input->getNumDim(), input->getDimPtr()); lt_zero = matLT(input, 0.0f, lt_zero.get()); AprilUtils::SharedPtr error_units; error_units = matConvertTo(lt_zero.get(), error_units.get()); error_units = matCmul(matCmul(error_units.get(), input), error); if (scalar) { (*grads_mat)(0,0) += matSum(error_units.get()); } else { // accumulated over previous gradients matSum(error_units.get(), 0, grads_mat, true); } } void PReLUActfANNComponent::reset(unsigned int it) { ANNComponent::reset(it); weights->resetSharedCount(); } ANNComponent *PReLUActfANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); PReLUActfANNComponent *obj = new PReLUActfANNComponent(scalar, size, name.c_str(), weights_name.c_str()); return obj; } void PReLUActfANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ActivationFunctionANNComponent::build(_input_size, _output_size, weights_dict, components_dict); unsigned int _size = getInputSize(); if (this->size != 0 && _size != 0 && this->size != _size) { ERROR_EXIT(128, "Incompatible sizes in build call\n"); } if (_size != 0) this->size = _size; this->input_size = this->output_size = this->size; if (this->size == 0) ERROR_EXIT(256, "Unable to allocate prelu weights\n"); unsigned int weights_size = (scalar) ? (1) : (this->size); // { // block for w variable MatrixFloat *w = weights_dict.opt(getWeightsName(), 0); if (w != 0) { weights = w; } else { if (!weights) { weights = Connections::build(1, weights_size); } weights_dict.put(getWeightsName(), weights.get()); } } // end of block for w variable // if (weights->size() != static_cast(weights_size)) { ERROR_EXIT1(257, "Unexpected matrix size [%s]\n", name.c_str()); } } const char *PReLUActfANNComponent::luaCtorName() const { return "ann.components.actf.prelu"; } int PReLUActfANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name.c_str(); t["weights"] = weights_name.c_str(); t["size"] = size; t["scalar"] = scalar ? "true" : "false"; t["matrix"] = weights.get(); t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/prelu_actf_component.h000066400000000000000000000051361263004425400241600ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2015, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef PRELUACTFCOMPONENT_H #define PRELUACTFCOMPONENT_H #include "activation_function_component.h" #include "ann_component.h" #include "gpu_mirrored_memory_block.h" #include "smart_ptr.h" namespace ANN { /** * @brief Component for the PReLU activation function. * * @see http://arxiv.org/pdf/1502.01852.pdf * * @todo Add ability to work with multiple input/output planes, for * convolutions. */ class PReLUActfANNComponent : public ActivationFunctionANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(PReLUActfANNComponent); AprilUtils::SharedPtr weights; unsigned int size; bool scalar; protected: virtual void applyActivation(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units); virtual void multiplyDerivatives(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units, Basics::MatrixFloat *input_errors, Basics::MatrixFloat *output_errors); public: PReLUActfANNComponent(bool scalar = false, unsigned int size = 0, const char *name = 0, const char *weights_name = 0, Basics::MatrixFloat *matrix = 0); virtual ~PReLUActfANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void computeGradients(const char *weights_name, AprilUtils::LuaTable &weight_grads); virtual void build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual void reset(unsigned int it=0); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // PRELUACTFCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/probabilistic_matrix_component.cc000066400000000000000000000270471263004425400264110ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2015, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "activation_function_kernels.h" #include "probabilistic_matrix_component.h" #include "matrixFloat.h" #include "sparse_matrixFloat.h" #include "swap.h" #include "token_base.h" #include "token_matrix.h" #include "table_of_token_codes.h" #include "token_sparse_matrix.h" #include "unused_variable.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilMath::MatrixExt::Operations; using namespace AprilMath::MatrixExt::Reductions; using namespace AprilUtils; using namespace Basics; namespace ANN { /////////////////////////////////////////// // ProbabilisticMatrixANNComponent implementation // /////////////////////////////////////////// ProbabilisticMatrixANNComponent:: ProbabilisticMatrixANNComponent(NormalizationSide side, const char *name, const char *weights_name, unsigned int input_size, unsigned int output_size, MatrixFloat *matrix) : VirtualMatrixANNComponent(name, weights_name, input_size, output_size), weights_mat(matrix), needs_weights_normalization(true), side(side) { setInputContiguousProperty(true); if (weights_name == 0) generateDefaultWeightsName("w"); } ProbabilisticMatrixANNComponent::~ProbabilisticMatrixANNComponent() { } MatrixFloat *ProbabilisticMatrixANNComponent:: privateDoForward(MatrixFloat *input_mat, bool during_training) { UNUSED_VARIABLE(during_training); if (input_mat->getNumDim() < 2) ERROR_EXIT2(128, "At 2-dimensional matrix is expected, found %d. " "[%s]", input_mat->getNumDim(), name.c_str()); if (weights_mat.empty()) ERROR_EXIT1(129, "Not built component %s\n", getName().c_str()); if (needs_weights_normalization) { // compute softmax over weights matrix in order to convert raw weights into // linear combination coefficients (sum 1, values in range [0,1]) if (side == LEFT) { april_assert(!T_weights_mat.empty()); april_assert(!T_normalized_weights_mat.empty()); Kernels::applySoftmax(T_normalized_weights_mat.get(), T_weights_mat.get()); } else { Kernels::applySoftmax(normalized_weights_mat.get(), weights_mat.get()); } // when not training, this flag would be true the first iteration and // false in the following needs_weights_normalization = during_training; } // unsigned int bunch_size = input_mat->getDimSize(0); // new output to fit the bunch MatrixFloat *output_mat; int dims[2] = { static_cast(bunch_size), static_cast(getOutputSize()) }; output_mat = new MatrixFloat(2, dims); #ifdef USE_CUDA output_mat->setUseCuda(use_cuda); #endif if (bunch_size == 1) { // vector x matrix product matGemv(output_mat, CblasNoTrans, 1.0f, normalized_weights_mat.get(), input_mat, 0.0f); } // if bunch_size==1 else { // matrix x matrix product // C = \alpha op(A) op(B) + \beta C // input * weights = output matGemm(output_mat, CblasNoTrans, CblasTrans, 1.0f, input_mat, normalized_weights_mat.get(), 0.0f); } // if bunch_size==1 ... else return output_mat; } MatrixFloat *ProbabilisticMatrixANNComponent:: privateDoBackprop(MatrixFloat *error_input_mat) { // new error output to fit the bunch unsigned int bunch_size = error_input_mat->getDimSize(0); // new output to fit the bunch MatrixFloat *error_output_mat; int dims[2] = { static_cast(bunch_size), static_cast(getInputSize()) }; error_output_mat = new MatrixFloat(2, dims); #ifdef USE_CUDA error_output_mat->setUseCuda(use_cuda); #endif // if (bunch_size > 1) { // C = alpha * A * B + beta * C matGemm(error_output_mat, CblasNoTrans, CblasNoTrans, 1.0f, error_input_mat, normalized_weights_mat.get(), 0.0f); } else { matGemv(error_output_mat, CblasTrans, 1.0f, normalized_weights_mat.get(), error_input_mat, 0.0f); } return error_output_mat; } void ProbabilisticMatrixANNComponent::privateReset(unsigned int it) { UNUSED_VARIABLE(it); weights_mat->resetSharedCount(); } MatrixFloat *ProbabilisticMatrixANNComponent:: initializeComputeGradients(const char *name, AprilUtils::LuaTable &grads_mat_dict) { weights_mat->addToSharedCount(); MatrixFloat *grads_mat = grads_mat_dict.opt(name, 0); if (grads_mat == 0) { grads_mat = weights_mat->cloneOnlyDims(); matZeros(grads_mat); grads_mat_dict.put(name, grads_mat); } else if (!grads_mat->sameDim(weights_mat.get())) { ERROR_EXIT(128, "Incorrect weights matrix dimensions\n"); } #ifdef USE_CUDA grads_mat->setUseCuda(use_cuda); #endif return grads_mat; } void ProbabilisticMatrixANNComponent:: computeGradients(const char *name, AprilUtils::LuaTable & grads_mat_dict) { MatrixFloat *grads_mat = initializeComputeGradients(name, grads_mat_dict); MatrixFloat *error_input_mat; error_input_mat = getErrorInputMatrix(); MatrixFloat *input_mat = getInputMatrix(); // compute gradients respect to normalized weights AprilUtils::SharedPtr norm_grads_mat(grads_mat->cloneOnlyDims()); matGemm(norm_grads_mat.get(), CblasTrans, CblasNoTrans, 1.0f, error_input_mat, // A input_mat, // B 0.0f); int norm_dim; // multiply by softmax derivative to obtain non-normalized weight gradients if (side == LEFT) { april_assert(!T_normalized_weights_mat.empty()); norm_dim = 0; AprilUtils::SharedPtr T_grads_mat(grads_mat->transpose()); AprilUtils::SharedPtr T_norm_grads_mat(norm_grads_mat->transpose()); Kernels::applySoftmaxDerivative(T_grads_mat.get(), T_norm_grads_mat.get(), T_normalized_weights_mat.get()); } else { norm_dim = 1; Kernels::applySoftmaxDerivative(grads_mat, norm_grads_mat.get(), normalized_weights_mat.get()); } // normalize the weights, to avoid weights exploding AprilUtils::SharedPtr max( matMax(weights_mat.get(), norm_dim) ); AprilUtils::SharedPtr row; for (int i=0; igetDimSize(norm_dim); ++i) { row = weights_mat->select(norm_dim, i); matAxpy(row.get(), -1.0f, max.get()); } matClamp(weights_mat.get(), -30.0f, 1.0f); // just in case, if gradients have been computed, weights may be changed // after, so update the flag needs_weights_normalization = true; } ANNComponent *ProbabilisticMatrixANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); ProbabilisticMatrixANNComponent *component = new ProbabilisticMatrixANNComponent(side, getName().c_str(), getWeightsName().c_str(), getInputSize(), getOutputSize()); return component; } void ProbabilisticMatrixANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { VirtualMatrixANNComponent::build(_input_size, _output_size, weights_dict, components_dict); // if (getInputSize() == 0 || getOutputSize() == 0) ERROR_EXIT1(141, "Impossible to compute input/output " "sizes for this component [%s]\n", getName().c_str()); unsigned int weights_input_size = getInputSize(); unsigned int weights_output_size = getOutputSize(); //////////////////////////////////////////////////////////////////// MatrixFloat *w = weights_dict.opt(getWeightsName(), 0); // printf("%s :: %p %p\n", weights_name.c_str(), w, weights_mat); if (w != 0) { // printf("COPY OF WEIGHTS FROM HASH %s\n", weights_name.c_str()); weights_mat = w; if (!Connections::checkInputOutputSizes(weights_mat.get(), weights_input_size, weights_output_size)) ERROR_EXIT5(256,"The weights matrix input/output sizes are not correct, " "expected %d and %d, found %d and %d [%s]\n", weights_input_size, weights_output_size, Connections::getInputSize(weights_mat.get()), Connections::getOutputSize(weights_mat.get()), getName().c_str()); } else { if (weights_mat.empty()) { // printf("NEW OF WEIGHTS %s\n", weights_name.c_str()); weights_mat = Connections::build(weights_input_size, weights_output_size); } // else printf("USING PREVIOUS WEIGHTS %s\n", weights_name.c_str()); weights_dict.put(getWeightsName(), weights_mat.get()); } normalized_weights_mat = weights_mat->cloneOnlyDims(); if (side == LEFT) { T_weights_mat = weights_mat->transpose(); T_normalized_weights_mat = normalized_weights_mat->transpose(); } } void ProbabilisticMatrixANNComponent::copyWeights(AprilUtils::LuaTable &weights_dict) { if (!weights_mat) { ERROR_EXIT1(100, "Component not built, impossible execute copyWeights [%s]\n", getName().c_str()); } MatrixFloat *w = weights_dict.opt(getWeightsName(), 0); if (w != 0 && w != weights_mat.get()) ERROR_EXIT2(101, "Weights dictionary contains %s weights name which is " "not shared with weights_mat attribute [%s]\n", getWeightsName().c_str(), getName().c_str()); else if (w == 0) { weights_dict.put(getWeightsName(), weights_mat.get()); } } const char *ProbabilisticMatrixANNComponent::luaCtorName() const { return "ann.components.probabilistic_matrix"; } int ProbabilisticMatrixANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["side"] = (side == LEFT) ? "left" : "right"; t["name"] = getName().c_str(); t["weights"] = getWeightsName().c_str(); t["input"] = getInputSize(); t["output"] = getOutputSize(); t["matrix"] = weights_mat.get(); t.pushTable(L); return 1; } ////////////////////////////////////////////////////////////////////////// } april-ann-0.4.1/packages/ann/ann/c_src/probabilistic_matrix_component.h000066400000000000000000000075051263004425400262500ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2015, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef PROBABILISTICMATRIXANNCOMPONENT_H #define PROBABILISTICMATRIXANNCOMPONENT_H #include "cblas_headers.h" #include "connection.h" #include "matrix_component.h" #include "smart_ptr.h" #include "token_matrix.h" namespace ANN { /** * @brief This component computes multiplication by a probabilistic matrix. * * Weights are forced to sum 1 and to be in range [0,1]. To achieve this goal, * the component has a set of raw weights which are transformed by means of * softmax function. The transformed weights are multiplied by the given * input. The transformation can be LEFT (by columns) or RIGHT (by rows), * normalizing outgoing or incoming weights respectively. * * @note This component uses @c during_training flag at @c forward() method * to force weights normalization via softmax transformation. */ class ProbabilisticMatrixANNComponent : public VirtualMatrixANNComponent { public: enum NormalizationSide { LEFT, RIGHT }; private: APRIL_DISALLOW_COPY_AND_ASSIGN(ProbabilisticMatrixANNComponent); /// The raw weights of this component. AprilUtils::SharedPtr weights_mat, /// Weights after softmax normalization normalized_weights_mat, /// Transposed version of raw weights, required for 'left' transformation T_weights_mat, /// Transposed version of normalized weights, for 'left' transformation T_normalized_weights_mat; bool needs_weights_normalization; NormalizationSide side; protected: // from MatrixANNComponentHelper virtual Basics::MatrixFloat *privateDoForward(Basics::MatrixFloat *input, bool during_training); virtual Basics::MatrixFloat *privateDoBackprop(Basics::MatrixFloat *error_input); virtual void privateReset(unsigned int it=0); virtual void computeGradients(const char *name, AprilUtils::LuaTable &weight_grads_dict); Basics::MatrixFloat *initializeComputeGradients(const char *name, AprilUtils::LuaTable &grads_mat_dict); public: ProbabilisticMatrixANNComponent(NormalizationSide side, const char *name=0, const char *weights_name=0, unsigned int input_size = 0, unsigned int output_size = 0, Basics::MatrixFloat *matrix = 0); virtual ~ProbabilisticMatrixANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void build(unsigned int input_size, unsigned int output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual void copyWeights(AprilUtils::LuaTable &weights_dict); Basics::MatrixFloat *getNormalizedWeights() { return normalized_weights_mat.get(); } virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // PROBABILISTICMATRIXANNCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/relu_actf_component.cc000066400000000000000000000040061263004425400241310ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "activation_function_kernels.h" #include "cblas_headers.h" #include "relu_actf_component.h" #include "unused_variable.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::Operations; using namespace AprilUtils; using namespace Basics; namespace ANN { ReLUActfANNComponent::ReLUActfANNComponent(const char *name) : ActivationFunctionANNComponent(name) { } ReLUActfANNComponent::~ReLUActfANNComponent() { } void ReLUActfANNComponent::applyActivation(MatrixFloat *input_units, MatrixFloat *output_units) { Kernels::applyReLU(output_units, input_units); } void ReLUActfANNComponent::multiplyDerivatives(MatrixFloat *input_units, MatrixFloat *output_units, MatrixFloat *input_errors, MatrixFloat *output_errors) { UNUSED_VARIABLE(output_units); Kernels::applyReLUDerivative(output_errors, input_units); matCmul(output_errors, input_errors); } ANNComponent *ReLUActfANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); ReLUActfANNComponent *obj = new ReLUActfANNComponent(name.c_str()); return obj; } const char *ReLUActfANNComponent::luaCtorName() const { return "ann.components.actf.relu"; } } april-ann-0.4.1/packages/ann/ann/c_src/relu_actf_component.h000066400000000000000000000034521263004425400237770ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef RELUACTFCOMPONENT_H #define RELUACTFCOMPONENT_H #include "activation_function_component.h" #include "ann_component.h" #include "gpu_mirrored_memory_block.h" namespace ANN { /// Component for the ReLU activation function. class ReLUActfANNComponent : public ActivationFunctionANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(ReLUActfANNComponent); protected: virtual void applyActivation(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units); virtual void multiplyDerivatives(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units, Basics::MatrixFloat *input_errors, Basics::MatrixFloat *output_errors); public: ReLUActfANNComponent(const char *name); virtual ~ReLUActfANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual const char *luaCtorName() const; // virtual int exportParamsToLua(lua_State *L); }; } #endif // RELUACTFCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/rewrap_component.cc000066400000000000000000000071061263004425400234710ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "error_print.h" #include "table_of_token_codes.h" #include "token_vector.h" #include "token_matrix.h" #include "rewrap_component.h" using namespace Basics; using namespace AprilUtils; using namespace AprilMath; namespace ANN { RewrapANNComponent::RewrapANNComponent(const int *rewrap_dims, int n, const char *name) : VirtualMatrixANNComponent(name, 0, mult(rewrap_dims,n), mult(rewrap_dims,n)), rewrap_dims(new int[n+1]), n(n+1) { setInputContiguousProperty(true); for (int i=1; in; ++i) this->rewrap_dims[i] = rewrap_dims[i-1]; } RewrapANNComponent::~RewrapANNComponent() { delete[] rewrap_dims; } MatrixFloat *RewrapANNComponent:: privateDoForward(MatrixFloat* input_mat, bool during_training) { UNUSED_VARIABLE(during_training); rewrap_dims[0] = input_mat->getDimSize(0); if (input_mat->getNumDim() < 2) ERROR_EXIT2(128, "At least 2-dimensional matrix is expected, found %d. " "[%s]", input_mat->getNumDim(), name.c_str()); MatrixFloat *output_mat = input_mat->rewrap(rewrap_dims, n); return output_mat; } MatrixFloat *RewrapANNComponent:: privateDoBackprop(MatrixFloat *error_input_mat) { MatrixFloat *input_mat = getInputMatrix(); MatrixFloat *error_output_mat; error_output_mat = error_input_mat->rewrap(input_mat->getDimPtr(), input_mat->getNumDim()); return error_output_mat; } void RewrapANNComponent::privateReset(unsigned int it) { UNUSED_VARIABLE(it); } ANNComponent *RewrapANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); RewrapANNComponent *rewrap_component = new RewrapANNComponent(rewrap_dims+1, n-1, name.c_str()); return rewrap_component; } void RewrapANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { unsigned int sz = 1; for (int i=1; in; ++i) sz *= rewrap_dims[i]; // if (_output_size != 0 && _output_size != sz) ERROR_EXIT2(256, "Incorrect output size, expected %d, found %d\n", sz, _output_size); if (_input_size != 0 && _input_size != sz) ERROR_EXIT2(256, "Incorrect input size, expected %d, found %d\n", sz, _input_size); // ANNComponent::build(sz, sz, weights_dict, components_dict); } const char *RewrapANNComponent::luaCtorName() const { return "ann.components.rewrap"; } int RewrapANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); AprilUtils::LuaTable size(L); t["name"] = name.c_str(); t["size"] = size; for (int i=1; i &input_size, AprilUtils::vector &output_size) { UNUSED_VARIABLE(input_size); output_size.clear(); for (int i=0; igetTokenCode() != table_of_token_codes::token_matrix)) ERROR_EXIT1(129,"Incorrect input Token type, expected token_matrix! [%s]\n", name.c_str()); // change current input by new input AssignRef(input,_input->convertTo()); #ifdef USE_CUDA input->getMatrix()->setUseCuda(use_cuda); #endif // new output to fit the bunch AssignRef(output,new TokenMatrixFloat(input->getMatrix()->clone())); MatrixFloat *output_mat = output->getMatrix(); for (MatrixFloat::iterator it(output_mat->begin()); it != output_mat->end(); ++it) { float p = random->rand(); if (p < prob) { if (p < prob * 0.5f) *it = zero; else *it = one; } } #ifdef USE_CUDA output->getMatrix()->setUseCuda(use_cuda); #endif return output; } Token *SaltAndPepperANNComponent::doBackprop(Token *_error_input) { AssignRef(error_input, _error_input); AssignRef(error_output, _error_input); return error_output; } void SaltAndPepperANNComponent::reset(unsigned int it) { StochasticANNComponent::reset(it); if (input) DecRef(input); if (error_input) DecRef(error_input); if (output) DecRef(output); if (error_output) DecRef(error_output); input = 0; error_input = 0; output = 0; error_output = 0; } ANNComponent *SaltAndPepperANNComponent::clone(AprilUtils::LuaTable &copies) { MTRand *rng_clone = copies[getRandom()].opt(0); if (rng_clone == 0) { copies[getRandom()] = rng_clone = new MTRand(*getRandom()); } SaltAndPepperANNComponent *copy_component = new SaltAndPepperANNComponent(rng_clone, zero, one, prob, name.c_str(), input_size); return copy_component; } void SaltAndPepperANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); if (output_size == 0) output_size = input_size; if (input_size == 0) input_size = output_size; if (input_size != output_size) ERROR_EXIT3(128, "Incorrect input/output sizes: input=%d output=%d [%s]\n", input_size, output_size, name.c_str()); } const char *SaltAndPepperANNComponent::luaCtorName() const { return "ann.components.salt_and_pepper"; } int SaltAndPepperANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name.c_str(); t["size"] = input_size; t["random"] = random; t["zero"] = zero; t["one"] = one; t["prob"] = prob; t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/salt_and_pepper_component.h000066400000000000000000000060171263004425400251730ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SALTANDPEPPERCOMPONENT_H #define SALTANDPEPPERCOMPONENT_H #include "ann_component.h" #include "token_matrix.h" #include "stochastic_component.h" namespace ANN { /// This component adds to the input matrix Salt and Pepper noise, using a /// given random object, the noise probability (50% is this is for zero, and /// 50% for one), and the float values of zero and one. The matrix size and /// dimensions are not restricted. class SaltAndPepperANNComponent : public StochasticANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(SaltAndPepperANNComponent); Basics::TokenMatrixFloat *input, *output; Basics::Token *error_input, *error_output; float zero, one; float prob; public: SaltAndPepperANNComponent(Basics::MTRand *random, float zero, float one, float prob, const char *name=0, unsigned int size=0); virtual ~SaltAndPepperANNComponent(); virtual Basics::Token *getInput() { return input; } virtual Basics::Token *getOutput() { return output; } virtual Basics::Token *getErrorInput() { return error_input; } virtual Basics::Token *getErrorOutput() { return error_output; } // virtual void setInput(Basics::Token *tk) { AssignRef(input, tk->convertTo()); } virtual void setOutput(Basics::Token *tk) { AssignRef(output, tk->convertTo()); } virtual void setErrorInput(Basics::Token *tk) { AssignRef(error_input, tk); } virtual void setErrorOutput(Basics::Token *tk) { AssignRef(error_output, tk); } virtual Basics::Token *doForward(Basics::Token* input, bool during_training); virtual Basics::Token *doBackprop(Basics::Token *input_error); virtual void reset(unsigned int it=0); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // SALTANDPEPPERCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/select_component.cc000066400000000000000000000071541263004425400234530ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "error_print.h" #include "table_of_token_codes.h" #include "token_vector.h" #include "token_matrix.h" #include "select_component.h" #include "smart_ptr.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilUtils; using namespace Basics; namespace ANN { SelectANNComponent::SelectANNComponent(int dimension, int index, const char *name) : VirtualMatrixANNComponent(name, 0, 0, 0), dimension(dimension), index(index) { setInputContiguousProperty(false); } SelectANNComponent::~SelectANNComponent() { } MatrixFloat *SelectANNComponent:: privateDoForward(MatrixFloat* input_mat, bool during_training) { UNUSED_VARIABLE(during_training); if (input_mat->getNumDim() < 3) ERROR_EXIT2(128, "At least 3 dimensional matrix is expected, found %d. " "First dimension is bunch-size, and the rest are pattern data " "[%s]", input_mat->getNumDim(), name.c_str()); AprilUtils::SharedPtr aux_output_mat( input_mat->select(dimension+1, index) ); MatrixFloat *output_mat = aux_output_mat->clone(); return output_mat; } MatrixFloat *SelectANNComponent:: privateDoBackprop(MatrixFloat *error_input_mat) { MatrixFloat *output_mat = getOutputMatrix(); MatrixFloat *input_mat = getInputMatrix(); if (!output_mat->sameDim(error_input_mat)) ERROR_EXIT1(128, "Error input token has incorrect dimensions [%s]\n", name.c_str()); MatrixFloat *error_output_mat = input_mat->cloneOnlyDims(); matZeros(error_output_mat); AprilUtils::SharedPtr select_error_output_mat( error_output_mat->select(dimension+1, index) ); matCopy(select_error_output_mat.get(), error_input_mat); #ifdef USE_CUDA select_error_output_mat->setUseCuda(use_cuda); #endif return error_output_mat; } void SelectANNComponent::privateReset(unsigned int it) { UNUSED_VARIABLE(it); } ANNComponent *SelectANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); SelectANNComponent *select_component = new SelectANNComponent(dimension, index, name.c_str()); return select_component; } void SelectANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); } const char *SelectANNComponent::luaCtorName() const { return "ann.components.select"; } int SelectANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name.c_str(); t["dimension"] = dimension; t["index"] = index; t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/select_component.h000066400000000000000000000042431263004425400233110ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SELECTCOMPONENT_H #define SELECTCOMPONENT_H #include "matrix_component.h" #include "token_matrix.h" namespace ANN { /// This component has a dimension and index properties, and applies the /// matrix::select(dimension, index) method to the input matrix. The size and /// dimensions of the input matrix are not restricted, only the given /// dimension property and index must be valid at the input matrix. class SelectANNComponent : public VirtualMatrixANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(SelectANNComponent); int dimension, index; protected: virtual Basics::MatrixFloat *privateDoForward(Basics::MatrixFloat* input, bool during_training); virtual Basics::MatrixFloat *privateDoBackprop(Basics::MatrixFloat *input_error); virtual void privateReset(unsigned int it=0); public: SelectANNComponent(int dimension, int index, const char *name=0); virtual ~SelectANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // SELECTCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/sin_actf_component.cc000066400000000000000000000040511263004425400237530ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "cblas_headers.h" #include "sin_actf_component.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::Operations; using namespace AprilUtils; using namespace Basics; namespace ANN { SinActfANNComponent::SinActfANNComponent(const char *name) : ActivationFunctionANNComponent(name) { } SinActfANNComponent::~SinActfANNComponent() { } void SinActfANNComponent::applyActivation(MatrixFloat *input_units, MatrixFloat *output_units) { matSin(input_units, output_units); } void SinActfANNComponent::multiplyDerivatives(MatrixFloat *input_units, MatrixFloat *output_units, MatrixFloat *input_errors, MatrixFloat *output_errors) { UNUSED_VARIABLE(output_units); matCos(input_units, output_errors); matCmul(output_errors, input_errors); } ANNComponent *SinActfANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); SinActfANNComponent *obj = new SinActfANNComponent(name.c_str()); return obj; } const char *SinActfANNComponent::luaCtorName() const { return "ann.components.actf.sin"; } } april-ann-0.4.1/packages/ann/ann/c_src/sin_actf_component.h000066400000000000000000000034231263004425400236170ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SINACTFCOMPONENT_H #define SINACTFCOMPONENT_H #include "activation_function_component.h" #include "ann_component.h" #include "gpu_mirrored_memory_block.h" namespace ANN { /// A component which computes the Sin activation function. class SinActfANNComponent : public ActivationFunctionANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(SinActfANNComponent); protected: virtual void applyActivation(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units); virtual void multiplyDerivatives(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units, Basics::MatrixFloat *input_errors, Basics::MatrixFloat *output_errors); public: SinActfANNComponent(const char *name); virtual ~SinActfANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual const char *luaCtorName() const; // virtual int exportParamsToLua(lua_State *L); }; } #endif // SINACTFCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/slice_component.cc000066400000000000000000000102561263004425400232700ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "error_print.h" #include "table_of_token_codes.h" #include "token_vector.h" #include "token_matrix.h" #include "slice_component.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilUtils; using namespace Basics; namespace ANN { SliceANNComponent::SliceANNComponent(const int *slice_offset, const int *slice_size, int n, const char *name) : VirtualMatrixANNComponent(name, 0, 0, mult(slice_size, n)), slice_offset(new int[n+1]), slice_size(new int[n+1]), n(n+1) { setInputContiguousProperty(false); for (int i=1; in; ++i) { this->slice_offset[i] = slice_offset[i-1]; this->slice_size[i] = slice_size[i-1]; } } SliceANNComponent::~SliceANNComponent() { delete[] slice_offset; delete[] slice_size; } MatrixFloat *SliceANNComponent:: privateDoForward(MatrixFloat* input_mat, bool during_training) { UNUSED_VARIABLE(during_training); slice_offset[0] = 0; slice_size[0] = input_mat->getDimSize(0); if (input_mat->getNumDim() < 2) ERROR_EXIT2(128, "At least 2-dimensional matrix is expected, found %d. " "[%s]", input_mat->getNumDim(), name.c_str()); MatrixFloat *output_mat = new MatrixFloat(input_mat, slice_offset, slice_size, false); return output_mat; } MatrixFloat *SliceANNComponent:: privateDoBackprop(MatrixFloat *error_input_mat) { MatrixFloat *input_mat = getInputMatrix(); MatrixFloat *error_output_mat; error_output_mat = input_mat->cloneOnlyDims(); matZeros(error_output_mat); MatrixFloat *error_output_mat_slice = new MatrixFloat(error_output_mat, slice_offset, slice_size, false); matCopy(error_output_mat_slice, error_input_mat); delete error_output_mat_slice; return error_output_mat; } void SliceANNComponent::privateReset(unsigned int it) { UNUSED_VARIABLE(it); } ANNComponent *SliceANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); SliceANNComponent *slice_component = new SliceANNComponent(slice_offset+1, slice_size+1, n-1, name.c_str()); return slice_component; } void SliceANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { unsigned int sz = mult(slice_size+1, n-1); // if (_output_size != 0 && _output_size != sz) ERROR_EXIT2(256, "Incorrect output size, expected %d, found %d\n", sz, _output_size); // ANNComponent::build(_input_size, sz, weights_dict, components_dict); if (input_size != 0 && input_size < output_size) ERROR_EXIT2(256, "Incorrect input size %d < slice size %d\n", input_size, output_size); } const char *SliceANNComponent::luaCtorName() const { return "ann.components.slice"; } int SliceANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); AprilUtils::LuaTable size(L); AprilUtils::LuaTable pos(L); t["name"] = name.c_str(); t["size"] = size; t["pos"] = pos; for (int i=0; igetTokenCode() ) { case table_of_token_codes::token_sparse_matrix: { // change current input by new input AssignRef(input,_input->convertTo()); input_mat = input->getMatrix(); } default: input_mat = 0; ERROR_EXIT1(129,"Incorrect input Token type, expected token_matrix! [%s]\n", name.c_str()); } #ifdef USE_CUDA input_mat->setUseCuda(use_cuda); #endif if (input_mat->getSparseFormat() != CSR_FORMAT) { ERROR_EXIT(128, "Sparse matrix must be in csr format\n"); } if (input_size > 0) { april_assert(input_mat->getDimSize(1) == static_cast(input_size)); } ///////////////////////// // FORWARD COMPUTATION // MatrixFloat *output_mat = privateDoForward(input_mat, during_training); ///////////////////////// AssignRef(output,new TokenMatrixFloat(output_mat)); return output; } Token *VirtualSparseMatrixANNComponent::doBackprop(Token *_error_input) { if ( (_error_input == 0) || (_error_input->getTokenCode() != table_of_token_codes::token_matrix)) ERROR_EXIT1(129,"Incorrect input error Token type, expected token_matrix! [%s]\n", name.c_str()); // change current input by new input AssignRef(error_input,_error_input->convertTo()); MatrixFloat *error_input_mat = error_input->getMatrix(); #ifdef USE_CUDA error_input_mat->setUseCuda(use_cuda); #endif ASSERT_MATRIX(error_input_mat); april_assert(output_size == 0 || error_input_mat->size()/error_input_mat->getDimSize(0) == static_cast(output_size)); if (getInputContiguousProperty() && !error_input_mat->getIsContiguous()) { error_input_mat = error_input_mat->clone(); AssignRef(error_input,new TokenMatrixFloat(error_input_mat)); } if (! error_input_mat->sameDim(output->getMatrix()) ) ERROR_EXIT1(129, "Different matrix sizes found at doForward and " "doBackprop [%s]\n", name.c_str()); ////////////////////////// // BACKPROP COMPUTATION // SparseMatrixFloat *error_output_mat = privateDoBackprop(error_input_mat); ////////////////////////// if (error_output_mat != 0) AssignRef(error_output, new TokenSparseMatrixFloat(error_output_mat)); else if (error_output) { if (error_output) DecRef(error_output); error_output = 0; } return error_output; } void VirtualSparseMatrixANNComponent::reset(unsigned int it) { if (input) DecRef(input); if (error_input) DecRef(error_input); if (output) DecRef(output); if (error_output) DecRef(error_output); input = 0; error_input = 0; output = 0; error_output = 0; // reset shared counter privateReset(it); } } april-ann-0.4.1/packages/ann/ann/c_src/sparse_matrix_component.h000066400000000000000000000115611263004425400247140ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SPARSEMATRIXANNCOMPONENT_H #define SPARSEMATRIXANNCOMPONENT_H #include "cblas_headers.h" #include "ann_component.h" #include "component_properties.h" #include "connection.h" #include "matrixFloat.h" #include "sparse_matrixFloat.h" #include "token_matrix.h" #include "token_sparse_matrix.h" namespace ANN { /** * An abstract component which defines basic interface for components which * expect sparse matrix as input and produce dense matrix as output. */ class VirtualSparseMatrixANNComponent : public ANNComponent, public ComponentPropertiesAndAsserts { APRIL_DISALLOW_COPY_AND_ASSIGN(VirtualSparseMatrixANNComponent); Basics::TokenSparseMatrixFloat *input, *error_output; Basics::TokenMatrixFloat *output, *error_input; protected: // Auxiliary methods Basics::SparseMatrixFloat *getInputMatrix() { return input->getMatrix(); } Basics::MatrixFloat *getOutputMatrix() { return output->getMatrix(); } Basics::MatrixFloat *getErrorInputMatrix() { return error_input->getMatrix(); } Basics::SparseMatrixFloat *getErrorOutputMatrix() { return error_output->getMatrix(); } // Abstract methods /** * Forward computation using SparseMatrixFloat input and MatrixFloat output * * @param input - The SparseMatrixFloat received as input. * @param during_training - Indicates if it is training or not. * @return A MatrixFloat with the forward computation result. */ virtual Basics::MatrixFloat *privateDoForward(Basics::SparseMatrixFloat *input, bool during_training) = 0; /** * Backprop computation using SparseMatrixFloat and MatrixFloat * * @param input_error - The MatrixFloat received as input_error. * @return A SparseMatrixFloat with the backprop computation result. */ virtual Basics::SparseMatrixFloat *privateDoBackprop(Basics::MatrixFloat *input_error) = 0; /** * Reset of intermediate data * * @param it - Current iteration of optimization algorithm. */ virtual void privateReset(unsigned int it=0) = 0; // virtual void computeGradients(const char *name, AprilUtils::LuaTable &weight_grads_dict) = 0; public: VirtualSparseMatrixANNComponent(const char *name, const char *weights_name, unsigned int input_size, unsigned int output_size); virtual ~VirtualSparseMatrixANNComponent(); virtual Basics::Token *getInput() { return input; } virtual Basics::Token *getOutput() { return output; } virtual Basics::Token *getErrorInput() { return error_input; } virtual Basics::Token *getErrorOutput() { return error_output; } // virtual void setInput(Basics::Token *tk) { AssignRef(input, tk->convertTo()); } virtual void setOutput(Basics::Token *tk) { AssignRef(output, tk->convertTo()); } virtual void setErrorInput(Basics::Token *tk) { AssignRef(error_input, tk->convertTo()); } virtual void setErrorOutput(Basics::Token *tk) { AssignRef(error_output, tk->convertTo()); } virtual Basics::Token *doForward(Basics::Token* input, bool during_training); virtual Basics::Token *doBackprop(Basics::Token *input_error); virtual void reset(unsigned int it=0); // The following methods are not implemented, derived classes had to // // virtual ANNComponent *clone(AprilUtils::LuaTable &copies) = 0; /* virtual void build(unsigned int input_size, unsigned int output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) = 0; */ // virtual void copyWeights(AprilUtils::LuaTable &weights_dict) = 0; // virtual const char *luaCtorName() const; // virtual int exportParamsToLua(lua_State *L); }; } #endif // SPARSEMATRIXANNCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/stack_component.cc000066400000000000000000000144641263004425400233030ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "stack_component.h" using namespace Basics; using namespace AprilUtils; using namespace AprilMath; namespace ANN { StackANNComponent::StackANNComponent(const char *name, unsigned int input, unsigned int output) : ANNComponent(name, 0, input, output) { } StackANNComponent::~StackANNComponent() { for (unsigned int i=0; igetInputSize() > 0u) { input_size = components[0]->getInputSize(); } } ANNComponent *StackANNComponent::topComponent() { return components.back(); } void StackANNComponent::popComponent() { DecRef(components.back()); components.pop_back(); if (components.size() > 0u) { output_size = components.back()->getOutputSize(); } else { input_size = output_size = 0; } } Token *StackANNComponent::getInput() { return components[0]->getInput(); } Token *StackANNComponent::getOutput() { return components.back()->getOutput(); } Token *StackANNComponent::getErrorInput() { return components.back()->getErrorInput(); } Token *StackANNComponent::getErrorOutput() { return components[0]->getErrorOutput(); } Token *StackANNComponent::doForward(Token* input, bool during_training) { Token *aux_token = input; for (unsigned int c=0; cdoForward(aux_token, during_training); return aux_token; } Token *StackANNComponent::doBackprop(Token *input_error) { Token *aux_token = input_error; for (unsigned int c=components.size(); c>0; --c) aux_token = components[c-1]->doBackprop(aux_token); return aux_token; } void StackANNComponent::reset(unsigned int it) { for (unsigned int c=0; creset(it); } void StackANNComponent::computeAllGradients(AprilUtils::LuaTable &weight_grads_dict) { for (unsigned int c=0; ccomputeAllGradients(weight_grads_dict); } } ANNComponent *StackANNComponent::clone(AprilUtils::LuaTable &copies) { StackANNComponent *obj = new StackANNComponent(name.c_str()); for (unsigned int c=0; cpushComponent(components[c]->clone(copies)); obj->input_size = input_size; obj->output_size = output_size; return obj; } void StackANNComponent::setUseCuda(bool v) { ANNComponent::setUseCuda(v); for (unsigned int c=0; csetUseCuda(v); } void StackANNComponent::build(unsigned int _input_size, unsigned int _output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict) { ANNComponent::build(_input_size, _output_size, weights_dict, components_dict); ////////////////////////////////////////////////////////////// if (components.size() == 0) ERROR_EXIT1(128, "StackANNComponent needs one or more components, " "use pushComponent method [%s]\n", name.c_str()); // unsigned int current_input_size = input_size; unsigned int current_output_size = 0; for (unsigned int c=0; cgetInputSize(); components[c]->build(current_input_size, current_output_size, weights_dict, components_dict); current_input_size = components[c]->getOutputSize(); current_output_size = 0; } if (input_size == 0) input_size = components[0]->getInputSize(); if (output_size == 0) output_size = components.back()->getOutputSize(); else if (output_size != components.back()->getOutputSize()) ERROR_EXIT3(141, "StackANNComponent output size is not correct: " "%d != %d [%s]\n", output_size, components.back()->getOutputSize(), name.c_str()); /* if (input_size == 0 || output_size == 0) ERROR_PRINT3("# WARNING: Impossible to compute input/output " "sizes for this component input=%d output=%d [%s]\n", input_size, output_size, name.c_str()); */ } void StackANNComponent::copyWeights(AprilUtils::LuaTable &weights_dict) { for (unsigned int c=0; ccopyWeights(weights_dict); } void StackANNComponent::copyComponents(AprilUtils::LuaTable &components_dict) { ANNComponent::copyComponents(components_dict); for (unsigned int c=0; ccopyComponents(components_dict); } ANNComponent *StackANNComponent::getComponent(string &name) { ANNComponent *component = ANNComponent::getComponent(name); for (unsigned int c=0; cgetComponent(name); return component; } const char *StackANNComponent::luaCtorName() const { return "ann.components.stack"; } int StackANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name.c_str(); t["input"] = getInputSize(); t["output"] = getOutputSize(); AprilUtils::LuaTable c(L); t["components"] = c; for (unsigned int i=0; i components; public: StackANNComponent(const char *name=0, unsigned int input=0, unsigned int output=0); virtual ~StackANNComponent(); /// Method to push a new component at the top of the stack void pushComponent(ANNComponent *component); /// Returns the component at the top of the stack ANNComponent *topComponent(); /// Removes the component at the top of the stack void popComponent(); /// Returns the component at the given index ANNComponent *getComponentAt(unsigned int i) { return components[i]; } /// Returns the component at the given index const ANNComponent *getComponentAt(unsigned int i) const { return components[i]; } virtual void precomputeOutputSize(const AprilUtils::vector &input_size, AprilUtils::vector &output_size) { AprilUtils::vector aux(input_size); if (getOutputSize()>0) output_size.push_back(getOutputSize()); else { for (unsigned int i=0; iprecomputeOutputSize(aux, output_size); aux.swap(output_size); } aux.swap(output_size); } } virtual Basics::Token *getInput(); virtual Basics::Token *getOutput(); virtual Basics::Token *getErrorInput(); virtual Basics::Token *getErrorOutput(); virtual void setInput(Basics::Token *tk) { components[0]->setInput(tk); } virtual void setOutput(Basics::Token *tk) { components.back()->setOutput(tk); } virtual void setErrorInput(Basics::Token *tk) { components[0]->setErrorInput(tk); } virtual void setErrorOutput(Basics::Token *tk) { components.back()->setErrorOutput(tk); } virtual void copyState(AprilUtils::LuaTable &dict) { ANNComponent::copyState(dict); for (unsigned int i=0; icopyState(dict); } } virtual void setState(AprilUtils::LuaTable &dict) { ANNComponent::setState(dict); for (unsigned int i=0; isetState(dict); } } virtual Basics::Token *doForward(Basics::Token* input, bool during_training); virtual Basics::Token *doBackprop(Basics::Token *input_error); virtual void reset(unsigned int it=0); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual void setUseCuda(bool v); virtual void build(unsigned int input_size, unsigned int output_size, AprilUtils::LuaTable &weights_dict, AprilUtils::LuaTable &components_dict); virtual void copyWeights(AprilUtils::LuaTable &weights_dict); virtual void copyComponents(AprilUtils::LuaTable &components_dict); virtual ANNComponent *getComponent(AprilUtils::string &name); virtual void computeAllGradients(AprilUtils::LuaTable &weight_grads_dict); virtual void debugInfo() { ANNComponent::debugInfo(); for (unsigned int i=0; idebugInfo(); } } unsigned int size() { return components.size(); } virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // STACKCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/stochastic_component.h000066400000000000000000000075131263004425400242010ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef STOCHASTICCOMPONENT_H #define STOCHASTICCOMPONENT_H #include "april_assert.h" #include "ann_component.h" #include "MersenneTwister.h" #include "vector.h" namespace ANN { /// This class is a base class for stochastic components. It contains a random /// MTRand object and other properties in order to produce random numbers. The /// sequence of random numbers could be stored to repeat it several times. For /// this purpose, the reset method receives an iteration number. So, in the /// first iteration (number 0), the object stores the sequence of random /// objects. In the following iterations, this sequence is repeated. class StochasticANNComponent : public ANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(StochasticANNComponent); enum StochasticState { NORMAL = 0, KEEP = 1, FROZEN = 2 }; StochasticState stochastic_state; unsigned int last_reset_it; uint32_t *random_frozen_state; protected: Basics::MTRand *random; public: StochasticANNComponent(Basics::MTRand *random, const char *name=0, const char *weights=0, unsigned int input_size=0, unsigned int output_size=0) : ANNComponent(name, weights, input_size, output_size), stochastic_state(NORMAL), last_reset_it(0), random(random) { april_assert(random != 0 && "Needs a random object\n"); IncRef(random); random_frozen_state = new uint32_t[Basics::MTRand::SAVE]; } virtual ~StochasticANNComponent() { DecRef(random); delete[] random_frozen_state; } virtual Basics::Token *doForward(Basics::Token* input, bool during_training) { if (!during_training) stochastic_state = NORMAL; return input; } virtual void reset(unsigned int it=0) { if (it == 0) { // first iteration, goes to KEEP state switch(stochastic_state) { case FROZEN: case NORMAL: stochastic_state = KEEP; random->save(random_frozen_state); break; default: ; } } else if (it != last_reset_it) { // iteration change, reinitialize the store sequence position pointer // and goes to FROZEN state stochastic_state = FROZEN; random->load(random_frozen_state); } last_reset_it = it; } /// Method to restore previously serialized random object virtual void setRandom(Basics::MTRand *random) { DecRef(this->random); this->random = random; IncRef(this->random); last_reset_it = 0; } /// Method to serialize the underlying random object virtual Basics::MTRand *getRandom() { return random; } /// Method to serialize the underlying random object virtual const Basics::MTRand *getRandom() const { return random; } /* virtual void copyState(AprilUtils::LuaTable &dict) { } virtual void setState(AprilUtils::LuaTable &dict) { } */ // virtual const char *luaCtorName() const; // virtual int exportParamsToLua(lua_State *L); }; } #endif // STOCHASTICCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/tanh_actf_component.cc000066400000000000000000000040071263004425400241150ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "activation_function_kernels.h" #include "cblas_headers.h" #include "tanh_actf_component.h" #include "unused_variable.h" using namespace AprilMath; using namespace AprilMath::MatrixExt::Operations; using namespace AprilUtils; using namespace Basics; namespace ANN { TanhActfANNComponent::TanhActfANNComponent(const char *name) : ActivationFunctionANNComponent(name) { } TanhActfANNComponent::~TanhActfANNComponent() { } void TanhActfANNComponent::applyActivation(MatrixFloat *input_units, MatrixFloat *output_units) { Kernels::applyTanh(output_units, input_units); } void TanhActfANNComponent::multiplyDerivatives(MatrixFloat *input_units, MatrixFloat *output_units, MatrixFloat *input_errors, MatrixFloat *output_errors) { UNUSED_VARIABLE(input_units); Kernels::applyTanhDerivative(output_errors, output_units); matCmul(output_errors, input_errors); } ANNComponent *TanhActfANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); TanhActfANNComponent *obj = new TanhActfANNComponent(name.c_str()); return obj; } const char *TanhActfANNComponent::luaCtorName() const { return "ann.components.actf.tanh"; } } april-ann-0.4.1/packages/ann/ann/c_src/tanh_actf_component.h000066400000000000000000000035521263004425400237630ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef TANHACTFCOMPONENT_H #define TANHACTFCOMPONENT_H #include "activation_function_component.h" #include "ann_component.h" #include "gpu_mirrored_memory_block.h" namespace ANN { /// ANN component which computes TANH activation function class TanhActfANNComponent : public ActivationFunctionANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(TanhActfANNComponent); protected: virtual void applyActivation(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units); virtual void multiplyDerivatives(Basics::MatrixFloat *input_units, Basics::MatrixFloat *output_units, Basics::MatrixFloat *input_errors, Basics::MatrixFloat *output_errors); public: TanhActfANNComponent(const char *name); virtual ~TanhActfANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual const char *luaCtorName() const; // virtual int exportParamsToLua(lua_State *L); }; } #endif // TANHACTFCOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/transpose_component.cc000066400000000000000000000072161263004425400242110ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2015, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "error_print.h" #include "table_of_token_codes.h" #include "token_vector.h" #include "token_matrix.h" #include "transpose_component.h" using namespace Basics; using namespace AprilUtils; using namespace AprilMath; namespace ANN { TransposeANNComponent::TransposeANNComponent(const int *which, const char *name) : VirtualMatrixANNComponent(name, 0, 0, 0) { if (which != 0) { this->which = new int[2]; this->which[0] = which[0]; this->which[1] = which[1]; } } TransposeANNComponent::~TransposeANNComponent() { } MatrixFloat *TransposeANNComponent:: transposeBunch(MatrixFloat *input_mat) const { const int N = input_mat->getNumDim(); AprilUtils::UniquePtr dims( new int[N] ); dims[0] = input_mat->getDimSize(0); if (!which.empty()) { for (int i=1; igetDimSize(i); } AprilUtils::swap(dims[which[0]+1], dims[which[1]+1]); } else { for (int i=1; igetDimSize(N - i); } } MatrixFloat *output_mat = new MatrixFloat(N, dims.get()); AprilUtils::SharedPtr output_row; AprilUtils::SharedPtr input_row; for(int i=0; iselect(0, i, output_row.get()); input_row = input_mat->select(0, i, input_row.get()); AprilUtils::UniquePtr input_row_T; if (!which.empty()) { input_row_T = input_row->transpose(which[0], which[1]); } else { input_row_T = input_row->transpose(); } AprilMath::MatrixExt::BLAS:: matCopy(output_row.get(), input_row_T.get()); } return output_mat; } MatrixFloat *TransposeANNComponent:: privateDoForward(MatrixFloat* input_mat, bool during_training) { UNUSED_VARIABLE(during_training); return transposeBunch(input_mat); } MatrixFloat *TransposeANNComponent:: privateDoBackprop(MatrixFloat *error_input_mat) { return transposeBunch(error_input_mat); } void TransposeANNComponent::privateReset(unsigned int it) { UNUSED_VARIABLE(it); } ANNComponent *TransposeANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); TransposeANNComponent *transpose_component = new TransposeANNComponent(which.get(), name.c_str()); return transpose_component; } const char *TransposeANNComponent::luaCtorName() const { return "ann.components.transpose"; } int TransposeANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name.c_str(); if (!which.empty()) { AprilUtils::LuaTable dims(L); t["dims"] = dims; dims[1] = which[0]+1; dims[2] = which[1]+1; } t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/transpose_component.h000066400000000000000000000043031263004425400240450ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2015, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef TRANSPOSECOMPONENT_H #define TRANSPOSECOMPONENT_H #include "unused_variable.h" #include "vector.h" #include "matrix_component.h" #include "token_vector.h" #include "token_matrix.h" namespace ANN { /// This component modifies the input matrix to be reinterpreted as the given /// dimension sizes array. If the input matrix is not contiguous in memory, it /// will be cloned. If it is contiguous, the output of this component is a /// reinterpretation of input matrix, but the memory pointer will be shared. class TransposeANNComponent : public VirtualMatrixANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(TransposeANNComponent); virtual Basics::MatrixFloat *privateDoForward(Basics::MatrixFloat* input, bool during_training); virtual Basics::MatrixFloat *privateDoBackprop(Basics::MatrixFloat *input_error); virtual void privateReset(unsigned int it=0); Basics::MatrixFloat *transposeBunch(Basics::MatrixFloat *input) const; AprilUtils::UniquePtr which; public: TransposeANNComponent(const int *which=0, const char *name=0); virtual ~TransposeANNComponent(); virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // TRANSPOSECOMPONENT_H april-ann-0.4.1/packages/ann/ann/c_src/zca_whitening_component.cc000066400000000000000000000062361263004425400250250ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "error_print.h" #include "table_of_token_codes.h" #include "token_vector.h" #include "token_matrix.h" #include "zca_whitening_component.h" #include "utilMatrixFloat.h" using namespace AprilIO; using namespace AprilMath; using namespace AprilMath::MatrixExt::Operations; using namespace AprilUtils; using namespace Basics; #define WEIGHTS_NAME "U" namespace ANN { ZCAWhiteningANNComponent::ZCAWhiteningANNComponent(MatrixFloat *U, SparseMatrixFloat *S, float epsilon, unsigned int takeN, const char *name) : PCAWhiteningANNComponent(U,S,epsilon,takeN,name), dot_product_decoder(0, WEIGHTS_NAME, getOutputSize(), getInputSize(), false) { output_size = input_size; MatrixFloat *aux_U = U; if (takeN != 0) { int coords[2] = { 0,0 }; int sizes[2] = { U->getDimSize(0), static_cast(takeN) }; aux_U = new MatrixFloat(this->U, coords, sizes, true); } matrix_set.put(WEIGHTS_NAME, aux_U); AprilUtils::LuaTable components_dict; dot_product_decoder.build(0, 0, matrix_set, components_dict); // avoid problems with DecRef in LuaTable IncRef(&dot_product_decoder); } ZCAWhiteningANNComponent::~ZCAWhiteningANNComponent() { } Token *ZCAWhiteningANNComponent::doForward(Token* _input, bool during_training) { Token *rotated = PCAWhiteningANNComponent::doForward(_input, during_training); return dot_product_decoder.doForward(rotated, during_training); } Token *ZCAWhiteningANNComponent::doBackprop(Token *_error_input) { Token *rotated_error = dot_product_decoder.doBackprop(_error_input); return PCAWhiteningANNComponent::doBackprop(rotated_error); } ANNComponent *ZCAWhiteningANNComponent::clone(AprilUtils::LuaTable &copies) { UNUSED_VARIABLE(copies); ZCAWhiteningANNComponent *component = new ZCAWhiteningANNComponent(U, S, epsilon, takeN, name.c_str()); return component; } const char *ZCAWhiteningANNComponent::luaCtorName() const { return "ann.components.zca_whitening"; } int ZCAWhiteningANNComponent::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); t["name"] = name.c_str(); t["U"] = U; t["S"] = S; t["epsilon"] = epsilon; t["takeN"] = takeN; t.pushTable(L); return 1; } } april-ann-0.4.1/packages/ann/ann/c_src/zca_whitening_component.h000066400000000000000000000060271263004425400246650ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef ZCAWHITENINGCOMPONENT_H #define ZCAWHITENINGCOMPONENT_H #include "sparse_matrixFloat.h" #include "matrixFloat.h" #include "vector.h" #include "ann_component.h" #include "token_vector.h" #include "token_matrix.h" #include "pca_whitening_component.h" #include "dot_product_component.h" namespace ANN { class ZCAWhiteningANNComponent : public PCAWhiteningANNComponent { APRIL_DISALLOW_COPY_AND_ASSIGN(ZCAWhiteningANNComponent); DotProductANNComponent dot_product_decoder; //< Applies the reconstruction from PCA rotated data public: ZCAWhiteningANNComponent(Basics::MatrixFloat *U, Basics::SparseMatrixFloat *S, float epsilon=0.0f, unsigned int takeN=0, const char *name=0); virtual ~ZCAWhiteningANNComponent(); virtual Basics::Token *doForward(Basics::Token* input, bool during_training); virtual Basics::Token *doBackprop(Basics::Token *input_error); virtual Basics::Token *getInput() { return PCAWhiteningANNComponent::getInput(); } virtual Basics::Token *getOutput() { return dot_product_decoder.getOutput(); } virtual Basics::Token *getErrorInput() { return dot_product_decoder.getErrorInput(); } virtual Basics::Token *getErrorOutput() { return PCAWhiteningANNComponent::getErrorOutput(); } // virtual void setInput(Basics::Token *tk) { PCAWhiteningANNComponent::setInput(tk); } virtual void setOutput(Basics::Token *tk) { dot_product_decoder.setOutput(tk); } virtual void setErrorInput(Basics::Token *tk) { dot_product_decoder.setErrorInput(tk); } virtual void setErrorOutput(Basics::Token *tk) { PCAWhiteningANNComponent::setErrorOutput(tk); } // FIXME: Is it needd an implementation of copyState and setState? /* virtual void copyState(AprilUtils::LuaTable &dict) { dot_product->copyState(dict); bias->copyState(dict); } virtual void setState(AprilUtils::LuaTable &dict) { dot_product->setState(dict); bias->setState(dict); } */ virtual ANNComponent *clone(AprilUtils::LuaTable &copies); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // ZCAWHITENINGCOMPONENT_H april-ann-0.4.1/packages/ann/ann/lua_src/000077500000000000000000000000001263004425400201335ustar00rootroot00000000000000april-ann-0.4.1/packages/ann/ann/lua_src/annbase.lua000066400000000000000000001604441263004425400222560ustar00rootroot00000000000000get_table_from_dotted_string("ann.mlp.all_all", true) get_table_from_dotted_string("ann.components", true) ---------------------------------------------------------------------- class.extend(ann.components.base, "get_is_recurrent", function() return false end) ---------------------------------------------------------------------- ann.components.batchnorm = function(t) local params = get_table_fields( { affine = { type_match="boolean", default=true }, alpha = { type_match="number" }, bias_name = { type_match="string" }, bias_weights = { type_match="string" }, epsilon = { type_match="number" }, mul_name = { type_match="string" }, mul_weights = { type_match="string" }, name = { type_match="string" }, size = { type_match="number" }, mean = { isa_match=matrix }, inv_std = { isa_match=matrix }, }, t) local component = ann.components.batch_standardization{ name = params.name, epsilon = params.epsilon, alpha = params.alpha, mean = params.mean, inv_std = params.inv_std, } if params.affine then local mat local stack = ann.components.stack() stack:push( component ) stack:push( ann.components.mul{ name = params.mul_name, size = params.size, weights = params.mul_weights, matrix = mat, } ) stack:push( ann.components.bias{ name = params.bias_name, size = params.size, weights = params.bias_weights, } ) component = stack end return component end ---------------------------------------------------------------------- ann.components.const_mul = function(t) local params = get_table_fields( { data = { mandatory=true }, weights = { type_match="string" }, name = { type_match="string" }, }, t) local m = params.data params.data = nil if tonumber(m) then m = matrix{ m } elseif type(m) == "table" then m = matrix(m) else assert(class.is_a(m, matrix), "Needs a matrix, table or number in 'data' field") end assert(m:num_dim() == 1, "Needs a one-dimensional matrix") params.scalar = (m:size() == 1) if not params.scalar then params.size = m:size() end local c = ann.components.mul(params) local wname = c:get_weights_name() c:build{ weights = { [wname] = m } } local const_name = c:get_name() .. "_const" return ann.components.const{ component = c, name = const_name } end ---------------------------------------------------------------------- ann.components.left_probabilistic_matrix = function(t) t.side = "left" return ann.components.probabilistic_matrix(t) end ann.components.right_probabilistic_matrix = function(t) t.side = "right" return ann.components.probabilistic_matrix(t) end ---------------------------------------------------------------------- local ann_wrapper, ann_wrapper_methods = class("ann.components.wrapper") ann.components.wrapper = ann_wrapper -- global environment function ann_wrapper:constructor(t) local params = get_table_fields( { input = { mandatory = true, type_match="number", default=0 }, output = { mandatory = true, type_match="number", default=0 }, weights = { mandatory = true }, forward = { mandatory = true, type_match="function" }, backprop = { mandatory = false, type_match="function" }, compute_gradients = { mandatory=false, type_match="function" }, reset = { mandatory=false, type_match="function" }, state = { mandatory=false }, }, t) self.forward_function = params.forward self.backprop_function = params.backprop or function() error"Not implemented for THIS wrapper component" end self.compute_gradients_function = params.compute_gradients or function() error"Not implemented for THIS wrapper component" end self.reset_function = params.reset or function() end self.input = params.input self.output = params.output self.weights = params.weights self.state = params.state end function ann_wrapper_methods:has_weights_name() return false end function ann_wrapper_methods:get_is_built() return true end function ann_wrapper_methods:debug_info() end function ann_wrapper_methods:copy_state(tbl) error("Not implemented") end function ann_wrapper_methods:set_state(tbl) error("Not implemented") end function ann_wrapper_methods:get_input_size() return self.input_size end function ann_wrapper_methods:get_output_size() return self.output_size end function ann_wrapper_methods:get_input() return self.input end function ann_wrapper_methods:get_output() return self.output end function ann_wrapper_methods:get_error_input() return self.input end function ann_wrapper_methods:get_error_output() return self.output end function ann_wrapper_methods:forward(input, during_training) self:reset() self.input = input self.output = self:forward_function(input, during_training) return self.output end function ann_wrapper_methods:backprop(input) self.error_input = input self.error_output = self:backprop_function(input) return self.error_output end function ann_wrapper_methods:reset(n) self:reset_function(n) self.input = nil self.output = nil self.error_input = nil self.error_output = nil end function ann_wrapper_methods:compute_gradients(dict) local dict = dict or {} self:compute_gradients_function(dict) return dict end function ann_wrapper_methods:build(params) params = params or {} local input,output,weights = params.input,params.output,params.weights -- TODO: check input/output sizes if params.weights then matrix.dict.replace( self.weights, params.weights ) end return self,self.weights,{} end function ann_wrapper_methods:copy_weights() return self.weights end function ann_wrapper_methods:copy_components() return {} end function ann_wrapper_methods:ctor_name() error("Impossible to serialize a wrapper component") end function ann_wrapper_methods:ctor_params() error("Impossible to serialize a wrapper component") end function ann_wrapper_methods:get_name() error("Not implemented in wrapper component") end function ann_wrapper_methods:get_weights_name() error("Not implemented in wrapper component") end function ann_wrapper_methods:precompute_output_size() error("Not implemented in wrapper component") end function ann_wrapper_methods:clone() error("Not implemented in wrapper component") end function ann_wrapper_methods:set_use_cuda() error("Not implemented in wrapper component") end function ann_wrapper_methods:get_use_cuda() error("Not implemented in wrapper component") end function ann_wrapper_methods:get_component(name) error("Not implemented in wrapper component") end ---------------------------------------------------------------------- local lua_component_methods ann.components.lua,lua_component_methods = class("ann.components.lua", ann.components.base) ann.components.lua.constructor = function(self, tbl) local tbl = get_table_fields({ name = { type_match="string" }, input = { type_match="number" }, output = { type_match="number" }, }, tbl or {}) self.name = tbl.name or ann.generate_name() self.input_size = tbl.input self.output_size = tbl.output end lua_component_methods.ctor_name = function(self) return class.obj_id(self) end lua_component_methods.ctor_params = function(self) return { name=self.name, input=self.input_size, output=self.output_size } end lua_component_methods.set_input = function(self,tk) self.input_token = tk end lua_component_methods.set_output = function(self,tk) self.output_token = tk end lua_component_methods.set_error_input = function(self,tk) self.error_input_token = tk end lua_component_methods.set_error_output = function(self,tk) self.error_output_token = tk end lua_component_methods.build = function(self,tbl) tbl = tbl or {} self.is_built = true local input_size,output_size if tbl.input and tbl.input ~= 0 then input_size = tbl.input end if tbl.output and tbl.output ~= 0 then output_size = tbl.output end local self_input_size = rawget(self,"input_size") local self_output_size = rawget(self,"output_size") self.input_size = input_size or self_input_size self.output_size = output_size or self_output_size return self,tbl.weights or {},{ [self.name] = self } end lua_component_methods.forward = function(self, input, during_training) assert(rawget(self,"is_built"), "It is needed to call build method") self.input_token = input self.output_token = input return input end lua_component_methods.backprop = function(self, input) assert(rawget(self,"is_built"), "It is needed to call build method") assert(rawget(self,"output_token"), "It is needed to call forward method") self.error_input_token = input self.error_output_token = input return input end lua_component_methods.compute_gradients = function(self, weight_grads) assert(rawget(self,"is_built"), "It is needed to call build method") assert(rawget(self,"output_token"), "It is needed to call forward method") assert(rawget(self,"error_output_token"), "It is needed to call backprop method") return weight_grads or {} end lua_component_methods.reset = function(self, n) self.input_token = nil self.output_token = nil self.error_input_token = nil self.error_output_token = nil end lua_component_methods.get_name = function(self) return self.name end lua_component_methods.get_weights_name = function(self) return nil end lua_component_methods.has_weights_name = function(self) return false end lua_component_methods.get_is_built = function(self) return rawget(self,"is_built") or false end lua_component_methods.debug_info = function(self) error("Not implemented") end lua_component_methods.copy_state = function(self, tbl) tbl = tbl or {} tbl[self.name] = { input = self:get_input(), output = self:get_output(), error_input = self:get_error_input(), error_output = self:get_error_output(), } return tbl end lua_component_methods.set_state = function(self, tbl) local tbl = april_assert(tbl[self.name], "State %s not found", self.name) self.input = tbl.input self.output = tbl.output self.error_input = tbl.input self.error_output = tbl.output return self end lua_component_methods.get_input_size = function(self) return rawget(self,"input_size") or 0 end lua_component_methods.get_output_size = function(self) return rawget(self,"output_size") or 0 end lua_component_methods.get_input = function(self) return rawget(self,"input_token") or tokens.null() end lua_component_methods.get_output = function(self) return rawget(self,"output_token") or tokens.null() end lua_component_methods.get_error_input = function(self) return rawget(self,"error_input_token") or tokens.null() end lua_component_methods.get_error_output = function(self) return rawget(self,"error_output_token") or tokens.null() end lua_component_methods.precompute_output_size = function(self, tbl) error("Not implemented") end lua_component_methods.clone = function(self) return class.of(self){ name=self.name, input=self:get_input_size(), output=self:get_output_size() } end lua_component_methods.set_use_cuda = function(self, v) self.use_cuda = v end lua_component_methods.get_use_cuda = function(self) return rawget(self,"use_cuda") or false end lua_component_methods.copy_weights = function(self, dict) return dict or {} end lua_component_methods.copy_components = function(self, dict) local dict = dict or {} dict[self.name] = self return dict end lua_component_methods.get_component = function(self, name) if self.name == name then return self end end ---------------------------------------------------------------------- function ann.connections.input_filters_image(w, shape, options) local params = get_table_fields({ margin = { type_match="number", mandatory=false, default=1 }, bgcolor = { type_match="number", mandatory=false, default=0 }, rows = { type_match="number", mandatory=false }, cols = { type_match="number", mandatory=false }, }, options) local notranspose = false assert(type(shape) == "table", "Needs a shape table as 2nd argument") assert(#shape == 2 or #shape == 3, "Expected shape with 2 or 3 dimensions") assert(#shape == 2 or shape[3] == 3, "Expected 3 components at the 3rd dimension (color RGB)") assert(shape[1] and shape[2], "Found nil values in shape (2nd argument)") local margin = params.margin local bgcolor = params.bgcolor local R = math.ceil(math.sqrt(w:dim(1))) local C = math.floor(math.sqrt(w:dim(1))) if params.rows then R = params.rows if params.cols then C = params.cols assert(R*C == w:dim(1), "Incorrect number of rows and cols") else C = math.ceil(w:dim(1)/R) end elseif params.cols then C = params.cols R = math.ceil(w:dim(1)/C) end local result = matrix(R*(shape[1]+margin)-margin,C*(shape[2]+margin)-margin,shape[3]) result:fill(bgcolor) local neuron_weights local step = { shape[1]+margin, shape[2]+margin } if #shape == 3 then step[3] = 1 end local result_sw = result:sliding_window{ size=shape, step=step } local result_m assert(shape[1]*shape[2]*(shape[3] or 1) == w:dim(2), "Incorrect shape dimensions") for i=1,w:dim(1) do result_m = result_sw:get_matrix(result_m) neuron_weights = w:select(1,i,neuron_weights) local normalized = neuron_weights:clone(): rewrap(table.unpack(shape)):clone(): scal(1/neuron_weights:norm2()): adjust_range(0,1) result_m:copy(normalized) -- result_sw:next() end if #shape == 2 then return Image(result) else return ImageRGB(result) end end ---------------------------------------------------------------------- ann.save = function() error("Not available, use util.serialize instead") end ann.load = util.deserialize ---------------------------------------------------------------------- april_set_doc(ann.mlp, { class="namespace", summary="Namespace with utilties for easy MLP training", }) ---------------------------------------------------------------------- april_set_doc(ann.mlp.all_all, { class="namespace", summary="Namespace with utilities for all-all MLP training", }) ---------------------------------------------------------------------- ann.mlp.all_all.generate = april_doc { class="function", summary="Function to build all-all stacked ANN models", description= { "This function composes a component object from the", "given topology description (stacked all-all).", "It generates default names for components and connection", "weights. Each layer has one ann.components.dot_product", "with name=PREFIX..'w'..NUMBER and", "weights_name=PREFIX..'w'..NUMBER,", "one ann.components.bias with name='b'..NUMBER and", "weights_name=PREFIX..'b'..NUMBER, and an", "ann.components.actf with", "name=PREFIX..'actf'..NUMBER.", "NUMBER is a counter initialized at 1, or with the", "value of second argument (count) for", "ann.mlp.all_all(topology, count) if it is given.", "PREFIX is the third argument of the function, by default", "is an empty string.", }, params= { { "Topology description string as ", "'1024 inputs 128 logistc 10 log_softmax" }, { "A table with extra arguments. Positional arguments are given as", "parameters designed by #n in topology options string. Besides,", "first_count and names_prefix keys can be given.", }, }, outputs= { {"A component object with the specified ", "neural network topology" } } } .. function(topology, tbl, first_count, names_prefix) if type(tbl) == "table" then assert(not first_count and not names_prefix) first_count, names_prefix = tbl.first_count, tbl.names_prefix else -- for back compatibility, it will be deprecated first_count, names_prefix = tbl, first_count end local first_count = tonumber(first_count or 1) local names_prefix = names_prefix or "" local thenet local name = "layer" local count = first_count local prev_size local names_order = {} -- RECURSIVE DESCENT PARSER -- reads a token which can be any string and symbols of {}= local tokenizer = coroutine.wrap(function() local last = 1 for i=1,#topology do local c = topology:sub(i,i) if c:find("[%s%c,]") then if last < i then coroutine.yield(topology:sub(last,i-1)) end last = i+1 else -- if c is space or special then ... else if c:find("[{}=]") then if last < i then coroutine.yield(topology:sub(last,i-1)) end coroutine.yield(c) last = i+1 end -- if c in [{}=] end -- if c is space or special then ... else ... end end -- for i=1,#topology if last < #topology then coroutine.yield(topology:sub(last)) end end) -- coroutine.wrap(function() -- reads a sequence of options delimited by braces local function read_options(safe_tokenizer, params) local options = {} repeat local tk = safe_tokenizer() if tk ~= "}" then local key = tk assert(safe_tokenizer() == "=", "Incorrect topology string") local value = safe_tokenizer() if value:sub(1,1) == "#" then value = params[tonumber(value:sub(2))] end if value == "true" then value = true elseif value == "false" then value = false else value = tonumber(value) or value end options[key] = value end until tk == "}" return options end -- reads ANN components from the topology string and push them into the -- stacked model local function read_component(tk0, tokenizer, params) local safe_tokenizer = function() return assert(tokenizer(), "Incorrect topology string") end local n0 = tonumber(tk0) local kind = tk0 local options = {} if n0 then kind = safe_tokenizer() end tk0 = tokenizer() if tk0 == "{" then -- the string contains options for current component options = read_options(safe_tokenizer, params) tk0 = tokenizer() end -- push the corresponding components if kind ~= "inputs" then assert(thenet, "'inputs' string is required") if n0 then -- hyperplane + activation function local size = n0 thenet:push( ann.components.hyperplane{ input=prev_size, output=size, bias_weights=names_prefix.."b" .. count, dot_product_weights=names_prefix.."w" .. count, name=names_prefix.."layer" .. count, bias_name=names_prefix.."b" .. count, dot_product_name=names_prefix.."w" .. count } ) table.insert(names_order, names_prefix.."b"..count) table.insert(names_order, names_prefix.."w"..count) local ctor = ann.components.actf[kind] or ann.components[kind] assert(ctor, "Incorrect component class: " .. kind) options.name = names_prefix .. "actf" .. count thenet:push( ctor( options ) ) else -- any other kind of component options.name = names_prefix .. "component" .. count local ctor = ann.components[kind] or ann.components.actf[kind] if ctor == assert( ann.components.batchnorm ) then options.bias_weights = options.bias_weights or names_prefix.."b"..count options.bias_name = options.bias_name or names_prefix.."b"..count options.mul_weights = options.mul_weights or names_prefix.."m"..count options.mul_name = options.mul_name or names_prefix.."m"..count end assert(ctor, "Incorrect component class: " .. kind) thenet:push( ctor( options ) ) end count = count + 1 else -- if kind ~= "inputs" thenet = ann.components.stack{ name=names_prefix.."stack", input=n0 } end prev_size = n0 or prev_size return tk0 end -- main loop of the parser local tk0,component = tokenizer(),nil while tk0 do tk0 = read_component(tk0, tokenizer, tbl) end -- local aux = get_lua_properties_table(thenet) aux.description = topology aux.first_count = first_count aux.names_prefix = names_prefix aux.names_order = names_order return thenet end ------------------------------------------------------------------- function ann.mlp.all_all.save(model, filename, mode, old) error("DEPRECATED: this method is deprecated, please use standard ANN ".. "components and trainable.supervised_trainer objects") end ------------------------------------------------------------------- ann.mlp.all_all.load = april_doc{ class="function", summary="Loads an all-all stacked ANN model", description={ "This function loads an all-all ANN model. It only works", "with models generated via ann.mlp.all_all.generate", "function.", }, params= { { "A filename string" }, }, outputs = { "An all-all ANN model" } } .. -- this function is for retro-compatibility function(filename) fprintf(io.stderr, "DEPRECATED: this method is deprecated, please use standard ANN ".. "components and trainable.supervised_trainer objects\n") local c = loadfile(filename) local data = c() local model = ann.mlp.all_all.generate(data[1], data.first_count, data.prefix) local w = data[2] local oldw = data[3] or w local _,weights_table,_ = model:build() local names_order = get_lua_properties_table(model).names_order local pos = 0 for i=1,#names_order,2 do local bname = names_order[i] local wname = names_order[i+1] local bias = weights_table[bname] local weights = weights_table[wname] local colsize = ann.connections.get_input_size(weights) + 1 ann.connections.load(bias, { w=w, oldw=oldw, first_pos=pos, column_size=colsize }) pos = ann.connections.load(weights, { w=w, oldw=oldw, first_pos=pos+1, column_size=colsize }) - 1 end return model end --------------------------- -- BINDING DOCUMENTATION -- --------------------------- april_set_doc(ann, { class="namespace", summary="Namespace which contains all ANN related classes", }) ------------------------------------------------------------------- april_set_doc(ann.connections, { class="namespace", summary="Connections namespace, stores helper functions", }) ------------------------------------------------------------------- april_set_doc(ann.connections.input_filters_image, { class="function", summary="Builds an image with the filters in the given weights matrix", params={ { "The weights matrix" }, { "The shape of the inputs, a table with 2 or 3 components" }, { "The margin between each filter [optional], by default it is 1" }, { "No transpose [optional], by default it is nil" }, }, outputs={ "A squared image (instance of Image) containing all the filters", } }) ------------------------------------------------------------------- april_set_doc(ann.connections, { class="function", summary="Builds a matrix for connections", description= { "The constructor reserves memory for the given input and", "output sizes. The weights are in row-major from the outside,", "but internally they are stored in col-major order.", }, params={ ["input"] = "Input size (number of rows).", ["output"] = "Output size (number of cols).", }, outputs = { "An instance of ann.connections" } }) april_set_doc(ann.connections, { class="function", summary="Builds a matrix for connections", description= { "The constructor reserves memory for the given input and", "output sizes. It loads a matrix with", "weights trained previously, or computed with other", "toolkits. The weights are in row-major from the outside,", "but internally they are stored in col-major order.", }, params={ ["input"] = "Input size (number of rows).", ["output"] = "Output size (number of cols).", ["w"] = "A matrix with enough number of data values.", ["oldw"] = "A matrix used to compute momentum (same size of w) [optional]", ["first_pos"] = "Position of the first weight on the given ".. "matrix w [optional]. By default is 0", ["column_size"] = "Leading size of the weights [optional]. ".. "By default is input" }, outputs = { "An instance of ann.connections" } }) ------------------------------------------------------------------- april_set_doc(ann.connections.randomize_weights, { class="function", summary="Initializes following uniform random distribution: [inf,sup]", params={ "A weights matrix", "A table with fields: random, inf and sup", }, }) ------------------------------------------------------------------- ------------------------------------------------------------------- ------------------------------------------------------------------- april_set_doc(ann.components, { class="namespace", summary="Namespace which all ANN components classes", }) ------------------------------------------------------------------- april_set_doc(ann.components.base, { class="class", summary="ANN component parent class", description= { "ANN components are the blocks used to build neural networks.", "Each block has a name property which serves as unique", "identifier.", "Besides, the property weights_name is a non unique", "identifier of the ann.connections object property of a", "given ann.components object.", "Each component has a number of inputs and a number of", "outputs.", "Components has options (as learning_rate, momentum, ...)", "which modify they behaviour.", "Tokens are the basic data which components interchange.", "Matrix types are a kind of Token, so it is transparent.", "The ANNs are trained following gradient descent algorithm,", "so each component has four main properties: input, output,", "error_input and error_output.", "All classes inside the table ann.components are child of", "this superclass", }, }) ------------------------------------------------------------------- april_set_doc(ann.components.base, { class="method", summary="Constructor", description= { "The base component is a dummy component which implements", "identity function.", "This is the parent class for the rest of components.", }, params = { ["name"] = "The unique identifier of the component ".. "[optional]. By default it is generated automatically.", ["weights"] = "The non unique identifier of its ".. "ann.connections property [optional]. By default is nil.", ["size"] = "Input and output size, are the same [optional]. ".. "By default is 0. This size could be overwritten at ".. "build method.", }, outputs = { "An instance of ann.components.base" } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."precompute_output_size", { class="method", summary="Precomputes the shape of the output (a table)", params = { "A table with the input's shape (a table) [optional]", }, outputs = { "A table with the output's shape", } }) ------------------------------------------------------------------- april_set_doc(ann.components.base.."get_is_built", { class="method", summary="Returns the build state of the object", outputs = { "A boolean with the build state" } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."get_input_size", { class="method", summary="Returns the size INPUT", outputs = { "A number with the size", } }) ------------------------------------------------------------------- april_set_doc(ann.components.base.."get_output_size", { class="method", summary="Returns the size OUTPUT", outputs = { "A number with the size", } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."get_input", { class="method", summary="Returns the token at component input", outputs = { "A token or nil (usually a matrix)", } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."get_output", { class="method", summary="Returns the token at component output", outputs = { "A token or nil (usually a matrix)", } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."get_error_input", { class="method", summary="Returns the token at component error input", description={ "The error input is the gradient incoming from", "next component(s). Note that the error input comes", "in reverse order (from the output)." }, outputs = { "A token or nil (usually a matrix)", } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."get_error_output", { class="method", summary="Returns the token at component error output", description={ "The error output is the gradient going to", "previous component(s). Note that the error output goes", "in reverse order (to the input).", }, outputs = { "A token or nil (usually a matrix)", } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."forward", { class="method", summary="Computes forward step with the given token", params={ "An input token (usually a matrix)", { "A boolean indicating if the forward is during_training or not.", "This information is used by ann.components.actf objects to", "apply dropout during training, and to halve the activation", "during validation (or test). It is [optional], by default", "is false.", } }, outputs = { "An output token (usually a matrix)", } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."backprop", { class="method", summary="Computes gradient step (backprop) with the given error input", description={ "Computes gradient step (backprop) with the given error input.", "This method is only valid after forward." }, params={ "An error input token (usually a matrix)" }, outputs = { "An error output token (usually a matrix)", } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."reset", { class="method", summary="Reset all stored tokens", description={ "This method resets all stored tokens as property of this", "component. Input, output, error input and error output", "tokens are set to nil", }, params = { { "An optional number with the current iteration. It is", "used by iterative algorithms as Conjugate Gradient", "to indicate components current iteration number", "[optional]. By default it is 0", } } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."clone", { class="method", summary="Makes a deep-copy of the component, except connections", description={ "Makes a deep-copy of the component, except connections.", "All component options are cloned, except use_cuda flag.", }, outputs={ "A new instance of ann.components" } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."set_use_cuda", { class="method", summary="Modifies use_cuda flag", description={ "Sets the use_cuda flag. If use_cuda=true then all the", "computation will be done at GPU.", } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."build", { class="method", summary="This method needs to be called after component creation", description={ "Components can be composed in a hierarchy interchanging", "input/output tokens. After components composition, it is", "mandatory to call this method.", "It reserves memory necessary for connections and setup", "auxiliary data structures. Connection weights are not valid", "before calling build. Build methods of components are", "automatically called recursively. A component can be", "built twice, but is mandatory to call reset_connections()", "method before each additional build (or always if doubt).", }, params = { ["input"] = {"Input size of the component [optional]. By", "default it is input size given at constructor."}, ["output"] = {"Output size of the component [optional]. By", "default it is output size given at constructor."}, ["weights"] = {"A dictionary table ", "weights_name=>ann.connections object.", "If the corresponding weights_name is found,", "the connections property of the", "component is assigned to table value.", "Otherwise, connections property is new reserved", }, }, outputs= { { "The caller ANN component."}, { "A table with all the weights_name=>ann.connections found", "at the components hierarchy."}, { "A table with all the name=>ann.components found", "at the hierarchy."}, } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."debug_info", { class="method", summary="Debug info at screen", }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."copy_weights", { class="method", summary="Returns the dictionary weights_name=>ann.connections", outputs= { { "A matrix table weights_name=>matrix with matrices found", "at the components hierarchy."}, } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."copy_components", { class="method", summary="Returns the dictionary name=>ann.components", outputs= { { "A table with all the name=>ann.components found", "at the components hierarchy."}, } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."get_component", { class="method", summary="Returns the ann.component with the given name property", params={ "An string with the given name" }, outputs= { { "An ann.components which has the given name", "at the components hierarchy."}, } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."get_name", { class="method", summary="Returns the name of this ann.component", outputs= { { "A string with the name."}, } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."get_weights_name", { class="method", summary="Returns the weigths_name of this ann.component", outputs= { { "A string with the weigths_name."}, } }) ---------------------------------------------------------------------- april_set_doc(ann.components.base.."has_weights_name", { class="method", summary="Indicates if this component has connection weights object", outputs= { { "A boolean"}, } }) ------------------------------- -- COMPONENTS -- ------------------------------- april_set_doc(ann.components.dot_product, { class="class", summary="A component which implements output = input x weights", description = { "The dot product component implements a dot product between", "its input and a weights matrix. If the input is a bunch", "(more than one pattern), a matrix-matrix product will be", "done, as many outputs as inputs.", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.dot_product, { class="method", summary="Constructor of the component", description = { "All the paremeters are", "[optional]. Names are generated automatically if non given.", "Sizes are set to zero by default, so will be mandatory to", "indicate the sizes at build method.", }, params={ ["name"] = "A string with the given name [optional]", ["weights"] = { "A string with the weights name, two components with", "the same weights name share the weights matrix [optional]", }, ["input"] = "Number of component input neurons [optional]", ["output"] = "Number of component output neurons [optional]", ["transpose"] = { "Indicates if the matrix is transposed before dot/matrix", "product [optional]. By default is false", } }, outputs= { "An instance of ann.components.dot_product" } }) ---------------------------------------------------------------------- april_set_doc(ann.components.bias, { class="class", summary="A component which implements output = input + bias", description = { "The bias component implements the addition of bias to", "its input. If the input is a bunch", "(more than one pattern), bias is added to all of them,", "producing as many outputs as inputs.", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.bias, { class="method", summary="Constructor of the component", description = { "All the paremeters are", "[optional]. Names are generated automatically if non given.", }, params={ ["name"] = "A string with the given name [optional]", ["weights"] = { "A string with the weights name, two components with", "the same weights name share the weights matrix [optional]", }, ["size"] = "A number with the size [optional]", }, outputs= { "An instance of ann.components.bias" } }) ---------------------------------------------------------------------- april_set_doc(ann.components.hyperplane, { class="class", summary="A component which implements output=input*weigths + bias", description = { "This component is composed by an ann.components.dot_product", "and a ann.components.bias.", "It implements an standard ANN layer computation:", "output = input * weights + bias.", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.hyperplane, { class="method", summary="Constructor of the component", description = { "All the paremeters are", "[optional]. Names are generated automatically if non given.", "Sizes are set to zero by default, so will be mandatory to", "indicate the sizes at build method.", }, params={ ["name"] = "A string with the given name [optional]", ["dot_product_name"] = { "A string with the name for the dot_product", "component [optional]", }, ["bias_name"] = { "A string with the name for the bias", "component [optional]", }, ["dot_product_weights"] = { "A string with the weights name for the dot_product", "component [optional]", }, ["bias_weights"] = { "A string with the weights name for the bias", "component [optional]", }, ["input"] = "Number of component input neurons [optional]", ["output"] = "Number of component output neurons [optional]", ["transpose"] = { "Indicates if the dot_product matrix is transposed", "[optional]. By default is false", } }, outputs= { "An instance of ann.components.hyperplane" } }) ---------------------------------------------------------------------- april_set_doc(ann.components.stack, { class="class", summary="A container component for stack multiple components", description = { "This component is a container composed by several", "stacked components, so the output of one component is the", "input of the next." }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.stack, { class="method", summary="Constructor of the component", description = { "The Name is generated automatically if non given.", }, params={ ["name"] = "A string with the given name [optional]", }, outputs= { "An instance of ann.components.stack" } }) ---------------------------------------------------------------------- april_set_doc(ann.components.stack.."push", { class="method", summary="Pushes a list of components to the stack", params={ "An instance of ann.components.base (or any child class)", "An instance of ann.components.base (or any child class)", "...", "An instance of ann.components.base (or any child class)", }, outputs = { "The caller object" }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.stack.."unroll", { class="method", summary="Returns the list of components of the stack", outputs = { "An instance of ann.components.base", "An instance of ann.components.base", "...", "An instance of ann.components.base", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.stack.."get", { class="method", summary="Returns the components of the stack at the given indexes", params = { "Index of component", "Index of component", "...", "Index of component", }, outputs = { "An instance of ann.components.base", "An instance of ann.components.base", "...", "An instance of ann.components.base", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.stack.."pop", { class="method", summary="Pops the top component of the stack", }) ---------------------------------------------------------------------- april_set_doc(ann.components.stack.."top", { class="method", summary="Returns the top component of the stack", outputs={ "An instance of ann.components.base" }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.join, { class="class", summary="A container component for join multiple components", description = { "This component is a container composed by several", "joined components, so the input is fragmented given each", "fragment to only one component, and the output of every", "component is join to compose a unique output token", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.join, { class="method", summary="Constructor of the component", description = { "The Name is generated automatically if non given.", }, params={ ["name"] = "A string with the given name [optional]", }, outputs= { "An instance of ann.components.join" } }) ---------------------------------------------------------------------- april_set_doc(ann.components.join.."add", { class="method", summary="Adds a component to the join", params={ "An instance of ann.components.base (or any child class)", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.copy, { class="class", summary="A dummy component for copy multiple times its input",}) ---------------------------------------------------------------------- april_set_doc(ann.components.copy, { class="method", summary="Constructor of the component", description = { "The Name is generated automatically if non given.", "Sizes are set to zero by default, so it is mandatory to give", "it at build method if not given at the constructor." }, params={ ["times"] = { "A number indicating how many times the", "input is replicated", }, ["name"] = "A string with the given name [optional]", ["input"] = "Number of component input neurons [optional]", ["output"] = "Number of component output neurons [optional]", }, outputs= { "An instance of ann.components.copy" } }) ---------------------------------------------------------------------- april_set_doc(ann.components.select, { class="class", summary="A component for select operation (see matrix.select)",}) ---------------------------------------------------------------------- april_set_doc(ann.components.select, { class="method", summary="Constructor of the component select (see matrix.select)", description = { "The Name is generated automatically if non given.", }, params={ ["name"] = "A string with the given name [optional]", ["dimension"] = "Number with the selected dimension", ["index"] = "Number with the selected index", }, outputs= { "An instance of ann.components.select" } }) ---------------------------------------------------------------------- april_set_doc(ann.components.rewrap, { class="class", summary="A component for change the dimension of matrix (see matrix.rewrap)",}) ---------------------------------------------------------------------- april_set_doc(ann.components.rewrap, { class="method", summary="Constructor of the component rewrap (see matrix.rewrap)", description = { "The Name is generated automatically if non given.", }, params={ ["name"] = "A string with the given name [optional]", ["size"] = { "A table with the sizes of re-wrapped matrix dimensions.", } }, outputs= { "An instance of ann.components.rewrap" } }) ---------------------------------------------------------------------- april_set_doc(ann.components.slice, { class="class", summary="A component which takes a slice of a matrix (see matrix.slice)",}) ---------------------------------------------------------------------- april_set_doc(ann.components.slice, { class="method", summary="Constructor of the component slice (see matrix.slice)", description = { "The name is generated automatically if non given.", }, params={ ["name"] = "A string with the given name [optional]", ["pos"] = { "A table with the coordinates of the slice.", }, ["size"] = { "A table with the slice size.", } }, outputs= { "An instance of ann.components.slice" } }) ---------------------------------------------------------------------- april_set_doc(ann.components.stochastic, { class="class", summary="An abstract component which implements basic interface of stochastic components",}) april_set_doc(ann.components.stochastic.."get_random", { class="method", summary="Returns the underlying random object", outputs={ "A random object" }, }) april_set_doc(ann.components.stochastic.."set_random", { class="method", summary="Sets the underlying random object", params={ "A random object" }, outputs={ "The caller object" }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.gaussian_noise, { class="class", summary="A component which adds Gaussian noise to data",}) april_set_doc(ann.components.gaussian_noise, { class="method", summary="Constructor of the component", description = { "The Name is generated automatically if non given.", "Size is set to zero by default, so it is mandatory to give", "it at build method if not given at the constructor." }, params={ ["name"] = "A string with the given name [optional]", ["size"] = "A number with the size [optional]", ["mean"] = "Mean of the gaussian noise [optional], by default it is 0", ["var"] = "Variance of the gaussian noise [optional], by default it is 0.1", ["random"] = "Random object instance [optional]", }, outputs= { "An instance of ann.components.gaussian_noise" } }) ---------------------------------------------------------------------- april_set_doc(ann.components.salt_and_pepper, { class="class", summary="A component which adds salt and pepper noise to data",}) april_set_doc(ann.components.salt_and_pepper, { class="method", summary="Constructor of the component", description = { "The Name is generated automatically if non given.", "Size is set to zero by default, so it is mandatory to give", "it at build method if not given at the constructor." }, params={ ["name"] = "A string with the given name [optional]", ["size"] = "A number with the size [optional]", ["prob"] = "Probability of noise [optional], by default it is 0.2", ["zero"] = "Value of ZERO [optional], by default it is 0", ["one"] = "Value of ONE [optional], by default it is 1", ["random"] = "Random object instance [optional]", }, outputs= { "An instance of ann.components.salt_and_pepper" } }) ---------------------------------------------------------------------- april_set_doc(ann.components.dropout, { class="class", summary="A component which adds salt and pepper noise to data",}) april_set_doc(ann.components.dropout, { class="method", summary="Constructor of the component", description = { "The Name is generated automatically if non given.", "Size is set to zero by default, so it is mandatory to give", "it at build method if not given at the constructor." }, params={ ["name"] = "A string with the given name [optional]", ["size"] = "A number with the size [optional]", ["prob"] = "Probability of noise [optional], by default it is 0.5", ["value"] = "Mask value [optional], by default it is 0", ["random"] = "Random object instance [optional]", ["norm"] = "Boolean value indicating if apply normalization when not training [optional] by default it is true", }, outputs= { "An instance of ann.components.dropout" } }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf, { class="namespace", summary="Namespace which contains all activation functions", }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf, { class="class", summary="Abstract class child of ann.components.base", description={ "This class is used as parent of all activation functions.", "Activation functions input/output sizes are equal,", "and they are set depending on previous components", "or at the build method.", "This parent class implements dropout technique to improve", "training of very large neural networks.", "Dropout must be applied ONLY to activation function", "components by using set_option method (other components", "may abort the program with error).", "Dropout is forbidden at OUTPUT activation components, so", "don't set it indiscrimately. It must be applied component", "by component." }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.logistic, { class="class", summary="Logistic (or sigmoid) activation function", }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.logistic, { class="method", summary="Constructor of the component", params={ ["name"] = "The name of the component [optional].", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.tanh, { class="class", summary="Tanh activation function", }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.tanh, { class="method", summary="Constructor of the component", params={ ["name"] = "The name of the component [optional].", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.softsign, { class="class", summary="Softsign activation function", }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.softsign, { class="method", summary="Constructor of the component", params={ ["name"] = "The name of the component [optional].", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.log_logistic, { class="class", summary="Logarithm of logistic activation function", description={ "This activation function only works if the loss function is", "cross-entropy or multi-class cross-entropy", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.log_logistic, { class="method", summary="Constructor of the component", params={ ["name"] = "The name of the component [optional].", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.softmax, { class="class", summary="Softmax activation function", description={ "This activation function is computed over each input", "pattern and ensures that outputs are probabilities." }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.softmax, { class="method", summary="Constructor of the component", params={ ["name"] = "The name of the component [optional].", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.log_softmax, { class="class", summary="Logarithm of softmax activation function", description={ "This activation function is computed over each input", "pattern and ensures that outputs are probabilities.", "It only works with multi-class cross-entropy loss function.", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.log_softmax, { class="method", summary="Constructor of the component", params={ ["name"] = "The name of the component [optional].", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.softplus, { class="class", summary="Softplus activation function", }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.softplus, { class="method", summary="Constructor of the component", params={ ["name"] = "The name of the component [optional].", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.relu, { class="class", summary="Rectifier Linear Unit (ReLU) activation function", }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.relu, { class="method", summary="Constructor of the component", params={ ["name"] = "The name of the component [optional].", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.sin, { class="class", summary="Sin activation function", }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.sin, { class="method", summary="Constructor of the component", params={ ["name"] = "The name of the component [optional].", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.linear, { class="class", summary="Linear activation function", }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.linear, { class="method", summary="Constructor of the component", params={ ["name"] = "The name of the component [optional].", }, }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.hardtanh, { class="class", summary="Hardtanh activation function", }) ---------------------------------------------------------------------- april_set_doc(ann.components.actf.hardtanh, { class="method", summary="Constructor of the component", params={ ["name"] = "The name of the component [optional].", ["inf"] = "The name of the component [optional], by default is -1.0.", ["sup"] = "The name of the component [optional], by default is 1.0.", }, }) april-ann-0.4.1/packages/ann/ann/package.lua000066400000000000000000000025621263004425400206060ustar00rootroot00000000000000 package{ name = "ann", version = "1.0", depends = { "util", "tokens", "random", "matrix", "functions" }, keywords = { "ANN interfaces" }, description = "Define ANNs classes and interfaces", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test.lua", "test/test-components.lua", "test/test-sparse.lua", }, }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_ann_base.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, object{ file = "c_src/*.cu", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_ann_base.lua.cc", dest_dir = "build", } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/ann/ann/test/000077500000000000000000000000001263004425400174625ustar00rootroot00000000000000april-ann-0.4.1/packages/ann/ann/test/digits.png000066400000000000000000000605771263004425400214720ustar00rootroot00000000000000PNG  IHDR@0IaFIDATxڥۖ亪DgUe"f W|N@ vss>ߋ1g@Bm~)ѹ2?':S@&&~|̶OӐR/%ڥOO(KU+`& "r՟zzT_Zo|bjL| X2?ڱZYj_@Up_6CMʇNKwH'HL#$B([6ڈ|so|q[%q;L4{fҊojg;Wri^Y1k0?ro}@`= dV@/ dM&|ˇ{_qStuG[9p˾v[tw6rRv sZ`rxBS ։Q+2nUzQ oH=Od_pXs"R502|=!Ny_| "7 /5Rݲ { 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XPMңٙb5t5+8aCp>HV6 e c54;߇LnlJhjsNlvM(A+JФz`v"bpdЕB)V*g DIg%RC9"Eu 6/G X i@́HA Σq܅OFt#ڈ k !IĚhO Ad㻻72-qL#B"JKMn-e[K T"D$t?<eU\\)J.#aD} k-h1zg]^nL1Dm݂hϑ4IUX݈9SajIQ! r`7z1Zo/$-I܂&ĎWw_&iӣ3|7OBqcOwSnTB~P:H m:TE.(9.孴<{8ͧ*h[#unm|7)i&91mN\8lw9-\Dp^q~!6n΅l49p}yym7N+|?~x߽dyׄjqX\ڋ>wXn ̲dU wݿq߶kyؐRi!Kzmv,&ip<1g'f,3DL݃",GrD&RnAzFg9-"4jPCL!1)IgN , ؓ#ܡδ9b3&{  s.www_;Z@q,-u=2t;#]9zaAL MǘjĉkeMs^ *Q4!ZqDa.mf|nM֭>B~t볻o)-XDV$vIBT%R$ʚ(aHd/>͹ \N', MATRIX, {a,b}, function(self, ...) local a = self.args[1]:eval(...) local b = self.args[2]:eval(...) return a:clone():gt(b):convert_to("float") end, function(self, seed, result) return result end, function(self, dest) local a,b = self.args[1],self.args[2] local str_tbl = { a.var_name, ':clone():gt(', b.var_name, '):convert_to("float")' } dest:write_expr_assign(self.var_name, table.concat(str_tbl, "")) end) if a.dims or b.dims then assert( check_dims(a.dims, b.dims), "Incorrect dimensions" ) s:set_dims(a.dims or b.dims) end return s end, fill = function(a,b) local a,b = coercion(a),coercion(b) local s if b.dtype == SCALAR or b.dtype == CONSTANT then s = gen_op('fill', MATRIX, {a,b}, function(self, ...) local a = self.args[1]:eval(...) local b = self.args[2]:eval(...) assert(type(a) == "matrix") assert(type(b) == "number") return matrix.as(a):fill(b) end, function(self, seed, result) return result end, function(self, dest) local a,b = self.args[1],self.args[2] local str_tbl = { 'matrix.as(', a.var_name, '):fill(', b.var_name, ')' } dest:write_expr_assign(self.var_name, table.concat(str_tbl, "")) end) elseif b.dtype == MATRIX then s = gen_op('fill', MATRIX, {a,b}, function(self, ...) local a = self.args[1]:eval(...) local b = self.args[2]:eval(...) assert(type(a) == "matrix") assert(type(b) == "matrix") local result = matrix.as(a) local sw = result:sliding_window{ size=b:dim(), step=b:dim() } local slice while not sw:is_end() do slice = sw:get_matrix(slice) slice:copy(b) sw:next() end return result end, function(self, seed, result) return result end, function(self, dest) local a,b = self.args[1],self.args[2] dest:write_expr_assign(self.var_name, string.format("matrix.as( %s )", a.var_name)) local sw = gen_var_name() dest:write_expr_assign(sw, string.format("%s:sliding_window{ size=%s:dim(), step=%s:dim() }", self.var_name, b.var_name, b.var_name)) local slice = gen_var_name() dest:write_var(slice) dest:write_expr_block(string.format([[ while not %s:is_end() do %s = %s:get_matrix( %s ) %s:copy( %s ) %s:next() end ]], sw, slice, sw, slice, slice, b.var_name, sw)) end) else error("Not recognized dtype: " .. tostring(b.dtype)) end if a.dims then s:set_dims(a.dims) end return s end, sum = function(a,dim) local a,dim = coercion(a),dim and coercion(dim) local s if not dim then s = gen_op('sum', SCALAR, {a}, function(self, ...) local a = self.args[1]:eval(...) assert(type(a) == "matrix") return a:sum() end, function(self, seed, result) local a = self.args[1] a:diff(autodiff.op.fill(a, seed), result) return result end, function(self, dest) local a = self.args[1] local str_tbl = { a.var_name, ':sum()' } dest:write_expr_assign(self.var_name, table.concat(str_tbl, "")) end) else s = gen_op('sum', MATRIX, {a,dim}, function(self, ...) local a = self.args[1]:eval(...) local dim = self.args[2]:eval(...) assert(type(a) == "matrix") assert(type(dim) == "number") return a:sum(dim) end, function(self, seed, result) local a,dim = self.args[1],self.args[2] a:diff(autodiff.op.fill(a, seed), result) return result end, function(self, dest) local a,dim = self.args[1],self.args[2] local str_tbl = { a.var_name, ':sum(', dim.var_name, ')' } dest:write_expr_assign(self.var_name, table.concat(str_tbl, "")) end) end return s end, select = function(a,dim,value) local a,dim,value = coercion(a),coercion(dim),coercion(value) local s = gen_op('select', MATRIX, {a,dim,value}, function(self, ...) local a = self.args[1]:eval(...) local dim = self.args[2]:eval(...) local value = self.args[3]:eval(...) assert(type(a) == "matrix") return a:select(dim,value) end, function(self, seed, result) error("NOT IMPLEMENTED") end, function(self, dest) local a = self.args[1] local dim = self.args[2] local value = self.args[3] local str_tbl = { a.var_name, ':select(', dim.var_name, ',', value.var_name, ')' } dest:write_expr_assign(self.var_name, table.concat(str_tbl, "")) end) -- TODO: modify dims return s end, slice = function(...) local arg = iterator(ipairs(table.pack(...))):select(2):map(coercion):table() local s = gen_op('slice', MATRIX, arg, function(self, ...) local arg = iterator(ipairs(self.args)): select(2):call('eval',...):table() local a = table.remove(arg,1) assert(type(a) == "matrix") return a(table.unpack(arg)) end, function(self, seed, result) local a = self.args[1] local arg = iterator(range(2,#self.args)): map(function(i) return self.args[i] end):table() -- local dest = autodiff.op.fill(self,0) dest = autodiff.op.copy(dest, seed, table.unpack(arg)) a:diff(dest, result) return result end, function(self, dest) local a = self.args[1] local str_tbl = { a.var_name, '(' } table.insert(str_tbl, self.args[2].var_name) for i=3,#self.args do table.insert(str_tbl, ',') table.insert(str_tbl, self.args[i].var_name) end table.insert(str_tbl, ')') dest:write_expr_assign(self.var_name, table.concat(str_tbl, "")) end) -- TODO: modify dims return s end, copy = function(...) local arg = iterator(ipairs(table.pack(...))):select(2):map(coercion):table() local s = gen_op('copy', MATRIX, arg, function(self, ...) local arg = iterator(ipairs(self.args)): select(2):call('eval',...):table() local a = table.remove(arg,1) local b = table.remove(arg,2) assert(type(a) == "matrix") assert(type(b) == "matrix") a = a:clone() if #arg > 0 then a(table.unpack(arg)):copy(b) else a:copy(b) end return a end, function(self, seed, result) return result end, function(self, dest) local a = self.args[1] local b = self.args[2] local str_tbl = { a.var_name, ':clone()' } if #self.args > 2 then table.insert(str_tbl, '(') table.insert(str_tbl, self.args[3].var_name) for i=4,#self.args do table.insert(str_tbl, ',') table.insert(str_tbl, self.args[i].var_name) end table.insert(str_tbl, ')') end table.insert(str_tbl, ':copy(') table.insert(str_tbl, b.var_name) table.insert(str_tbl, ')') dest:write_expr_assign(self.var_name, table.concat(str_tbl, "")) end) -- TODO: modify dims return s end, get = function(...) local arg = iterator(ipairs(table.pack(...))):select(2):map(coercion):table() local s = gen_op('get', SCALAR, arg, function(self, ...) local arg = iterator(ipairs(self.args)): select(2):call('eval', ...):table() local a = table.remove(arg,1) assert(type(a) == "matrix") return a:get(table.unpack(arg)) end, function(self, seed, result) local a = self.args[1] local arg = iterator(range(2,#self.args)): map(function(i) return self.args[i] end):table() local aux = autodiff.op.fill(a, 0) aux = autodiff.op.copy(aux,seed,table.unpack(arg)) a:diff(aux, result) return result end, function(self, dest) local a = self.args[1] local str_tbl = { a.var_name, ':get(' } table.insert(str_tbl, self.args[2].var_name) for i=3,#self.args do table.insert(str_tbl, ',') table.insert(str_tbl, self.args[i].var_name) end table.insert(str_tbl, ')') dest:write_expr_assign(self.var_name, table.concat(str_tbl, "")) end) return s end, sign = function(a) local a = coercion(a) local s = gen_op('sign', MATRIX, {a}, function(self, ...) local a = self.args[1]:eval(...) assert(type(a) == "matrix") return a:clone():sign() end, function(self, seed, result) return result end, function(self, dest) local a = self.args[1] local str_tbl = { a.var_name, ':clone():sign()' } dest:write_expr_assign(self.var_name, table.concat(str_tbl, "")) end) if a.dims then s:set_dims(a.dims) end return s end, abs = function(a) local a = coercion(a) local s = gen_op('abs', MATRIX, {a}, function(self, ...) local a = self.args[1]:eval(...) assert(type(a) == "matrix") return a:clone():abs() end, function(self, seed, result) local a = self.args[1] a:diff(autodiff.op.cmul(a,seed) * (1/self), result) return result end, function(self, dest) local a = self.args[1] local str_tbl = { a.var_name, ':clone():abs()' } dest:write_expr_assign(self.var_name, table.concat(str_tbl, "")) end) if a.dims then s:set_dims(a.dims) end return s end, dim = function(a, b) local a,b = coercion(a),coercion(b) local s = gen_op('dim', SCALAR, {a,b}, function(self, ...) local a,b = self.args[1]:eval(...),self.args[2]:eval(...) assert(type(a) == "matrix") return a:dim(b) end, function(self, seed, result) return result end, function(self, dest) local a = self.args[1] local b = self.args[2] local str_tbl = { a.var_name, ':dim(', b.var_name, ')' } dest:write_expr_assign(self.var_name, table.concat(str_tbl, "")) end) -- TODO: if a.dims then s:set_dims(a.dims) end return s end, size = function(a) local a = coercion(a) local s = gen_op('size', SCALAR, {a}, function(self, ...) local a = self.args[1]:eval(...) assert(type(a) == "matrix") return a:size() end, function(self, seed, result) return result end, function(self, dest) local a = self.args[1] local str_tbl = { a.var_name, ':size()' } dest:write_expr_assign(self.var_name, table.concat(str_tbl, "")) end) if a.dims then s:set_dims(a.dims) end return s end, mean = function(a) return autodiff.op.sum(a) / autodiff.op.size(a) end, max = function(a) local a = coercion(a) local s = gen_op('max', SCALAR, {a}, function(self, ...) local a = self.args[1]:eval(...) assert(type(a) == "matrix") return a:clone():max() end, function(self, seed, result) local a = self.args[1] local argmax = autodiff.op.argmax(a) local out = autodiff.op.fill(a,0) local out = autodiff.op.copy(out, seed, argmax) a:diff(out, result) return result end, function(self, dest) local a = self.args[1] local str_tbl = { a.var_name, ':clone():max()' } dest:write_expr_assign(self.var_name, table.concat(str_tbl, "")) end) if a.dims then s:set_dims(a.dims) end return s end, argmax = function(a) local a = coercion(a) local s = gen_op('argmax', SCALAR, {a}, function(self, ...) local a = self.args[1]:eval(...) assert(type(a) == "matrix") return select(2,a:clone():max()) end, function(self, seed, result) return result end, function(self, dest) local a = self.args[1] local str_tbl = { 'select(2,', a.var_name, ':clone():max())' } dest:write_expr_assign(self.var_name, table.concat(str_tbl, "")) end) if a.dims then s:set_dims(a.dims) end return s end, clamp = function(a,lower,upper) local a,lower,upper = coercion(a),coercion(lower),coercion(upper) local s = gen_op('clamp', MATRIX, {a,lower,upper}, function(self, ...) local a = self.args[1]:eval(...) local lower = self.args[2]:eval(...) local upper = self.args[3]:eval(...) -- TODO: check types return a:clone():clamp(lower, upper) end, function(self, seed, result) local a = self.args[1] a:diff(seed, result) return result end, function(self, dest) local a = self.args[1] local lower = self.args[2] local upper = self.args[3] local str_tbl = { a.var_name, ':clone()', ':clamp(', lower.var_name, ',', upper.var_name, ')' } dest:write_expr_assign(self.var_name, table.concat(str_tbl, "")) end) if a.dims then s:set_dims(a.dims) end return s end, } ------------------------------------------------------------------------------ ------------------------------------------------------------------------------ ------------------------------------------------------------------------------ local function cmul_general_optimization(...) for node in autodiff.graph_iterators.post_order_traversal(...) do if node.isop == '.*' then -- modify the current symbol with all the stored additions at flat_mul local constant = autodiff[CONSTANT](1) local scalar = autodiff[CONSTANT](1) local exp = autodiff[CONSTANT](0) local vd = {} local function count(a,b) local b = b or autodiff[CONSTANT](1) if a.dtype == CONSTANT then constant = constant * a^b elseif a.dtype == SCALAR then scalar = scalar * a^b else vd[a] = (vd[a] or autodiff[CONSTANT](0)) + b end end local function child_traverse(child) if child.isop == '.*' then for i,v in child:arg_ipairs() do child_traverse(v) end elseif child.isop == '.^' then count(child.args[1], child.args[2]) elseif child.isop == 'exp' then exp = exp + child.args[1] else count(child) end end child_traverse(node) -- modify the current symbol with all the stored multiplications local vars = iterator(pairs(vd)):select(1):table() -- canonical form (sorted) table.sort(vars) -- new symbol local new_node = constant * scalar if exp ~= autodiff[CONSTANT](0) then new_node = autodiff.op.cmul(new_node, autodiff.op.exp(exp)) end for i,v in ipairs(vars) do new_node = autodiff.op.cmul(new_node, (v^vd[v])) end -- substitution if new_node ~= node then node:replace(new_node) end end -- if node.isop == '.*' end -- if node in post_order_traversal end local function pow_matrix_optimization(...) for node in autodiff.graph_iterators.post_order_traversal(...) do if node.isop == '.^' and node.dtype == MATRIX then local a,b = node.args[1],node.args[2] if a.isop == '.^' and a.dtype == MATRIX then local new_node = a.args[1]^(b*a.args[2]) -- substitution if new_node ~= node then node:replace(new_node) end end end -- if node.isop == '^' end -- for node in post_order_traversal end local function exp_matrix_optimization(...) for node in autodiff.graph_iterators.post_order_traversal(...) do if node.isop == '.^' and node.dtype == MATRIX then local a,b = node.args[1],node.args[2] if a.isop == 'exp' and a.dtype == MATRIX then local new_node = autodiff.op.exp(a.args[1]*b) -- substitution if new_node ~= node then node:replace(new_node) end end end -- if node.isop == '^' end -- for node in post_order_traversal end -- register optimizations autodiff.optdb.register_global(cmul_general_optimization) autodiff.optdb.register_global(pow_matrix_optimization) autodiff.optdb.register_global(exp_matrix_optimization) april-ann-0.4.1/packages/autodiff/autodiff/lua_src/scalar.lua000066400000000000000000000276251263004425400241710ustar00rootroot00000000000000local CONSTANT = autodiff.dtypes.CONSTANT local SCALAR = autodiff.dtypes.SCALAR local MATRIX = autodiff.dtypes.MATRIX local TABLE = autodiff.dtypes.TABLE local STRING = autodiff.dtypes.STRING -- local gen_var_name = autodiff.gen_var_name local coercion = autodiff.coercion local gen_op = autodiff.gen_op -- SCALAR autodiff[SCALAR] = function(names) return autodiff.symbol(names, SCALAR) end -- SCALAR OPERATIONS autodiff.op[SCALAR] = { -- basic math operations add = function(a,b) local a,b = coercion(a),coercion(b) -- simplifications if bgetRawDataAccess()->getPPALForRead(); if (mat->getNumDim() != 2 || mat->getDimSize(0) != 3 || mat->getDimSize(1) != 3) { LUABIND_ERROR("2D affine transform matrix must be 3x3"); } if (data[6] != 0 || data[7] != 0 || data[8] != 1) { LUABIND_FERROR3("Bottom row of the 2D affine transform matrix must be [0 0 1] " "([%f %f %f] found)", data[6], data[7], data[8]); } obj = new AffineTransform2D(mat); } LUABIND_RETURN(AffineTransform2D, obj); } //BIND_END //BIND_DESTRUCTOR AffineTransform2D { } //BIND_END //BIND_METHOD AffineTransform2D accumulate { LUABIND_CHECK_ARGN(==, 1); AffineTransform2D *other; LUABIND_GET_PARAMETER(1, AffineTransform2D, other); obj->accumulate(other); LUABIND_RETURN(AffineTransform2D, obj); } //BIND_END //BIND_METHOD AffineTransform2D rotate { int argn = lua_gettop(L); if (argn == 1) { float angle; LUABIND_GET_PARAMETER(1, float, angle); obj->rotate(angle); } else if (argn == 3) { float angle, center_x, center_y; LUABIND_GET_PARAMETER(1, float, angle); LUABIND_GET_PARAMETER(2, float, center_x); LUABIND_GET_PARAMETER(3, float, center_y); obj->rotate(angle, center_x, center_y); } else { LUABIND_ERROR("rotate accepts only 1 or 3 arguments"); } LUABIND_RETURN(AffineTransform2D, obj); } //BIND_END //BIND_METHOD AffineTransform2D scale { LUABIND_CHECK_ARGN(==, 2); float x, y; LUABIND_GET_PARAMETER(1, float, x); LUABIND_GET_PARAMETER(2, float, y); obj->scale(x, y); LUABIND_RETURN(AffineTransform2D, obj); } //BIND_END //BIND_METHOD AffineTransform2D translate { LUABIND_CHECK_ARGN(==, 2); float x, y; LUABIND_GET_PARAMETER(1, float, x); LUABIND_GET_PARAMETER(2, float, y); obj->translate(x, y); LUABIND_RETURN(AffineTransform2D, obj); } //BIND_END //BIND_METHOD AffineTransform2D shear { LUABIND_CHECK_ARGN(==, 2); float angle_x, angle_y; LUABIND_GET_PARAMETER(1, float, angle_x); LUABIND_GET_PARAMETER(2, float, angle_y); obj->shear(angle_x, angle_y); LUABIND_RETURN(AffineTransform2D, obj); } //BIND_END //BIND_METHOD AffineTransform2D transform { LUABIND_CHECK_ARGN(==, 2); float x, y, dstx, dsty; LUABIND_GET_PARAMETER(1, float, x); LUABIND_GET_PARAMETER(2, float, y); obj->transform(x,y, &dstx, &dsty); LUABIND_RETURN(float, dstx); LUABIND_RETURN(float, dsty); } //BIND_END april-ann-0.4.1/packages/basics/AffineTransform2D/c_src/000077500000000000000000000000001263004425400227625ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/AffineTransform2D/c_src/affine_transform.cc000066400000000000000000000067641263004425400266310ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "affine_transform.h" #include "cmath_overloads.h" #include "smart_ptr.h" using AprilUtils::SharedPtr; namespace Basics { const int AffineTransform2D::dimensions[2] = {3,3}; /// Identity transform AffineTransform2D::AffineTransform2D(): MatrixFloat(2, dimensions) { AprilMath::MatrixExt::Initializers::matZeros(this); MatrixFloat::random_access_iterator data(this); data(0,0) = 1.0f; data(1,1) = 1.0f; data(2,2) = 1.0f; } AffineTransform2D::AffineTransform2D(MatrixFloat *mat): MatrixFloat(mat) { april_assert("AffineTransform2D: Matrix must be 3x3" && numDim == 2 && matrixSize[0] == 3 && matrixSize[1] == 3); april_assert("AffineTransform2D: Last row must be [0 0 1]" && (*this)(2,0) == 0 && (*this)(2,1) == 0 && (*this)(2,2) == 1); } AffineTransform2D *AffineTransform2D::accumulate(AffineTransform2D *other) { SharedPtr this_clone( this->clone() ); AprilMath::MatrixExt::BLAS::matGemm(this, CblasNoTrans, CblasNoTrans, 1.0f, other, this_clone.get(), 0.0f); return this; } AffineTransform2D *AffineTransform2D::rotate(float angle) { AffineTransform2D trans; // 3x3 identity trans(0,0) = AprilMath::m_cos(angle); trans(0,1) = -AprilMath::m_sin(angle); trans(1,0) = AprilMath::m_sin(angle); trans(1,1) = AprilMath::m_cos(angle); accumulate(&trans); return this; } AffineTransform2D *AffineTransform2D::rotate(float angle, float center_x, float center_y) { translate(-center_x, -center_y); rotate(angle); translate(center_x, center_y); return this; } AffineTransform2D *AffineTransform2D::translate(float x, float y) { AffineTransform2D trans; // 3x3 identity trans(0,2) = x; trans(1,2) = y; accumulate(&trans); return this; } AffineTransform2D *AffineTransform2D::scale(float x, float y) { AffineTransform2D trans; // 3x3 identity trans(0,0) = x; trans(1,1) = y; accumulate(&trans); return this; } AffineTransform2D *AffineTransform2D::shear(float x, float y) { AffineTransform2D trans; // 3x3 identity trans(0,1) = tanf(x); trans(1,0) = tanf(y); accumulate(&trans); return this; } void AffineTransform2D::transform(float x, float y, float *dst_x, float *dst_y) const { MatrixFloat::const_random_access_iterator data(this); float res_x = data(0,0)*x+data(0,1)*y+data(0,2); float res_y = data(1,0)*x+data(1,1)*y+data(1,2); *dst_x=res_x; *dst_y=res_y; } } // namespace Basics april-ann-0.4.1/packages/basics/AffineTransform2D/c_src/affine_transform.h000066400000000000000000000030701263004425400264560ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef AFFINE_TRANSFORM_H #define AFFINE_TRANSFORM_H #include "matrixFloat.h" namespace Basics { class AffineTransform2D: public MatrixFloat { public: AffineTransform2D(); AffineTransform2D(MatrixFloat *mat); ~AffineTransform2D() {} AffineTransform2D *accumulate(AffineTransform2D *other); AffineTransform2D *rotate(float angle); AffineTransform2D *rotate(float angle, float center_x, float center_y); AffineTransform2D *translate(float x, float y); AffineTransform2D *scale(float x, float y); AffineTransform2D *shear(float angle_x, float angle_y); void transform(float x, float y, float *dstx, float *dsty) const; private: static const int dimensions[2]; }; } // namespace Basics #endif april-ann-0.4.1/packages/basics/AffineTransform2D/lua_src/000077500000000000000000000000001263004425400233215ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/AffineTransform2D/lua_src/affine_transform.lua000066400000000000000000000016711263004425400273540ustar00rootroot00000000000000AffineTransform2D.meta_instance.__tostring = function(self) local dims = self:dim() local major = self:get_major_order() local coords = {} local out = {} local row = {} for i=1,#dims do coords[i]=1 end for i=1,self:size() do if #dims > 2 and coords[#dims] == 1 and coords[#dims-1] == 1 then table.insert(out, string.format("\n# pos [%s]", table.concat(coords, ","))) end table.insert(row, string.format("% -11.6g", self:get(table.unpack(coords)))) local j=#dims+1 repeat j=j-1 coords[j] = coords[j] + 1 if coords[j] > dims[j] then coords[j] = 1 end until j==1 or coords[j] ~= 1 if coords[#coords] == 1 then table.insert(out, table.concat(row, " ")) row={} end end table.insert(out, string.format("# AffineTransform2D of size [%s] in %s [%s]", table.concat(dims, ","), major, self:get_reference_string())) return table.concat(out, "\n") end april-ann-0.4.1/packages/basics/AffineTransform2D/package.lua000066400000000000000000000020721263004425400237700ustar00rootroot00000000000000 package{ name = "AffineTransform2D", version = "1.0", depends = { "util", "matrix" }, keywords = { "AffineTransform2D" }, description = "An affine transform class", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_affine_transform.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_affine_transform.lua.cc", dest_dir = "build", } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/aprilio/000077500000000000000000000000001263004425400200565ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/aprilio/binding/000077500000000000000000000000001263004425400214705ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/aprilio/binding/bind_april_io.lua.cc000066400000000000000000000357551263004425400253700ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_H #include "archive_package.h" #include "buffered_stream.h" #include "c_string.h" #include "file_stream.h" #include "lua_string.h" #include "serializable.h" #include "stream.h" #include "stream_memory.h" using namespace AprilIO; //BIND_END //BIND_FOOTER_H template int callFileStreamConstructor(lua_State *L) { const char *path = luaL_checkstring(L, 1); const char *mode = luaL_optstring(L, 2, "r"); StreamInterface *stream = new T(path, mode); if (stream->isOpened()) { lua_pushStreamInterface(L, stream); return 1; } else { int num_returns = 1; lua_pushnil(L); if (stream->hasError()) { lua_pushstring(L, stream->getErrorMsg()); ++num_returns; } delete stream; return num_returns; } } template int callArchivePackageConstructor(lua_State *L) { ArchivePackage *obj; if (lua_isstring(L,1)) { // from a file name const char *path = luaL_checkstring(L, 1); const char *mode = luaL_optstring(L, 2, "r"); obj = new T(path, mode); } else { // from a stream StreamInterface *stream = lua_toStreamInterface(L,1); obj = new T(stream); } if (obj->good()) { lua_pushArchivePackage(L, obj); } else { lua_pushnil(L); delete obj; } return 1; } template int lua_isAuxStreamInterface(lua_State *L, int index) { luaL_Stream *p = ((luaL_Stream *)luaL_testudata(L, index, LUA_FILEHANDLE)); if (p == 0) { StreamInterface *s = lua_toStreamInterface(L, index); if (s == 0) return 0; T *s_casted = dynamic_cast(s); if (s_casted == 0) return 0; } return 1; } template T *lua_toAuxStreamInterface(lua_State *L, int index) { StreamInterface *s; luaL_Stream *p = ((luaL_Stream *)luaL_testudata(L, index, LUA_FILEHANDLE)); if (p == 0) s = lua_toStreamInterface(L, index); else s = new FileStream(p->f); T *s_casted = dynamic_cast(s); if (s_casted == 0) return 0; return s_casted; } //BIND_END //BIND_HEADER_C #include "april_assert.h" #include "bind_util.h" IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(StreamInterface); namespace AprilIO { int readAndPushNumberToLua(lua_State *L, StreamInterface *obj, CStringStream *&c_string) { if (obj->eof()) return 0; if (c_string == 0) AssignRef(c_string, new CStringStream()); c_string->clear(); obj->get(c_string, " ,;\t\n\r"); if (c_string->empty()) { lua_pushnil(L); return 1; } double number; if (!c_string->getConstString().extract_double(&number)) { ERROR_EXIT(256, "Impossible to extract a number from current file pos\n"); } lua_pushnumber(L, number); return 1; } int readAndPushStringToLua(lua_State *L, StreamInterface *obj, int size, OutputLuaStringStream *&lua_string) { if (obj->eof()) return 0; if (lua_string == 0) AssignRef(lua_string, new OutputLuaStringStream(L)); lua_string->clear(); obj->get(lua_string, size); if (obj->eof() && lua_string->empty()) return 0; return lua_string->push(L); } int readAndPushLineToLua(lua_State *L, StreamInterface *obj, OutputLuaStringStream *&lua_string) { if (obj->eof()) return 0; if (lua_string == 0) AssignRef(lua_string, new OutputLuaStringStream(L)); lua_string->clear(); extractLineFromStream(obj, lua_string); if (obj->eof() && lua_string->empty()) return 0; return lua_string->push(L); } int readAndPushAllToLua(lua_State *L, StreamInterface *obj, OutputLuaStringStream *&lua_string) { if (obj->eof()) return 0; if (lua_string == 0) AssignRef(lua_string, new OutputLuaStringStream(L)); lua_string->clear(); obj->get(lua_string); if (obj->eof() && lua_string->empty()) return 0; return lua_string->push(L); } } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME StreamInterface aprilio.stream //BIND_CPP_CLASS StreamInterface //BIND_CONSTRUCTOR StreamInterface { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD StreamInterface good { LUABIND_RETURN(boolean, obj->good()); } //BIND_END //BIND_METHOD StreamInterface eof { LUABIND_RETURN(boolean, obj->eof()); } //BIND_END //BIND_METHOD StreamInterface is_opened { LUABIND_RETURN(boolean, obj->isOpened()); } //BIND_END //BIND_METHOD StreamInterface close { obj->close(); } //BIND_END //BIND_METHOD StreamInterface read { if (!obj->good()) { lua_pushnil(L); return 1; } /* "*n" reads a number; this is the only format that returns a number instead of a string. "*a" reads the whole file, starting at the current position. On end of file, it returns the empty string. "*l" reads the next line (skipping the end of line), returning nil on end of file. This is the default format. number reads a string with up to that number of characters, returning nil on end of file. If number is zero, it reads nothing and returns an empty string, or nil on end of file. */ int argn = lua_gettop(L); // number of arguments OutputLuaStringStream *lua_string = 0; CStringStream *c_string = 0; if (argn == 0) { LUABIND_INCREASE_NUM_RETURNS(readAndPushLineToLua(L, obj, lua_string)); } else { for (int i=1; i<=argn; ++i) { if (lua_isnumber(L, i)) { int size = luaL_checkint(L, i); LUABIND_INCREASE_NUM_RETURNS(readAndPushStringToLua(L, obj, size, lua_string)); } else { const char *format = luaL_checkstring(L, i); // a number if (strcmp(format, "*n") == 0) { LUABIND_INCREASE_NUM_RETURNS(readAndPushNumberToLua(L, obj, c_string)); } // the whole file else if (strcmp(format, "*a") == 0) { LUABIND_INCREASE_NUM_RETURNS(readAndPushAllToLua(L, obj, lua_string)); } // a line else if (strcmp(format, "*l") == 0) { LUABIND_INCREASE_NUM_RETURNS(readAndPushLineToLua(L, obj, lua_string)); } else { LUABIND_FERROR1("Unrecognized format string '%s'", format); } // if (strcmp(format), ...) ... } // if isnil ... else if isnumber ... else ... } // for (int i=1; i<= argn; ++i) } // if (argn == 0) ... else if (lua_string != 0) DecRef(lua_string); if (c_string != 0) DecRef(c_string); } //BIND_END //BIND_METHOD StreamInterface write { int argn = lua_gettop(L); // number of arguments for (int i=1; i<=argn; ++i) { const char *value = luaL_checkstring(L, i); obj->put(value, luaL_len(L, i)); } if (obj->hasError()) { LUABIND_RETURN_NIL(); LUABIND_RETURN(string, obj->getErrorMsg()); } else { LUABIND_RETURN(StreamInterface, obj); } } //BIND_END //BIND_METHOD StreamInterface seek { const char *whence = luaL_optstring(L, 1, "cur"); int offset = luaL_optint(L, 2, 0); int int_whence; if (strcmp(whence, "cur") == 0) { int_whence = SEEK_CUR; } else if (strcmp(whence, "set") == 0) { int_whence = SEEK_SET; } else { int_whence = SEEK_END; LUABIND_FERROR1("Not supported whence '%s'", whence); } off_t ret = obj->seek(int_whence, offset); if (ret < 0) { LUABIND_RETURN_NIL(); LUABIND_RETURN(string, obj->getErrorMsg()); } else { // sanity check april_assert( static_cast( static_cast( ret ) ) == ret ); LUABIND_RETURN(number, static_cast(ret)); return 1; } } //BIND_END //BIND_METHOD StreamInterface flush { obj->flush(); } //BIND_END //BIND_METHOD StreamInterface setvbuf { LUABIND_ERROR("NOT IMPLEMENTED"); } //BIND_END //BIND_METHOD StreamInterface has_error { LUABIND_RETURN(boolean, obj->hasError()); } //BIND_END //BIND_METHOD StreamInterface error_msg { LUABIND_RETURN(string, obj->getErrorMsg()); } //BIND_END //BIND_METHOD StreamInterface get { if (!obj->eof()) { AprilUtils::SharedPtr dest; OutputLuaStringStream *aux_lua_string = 0; size_t size = SIZE_MAX; const char *delim = 0; bool keep_delim = false; if (lua_istable(L,1)) { // complete API check_table_fields(L, 1, "dest", "size", "delim", "keep_delim", (const char*)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, dest, StreamInterface, dest, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, size, uint, size, SIZE_MAX); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, delim, string, delim, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, keep_delim, boolean, keep_delim, false); } else { // simplified API if (lua_isuint(L,1)) LUABIND_GET_PARAMETER(1, uint, size); else if (lua_isstring(L,1)) LUABIND_GET_PARAMETER(1, string, delim); else LUABIND_ERROR("Needs delimitiers string or number as 1st argument"); LUABIND_GET_OPTIONAL_PARAMETER(2, boolean, keep_delim, false); } if (dest.empty()) { aux_lua_string = new OutputLuaStringStream(L); dest = aux_lua_string; } size_t len = obj->get(dest.get(), size, delim, keep_delim); if (!obj->eof() || len!=0) { if (aux_lua_string == 0) LUABIND_RETURN(StreamInterface, dest.get()); else LUABIND_INCREASE_NUM_RETURNS(aux_lua_string->push(L)); LUABIND_RETURN(uint, len); } } } //BIND_END //BIND_METHOD StreamInterface put { AprilUtils::SharedPtr ptr; const char *buffer; size_t len; if (lua_isStreamInterface(L,1)) { size_t size; LUABIND_GET_PARAMETER(1, StreamInterface, ptr); LUABIND_GET_OPTIONAL_PARAMETER(2, uint, size, SIZE_MAX); len = obj->put(ptr.get(), size); } else { LUABIND_GET_PARAMETER(1, string, buffer); len = obj->put(buffer); } LUABIND_RETURN(uint, len); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME FileStream aprilio.stream.file //BIND_CPP_CLASS FileStream //BIND_SUBCLASS_OF FileStream StreamInterface //BIND_CONSTRUCTOR FileStream { LUABIND_INCREASE_NUM_RETURNS(callFileStreamConstructor(L)); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME InputLuaStringStream aprilio.stream.input_lua_string //BIND_CPP_CLASS InputLuaStringStream //BIND_SUBCLASS_OF InputLuaStringStream StreamInterface //BIND_CONSTRUCTOR InputLuaStringStream { obj = new InputLuaStringStream(L, 1); LUABIND_RETURN(InputLuaStringStream, obj); } //BIND_END //BIND_METHOD InputLuaStringStream value { LUABIND_INCREASE_NUM_RETURNS(obj->push(L)); } //BIND_END //BIND_CLASS_LUA_TO_HOOK InputLuaStringStream { obj->retrieveStringFromRegistry(L); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME CStringStream aprilio.stream.c_string //BIND_CPP_CLASS CStringStream //BIND_SUBCLASS_OF CStringStream StreamInterface //BIND_CONSTRUCTOR CStringStream { const char *str; LUABIND_GET_OPTIONAL_PARAMETER(1, string, str, 0); if (str != 0) { obj = new CStringStream(str, luaL_len(L,1)); } else { obj = new CStringStream(); } LUABIND_RETURN(CStringStream, obj); } //BIND_END //BIND_METHOD CStringStream value { LUABIND_INCREASE_NUM_RETURNS(obj->push(L)); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME ArchivePackage aprilio.package //BIND_CPP_CLASS ArchivePackage //BIND_CONSTRUCTOR ArchivePackage { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD ArchivePackage has_error { LUABIND_RETURN(boolean, obj->hasError()); } //BIND_END //BIND_METHOD ArchivePackage error_msg { LUABIND_RETURN(string, obj->getErrorMsg()); } //BIND_END //BIND_METHOD ArchivePackage close { obj->close(); } //BIND_END //BIND_METHOD ArchivePackage open { int flags = 0; StreamInterface *stream; int argn = lua_gettop(L); // number of arguments for (int i=2; i<=argn; ++i) { int current = lua_toint(L,i); flags |= current; } if (lua_isnumber(L,1)) { // open with a file index number unsigned int idx; LUABIND_GET_PARAMETER(1, uint, idx); if (idx < 1) { LUABIND_RETURN_NIL(); LUABIND_RETURN(string, "Index starts at 1"); return 2; } stream = obj->openFile(idx - 1, flags); } else { // open with a file name const char *filename; LUABIND_GET_PARAMETER(1, string, filename); stream = obj->openFile(filename, flags); } if (stream != 0) { LUABIND_RETURN(StreamInterface, stream); } else { LUABIND_RETURN_NIL(); LUABIND_RETURN(string, "Unable to open the file"); } } //BIND_END //BIND_METHOD ArchivePackage good { LUABIND_RETURN(boolean, obj->good()); } //BIND_END //BIND_METHOD ArchivePackage number_of_files { LUABIND_RETURN(uint, obj->getNumberOfFiles()); } //BIND_END //BIND_METHOD ArchivePackage name_of { unsigned int idx; LUABIND_GET_PARAMETER(1, uint, idx); if (idx < 1) LUABIND_ERROR("Index starts at 1"); const char *name = obj->getNameOf(idx - 1); if (name == 0) LUABIND_RETURN_NIL(); else LUABIND_RETURN(string, name); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME Serializable aprilio.serializable //BIND_CPP_CLASS Serializable //BIND_CONSTRUCTOR Serializable { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD Serializable write { OutputLuaStringStream *aux_lua_string; StreamInterface *ptr; AprilUtils::SharedPtr dest; int options_pos; if (!lua_istable(L,1)) { LUABIND_GET_OPTIONAL_PARAMETER(1, AuxStreamInterface, ptr, 0); options_pos = 2; AprilUtils::LuaTable options(L,2); } else { options_pos = 1; ptr = 0; } AprilUtils::LuaTable options(L,options_pos); if (ptr == 0) { aux_lua_string = new OutputLuaStringStream(L); dest = aux_lua_string; } else { dest.reset(ptr); } obj->write(dest.get(), options); if (ptr == 0) LUABIND_INCREASE_NUM_RETURNS(aux_lua_string->push(L)); } //BIND_END //BIND_METHOD Serializable ctor_name { LUABIND_RETURN(string, obj->luaCtorName()); } //BIND_END //BIND_METHOD Serializable ctor_params { LUABIND_INCREASE_NUM_RETURNS(obj->exportParamsToLua(L)); } //BIND_END april-ann-0.4.1/packages/basics/aprilio/c_src/000077500000000000000000000000001263004425400211475ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/aprilio/c_src/archive_package.h000066400000000000000000000055511263004425400244220ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef ARCHIVE_PACKAGE_H #define ARCHIVE_PACKAGE_H #include "mystring.h" #include "referenced.h" #include "smart_ptr.h" #include "stream.h" namespace AprilIO { /** * @brief Class which represent interface of package formats as ZIP or TAR. */ class ArchivePackage : public Referenced { public: /// Constructor. ArchivePackage() : Referenced() { } /// Destructor. virtual ~ArchivePackage() { } /// Indicates if the object is in good state. virtual bool good() const = 0; /// Indicates if a call has produced an error. virtual bool hasError() const = 0; /// Returns the error message from last call error. virtual const char *getErrorMsg() = 0; /// Closes the package. virtual void close() = 0; /// Returns the number of files contained inside the package. virtual size_t getNumberOfFiles() = 0; /// Returns the name of the file with index idx. virtual const char *getNameOf(size_t idx) = 0; /** * @brief Opens a file given its name and a flags integer. * * @note The flags will change depending in the package. * * @param name - The filename as it is indicated by getNameOf() method. * * @param flags - The flags to open the file, which indicates the package * library how to find the given filename. * * @return A StreamInterface pointer or NULL if the call fails. */ virtual StreamInterface *openFile(const char *name, int flags) = 0; /** * @brief Opens a file given its index and a flags integer. * * @note The flags will change depending in the package. * * @param idx - The index of the file inside the package. * * @param flags - The flags to open the file, which indicates the package * library how to find the filename by using its index idx. * * @return A StreamInterface pointer or NULL if the call fails. */ virtual StreamInterface *openFile(size_t idx, int flags) = 0; }; } // namespace AprilIO #endif // ARCHIVE_PACKAGE_H april-ann-0.4.1/packages/basics/aprilio/c_src/buffered_stream.cc000066400000000000000000000202261263004425400246150ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include #include extern "C" { #include #include #include } #include "maxmin.h" #include "buffered_stream.h" namespace AprilIO { BufferedStream::BufferedStream(size_t buf_size) : StreamBuffer(), max_buffer_len(buf_size) { in_buffer = new char[max_buffer_len]; out_buffer = new char[max_buffer_len]; } BufferedStream::~BufferedStream() { delete[] in_buffer; delete[] out_buffer; } void BufferedStream::close() { if (isOpened()) { flush(); closeStream(); } } off_t BufferedStream::seek(int whence, long offset) { if (whence == SEEK_CUR) { off_t real_pos = seekStream(SEEK_CUR, 0); off_t current_pos = real_pos - getInBufferAvailableSize(); if (offset == 0) return current_pos; offset -= (real_pos - current_pos); } flush(); resetBuffers(); return seekStream(whence, offset); } void BufferedStream::flush() { size_t nbytes = flushBuffer(out_buffer, getOutBufferPos()); if (nbytes < max_buffer_len - getOutBufferPos()) { memmove(out_buffer, out_buffer + nbytes, max_buffer_len - nbytes); } resetOutBuffer(); } int BufferedStream::setvbuf(int mode, size_t size) { // TODO: UNUSED_VARIABLE(mode); UNUSED_VARIABLE(size); return 0; } const char *BufferedStream::nextInBuffer(size_t &buf_len) { buf_len = fillBuffer(in_buffer, max_buffer_len); return in_buffer; } char *BufferedStream::nextOutBuffer(size_t &buf_len) { buf_len = max_buffer_len; return out_buffer; } //////////////////////////////////////////////////////////// BufferedInputStream::BufferedInputStream(size_t buf_size) : StreamInterface(), max_buffer_size(buf_size) { in_buffer = new char[max_buffer_size + 1]; in_buffer_pos = in_buffer_len = 0; } BufferedInputStream::~BufferedInputStream() { delete[] in_buffer; } void BufferedInputStream::prepareInBufferData() { // read only when the buffer is empty if (in_buffer_pos == in_buffer_len) { int nbytes = privateRead(in_buffer, max_buffer_size); // TODO: check errors in_buffer_len = static_cast(nbytes); in_buffer_pos = 0; // WARNING: strpbrk needs this '\0' at buffer end position in_buffer[in_buffer_len] = '\0'; } } void BufferedInputStream::trimInBuffer(const char *delim) { if (delim != 0) { do { prepareInBufferData(); // move buffer position as many delimitiers are in the buffer while(in_buffer_pos < in_buffer_len && strchr(delim, in_buffer[in_buffer_pos]) != 0) { ++in_buffer_pos; } // continue reading data while all the buffer are delimitiers } while(in_buffer_pos == in_buffer_len && in_buffer_len > 0); } } // putOp is a predicate which wraps a StreamInterface or a char buffer. template size_t BufferedInputStream::templatizedGet(T &putOp, size_t max_size, const char *delim, bool keep_delim) { size_t dest_len=0; if (!keep_delim) trimInBuffer(delim); // Read data until complete the given max_size or a delimitier is found, and // no errors are found. while( this->good() && !putOp.hasError() && dest_len < max_size ) { prepareInBufferData(); // Condition of empty buffer, no data is available. if (in_buffer_pos >= in_buffer_len) break; size_t available_size = in_buffer_len - in_buffer_pos; size_t buf_len = AprilUtils::min(available_size, max_size - dest_len); if (delim != 0) { // WARNING: in_buffer needs a '\0' to indicate its size char *delim_pos = strpbrk(in_buffer + in_buffer_pos, delim); if (delim_pos != NULL) { if (delim_pos < in_buffer + in_buffer_len && keep_delim) ++delim_pos; ptrdiff_t ptr_diff = delim_pos - (in_buffer + in_buffer_pos); size_t diff = static_cast(ptr_diff); buf_len = AprilUtils::min(buf_len, diff); } } // Put data into the given operator, which wraps a StreamInterface or a // char buffer. size_t len = putOp(in_buffer + in_buffer_pos, buf_len); in_buffer_pos += len; dest_len += len; // Delim true condition. if (len != available_size) break; } return dest_len; } bool BufferedInputStream::good() const { return isOpened() && !eof(); } size_t BufferedInputStream::get(StreamInterface *dest, const char *delim, bool keep_delim) { return get(dest, SIZE_MAX, delim, keep_delim); } // Operator for put data into a StreamInterface object. struct putOperatorStream { StreamInterface *dest; putOperatorStream(StreamInterface *dest) : dest(dest) { } size_t operator()(char *buffer, size_t len) { return dest->put(buffer, len); } bool hasError() const { return dest->hasError(); } }; // Get method. size_t BufferedInputStream::get(StreamInterface *dest, size_t max_size, const char *delim, bool keep_delim) { putOperatorStream put_op(dest); return templatizedGet(put_op, max_size, delim, keep_delim); } // Operator for put data into a char buffer. struct putOperatorBuffer { char *dest; putOperatorBuffer(char *dest) : dest(dest) { } size_t operator()(char *buffer, size_t len) { memcpy(dest, buffer, len); return len; } bool hasError() const { return false; } }; // Get method. size_t BufferedInputStream::get(char *dest, size_t max_size, const char *delim, bool keep_delim) { putOperatorBuffer put_op(dest); return templatizedGet(put_op, max_size, delim, keep_delim); } size_t BufferedInputStream::put(StreamInterface *source, size_t size) { char *buf = new char[size]; size_t source_len = 0; while( !this->hasError() && source->good() && source_len < size ) { size_t len = source->get(buf + source_len, size - source_len, 0); source_len += len; } size_t ret_value = put(buf, source_len); delete[] buf; return ret_value; } size_t BufferedInputStream::put(const char *source) { return put(source, strlen(source)); } size_t BufferedInputStream::put(const char *source, size_t size) { // TODO: control errors return privateWrite(source, size); } int BufferedInputStream::printf(const char *format, ...) { va_list arg; char *aux_buffer; size_t len; va_start(arg, format); if (vasprintf(&aux_buffer, format, arg) < 0) { ERROR_EXIT(256, "Problem creating auxiliary buffer\n"); } len = strlen(aux_buffer); if (len > 0) len = put(aux_buffer, len); free(aux_buffer); return len; } bool BufferedInputStream::eof() const { return (in_buffer_pos == in_buffer_len) && privateEof(); } off_t BufferedInputStream::seek(int whence, long offset) { if (whence == SEEK_CUR) { off_t real_pos = privateSeek(SEEK_CUR, 0); off_t current_pos = real_pos - (in_buffer_len - in_buffer_pos); if (offset == 0) return current_pos; offset -= (real_pos - current_pos); } in_buffer_pos = in_buffer_len = 0; return privateSeek(whence, offset); } } april-ann-0.4.1/packages/basics/aprilio/c_src/buffered_stream.h000066400000000000000000000137241263004425400244640ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef BUFFERED_STREAM_H #define BUFFERED_STREAM_H #include #include #include "constString.h" #include "error_print.h" #include "referenced.h" #include "stream.h" #include "unused_variable.h" namespace AprilIO { /** * @brief A specialization of StreamBuffer which defines a new interface for * streams which need both, an input and an output buffer. * * @note This class is abstract, it cannot be instantiated. */ class BufferedStream : public StreamBuffer { public: /// The constructor allocates input/output buffers of @c buf_size. BufferedStream(size_t buf_size = BUFSIZ); /// Destructor. virtual ~BufferedStream(); // virtual bool isOpened() const = 0; virtual void close(); virtual off_t seek(int whence = SEEK_CUR, long offset = 0); virtual void flush(); virtual int setvbuf(int mode, size_t size); // virtual bool hasError() const = 0; // virtual const char *getErrorMsg() const = 0; protected: /// Returns a buffer for input data and indicates its size at @c buf_len. virtual const char *nextInBuffer(size_t &buf_len); /// Returns a buffer for output data and indicates its size at @c buf_len. virtual char *nextOutBuffer(size_t &buf_len); /// Reads from the real stream and puts data into the given buffer. virtual ssize_t fillBuffer(char *dest, size_t max_size) = 0; /// Writes the given buffer into the real stream. virtual ssize_t flushBuffer(const char *source, size_t max_size) = 0; /// Closes the real stream. virtual void closeStream() = 0; /// Executes seek operation to the real stream. virtual off_t seekStream(int whence, long offset) = 0; /// Returns true if the real stream is at EOF. virtual bool eofStream() const = 0; private: /// Reading buffer char *in_buffer; /// Writing buffer char *out_buffer; /// Reserved size of the buffer size_t max_buffer_len; }; ///////////////////////////////////////////////////////// /** * @brief Generic stream with buffer for input but not for output. * * @note This class is abstract, it cannot be instantiated. */ class BufferedInputStream : public AprilIO::StreamInterface { public: /// Constructor with @c buf_size input buffer. BufferedInputStream(size_t buf_size = DEFAULT_BUFFER_SIZE); /// Destructor. virtual ~BufferedInputStream(); virtual bool good() const; virtual size_t get(StreamInterface *dest, const char *delim = 0, bool keep_delim = false); virtual size_t get(StreamInterface *dest, size_t max_size, const char *delim = 0, bool keep_delim = false); virtual size_t get(char *dest, size_t max_size, const char *delim = 0, bool keep_delim = false); virtual size_t put(StreamInterface *source, size_t size); virtual size_t put(const char *source, size_t size); virtual size_t put(const char *source); virtual int printf(const char *format, ...); virtual bool eof() const; virtual off_t seek(int whence=SEEK_CUR, long offset=0); // virtual bool isOpened() const = 0; // virtual void close() = 0; // virtual void flush() = 0; // virtual int setvbuf(int mode, size_t size) = 0; // virtual bool hasError() const = 0; // virtual const char *getErrorMsg() const = 0; protected: /// Returns if the real stream EOF has been received. virtual bool privateEof() const = 0; /// Writes data into the real stream. virtual size_t privateWrite(const char *buf, size_t size) = 0; /// Reads data from the real stream. virtual size_t privateRead(char *buf, size_t max_size) = 0; /// Moves the real stream pointer. virtual off_t privateSeek(int whence, long offset) = 0; private: /// Default input buffer size, it must be a large size because this class is /// used for reading compressed files. static const size_t DEFAULT_BUFFER_SIZE = 4*1024*1024; // 4M /// Input buffer. char *in_buffer; size_t in_buffer_pos, ///< Input buffer position pointer. in_buffer_len, ///< Input buffer length. max_buffer_size; ///< Input buffer maximum size. /// Auxiliary method which reads data into the input buffer. void prepareInBufferData(); /// Auxiliary method which removes delimitiers from buffer left part. void trimInBuffer(const char *delim); /** * @brief Auxiliary method which allow to implement get() methods in a * generic way. * * @param putOp - A class or struct with operator() implemented, and with a * @c hasError method. The operator() allows to put data into the stream. * * @param max_size - Maximum size allowed to the get function. * * @param delim - A list of delimitiers. * * @param keep_delim - A boolean indicating if the delimitier must be keep * or not in the buffer. * * @return The number of bytes read from the stream. */ template size_t templatizedGet(T &putOp, size_t max_size, const char *delim, bool keep_delim); }; } // namespace AprilIO #endif // BUFFERED_STREAM_H april-ann-0.4.1/packages/basics/aprilio/c_src/c_string.cc000066400000000000000000000107331263004425400232720ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "april_assert.h" #include "c_string.h" namespace AprilIO { CStringStream::CStringStream() : StreamMemory(), in_pos(0), out_pos(0), eof(false) { data.reserve(StreamMemory::BLOCK_SIZE); } CStringStream::CStringStream(const AprilUtils::string &str) : StreamMemory(), data(str), in_pos(0), out_pos(data.size()), eof(false) { } CStringStream::CStringStream(const char *str, size_t size) : StreamMemory(), data(str, size), in_pos(0), out_pos(size), eof(false) { } CStringStream::~CStringStream() { close(); } AprilUtils::constString CStringStream::getConstString() const { return AprilUtils::constString(data.c_str(), size()); } void CStringStream::swapString(AprilUtils::string &other) { data.swap(other); } char *CStringStream::releaseString() { resetBuffers(); in_pos = out_pos = 0; return data.release(); } bool CStringStream::empty() const { return data.empty(); } size_t CStringStream::size() const { return data.size(); } size_t CStringStream::capacity() const { return data.capacity()-1; } char CStringStream::operator[](size_t pos) const { april_assert(pos < size()); return data[pos]; } char &CStringStream::operator[](size_t pos) { april_assert(pos < size()); return data[pos]; } void CStringStream::clear() { resetBuffers(); data.clear(); in_pos = out_pos = 0; } int CStringStream::push(lua_State *L) { lua_pushlstring(L, data.c_str(), size()); return 1; } bool CStringStream::isOpened() const { return true; } void CStringStream::close() { flush(); // FIXME: closed = true; ??? } off_t CStringStream::seek(int whence, long offset) { if (whence == SEEK_CUR && offset == 0) return size(); off_t aux_pos = 0; switch(whence) { case SEEK_SET: aux_pos = offset; break; case SEEK_CUR: aux_pos = out_pos + getOutBufferPos() + offset; break; case SEEK_END: aux_pos = size() + offset; break; } ERROR_EXIT(128, "NOT IMPLEMENTED BEHAVIOR\n"); if (aux_pos < 0) aux_pos = 0; else if (static_cast(aux_pos) > size()) { aux_pos = static_cast(size()); } in_pos = out_pos = static_cast(aux_pos); return aux_pos; } void CStringStream::flush() { size_t new_size = out_pos + getOutBufferPos(); // april_assert(capacity() >= new_size); if (size() < new_size+1) { data.reserve(new_size+1); data.resize(new_size); } data[size()] = '\0'; if (in_pos < size()) eof = false; } int CStringStream::setvbuf(int mode, size_t size) { UNUSED_VARIABLE(mode); UNUSED_VARIABLE(size); return 0; } bool CStringStream::hasError() const { return false; } const char *CStringStream::getErrorMsg() const { return StreamInterface::NO_ERROR_STRING; } const char *CStringStream::nextInBuffer(size_t &buf_len) { april_assert(size() >= in_pos + getInBufferPos()); in_pos += getInBufferPos(); buf_len = size() - in_pos; if (buf_len == 0u) eof = true; return data.c_str() + in_pos; } char *CStringStream::nextOutBuffer(size_t &buf_len) { out_pos += getOutBufferPos(); if (out_pos >= capacity()) { // NOTE: Here we use data.capacity() which is capacity()+1. data.reserve(data.capacity() << 1); in_pos += getInBufferPos(); resetBuffers(); } buf_len = capacity() - out_pos; return data.begin() + out_pos; } bool CStringStream::eofStream() const { return eof; } void CStringStream::moveOutBuffer(size_t len) { StreamBuffer::moveOutBuffer(len); flush(); } } // namespace AprilIO april-ann-0.4.1/packages/basics/aprilio/c_src/c_string.h000066400000000000000000000044711263004425400231360ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef C_STRING_H #define C_STRING_H #include "mystring.h" #include "stream_memory.h" namespace AprilIO { /** * @brief A class which works as a file in memory using C strings. * * @note The string is ended with a '\0' in order to ensure safe operations. */ class CStringStream : public StreamMemory { AprilUtils::string data; size_t in_pos, out_pos; bool eof; public: CStringStream(); CStringStream(const AprilUtils::string &str); CStringStream(const char *str, size_t size); virtual ~CStringStream(); AprilUtils::constString getConstString() const; void swapString(AprilUtils::string &other); char *releaseString(); const char *c_str() const { return data.c_str(); } virtual bool empty() const; virtual size_t size() const; virtual size_t capacity() const; virtual char operator[](size_t pos) const; virtual char &operator[](size_t pos); virtual void clear(); virtual int push(lua_State *L); virtual bool isOpened() const; virtual void close(); virtual off_t seek(int whence = SEEK_CUR, long offset = 0); virtual void flush(); virtual int setvbuf(int mode, size_t size); virtual bool hasError() const; virtual const char *getErrorMsg() const; protected: virtual const char *nextInBuffer(size_t &buf_len); virtual char *nextOutBuffer(size_t &buf_len); virtual bool eofStream() const; virtual void moveOutBuffer(size_t len); }; } // namespace AprilIO #endif // LUA_STRING_H april-ann-0.4.1/packages/basics/aprilio/c_src/file_stream.cc000066400000000000000000000073711263004425400237600ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include extern "C" { #include #include #include #include } #include "constString.h" #include "file_stream.h" namespace AprilIO { template T FileStream::checkReturnValue(T ret_value) { errnum = (ret_value < 0) ? errno : 0; return ret_value; } ssize_t FileStream::fillBuffer(char *dest, size_t max_size) { ssize_t ret_value, total_size = 0; do { size_t len = max_size - total_size; if ((ret_value = read(fd, dest + total_size, len)) > 0) { total_size += ret_value; } else if (ret_value == 0) is_eof = true; } while( checkReturnValue(ret_value)<0 && errnum==EINTR && total_size < static_cast(max_size) ); return (errnum==0) ? total_size : ret_value; } ssize_t FileStream::flushBuffer(const char *source, size_t max_size) { ssize_t ret_value=0, total_size = 0; if (flags & (O_RDWR | O_WRONLY)) { do { if ((ret_value = write(fd, source, max_size)) > 0) total_size += ret_value; } while( checkReturnValue(ret_value)<0 && errnum==EINTR ); } return (errnum==0) ? total_size : ret_value; } void FileStream::closeStream() { seekStream(SEEK_CUR, -getInBufferAvailableSize()); if (checkReturnValue(::close(fd)) == 0) fd = -1; } off_t FileStream::seekStream(int whence, long offset) { is_eof = false; return checkReturnValue(lseek(fd, offset, whence)); } FileStream::FileStream(const char *path, const char *mode) : BufferedStream(), errnum(0), is_eof(false) { AprilUtils::constString mode_cstr(mode); if (mode_cstr.empty() || mode_cstr == "r") { flags = O_RDONLY; } else if (mode_cstr == "r+") { flags = O_RDWR; } else if (mode_cstr == "w") { flags = O_WRONLY | O_CREAT | O_TRUNC; } else if (mode_cstr == "w+") { flags = O_RDWR | O_CREAT | O_TRUNC; } else if (mode_cstr == "a") { flags = O_WRONLY | O_APPEND; } else if (mode_cstr == "a+") { flags = O_RDWR | O_CREAT | O_APPEND; } else { flags = 0; ERROR_EXIT1(128, "Unknown given mode string '%s'\n", mode); } fd = checkReturnValue(open(path, flags, S_IRUSR | S_IWUSR | S_IRGRP | S_IWGRP | S_IROTH)); } FileStream::FileStream(FILE *f) : BufferedStream(), errnum(0), is_eof(false) { fflush(f); fd = checkReturnValue(dup(::fileno(f))); flags = fcntl(fd, F_GETFL); seekStream(SEEK_SET, ftell(f)); } FileStream::FileStream(int f) : BufferedStream(), errnum(0), is_eof(false) { fd = checkReturnValue(dup(f)); flags = fcntl(fd, F_GETFL); } FileStream::~FileStream() { close(); } bool FileStream::isOpened() const { return fd >= 0; } bool FileStream::eofStream() const { return is_eof; } bool FileStream::hasError() const { return errnum != 0; } const char *FileStream::getErrorMsg() const { return strerror(errnum); } } april-ann-0.4.1/packages/basics/aprilio/c_src/file_stream.h000066400000000000000000000046121263004425400236150ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef FILE_STREAM_H #define FILE_STREAM_H #include #include #include "handled_stream.h" #include "error_print.h" #include "referenced.h" #include "stream.h" #include "buffered_stream.h" #include "unused_variable.h" namespace AprilIO { /** * @brief Specialization of BufferedStream and HandledStreamInterface for * input/output operations into a disk file. */ class FileStream : public BufferedStream, public HandledStreamInterface { int fd, ///< File descriptor. errnum, ///< Last error number. flags; ///< Flags given at open function. bool is_eof; ///< Indicator of EOF. /// Auxiliary method which allow to process returned values from C POSIX /// functions. template T checkReturnValue(T ret_value); protected: virtual ssize_t fillBuffer(char *dest, size_t max_size); virtual ssize_t flushBuffer(const char *source, size_t max_size); virtual void closeStream(); virtual off_t seekStream(int whence, long offset); virtual bool eofStream() const; public: /// Constructor from a path and a mode, in the same way as @c fopen. FileStream(const char *path, const char *mode=0); /// Constructor from a C @c FILE struct. FileStream(FILE *f); /// Constructor from a C file descriptor. FileStream(int fd); /// Destructor virtual ~FileStream(); int fileno() const { return fd; } virtual bool isOpened() const; virtual bool hasError() const; virtual const char *getErrorMsg() const; }; } // namespace AprilIO #endif // STREAM_BUFFER_H april-ann-0.4.1/packages/basics/aprilio/c_src/handled_stream.h000066400000000000000000000026401263004425400242740ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef HANDLED_STREAM_H #define HANDLED_STREAM_H #include "stream.h" namespace AprilIO { /** * @brief Introduces abstract methods useful for streams based on file handler * descriptor. * * @note It is not derived from StreamInterface so any derived class must be * also derived from any kind of StreamInterface classes. */ class HandledStreamInterface { public: HandledStreamInterface() { } virtual ~HandledStreamInterface() { } /// Returns the underlying file handler descriptor. virtual int fileno() const = 0; }; } // namespace AprilIO #endif // HANDLED_STREAM_H april-ann-0.4.1/packages/basics/aprilio/c_src/lua_string.cc000066400000000000000000000145751263004425400236410ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "april_assert.h" #include "lua_string.h" namespace AprilIO { OutputLuaStringStream::OutputLuaStringStream(lua_State *L, size_t block_size) : L(L), block_size(block_size), total_size(0), closed(false) { luaL_buffinit(L, &lua_buffer); out_buffer = new char[block_size]; } OutputLuaStringStream::~OutputLuaStringStream() { close(); delete[] out_buffer; } bool OutputLuaStringStream::empty() const { return total_size == 0u; } size_t OutputLuaStringStream::size() const { return total_size; } char &OutputLuaStringStream::operator[](size_t pos) { UNUSED_VARIABLE(pos); ERROR_EXIT(128, "NOT IMPLEMENTED\n"); return StreamInterface::DUMMY_CHAR; } void OutputLuaStringStream::clear() { if (total_size > 0) { close(); closed = false; luaL_buffinit(L, &lua_buffer); resetBuffers(); total_size = 0; } } bool OutputLuaStringStream::isOpened() const { return !closed; } void OutputLuaStringStream::close() { if (!closed && out_buffer != 0) { flush(); closed = true; } } off_t OutputLuaStringStream::seek(int whence, long offset) { if (whence == SEEK_CUR && offset == 0) return total_size; ERROR_EXIT(128, "NOT IMPLEMENTED BEHAVIOR\n"); return 0; } int OutputLuaStringStream::push(lua_State *L) { if (L != this->L) { ERROR_EXIT(128, "Incorrect lua_State reference\n"); } flush(); UNUSED_VARIABLE(L); luaL_pushresult(&lua_buffer); return 1; } void OutputLuaStringStream::flush() { if (getOutBufferPos() > 0) { total_size += getOutBufferPos(); luaL_addlstring(&lua_buffer, out_buffer, getOutBufferPos()); resetOutBuffer(); } } int OutputLuaStringStream::setvbuf(int mode, size_t size) { UNUSED_VARIABLE(mode); UNUSED_VARIABLE(size); return 0; } bool OutputLuaStringStream::hasError() const { return false; } const char *OutputLuaStringStream::getErrorMsg() const { return StreamInterface::NO_ERROR_STRING; } const char *OutputLuaStringStream::nextInBuffer(size_t &buf_len) { buf_len=0; return 0; } char *OutputLuaStringStream::nextOutBuffer(size_t &buf_len) { buf_len = block_size - getOutBufferPos(); return out_buffer + getOutBufferPos(); } bool OutputLuaStringStream::eofStream() const { return !isOpened(); } void OutputLuaStringStream::moveOutBuffer(size_t len) { StreamBuffer::moveOutBuffer(len); flush(); } /////////////////////////////////////////////////////////////////////////// InputLuaStringStream::InputLuaStringStream(lua_State *L, int pos) : L(L), data_pos(0) { if (!lua_isstring(L, pos)) { ERROR_EXIT(256, "Needs a Lua string argument\n"); } total_size = static_cast(luaL_len(L, pos)); /* FIXME: check this issue in future Lua versions if (total_size < 15u) { ERROR_EXIT(128, "Strings larger than 15 bytes are needed to " "avoid fast string optimization of modern Lua versions\n"); } */ lua_pushvalue(L, pos); // put string into registry to avoid garbage collection ref = luaL_ref(L, LUA_REGISTRYINDEX); // get the pointer the stack data = lua_tostring(L, pos); } InputLuaStringStream::~InputLuaStringStream() { close(); } bool InputLuaStringStream::empty() const { return total_size == 0u; } size_t InputLuaStringStream::size() const { return total_size; } char InputLuaStringStream::operator[](size_t pos) const { april_assert(pos < total_size); return data[pos]; } int InputLuaStringStream::push(lua_State *L) { if (L != this->L) { ERROR_EXIT(128, "Incorrect lua_State reference\n"); } lua_rawgeti(L, LUA_REGISTRYINDEX, ref); return 1; } bool InputLuaStringStream::isOpened() const { return ref != LUA_NOREF; } void InputLuaStringStream::close() { if (ref != LUA_NOREF) { luaL_unref(L, LUA_REGISTRYINDEX, ref); ref = LUA_NOREF; data = 0; total_size = 0; } } off_t InputLuaStringStream::seek(int whence, long offset) { off_t aux_pos = data_pos; switch(whence) { case SEEK_SET: aux_pos = offset; break; case SEEK_CUR: aux_pos += getInBufferPos() + offset; break; case SEEK_END: aux_pos = total_size + offset; break; } if (aux_pos < 0) aux_pos = 0; else if (static_cast(aux_pos) > total_size) { aux_pos = static_cast(total_size); } data_pos = aux_pos; resetBuffers(); return aux_pos; } int InputLuaStringStream::setvbuf(int mode, size_t size) { UNUSED_VARIABLE(mode); UNUSED_VARIABLE(size); return 0; } bool InputLuaStringStream::hasError() const { return false; } const char *InputLuaStringStream::getErrorMsg() const { return StreamInterface::NO_ERROR_STRING; } const char *InputLuaStringStream::nextInBuffer(size_t &buf_len) { data_pos = data_pos + getInBufferPos(); april_assert(data_pos <= total_size); buf_len = total_size - data_pos; return data + data_pos; } char *InputLuaStringStream::nextOutBuffer(size_t &buf_len) { buf_len = 0; return 0; } bool InputLuaStringStream::eofStream() const { return data_pos >= total_size; } void InputLuaStringStream::retrieveStringFromRegistry(lua_State *L) { if (L != this->L) ERROR_EXIT(256, "Incorrect Lua state given\n"); lua_rawgeti(L, LUA_REGISTRYINDEX, ref); data = lua_tostring(L, -1); } } // namespace AprilIO april-ann-0.4.1/packages/basics/aprilio/c_src/lua_string.h000066400000000000000000000110461263004425400234710ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LUA_STRING_H #define LUA_STRING_H extern "C" { #include "lauxlib.h" #include "lualib.h" #include "lua.h" } #include "stream_memory.h" namespace AprilIO { /** * @brief A class which generates a Lua string on-the-fly using small * intermediate C strings. * * @note The string is generated by adding data to a @c luaL_Buffer. * * @note Never instantiate this in Lua, it needs a Lua stack in C to work and * it is not safe to reuse the same object between different C calls from Lua. */ class OutputLuaStringStream : public StreamMemory { lua_State *L; ///< @c lua_State where the string is allocated. const size_t block_size; ///< Default size of the written block. size_t total_size; ///< Total size written until the moment. luaL_Buffer lua_buffer; ///< A Lua string buffer allocated at @c L. char *out_buffer; ///< A string buffer where data is written. bool closed; ///< Closed indicator flag. public: /// Constructor from a @c lua_State and a @c block_size. OutputLuaStringStream(lua_State *L, size_t block_size=StreamMemory::BLOCK_SIZE); /// Destructor virtual ~OutputLuaStringStream(); WRITE_ONLY_STREAM(OutputLuaStringStream); WRITE_ONLY_STREAM_MEMORY(OutputLuaStringStream); virtual bool empty() const; virtual size_t size() const; virtual char &operator[](size_t pos); virtual void clear(); virtual int push(lua_State *L); virtual bool isOpened() const; virtual void close(); virtual off_t seek(int whence = SEEK_CUR, long offset = 0); virtual void flush(); virtual int setvbuf(int mode, size_t size); virtual bool hasError() const; virtual const char *getErrorMsg() const; protected: virtual const char *nextInBuffer(size_t &buf_len); virtual char *nextOutBuffer(size_t &buf_len); virtual bool eofStream() const; void moveOutBuffer(size_t len); }; /** * @brief A class which reads from a Lua string. * * @note A reference to the string is allocated at the registry in order to * avoid garbage collection. * * @note This class uses a hook in the binding to retrieve the Lua string * from the registry every time a C call is produced. This behavior is * implemented by the lua_toInputLuaStringStream() function. * * @note This class can modify the stack by adding a reference to the string * allocated at the registry. */ class InputLuaStringStream : public StreamMemory { lua_State *L; ///< The @c lua_State where the string is allocated. int ref; ///< A Lua reference to the registry. const char *data; ///< The string pointer in C. size_t total_size, ///< Length of the string. data_pos; ///< Current position for read. public: /// Constructor from @c lua_State and the stack @c pos of the string. InputLuaStringStream(lua_State *L, int pos); /// Destructor virtual ~InputLuaStringStream(); READ_ONLY_STREAM(InputLuaStringStream); READ_ONLY_STREAM_MEMORY(InputLuaStringStream); virtual bool empty() const; virtual size_t size() const; virtual char operator[](size_t pos) const; virtual int push(lua_State *L); virtual bool isOpened() const; virtual void close(); virtual off_t seek(int whence = SEEK_CUR, long offset = 0); virtual int setvbuf(int mode, size_t size); virtual bool hasError() const; virtual const char *getErrorMsg() const; void retrieveStringFromRegistry(lua_State *L); protected: virtual const char *nextInBuffer(size_t &buf_len); virtual char *nextOutBuffer(size_t &buf_len); virtual bool eofStream() const; }; } // namespace AprilIO #endif // LUA_STRING_H april-ann-0.4.1/packages/basics/aprilio/c_src/serializable.h000066400000000000000000000104531263004425400237710ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SERIALIZABLE_H #define SERIALIZABLE_H extern "C" { #include "lauxlib.h" #include "lualib.h" #include "lua.h" } #include "base.h" #include "error_print.h" #include "lua_table.h" #include "mystring.h" #include "referenced.h" #include "stream.h" #include "unused_variable.h" namespace AprilIO { /// Uses Lua util.serialize function to write the given object. template void serialize(T object, StreamInterface *dest) { lua_State *L = Base::getAndCheckGlobalLuaState(); lua_getglobal(L, "util"); lua_getfield(L, -1, "serialize"); AprilUtils::LuaTable::pushInto(L, object); AprilUtils::LuaTable::pushInto(L, dest); if (lua_pcall(L, 2, 0, 0) != LUA_OK) { AprilUtils::string str(lua_tostring(L,-1)); lua_pop(L,1); ERROR_EXIT1(128, "%s", str.c_str()); } lua_pop(L, 1); } /// Uses Lua util.serialize function to write the given object into a string; template AprilUtils::string serialize(T object) { lua_State *L = Base::getAndCheckGlobalLuaState(); lua_getglobal(L, "util"); lua_getfield(L, -1, "serialize"); AprilUtils::LuaTable::pushInto(L, object); if (lua_pcall(L, 2, 1, 0) != LUA_OK) { AprilUtils::string str(lua_tostring(L,-1)); lua_pop(L,1); ERROR_EXIT1(128, "%s", str.c_str()); } AprilUtils::string result(lua_tostring(L, -1)); lua_pop(L, 2); return result; } /// Uses Lua util.deserialize function to retrieve an object. template T deserialize(StreamInterface *dest) { lua_State *L = Base::getAndCheckGlobalLuaState(); lua_getglobal(L, "util"); lua_getfield(L, -1, "deserialize"); AprilUtils::LuaTable::pushInto(L, dest); if (lua_pcall(L, 1, 1, 0) != LUA_OK) { AprilUtils::string str(lua_tostring(L,-1)); lua_pop(L,1); ERROR_EXIT1(128, "%s", str.c_str()); } T obj = AprilUtils::LuaTable::convertTo(L, -1); lua_pop(L, 2); return obj; } /** * @brief This class defines the basic API for serializable classes. */ class Serializable : public Referenced { public: Serializable() : Referenced() { } virtual ~Serializable() { } // The read method needs to be implemented in derived classes. // Whatever *read(StreamInterface *dest, // const AprilUtils::LuaTable &options); /// Writes the object data into dest, and it could be retrieved by read. virtual void write(StreamInterface *dest, const AprilUtils::LuaTable &options) { UNUSED_VARIABLE(dest); UNUSED_VARIABLE(options); ERROR_EXIT(128, "Unable to use write method\n"); } /** * @brief Returns the class constructor for serialized objects. * * This method is needed in C++ to allow polymorphic calls from Lua side. */ virtual const char *luaCtorName() const { ERROR_EXIT(128, "Unable to retrieve Lua ctor name\n"); return 0; } /** * @brief Stores into an AprilUtils::LuaTable all the parameters of this * object. * * The parameters will use to serialize the object, and them will be given * to the Lua binding constructor to retrieve a serialized object. This * method is needed in C++ to allow polymorphic calls from Lua side. * * @returns The number of items pushed into Lua stack. */ virtual int exportParamsToLua(lua_State *L) { UNUSED_VARIABLE(L); return 0; } }; } // namespace AprilUtils #endif // SERIALIZABLE_H april-ann-0.4.1/packages/basics/aprilio/c_src/stream.cc000066400000000000000000000164631263004425400227630ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include #include "maxmin.h" #include "mystring.h" #include "stream.h" // #include "stream_memory.h" #include "unused_variable.h" namespace AprilIO { char StreamInterface::DUMMY_CHAR = '\0'; const char *StreamInterface::NO_ERROR_STRING = "Success"; StreamBuffer::StreamBuffer() : StreamInterface(), in_buffer(0), in_buffer_pos(0), in_buffer_len(0), out_buffer(0), out_buffer_pos(0), out_buffer_len(0) { } StreamBuffer::~StreamBuffer() { } void StreamBuffer::trimInBuffer(const char *delim, size_t max) { if (delim != 0) { size_t pos, buf_len, total=0; // size_t delim_len = strlen(delim); do { const char *buf = getInBuffer(buf_len, SIZE_MAX, 0, false); // pos = AprilUtils::strnspn(buf, buf_len, delim, delim_len); pos = 0; while(pos < buf_len && strchr(delim, buf[pos]) != 0 && total < max) ++pos,++total; moveInBuffer(pos); } while(pos == buf_len && buf_len > 0 && total < max); } } bool StreamBuffer::good() const { return isOpened() && !eof() && !hasError(); } size_t StreamBuffer::get(StreamInterface *dest, const char *delim, bool keep_delim) { return get(dest, SIZE_MAX, delim, keep_delim); } size_t StreamBuffer::get(StreamInterface *dest, size_t max_size, const char *delim, bool keep_delim) { const char *buf; size_t buf_len, dest_len=0; while( this->good() && !dest->hasError() && dest_len < max_size && (buf = getInBuffer(buf_len, max_size - dest_len, delim, keep_delim)) ) { size_t in_buffer_available_size = getInBufferAvailableSize(); size_t len = dest->put(buf, buf_len); bool has_delim = keep_delim && len>0 && strchr(delim,buf[len-1]); moveInBuffer(len); dest_len += len; // delim true condition if (has_delim || len != in_buffer_available_size) break; } if (!keep_delim) trimInBuffer(delim, 1); return dest_len; } size_t StreamBuffer::get(char *dest, size_t max_size, const char *delim, bool keep_delim) { const char *buf; size_t buf_len, dest_len=0; while( dest_len < max_size && this->good() && (buf = getInBuffer(buf_len, max_size - dest_len, delim, keep_delim)) ) { size_t in_buffer_available_size = getInBufferAvailableSize(); memcpy(dest + dest_len, buf, buf_len); bool has_delim = keep_delim && buf_len>0 && strchr(delim, buf[buf_len-1]); moveInBuffer(buf_len); dest_len += buf_len; // delim true condition if (has_delim || buf_len != in_buffer_available_size) break; } if (!keep_delim) trimInBuffer(delim, 1); return dest_len; } size_t StreamBuffer::put(StreamInterface *source, size_t size) { char *buf; size_t buf_len, source_len = 0; while( !this->hasError() && source->good() && source_len < size && (buf = getOutBuffer(buf_len, size - source_len)) ) { size_t len = source->get(buf, buf_len, 0); moveOutBuffer(len); source_len += len; } return source_len; } size_t StreamBuffer::put(const char *source, size_t size) { char *buf; size_t buf_len, source_len = 0; while( source_len < size && !this->hasError() && (buf = getOutBuffer(buf_len, size - source_len)) ) { memcpy(buf, source + source_len, buf_len); moveOutBuffer(buf_len); source_len += buf_len; } return source_len; } size_t StreamBuffer::put(const char *source) { return put(source, strlen(source)); } int StreamBuffer::printf(const char *format, ...) { va_list arg; char *aux_buffer; size_t len; va_start(arg, format); if (vasprintf(&aux_buffer, format, arg) < 0) { ERROR_EXIT(256, "Problem creating auxiliary buffer\n"); } len = strlen(aux_buffer); if (len > 0) len = put(aux_buffer, len); free(aux_buffer); return len; } bool StreamBuffer::eof() const { return (in_buffer_pos == in_buffer_len) && eofStream(); } ////////////////////////////////////////////////////////////////////////// void StreamBuffer::resetBuffers() { in_buffer_pos = in_buffer_len = 0; out_buffer_pos = out_buffer_len = 0; } void StreamBuffer::resetOutBuffer() { out_buffer_pos = out_buffer_len = 0; } size_t StreamBuffer::getInBufferPos() const { return in_buffer_pos; } size_t StreamBuffer::getOutBufferPos() const { return out_buffer_pos; } const char *StreamBuffer::getInBuffer(size_t &buffer_len, size_t max_size, const char *delim, bool keep_delim) { if (in_buffer == 0) in_buffer = nextInBuffer(in_buffer_len); buffer_len = AprilUtils::min(in_buffer_len - in_buffer_pos, max_size); if (delim != 0) { size_t pos = in_buffer_pos; size_t last = pos + buffer_len; /* pos = in_buffer_pos + AprilUtils::strncspn(in_buffer + pos, buffer_len, delim, strlen(delim)); */ while(pos < last && strchr(delim, in_buffer[pos]) == 0) ++pos; if (pos < last && keep_delim) ++pos; buffer_len = pos - in_buffer_pos; } return in_buffer + in_buffer_pos; } char *StreamBuffer::getOutBuffer(size_t &buffer_len, size_t max_size) { if (out_buffer == 0) out_buffer = nextOutBuffer(out_buffer_len); buffer_len = AprilUtils::min(out_buffer_len - out_buffer_pos, max_size); return out_buffer + out_buffer_pos; } size_t StreamBuffer::getInBufferAvailableSize() const { return in_buffer_len - in_buffer_pos; } size_t StreamBuffer::getOutBufferAvailableSize() const { return out_buffer_len - out_buffer_pos; } void StreamBuffer::moveInBuffer(size_t len) { if (len > getInBufferAvailableSize()) { ERROR_EXIT(128, "Read buffer overflow!!!\n"); } in_buffer_pos += len; if (in_buffer_pos == in_buffer_len) { in_buffer = nextInBuffer(in_buffer_len); in_buffer_pos = 0; } } void StreamBuffer::moveOutBuffer(size_t len) { if (len > getOutBufferAvailableSize()) { ERROR_EXIT(128, "Write buffer overflow!!!\n"); } out_buffer_pos += len; if (out_buffer_pos == out_buffer_len) { flush(); out_buffer = nextOutBuffer(out_buffer_len); out_buffer_pos = 0; } } } // namespace AprilIO april-ann-0.4.1/packages/basics/aprilio/c_src/stream.h000066400000000000000000000263341263004425400226230ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef STREAM_H #define STREAM_H #include #include extern "C" { #include // for SIZE_MAX (using stdint.h because cstdint needs c++11 // support) } #ifndef SIZE_MAX #include #define SIZE_MAX std::numeric_limits::max() #endif #include "constString.h" #include "error_print.h" #include "lua_table.h" #include "referenced.h" #include "unused_variable.h" #define READ_ONLY_STREAM(name) \ virtual size_t put(StreamInterface *source, size_t size) { \ UNUSED_VARIABLE(source); \ UNUSED_VARIABLE(size); \ ERROR_EXIT(128, "Read only " #name "\n"); \ return 0; \ } \ virtual size_t put(const char *source, size_t size) { \ UNUSED_VARIABLE(source); \ UNUSED_VARIABLE(size); \ ERROR_EXIT(128, "Read only " #name "\n"); \ return 0; \ } \ virtual size_t put(const char *source) { \ UNUSED_VARIABLE(source); \ ERROR_EXIT(128, "Read only " #name "\n"); \ return 0; \ } \ virtual int printf(const char *format, ...) { \ UNUSED_VARIABLE(format); \ ERROR_EXIT(128, "Read only " #name "\n"); \ return 0; \ } #define WRITE_ONLY_STREAM(name) \ virtual size_t get(StreamInterface *dest, const char *delim, \ bool keep_delim ) { \ UNUSED_VARIABLE(dest); \ UNUSED_VARIABLE(delim); \ UNUSED_VARIABLE(keep_delim); \ ERROR_EXIT(128, "Write only " #name "\n"); \ return 0; \ } \ virtual size_t get(StreamInterface *dest, size_t max_size, const char *delim, \ bool keep_delim ) { \ UNUSED_VARIABLE(dest); \ UNUSED_VARIABLE(max_size); \ UNUSED_VARIABLE(delim); \ UNUSED_VARIABLE(keep_delim); \ ERROR_EXIT(128, "Write only " #name "\n"); \ return 0; \ } \ virtual size_t get(char *dest, size_t max_size, const char *delim, \ bool keep_delim ) { \ UNUSED_VARIABLE(dest); \ UNUSED_VARIABLE(max_size); \ UNUSED_VARIABLE(delim); \ UNUSED_VARIABLE(keep_delim); \ ERROR_EXIT(128, "Write only " #name "\n"); \ return 0; \ } /** * @brief Declaration of interfaces and generic classes for input/output purposes. */ namespace AprilIO { /** * @brief The StreamInterface is the basic public interface needed to * implement a Stream. */ class StreamInterface : public Referenced { public: StreamInterface() : Referenced() { } virtual ~StreamInterface() { } /// Returns if the stream is properly opened and not EOF and no errors. virtual bool good() const = 0; /// Reads a string delimited by any of the given chars and puts it into the /// given Stream. If delim==0 then this method ends when dest->eof() is /// true. virtual size_t get(StreamInterface *dest, const char *delim = 0, bool keep_delim = false ) = 0; /// Reads a string with max_size length and delimited by any of the given /// chars and puts it into the given Stream. virtual size_t get(StreamInterface *dest, size_t max_size, const char *delim = 0, bool keep_delim = false ) = 0; /// Reads a string of a maximum given size delimited by any of the given /// chars and puts it into the given char buffer. virtual size_t get(char *dest, size_t max_size, const char *delim = 0, bool keep_delim = false ) = 0; /// Puts a string of a maximum given size taken from the given Stream. virtual size_t put(StreamInterface *source, size_t size) = 0; /// Puts a string of a maximum given size taken from the given char buffer. virtual size_t put(const char *source, size_t size) = 0; /// Puts a zero ended string, uses strlen to compute source length. virtual size_t put(const char *source) = 0; /// Writes a set of values following the given format. Equals to C printf. virtual int printf(const char *format, ...) = 0; /// Indicates if end-of-file flag is true. virtual bool eof() const = 0; ///////// ABSTRACT INTERFACE ///////// /// Indicates if the stream is correctly open. virtual bool isOpened() const = 0; /// Closes the stream. virtual void close() = 0; /// Moves the stream cursor to the given offset from given whence position. virtual off_t seek(int whence = SEEK_CUR, long offset = 0) = 0; /// Forces to write pending data at stream object. virtual void flush() = 0; /// Modifies the behavior of the buffer. virtual int setvbuf(int mode, size_t size) = 0; /// Indicates if an error has been produced. virtual bool hasError() const = 0; /// Returns an internal string with the last error message. virtual const char *getErrorMsg() const = 0; protected: static char DUMMY_CHAR; static const char *NO_ERROR_STRING; }; /** * @brief The Stream is the parent class which needs to be dervied by I/O * facilities based in input/output buffers. */ class StreamBuffer : public StreamInterface { const char *in_buffer; size_t in_buffer_pos, in_buffer_len; char *out_buffer; size_t out_buffer_pos, out_buffer_len; public: StreamBuffer(); virtual ~StreamBuffer(); virtual bool good() const; virtual size_t get(StreamInterface *dest, const char *delim = 0, bool keep_delim = false ); virtual size_t get(StreamInterface *dest, size_t max_size, const char *delim = 0, bool keep_delim = false ); virtual size_t get(char *dest, size_t max_size, const char *delim = 0, bool keep_delim = false ); virtual size_t put(StreamInterface *source, size_t size); virtual size_t put(const char *source, size_t size); virtual size_t put(const char *source); virtual int printf(const char *format, ...); virtual bool eof() const; ///////// ABSTRACT INTERFACE ///////// // virtual bool isOpened() const = 0; // virtual void close() = 0; // virtual off_t seek(int whence, long offset) = 0; // virtual void flush() = 0; // virtual int setvbuf(int mode, size_t size) = 0; // virtual bool hasError() const = 0; // virtual const char *getErrorMsg() const = 0; protected: // Auxiliary protected methods virtual void resetBuffers(); virtual size_t getInBufferPos() const; virtual size_t getOutBufferPos() const; virtual void resetOutBuffer(); /// Indicates the available data in the current input buffer. virtual size_t getInBufferAvailableSize() const; /// Indicates the available data in the current output buffer. virtual size_t getOutBufferAvailableSize() const; /** * @brief Moves input buffer current position. * * Moves the input buffer pointer a given number of bytes, when empty * buffer, this call will refill the buffer with new data from the real * stream. * * @param len - Size of the movement (<= available size). */ virtual void moveInBuffer(size_t len); /** * @brief Moves output buffer current position. * * Moves the output buffer pointer a given number of bytes, when full * buffer, this call will flush the data into the real stream. * * @param len - Size of the movement (<= available size). */ virtual void moveOutBuffer(size_t len); ///// ABSTRACT METHODS ///// virtual const char *nextInBuffer(size_t &buf_len) = 0; virtual char *nextOutBuffer(size_t &buf_len) = 0; virtual bool eofStream() const = 0; //////////////////////////// private: void trimInBuffer(const char *delim, size_t max=SIZE_MAX); /** * @brief Returns a pointer to the current input buffer with at most * max_size bytes delimited by the given string of delimitiers. * * @param[out] buffer_len - Size of the returned pointer (<= max_size). * @param max_size - The maximum size required for the buffer. * @param delim - A string with delimitiers. * @param keep_delim - Indicates if keep or not the delimitier at the end. * * @return A pointer to input buffer position. */ virtual const char *getInBuffer(size_t &buffer_len, size_t max_size, const char *delim, bool keep_delim); /** * @brief Returns a pointer to the current output buffer with at most * max_size. * * @param[out] buffer_len - Size of the returned pointer (<= max_size). * @param max_size - The maximum size required for the buffer. * * @return A pointer to input buffer position. */ virtual char *getOutBuffer(size_t &buffer_len, size_t max_size); }; } // namespace AprilIO DECLARE_LUA_TABLE_BIND_SPECIALIZATION(AprilIO::StreamInterface); #endif // STREAM_H april-ann-0.4.1/packages/basics/aprilio/c_src/stream_memory.cc000066400000000000000000000027511263004425400243460ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "stream_memory.h" namespace AprilIO { size_t extractLineFromStream(StreamInterface *source, StreamMemory *dest, bool keep_delim) { dest->clear(); return source->get(dest, "\n\r", keep_delim); } size_t extractULineFromStream(StreamInterface *source, StreamMemory *dest, bool keep_delim) { do { dest->clear(); source->get(dest, "\n\r", keep_delim); } while ( ((dest->size() > 0) && ((*dest)[0] == '#')) || // ignore empty lines ((dest->size() == 1) && ((*dest)[0] == '\r' || (*dest)[0] == '\n')) ); return dest->size(); } } // namespace AprilIO april-ann-0.4.1/packages/basics/aprilio/c_src/stream_memory.h000066400000000000000000000074621263004425400242140ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef STREAM_MEMORY_H #define STREAM_MEMORY_H extern "C" { #include "lauxlib.h" #include "lualib.h" #include "lua.h" #include // for SIZE_MAX (using stdint.h because cstdint needs c++11 // support) } #include #include #include "constString.h" #include "error_print.h" #include "referenced.h" #include "stream.h" #include "unused_variable.h" #define WRITE_ONLY_STREAM_MEMORY(name) \ virtual char operator[](size_t pos) const { \ UNUSED_VARIABLE(pos); \ ERROR_EXIT(128, "Read only " #name "\n"); \ return 0; \ } #define READ_ONLY_STREAM_MEMORY(name) \ virtual char &operator[](size_t pos) { \ UNUSED_VARIABLE(pos); \ ERROR_EXIT(128, "Write only " #name "\n"); \ return StreamMemory::DUMMY_CHAR; \ } \ virtual void clear() { \ ERROR_EXIT(128, "Read only " #name "\n"); \ } \ virtual void flush() { \ ERROR_EXIT(128, "Read only " #name "\n"); \ } namespace AprilIO { class StreamMemory; /// Returns a whole line of the stream (a string delimited by \n). size_t extractLineFromStream(StreamInterface *source, StreamMemory *dest, bool keep_delim = false); /// Returns a whole line of the stream (a string delimited by \n), but /// avoiding lines which begins with #. Lines beginning with # are taken as /// commented lines. size_t extractULineFromStream(StreamInterface *source, StreamMemory *dest, bool keep_delim = false); /////////////////////////////////////////////////////////////////////////// /** * @brief Specialization of StreamBuffer for streams which are allocated at * memory, as C strings or Lua strings. */ class StreamMemory : public StreamBuffer { public: static const size_t BLOCK_SIZE = 1024; StreamMemory() { } virtual ~StreamMemory() { } /// Empty flag of the underlying string. virtual bool empty() const = 0; /// Size of the underlying string. virtual size_t size() const = 0; /// Random access operator. virtual char operator[](size_t pos) const = 0; /// Random access operator. virtual char &operator[](size_t pos) = 0; /// Sets to zero the string and starts again. virtual void clear() = 0; /// Pushes the current data into the given Lua stack. virtual int push(lua_State *L) = 0; }; } // namespace AprilIO #endif // STREAM_MEMORY_H april-ann-0.4.1/packages/basics/aprilio/lua_src/000077500000000000000000000000001263004425400215065ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/aprilio/lua_src/april_io.lua000066400000000000000000000072611263004425400240150ustar00rootroot00000000000000-- modificamos el io.open aprilio = aprilio or {} local open_by_extension = { } local io_old_open = io.open aprilio.open = function(name, ...) local open = (name and open_by_extension[string.get_extension(name)]) or io_old_open local x,msg = open(name, ...) if not x then return x,msg end if not class.is_a(x, aprilio.package) then return x end if x:number_of_files() ~= 1 then return nil,"Opening package %s requires 1 and only 1 file in it"%{name} end return x:open(1) end io.open = aprilio.open local io_old_lines = io.lines aprilio.lines = function(name, ...) if not name then return io_old_lines() end local f = april_assert(io.open(name), "cannot open file '%s'", name) assert(f.lines, "lines method not implemented to this kind of file") local it = f:lines(...) return function() local result = table.pack(it()) if #result == 0 then f:close() else return table.unpack(result) end end end io.lines = aprilio.lines function aprilio.register_open_by_extension(ext, func) open_by_extension[ext] = func end class.extend(aprilio.stream, "lines", function(self, ...) local arg = { ... } return function() return self:read(table.unpack(arg)) end end) aprilio.lua_open = io_old_open aprilio.lua_lines = io_old_lines class.extend(aprilio.package, "files", function(self) local i,n = 0,self:number_of_files() return function() if i 0 then local needs_unpack = true if params.n == 1 then params = params[1] needs_unpack=false else params.n = nil end params_str = table.tostring(params, ...) if needs_unpack then params_str = "table.unpack(%s)"%{params_str} end end return "%s(%s)"% { self:ctor_name(), params_str } end class.extend(aprilio.serializable, "to_lua_string", to_lua_string) local lua_serializable, lua_serializable_methods = class("aprilio.lua_serializable") -- global declaration aprilio.lua_serializable = lua_serializable lua_serializable_methods.to_lua_string = to_lua_string lua_serializable_methods.ctor_name = function() error("Serialization not implemented") end lua_serializable_methods.ctor_params = function() error("Serialization not implemented") end lua_serializable_methods.ctor_requires = function() return {} end lua_serializable_methods.save = util.serialize lua_serializable.load = util.deserialize --------------------------------------------------------------------------- april_set_doc(aprilio.serializable.."write", { class = "method", summary = "It allows to store an object into a stream.", description ={ "It allows to store an object into a stream.", "It uses a format expected by read method.", }, params = { { "A aprilio.stream instance. If not given any,", "the object is serialized to a Lua string", }, "A Lua table with options [optional].", }, outputs = { }, }) april_set_doc(aprilio.serializable.."write", { class = "method", summary = "It allows to store an object into a Lua string.", description ={ "It allows to store an object into a Lua string.", "It uses a format expected by read method.", }, params = { "A Lua table with options [optional].", }, outputs = { "A Lua string with the serialization result.", }, }) return aprilio april-ann-0.4.1/packages/basics/aprilio/package.lua000066400000000000000000000023241263004425400221550ustar00rootroot00000000000000 package{ name = "aprilio", version = "1.0", depends = { "util" }, keywords = { "aprilio" }, description = "modifys io.open behavior", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test_april_io.lua", }, }, c_unit_test{ file = { "test/test_april_io.cc" }, }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_april_io.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_april_io.lua.cc", dest_dir = "build", } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/aprilio/test/000077500000000000000000000000001263004425400210355ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/aprilio/test/test_april_io.cc000066400000000000000000000126711263004425400242100ustar00rootroot00000000000000#include #include #include "file_stream.h" #include "c_string.h" #include "gtest.h" #include "smart_ptr.h" const char *FILE1 = "/tmp/APRIL_IO_TEST1.txt"; const char *DATA = "some data\n\nin several lines\n\n\n\nto test streams.\n"; const char *LINE1 = "some data"; const char *LINE2 = "in several lines"; const char *LINE3 = "to test streams."; const size_t N = strlen(DATA); const size_t N1 = strlen(LINE1); const size_t N2 = strlen(LINE2); const size_t N3 = strlen(LINE3); const size_t REP = 10000; namespace AprilIO { TEST(FileStream, ConstructorTests) { AprilUtils::SharedPtr ptr; remove(FILE1); // Constructor read-only open failure ptr.reset(new FileStream(FILE1, "r")); EXPECT_TRUE( ptr->hasError() ); EXPECT_FALSE( ptr->isOpened() ); // Constructor write-only ptr.reset(new FileStream(FILE1, "w")); EXPECT_FALSE( ptr->hasError() ); EXPECT_TRUE( ptr->isOpened() ); ptr->close(); EXPECT_FALSE( ptr->hasError() ); // Constructor from opened FILE FILE *file = tmpfile(); ptr.reset(new FileStream(file)); EXPECT_FALSE( ptr->hasError() ); EXPECT_TRUE( ptr->isOpened() ); ptr->close(); EXPECT_FALSE( ptr->hasError() ); fclose(file); // Constructor from opened file descriptor char tmp_name[] = "/tmp/aXXXXXX"; int fd = mkstemp(tmp_name); EXPECT_GE( fd, 0 ); ptr.reset(new FileStream(fd)); EXPECT_FALSE( ptr->hasError() ); EXPECT_TRUE( ptr->isOpened() ); ptr->close(); EXPECT_FALSE( ptr->hasError() ); close(fd); // remove(FILE1); remove(tmp_name); } TEST(FileStream, ReadAndWrite) { AprilUtils::UniquePtr aux( new char[N+1] ); AprilUtils::SharedPtr ptr; // write of a bunch of data ptr.reset( new FileStream(FILE1, "w") ); EXPECT_FALSE( ptr->hasError() ); EXPECT_TRUE( ptr->isOpened() ); EXPECT_TRUE( ptr->good() ); for (unsigned int i=0; iput(DATA, N), N ); EXPECT_FALSE( ptr->hasError() ); } ptr->close(); EXPECT_FALSE( ptr->hasError() ); // read of previous bunch of data ptr.reset( new FileStream(FILE1, "r")); EXPECT_FALSE( ptr->hasError() ); EXPECT_TRUE( ptr->isOpened() ); EXPECT_TRUE( ptr->good() ); for (unsigned int i=0; ieof() ); EXPECT_EQ( ptr->get(aux.get(), N), N ); EXPECT_FALSE( ptr->hasError() ); aux[N] = '\0'; EXPECT_STREQ( aux.get(), DATA ); } EXPECT_EQ( ptr->get(aux.get(), 1u), 0u ); // just in case to force EOF read EXPECT_TRUE( ptr->eof() ); ptr->close(); EXPECT_FALSE( ptr->hasError() ); // read of previous bunch of data by lines ptr.reset( new FileStream(FILE1, "r")); EXPECT_FALSE( ptr->hasError() ); EXPECT_TRUE( ptr->isOpened() ); EXPECT_TRUE( ptr->good() ); for (unsigned int i=0; ieof() ); // LINE 1 EXPECT_EQ( ptr->get(aux.get(), N, "\r\n"), N1 ); EXPECT_FALSE( ptr->hasError() ); aux[N1] = '\0'; EXPECT_STREQ( aux.get(), LINE1 ); ptr->get(aux.get(), N, "\r\n"); // blankline // LINE 2 EXPECT_EQ( ptr->get(aux.get(), N, "\r\n"), N2 ); EXPECT_FALSE( ptr->hasError() ); aux[N2] = '\0'; EXPECT_STREQ( aux.get(), LINE2 ); ptr->get(aux.get(), N, "\r\n"); // blankline ptr->get(aux.get(), N, "\r\n"); // blankline ptr->get(aux.get(), N, "\r\n"); // blankline // LINE 3 EXPECT_EQ( ptr->get(aux.get(), N, "\r\n"), N3 ); EXPECT_FALSE( ptr->hasError() ); aux[N3] = '\0'; EXPECT_STREQ( aux.get(), LINE3 ); } EXPECT_TRUE( ptr->eof() ); ptr->close(); EXPECT_FALSE( ptr->hasError() ); // read into a c_string AprilUtils::SharedPtr c_str; c_str.reset( new CStringStream() ); EXPECT_TRUE( c_str->empty() ); // EXPECT_TRUE( c_str->good() ); EXPECT_EQ( c_str->size(), 0u ); EXPECT_FALSE( c_str->hasError() ); ptr.reset( new FileStream(FILE1, "r")); EXPECT_FALSE( ptr->hasError() ); EXPECT_TRUE( ptr->isOpened() ); EXPECT_TRUE( ptr->good() ); for (unsigned int i=0; ieof() ); // LINE 1 EXPECT_EQ( ptr->get(c_str.get(), "\r\n"), N1 ); EXPECT_FALSE( ptr->hasError() ); c_str->flush(); EXPECT_EQ( c_str->get(aux.get(), N1), N1 ); aux[N1] = '\0'; EXPECT_STREQ( aux.get(), LINE1 ); ptr->get(aux.get(), N, "\r\n"); // blankline // LINE 2 EXPECT_EQ( ptr->get(c_str.get(), "\r\n"), N2 ); EXPECT_FALSE( ptr->hasError() ); c_str->flush(); EXPECT_EQ( c_str->get(aux.get(), N2), N2 ); aux[N2] = '\0'; EXPECT_STREQ( aux.get(), LINE2 ); ptr->get(aux.get(), N, "\r\n"); // blankline ptr->get(aux.get(), N, "\r\n"); // blankline ptr->get(aux.get(), N, "\r\n"); // blankline // LINE 3 EXPECT_EQ( ptr->get(c_str.get(), "\r\n"), N3 ); EXPECT_FALSE( ptr->hasError() ); c_str->flush(); EXPECT_EQ( c_str->get(aux.get(), N3), N3 ); aux[N3] = '\0'; EXPECT_STREQ( aux.get(), LINE3 ); // c_string asserts EXPECT_FALSE( c_str->hasError() ); EXPECT_EQ( c_str->size(), (N1+N2+N3)*(i+1) ); } EXPECT_TRUE( ptr->eof() ); ptr->close(); EXPECT_FALSE( ptr->hasError() ); c_str->close(); // remove(FILE1); } } APRILANN_GTEST_MAIN(test_april_io) april-ann-0.4.1/packages/basics/aprilio/test/test_april_io.lua000066400000000000000000000017631263004425400244040ustar00rootroot00000000000000local check = utest.check local T = utest.test -- local lines = { "first line", "second line with more data", "third line with a lot more of data", } local lines_concat = table.concat(lines, "\n") .. "\n" local REP = 10000 -- T("CStringTest", function() local s = aprilio.stream.c_string() check.FALSE( s:eof() ) s:read(1) check.TRUE( s:eof() ) for i=1,REP do s:write(lines_concat) end check.FALSE( s:eof() ) local j = 0 for line in s:lines() do check.eq( line, lines[j+1] ) j = (j+1) % #lines end check.TRUE( s:eof() ) end) -- T("InputLuaStringTest", function() local s = aprilio.stream.input_lua_string(lines_concat) check.FALSE( s:eof() ) local j = 0 for line in s:lines() do check.eq( line, lines[j+1] ) j = (j+1) % #lines end check.TRUE( s:eof() ) end) -- T("ReadAllTest", function() local s = aprilio.stream.input_lua_string(lines_concat) local out = s:read("*a") check.eq( out, lines_concat ) end) april-ann-0.4.1/packages/basics/base/000077500000000000000000000000001263004425400173315ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/base/binding/000077500000000000000000000000001263004425400207435ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/base/binding/bind_base.lua.cc000066400000000000000000000017101263004425400237370ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_H #include "base.h" //BIND_END //BIND_STATIC_CONSTRUCTOR base_static_constructor { Base::registerGlobalLuaState(L); } //BIND_END april-ann-0.4.1/packages/basics/base/c_src/000077500000000000000000000000001263004425400204225ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/base/c_src/base.cc000066400000000000000000000025541263004425400216510ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include #include "base.h" namespace Base { static lua_State *globalL = 0; void registerGlobalLuaState(lua_State *L) { if (globalL != 0 && globalL != L) { fprintf(stderr, "FATAL ERROR: Global Lua State set twice!!!\n"); exit(128); } globalL = L; } lua_State *getGlobalLuaState() { return globalL; } lua_State *getAndCheckGlobalLuaState() { if (globalL == 0) { fprintf(stderr, "FATAL ERROR: Global Lua State not initialized!!!\n"); exit(128); } return globalL; } } april-ann-0.4.1/packages/basics/base/c_src/base.h000066400000000000000000000020241263004425400215030ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef BASE_H #define BASE_H extern "C" { #include "lua.h" } namespace Base { void registerGlobalLuaState(lua_State *L); lua_State *getGlobalLuaState(); lua_State *getAndCheckGlobalLuaState(); } #endif // BASE_H april-ann-0.4.1/packages/basics/base/lua_src/000077500000000000000000000000001263004425400207615ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/base/lua_src/base.lua000066400000000000000000000013541263004425400224010ustar00rootroot00000000000000aprilann = { _NAME = "APRIL-ANN" } make_deprecated_function = function(name, new_name, new_func) return function(...) if new_func then if new_name then io.stderr:write(debug.traceback(string.format("Warning: %s is in deprecated state, use %s instead", name, new_name))) else io.stderr:write(debug.traceback(string.format("Warning: %s is in deprecated state", name))) end io.stderr:write("\n") return new_func(...) else error(string.format("%s is in deprecated state%s", name, new_name and (", currently it is %s"%{new_name}) or "")) end end end april-ann-0.4.1/packages/basics/base/package.lua000066400000000000000000000021261263004425400214300ustar00rootroot00000000000000package{ name = "base", version = "1.0", depends = { }, keywords = { }, description = "", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_base.lua.cc" , dest_dir = "include" }, }, target{ name = "test", -- lua_unit_test{ -- file={ -- "test/test-class.lua", -- }, -- }, }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", dest_dir = "build", -- flags = "-std=c99", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_base.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/class/000077500000000000000000000000001263004425400175245ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/class/lua_src/000077500000000000000000000000001263004425400211545ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/class/lua_src/class.lua000066400000000000000000000326111263004425400227670ustar00rootroot00000000000000--[[ Copyright (c) 2014 Francisco Zamora-Martinez (pakozm@gmail.com) Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ]] -- DOCUMENTATION AT README.md -- https://github.com/pakozm/lua-oop-iter/blob/master/README.md class module -- section. ----------------------------- -- class module definition -- ----------------------------- local class = { _NAME = "class", _VERSION = "0.4", } -- a list of class tables declared using class function local class_tables_list = setmetatable({}, { __mode = "k" }) local function register_class_table(class_table, class_name) assert(not class_tables_list[class_name], string.format("%s class name exists", class_name)) class_tables_list[class_name] = class_table end ----------------------- -- Private functions -- ----------------------- -- Detect if APRIL-ANN is available. local type = type local aprilann_available = (aprilann ~= nil) if aprilann_available then type = luatype or type end -- Given two object meta_instance, sets the second as parent of the first. local function set_parent(child, parent) setmetatable(child.index_table, parent) end -- Checks if the type of the given object is "table" local function is_table(t) return type(t) == "table" end -- Checks if the given Lua object is a class table and returns its meta_instance -- table. local function has_metainstance(t) return is_table(t) and t.meta_instance end -- Checks if the given object is a class table and returns its -- meta_instance.index_table. local function has_class_instance_index_metamethod(t) return has_metainstance(t) and t.meta_instance.index_table end -- Checks if the given object is a class instance and returns its index_table -- metamethod. local function has_instance_index_metamethod(t) return t and getmetatable(t) and getmetatable(t).index_table end -- Converts a Lua object in an instance of the given class. local function class_instance(obj, class) setmetatable(obj, assert(has_metainstance(class), "2nd argument needs to be a class table")) obj.__instance__ = true return obj end ---------------------- -- Public functions -- ---------------------- -- Returns the class table associated with the given class_name. -- -- @param class_name - A Lua string with the class_name. -- @return class_table,methods_table - A Lua class table, and its methods table. function class.find(class_name) local cls = class_tables_list[class_name] if cls then return class_tables_list[class_name],cls.meta_instance.index_table end end -- Removes the given class name from the auxiliary class table. -- -- @param class_name - A Lua string with the class_name. function class.forget(class_name) class_tables_list[class_name] = nil end -- Predicate which returns true if a given object instance is a subclass of a -- given Lua class table. -- -- @param object_instance - A class instance object. -- @param base_class_table - A class table. -- @return boolean function class.is_a(object_instance, base_class_table) if not class.of(object_instance) then return false end assert(has_metainstance(base_class_table), "Needs a class table as 2nd parameter") local id = (base_class_table.meta_instance or {}).id local ok,result = pcall(function() return object_instance["is_" .. id] ~= nil end) return ok and result end -- Returns the super class table of a given derived class table. Throws an error -- if the given class has not a super class. -- -- @param class_table - A class table. -- @return super_class_table - The parent (super) class table. function class.super(class_table) assert(has_metainstance(class_table), "Needs a class table as 1st parameter") return assert( (getmetatable(class_table) or {}).parent, "The given class hasn't a super-class" ) end -- Returns the class table of the given object instance. -- -- @param obj - A Lua object. -- @return class_table - The class table of the given object. function class.of(obj) return (getmetatable(obj) or {}).cls end -- Returns the class id of the given object instance. function class.obj_id(obj) return (getmetatable(obj) or {}).id end -- Returns the value associated with the given key at the given -- class_table. Throws an error if the 1st parameter is not a class table. -- -- @param class_table - A Lua class table. -- @param key - A Lua string with the name you want to consult. -- @return value - The Lua value associated to the given key name. function class.consult(class_table, key) local index = has_class_instance_index_metamethod(class_table) assert(index, "The given object is not a class") if type(index) == "function" then return index(nil,key) else return index[key] end end -- Returns the value associated with the given key at the given class_table -- meta_instance. Throws an error if the 1st parameter is not a class table. -- -- @param class_table - A Lua class table. -- @param key - A Lua string with the name you want to consult at the meta_instance. -- @return value - The Lua value associated to the given key name. function class.consult_metamethod(class_table, key) return assert(has_metainstance(class_table), "The given object is not a class")[key] end -- Calls a method in a given class_table using the given vararg arguments. It -- throws an error if the 1st parameter is not a class table or if the given -- method doesn't exist. -- -- @param class_table - A Lua class_table. -- @param method - A Lua value with the method key. -- @param ... - A vararg list which will be passed to the method call. -- @return value - The value returned by the method call. function class.call(class_table, method, ...) local method = assert(class.consult(class_table, method), "Method " .. method .. " not implemented") return method(...) end -- Extends the given class table with the addition of a new key = value pair -- into the object instance table. It throws an error if the 1st parameter is -- not a class table. -- -- @param class_table - A Lua class table. -- @param key - A Lua key used as index. -- @param value - A Lua value which will be stored at the given key. function class.extend(class_table, key, value) local index = has_class_instance_index_metamethod(class_table) assert(index, "The given 1st parameter is not a class") assert(type(index) == "table") index[key] = value end -- Extends the given class table with the addition of a new key = value pair -- into the object meta_instance table, where metamethods are stored. It throws -- an error if the 1st parameter is not a class table. Be careful, several -- metamethods (__index, __gc) are defined by default in order to implement OOP, -- overwritten them will produce unexpected errors. However, __tostring -- metamethod is also defined but it is totally safe to overwrite it. -- -- @param class_table - A Lua class table. -- @param key - A Lua key used as index. -- @param value - A Lua value which will be stored at the given key. function class.extend_metamethod(class_table, key, value) assert(key ~= "__index" and key ~= "__gc", "__index and __gc metamethods are forbidden") assert(key ~= "id" and key ~= "cls", "id and cls keys are forbidden") assert(has_metainstance(class_table), "The given 1st parameter is not a class")[key] = value end -- Returns true/false if the given instance object is an instance of a derived -- class. -- -- @param obj - A Lua class instance. -- @return boolean function class.is_derived(obj) return getmetatable((getmetatable(obj) or {}).cls or {}).parent ~= nil end -- Returns true/false if the given Lua value is a class table. -- -- @param t - A Lua value. -- @return boolean function class.is_class(t) -- not not allows to transform the returned value into boolean return not not has_class_instance_index_metamethod(t) end -- Changes the __index table by a given function, in case the function -- returns "nil", the key would be searched at the old index field function class.declare_functional_index(cls, func) assert(class.is_class(cls), "Needs a class as first argument") assert(type(func) == "function", "Needs a function as second argument") local old_index = cls.meta_instance.__index if type(old_index) ~= "function" then cls.meta_instance.__index = function(self,key) local v = func(self,key) return v~=nil and v or old_index[key] end else cls.meta_instance.__index = function(self,key) local v = func(self,key) return v~=nil and v or old_index(self,key) end end end -- TODO: reimplement this function -- -- makes a wrapper around an object, delegating the function calls to the given -- object if they are not implemented in the given wrapper table local function wrapper(obj,wrapper) local wrapper = wrapper or {} local current = obj while class.of(current) do -- and not rawequal(getmetatable(current).__index,current) do current = instance_index_metamethod(current) for i,v in pairs(current) do if wrapper[i] == nil then if type(v) == "function" then wrapper[i] = function(first, ...) if rawequal(first,wrapper) then return obj[i](obj, ...) else return obj[i](...) end end -- function elseif getmetatable(v) and getmetatable(v).__call then error("Not implemented wrapper for callable tables") else -- if type(v) == "function" wrapper[i] = v end -- if type(v) == "function" ... else end -- if wrapper[i] == nil end -- for end -- while if class.of(wrapper) then if class.is_derived(wrapper) then error("class_wrapper not works with derived or nil_safe objects") else set_parent(getmetatable(wrapper),getmetatable(obj)) end else wrapper = class_instance(wrapper, class.of(obj)) end return wrapper end -- Creates a class table with a given class_name. It receives an optional parent -- class to implement simple heritance. It returns the class table; another -- table which will contain the methods of the object. Constructor and -- destructor methods will be declared into the class table as -- class_name:constructor(...) and class_name:destructor(). Additionally, a -- third optional argument is given, which allows to give a predefined -- class_table, useful is you want to make global instead of local variables. local class_call_metamethod = function(self, class_name, parentclass, class_table) local class_table = class_table or {} assert(not class_table.constructor and not class_table.destructor and not class_table.meta_instance, "3rd argument has a constructor, destructor or meta_instance field") class_table.constructor = function() end class_table.destructor = function() end -- register_class_table(class_table, class_name) -- local class_table = get_table_from_dotted_string(class_name, true) -- if type(parentclass) == "string" then -- parentclass = get_table_from_dotted_string(parentclass) -- end assert(parentclass==nil or has_metainstance(parentclass), "The parentclass must be defined by 'class' function") -- local t = string.tokenize(class_name,".") -- local meta_instance = { id = class_name, cls = class_table, __tostring = function(self) return "instance of " .. class_name end, __index = { ["is_"..class_name] = true }, } meta_instance.index_table = meta_instance.__index meta_instance.__gc = function(self) if self.__instance__ then class_table.destructor(self) if parentclass then parentclass.meta_instance.__gc(self) end end end local class_metatable = { id = class_name .. " class", parent = parentclass, __tostring = function() return "class ".. class_name .. " class" end, __concat = function(a,b) assert(type(b) == "string", "Needs a string as second argument") return class.consult(a,b) end, __call = function(self, ...) local obj = class_instance({}, self) class_table.constructor(obj, ...) return obj end, -- __index = function(t,k) -- local aux = rawget(t,k) -- if aux then return aux else return t.meta_instance.__index[k] end -- end, } if parentclass then set_parent(meta_instance, parentclass.meta_instance) end -- class_table.meta_instance = meta_instance setmetatable(class_table, class_metatable) return class_table, class_table.meta_instance.__index end setmetatable(class, { __call = class_call_metamethod }) -- In APRIL-ANN this module is defined at global environment if aprilann_available then _G.class = class _G.class_instance = class_instance end return class april-ann-0.4.1/packages/basics/class/package.lua000066400000000000000000000021351263004425400216230ustar00rootroot00000000000000package{ name = "class", version = "1.0", depends = { "base" }, keywords = { }, description = "", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", --copy{ file= "c_src/*.h", dest_dir = "include" }, --provide_bind{ file = "binding/bind_util.lua.cc" , dest_dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test-class.lua", }, }, }, target{ name = "build", depends = "provide", use_timestamp = true, -- object{ -- file = "c_src/*.cc", -- dest_dir = "build", -- -- flags = "-std=c99", -- }, luac{ orig_dir = "lua_src", dest_dir = "build", }, --build_bind{ file = "binding/bind_util.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/class/test/000077500000000000000000000000001263004425400205035ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/class/test/test-class.lua000066400000000000000000000033421263004425400232720ustar00rootroot00000000000000local check = utest.check local T = utest.test -- myClass1 local myClass1,myClass1Methods = class("myClass1") function myClass1:constructor(n) self.n = n end function myClass1:destructor() print("I am myClass1 destructor: " .. tostring(self) .. " " .. (self.n or "nil")) end function myClass1Methods:print() print(self.n) end -- myClass2 local myClass2,myClass2Methods = class("myClass2", myClass1) function myClass2:constructor(...) myClass1.constructor(self,...) end function myClass2Methods:print() print("I am myClass2") local super_print = myClass1.."print" super_print(self) class.call(class.super(myClass2),"print",self) end -- myClass3 local myClass3,myClass3Methods = class("myClass3", myClass2) function myClass3:constructor(...) myClass2.constructor(self,...) end ------------------------------------------------------------------------------ local t1 = myClass1(10) local t2 = myClass2(33) local t3 = myClass3(100) t1:print() t2:print() t3:print() T("ClassIsA",function() check.TRUE(class.is_a(t1, myClass1)) check.FALSE(class.is_a(t1, myClass2)) check.FALSE(class.is_a(t1, myClass3)) check.TRUE(class.is_a(t2, myClass1)) check.TRUE(class.is_a(t2, myClass2)) check.FALSE(class.is_a(t2, myClass3)) check.TRUE(class.is_a(t3, myClass1)) check.TRUE(class.is_a(t3, myClass2)) check.TRUE(class.is_a(t3, myClass3)) end) T("ClassOf",function() check.eq(class.of(t1), myClass1) check.eq(class.of(t2), myClass2) check.eq(class.of(t3), myClass3) end) T("ClassExtend", function() class.extend(myClass2, "ext", 120) check.eq(t2.ext, 120) end) T("ClassDerived", function() check.FALSE(class.is_derived(t1)) check.TRUE(class.is_derived(t2)) check.TRUE(class.is_derived(t3)) end) april-ann-0.4.1/packages/basics/cmdOpt/000077500000000000000000000000001263004425400176455ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/cmdOpt/lua_src/000077500000000000000000000000001263004425400212755ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/cmdOpt/lua_src/cmdOpt.lua000066400000000000000000000322621263004425400232330ustar00rootroot00000000000000-- See the test file for details -- A cmdOpt object is created and two main methods can be used: -- - Generate help message -- - parse arguments, which returns string (error) or a table -- There are short (1 letter) and long options -- The following formats are accepted: -- -c if c does not require arguments -- -cdef if c,d,e and f does not require arguments -- -cdefblah if c,d,e does not require arguments and f can accept arguments -- --longoption --longoption=value -- long options can use a prefix is there is non ambiguity -- the void long option "--" can be used to stop option list -- a lua class: local cmdOpt,cmdopt_methods = class("cmdOpt") _G.cmdOpt = cmdOpt function cmdopt_methods:add_option(option) -- option is a table with the following parameters: -- index_name -> name of option in result table -- description -> useful to generate help description -- filter -> nil or a function to filter the value -- action -> to execute with the option value -- short -> a single letter, without "-", several options are allowed -- long -> name of long option -- mode -> 'usergiven' 'always', default 'usergiven' -- argument -> 'yes','no','optional' -- default_value -> default value when argument ~= 'no' local opt = get_table_fields( { filter = { type_match="function", default=nil }, action = { type_match="function", default=nil }, index_name = { type_match="string" }, description = { mandatory=true, type_match="string" }, argument = { mandatory=true, type_match="string" }, argument_name = { type_match="string", default="VALUE" }, mode = { type_match="string", default="usergiven" }, default_value = { default=nil }, short = { default=nil }, long = { default=nil }, }, option) assert(opt.argument=="yes" or opt.argument=="no" or opt.argument=="optional" or opt.argument==nil, "Expected 'yes', 'no', 'optional' or nil in argument field") assert(opt.short or opt.long, "It is mandatory to give a long or a short field") opt.short,opt.long=nil,nil table.insert(self.options,opt) -- insert options in list -- assert(opt.mode=="always" or opt.mode=="usergiven", "Given incorrect mode '"..tostring(opt.mode).."'. Use 'usegiven' or 'always'") -- if opt.default_value and not opt.mode=="always" then error("default_value only allowed if mode='always', otherwise is forbidden") end -- local shorts = option.short if shorts then if type(shorts) == "string" then shorts = { shorts } end if type(shorts) ~= "table" then error("cmdOpt constructor") end for i,letter in ipairs(shorts) do if #letter ~= 1 or letter == '-' then error("cmdOpt: bad short option '"..letter.."'") end if self.short_options[letter] ~= nil then error("cmdOpt: short option '"..letter.."'already defined") end self.short_options[letter] = opt end opt.short_options = shorts end -- local longs = option.long if longs then if type(longs) == "string" then longs = { longs } end if type(longs) ~= "table" then error("cmdOpt constructor") end for i,str in ipairs(longs) do if #str == 0 then error("cmdOpt: long option must have size >0") end if self.long_options[str] ~= nil then error("cmdOpt: long option '"..str.."'already defined") end self.long_options[str] = opt end end opt.long_options = longs end -- constructor -- tbl is a table with the following arguments: -- posix_mode -> true in order to stop -- program_name -> a string -- argument_description -> string, description of positional arguments -- the "vector part" of tbl are just options to add with add_option function cmdOpt:constructor(tbl) self.options = {} -- lista de opciones self.short_options = {} -- diccionario opciones cortas self.long_options = {} -- diccionario opciones largas self.posix_mode = tbl.posix_mode or false self.program_name = tbl.program_name or arg[0] self.argument_description = tbl.argument_description or "positional_arguments" self.main_description = tbl.main_description or "" self.author = tbl.author or "" self.copyright = tbl.copyright or "" self.see_also = tbl.see_also or "" for i,option in ipairs(tbl) do self:add_option(option) end end -- cool function to generate the help text function cmdopt_methods:generate_help() local message = {} table.insert(message,"USAGE:\n\t"..self.program_name) for i,opt in ipairs(self.options) do local total = 0 if opt.short_options then total = #opt.short_options end if opt.long_options then total = total+#opt.long_options end local remains=total if (total>0) then local mandatory = (opt.mode == "always" and not opt.default_value) table.insert(message, ((not mandatory and " [") or " ")..(total>1 and "(" or "")) for j,short in ipairs(opt.short_options or {}) do local str="-"..short if opt.argument == "yes" then str=str..opt.argument_name elseif opt.argument ~= "no" then str=str.."["..opt.argument_name.."]" end remains=remains-1 if remains>0 then str=str.."|" end table.insert(message,str) end if opt.long_options then for j,long in ipairs(opt.long_options or {}) do local str="--"..long if opt.argument == "yes" then str=str.."="..opt.argument_name elseif opt.argument ~= "no" then str=str.."[="..opt.argument_name.."]" end remains=remains-1 if remains>0 then str=str.."|" end table.insert(message,str) end end table.insert(message,(total>1 and ")" or "").. ((not mandatory and "]") or " ")) end end table.insert(message," ") table.insert(message,self.argument_description) table.insert(message,"\n\nDESCRIPTION:\n") if self.main_description ~= "" then table.insert(message,"\t"..self.main_description.."\n\n") end -- usage line is finished, now we proceed to describe every argument: for i,opt in ipairs(self.options) do local total = 0 if opt.short_options then total = #opt.short_options end if opt.long_options then total = total+#opt.long_options end local remains=total if (total>0) then local mandatory = (opt.mode == "always" and not opt.default_value) table.insert(message,"\t") for j,short in ipairs(opt.short_options or {}) do local str="-"..short if opt.argument == "yes" then str=str..opt.argument_name elseif opt.argument ~= "no" then str=str.."["..opt.argument_name.."]" end remains=remains-1 if remains>0 then str=str..", " end table.insert(message,str) end if opt.long_options then for j,long in ipairs(opt.long_options or {}) do local str="--"..long if opt.argument == "yes" then str=str.."="..opt.argument_name elseif opt.argument ~= "no" then str=str.."[="..opt.argument_name.."]" end remains=remains-1 if remains>0 then str=str..", " end table.insert(message,str) end end if opt.default_value == nil then table.insert(message,"\t "..(opt.description or "").. ((not mandatory and " "..ansi.fg["green"].."(optional)") or "")..ansi.fg["default"].."\n") else table.insert(message,"\t "..(opt.description or "").. ((not mandatory and " "..ansi.fg["green"].."(optional)") or "").." [DEFAULT: ".. tostring(opt.default_value) .. "]".. ansi.fg["default"].."\n") end end end if self.author ~= "" then table.insert(message,"AUTHOR\n\t"..self.author.."\n\n") end if self.copyright ~= "" then table.insert(message,"COPYRIGHT\n\t"..self.copyright.."\n\n") end if self.see_also ~= "" then table.insert(message,"SEE ALSO\n\t"..self.see_also.."\n\n") end return table.concat(message) end -- auxiliary method function cmdopt_methods:search_long_option(str) -- prefer exact match if self.long_options[str] then return self.long_options[str] end -- search for prefixes local strlen = #str local found for optname,opt in pairs(self.long_options) do if string.sub(optname,1,strlen) == str then if found ~= nil then -- hay conflicto, el prefijo es ambiguo return nil else found = opt end end end return found end -- main method, throws an error in case of fail, or returns -- or a table with positinal and rest of arguments -- actions are simply executed before return function cmdopt_methods:parse_without_check(arguments, verbose) if verbose == nil then verbose = true end local arguments = arguments or arg -- arg is the global variable local opt_list = {} -- list of options to process local result = {} -- result table local consider_options = true local pos=1 local nargs=#arguments local i=1 while i<=nargs do local key,value,opt local str = arguments[i] if consider_options and string.sub(str, 1, 2) == "--" then -- long option local pos = string.find(str, "=", 1, true) if pos then key = string.sub(str, 3, pos-1) value = string.sub(str, pos+1) else key = string.sub(str, 3) end --printf("jarl key %s value %s",key,value or "nil") if key == "" then -- "--" is used to stop considering options consider_options = false else -- search long option (prefix) in table: opt = self:search_long_option(key) assert(opt,"ambiguous or non-existent long option: "..str) if opt.argument == "no" then april_assert(value == nil, "long option '%s' has no arguments but received argument %s", key,value) value = true end assert(opt.argument ~= "yes" or value ~= nil, "long option '"..key.."' has obligatory argument") -- guardamos opt y value para procesar table.insert(opt_list,{opt,value}) end elseif consider_options and string.sub( str, 1, 1 ) == "-" then -- short option -- vamos a procesar las opciones de izquierda a derecha -- mientras encontremos opciones sin argumentos -- si encontramos una opcion con argumento opcional u -- obligatorio procesamos el resto de la cadena como su valor, a -- menos que sea el ultimo caracter, en cuyo caso tomamos el -- argumento siguiente como su valor solamente en caso de tener -- argumento obligatorio local j=2 local strlen = #str local go_on = true while j<=strlen and go_on do key = string.sub(str, j, j) opt = self.short_options[key] assert(opt, "short option '"..key.."' not found") if opt.argument == 'no' then -- store opt and value to process later value = true else -- argument is obligatory or optional go_on = false -- stop -- let's see the rest of the string value = string.sub( str, j+1 ) if value == "" and opt.argument == 'yes' then i=i+1 assert(i<=nargs,"short option '"..key.."' expects obligatory argument") value = arguments[i] end end table.insert(opt_list,{opt,value}) j=j+1 end -- while that traverses string else -- if else that check "-" and "--" table.insert(result,str) -- positional argument if self.posix_mode then consider_options = false end end i = i+1 end -- while igetValue(); } else if (lua_isstring(L, n)) { const char *str; LUABIND_GET_PARAMETER(n, string, str); LuaComplexFNumber aux(str); return aux.getValue(); } else if (lua_isnumber(L, n)) { float aux; LUABIND_GET_PARAMETER(n, float, aux); return ComplexF(aux, 0.0f); } else LUABIND_ERROR("Incorrect Lua complex representation, use string " "or complex object"); return ComplexF(); } #undef FUNCTION_NAME void lua_pushComplexF(lua_State *L, const ComplexF &number) { LuaComplexFNumber *obj = new LuaComplexFNumber(number); lua_pushLuaComplexFNumber(L, obj); } namespace AprilUtils { template<> AprilMath::ComplexF LuaTable:: convertTo(lua_State *L, int idx) { return lua_toComplexF(L, idx); } template<> void LuaTable:: pushInto(lua_State *L, AprilMath::ComplexF value) { lua_pushComplexF(L, value); } template<> bool LuaTable:: checkType(lua_State *L, int idx) { return lua_isComplexF(L, idx); } } //BIND_END //BIND_HEADER_H #include "referenced.h" #include "complex_number.h" #include "error_print.h" #include "constString.h" using AprilMath::ComplexF; using AprilMath::LuaComplexFNumber; // This function is to be used with LUABIND_GET_.... macros ComplexF lua_toComplexF(lua_State *L, int n); // This function is to be used with LUABIND_GET_.... macros bool lua_isComplexF(lua_State *L, int n); void lua_pushComplexF(lua_State *L, const ComplexF &number); //BIND_END //BIND_LUACLASSNAME LuaComplexFNumber complex //BIND_CPP_CLASS LuaComplexFNumber //BIND_CONSTRUCTOR LuaComplexFNumber { int argn = lua_gettop(L); // number of arguments if (argn == 2) { ComplexF number; LUABIND_GET_PARAMETER(1, float, number.real()); LUABIND_GET_PARAMETER(2, float, number.img()); obj = new LuaComplexFNumber(number); } else if (argn == 1) { const char *str; LUABIND_GET_PARAMETER(1, string, str); obj = new LuaComplexFNumber(str); } else { LUABIND_FERROR1("Incorrect number of arguments, expected 1 or 2, found %d", argn); } LUABIND_RETURN(LuaComplexFNumber, obj); } //BIND_END //BIND_METHOD LuaComplexFNumber clone { LuaComplexFNumber *other = new LuaComplexFNumber(obj->getValue()); LUABIND_RETURN(LuaComplexFNumber, other); } //BIND_END //BIND_METHOD LuaComplexFNumber eq { LuaComplexFNumber *other; LUABIND_GET_PARAMETER(1, LuaComplexFNumber, other); LUABIND_RETURN(bool, obj->getValue() == other->getValue()); } //BIND_END //BIND_METHOD LuaComplexFNumber mul { LuaComplexFNumber *other, *result; LUABIND_GET_PARAMETER(1, LuaComplexFNumber, other); result = new LuaComplexFNumber( obj->getValue() * other->getValue() ); LUABIND_RETURN(LuaComplexFNumber, result); } //BIND_END //BIND_METHOD LuaComplexFNumber add { LuaComplexFNumber *other, *result; LUABIND_GET_PARAMETER(1, LuaComplexFNumber, other); result = new LuaComplexFNumber( obj->getValue() + other->getValue() ); LUABIND_RETURN(LuaComplexFNumber, result); } //BIND_END //BIND_METHOD LuaComplexFNumber sub { LuaComplexFNumber *other, *result; LUABIND_GET_PARAMETER(1, LuaComplexFNumber, other); result = new LuaComplexFNumber( obj->getValue() - other->getValue() ); LUABIND_RETURN(LuaComplexFNumber, result); } //BIND_END //BIND_METHOD LuaComplexFNumber div { LuaComplexFNumber *other, *result; LUABIND_GET_PARAMETER(1, LuaComplexFNumber, other); result = new LuaComplexFNumber( obj->getValue() / other->getValue() ); LUABIND_RETURN(LuaComplexFNumber, result); } //BIND_END //BIND_METHOD LuaComplexFNumber neg { LuaComplexFNumber *result; result = new LuaComplexFNumber( -obj->getValue() ); LUABIND_RETURN(LuaComplexFNumber, result); } //BIND_END //BIND_METHOD LuaComplexFNumber conj { obj->getValue().conj(); LUABIND_RETURN(LuaComplexFNumber, obj); } //BIND_END //BIND_METHOD LuaComplexFNumber exp { LuaComplexFNumber *result = new LuaComplexFNumber( obj->getValue().expc() ); LUABIND_RETURN(LuaComplexFNumber, result); } //BIND_END //BIND_METHOD LuaComplexFNumber real { LUABIND_RETURN(float, obj->getValue().real()); } //BIND_END //BIND_METHOD LuaComplexFNumber img { LUABIND_RETURN(float, obj->getValue().img()); } //BIND_END //BIND_METHOD LuaComplexFNumber plane { LUABIND_RETURN(float, obj->getValue().real()); LUABIND_RETURN(float, obj->getValue().img()); } //BIND_END //BIND_METHOD LuaComplexFNumber polar { float r, phi; obj->getValue().polar(r, phi); LUABIND_RETURN(float, r); LUABIND_RETURN(float, phi); } //BIND_END //BIND_METHOD LuaComplexFNumber abs { LUABIND_RETURN(float, obj->getValue().abs()); } //BIND_END //BIND_METHOD LuaComplexFNumber angle { LUABIND_RETURN(float, obj->getValue().angle()); } //BIND_END //BIND_METHOD LuaComplexFNumber sqrt { LUABIND_RETURN(float, obj->getValue().sqrtc()); } //BIND_END april-ann-0.4.1/packages/basics/complex/c_src/000077500000000000000000000000001263004425400211575ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/complex/c_src/complex_number.cu000066400000000000000000000043711263004425400245340ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include "complex_number.h" namespace AprilMath { template struct Complex; template struct Complex; } namespace AprilUtils { void aprilPrint(const AprilMath::ComplexF &v) { printf("%f%c%fi", v.real(), (v.img()>+0.0f)?'+':' ', v.img()); } void aprilPrint(const AprilMath::ComplexD &v) { printf("%f%c%fi", v.real(), (v.img()>+0.0)?'+':' ', v.img()); } template<> unsigned int binarizer::binary_size(){ return 10; } template<> unsigned int binarizer::binary_size() { return 20; } template<> void binarizer:: code(const AprilMath::ComplexF &value, char *b) { binarizer::code_float(value.real(), b); binarizer::code_float(value.img(), b+5); } template<> void binarizer:: code(const AprilMath::ComplexD &value, char *b) { binarizer::code_double(value.real(), b); binarizer::code_double(value.img(), b+10); } template<> AprilMath::ComplexF binarizer::decode(const char *b) { float real, img; real = binarizer::decode_float(b); img = binarizer::decode_float(b+5); return AprilMath::ComplexF(real,img); } template<> AprilMath::ComplexD binarizer::decode(const char *b) { double real, img; real = binarizer::decode_float(b); img = binarizer::decode_float(b+5); return AprilMath::ComplexD(real,img); } } april-ann-0.4.1/packages/basics/complex/c_src/complex_number.h000066400000000000000000000400621263004425400243510ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef COMPLEX_NUMBER_H #define COMPLEX_NUMBER_H #ifndef _USE_MATH_DEFINES #define _USE_MATH_DEFINES #define UNDEF_MATH_DEFINES #endif #include #ifndef NAN #define NAN sqrtf(-1.0f) #endif #include "binarizer.h" #include "constString.h" #include "lua_table.h" #include "error_print.h" #include "referenced.h" #ifdef UNDEF_MATH_DEFINES #undef _USE_MATH_DEFINES #undef UNDEF_MATH_DEFINES #endif #define REAL_IDX 0 #define IMG_IDX 1 #ifndef __host__ #define __host__ #define UNDEF_HOST #endif #ifndef __device__ #define __device__ #define UNDEF_DEVICE #endif namespace AprilMath { /** * @brief A class which declares a complex number. * * This class is intended to be used as template parameter of Basics::Matrix * class, allowing to do algebra operations in complex domain. */ template struct Complex { /// The complex number is an array where [0]=REAL, [1]=IMAGINARY. T data[2]; /// Static function for instantiation of \c 1+1i complex number. __host__ __device__ static Complex one_one() { return Complex(static_cast(1.0), static_cast(1.0)); } /// Static function for instantiation of \c 0+0i complex number. __host__ __device__ static Complex zero_zero() { return Complex(static_cast(0.0), static_cast(0.0)); } /// Static function for instantiation of \c 1+0i complex number. __host__ __device__ static Complex one_zero() { return Complex(static_cast(1.0), static_cast(0.0)); } /// Static function for instantiation of 0+1i complex number. __host__ __device__ static Complex zero_one() { return Complex(static_cast(0.0), static_cast(1.0)); } /// Default constructor, declares \c 0+0i complex number. __host__ __device__ Complex() { data[REAL_IDX] = T(); data[IMG_IDX] = T(); } /// Construction for \c r+0i complex number, being \c r the argument. __host__ __device__ Complex(T r) { data[REAL_IDX] = r; data[IMG_IDX] = static_cast(0.0); } /// Full construction from real (r) and imaginary (i) arguments. __host__ __device__ Complex(T r, T i) { data[REAL_IDX] = r; data[IMG_IDX] = i; } __host__ __device__ ~Complex() { } __host__ __device__ Complex(const Complex &other) { this->data[0] = other.data[0]; this->data[1] = other.data[1]; } __host__ __device__ Complex &operator=(const Complex &other) { this->data[REAL_IDX] = other.data[REAL_IDX]; this->data[IMG_IDX] = other.data[IMG_IDX]; return *this; } /// Casting returns only real part. __host__ __device__ operator int() const { return static_cast(data[REAL_IDX]); } /// Casting returns only real part. __host__ __device__ operator float() const { return static_cast(data[REAL_IDX]); } /// Casting returns only real part. __host__ __device__ operator double() const { return static_cast(data[REAL_IDX]); } /// Casting returns only real part. __host__ __device__ operator bool() const { return static_cast(data[REAL_IDX]); } /// Casting returns only real part. __host__ __device__ operator char() const { return static_cast(data[REAL_IDX]); } /// Two complex numbers are equal if their difference module is < 0.0001 __host__ __device__ bool operator==(const Complex &other) const { Complex r(other - *this); return (r.abs() < static_cast(0.0001)); } /// Defined using negation of operatior == __host__ __device__ bool operator!=(const Complex &other) const { return !(*this == other); } __host__ __device__ Complex operator*(const Complex &other) const { Complex result; result.data[REAL_IDX] = (this->data[REAL_IDX]*other.data[REAL_IDX] - this->data[IMG_IDX]*other.data[IMG_IDX]); result.data[IMG_IDX] = (this->data[REAL_IDX]*other.data[IMG_IDX] + this->data[IMG_IDX]*other.data[REAL_IDX]); return result; } __host__ __device__ Complex operator/(const Complex &other) const { T c2_d2 = ( other.data[REAL_IDX]* other.data[REAL_IDX] + other.data[IMG_IDX] * other.data[IMG_IDX] ); Complex result; result.data[REAL_IDX] = (this->data[REAL_IDX]*other.data[REAL_IDX] + this->data[IMG_IDX]*other.data[IMG_IDX]) / c2_d2; result.data[IMG_IDX] = (this->data[IMG_IDX]*other.data[REAL_IDX] - this->data[REAL_IDX]*other.data[IMG_IDX]) / c2_d2; return result; } __host__ __device__ Complex &operator+=(const Complex &other) { this->data[REAL_IDX] += other.data[REAL_IDX]; this->data[IMG_IDX] += other.data[IMG_IDX]; return *this; } __host__ __device__ Complex &operator*=(const Complex &other) { this->data[REAL_IDX] = (this->data[REAL_IDX]*other.data[REAL_IDX] - this->data[IMG_IDX]*other.data[IMG_IDX]); this->data[IMG_IDX] = (this->data[REAL_IDX]*other.data[IMG_IDX] + this->data[IMG_IDX]*other.data[REAL_IDX]); return *this; } __host__ __device__ Complex &operator/=(const Complex &other) { T c2_d2 = ( other.data[REAL_IDX]* other.data[REAL_IDX] + other.data[IMG_IDX] * other.data[IMG_IDX] ); this->data[REAL_IDX] = (this->data[REAL_IDX]*other.data[REAL_IDX] + this->data[IMG_IDX]*other.data[IMG_IDX]) / c2_d2; this->data[IMG_IDX] = (this->data[IMG_IDX]*other.data[REAL_IDX] - this->data[REAL_IDX]*other.data[IMG_IDX]) / c2_d2; return *this; } __host__ __device__ Complex operator+(const Complex &other) const { Complex result; result.data[REAL_IDX] = this->data[REAL_IDX]+other.data[REAL_IDX]; result.data[IMG_IDX] = this->data[IMG_IDX]+other.data[IMG_IDX]; return result; } __host__ __device__ Complex operator-(const Complex &other) const { Complex result; result.data[REAL_IDX] = this->data[REAL_IDX]-other.data[REAL_IDX]; result.data[IMG_IDX] = this->data[IMG_IDX]-other.data[IMG_IDX]; return result; } __host__ __device__ Complex operator-() const { Complex result; result.data[REAL_IDX] = -this->data[REAL_IDX]; result.data[IMG_IDX] = -this->data[IMG_IDX]; return result; } /// Complex numbers are sorted by its modulus. __host__ __device__ bool operator<(const Complex &other) const { // FIXME: are you sure? return abs() < other.abs(); } /// Complex numbers are sorted by its modulus. __host__ __device__ bool operator>(const Complex &other) const { // FIXME: are you sure? return abs() > other.abs(); } /// Exponential operation. __host__ __device__ Complex expc() const { T expa = exp(data[REAL_IDX]); return Complex(expa*cos(data[REAL_IDX]), expa*sin(data[IMG_IDX])); } /// Conjugate operation, it is done \b IN-PLACE __host__ __device__ void conj() { data[IMG_IDX] = -data[IMG_IDX]; } __host__ __device__ T real() const { return data[REAL_IDX]; } __host__ __device__ T &real() { return data[REAL_IDX]; } __host__ __device__ T img() const { return data[IMG_IDX]; } __host__ __device__ T &img() { return data[IMG_IDX]; } __host__ __device__ T abs() const { return sqrt( data[REAL_IDX]*data[REAL_IDX] + data[IMG_IDX]*data[IMG_IDX] ); } /// Returns the square root of the complex number. __host__ __device__ T sqrtc() const { return sqrt( (data[REAL_IDX] + abs()) / 2.0 ); } __host__ __device__ T angle() const { T phi; if (real() > 0) phi = atan(img()/real()); else if (real() < 0 && img() >= 0) phi = atan(img()/real()) + M_PI; else if (real() < 0 && img() < 0) phi = atan(img()/real()) - M_PI; else if (real() == 0 && img() > 0) phi = M_PI/2; else if (real() == 0 && img() < 0) phi = -M_PI/2; else phi = NAN; return phi; } /// Retruns by reference the modulus \c r and angle \c phi. __host__ __device__ void polar(T &r, T &phi) const { r = abs(); phi = angle(); } // POINTER ACCESS __host__ __device__ T *ptr() { return data; } __host__ __device__ const T *ptr() const { return data; } }; typedef Complex ComplexF; typedef Complex ComplexD; /** * @brief The class LuaComplexFNumber is intended to parse float Complex * numbers ( ComplexF ) from a const char * coming from Lua. * * It uses a simple automaton to perform the parsing of the string following * this regexp: \c ([+-]N)?([+-]Ni)? * * @note The automaton in dot format, excluding ERROR state (non expected * tokens achieve always ERROR state): * \dot * digraph ComplexAutomaton { * rankdir=LR; * lambda [shape=none, label=""]; * FINAL [shape=doublecircle]; * lambda -> INITIAL; * INITIAL -> SIGN [label="TOKEN_SIGN"]; * INITIAL -> NUMBER [label="TOKEN_FLOAT"]; * INITIAL -> FINAL [label="TOKEN_I"]; * SIGN -> NUMBER [label="TOKEN_FLOAT"]; * SIGN -> FINAL [label="TOKEN_I"]; * NUMBER -> R_SIGN [label="TOKEN_SIGN"]; * NUMBER -> FINAL [label="TOKEN_I"]; * NUMBER -> FINAL [label="TOKEN_END"]; * R_SIGN -> R_NUMBER [label="TOKEN_FLOAT"]; * R_SIGN -> FINAL [label="TOKEN_I"]; * R_NUMBER -> FINAL [label="TOKEN_I"]; * } * \enddot */ class LuaComplexFNumber : public Referenced { public: LuaComplexFNumber(const ComplexF &number) : Referenced(), number(number) { } /** * @brief Constructor from const char *, implements an automaton * (FSM). * * Constructor from const char *, implements an automaton * (FSM). * * @see LuaComplexFNumber class for the automaton dot graph. */ LuaComplexFNumber(const char *str) : Referenced() { #define SET_SIGN(s, n) (n) = ( (s) == '+' ) ? 1.0f : -1.0f float num; char sign='+'; // initialized to avoid compilation warning AprilUtils::constString cs(str); STATES state = INITIAL; TOKENS token; while(state != FINAL && state != ERROR) { token = getToken(cs,num,sign); switch(state) { case INITIAL: switch(token) { case TOKEN_SIGN: SET_SIGN(sign, number.real()); state=SIGN; break; case TOKEN_FLOAT: number.real()=num; state=NUMBER; break; case TOKEN_I: number.real()=0.0f; number.img()=1.0f; state=FINAL; break; default: state=ERROR; } break; case SIGN: switch(token) { case TOKEN_FLOAT: number.real()=number.real()*num; state=NUMBER; break; case TOKEN_I: number.img()=number.real(); number.real()=0.0f; state=FINAL; break; default: state=ERROR; } break; case NUMBER: switch(token) { case TOKEN_SIGN: SET_SIGN(sign, number.img()); state=R_SIGN; break; case TOKEN_I: number.img()=number.real(); number.real()=0.0f; state=FINAL; break; case TOKEN_END: number.img()=0.0f; state=FINAL; break; default: state=ERROR; } break; case R_SIGN: switch(token) { case TOKEN_FLOAT: number.img()=number.img()*num; state=R_NUMBER; break; case TOKEN_I: state=FINAL; break; default: state=ERROR; } break; case R_NUMBER: switch(token) { case TOKEN_I: state=FINAL; break; default: state=ERROR; } break; default: state=ERROR; } } if (state == ERROR || !cs.empty()) ERROR_EXIT1(256, "Incorrect complex string format '%s'\n",str); #undef SET_SIGN } /// Returns the read complex number by reference. ComplexF &getValue() { return number; } /// Returns the read complex number by const reference. const ComplexF &getValue() const { return number; } private: /// The parsed number result. ComplexF number; /// Automaton states (syntactic structure). enum STATES { INITIAL, ///< Initial state of the automaton. SIGN, ///< A sign has been read. NUMBER, ///< A number has been read. R_SIGN, ///< A sign after the real part. R_NUMBER, ///< A number after the real part (with/without sign). FINAL, ///< Parsing finished. ERROR ///< Unexpected symbol or token error. }; /// Automaton tokens (lexical symbols). enum TOKENS { TOKEN_FLOAT, ///< A real number in scientific format. TOKEN_SIGN, ///< A sign symbol. TOKEN_I, ///< The i symbol. TOKEN_UNKOWN, ///< Unrecognized token. TOKEN_END ///< End of the string. }; /** * @brief Parses a AprilUtils::constString and returns its token type and * value. * * This function receives a * AprilUtils::constString and returns its token identifier. Additionally, * if the token is a TOKEN_FLOAT, the argument \c num will be filled with * the read number; if the token is a TOKEN_SIGN, the argument \c sign will * be filled with a '+' or '-' symbol. * * @note This function uses AprilUtils::constString::operator[] and * AprilUtils::constString::extract_float methods to read the char (sign \c * '+'/'-'or \c 'i' symbols), or the float number. */ TOKENS getToken(AprilUtils::constString &cs, float &num, char &sign) { if (cs.empty()) return TOKEN_END; char ch = cs[0]; if (ch == '+' || ch == '-') { cs.skip(1); sign=ch; return TOKEN_SIGN; } else if (ch == 'i') { cs.skip(1); return TOKEN_I; } else if (cs.extract_float(&num)) return TOKEN_FLOAT; return TOKEN_UNKOWN; } }; } // namespace AprilMath #ifdef UNDEF_HOST #undef __host__ #undef UNDEF_HOST #endif #ifdef UNDEF_DEVICE #undef __device__ #undef UNDEF_DEVICE #endif namespace AprilUtils { void aprilPrint(const AprilMath::ComplexF &v); void aprilPrint(const AprilMath::ComplexD &v); template<> unsigned int binarizer::binary_size(); template<> unsigned int binarizer::binary_size(); template<> void binarizer:: code(const AprilMath::ComplexF &value, char *b); template<> void binarizer:: code(const AprilMath::ComplexD &value, char *b); template<> AprilMath::ComplexF binarizer::decode(const char *b); template<> AprilMath::ComplexD binarizer::decode(const char *b); //////////////////////////////////////////////////////////////////////////// // This section allows to push complex numbers from C++ into Lua by calling // LuaTable object methods. template<> AprilMath::ComplexF LuaTable:: convertTo(lua_State *L, int idx); template<> void LuaTable:: pushInto(lua_State *L, AprilMath::ComplexF value); template<> bool LuaTable:: checkType(lua_State *L, int idx); } #endif // COMPLEX_NUMBER_H april-ann-0.4.1/packages/basics/complex/lua_src/000077500000000000000000000000001263004425400215165ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/complex/lua_src/complex.lua000066400000000000000000000024061263004425400236720ustar00rootroot00000000000000-- OVERWRITTING TOSTRING FUNCTION local function get_operands(op1,op2) if not class.is_a(op1,complex) then op1,op2=op2,op1 end local t2 = type(op2) if t2 == "number" then op2 = complex(op2, 0.0) elseif t2 == "string" then op2 = complex(op2) end return op1,op2 end class.extend(complex, "ctor_name", function(self) return "complex" end) class.extend(complex, "ctor_params", function(self) return self:plane() end) class.extend(complex, "to_lua_string", function(self) return "complex(%g,%g)"%{ self:plane() } end) complex.meta_instance.__tostring = function(self) return string.format("% g%+gi", self:plane()) end complex.meta_instance.__eq = function(op1, op2) local op1,op2 = get_operands(op1,op2) return op1:eq(op2) end complex.meta_instance.__add = function(op1, op2) local op1,op2 = get_operands(op1,op2) return op1:add(op2) end complex.meta_instance.__sub = function(op1, op2) local op1,op2 = get_operands(op1,op2) return op1:sub(op2) end complex.meta_instance.__mul = function(op1, op2) local op1,op2 = get_operands(op1,op2) return op1:mul(op2) end complex.meta_instance.__div = function(op1, op2) local op1,op2 = get_operands(op1,op2) return op1:div(op2) end complex.meta_instance.__unm = function(op) return op:neg() end april-ann-0.4.1/packages/basics/complex/package.lua000066400000000000000000000022121263004425400221610ustar00rootroot00000000000000package{ name = "complex", version = "1.0", depends = { "util" }, keywords = { }, description = "Complex numbers library", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test.lua", }, }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_complex.lua.cc" , dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", dest_dir = "build", }, object{ file = "c_src/*.cu", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_complex.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/complex/test/000077500000000000000000000000001263004425400210455ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/complex/test/test.lua000066400000000000000000000043241263004425400225320ustar00rootroot00000000000000local check = utest.check local T = utest.test T("ComplexTest", function() check.eq(complex("i"), complex(0,1)) check.eq(complex("-i"), complex(0,-1)) check.eq(complex("1"), complex(1,0)) check.eq(complex("+1"), complex(1,0)) check.eq(complex("-1"), complex(-1,0)) check.eq(complex("2i"), complex(0,2)) check.eq(complex("+2i"), complex(0,2)) check.eq(complex("-2i"), complex(0,-2)) check.eq(complex("1+i"), complex(1,1)) check.eq(complex("1-i"), complex(1,-1)) check.eq(complex("1+2i"), complex(1,2)) check.eq(complex("1-2i"), complex(1,-2)) check.eq(complex("+1-2i"), complex(1,-2)) check.eq(complex("-1+2i"), complex(-1,2)) -- check.errored(function() complex("--1") end) check.errored(function() complex("-+1") end) check.errored(function() complex("+-1") end) check.errored(function() complex("++1") end) check.errored(function() complex("1 i") end) check.errored(function() complex("1 2i") end) check.errored(function() complex("1+2") end) check.errored(function() complex("1++2i") end) check.errored(function() complex("1+-2i") end) check.errored(function() complex("1-+2i") end) check.errored(function() complex("1--2i") end) check.errored(function() complex("1-2i garbage") end) -- local a = complex(2,-3) check.number_eq(a:real(),2) check.number_eq(a:img(),-3) local t = table.pack(a:plane()) check.eq(#t, 2) check.number_eq(t[1],2) check.number_eq(t[2],-3) local t = table.pack(a:polar()) check.eq(#t, 2) check.number_eq(t[1], math.sqrt(2*2 + 3*3)) check.number_eq(t[2], -0.98279) check.number_eq(a:abs(), math.sqrt(2*2 + 3*3)) check.number_eq(a:angle(), -0.98279) check.number_eq(a:sqrt(), 1.674149) -- local b = complex("2-3i") check.eq(a,b) check.eq(a,a:clone()) check.eq(a:clone():conj(), complex(2,3)) check.eq(a:exp(), complex(-3.07493, -1.04274)) check.eq(tostring(a),tostring(b)) check.eq(a+b, complex(4,-6)) check.eq(a-2*b, complex(-2,3)) check.eq(2*a, complex(4,-6)) check.eq(a/2, complex(1,-1.5)) check.eq(complex(2,-3) * complex(-4,5), complex(2*-4 + 3*5, 2*5 + 3*4)) check.eq(-a, complex(-2,3)) end) april-ann-0.4.1/packages/basics/data_frame/000077500000000000000000000000001263004425400205025ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/data_frame/binding/000077500000000000000000000000001263004425400221145ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/data_frame/binding/bind_parse_csv_line.lua.cc000066400000000000000000000077161263004425400272060ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2015, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_H extern "C" { #include } #include "smart_ptr.h" #include "constString.h" //BIND_END //BIND_HEADER_C using namespace AprilUtils; double tonumber(constString tk, const char *decimal) { char *aux; double result; AprilUtils::UniquePtr new_tk = tk.newString(); for (size_t i=0; i 0) { if (n > old_n) { LUABIND_ERROR("Incorrect number of columns"); } else if (n < old_n) { for (++n; n <= old_n; ++n) { lua_pushvalue(L, NA_pos); lua_rawseti(L, t_pos, n); } } } lua_pushvalue(L, t_pos); LUABIND_INCREASE_NUM_RETURNS(1); } //BIND_END april-ann-0.4.1/packages/basics/data_frame/lua_src/000077500000000000000000000000001263004425400221325ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/data_frame/lua_src/data_frame.lua000066400000000000000000001570761263004425400247400ustar00rootroot00000000000000-- Inspired in pandas (Python) dataframe -- http://pandas-docs.github.io/pandas-docs-travis/ local data_frame,methods = class("data_frame", aprilio.lua_serializable) local groupped,groupped_methods = class("data_frame.groupped") local series,series_methods = class("data_frame.series", aprilio.lua_serializable) data_frame.series = series _G.data_frame = data_frame -- global definition ------------------------------------------------------------------ local assert = assert local ipairs = ipairs local pairs = pairs local tostring = tostring local tonumber = tonumber local type = type local NA = nan -- NaN values are used as "Not Available" local defNA = "NA" local tostring_nan = tostring(NA) -- utilities local function take(data, indices) local result if type(data) == "table" then result = {} for i=1,#indices do result[i] = data[indices[i]] end elseif type(data):find("^matrix") then result = data:index(1, indices) else error("Not recognized column data type") end return result end local function sparse_join(tbl, categories) local nrows = tbl[1]:dim(1) local ncols = iterator(tbl):map(bind(tbl[1].dim, nil, 2)):sum() local values = {} local indices,acc = {},0 for i=1,#tbl do values[i] = matrix(nrows, 1, tbl[i]:values()) indices[i] = matrixInt32(nrows, 1, tbl[i]:indices() ):scalar_add(acc) acc = acc + tbl[i]:dim(2) end values = matrix.join(2, values):data() indices = matrix.join(2, indices):data() local first_index = matrixInt32( tbl[1]:first_index() ):scal(#tbl):data() return matrix.sparse.csr(nrows, ncols, values, indices, first_index) end local function is_nan(v) return tonumber(v) and tostring(v) == tostring_nan end local function build_sorted_order(tbl, NA_symbol) local symbols = {} for i=1,#tbl do local v=tbl[i] symbols[is_nan(v) and NA_symbol or v] = true end local order = iterator(pairs(symbols)):select(1):table() table.sort(order, function(a,b) if type(a)~=type(b) then return tostring(a) < tostring(b) else return a 2, "For binary data sparse is not allowed") -- assuming the underlying data is categorical local values = matrix(#data):fill(1.0):data() local indices = matrixInt32(data):scalar_add(-1.0):data() local first_index = matrixInt32(indices:size()+1):linear():data() return matrix.sparse.csr(indices:size(), -- num rows ncols, -- num cols values, indices, first_index) else local ctor = april_assert(matrix_ctor[dtype], "Unable to build matrix type %s", dtype) if type(data) == "table" then return ctor(#data,1,data) else data = class.of(data)==ctor and data or data:convert_to(dtype) return data:right_inflate() end end end end -- concats a matrix or a table data using sep as delimiter local function concat(array, sep) if type(array) ~= "table" then array = array:toTable() end return table.concat(array, sep) end local function next_token_find(line, init, match, sep, quotechar) local quoted local i,j = line:find(match, init) if j and line:sub(j,j) ~= sep then i,j = line:find(quotechar, j+1) i,j = line:find(sep, j+1) i,j = i or #line, j or #line + 1 quoted = true end return i,j,quoted end local find = string.find local gsub = string.gsub local sub = string.sub local yield = coroutine.yield local tonumber = tonumber -- parses a CSV line using sep as delimiter and adding NA when required local parse_csv_line = util.__parse_csv_line__ -- checks if an array is a table or a matrix local function check_array(array, field) if type(array) ~= "table" then local c = class.of(array) april_assert(c, "Needs an array in parameter %s", field) local nd = array.num_dim assert(nd and nd(array) == 1, "Needs a one-dimensional matrix or a table") else for i=1,#array do array[i] = tonumber(array[i]) or array[i] end end return array end -- returns the inverted map of an array or a matrix local function invert(array) local t = {} for i,v in ipairs(array) do april_assert(not t[v], "Repeated identifier %s", tostring(v)) t[v] = i end return t end --------------------------------------------------------------------------- --------------------------------------------------------------------------- --------------------------------------------------------------------------- local function quote(x, sep, quotechar, decimal) if tonumber(x) then x = tostring(x) if decimal ~= "." then x = x:gsub("%.", decimal) end end if x:find(sep) then return "%s%s%s"%{quotechar,x,quotechar} else return x end end -- support for IPyLua local function data_frame_show(proxy) local plain = tostring(proxy) local html = {} local self = getmetatable(proxy) table.insert(html, "

") if not next(rawget(self, "data")) then table.insert(html, "

Empty data_frame

") else table.insert(html, "") table.insert(html, "") table.insert(html, "") for j,col_name in ipairs(rawget(self, "columns")) do if j > 20 then table.insert(html, "") break end table.insert(html, ""%{quote(col_name, '%s', '"', '.')}) end table.insert(html, "") local truncated = false for i,row_name in ipairs(rawget(self, "index")) do table.insert(html, "") if i > 20 then for j=1,(#rawget(self, "columns"))+1 do table.insert(html, "") if j > 21 then break end end truncated = true break else table.insert(html, ""%{row_name}) for j,col_name in ipairs(rawget(self, "columns")) do if j > 20 then table.insert(html, "") break end table.insert(html, ""%{quote(rawget(self, "data")[col_name][i], '%s', '"', '.')}) end end table.insert(html, "") end table.insert(html, "
...%s
...%s...%s
") end table.insert(html, "
# data_frame of %d rows x %d columns
"% {#rawget(self,"index"),#rawget(self,"columns")}) table.insert(html, "
") -- local data = { ["text/plain"] = plain, ["text/html"] = table.concat(html), } return data end local function dataframe_tostring(proxy) local self = getmetatable(proxy) if not next(rawget(self, "data")) then return table.concat{ "Empty data_frame\n", "# data_frame of %d rows x %d columns\n"% {#rawget(self,"index"),#rawget(self,"columns")} } else local tbl = { } for j,col_name in ipairs(rawget(self, "columns")) do table.insert(tbl, "\t") table.insert(tbl, quote(col_name, '%s', '"', '.')) end table.insert(tbl, "\n") local truncated = false for i,row_name in ipairs(rawget(self, "index")) do if i > 20 then table.insert(tbl, "...\n") truncated = true break end table.insert(tbl, row_name) for j,col_name in ipairs(rawget(self, "columns")) do table.insert(tbl, "\t") table.insert(tbl, quote(rawget(self, "data")[col_name][i], '%s', '"', '.')) end table.insert(tbl, "\n") end if truncated then local index = rawget(self,"index") for i=math.max(#index - 20, 21),#index do local row_name=index[i] table.insert(tbl, row_name) for j,col_name in ipairs(rawget(self, "columns")) do table.insert(tbl, "\t") table.insert(tbl, quote(rawget(self, "data")[col_name][i], '%s', '"', '.')) end table.insert(tbl, "\n") end end table.insert(tbl, "# data_frame of %d rows x %d columns\n"% {#rawget(self,"index"),#rawget(self,"columns")}) return table.concat(tbl) end end local function dataframe_index(proxy, key) local self = getmetatable(proxy) local tt = type(key) if tt == "number" then key, tt = { rawget(self,"columns")[key] }, "table" end if tt == "table" then local v = methods.column(proxy, key[1]) return v else return methods[key] end end local function dataframe_newindex(proxy, key, value) local self = getmetatable(proxy) local tt = type(key) if tt == "number" then key, tt = { rawget(self,"columns")[key] }, "table" end if tt == "table" then local data = rawget(self, "data") if data then local col_data = value local key = tonumber(key[1]) or key[1] local v = data[key] if v then methods.set(proxy, key, col_data) else methods.insert(proxy, col_data, { column_name=key }) end end else error("Unable to index with string, use a number or a table with the column name") end end data_frame.constructor = april_doc{ class = "method", summary = "Constructor for data_frame objects", description = "Builds an empty data_frame or a data_frame taken from given data", params = { data = { "A table indexed by column names with all the expected columns data [optional]" }, index = { "An index table (or matrix) which allow to identify every row [optional]" }, columns = { "Order of the columns given in data [optional]" }, }, outputs = { "An instance of data_frame class", }, } .. function(self, params) -- configure as proxy table local proxy do local mt = getmetatable(self) proxy = self self = {} self.__newindex = dataframe_newindex self.__index = dataframe_index self.__tostring = dataframe_tostring self.index_table = mt.index_table self.cls = mt.cls self.id = mt.id -- support for IPyLua self.ipylua_show = data_frame_show setmetatable(proxy, self) setmetatable(self, mt) end local params = get_table_fields({ data = { }, -- data can be a matrix or a Lua table index = { }, columns = { }, }, params or {}) local tdata = type(data) rawset(self, "columns", check_array( params.columns or {}, "columns" )) rawset(self, "col2id", invert(rawget(self, "columns"))) rawset(self, "data", {}) local t_params_index = type(params.index) if t_params_index == "string" or t_params_index == "number" then rawset(self, "index", {}) else rawset(self, "index", check_array( params.index or {}, "index" )) end rawset(self, "index2id", invert(rawget(self, "index"))) local data = params.data if type(data) == "table" then if #rawget(self, "index") == 0 then local n = #select(2,next(data)) rawset(self, "index", matrixInt32(n):linspace()) end local n = #rawget(self, "index") local cols = {} for col_name,col_data in pairs(data) do col_name = tonumber(col_name) or col_name table.insert(cols, col_name) if #rawget(self, "columns") > 0 then april_assert(rawget(self, "col2id")[col_name], "Not valid column name %s", col_name) end assert(n == #col_data, "Length of values does not match number of rows") if class.of(col_data) then local sq = assert(col_data.squeeze, "Needs matrix or table as columns") col_data = col_data:squeeze() assert(col_data:num_dim() == 1, "Needs a rank one matrix") end rawget(self, "data")[col_name] = col_data end if #rawget(self, "columns") == 0 then table.sort(cols) rawset(self, "columns", cols) rawset(self, "col2id", invert(cols)) end elseif data then assert(class.of(data), "Needs a matrix or dictionary in argument data") local nd = data.num_dim assert(nd and nd(data)==2, "Needs a bi-dimensional matrix in argument data") if #rawget(self, "columns") == 0 then rawset(self, "columns", iterator.range(data:dim(2)):table()) rawset(self, "col2id", invert(rawget(self, "columns"))) else assert(data:dim(2) == #rawget(self, "columns"), "Incorrect number of columns in data") end if #rawget(self, "index") == 0 then rawset(self, "index", matrixInt32(data:dim(1)):linspace()) rawset(self, "index2id", invert(rawget(self, "index"))) else assert(data:dim(1) == #rawget(self, "index"), "Incorrect number of rows in data") end for j,col_name in ipairs(rawget(self, "columns")) do rawget(self, "data")[col_name] = data:select(2,j) end end if t_params_index == "string" or t_params_index == "number" then proxy:set_index(params.index) end collectgarbage("collect") end data_frame.from_csv = april_doc{ class = "function", summary = "Builds a data_frame from a CSV file", description = "This loader allow empty fields", params = { "First parameter is the path to CSV filename, second parameter is a table", header = { "A boolean indicating if the CSV has a header row [optional],", "by default it is true" }, sep = { "Sep charecter for every field [optional], by default it is: ,"}, quotechar = { "Character used to as delimiter for strings [optional],", "by default it is: \"" }, decimal = { "Decimal point character [optional], by default it is: .", }, NA = { "Not avaliable token [optional], by default it is NA" }, index = { "Table or matrix with an index to identify every row, it", "can be a string indicating which column in CSV file is the", "index [optional]" }, columns = { "A table with column keys [optional]" }, }, outputs = { "An instance of data_frame class" }, } .. function(path, params) local proxy = data_frame() local self = getmetatable(proxy) local data = {} local params = get_table_fields({ header = { default=true }, sep = { default=',' }, quotechar = { default='"' }, decimal = { default='.' }, NA = { default=defNA }, index = { }, columns = { }, }, params or {}) local sep = params.sep local quotechar = params.quotechar local decimal = params.decimal local NA_str = params.NA local double_quote = quotechar..quotechar local quote_match = "^"..quotechar local quote_closing = quotechar.."("..quotechar.."?)" local decimal_match = "%"..decimal local number_match = "^[+-]?%d*"..decimal.."?%d+[eE]?[+-]?%d*$" assert(#sep == 1, "Only one character sep is allowed") assert(#quotechar <= 1, "Only zero or one character quotechar is allowed") assert(#decimal == 1, "Only one character decimal is allowed") local line_n = 0 local f = type(path)~="string" and path or assert( io.open(path) ) local aux = {} if params.header then line_n = line_n + 1 local line = f:read("*l") if line then local t,msg = parse_csv_line(aux, line..sep, sep, quotechar, decimal, NA_str, nan) if not t then error("Problem reading CSV filename at line 1: "..msg) end rawset(self, "columns", iterator(t):table()) for i,col_name in ipairs(rawget(self, "columns")) do if is_nan(col_name) then col_name = next_number(rawget(self, "columns")) rawget(self, "columns")[i] = col_name end end if params.columns then assert(#rawget(self,"columns") == #params.columns, "Incorrect number of columns at field 'columns'") rawset(self, "columns", params.columns) end rawset(self, "col2id", invert(rawget(self, "columns"))) for j,col_name in ipairs(rawget(self, "columns")) do data[j] = {} end else -- not line rawset(self, "columns", {}) rawset(self, "col2id", {}) end elseif params.columns then rawset(self, "columns", params.columns) rawset(self, "col2id", invert(rawget(self, "columns"))) for j,col_name in ipairs(rawget(self, "columns")) do data[j] = {} end end local n = 0 if #rawget(self, "columns") == 0 then line_n = line_n + 1 n = n + 1 local line = f:read("*l") if line then local parsed_t,msg = parse_csv_line(aux, line..sep, sep, quotechar, decimal, NA_str, nan) if not parsed_t then error("Problem reading CSV filename at line %d: %s"%{line_n,msg}) end local first_line = iterator(parsed_t):table() rawset(self, "columns", iterator.range(#first_line):table()) rawset(self, "col2id", invert(rawget(self, "columns"))) for j,col_name in ipairs(rawget(self, "columns")) do data[j] = { first_line[j] } end else -- not line rawset(self, "columns", {}) rawset(self, "col2id", {}) end end local columns = rawget(self, "columns") for row_line in f:lines() do line_n = line_n + 1 n = n + 1 local t,msg repeat t,msg = parse_csv_line(aux, row_line..sep, sep, quotechar, decimal, NA_str, nan) if not t then if msg:find("unmatched") then -- retry appending the next line row_line = table.concat({row_line,"\n",f:read("*l")},"\n") else error("Problem reading CSV filename at line %d: %s"%{line_n,msg}) end end until t for j=1,#t do data[j][n] = t[j] end if n%1000000 == 0 then collectgarbage("collect") end end local obj_data = rawget(self, "data") for j,col_name in ipairs(rawget(self, "columns")) do obj_data[col_name] = data[j] end if n == 0 then rawset(self, "index", {}) rawset(self, "index2id", {}) else rawset(self, "index", matrixInt32(n):linspace()) rawset(self, "index2id", invert(rawget(self, "index"))) end if path ~= f then f:close() end if params.index then proxy:set_index(params.index) end collectgarbage("collect") return proxy end methods.to_csv = april_doc{ class = "method", summary = "Writes the caller data_frame into a CSV filename", params = { "The first one is a filename, the second one is a table", header = { "Boolean indicating if the header should be written [optional], by default it is true" }, sep = { "Character used as sep [optional], by default it is: ," }, quotechar = { "Character used to as delimiter for strings [optional],", "by default it is: \"" }, decimal = { "Decimal point character [optional], by default it is: .", }, NA = { "Not avaliable token [optional], by default it is NA" }, }, } .. function(self, path, params) local self = getmetatable(self) local params = get_table_fields({ header = { default=true }, sep = { default=',' }, quotechar = { default='"' }, NA = { default=defNA }, decimal = { default="." }, }, params or {}) local sep = params.sep local quotechar = params.quotechar local NA_str = params.NA local decimal = params.decimal assert(#sep == 1, "Only one character sep is allowed") assert(#quotechar <= 1, "Only zero or one character quotechar is allowed") local f = type(path)~="string" and path or assert( io.open(path, "w") ) if params.header then local columns = {} for i,col_name in ipairs(rawget(self, "columns")) do columns[i] = quote(col_name, sep, quotechar, decimal) end f:write(concat(columns, sep)) f:write("\n") end local data = rawget(self, "data") local tbl = {} for i,row_name in ipairs(rawget(self, "index")) do for j,col_name in ipairs(rawget(self, "columns")) do local v = data[col_name][i] if tonumber(v) and is_nan(v) then v = NA_str end tbl[j] = quote(v, sep, quotechar, decimal) end f:write(table.concat(tbl, sep)) f:write("\n") table.clear(tbl) end if path ~= f then f:close() end collectgarbage("collect") end methods.drop = april_doc{ class = "method", summary = "Removes one column or row from the data_frame (it is done in-place)", params = { "A dimension number (1 for rows, 2 for columns)", "First column or row name to drop", "Second column or row name to drop", "...", "Last column or row name to drop", } } .. function(self, dim, ...) local self = getmetatable(self) assert(dim, "Needs a dimension number, 1 or 2") local labels = table.pack(...) if dim == 1 then error("Not implemented for index") elseif dim == 2 then local num_cols = #rawget(self, "columns") local new_columns = {} if type(rawget(self, "columns")) ~= "table" then new_columns = matrixInt32(num_cols - #labels) end local deleted = {} for _,col_name in ipairs(labels) do local col_name = tonumber(col_name) or col_name local col_id = april_assert(rawget(self, "col2id")[col_name], "Unknown column name %s", col_name) deleted[col_id] = true rawget(self, "data")[col_name] = nil rawget(self, "col2id")[col_name] = nil end local j=1 for i=1,num_cols do if not deleted[i] then local v = rawget(self, "columns")[i] new_columns[j] = v rawget(self, "col2id")[v] = j j=j+1 end end rawset(self, "columns", new_columns) else error("Incorrect dimension number, it should be 1 or 2") end end methods.as_matrix = april_doc{ class = "method", summary = "Converts the whole data_frame (or a given list of its columns) into a matrix", params = { "First column [optional]", "...", "Last column [optional]", "Last argument can be a table of parameters with fields: dtype, categorical_dtype, categories, NA", }, outputs = { "A matrix instance", } } .. function(self, ...) local self = getmetatable(self) local args = table.pack(...) local params = {} if #args > 0 and type(args[#args]) == "table" then params = table.remove(args) end params = get_table_fields({ dtype = { type_match = "string", default = "float" }, categorical_dtype = { type_match = "string", default = "float" }, categories = { type_match = "table", default = nil }, NA = { default = NA }, }, params) local categories = params.categories or {} local inv_categories = {} local dtype = params.dtype local categorical_dtype = params.categorical_dtype local NA = params.NA assert(dtype ~= "sparse", "Sparse is only allowed in categorical_dtype field") local data = rawget(self, "data") local col2id = rawget(self, "col2id") local cols_slice if #args == 0 then cols_slice = rawget(self, "columns") else cols_slice = args --if dtype == "categorical" then --assert(#categories == 0 or type(categories[1]) == "table" and --#categories == #args, "Needs a table with category arrays in categories field") --end end local tbl = {} for i,col_name in ipairs(cols_slice) do local dtype = dtype april_assert(col2id[col_name], "Unknown column name %s", col_name) local col_data = data[col_name] if dtype == "categorical" then dtype = categorical_dtype col_data,categories[i],inv_categories[i] = categorical(col_data, NA, categories[i]) end local ncols = categories[i] and #categories[i] local m = to_matrix(col_data, dtype, ncols) if not is_nan(NA) then m[m:eq(nan)] = NA end if ncols and ncols <= 2 then m:scalar_add(-1.0) end table.insert(tbl, m) end if dtype == "categorical" then if categorical_dtype == "sparse" then return sparse_join(tbl, categories),categories,inv_categories else return matrix.join(2, tbl),categories,inv_categories end else return matrix.join(2, tbl) end end -- methods.loc = -- function(proxy, row_key) -- local self = getmetatable(proxy) -- local row_key = tonumber(row_key) or row_key -- local i = assert(rawget(self, "index2id")[row_key], "Unknown label") -- return methods.iloc(proxy, i) -- end -- methods.iloc = -- function(proxy, i) -- local self = getmetatable(proxy) -- local data = rawget(self, "data") -- local result = {} -- for _,col_name in ipairs(rawget(self, "columns")) do -- result[col_name] = { data[col_name][i] } -- end -- return data_frame{ -- data = result, -- index = { (assert(rawget(self, "index")[i], "Index out-of-bounds")) }, -- columns = rawget(self, "columns"), -- } -- end methods.column = april_doc{ class = "method", summary = "Returns a column data", params = { "The column name" }, outputs = { "The column data" }, } .. function(self, key) local self = getmetatable(self) local data = rawget(self, "data") if data then return data[tonumber(key) or key] end end methods.insert = april_doc{ class = "method", summary = "Inserts a new column", params = { "The column data", "A table with column_name and location [optional]", }, } .. function(self, col_data, params) local self = getmetatable(self) local params = get_table_fields({ column_name = { }, location = { type_match="number" }, }, params or {}) local col_name = params.column_name or next_number(rawget(self, "columns")) local location = params.location or (#rawget(self, "columns")+1) col_name = tonumber(col_name) or col_name assert(location >= 1 and location <= (#rawget(self, "columns")+1), "Parameter location is out-of-bounds") april_assert(not rawget(self, "col2id")[col_name], "Column name collision: %s", col_name) local columns = rawget(self, "columns") if type(columns) ~= "table" then columns = columns:toTable() end table.insert(columns, location, col_name) rawset(self, "columns", columns) rawset(self, "col2id", invert(rawget(self, "columns"))) if class.of(col_data) then local sq = assert(col_data.squeeze, "Needs matrix or table as columns") col_data = col_data:squeeze() assert(col_data:num_dim() == 1, "Needs a rank one matrix") end if #rawget(self, "index") == 0 then rawset(self, "index", matrixInt32(#col_data):linspace()) end assert(#col_data == #rawget(self, "index"), "Length of values does not match number of rows") rawget(self, "data")[col_name] = col_data end methods.set = april_doc{ class = "method", summary = "Changes the data in a given column name", params = { "The column name", "The new column data", }, } .. function(self, col_name, col_data) local self = getmetatable(self) assert(col_name, "Needs column name as first argumnet") assert(col_data, "Needs column data as second argument") local col_name = tonumber(col_name) or col_name april_assert(rawget(self, "col2id")[col_name], "Unknown column name: %s", col_name) if class.of(col_data) then local sq = assert(col_data.squeeze, "Needs matrix or table as columns") col_data = col_data:squeeze() assert(col_data:num_dim() == 1, "Needs a rank one matrix") end assert(#col_data == #rawget(self, "index"), "Length of values does not match number of rows") rawget(self, "data")[col_name] = col_data end methods.reorder = april_doc{ class="method", summary="Changes the order of the columns", } .. function(self, columns) local self = getmetatable(self) local columns = check_array(columns) for i,col_name in pairs(columns) do april_assert(rawget(self, "col2id")[col_name], "Unknown column %s", col_name) end assert(#columns == #rawget(self, "columns"), "Unexpected number of columns") rawset(self, "columns", columns) rawset(self, "col2id", invert(columns)) end methods.set_index = april_doc{ class="method", summary="Changes the index", } .. function(self, col_name_or_data) local self = getmetatable(self) local col_name_or_data = tonumber(col_name_or_data) or col_name_or_data local tt = type(col_name_or_data) if tt == "string" or tt == "number" then rawset(self, "index", check_array(april_assert(rawget(self, "data")[col_name_or_data], "Unable to locate column %s", col_name_or_data), "1")) else rawset(self, "index", check_array( col_name_or_data or {}, "1" )) end rawset(self, "index2id", invert(rawget(self, "index"))) end do local function get_key(df, key) if not key then return df:get_index() else return (april_assert(df[{ key }], "Unable to locate column name %s", key)) end end methods.merge = april_doc{ class="method", summary="Implements join operation between this and other data_frame", } .. function(self, other, params) local params = get_table_fields({ how = { default="left" }, on = { }, left_on = { }, right_on = { }, }, params or {}) local how = params.how local left_key = params.left_on or params.on local right_key = params.right_on or params.on if how == "right" then self,other = other,self end local result = data_frame() local result_proxy = result local result = getmetatable(result) local self_proxy = self local other_proxy = other local self = getmetatable(self) local other = getmetatable(other) local self_index = rawget(self, "index") local other_index = rawget(other, "index") local other_index2id = rawget(other, "index2id") local result_index -- if left_key then april_assert(self_proxy[{ left_key }], "Unable to locate column %s", left_key) end if right_key then april_assert(other_proxy[{ right_key }], "Unable to locate column %s", right_key) end -- prepare the result_index depending in the given join type (how) if how == "right" or how == "left" then result_proxy:set_index(self_index) elseif how == "outer" then error("Not implemented") assert(type(other_index) == type(self_index), "Incompatible indices in given data_frames") local idx = {} for i=1,#self_index do idx[self_index[i]] = true end for i=1,#other_index do idx[other_index[i]] = true end idx = iterator(pairs(idx)):select(1):table() table.sort(idx) if type(self_index) ~= "table" then idx = class.of(self_index)(idx) end result_proxy:set_index(idx) elseif how == "inner" then error("Not implemented") local self_key = get_key(self_proxy, key) local other_key = get_key(other_proxy, key) assert(type(other_index) == type(self_index), "Incompatible indices in given data_frames") local idx = {} for i=1,#self_index do local j = self_index[i] if other_index2id[j] then table.insert(idx, j) end end if type(self_index) ~= "table" then idx = class.of(self_index)(idx) end result_proxy:set_index(idx) else error("Incorrect how type " .. tostring(how)) end local result_index = rawget(result, "index") local function process_columns(df, index2id, id2index) local col_names = rawget(df, "columns") local data = rawget(df, "data") for j=1,#col_names do local result_col2id = rawget(result, "col2id") local col_name = col_names[j] local col_data = data[col_name] if type(col_name) == "number" or not result_col2id[col_name] then local new_col_data if type(data) == "table" then new_col_data = {} else new_col_data = class.of(col_data)(#col_data) end for i=1,#result_index do local k = index2id[id2index[i]] new_col_data[i] = k and col_data[k] or NA end -- for every index in self if type(col_name) == "number" then col_name = next_number(rawget(result, "columns")) end result_proxy[{col_name}] = new_col_data else -- if it is a new column local new_col_data = result_proxy[{col_name}] for i=1,#result_index do local k = index2id[id2index[i]] if k then local v = new_col_data[i] if not v or is_nan(v) then new_col_data[i] = col_data[k] else -- { v and not is_nan(v) } assert(v == col_data[k], "Not compatible data frames") end end -- if exists current index key in df end -- for every index in result end -- existing column end -- for every column in df end -- function process_columns -- process all columns in both data frames if how == "left" then process_columns(self, rawget(self, "index2id"), result_index) process_columns(other, invert(get_key(other_proxy, right_key)), get_key(result_proxy, left_key)) elseif how == "right" then process_columns(other, rawget(other, "index2id"), result_index) process_columns(self, invert(get_key(self_proxy, right_key)), get_key(result_proxy, left_key)) else error("Not implemented") end return result_proxy end end methods.get_index = function(self) local self = getmetatable(self) return util.clone(rawget(self, "index")) end methods.get_columns = function(self) local self = getmetatable(self) return util.clone(rawget(self, "columns")) end methods.ncols = function(self) local self = getmetatable(self) return #rawget(self, "columns") end methods.nrows = function(self) local self = getmetatable(self) return #rawget(self, "index") end methods.levels = function(self, key, NA_symbol) local self = getmetatable(self) local key = tonumber(key) or key local data = rawget(self, "data") return build_sorted_order(data[key], NA_symbol or defNA) end methods.counts = function(self, key, NA_symbol) NA_symbol = NA_symbol or defNA local self = getmetatable(self) local key = tonumber(key) or key local data = rawget(self, "data") local tbl = data[key] local counts = {} for i=1,#tbl do local v = tbl[i] local x = is_nan(v) and NA_symbol or v counts[x] = (counts[x] or 0) + 1 end return counts end methods.ctor_name = function(self) return "data_frame" end methods.ctor_params = function(self) local self = getmetatable(self) return { data = rawget(self, "data"), index = rawget(self, "index"), columns = rawget(self, "columns"), } end methods.clone = function(self) return data_frame(util.clone(self:ctor_params())) end methods.map = april_doc{ class="method", summary="Maps a list of columns data into a new result table", } .. function(self, ...) local col_names = { ... } local func = table.remove(col_names) assert(type(func) == "function", "Needs a function as last argument") local self = getmetatable(self) local data = {} for i=1,#col_names do local col_name = col_names[i] data[i] = april_assert(rawget(self, "data")[col_name], "Unable to locate column %s", col_name) end local result,input = {},{} for i=1,#rawget(self, "index") do for j=1,#data do input[j] = data[j][i] end result[i] = func(table.unpack(input)) end return result end methods.iterate = april_doc{ class="method", summary="Iterates over all rows (as ipairs). Be careful, the returned table is reused between loop iterations.", } .. function(proxy, ...) local self = getmetatable(proxy) local data = rawget(self, "data") local columns = table.pack(...) if #columns == 0 then columns = rawget(self, "columns") end local col2id = rawget(self, "col2id") local idata = {} for i,name in ipairs(columns) do april_assert(col2id[name], "Unknown column name %s", tostring(name)) idata[i] = data[name] end local row = {} return function(self, i) if i < #rawget(self,"index") then i = i + 1 for j=1,#columns do row[columns[j]] = idata[j][i] end return i,row end end,self,0 end methods.parse_datetime = april_doc{ class="method", summary="Transforms the given columns into timestamp", outputs={ "A Lua table", }, } .. function(self, ...) local self = getmetatable(self) local data = rawget(self, "data") local args = table.pack( ... ) -- returns a table with year,month,day,hour,min,sec,isdst, as in os.time local parser = assert( (type(args[#args]) == "function") and table.remove(args) or nil, "Needs a parser function as last argument" ) local list = iterator(ipairs(args)): map(function(i,col_name) col_name = tonumber(col_name) or col_name return i,april_assert(data[col_name], "Unable to locate column %s", col_name) end):table() local result = iterator(multiple_ipairs(table.unpack(list))): -- FIXME: check table returned by parser function map(function(i,...) return i,os.time(parser(table.concat({...}, " "))) end): table() return result end methods.count_NAs = function(proxy) local self = getmetatable(proxy) local data = rawget(self, "data") local result = {} for col_name,v in pairs(data) do local count = 0 for i=1,#v do if is_nan(v[i]) then count=count+1 end end result[col_name] = count end return result end methods.select = function(self,params) end methods.groupby = april_doc{ class="method", summary="Groups all data using the given columns values", outputs={ "A groupped data object", }, } .. function(self, ...) return groupped(self, ...) end methods.index = april_doc{ class="method", summary="Indexes the data frame by rows using the given indices table or matrix. The indices table or matrix are row numbers, not real index values.", outputs={ "A new allocated data_frame", }, } .. function(proxy, indices) local self = getmetatable(proxy) local data = rawget(self, "data") local idx = take(rawget(self, "index"), indices) local result = data_frame{ index=idx } for _,col_name in ipairs(rawget(self, "columns")) do result[{col_name}] = take(data[col_name], indices) end return result end ------------------------------------------------------------------ function groupped.constructor(self, df, ...) local args = table.pack(...) self.depth = args.n self.columns = args self.df = df local groups = {} local level2id = {} for _,col_name in ipairs(args) do groups[col_name] = {} level2id[col_name] = {} local current = groups[col_name] local lv2id = level2id[col_name] local data = df[{col_name}] -- if type(data):find("^matrix") then data = data:toTable() end local k = 0 for i=1,#data do local v = data[i] local x = lv2id[v] or (k+1) if x == k+1 then lv2id[v],k=x,x current[x]={} end local t = current[x] t[#t+1] = i end end self.groups = groups self.level2id = level2id collectgarbage("collect") end groupped_methods.levels = function(self, col_name) return table.invert(self.level2id[col_name]) end local function intersect(a,b) local t = {} local i,j=1,1 local Na,Nb = #a,#b while i<=Na and j<=Nb do if a[i] < b[j] then i=i+1 elseif b[j] < a[i] then j=j+1 else t[#t+1],i,j = a[i],i+1,j+1 end end return t end local function get_columns_indices(self, key) local columns = self.columns local groups = self.groups local level2id = self.level2id local aux = {} for i=1,#key do local v = key[i] local c = columns[i] local x = april_assert(level2id[c][v], "Unknown column value level: %s", key[i]) aux[i] = groups[c][x] end return aux end local function binary_intersect(self, key) local aux = get_columns_indices(self, key) -- binary intersection while #aux > 1 do local N = #aux for j=1,math.floor(N/2),1 do local k = N-j+1 local a,b a,b,aux[k] = aux[j],aux[k],nil aux[j] = intersect(a,b) end end return aux[1] end groupped_methods.get_group = function(self, ...) local key = { ... } assert(#key == self.depth, "Incompatible number of column values") local df = self.df:index( binary_intersect(self, key) ) collectgarbage("collect") return df end local MAX = 40 local function levels_to_string(x) local size = 0 local t = {} for i=1,#x do local y = tostring(x[i]) size = size+#y if size>=MAX then break end t[i] = y end if #t ~= #x then t[#t+1] = "..." if #tostring(x[#x]) < MAX then t[#t+1] = tostring(x[#x]) end end return table.concat(t, " ") end class.extend_metamethod(groupped, "__tostring", function(self) local level2id = self.level2id local t = { } for i,col_name in ipairs(self.columns) do local levels = self:levels(col_name) table.sort(levels, function(a,b) if type(a)~=type(b) then return tostring(a) < tostring(b) else return a= 2) assert(#x == #y) local i = 1 -- traverse x and y tables result:zeros() -- interpolate first segment if x[i] < start then local x1,x2 = x[i],x[i+1] if x2 > start then local y1,y2 = y[i],y[i+1] local x1,y1 = one_interp(x1, x2, y1, y2, start) integrate(result, inv_T, x1, x2, y1, y2) end i = i + 1 end -- integrate the whole region between start and frontier do assert(x[i] >= start) local j = i while j<#x and x[j+1] <= frontier do j = j + 1 end if i ~= j then local x_dif = x[{ {i+1,j} }] - x[{ {i,j-1} }] local y_sum = y[{ {i+1,j} }] + y[{ {i,j-1} }] result:scalar_add( 0.5 * inv_T * x_dif:cmul( y_sum ):sum() ) end i = j end -- interpolate last segment if i<#x then local x1,x2 = x[i],x[i+1] local y1,y2 = y[i],y[i+1] local x2,y2 = one_interp(x1, x2, y1, y2, frontier) integrate(result, inv_T, x1, x2, y1, y2) i = i + 1 end assert(i == #x) end local function aggregate_rectangle(result, period, inv_T, x, y, start, frontier) assert(#x >= 2) assert(#x == #y) local i = 1 -- traverse x and y tables result:zeros() -- interpolate first segment if x[i] < start then local x1,x2 = x[i],x[i+1] if x2 > start then local x1 = start local y1 = y[i+1] local y2 = y1 integrate(result, inv_T, x1, x2, y1, y2) end i = i + 1 end -- integrate the whole region between start and frontier do assert(x[i] >= start) local j = i while j<#x and x[j+1] <= frontier do j = j + 1 end if i ~= j then local x_dif = x[{ {i+1,j} }] - x[{ {i,j-1} }] local y_sum = y[{ {i,j-1} }] * 2 result:scalar_add( 0.5 * inv_T * x_dif:cmul( y_sum ):sum() ) end i = j end -- interpolate last segment if i<#x then local x1,x2 = x[i],frontier local y1 = y[i] local y2 = y1 integrate(result, inv_T, x1, x2, y1, y2) i = i + 1 end assert(i == #x) end local function check_sequential(self) local time = self.time if #time == 1 then self.seq_period = 1 elseif #time == 2 then self.seq_period = time[2] - time[1] else local aux = time[{'2:'}] - time[{'1:-2'}] if aux:eq( (aux:max()) ):all() then self.seq_period = max end end end -------------------------------------------------- -------------------------------------------------- -------------------------------------------------- series.constructor = april_doc{ class = "method", summary = "Constructs a time series given a data_frame and a serie of column names", description = { "Time stamp column should be numeric and will be interpreted with double resolution.", "Data columns should be numeric and will be interpreted to float resolution.", "This class clones the memory of the given data_frame for performance purposes.", }, params = { "A data_frame instance", "A timestamp column name. It can be nil, in which case a sequence would be generated", "A data column name", "...", }, outputs = { "An instance of series class", }, } .. function(self, df, time_column, ...) if not class.is_a(df, data_frame) then -- loading directly from matrix data local time = df local data = time_column assert(class.is_a(time, matrixDouble)) assert(class.is_a(data, matrix)) self.time_column_name = select(1, ...) self.data_column_names = table.pack( select(2, ...) ) self.time = time self.data = data check_sequential(self) else assert(class.is_a(df, data_frame), "Needs a data_frame as first argument") assert(..., "At least three arguments are needed") local data_columns = table.pack(...) self.time_column_name = time_column or "time" self.data_column_names = data_columns self.data = df:as_matrix(...) -- by default it is float if time_column then self.time = df:as_matrix(time_column, { dtype="double" }):squeeze() check_sequential(self) else -- generate a sequence for time column self.time = matrixDouble(self.data:dim(1)):linear() self.seq_period = 1 end end end series_methods.ctor_name = function(self) return "data_frame.series" end series_methods.ctor_params = function(self) return self.time, self.data, self.time_column_name, table.unpack(self.data_column_names) end series_methods.clone = function(self) return series(table.unpack(util.clone(table.pack(self:ctor_params())))) end series_methods.get_time = april_doc{ class = "method", summary = "Returns the time column", } .. function(self) return self.time end series_methods.get_data = april_doc{ class = "method", summary = "Returns the data column", } .. function(self) return self.data end series_methods.to_data_frame = april_doc{ class = "method", summary = "Returns a data_frame which references this time series", } .. function(self) local col_names = table.join( {self.time_column_name}, self.data_column_names) local df_data = iterator.zip( iterator(self.data_column_names), iterator(matrix.ext.iterate(self.data, 2):select(2) ) ):table() df_data[self.time_column_name] = self.time return data_frame{ data=df_data, columns = col_names } end series_methods.resampleU = april_doc{ class = "method", summary = "Resamples the time series using a uniform time period", params = { "The desired time period, a number >= 1 in same units as timestamp column", { "A table of extra arguements, as start_time, stop_time, and resampling method.", "Currently method can be 'trapezoid' (by default) or 'rectangle'", }, }, outputs = { "A new series instance with all resampled data", }, } .. function(self, period, params) local params = get_table_fields({ start_time={type_match="number"}, stop_time={type_match="number"}, method={type_match="string", default="trapezoid"}, }, params) local start_time = params.start_time local stop_time = params.stop_time local method = params.method local interpolate,aggregate if method == "trapezoid" then interpolate = interpolate_trapezoid aggregate = aggregate_trapezoid elseif method == "rectangle" then interpolate = interpolate_rectangle aggregate = aggregate_rectangle else error("Unknown method " .. method) end -- HALF is used to move time labels in order to center data aggregations -- into the resampled time labels. local HALF = period * 0.5 local time = self.time + HALF local data = self.data local inv_T = 1/period -- data should be sorted by time, it is expected monotonous time (increasing) assert(type(period) == "number" , "Needs a period number as first argument") assert(period >= 1 and math.floor(period) == period, "Expected an integer period >= 1 as first argument") local N = #data local first = math.floor( time[1] * inv_T + 1 ) * period local last = math.floor( time[#time] * inv_T - 1 ) * period if start_time then assert(start_time % period == 0, "start_time should be multiple of period") start_time = start_time + HALF assert(start_time >= first, "start_time should be >= than first timestamp+period") first = start_time end if stop_time then assert(stop_time % period == 0, "stop_time should be multiple of period") stop_time = stop_time + HALF assert(stop_time <= last, "stop_time should be <= than last timestamp-period") last = stop_time end -- remove first value to avoid rounding problems with large timestamp values -- in float resolution at aggregation and/or interpolate functions local time = time:scalar_add(-first):convert_to("float") local old_first old_first, first, last = first, 0, last-first local result_length = (last - first)/period local result_times = matrixDouble(result_length):linspace():scal(period):scalar_add(old_first) local result = matrix(result_length, data:dim(2)) local i,j = 1,1 while i<=result_length do if i%1000000 == 0 then collectgarbage("collect") end local slice_first, slice_next = i*period, (i+1)*period -- search the lower bound for slice_first (if possible) while time[j] < slice_first do j = j+1 end j = j - 1 -- search the upper bound for slice_next local k = j while time[k] < slice_next do k = k + 1 end local x = time[{ {j,k} }] local t_j = x[1] local t_k = x[#x] -- Two cases: -- 1. When #x == 2, interpolate. -- 2. Otherwise aggregate. if #x==2 and x[1] < slice_first and x[2] > slice_next then local next_i = i + math_floor(t_k * inv_T) - math_ceil(t_j * inv_T) - 1 interpolate(result[{ {i,next_i}, ':' }], period, inv_T, x, data[{ {j,k}, ':' }]) i = next_i else -- dt <= period assert(#x >= 2) aggregate(result[i], period, inv_T, x, data[{ {j,k}, ':'}], slice_first, slice_next) end j = k - 1 i = i + 1 end -- build resulting data_frame and time series instance local result_ts = series(result_times, result, self.time_column_name, table.unpack(self.data_column_names)) collectgarbage("collect") return result_ts end class.extend_metamethod( series, "__tostring", function(self) return tostring(self:to_data_frame()):gsub("data_frame", "data_frame.series") end ) class.extend_metamethod( series, "ipylua_show", function(self) local df = self:to_data_frame() local show = getmetatable(df).ipylua_show local tbl = show(df) for k,v in pairs(tbl) do tbl[k] = tbl[k]:gsub("data_frame", "data_frame.series") end return tbl end ) ------------------------------------------------------------------ ------------------------------------------------------------------ ------------------------------------------------------------------ return data_frame april-ann-0.4.1/packages/basics/data_frame/package.lua000066400000000000000000000017771263004425400226140ustar00rootroot00000000000000 package{ name = "data_frame", version = "1.0", depends = { "util", "mathcore", "matrix", "aprilio" }, keywords = { "data_frame" }, description = "no description available", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test.lua", }, }, }, target{ name = "provide", depends = "init", provide_bind{ file = "binding/bind_parse_csv_line.lua.cc", dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp = true, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_parse_csv_line.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/data_frame/test/000077500000000000000000000000001263004425400214615ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/data_frame/test/test.lua000066400000000000000000000206301263004425400231440ustar00rootroot00000000000000local check = utest.check local T = utest.test local warning = utest.warning T("DataFrameTest", function() local df1 = data_frame.from_csv(aprilio.stream.c_string("a,b,c\n1,2,3\n4,5,6"), { columns={"d","e","f"} }) check.eq(table.concat(df1:get_columns(),","), "d,e,f" ) check.errored(function() local df1 = data_frame.from_csv(aprilio.stream.c_string("a,c\n1,3\n4,6"), { columns={"d","e","f"} }) end) local df1 = data_frame.from_csv(aprilio.stream.c_string("a,b,c\n1,2,3\n4,5,6")) check.eq(table.concat(df1:get_columns(),","), "a,b,c") local df1 = data_frame() check.eq(#df1:get_index(), 0) check.eq(#df1:get_columns(), 0) check.NIL(df1[{"a"}]) check.TRUE(tostring(df1)) -- local df2 = data_frame{ data = { one = {1,2,3,4}, two = {5,6,7,8}, three = { "A", "B", "B", "C" }, }, columns = { "two", "one", "three" }, index = { "a", "b", "c", "d" } } print(df2:groupby("three"):get_group("B")) print(df2:groupby("three", "one"):get_group("B",2)) check.eq(#df2:get_index(), 4) check.eq(#df2:get_columns(), 3) check.eq(df2[{"three"}][1], "A") check.eq(df2[{"three"}][2], "B") check.eq(df2[{"three"}][3], "B") check.eq(df2[{"three"}][4], "C") local m_index = df2:as_matrix("three", { dtype="categorical" }) local m_sparse = df2:as_matrix("three", { dtype="categorical", categorical_dtype="sparse" }) local m_sparse2 = df2:as_matrix("three", "three", { dtype="categorical", categorical_dtype="sparse" }) check.eq(m_index, matrix(4,1,{1,2,2,3})) check.eq(m_sparse, matrix.sparse(matrix(4,3,{1,0,0,0,1,0,0,1,0,0,0,1}))) check.eq(m_sparse2, matrix.sparse(matrix(4,6,{1,0,0,1,0,0,0,1,0,0,1,0,0,1,0,0,1,0,0,0,1,0,0,1}))) local m = df2:as_matrix("one", "two") check.eq(m, matrix(4,2,{1,5,2,6,3,7,4,8})) local df22 = data_frame{ data = { three = { "A", "C", "D" }, four = { 3, 4, 5 } }, columns = { "three", "four" }, index = { "a", "e", "f" } } print(df2:merge(df22, { how="left" })) print(df2:merge(df22, { how="right" })) -- print(df2:merge(df22, { how="inner" })) -- print(df2:merge(df22, { how="outer" })) -- local df3 = data_frame{ data = matrix(4,20):linear() } local _ = df3[{3}] local _ = df3:as_matrix(2, { dtype="complex", }) -- local df4 = data_frame.from_csv(aprilio.stream.c_string[[id,cost 1,4 2,1 3,10 ]]) df4[{"cost"}] = {2,3,4} df4:drop(2, "id") local tmp = os.tmpname() df4:to_csv(tmp) os.remove(tmp) -- local m = matrix(20,1):linspace() local df5 = data_frame() df5:insert(m) -- local df6 = data_frame{ data = { one = { "A", "B", "B", "A" }, } } local m_index = df6:as_matrix({ dtype="categorical" }) check.eq(m_index, matrix(4,1,{0,1,1,0})) check.errored(function() local m_index = df6:as_matrix({ dtype="categorical", categorical_dtype = "sparse" }) end) end) T("TimeSeriesTest", function() local x = matrix(100):logspace(1,1000):toTable() local y = matrix(100, 1):logspace(1,10000) local df = data_frame{ data={ x=x, y=y } } local ts = data_frame.series(df, "x", "y") local tsp = ts:resampleU(12) local result = tsp:to_data_frame():as_matrix() local target = matrix.fromString[[81 2 ascii 24 69.562454223633 36 119.13578796387 48 174.67581176758 60 235.10885620117 72 299.74032592773 84 368.08569335938 96 439.77239990234 108 514.53790283203 120 592.09564208984 132 672.33374023438 144 755.01239013672 156 840.02197265625 168 927.25207519531 180 1016.5922851562 192 1107.9356689453 204 1201.1889648438 216 1296.2810058594 228 1393.1770019531 240 1491.8707275391 252 1592.0684814453 264 1693.8811035156 276 1797.4688720703 288 1902.2569580078 300 2008.7111816406 312 2116.6069335938 324 2225.6887207031 336 2336.4819335938 348 2448.1472167969 360 2561.6040039062 372 2675.83984375 384 2791.7150878906 396 2908.6181640625 408 3026.5341796875 420 3146.1591796875 432 3266.0690917969 444 3388.0759277344 456 3510.5451660156 468 3633.9838867188 480 3759.2885742188 492 3884.640625 504 4011.5393066406 516 4139.83984375 528 4268.1416015625 540 4398.0336914062 552 4529.3530273438 564 4660.671875 576 4793.0141601562 588 4927.3706054688 600 5061.7802734375 612 5196.404296875 624 5333.3442382812 636 5470.9174804688 648 5608.490234375 660 5746.794921875 672 5887.4311523438 684 6028.2412109375 696 6169.05078125 708 6310.6962890625 720 6454.6796875 732 6598.8017578125 744 6742.9248046875 756 6887.408203125 768 7034.4306640625 780 7181.9453125 792 7329.4599609375 804 7476.9755859375 816 7625.9130859375 828 7776.8823242188 840 7927.8676757812 852 8078.8520507812 864 8229.8388671875 876 8382.673828125 888 8537.212890625 900 8691.751953125 912 8846.291015625 924 9000.8310546875 936 9156.484375 948 9314.5732421875 960 9472.7490234375 972 9630.923828125 984 9789.099609375 ]] check.eq(result, target) local tsp = ts:resampleU(12, { method="rectangle" }) -- TODO: check method=rectangle output end) T("ParseCSVLineTest", function() local ref = 'Company2 Success 2011 3 125 nan Market Research|Marketing|Crowdfunding Marketing, sales nan nan nan No nan nan nan United States North America 5 0 2 0 4 20 No 0 medium Yes Large Yes Yes No No Product No Public Yes Both No Platform Local Non-Linear No Few Yes No Yes Yes No No Yes Yes Yes No Online B2C Low High Yes High Masters 21 Supply Chain Management & Entrepreneurship Yes Yes Tier_1 500 High 0 0 0 Medium 13 None 34 High Medium Yes No Low No Info No Yes Yes No No Yes Medium 1067034 Yes Yes No 3 Medium 0 6.666666667 5 Not Applicable 10 9 Trough 2 to 5 15.88235294 11.76470588 15 12.94117647 0 8.823529412 21.76470588 10.88235294 2.941176471 0 0 0 0 0 8' local x = 'Company2,Success,2011,3,125,,Market Research|Marketing|Crowdfunding,"Marketing, sales",,,,No,,,,United States,North America,5,0,2,0,4,20,No,0,medium,Yes,Large,Yes,Yes,No,No,Product,No,Public,Yes,Both,No,Platform,Local,Non-Linear,No,Few,Yes,No,Yes,Yes,No,No,Yes,Yes,Yes,No,Online,B2C,Low,High,Yes,High,Masters,21,Supply Chain Management & Entrepreneurship,Yes,Yes,Tier_1,500,High,0,0,0,Medium,13,None,34,High,Medium,Yes,No,Low,No Info,No,Yes,Yes,No,No,Yes,Medium,1067034,Yes,Yes,No,3,Medium,0,6.666666667,5,Not Applicable,10,9,Trough,2 to 5,15.88235294,11.76470588,15,12.94117647,0,8.823529412,21.76470588,10.88235294,2.941176471,0,0,0,0,0,8,' local y = 'Company2,Success,2011,3,125,,Market Research|Marketing|Crowdfunding,"Marketing, sales",,,,No,,,,United States,North America,5,0,2,0,4,20,No,0,medium,Yes,Large,Yes,Yes,No,No,Product,No,Public,Yes,Both,No,Platform,Local,Non-Linear,No,Few,Yes,No,Yes,Yes,No,No,Yes,Yes,Yes,No,Online,B2C,Low,High,Yes,High,Masters,21,Supply Chain Management & Entrepreneurship,Yes,Yes,Tier_1,500,High,0,0,0,Medium,13,None,34,High,Medium,Yes,No,Low,No Info,No,Yes,Yes,No,No,Yes,Medium,1067034,Yes,Yes,No,3,Medium,0,6.666666667,5,Not Applicable,10,9,Trough,2 to 5,15.88235294,11.76470588,15,12.94117647,0,8.823529412,21.76470588,10.88235294,2.941176471,0,0,0,0,0,"8",' local z = 'Company2 Success 2011 3 125 Market Research|Marketing|Crowdfunding "Marketing, sales" No United States North America 5 0 2 0 4 20 No 0 medium Yes Large Yes Yes No No Product No Public Yes Both No Platform Local Non-Linear No Few Yes No Yes Yes No No Yes Yes Yes No Online B2C Low High Yes High Masters 21 Supply Chain Management & Entrepreneurship Yes Yes Tier_1 500 High 0 0 0 Medium 13 None 34 High Medium Yes No Low No Info No Yes Yes No No Yes Medium 1067034 Yes Yes No 3 Medium 0 "6,666666667" 5 Not Applicable 10 9 Trough 2 to 5 "15,88235294" "11,76470588" 15 "12,94117647" 0 "8,823529412" "21,76470588" "10,88235294" "2,941176471" 0 0 0 0 0 "8" ' local tx = util.__parse_csv_line__({}, x, ',', '"', '.', 'NA', nan) local ty = util.__parse_csv_line__({}, y, ',', '"', '.', 'NA', nan) local tz = util.__parse_csv_line__({}, z, ' ', '"', ',', 'NA', nan) local sx = table.concat(tx," ") local sy = table.concat(ty," ") local sz = table.concat(tz," ") check.eq(sx, sy) check.eq(sx, sz) check.eq(sx, ref) end) april-ann-0.4.1/packages/basics/dataset/000077500000000000000000000000001263004425400200445ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/dataset/binding/000077500000000000000000000000001263004425400214565ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/dataset/binding/bind_dataset.lua.cc000066400000000000000000001244751263004425400252030ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Francisco Zamora-Martinez, Jorge * Gorbe-Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include #include "bind_function_interface.h" #include "bind_mtrand.h" #include "bind_referenced_vector.h" #include "bind_tokens.h" #include "error_print.h" #include "fmeasure.h" #include "matrix_ext.h" #include "MersenneTwister.h" using AprilUtils::constString; using namespace AprilMath::MatrixExt::Initializers; //devuelve true si consigue leer "name" en la tabla que esté en el top // y en v[] deja los n primeros valores bool leer_int_params(lua_State *L, const char *name, int *v, int n) { // table lua_pushstring(L, name); // name (atributo) lua_gettable(L,-2); if (lua_isnil(L,-1)) { lua_pop(L,1); //remove string return false; } else if (!lua_istable(L,-1)) { ERROR_EXIT1(128, "Expected a table in field %s\n", name); } // tabla del atributo for (int i = 1; i <= n; i++) { lua_rawgeti(L, -1, i); v[i-1] = (int)luaL_checknumber(L, -1); lua_pop(L,1); } lua_pop(L,1); //tabla del atributo return true; } //idem pero leyendo bool's bool leer_bool_params(lua_State *L, const char *name, bool *v, int n) { // table lua_pushstring(L, name); // name (atributo) lua_gettable(L,-2); if (lua_isnil(L,-1)) { lua_pop(L,1); //remove string return false; } else if (!lua_istable(L,-1)) { ERROR_EXIT1(128, "Expected a table in field %s\n", name); } // tabla del atributo for (int i = 1; i <= n; i++) { lua_rawgeti(L, -1, i); v[i-1] = (lua_toboolean(L, -1) != 0); lua_pop(L,1); } lua_pop(L,1); //tabla del atributo return true; } namespace Basics { int dataset_iterator_function(lua_State *L) { // se llama con: local var_1, ... , var_n = _f(_s, _var) donde _s es // el estado invariante (en este caso el dataset) y _var es var_1 de // iteracion anterior (en este caso el indice) DataSetFloat *obj = lua_toDataSetFloat(L,1); int index = (int)lua_tonumber(L,2) + 1; // le sumamos uno if (index > obj->numPatterns()) { lua_pushnil(L); return 1; } lua_pushnumber(L,index); int ps = obj->patternSize(); float *buff = new float[ps]; obj->getPattern(index-1,buff); // ojito que le RESTAMOS uno lua_newtable(L); for (int i=0; i < ps; i++) { lua_pushnumber(L,buff[i]); lua_rawseti(L,-2,i+1); } delete[] buff; return 2; } int datasetToken_iterator_function(lua_State *L) { // se llama con: local var_1, ... , var_n = _f(_s, _var) donde _s es // el estado invariante (en este caso el dataset) y _var es var_1 de // iteracion anterior (en este caso el indice) DataSetToken *obj = lua_toDataSetToken(L,1); int index = (int)lua_tonumber(L,2) + 1; // le sumamos uno if (index > obj->numPatterns()) { lua_pushnil(L); return 1; } lua_pushnumber(L,index); int ps = obj->patternSize(); AprilUtils::SharedPtr tk( obj->getPattern(index-1) ); // ojito que le RESTAMOS uno lua_pushAuxToken(L,tk); return 2; } } // namespace Basics bool lua_isAuxDataSetToken(lua_State *L, int n) { return lua_isDataSetFloat(L,n) || lua_isDataSetToken(L,n); } DataSetToken *lua_toAuxDataSetToken(lua_State *L, int n) { if (lua_isDataSetFloat(L, n)) { DataSetFloat *ds = lua_toDataSetFloat(L,n); return new DataSetFloat2TokenWrapper(ds); } return lua_toDataSetToken(L,n); } //BIND_END //BIND_HEADER_H #include "datasetFloat.h" //#include "utilMatrixFloat.h" #include "matrixFloat.h" #include "utilLua.h" #include "bind_matrix.h" #include "bind_sparse_matrix.h" #include // para sqrt en mean_deviation #include "bind_mtrand.h" #include "MersenneTwister.h" #include "datasetToken.h" using namespace Basics; //BIND_END //BIND_LUACLASSNAME LinearCombConfFloat dataset.linear_comb_conf //BIND_CPP_CLASS LinearCombConfFloat //BIND_CONSTRUCTOR LinearCombConfFloat { // la tabla (L,1) contiene un vector de tablas // cada una de ellas contiene tuplas (indice,valor) LUABIND_CHECK_PARAMETER(1, table); int patternsize; LUABIND_TABLE_GETN(1, patternsize); // vamos a calcular el total de pares (peso,valor) int i,j,total = 0,contador; for (i=1; i <= patternsize; i++) { lua_rawgeti(L,1,i); // tabla i-esima int aux; LUABIND_TABLE_GETN(2, aux); total += aux; lua_pop(L,1); // la quitamos de la pila } // creamos el objeto obj = new LinearCombConfFloat(patternsize,total); // rellenamos vectores de indices y de pesos for (i=1; i <= patternsize; i++) { lua_rawgeti(L,1,i); // tabla i-esima LUABIND_TABLE_GETN(2, obj->numTuplas[i-1]); lua_pop(L,1); // la quitamos de la pila } contador = 0; for (i=1; i <= patternsize; i++) { lua_rawgeti(L,1,i); // tabla i-esima for (j=1;j <= obj->numTuplas[i-1]; j++) { // recorremos la tabla i-esima lua_rawgeti(L,-1,j); // tupla j-esima de tabla i-esima lua_rawgeti(L,-1,1); // extraemos el indice obj->indices[contador] = (int)lua_tonumber(L,-1); lua_pop(L,1); // la quitamos de la pila lua_rawgeti(L,-1,2); // extraemos el peso obj->pesos[contador] = lua_tonumber(L,-1); contador++; lua_pop(L,2); // la quitamos de la pila el peso y la tupla j-esima } lua_pop(L,1); // la quitamos de la pila la tabla i-esima } // ponemos en obj->numTuplas los valores "acumulados" for (i=1; i < patternsize; i++) { obj->numTuplas[i] += obj->numTuplas[i-1]; } LUABIND_RETURN(LinearCombConfFloat, obj); } //BIND_END //BIND_LUACLASSNAME DataSetFloat dataset //BIND_CPP_CLASS DataSetFloat //BIND_CONSTRUCTOR DataSetFloat LUABIND_ERROR("use constructor methods: matrix, etc."); //BIND_END //BIND_DESTRUCTOR DataSetFloat { } //BIND_END //BIND_CLASS_METHOD DataSetFloat matrix /* Permite crear un dataset a partir de una matriz. Requiere 2 argumentos. El primer argumento debe ser la propia matriz. El segundo argumento es una tabla con los siguientes campos: - offset -> posicion inicial en la matriz - patternSize -> el producto de estos valores da patternSize() - stepSize -> cuanto se avanza en cada dimension - numSteps -> el producto de estos valores da numPatterns() - orderStep - circular - defaultValue */ { int argn = lua_gettop(L); // number of arguments if (argn < 1 || argn > 2) LUABIND_ERROR("incorrect number of arguments"); LUABIND_CHECK_PARAMETER(1, MatrixFloat); if (argn == 2) { LUABIND_CHECK_PARAMETER(2, table); check_table_fields(L, 2, "offset", "patternSize", "stepSize", "numSteps", "orderStep", "circular", "defaultValue", (const char *)0); } MatrixFloat *mat; LUABIND_GET_PARAMETER(1, MatrixFloat, mat); MatrixDataSet *obj = new MatrixDataSet(mat); //parseamos la tabla con las opciones int ndim = mat->getNumDim(); int *int_params = new int[ndim]; bool *bool_params = new bool[ndim]; if (argn > 1) { if (leer_int_params(L, "offset", int_params, ndim)) obj->setOffset(int_params); if (leer_int_params(L, "patternSize", int_params, ndim)) obj->setSubMatrixSize(int_params); if (leer_int_params(L, "stepSize", int_params, ndim)) obj->setStep(int_params); if (leer_int_params(L, "numSteps", int_params, ndim)) obj->setNumSteps(int_params); if (leer_int_params(L, "orderStep", int_params, ndim)) obj->setOrderStep(int_params); if (leer_bool_params(L, "circular", bool_params, ndim)) obj->setCircular(bool_params); lua_pushstring(L, "defaultValue"); lua_gettable(L,2); if (!lua_isnil(L,-1)) obj->setDefaultValue((float)luaL_checknumber(L, -1)); } delete[] int_params; delete[] bool_params; LUABIND_RETURN(DataSetFloat,obj); } //BIND_END //BIND_CLASS_METHOD DataSetFloat identity // Crea un dataset que recorre una matriz identidad // Es decir, patrones con valor cero excepto un uno en la posición // determinada por el índice. { LUABIND_CHECK_ARGN(>=, 1); LUABIND_CHECK_ARGN(<=, 3); int patsize; float zerovalue, onevalue; LUABIND_GET_PARAMETER(1, int, patsize); LUABIND_GET_OPTIONAL_PARAMETER(2, float, zerovalue, 0.0f); LUABIND_GET_OPTIONAL_PARAMETER(3, float, onevalue, 1.0f); DataSetFloat *obj = new IdentityDataSet(patsize, zerovalue, onevalue); LUABIND_RETURN(DataSetFloat,obj); } //BIND_END //BIND_CLASS_METHOD DataSetFloat union // permite que varios datasets que tienen el mismo patternSize se vean // como uno solo con un numPatterns igual al sumatorio de los // numPatterns de los DataSets que lo componen. Requiere un unico // argumento que es una tabla con los datasets necesarios. { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); int num; LUABIND_TABLE_GETN(1, num); if (num == 0) LUABIND_ERROR("at least one dataset is needed"); DataSetFloat **vds = new DataSetFloat*[num]; LUABIND_TABLE_TO_VECTOR(1, DataSetFloat, vds, num); DataSetFloat *obj = new UnionDataSet(num,vds); delete[] vds; LUABIND_RETURN(DataSetFloat,obj); } //BIND_END //BIND_CLASS_METHOD DataSetFloat join // Permite juntar las salidas de varios DataSets que tienen el mismo // numero de patrones (numPatterns). El patternSize del DataSet // resultante es igual al sumatorio de los patternSize de los DataSets // que lo componen. Requiere un unico argumento que es una tabla con // los datasets necesarios. { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); int num; LUABIND_TABLE_GETN(1, num); if (num == 0) LUABIND_ERROR("at least one dataset is needed"); DataSetFloat **vds = new DataSetFloat*[num]; LUABIND_TABLE_TO_VECTOR(1, DataSetFloat, vds, num); DataSetFloat *obj = new JoinDataSet(num,vds); delete[] vds; LUABIND_RETURN(DataSetFloat,obj); } //BIND_END //BIND_CLASS_METHOD DataSetFloat indexed // el formato indexado permite crear un mapping de indices a // patterns. Puede ser útil para especificar la salida de una // clasificación, en tal caso el DataSet sobre el que se basa el // IndexDataSet representa la salida asociada a cada una de las // clases. // Requiere 2 argumentos, y un 3 argumento opcional. El primero es el dataset // base. El segundo es una tabla con tantos datasets como patternSize tenga el // dataset base, cada uno de ellos actuará como diccionario. El patternSize del // dataset index resultante es igual a la suma de los patternSize de cada // diccionario. El tercer argumento es el primer valor del indice (normalmente 0 // o 1) { LUABIND_CHECK_ARGN(>=, 2); LUABIND_CHECK_ARGN(<=, 3); LUABIND_CHECK_PARAMETER(1, DataSetFloat); LUABIND_CHECK_PARAMETER(2, table); int numdics, firstindex; LUABIND_GET_OPTIONAL_PARAMETER(3, int, firstindex, 1); DataSetFloat *ds = lua_toDataSetFloat(L,1); LUABIND_TABLE_GETN(2, numdics); if (numdics != ds->patternSize()) LUABIND_FERROR2("bad number of dictionary datasets in table (%d instead of %d)", numdics,ds->patternSize()); DataSetFloat **vds = new DataSetFloat*[numdics+1]; vds[0] = ds; DataSetFloat **vds_aux = vds+1; LUABIND_TABLE_TO_VECTOR(2, DataSetFloat, vds_aux, numdics); DataSetFloat *obj = new IndexDataSet(vds, firstindex); delete[] vds; LUABIND_RETURN(DataSetFloat,obj); } //BIND_END //BIND_CLASS_METHOD DataSetFloat slice // permite seleccionar un subconjunto de patterns de un DataSet, // este subconjunto debe ser un intervalo (para subconjuntos más // generales se puede utilizar la clase IndexDataSet) // Requiere 3 argumentos. El primero es el dataset y luego necesita 2 // argumentos que son los indices inicial y final de los patrones que // se eligen como subconjunto. { LUABIND_CHECK_ARGN(==, 3); LUABIND_CHECK_PARAMETER(1, DataSetFloat); LUABIND_CHECK_PARAMETER(2, int); LUABIND_CHECK_PARAMETER(3, int); DataSetFloat *ds = lua_toDataSetFloat(L,1); int ini,fin; ini = (int)lua_tonumber(L,2) - 1; // ojito que le RESTAMOS uno fin = (int)lua_tonumber(L,3) - 1; // ojito que le RESTAMOS uno DataSetFloat *obj = new SubDataSet(ini,fin,ds); LUABIND_RETURN(DataSetFloat,obj); } //BIND_END //BIND_CLASS_METHOD DataSetFloat split // permite seleccionar un subconjunto de los elementos de salida de // un DataSet. Es decir, el DatSet resultante tiene el mismo numero // de patrones (numPatterns) pero un patternSize menor. El // subconjunto de salida es un intervalo del original { DataSetFloat *ds; int ini,fin; LUABIND_CHECK_ARGN(==, 3); LUABIND_CHECK_PARAMETER(1, DataSetFloat); LUABIND_CHECK_PARAMETER(2, int); LUABIND_CHECK_PARAMETER(3, int); LUABIND_GET_PARAMETER(1,DataSetFloat,ds); LUABIND_GET_PARAMETER(2,int,ini); LUABIND_GET_PARAMETER(3,int,fin); if (fin < ini) LUABIND_ERROR("Impossible interval, initial position is after end position"); if (fin < 1 || ini < 1) LUABIND_ERROR("Initial end end positions start counting from 1"); if (ini > ds->patternSize() || fin > ds->patternSize()) LUABIND_ERROR("The interval values are greater than the patternSize()"); DataSetFloat *obj = new SplitDataSet(ini-1,fin-1,ds); LUABIND_RETURN(DataSetFloat,obj); } //BIND_END //BIND_CLASS_METHOD DataSetFloat linearcomb // El LinearCombDataSet toma un dataset y realiza una combinación // lineal de sus patrones para generar el suyo. Si toma un dataset con // patternSize X y genera sus patrones de patternSize Y necesitaría // una matriz de XxY, PERO vamos a suponer que casi siempre será una // matriz muy dispersa y lo que haremos es una lista de pares // (indice,peso) de modo que cada uno de los Y elementos de salida // tendrá una lista de esas tuplas. { LUABIND_CHECK_ARGN(==, 2); LUABIND_CHECK_PARAMETER(1, DataSetFloat); LUABIND_CHECK_PARAMETER(2, LinearCombConfFloat); DataSetFloat *ds = lua_toDataSetFloat(L,1); LinearCombConfFloat *conf = lua_toLinearCombConfFloat(L,2); // creamos el dataset DataSetFloat *obj = new LinearCombDataSet(ds,conf); LUABIND_RETURN(DataSetFloat,obj); } //BIND_END //BIND_CLASS_METHOD DataSetFloat contextualizer // permite que un dataset añada contexto de los patrones situados en // posiciones adyacentes, cosa que más o menos se puede hacer con // otros datasets, exceptuando lo que ocurre en los bordes. En este // dataset el patrón se repite en caso necesario para rellenar los // bordes. { DataSetFloat *ds; int izq,der; LUABIND_CHECK_ARGN(>=, 3); LUABIND_CHECK_ARGN(<=, 4); LUABIND_CHECK_PARAMETER(1, DataSetFloat); LUABIND_CHECK_PARAMETER(2, int); LUABIND_CHECK_PARAMETER(3, int); LUABIND_GET_PARAMETER(1,DataSetFloat,ds); LUABIND_GET_PARAMETER(2,int,izq); LUABIND_GET_PARAMETER(3,int,der); bool reverse=false; LUABIND_GET_OPTIONAL_PARAMETER(4,bool,reverse,false); DataSetFloat *obj = new ContextualizerDataSet(ds,izq,der,reverse); LUABIND_RETURN(DataSetFloat,obj); } //BIND_END //BIND_CLASS_METHOD DataSetFloat accumulate { // sirve para acumular una serie de valores mediante putpattern se // obtiene la suma acumulada mediante getpattern no hay forma de // ponerlo a cero excepto al crearlo o haciendo un getpattern y un // putpattern del valor negado, salvo errores int patsz, numpat; LUABIND_CHECK_ARGN(==, 2); LUABIND_CHECK_PARAMETER(1, int); LUABIND_CHECK_PARAMETER(2, int); LUABIND_GET_PARAMETER(1,int,patsz); LUABIND_GET_PARAMETER(2,int,numpat); DataSetFloat *obj = new AccumulateDataSet(patsz,numpat); LUABIND_RETURN(DataSetFloat,obj); } //BIND_END //BIND_CLASS_METHOD DataSetFloat byte { // sirve para representar un conjunto de patrones con una precisión // de 8 bits cada valor, puede recibir 2 tipos de parametros: // caso 1) recibe un dataset del que hacer una copia, puede recibir // los valores min y max o bien calcularlos al vuelo en funcion de los // valores maximo y minimo del dataset, en cuyo caso resulta mas // costoso al necesitar iterar 2 veces sobre el dataset // caso 2) recibe el numero de patrones, el tamanyo de cada patron y // los valores min y max, satura si se sale de ese rango. Una vez // creado se rellena con putpattern int patsz, numpat; double min,max,a,b; DataSetFloat *obj; int argn = lua_gettop(L); // number of arguments if (argn >= 1 && lua_isDataSetFloat(L,1)) { DataSetFloat *ds = lua_toDataSetFloat(L,1); LUABIND_GET_OPTIONAL_PARAMETER(2, double, min, 0.0); LUABIND_GET_OPTIONAL_PARAMETER(3, double, max, 1.0); numpat = ds->numPatterns(); patsz = ds->patternSize(); float *patt = new float[patsz]; if (argn == 1) { ds->getPattern(0,patt); min = max = patt[0]; for (int i=0; igetPattern(i,patt); for (int j=0;j max) max = patt[j]; } } if (max - min < 1e-6) max = min + 1e-6; } b = min; a = (max-min)/255; obj = new ByteDataSet(patsz,numpat,a,b); for (int i=0; igetPattern(i,patt); obj->putPattern(i,patt); } delete[] patt; } else { LUABIND_CHECK_ARGN(>=, 2); LUABIND_CHECK_ARGN(<=, 4); LUABIND_CHECK_PARAMETER(1, int); LUABIND_CHECK_PARAMETER(2, int); LUABIND_GET_PARAMETER(1,int,patsz); LUABIND_GET_PARAMETER(2,int,numpat); LUABIND_GET_OPTIONAL_PARAMETER(3, double, min, 0.0); LUABIND_GET_OPTIONAL_PARAMETER(4, double, max, 1.0); b = min; a = (max-min)/255; obj = new ByteDataSet(patsz,numpat,a,b); } LUABIND_RETURN(DataSetFloat,obj); } //BIND_END //BIND_METHOD DataSetFloat getPattern // { int index; LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, int); LUABIND_GET_PARAMETER(1,int,index); if (index < 1 || index > obj->numPatterns()) LUABIND_ERROR("index out of range"); int ps = obj->patternSize(); float *buff = new float[ps]; obj->getPattern(index-1,buff); // ojito que le RESTAMOS uno LUABIND_VECTOR_TO_NEW_TABLE(float, buff, ps); delete[] buff; LUABIND_RETURN_FROM_STACK(-1); } //BIND_END //BIND_METHOD DataSetFloat putPattern { int index; LUABIND_CHECK_ARGN(==, 2); LUABIND_CHECK_PARAMETER(1, int); LUABIND_GET_PARAMETER(1,int,index); if (index < 1 || index > obj->numPatterns()) LUABIND_ERROR("index out of range"); int ps = obj->patternSize(); float *buff = new float[ps]; LUABIND_TABLE_TO_VECTOR(2, float, buff, ps); obj->putPattern(index-1,buff); // ojito que le RESTAMOS uno delete[] buff; } //BIND_END //BIND_METHOD DataSetFloat numPatterns { LUABIND_CHECK_ARGN(==, 0); LUABIND_RETURN(int,obj->numPatterns()); } //BIND_END //BIND_METHOD DataSetFloat patternSize { LUABIND_CHECK_ARGN(==, 0); LUABIND_RETURN(int,obj->patternSize()); } //BIND_END //BIND_METHOD DataSetFloat toMatrix // Genera una matriz de dimension 2 { LUABIND_CHECK_ARGN(==, 0); int dim[2]; dim[0] = obj->numPatterns(); dim[1] = obj->patternSize(); MatrixFloat* mat = new MatrixFloat(2,dim); float *d = mat->getRawDataAccess()->getPPALForWrite(); for (int i=0; i < dim[0]; i++) obj->getPattern(i,d+i*dim[1]); LUABIND_RETURN(MatrixFloat,mat); } //BIND_END //BIND_METHOD DataSetFloat saveFileAscii // imprime cada patron en una fila de un fichero // recibe un filename y opcionalmente la precision // que es una cadena estilo "%.7f", por defecto "%g" // ojo que podria petar si es incorrecta!!!! { LUABIND_CHECK_ARGN(>=, 1); LUABIND_CHECK_ARGN(<=, 2); constString cs_formato,cs_filename; LUABIND_GET_PARAMETER(1,constString,cs_filename); LUABIND_GET_OPTIONAL_PARAMETER(2,constString,cs_formato,constString("%g")); int np = obj->numPatterns(); int ps = obj->patternSize(); const char *formato = cs_formato; const char *filename = cs_filename; FILE *fich = fopen(filename,"w"); if (fich == 0) { LUABIND_FERROR1("Unable to open file \"%s\"",filename); } else { float *buff = new float[ps]; if (ps > 0) { for (int i=0; igetPattern(i,buff); for (int j=0; jnumPatterns(); int ps = obj->patternSize(); const char *filename = cs_filename; FILE *fich = fopen(filename,"w"); if (fich == 0) { LUABIND_FERROR1("Unable to open file \"%s\"",filename); } else { float *buff = new float[ps]; if (ps > 0) { for (int i=0; igetPattern(i,buff); fwrite(buff,sizeof(float),ps,fich); } } delete[] buff; fclose(fich); } } //BIND_END //BIND_METHOD DataSetFloat patterns // para iterar con un for index,pattern in obj:patterns() do ... end { LUABIND_CHECK_ARGN(==, 0); LUABIND_RETURN(cfunction,dataset_iterator_function); LUABIND_RETURN(DataSetFloat,obj); LUABIND_RETURN(int,0); } //BIND_END //BIND_METHOD DataSetFloat mean_deviation // devuelve 2 tablas, la primera con medias, la segunda con las // desviaciones típicas { LUABIND_CHECK_ARGN(==, 0); int npatt = obj->numPatterns(); int psize = obj->patternSize(); float *patt = new float[psize]; double *sum = new double[psize]; double *sum2 = new double[psize]; for (int j=0;jgetPattern(i,patt); for (int j=0;jpatternSize(); int npatt = obj->numPatterns(); LUABIND_CHECK_ARGN(==, 2); if (!lua_istable(L,1) || psize != luaL_len(L,1) || !lua_istable(L,2) || psize != luaL_len(L,2)) LUABIND_ERROR("dataset normalize_mean_deviation: wrong arguments"); float *patt = new float[psize]; float *mean = new float[psize]; float *invdev = new float[psize]; // cargar media y desviacion tipica de las tablas: // LUABIND_TABLE_TO_VECTOR(table, tipo, vector, longitud) LUABIND_TABLE_TO_VECTOR(1, float, mean, psize); LUABIND_TABLE_TO_VECTOR(2, float, invdev, psize); for (int i=0; i < psize; i++) { if (invdev[i] <= 0) LUABIND_FERROR2("dataset normalize_mean_deviation method dev[%d] == %f", i,invdev[i]); else invdev[i] = 1/invdev[i]; } // normalizar: for (int i=0; i < npatt; i++) { obj->getPattern(i,patt); for (int j=0;jputPattern(i,patt); } delete[] patt; delete[] mean; delete[] invdev; } //BIND_END //BIND_METHOD DataSetFloat mean // devuelve 1 tabla { LUABIND_CHECK_ARGN(==, 0); int npatt = obj->numPatterns(); int psize = obj->patternSize(); float *patt = new float[psize]; double *sum = new double[psize]; for (int j=0;jgetPattern(i,patt); for (int j=0;jnumPatterns(); int psize = obj->patternSize(); float *patt = new float[psize]; double *vmin = new double[psize]; double *vmax = new double[psize]; obj->getPattern(0,patt); for (int j=0;jgetPattern(i,patt); for (int j=0;j patt[j]) vmin[j] = patt[j]; if (vmax[j] < patt[j]) vmax[j] = patt[j]; } } // vector de minimos: LUABIND_VECTOR_TO_NEW_TABLE(double, vmin, psize); // vector de maximos: LUABIND_VECTOR_TO_NEW_TABLE(double, vmax, psize); delete[] patt; delete[] vmin; delete[] vmax; LUABIND_RETURN_FROM_STACK(1); LUABIND_RETURN_FROM_STACK(2); } //BIND_END //BIND_METHOD DataSetFloat cct // coordinate-cluster transformation (Kurmyshev et al 1996). // Recibe un threshold, devuelve una matriz de tamaño // 2**pattersize { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, float); float threshold; LUABIND_GET_PARAMETER(1,float,threshold); int npatt = obj->numPatterns(); int psize = obj->patternSize(); if (psize > 12) // fixme: revisar este valor LUABIND_ERROR("too big patternsize"); float *patt = new float[psize]; int histogramlength = 1 << psize; MatrixFloat* mat = new MatrixFloat(1,&histogramlength); matZeros(mat); for (int i=1; i < npatt; i++) { obj->getPattern(i,patt); int index = 0; for (int j=0;j threshold) ? 1 : 0); } (*mat)(index) += 1; } delete[] patt; LUABIND_RETURN(MatrixFloat,mat); } //BIND_END //////////////////////////////////////////////////////////////////////// //BIND_CLASS_METHOD DataSetFloat fmeasure { LUABIND_CHECK_ARGN(==,1); DataSetFloat *ds, *GT; LUABIND_GET_TABLE_PARAMETER(1, result_dataset, DataSetFloat, ds); LUABIND_GET_TABLE_PARAMETER(1, target_dataset, DataSetFloat, GT); float PR, RC, f; f = Fmeasure(ds, GT, PR, RC); LUABIND_RETURN(float, f); LUABIND_RETURN(float, PR); LUABIND_RETURN(float, RC); } //BIND_END //////////////////////////////////////////////////////////////////////// //BIND_CLASS_METHOD DataSetFloat bit { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "numPatterns", "patternSize", "dataset", (const char *)0); DataSetFloat *ds; int nump, patsize; LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, numPatterns, int, nump, -1); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, patternSize, int, patsize, -1); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, dataset, DataSetFloat, ds, 0); if (ds != 0 && (nump != -1 || patsize != -1)) LUABIND_ERROR("dataset.bit: dataset forbide numPatterns " "and patternSize in arguments table!!!\n"); if ((nump == -1 || patsize == -1) && ds == 0) LUABIND_ERROR("dataset.bit: needed numPatterns" "and patternSize in arguments table!!!\n"); if (ds) { nump = ds->numPatterns(); patsize = ds->patternSize(); } DataSetFloat *obj = new BitDataSet(nump, patsize); if (ds) { float *pat = new float[patsize]; for (int i=0; igetPattern(i, pat); obj->putPattern(i, pat); } } LUABIND_RETURN(DataSetFloat, obj); } //BIND_END ///////////////////////////////////////////////////////////////////////// //BIND_CLASS_METHOD DataSetFloat sparse /* Permite crear un dataset a partir de una matriz sparse, pero los patrones seran densos. */ { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, SparseMatrixFloat); SparseMatrixFloat *mat; LUABIND_GET_PARAMETER(1, SparseMatrixFloat, mat); SparseMatrixDatasetFloat *obj = new SparseMatrixDatasetFloat(mat); LUABIND_RETURN(DataSetFloat,obj); } //BIND_END ///////////////////////////////////////////////////////////////////////// //BIND_CLASS_METHOD DataSetFloat short_list { DataSetFloat *ds; check_table_fields(L, 1, "ds", "unk_word", "short_list_size", (const char *)0); LUABIND_GET_TABLE_PARAMETER(1, ds, DataSetFloat, ds); int unk_word, short_list_size; LUABIND_GET_TABLE_PARAMETER(1, unk_word, int, unk_word); LUABIND_GET_TABLE_PARAMETER(1, short_list_size, int, short_list_size); DataSetFloat *obj = new ShortListDataSetFloat(ds, short_list_size, unk_word); LUABIND_RETURN(DataSetFloat,obj); } //BIND_END ////////////////////////////////////////// //BIND_LUACLASSNAME IndexFilterDataSetFloat dataset.index_filter //BIND_CPP_CLASS IndexFilterDataSetFloat //BIND_SUBCLASS_OF IndexFilterDataSetFloat DataSetFloat //BIND_CONSTRUCTOR IndexFilterDataSetFloat { DataSetFloat *ds; ReferencedVectorUint *vec; LUABIND_GET_PARAMETER(1, DataSetFloat, ds); LUABIND_GET_PARAMETER(2, ReferencedVectorUint, vec); DataSetFloat *obj = new IndexFilterDataSetFloat(ds, vec); LUABIND_RETURN(DataSetFloat,obj); } //BIND_END ////////////////////////////////////////// //BIND_LUACLASSNAME PerturbationDataSetFloat dataset.perturbation //BIND_CPP_CLASS PerturbationDataSetFloat //BIND_SUBCLASS_OF PerturbationDataSetFloat DataSetFloat //BIND_CONSTRUCTOR PerturbationDataSetFloat { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "dataset", "mean", "variance", "random", (const char *)0); DataSetFloat *ds; MTRand *random; double mean, variance; LUABIND_GET_TABLE_PARAMETER(1, dataset, DataSetFloat, ds ); LUABIND_GET_TABLE_PARAMETER(1, random, MTRand, random); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, mean, double, mean, 0.0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, variance, double, variance, 1.0); DataSetFloat *obj = new PerturbationDataSetFloat(ds, random, mean, variance); LUABIND_RETURN(DataSetFloat,obj); } //BIND_END ////////////////////////////////////////// //BIND_LUACLASSNAME SaltNoiseDataSetFloat dataset.salt_noise //BIND_CPP_CLASS SaltNoiseDataSetFloat //BIND_SUBCLASS_OF SaltNoiseDataSetFloat DataSetFloat //BIND_CONSTRUCTOR SaltNoiseDataSetFloat { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "dataset", "vd", "zero", "random", (const char *)0); DataSetFloat *ds; MTRand *random; double vd; float zero; LUABIND_GET_TABLE_PARAMETER(1, dataset, DataSetFloat, ds ); LUABIND_GET_TABLE_PARAMETER(1, random, MTRand, random); LUABIND_GET_TABLE_PARAMETER(1, vd, double, vd); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, zero, float, zero, 0.0f); DataSetFloat *obj = new SaltNoiseDataSetFloat(ds, random, vd, zero); LUABIND_RETURN(DataSetFloat,obj); } //BIND_END ////////////////////////////////////////// //BIND_LUACLASSNAME SaltPepperNoiseDataSetFloat dataset.salt_pepper_noise //BIND_CPP_CLASS SaltPepperNoiseDataSetFloat //BIND_SUBCLASS_OF SaltPepperNoiseDataSetFloat DataSetFloat //BIND_CONSTRUCTOR SaltPepperNoiseDataSetFloat { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "dataset", "zero", "one", "random", "prob", (const char *)0); DataSetFloat *ds; MTRand *random; double prob; float zero, one; LUABIND_GET_TABLE_PARAMETER(1, dataset, DataSetFloat, ds ); LUABIND_GET_TABLE_PARAMETER(1, random, MTRand, random); LUABIND_GET_TABLE_PARAMETER(1, prob, double, prob); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, zero, float, zero, 0.0f); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, one, float, one, 1.0f); DataSetFloat *obj = new SaltPepperNoiseDataSetFloat(ds, random, prob, zero, one); LUABIND_RETURN(DataSetFloat,obj); } //BIND_END ////////////////////////////////////////// //BIND_LUACLASSNAME StepDataSetFloat dataset.step //BIND_CPP_CLASS StepDataSetFloat //BIND_SUBCLASS_OF StepDataSetFloat DataSetFloat //BIND_CONSTRUCTOR StepDataSetFloat { LUABIND_CHECK_ARGN(==, 2); LUABIND_CHECK_PARAMETER(1, DataSetFloat); LUABIND_CHECK_PARAMETER(2, int); DataSetFloat *ds; int step; LUABIND_GET_PARAMETER(1, DataSetFloat, ds); LUABIND_GET_PARAMETER(2, int, step); DataSetFloat *obj = new StepDataSetFloat(ds, step); LUABIND_RETURN(DataSetFloat,obj); } //BIND_END ////////////////////////////////////////// //BIND_LUACLASSNAME DerivDataSetFloat dataset.deriv //BIND_CPP_CLASS DerivDataSetFloat //BIND_SUBCLASS_OF DerivDataSetFloat DataSetFloat //BIND_CONSTRUCTOR DerivDataSetFloat { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "dataset", "deriv0", "deriv1", "deriv2", (const char *)0); DataSetFloat *ds; bool deriv0, deriv1, deriv2; LUABIND_GET_TABLE_PARAMETER(1, dataset, DataSetFloat, ds); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, deriv0, bool, deriv0, true); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, deriv1, bool, deriv1, true); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, deriv2, bool, deriv2, true); DataSetFloat *obj = new DerivDataSetFloat(ds, deriv0, deriv1, deriv2); LUABIND_RETURN(DataSetFloat,obj); } //BIND_END ////////////////////////////////////////// //BIND_LUACLASSNAME CacheDataSetFloat dataset.cache //BIND_CPP_CLASS CacheDataSetFloat //BIND_SUBCLASS_OF CacheDataSetFloat DataSetFloat //BIND_CONSTRUCTOR CacheDataSetFloat { DataSetFloat *ds; LUABIND_GET_PARAMETER(1, DataSetFloat, ds); int cache_size; LUABIND_GET_PARAMETER(4, int, cache_size); int voc_size; LUABIND_TABLE_GETN(2, voc_size); int **word2index = new int*[voc_size+1]; int *word2index_sizes = new int[voc_size+1]; float *decays = new float[cache_size+1]; LUABIND_TABLE_TO_VECTOR(3, float, (decays+1), cache_size); float near_zero; LUABIND_GET_PARAMETER(5, float, near_zero); int begin_token_id, end_token_id, null_token_id, cache_stop_token_id; LUABIND_GET_PARAMETER(6, int, begin_token_id); LUABIND_GET_PARAMETER(7, int, end_token_id); LUABIND_GET_PARAMETER(8, int, null_token_id); LUABIND_GET_PARAMETER(9, int, cache_stop_token_id); // el 0 esta reservado para la palabra vacia word2index[0] = 0; word2index_sizes[0] = 0; decays[0] = 0.0f; for (int i=1; i<=voc_size; ++i) { int sz; lua_rawgeti(L, 2, i); LUABIND_TABLE_GETN(-1, sz); word2index_sizes[i] = sz; if (sz == 0) word2index[i] = 0; else { word2index[i] = new int[sz]; LUABIND_TABLE_TO_VECTOR(-1, int, word2index[i], sz); } lua_pop(L, 1); } obj = new CacheDataSetFloat(ds, word2index, word2index_sizes, decays, voc_size, cache_size, near_zero, begin_token_id, end_token_id, null_token_id, cache_stop_token_id); LUABIND_RETURN(DataSetFloat, obj); } //BIND_END ////////////////////////////////////////// //BIND_LUACLASSNAME SubAndDivNormalizationDataSetFloat dataset.sub_and_div_normalization //BIND_CPP_CLASS SubAndDivNormalizationDataSetFloat //BIND_SUBCLASS_OF SubAndDivNormalizationDataSetFloat DataSetFloat //BIND_CONSTRUCTOR SubAndDivNormalizationDataSetFloat { LUABIND_CHECK_ARGN(==, 3); LUABIND_CHECK_PARAMETER(1, DataSetFloat); LUABIND_CHECK_PARAMETER(2, table); LUABIND_CHECK_PARAMETER(3, table); DataSetFloat *ds; LUABIND_GET_PARAMETER(1, DataSetFloat, ds); int n,m; LUABIND_TABLE_GETN(2,n); LUABIND_TABLE_GETN(3,m); if (n != ds->patternSize() || m != ds->patternSize()) LUABIND_ERROR("Incorrect size in table arguments\n"); float *sub = new float[n]; float *div = new float[n]; LUABIND_TABLE_TO_VECTOR(2, float, sub, n); LUABIND_TABLE_TO_VECTOR(3, float, div, n); obj = new SubAndDivNormalizationDataSet(ds,sub,div); delete[] sub; delete[] div; LUABIND_RETURN(SubAndDivNormalizationDataSetFloat,obj); } //BIND_END ////////////////////////////////////////// //BIND_LUACLASSNAME ClampDataSetFloat dataset.clamp //BIND_CPP_CLASS ClampDataSetFloat //BIND_SUBCLASS_OF ClampDataSetFloat DataSetFloat //BIND_CONSTRUCTOR ClampDataSetFloat { LUABIND_CHECK_ARGN(==, 3); LUABIND_CHECK_PARAMETER(1, DataSetFloat); LUABIND_CHECK_PARAMETER(2, float); LUABIND_CHECK_PARAMETER(3, float); DataSetFloat *ds; float lower, upper; LUABIND_GET_PARAMETER(1, DataSetFloat, ds); LUABIND_GET_PARAMETER(2, float, lower); LUABIND_GET_PARAMETER(3, float, upper); obj = new ClampDataSetFloat(ds,lower,upper); LUABIND_RETURN(ClampDataSetFloat,obj); } //BIND_END ////////////////////////////////////////// //BIND_LUACLASSNAME DataSetToken dataset.token //BIND_CPP_CLASS DataSetToken //BIND_CONSTRUCTOR DataSetToken { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD DataSetToken numPatterns { LUABIND_RETURN(int, obj->numPatterns()); } //BIND_END //BIND_METHOD DataSetToken patternSize { LUABIND_RETURN(int, obj->patternSize()); } //BIND_END //BIND_METHOD DataSetToken getPattern { int index; LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, int); LUABIND_GET_PARAMETER(1,int,index); if (index < 1 || index > obj->numPatterns()) LUABIND_ERROR("index out of range"); AprilUtils::SharedPtr token( obj->getPattern(index-1) ); // ojito que le RESTAMOS uno LUABIND_RETURN(AuxToken, token); } //BIND_END //BIND_METHOD DataSetToken getPatternBunch { unsigned int bunch_size; int *indexes; LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, table); LUABIND_TABLE_GETN(1,bunch_size); indexes = new int[bunch_size]; LUABIND_TABLE_TO_VECTOR_SUB1(1,uint,indexes,bunch_size); AprilUtils::SharedPtr token( obj->getPatternBunch(indexes,bunch_size) ); delete[] indexes; LUABIND_RETURN(AuxToken, token); } //BIND_END //BIND_METHOD DataSetToken putPattern { int index; AprilUtils::SharedPtr pattern; LUABIND_CHECK_ARGN(==,2); LUABIND_CHECK_PARAMETER(1, int); LUABIND_CHECK_PARAMETER(2, AuxToken); LUABIND_GET_PARAMETER(1,int,index); LUABIND_GET_PARAMETER(2,AuxToken,pattern); if (index < 1 || index > obj->numPatterns()) LUABIND_ERROR("index out of range"); obj->putPattern(index-1, pattern.get()); // ojito que le RESTAMOS uno } //BIND_END //BIND_METHOD DataSetToken putPatternBunch { unsigned int bunch_size; int *indexes; AprilUtils::SharedPtr pattern; LUABIND_CHECK_ARGN(==,2); LUABIND_CHECK_PARAMETER(1, table); LUABIND_CHECK_PARAMETER(2, AuxToken); LUABIND_GET_PARAMETER(2,AuxToken,pattern); LUABIND_TABLE_GETN(1,bunch_size); indexes = new int[bunch_size]; LUABIND_TABLE_TO_VECTOR_SUB1(1,uint,indexes,bunch_size); obj->putPatternBunch(indexes,bunch_size,pattern.get()); delete[] indexes; } //BIND_END //BIND_METHOD DataSetToken patterns // para iterar con un for index,pattern in obj:patterns() do ... end { LUABIND_CHECK_ARGN(==, 0); LUABIND_RETURN(cfunction,datasetToken_iterator_function); LUABIND_RETURN(DataSetToken,obj); LUABIND_RETURN(int,0); } //BIND_END ////////////////////////////////////////// //BIND_LUACLASSNAME UnionDataSetToken dataset.token.union //BIND_CPP_CLASS UnionDataSetToken //BIND_SUBCLASS_OF UnionDataSetToken DataSetToken //BIND_CONSTRUCTOR UnionDataSetToken { LUABIND_CHECK_ARGN(<=,1); int argn = lua_gettop(L); if (argn == 1) { unsigned int size; LUABIND_CHECK_PARAMETER(1, table); LUABIND_TABLE_GETN(1, size); if (size < 2) LUABIND_ERROR("UnionDataSetToken needs a Lua table with two or " "more DataSetToken\n"); DataSetToken **ds_array = new DataSetToken*[size]; LUABIND_TABLE_TO_VECTOR(1, AuxDataSetToken, ds_array, size); obj = new UnionDataSetToken(ds_array, size); delete[] ds_array; } else obj = new UnionDataSetToken(); LUABIND_RETURN(UnionDataSetToken, obj); } //BIND_END //BIND_METHOD UnionDataSetToken push_back { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, AuxDataSetToken); DataSetToken *ds; LUABIND_GET_PARAMETER(1, AuxDataSetToken, ds); obj->push_back(ds); } //BIND_END ////////////////////////////////////////// //BIND_LUACLASSNAME DataSetTokenVector dataset.token.vector //BIND_CPP_CLASS DataSetTokenVector //BIND_SUBCLASS_OF DataSetTokenVector DataSetToken //BIND_CONSTRUCTOR DataSetTokenVector { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, int); int pattern_size; LUABIND_GET_PARAMETER(1, int, pattern_size); obj = new DataSetTokenVector(pattern_size); LUABIND_RETURN(DataSetTokenVector, obj); } //BIND_END //BIND_METHOD DataSetTokenVector push_back { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, AuxToken); AprilUtils::SharedPtr token; LUABIND_GET_PARAMETER(1, AuxToken, token); obj->push_back(token.get()); } //BIND_END ////////////////////////////////////////// //BIND_LUACLASSNAME DataSetFloat2TokenWrapper dataset.token.wrapper //BIND_CPP_CLASS DataSetFloat2TokenWrapper //BIND_SUBCLASS_OF DataSetFloat2TokenWrapper DataSetToken //BIND_CONSTRUCTOR DataSetFloat2TokenWrapper { LUABIND_CHECK_ARGN(>=,1); LUABIND_CHECK_ARGN(<=,2); int argn = lua_gettop(L); // number of arguments LUABIND_CHECK_PARAMETER(1, DataSetFloat); DataSetFloat *ds; LUABIND_GET_PARAMETER(1, DataSetFloat, ds); obj = new DataSetFloat2TokenWrapper(ds); LUABIND_RETURN(DataSetFloat2TokenWrapper, obj); } //BIND_END ////////////////////////////////////////// //BIND_LUACLASSNAME DataSetTokenFilter dataset.token.filter //BIND_CPP_CLASS DataSetTokenFilter //BIND_SUBCLASS_OF DataSetTokenFilter DataSetToken //BIND_CONSTRUCTOR DataSetTokenFilter { LUABIND_CHECK_ARGN(==,2); LUABIND_CHECK_PARAMETER(1, AuxDataSetToken); LUABIND_CHECK_PARAMETER(2, FunctionInterface); DataSetToken *ds; FunctionInterface *filter; LUABIND_GET_PARAMETER(1, AuxDataSetToken, ds); LUABIND_GET_PARAMETER(2, FunctionInterface, filter); obj = new DataSetTokenFilter(ds,filter); LUABIND_RETURN(DataSetTokenFilter, obj); } //BIND_END ////////////////////////////////////////// //BIND_LUACLASSNAME SparseMatrixDataSetToken dataset.token.sparse_matrix //BIND_CPP_CLASS SparseMatrixDataSetToken //BIND_SUBCLASS_OF SparseMatrixDataSetToken DataSetToken //BIND_CONSTRUCTOR SparseMatrixDataSetToken { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, SparseMatrixFloat); SparseMatrixFloat *sparse_matrix; LUABIND_GET_PARAMETER(1, SparseMatrixFloat, sparse_matrix); obj = new SparseMatrixDataSetToken(sparse_matrix); LUABIND_RETURN(SparseMatrixDataSetToken, obj); } //BIND_END april-ann-0.4.1/packages/basics/dataset/c_src/000077500000000000000000000000001263004425400211355ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/dataset/c_src/dataset.cc000066400000000000000000001064051263004425400230770ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Francisco Zamora-Martinez, Jorge * Gorbe-Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef DATASET_CC_H #define DATASET_CC_H #include #include #include #include "dataset.h" #include "mod.h" #include "clamp.h" #include "error_print.h" #include "maxmin.h" #include "april_assert.h" namespace Basics { // --------------------------------------------------------------------- template MatrixDataSet::MatrixDataSet(Matrix *m) : DataSet() { if (!m->isSimple()) { ERROR_EXIT(128, "Matrix need to be simple (contiguous " "and in row-major)\n"); } #ifdef USE_CUDA m->setUseCuda(false); // never use CUDA with this dataset #endif // numdim debe ser siempre >0 int d = m->getNumDim(); matrix = m; IncRef(matrix); // garbage collection offset = new int[d]; subMatrixSize= new int[d]; circular = new bool[d]; step = new int[d]; numSteps = new int[d]; orderStep = new int[d]; coordinate = new int[d]; // valores por defecto defaultValue = 0; for (int i=0; igetDimSize(i); // ocupa todo el ancho orderStep[i] = d-(i+1); step[i] = 1; numSteps[i] = 1 ; // m->getDimSize(i); circular[i] = false; } if (d > 0) { subMatrixSize[0] = 1; numSteps[0] = m->getDimSize(0); } // calcular estos otros valores: numPatternsv = patternSizev = 1; for(int i=0;i void MatrixDataSet::setValue(int *dest, int *orig){ for(int i=0;igetNumDim();i++){ dest[i]=orig[i]; } } template void MatrixDataSet::setValue(bool *dest, bool *orig){ for(int i=0;igetNumDim();i++){ dest[i]=orig[i]; } } template void MatrixDataSet::setNumSteps(int *v) { setValue(numSteps,v); numPatternsv=1; for(int i=0;igetNumDim();i++) { if (numSteps[i] == 0) ERROR_EXIT1(1, "Error: numsteps[%d] == 0\n",i); numPatternsv=numPatternsv*numSteps[i]; } } template void MatrixDataSet::setSubMatrixSize(int *v) { setValue(subMatrixSize,v); patternSizev=1; for(int i=0;igetNumDim();i++) patternSizev=patternSizev*subMatrixSize[i]; } template void MatrixDataSet::index2coordinate(int index) { for (int i=0; i < matrix->getNumDim();i++) { int j = orderStep[i]; coordinate[j] = offset[j] + (index % numSteps[j])*step[j]; index=index/numSteps[j]; } } template void MatrixDataSet::auxGetPattern(int offsetmatrix, int d) { int i,c,t; t = matrix->getDimSize(d); // recursiva if (d == matrix->getNumDim()-1) { // ultima dimension, caso base const T *data = matrix->getRawDataAccess()->getPPALForRead() + offsetmatrix*t; if (circular[d]) { for(i = subMatrixSize[d], c = coordinate[d]; i; c++,i--) { pattern[offsetpat++] = data[AprilUtils::mod(c,t)]; } } else { for(i = subMatrixSize[d], c = coordinate[d]; i; c++,i--) { pattern[offsetpat++] = ((c < 0 || c >= t) ? defaultValue : data[c]); } } } else { // no es ultima dimension if (circular[d]) { // caso no base, es circular for(i = subMatrixSize[d], c = coordinate[d]; i; c++,i--) { auxGetPattern(offsetmatrix*matrix->getDimSize(d+1)+AprilUtils::mod(c,t),d+1); } // cierra for caso base no circular } else { // caso no base, no circular for(i = subMatrixSize[d], c = coordinate[d]; i; c++,i--) { if (c < 0 || c >= t) { // rellenar el resto de dimensiones con defaultValue int veces = 1; for (int j = d+1; j < matrix->getNumDim(); j++) veces *= subMatrixSize[j]; for (;veces;veces--) pattern[offsetpat++] = defaultValue; } else { auxGetPattern(offsetmatrix*matrix->getDimSize(d)+c,d+1); } } // cierra for : caso base no circular } // cierra else : caso no base, no circular } // cierra else : no es ultima dimension } //se asume que T *pat ya es un vector suficientemente grande template int MatrixDataSet::getPattern(int index, T *pat){ index2coordinate(index); // actualiza vector coordinate pattern = pat; offsetpat = 0; auxGetPattern(0, 0); // recibe offsetmatrix y dimension a tratar return patternSize(); } template void MatrixDataSet::auxPutPattern(int offsetmatrix, int d) { int i,c,t; t = matrix->getDimSize(d); // recursiva if (d == matrix->getNumDim()-1) { // ultima dimension, caso base T *data = matrix->getRawDataAccess()->getPPALForWrite() + offsetmatrix*t; if (circular[d]) { for(i = subMatrixSize[d], c = coordinate[d]; i; c++,i--) { data[AprilUtils::mod(c,t)] = const_pattern[offsetpat++]; } } else { for(i = subMatrixSize[d], c = coordinate[d]; i; c++,i--) { if ((0 <= c) && (c < t)) { data[c] = const_pattern[offsetpat]; } offsetpat++; } } } else { // no es ultima dimension if (circular[d]) { // caso no base, es circular for(i = subMatrixSize[d], c = coordinate[d]; i; c++,i--) { auxPutPattern(offsetmatrix*matrix->getDimSize(d+1)+(AprilUtils::mod(c,t)),d+1); } // cierra for caso base no circular } else { // caso no base, no circular for(i = subMatrixSize[d], c = coordinate[d]; i; c++,i--) { if (c < 0 || c >= t) { // te sales de la matriz // saltarse el resto de dimensiones int veces = 1; for (int j = d+1; j < matrix->getNumDim(); j++) veces *= subMatrixSize[j]; offsetpat += veces; } else { auxPutPattern(offsetmatrix*matrix->getDimSize(d)+c,d+1); } } // cierra for : caso base no circular } // cierra else : caso no base, no circular } // cierra else : no es ultima dimension } //se asume que T *pat ya es un vector suficientemente grande template int MatrixDataSet::putPattern(int index, const T *pat) { index2coordinate(index); // actualiza vector coordinate const_pattern = pat; // pattern es atributo que se va modificando offsetpat = 0; // idem auxPutPattern(0, 0); // llamada recursiva inicial return patternSize(); } template MatrixDataSet::~MatrixDataSet(){ delete[] offset; delete[] subMatrixSize; delete[] circular; delete[] step; delete[] numSteps; delete[] coordinate; delete[] orderStep; DecRef(matrix); // garbage collection } // --------------------------------------------------------------------- template IdentityDataSet::IdentityDataSet(int patternSize, T zerovalue, T onevalue) : DataSet(), zerovalue(zerovalue), onevalue(onevalue) { patternsz = patternSize; } template IdentityDataSet::~IdentityDataSet() { // Nothing to do } template int IdentityDataSet::getPattern(int index, T *pat) { april_assert("Incorrect index" && index >= 0 && index < numPatterns()); for (int i=0; i int IdentityDataSet::putPattern(int index, const T *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); return 0; } // --------------------------------------------------------------------- template UnionDataSet::UnionDataSet(int n, DataSet **v) : DataSet() { num = n; vds = new DataSet*[num]; d = new int[num+1]; d[0] = 0; patternsz = v[0]->patternSize(); int i; for (i=0; i < num; i++) { vds[i] = v[i]; IncRef(v[i]); // garbage collection if (patternsz != v[i]->patternSize()) { // ERROR!!!! // todo: comprobar esto en el binding ERROR_EXIT(1,"ERROR dataset.union: one of datasets has wrong patternsize\n"); } d[i+1] = d[i] + v[i]->numPatterns(); } } template UnionDataSet::~UnionDataSet() { for (int i=0; i < num; i++) { DecRef(vds[i]); // garbage collection } delete[] vds; // necesitamos borrar tambien los datasets apuntados? delete[] d; } template int UnionDataSet::getPattern(int index, T *pat) { // buscamos el dataset asociado y su indice correspondiente if (index < 0 || index >= numPatterns()) return 0; int izq,der,m; izq = 0; der = num; do { m = (izq+der)/2; if (d[m] <= index) izq = m; else der = m; } while (izq < der-1); return vds[izq]->getPattern(index-d[izq],pat); }; template int UnionDataSet::putPattern(int index, const T *pat) { // buscamos el dataset asociado y su índice correspondiente if (index < 0 || index >= numPatterns()) return 0; int izq,der,m; izq = 0; der = num; do { m = (izq+der)/2; if (d[m] <= index) izq = m; else der = m; } while (izq < der-1); return vds[izq]->putPattern(index-d[izq],pat); }; // --------------------------------------------------------------------- template SubDataSet::SubDataSet(int ini, int fin, DataSet *ds) : DataSet() { this->ds = ds; IncRef(ds); // garbage collection this->ini = ini; this->fin = fin; this->size = fin - ini + 1; } template SubDataSet::~SubDataSet() { DecRef(ds); // garbage collection } template int SubDataSet::getPattern(int index, T *pat) { // TODO: falta comprobar que el indice esta en el rango correcto return ds->getPattern(ini + index,pat); } template int SubDataSet::putPattern(int index, const T *pat) { // TODO: falta comprobar que el indice esta en el rango correcto return ds->putPattern(ini + index,pat); } // --------------------------------------------------------------------- template SplitDataSet::SplitDataSet(int ini, int fin, DataSet *ds) : DataSet() { this->ini = ini; this->fin = fin; this->ds = ds; IncRef(ds); // garbage collection size = fin-ini+1; aux = new T[ds->patternSize()]; } template SplitDataSet::~SplitDataSet() { DecRef(ds); // garbage collection delete[] aux; } template int SplitDataSet::getPattern(int index, T *pat) { ds->getPattern(index,aux); T *r = aux+ini; for (int i = 0; i < size; i++) pat[i] = r[i]; return size; } // --------------------------------------------------------------------- template JoinDataSet::JoinDataSet(int n, DataSet **v) : DataSet() { num = n; vds = new DataSet*[num]; d = new int[num+1]; d[0]= 0; int ps = v[0]->numPatterns(); int i; for (i=0; i < num; i++) { vds[i] = v[i]; IncRef(v[i]); // garbage collection if (ps != v[i]->numPatterns()) { // ERROR!!!! ERROR_EXIT(1,"Error in JoinDataSet constructor\n"); } d[i+1] = d[i] + v[i]->patternSize(); } } template JoinDataSet::~JoinDataSet() { for (int i=0; i < num; i++) { DecRef(vds[i]); // garbage collection } delete[] vds; delete[] d; } template int JoinDataSet::getPattern(int index, T *pat) { for (int i=0; i < num; i++) vds[i]->getPattern(index, pat+d[i]); return patternSize(); } template int JoinDataSet::putPattern(int index, const T *pat) { for (int i=0; i < num; i++) vds[i]->putPattern(index, pat+d[i]); return patternSize(); } // --------------------------------------------------------------------- template IndexDataSet::IndexDataSet(DataSet **datasets, int firstindex) : DataSet() { this->firstindex = firstindex; indices = datasets[0]; IncRef(indices); // garbage collection numdiccionarios = indices->patternSize(); diccionarios = new DataSet*[numdiccionarios]; patternindices = new T[numdiccionarios]; if (numdiccionarios == 0) { ERROR_EXIT(1,"error: indexDataSet needs at least 1 dictionary\n"); } patternsize = 0; for (int i=0; i < numdiccionarios; i++) { diccionarios[i] = datasets[i+1]; IncRef(diccionarios[i]); // garbage collection patternsize += diccionarios[i]->patternSize(); } } template IndexDataSet::~IndexDataSet() { delete[] patternindices; DecRef(indices); // garbage collection for (int i=0; i < numdiccionarios; i++) { DecRef(diccionarios[i]); // garbage collection } delete[] diccionarios; } template int IndexDataSet::getPattern(int index, T *pat) { int pos = 0; indices->getPattern(index,patternindices); for (int i=0; i < numdiccionarios; i++) { int idx = static_cast(patternindices[i])-firstindex; april_assert("Incorrect index at IndexDataSet" && idx >= 0); pos += diccionarios[i]->getPattern((int)idx,pat+pos); } return patternSize(); } template int IndexDataSet::putPattern(int index, const T *pat) { int pos = 0; index += firstindex; indices->getPattern(index,patternindices); for (int i=0; i < numdiccionarios; i++) { pos += diccionarios[i]->putPattern((int)patternindices[i]-firstindex,pat+pos); } return patternSize(); } // --------------------------------------------------------------------- template LinearCombDataSet::LinearCombDataSet(DataSet *ds, LinearCombConf *conf) : DataSet() { this->ds = ds; aux = new T[ds->patternSize()+1]; aux[0] = 1; IncRef(ds); // garbage collection this->conf = conf; IncRef(conf); // garbage collection } template LinearCombDataSet::~LinearCombDataSet() { delete[] aux; DecRef(conf); // garbage collection DecRef(ds); // garbage collection } template int LinearCombDataSet::getPattern(int index, T *pat) { int i,j,desde,hasta; desde = 0; ds->getPattern(index,aux+1); for (i=0; ipatternsize; i++) { // recorremos indices de salida pat[i] = 0; hasta = conf->numTuplas[i]; for (j=desde;jindices[j]]*conf->pesos[j]; desde = hasta; } return conf->patternsize; } // --------------------------------------------------------------------- template ContextualizerDataSet::ContextualizerDataSet(DataSet *ds, int izq, int der, bool reverse) : DataSet(), ctxtizq(izq), ctxtder(der), ds(ds), reverse(reverse) { IncRef(ds); // garbage collection numpatterns = ds->numPatterns(); patternsize = ds->patternSize()*(ctxtizq+1+ctxtder); } template ContextualizerDataSet::~ContextualizerDataSet() { DecRef(ds); // garbage collection } template int ContextualizerDataSet::getPattern(int index, T *pat) { T *vec = pat; int ps = ds->patternSize(), i,j = index-ctxtizq; if (reverse) { vec += (ctxtizq+ctxtder)*ps; ps = -ps; } for (i=0; igetPattern(((j >= 0) ? j : 0), vec); ds->getPattern(j, vec); vec += ps; j++; for (i=0; igetPattern(((j < numpatterns) ? j : numpatterns-1), vec); return patternsize; } template int ContextualizerDataSet::putPattern(int index, const T *pat) { const T *vec = pat; int ps = ds->patternSize(), i,j = index-ctxtizq; for (i=0; i= 0) ds->putPattern(j, vec); ds->putPattern(j, vec); vec += ps; j++; for (i=0; iputPattern(j, vec); return patternsize; } // --------------------------------------------------------------------- template AccumulateDataSet::AccumulateDataSet(int patsz, int numpat) : DataSet() { patternsize = patsz; numpatterns = numpat; data = new double[patsz]; for (int i=0;i AccumulateDataSet::~AccumulateDataSet() { delete[] data; } template int AccumulateDataSet::getPattern(int index, T *pat) { UNUSED_VARIABLE(index); // if (index < 0 || index >= numpatterns) // return 0; for (int i=0; i int AccumulateDataSet::putPattern(int index, const T *pat) { UNUSED_VARIABLE(index); // if (index < 0 || index >= numpatterns) // return 0; for (int i=0; i ByteDataSet::ByteDataSet(int patsz, int numpat, double a, double b) : DataSet() { patternsize = patsz; numpatterns = numpat; this->a = a; this->b = b; data = new unsigned char[patsz*numpat]; for (int i=0;i ByteDataSet::~ByteDataSet() { delete[] data; } template int ByteDataSet::getPattern(int index, T *pat) { // if (index < 0 || index >= numpatterns) // return 0; int offset = index*patternsize; for (int i=0; i int ByteDataSet::putPattern(int index, const T *pat) { // if (index < 0 || index >= numpatterns) // return 0; int offset = index*patternsize; for (int i=0; i BitDataSet::BitDataSet(int nump, int patsize) : DataSet() { numpatterns = nump; patternsize = patsize; int p = ((numpatterns*patternsize)>>3) + 1; data = new unsigned char[p]; for (int i=0; i BitDataSet::~BitDataSet() { delete[] data; } template int BitDataSet::getPattern(int index, T *pat) { index = index * patternsize; int bytePos = index >> 3; int bitPos = index & (0x07); for (int i=0; i> bitPos) & (0x01); if (v) pat[i] = T(1); else pat[i] = T(0); ++bitPos; if (bitPos > 7) { bitPos = 0; bytePos++; } } return patternsize; } template int BitDataSet::putPattern(int index, const T *pat) { index = index * patternsize; int bytePos = index >> 3; int bitPos = index & (0x07); for (int i=0; i 7) { bitPos = 0; bytePos++; } } return patternsize; } // --------------------------------------------------------------------- template SparseMatrixDataset::SparseMatrixDataset(SparseMatrix *m) : DataSet(), matrix(m), numpatterns(m->getDimSize(0)), patternsize(m->getDimSize(1)) { if (m->getSparseFormat() != CSR_FORMAT) { ERROR_EXIT(128, "SparseMatrix need to be in CSR format\n"); } IncRef(m); } template SparseMatrixDataset::~SparseMatrixDataset() { DecRef(matrix); } template int SparseMatrixDataset::getPattern(int index, T *pat) { // WARNING: only works with float for (int i=0; i::const_iterator it(matrix->iteratorAtFirst(index,0)); while(true) { int x0,x1; it.getCoords(x0,x1); if (x0 != index) break; pat[x1] = *it; } return patternsize; } template int SparseMatrixDataset::putPattern(int index, const T *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); ERROR_EXIT(1,"Method putPattern forbidden for SparseMatrixDataset!!!\n"); return 0; } // --------------------------------------------------------------------- template ShortListDataSet::ShortListDataSet(DataSet *ds, int short_list_size, int unk_word) : DataSet(), ds(ds), short_list_size(short_list_size), unk_word(unk_word) { IncRef(ds); patsize = ds->patternSize(); } template ShortListDataSet::~ShortListDataSet() { DecRef(ds); } template int ShortListDataSet::getPattern(int index, T *pat) { UNUSED_VARIABLE(index); //int aux = ds->getPattern(index, pat); for (int i=0; i short_list_size) pat[i] = unk_word; return patsize; } template int ShortListDataSet::putPattern(int index, const T *pat) { return ds->putPattern(index, pat); } //---------------------------------------------------------- template IndexFilterDataSet:: IndexFilterDataSet(DataSet *ds, AprilUtils::ReferencedVectorUint *indexes) : DataSet(), ds(ds), indexes(indexes) { IncRef(ds); IncRef(indexes); } template IndexFilterDataSet::~IndexFilterDataSet() { DecRef(ds); DecRef(indexes); } template int IndexFilterDataSet::getPattern(int index, T *pat) { // OJO: -1 porque la tabla viene de LUA y comienza en 1 return ds->getPattern((*indexes)[index]-1, pat); } template int IndexFilterDataSet::putPattern(int index, const T *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); ERROR_EXIT(1,"Method putPattern forbidden for IndexFilterDataSet!!!\n"); return 0; } //---------------------------------------------------------- template PerturbationDataSet::PerturbationDataSet(DataSet *ds, Basics::MTRand *random, double mean, double variance) : DataSet(), ds(ds), random(random), mean(mean), variance(variance) { IncRef(ds); IncRef(random); } template PerturbationDataSet::~PerturbationDataSet() { DecRef(ds); DecRef(random); } template int PerturbationDataSet::getPattern(int index, T *pat) { int ret = ds->getPattern(index, pat); int sz = ds->patternSize(); for (int i=0; irandNorm(mean,variance); return ret; } template int PerturbationDataSet::putPattern(int index, const T *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); ERROR_EXIT(1,"Method putPattern forbidden for PerturbationDataSet!!!\n"); return 0; } //------------------------------------------------------------- template SaltNoiseDataSet::SaltNoiseDataSet(DataSet *ds, Basics::MTRand *random, double vd, T zero) : DataSet(), ds(ds), random(random), vd(vd), zero(zero), number_of_zeroes(static_cast(vd*ds->patternSize())) { IncRef(ds); IncRef(random); zero_positions = new int[ds->patternSize()]; } template SaltNoiseDataSet::~SaltNoiseDataSet() { DecRef(ds); DecRef(random); delete[] zero_positions; } template int SaltNoiseDataSet::getPattern(int index, T *pat) { int ret = ds->getPattern(index, pat); int sz = ds->patternSize(); random->shuffle(sz, zero_positions); for (int i=0; i int SaltNoiseDataSet::putPattern(int index, const T *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); ERROR_EXIT(1,"Method putPattern forbidden for SaltNoiseDataSet!!!\n"); return 0; } //------------------------------------------------------------- template SaltPepperNoiseDataSet::SaltPepperNoiseDataSet(DataSet *ds, Basics::MTRand *random, double vd, T zero, T one) : DataSet(), ds(ds), random(random), vd(vd), zero(zero), one(one), number_of_perturbations(static_cast(vd*ds->patternSize())) { IncRef(ds); IncRef(random); perturbed_positions = new int[ds->patternSize()]; } template SaltPepperNoiseDataSet::~SaltPepperNoiseDataSet() { DecRef(ds); DecRef(random); delete[] perturbed_positions; } template int SaltPepperNoiseDataSet::getPattern(int index, T *pat) { int ret = ds->getPattern(index, pat); int sz = ds->patternSize(); random->shuffle(sz, perturbed_positions); for (int i=0; irand() < 0.5) ? zero : one; return ret; } template int SaltPepperNoiseDataSet::putPattern(int index, const T *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); ERROR_EXIT(1,"Method putPattern forbidden for SaltPepperNoiseDataSet!!!\n"); return 0; } //------------------------------------------------------------- template StepDataSet::StepDataSet(DataSet *ds, int step): DataSet(), ds(ds), step(step){ IncRef(ds); } template StepDataSet::~StepDataSet() { DecRef(ds); } template int StepDataSet::getPattern(int index, T *pat) { // The original position in the dataset int dst_index = (index * this->step); int ret = this->ds->getPattern(dst_index,pat); return ret; } template int StepDataSet::putPattern(int index, const T *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); ERROR_EXIT(1, "Method putPattern forbidden for StepDataset!!\n"); return 0; } //------------------------------------------------------------- template DerivDataSet::DerivDataSet(DataSet *ds, bool deriv0, bool deriv1, bool deriv2) : DataSet(), ds(ds), deriv0(deriv0), deriv1(deriv1), deriv2(deriv2) { IncRef(ds); origpatternsz = ds->patternSize(); patternsz = 0; if (deriv0) patternsz++; if (deriv1) patternsz++; if (deriv2) patternsz++; patternsz *= origpatternsz; numpatterns = ds->numPatterns(); left1 = new T[origpatternsz]; left2 = new T[origpatternsz]; right1 = new T[origpatternsz]; right2 = new T[origpatternsz]; orig = (!deriv0 && deriv2) ? (new T[origpatternsz]) : 0; } template DerivDataSet::~DerivDataSet() { DecRef(ds); delete[] left1; delete[] left2; delete[] right1; delete[] right2; if (!deriv0 && deriv2) delete[] orig; } template int DerivDataSet::getPattern(int index, T *pat) { ds->getPattern(AprilUtils::clamp(index-2,0,numpatterns-1),left2); ds->getPattern(AprilUtils::clamp(index-1,0,numpatterns-1),left1); ds->getPattern(AprilUtils::clamp(index+1,0,numpatterns-1),right1); ds->getPattern(AprilUtils::clamp(index+2,0,numpatterns-1),right2); T *aux_pat = pat; if (deriv0) { ds->getPattern(index, aux_pat); aux_pat += origpatternsz; } if (deriv1) { for (int i=0; igetPattern(index, orig); } for (int i=0; i int DerivDataSet::putPattern(int index, const T *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); ERROR_EXIT(1,"Method putPattern forbidden for DerivDataSet!!!\n"); return 0; } //------------------------------------------------------------- template CacheDataSet::CacheDataSet(DataSet *ds, int **word2cache, int *word2cache_sizes, T *decays, int voc_size, int cache_size, T near_zero, int begin_token_id, int end_token_id, int null_token_id, int cache_stop_token_id) : DataSet(), ds(ds),word2cache(word2cache), word2cache_sizes(word2cache_sizes), decays(decays), voc_size(voc_size), cache_size(cache_size), near_zero(near_zero), begin_token_id(begin_token_id), end_token_id(end_token_id), null_token_id(null_token_id), cache_stop_token_id(cache_stop_token_id) { IncRef(ds); float max_decay = 0.0f; for (int i=1; i<=cache_size; ++i) if (max_decay < decays[i]) max_decay = decays[i]; max_history = log(near_zero)/log(max_decay); if (ds->patternSize() > 1) { ERROR_EXIT(1,"Incorrect dataset size!!!\n"); } } template CacheDataSet::~CacheDataSet() { DecRef(ds); for (int i=0; i int CacheDataSet::getPattern(int index, T *pat) { T output; // ponemos la cache a cero for (int i=0; i= 0; --j) { ds->getPattern(j, &output); int wid = int(output); if (wid == end_token_id) break; } int k=0; // para toda la historia de la cache... for (j=j-1; j >= 0 && k < max_history; --j) { ds->getPattern(j, &output); int wid = int(output); // en caso de ser un stop, paramos if (wid == cache_stop_token_id) break; // solo se tiene en cuenta si la palabra es diferente a: bos, eos, null if (wid != begin_token_id && wid != end_token_id && wid != null_token_id) { // vector de indices int *idx_v = word2cache[wid]; if (idx_v != 0) { // para cada indice... for (int i=0; i near_zero) pat[idx-1] = exp_decay; // si es < near_zero le ponemos un 0.0 exacto else pat[idx-1] = 0.0f; } } } // procesamos una palabra mas ++k; } } return cache_size; } template int CacheDataSet::putPattern(int index, const T *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); ERROR_EXIT(1,"Method putPattern forbidden for CacheDataSet!!!\n"); return 0; } //------------------------------------------------------------- template SubAndDivNormalizationDataSet:: SubAndDivNormalizationDataSet(DataSet *ds, T *sub, T *div) : DataSet(), ds(ds) { IncRef(ds); const int psize=ds->patternSize(); this->sub = new T[psize]; memcpy(this->sub, sub, sizeof(T)*psize); this->div = new T[psize]; for (int i=0; idiv[i] = 1.0/div[i]; } template SubAndDivNormalizationDataSet::~SubAndDivNormalizationDataSet() { DecRef(ds); delete[] sub; delete[] div; } template int SubAndDivNormalizationDataSet::getPattern(int index, T *pat) { const int ret = ds->getPattern(index, pat); const int sz = ds->patternSize(); april_assert(ret==sz); for (int i=0; i int SubAndDivNormalizationDataSet::putPattern(int index, const T *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); ERROR_EXIT(1,"Method putPattern forbidden for SubAndDivNormalizationDataSet!!!\n"); return 0; } //------------------------------------------------------------- template ClampDataSet:: ClampDataSet(DataSet *ds, float lower, float upper) : DataSet(), ds(ds), lower(lower), upper(upper) { IncRef(ds); } template ClampDataSet::~ClampDataSet() { DecRef(ds); } template int ClampDataSet::getPattern(int index, T *pat) { const int ret = ds->getPattern(index, pat); const int sz = ds->patternSize(); april_assert(ret==sz); for (int i=0; i int ClampDataSet::putPattern(int index, const T *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); ERROR_EXIT(1,"Method putPattern forbidden for ClampDataSet!!!\n"); return 0; } //---------------------------------------------------------- } // namespace Basics #endif // DATASET_CC_H april-ann-0.4.1/packages/basics/dataset/c_src/dataset.h000066400000000000000000000557001263004425400227420ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Francisco Zamora-Martinez, Jorge * Gorbe-Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef DATASET_H #define DATASET_H #include #include #include "disallow_class_methods.h" #include "matrix.h" #include "MersenneTwister.h" #include "referenced.h" #include "referenced_vector.h" #include "sparse_matrix.h" #include "unused_variable.h" namespace Basics { /// A pure abstract templatized class that serves as interface. /** A DataSet is a class interface which define the concept of set of pattern vectors. The template argument is the type of the data stored. Methods for get the size of the set, or size of each pattern vector, are defined. Also methods to put a new pattern or to get a pattern. Patterns are indexed from 0 to N-1, being N the numPatterns of the DataSet. */ template class DataSet : public Referenced { APRIL_DISALLOW_COPY_AND_ASSIGN(DataSet); public: DataSet() { } virtual ~DataSet() { } /// Number of patterns in the set virtual int numPatterns()=0; /// Size of each pattern. virtual int patternSize()=0; /// Get the pattern index to the vector pat. The function call returns the /// patternSize(). virtual int getPattern(int index, T *pat)=0; /// Put the given vector pat at pattern index. The function returns the /// patternSize(). virtual int putPattern(int index, const T *pat)=0; }; /// DataSet specialization to put or get patterns from a Matrix object. template class MatrixDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(MatrixDataSet); private: /// A pointer referenced to the underlying Matrix object, shared pointer. Matrix *matrix; /// Initial position of each dimension int *offset; /// subPattern size. int *subMatrixSize; /// Circular boolean indicator for each dimension. bool *circular; /// Default value of positions out of Matrix limits. T defaultValue; /// Step of each dimension for the sliding window. int *step; /// Number of movements on each dimension (number of steps). int *numSteps; /// Order of movement for each dimension. int *orderStep; void setValue(int *dest, int* orig); void setValue(bool *dest, bool* orig); int numPatternsv; int patternSizev; /// Auxiliar, for getPattern. int *coordinate; /// Auxiliar, for getPattern. T *pattern; /// Auxiliar, for putPattern. const T *const_pattern; /// Auxiliar, for getPattern. int offsetpat; void index2coordinate(int index); void auxGetPattern(int offsetmatrix, int d); void auxPutPattern(int offsetmatrix, int d); public: MatrixDataSet(Matrix *m); virtual ~MatrixDataSet(); /// Setter for offset attribute. void setOffset(int* v) {setValue(offset,v);} /// Setter for step attribute. void setStep(int* v) {setValue(step,v);} /// Setter for submatrixsize attribute. void setSubMatrixSize(int* v); /// Setter for numSteps attribute. void setNumSteps(int* v); /// Setter for circular attribute. void setCircular(bool* v) {setValue(circular,v);} /// Setter for orderStep attribute. void setOrderStep(int* v) {setValue(orderStep,v);} /// Setter for default value attribute. void setDefaultValue(T f){defaultValue=f;} int numPatterns() { return numPatternsv; } int patternSize() { return patternSizev; } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// DataSet specialization to put or get patterns from a union of DataSets. /** This object allows several number of DataSets (which has exactly the same patternSize) to be treated as an unique DataSet. The numPatterns is the addition of the numPatterns of each individual DataSet. */ template class UnionDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(UnionDataSet); private: /// Number of DataSets. int num; /// Vector of referenced pointers to the DataSets. DataSet **vds; /// Vector of num+1 indices. int *d; /// Pattern size. int patternsz; public: UnionDataSet(int n, DataSet**v); virtual ~UnionDataSet(); int numPatterns() { return d[num]; } int patternSize() { return patternsz; } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// DataSet specialization which serves to getPatterns from an IdentityMatrix. template class IdentityDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(IdentityDataSet); private: /// Value of zero. const T zerovalue, /// Value of one. onevalue; /// Patterm size. int patternsz; public: IdentityDataSet(int patternSize, T zerovalue, T onevalue); virtual ~IdentityDataSet(); int numPatterns() { return patternsz; } int patternSize() { return patternsz; } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// A DataSet specialization which takes an interval of patterns from other. /** This object is specialized to take an interval of patterns from other DataSet. For more general subsets representation, see IndexDataSet documentation. */ template class SubDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(SubDataSet); private: /// Initial position of the interval int ini, /// Final position of the interval fin, /// Resulting numPatterns size; /// The underlying DataSet DataSet *ds; public: SubDataSet(int ini, int fin, DataSet*ds); virtual ~SubDataSet(); int numPatterns() { return size; } int patternSize() { return ds->patternSize(); } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// A specialization of DataSet which takes an split of other DataSet. /** This object allows to take a subset of the output elements from a given DataSet. That is, the resulting DataSet has the same numPatterns, but lower patternSize. The output subset is an interval. */ template class SplitDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(SplitDataSet); private: /// Initial position of the split interval. int ini, /// Final position of the split interval. fin, /// Resulting patternSize. size; /// An auxiliary vector. T *aux; /// The underlying DataSet DataSet *ds; public: SplitDataSet(int ini, int fin, DataSet *ds); virtual ~SplitDataSet(); int numPatterns() { return ds->numPatterns(); } int patternSize() { return size; } int getPattern(int index, T *pat); int putPattern(int index, const T *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); return 0; } // NO DEFINIDO }; /// A specialization of DataSet which join outputs from several DataSets. /** This object joins the output a several number of given DataSets. All DataSets must have exactly the same numPatterns. The resulting patternSize is the addition of each patternSize of individuals DataSets. */ template class JoinDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(JoinDataSet); private: /// Number of DataSets. int num; /// A vector of referenced pointers to the underlying DataSets. DataSet **vds; /// num+1 size vector which keep patternSize accumulated result. int *d; public: JoinDataSet(int n, DataSet **v); virtual ~JoinDataSet(); int numPatterns() { return vds[0]->numPatterns(); } int patternSize() { return d[num]; } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// A specialization of DataSet which takes a general sub set from other. /** This object allows to take any subset of patterns from other DataSet. It builds a mapping between indexes and patterns. It is also useful for classification output specification. */ template class IndexDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(IndexDataSet); // A float could represent the int value 16777216 private: /// DataSet from which take indexes. DataSet *indices; /// Number of dictionaries, we need indices->patternSize() dictionaries. int numdiccionarios; /// Dictionary DataSets from which take patterns. DataSet **diccionarios; /// Auxiliar vector. T *patternindices; /// Output pattern size. int patternsize; /// First index, to solve Lua/C problems because of Lua 1 first index. int firstindex; public: IndexDataSet(DataSet **datasets,int firstindex=0); virtual ~IndexDataSet(); int numPatterns() { return indices->numPatterns(); } int patternSize() { return patternsize; } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// An auxiliar object for LinearCombDataSet. template class LinearCombConf : public Referenced { APRIL_DISALLOW_COPY_AND_ASSIGN(LinearCombConf); public: /// Pattern size of the linear combination int patternsize; /// Number of pairs (index,weight) of each patternSize. int *numTuplas; /// Indices of the combinations. int *indices; /// Weights of the combinations. T *pesos; LinearCombConf(int pattsz, int numpairs) { patternsize = pattsz; numTuplas = (new int[pattsz+1])+1; numTuplas[-1] = 0; indices = new int[numpairs]; pesos = new T[numpairs]; } virtual ~LinearCombConf() { delete[] (numTuplas-1); delete[] indices; delete[] pesos; } }; /// A specialization of DataSet, takes a DataSet and outputs a linear combination of its patterns. /** This object takes a DataSet and produces a linear combination of its patterns. For instance, taking a DataSet with X patternSize and generates Y patternSize patterns, the object will need a matrix of XxY. However, this matrix will be normally very disperse, so, the object LinearCombConf stores pairs of (index,weight), and has a list of pairs for each Y output element. */ template class LinearCombDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(LinearCombDataSet); private: /// Linear combination configuration. LinearCombConf *conf; /// The underlying DataSet. DataSet *ds; /// Auxiliar vector. T *aux; public: LinearCombDataSet(DataSet *ds, LinearCombConf *conf); virtual ~LinearCombDataSet(); int numPatterns() { return ds->numPatterns(); } int patternSize() { return conf->patternsize; } int getPattern(int index, T *pat); int putPattern(int index, const T *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); return 0; } }; /// A specialization of DataSet which takes a DataSet and adds context to its patterns. /** This object adds context to the patterns of a given DataSet. The context are adjacents patterns, at left or/and at right positions from the interesting pattern index. In the case of a border limit, the interesting pattern will be repeated. */ template class ContextualizerDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(ContextualizerDataSet); private: /// Left context. int ctxtizq, /// Right context. ctxtder; /// The underlying DataSet. DataSet *ds; /// Number of patterns. int numpatterns, /// Size of each pattern. patternsize; /// Indicates if the context will be reversed. bool reverse; public: ContextualizerDataSet(DataSet *ds,int izq, int der, bool reverse=false); virtual ~ContextualizerDataSet(); int numPatterns() { return numpatterns; } int patternSize() { return patternsize; } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// A specialization of DataSet for data accumulation using putPattern template class AccumulateDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(AccumulateDataSet); private: /// Number of patterns int numpatterns, /// Pattern size patternsize; /// Data accumulation vector. double *data; // IMPORTANT: it is not T type, T will be casted from/to double public: AccumulateDataSet(int patsz, int numpat); virtual ~AccumulateDataSet(); int numPatterns() { return numpatterns; } int patternSize() { return patternsize; } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; template class ByteDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(ByteDataSet); // sirve para acumular una serie de valores mediante putpattern private: int numpatterns,patternsize; double a,b; // y = a*x+b con x entre 0 y 255 unsigned char *data; public: ByteDataSet(int patsz, int numpat, double a, double b); virtual ~ByteDataSet(); int numPatterns() { return numpatterns; } int patternSize() { return patternsize; } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; template class BitDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(BitDataSet); private: int numpatterns, patternsize; unsigned char *data; public: BitDataSet(int nump, int patsize); virtual ~BitDataSet(); int numPatterns() { return numpatterns; } int patternSize() { return patternsize; } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// A specialization of DataSet for use sparse data representation. /** This object takes a sparse matrix in CSR format, the matrix have NxM where N is numpatterns amd M is patternsize. Every getPattern will return a dense vector. To use sparse matrices use DatasetToken implementation. */ template class SparseMatrixDataset : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(SparseMatrixDataset); /// The underlying matrix with sparse data representation in CSR format. SparseMatrix *matrix; /// Number of patterns. int numpatterns, /// Pattern size. patternsize; public: SparseMatrixDataset(SparseMatrix *m); virtual ~SparseMatrixDataset(); int numPatterns() { return numpatterns; } int patternSize() { return patternsize; } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// A specialization DataSet for shortlist approach in NNLMs. /** This object takes a DataSet as a dictionary of word features, and each getPattern return features of given word index. If the index is greater than short_list_size, it will take unk_word index. */ template class ShortListDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(ShortListDataSet); /// The underlying DataSet DataSet *ds; /// Size of the shortlist approach. int short_list_size, /// Index of the unknown word (out-of-shortlist word) unk_word, /// Pattern size, number of features for each word patsize; public: ShortListDataSet(DataSet *ds, int short_list_size, int unk_word); virtual ~ShortListDataSet(); int numPatterns() { return ds->numPatterns(); } int patternSize() { return patsize; } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// Similar to IndexedDataSet but using a vector of unsigned int as indexes. template class IndexFilterDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(IndexFilterDataSet); /// The indexed DataSet. DataSet *ds; /// The vector of indexes. AprilUtils::ReferencedVectorUint *indexes; public: IndexFilterDataSet(DataSet *ds, AprilUtils::ReferencedVectorUint *indexes); virtual ~IndexFilterDataSet(); int numPatterns() { return (int)indexes->size(); } int patternSize() { return ds->patternSize(); } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// A specialization of DataSet which add gaussian noise to patterns. template class PerturbationDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(PerturbationDataSet); /// The underlying DataSet. DataSet *ds; /// A MTRand for random gaussian noise generation MTRand *random; /// Mean of the gaussian noise double mean, /// Variance of the gaussian noise variance; public: PerturbationDataSet(DataSet *ds, MTRand *random, double mean, double variance); virtual ~PerturbationDataSet(); int numPatterns() { return ds->numPatterns(); } int patternSize() { return ds->patternSize(); } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// A specialization of DataSet which add a fixed size salt noise to patterns. template class SaltNoiseDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(SaltNoiseDataSet); /// The underlying DataSet. DataSet *ds; /// A MTRand for random selection of pattern components MTRand *random; /// Percentage of values to be modified double vd; /// Value of the zero const T zero; /// Number of zeroes: vd * patternSize int number_of_zeroes; /// Vector of ints for the selected zero positions int *zero_positions; public: SaltNoiseDataSet(DataSet *ds, MTRand *random, double vd, T zero); virtual ~SaltNoiseDataSet(); int numPatterns() { return ds->numPatterns(); } int patternSize() { return ds->patternSize(); } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// A specialization of DataSet which add a fixed size salt and pepper noise to patterns. template class SaltPepperNoiseDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(SaltPepperNoiseDataSet); /// The underlying DataSet. DataSet *ds; /// A MTRand for random selection of pattern components MTRand *random; /// Percentage of values to be modified double vd; /// Value of the zero const T zero; /// Value of the one const T one; /// Number of zeroes: vd * patternSize int number_of_perturbations; /// Vector of ints for the selected zero positions int *perturbed_positions; public: SaltPepperNoiseDataSet(DataSet *ds, MTRand *random, double vd, T zero, T one); virtual ~SaltPepperNoiseDataSet(); int numPatterns() { return ds->numPatterns(); } int patternSize() { return ds->patternSize(); } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// A specialization of DataSet which takes samples on a defined step size. template class StepDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(StepDataSet); /// The underlying DataSet. DataSet *ds; int step; public: StepDataSet(DataSet *ds, int step); virtual ~StepDataSet(); int numPatterns() { return (int)ceil((float)ds->numPatterns()/step); } int patternSize() { return ds->patternSize(); } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// A specialization of DataSet for cacheNNLMs training. template class CacheDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(CacheDataSet); DataSet *ds; int **word2cache; int *word2cache_sizes; T *decays; int voc_size; int cache_size; T near_zero; int max_history; int begin_token_id; int end_token_id; int null_token_id; int cache_stop_token_id; public: CacheDataSet(DataSet *ds, int **word2cache, int *word2cache_sizes, T *decays, int voc_size, int cache_size, T near_zero, int begin_token_id, int end_token_id, int null_token_id, int cache_stop_token_id); virtual ~CacheDataSet(); int numPatterns() { return ds->numPatterns(); } int patternSize() { return cache_size; } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; template class DerivDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(DerivDataSet); DataSet *ds; bool deriv0,deriv1,deriv2; int numpatterns,origpatternsz,patternsz; T *orig,*left1,*left2,*right1,*right2; public: DerivDataSet(DataSet *ds, bool deriv0, bool deriv1, bool deriv2); virtual ~DerivDataSet(); int numPatterns() { return numpatterns; } int patternSize() { return patternsz; } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// A specialization of DataSet which performs sub, and div normalization template class SubAndDivNormalizationDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(SubAndDivNormalizationDataSet); /// The underlying DataSet. DataSet *ds; /// The vector with sub values T *sub; /// The vector with div values T *div; public: SubAndDivNormalizationDataSet(DataSet *ds, T *sub, T *div); virtual ~SubAndDivNormalizationDataSet(); int numPatterns() { return ds->numPatterns(); } int patternSize() { return ds->patternSize(); } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; /// A specialization of DataSet which performs a clamp template class ClampDataSet : public DataSet { APRIL_DISALLOW_COPY_AND_ASSIGN(ClampDataSet); /// The underlying DataSet. DataSet *ds; float lower, upper; public: ClampDataSet(DataSet *ds, float lower, float upper); virtual ~ClampDataSet(); int numPatterns() { return ds->numPatterns(); } int patternSize() { return ds->patternSize(); } int getPattern(int index, T *pat); int putPattern(int index, const T *pat); }; } /*** Implementacion ***/ #include "dataset.cc" #endif // DATASET_H april-ann-0.4.1/packages/basics/dataset/c_src/datasetFloat.h000066400000000000000000000034211263004425400237210ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Francisco Zamora-Martinez, Jorge * Gorbe-Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef UTILDATASETFLOAT_H #define UTILDATASETFLOAT_H #include "dataset.h" namespace Basics { typedef DataSet DataSetFloat; typedef MatrixDataSet MatrixDataSetFloat; typedef LinearCombConf LinearCombConfFloat; typedef SparseMatrixDataset SparseMatrixDatasetFloat; typedef ShortListDataSet ShortListDataSetFloat; typedef IndexFilterDataSet IndexFilterDataSetFloat; typedef PerturbationDataSet PerturbationDataSetFloat; typedef SaltNoiseDataSet SaltNoiseDataSetFloat; typedef SaltPepperNoiseDataSet SaltPepperNoiseDataSetFloat; typedef StepDataSet StepDataSetFloat; typedef DerivDataSet DerivDataSetFloat; typedef CacheDataSet CacheDataSetFloat; typedef SubAndDivNormalizationDataSet SubAndDivNormalizationDataSetFloat; typedef ClampDataSet ClampDataSetFloat; } // namespace Basics #endif // UTILDATASETFLOAT_H april-ann-0.4.1/packages/basics/dataset/c_src/datasetToken.cc000066400000000000000000000217471263004425400241050ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Francisco Zamora-Martinez, Jorge * Gorbe-Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "dataset.h" #include "datasetFloat.h" #include "datasetToken.h" #include "function_interface.h" #include "matrixFloat.h" #include "matrix_ext.h" #include "smart_ptr.h" #include "token_base.h" #include "token_matrix.h" #include "token_sparse_matrix.h" #include "token_vector.h" #include "table_of_token_codes.h" #include "unused_variable.h" #include "vector.h" using AprilMath::MatrixExt::BLAS::matCopy; using AprilUtils::SharedPtr; using AprilUtils::vector; using AprilMath::FloatGPUMirroredMemoryBlock; using AprilMath::Int32GPUMirroredMemoryBlock; namespace Basics { namespace DataSetTokenUtils { SharedPtr buildMatrixFloatBunch(DataSetToken *ds, const int *indexes, unsigned int bunch_size, SharedPtr aux_token) { if (aux_token.empty()) aux_token = ds->getPattern(indexes[0]); // FIXME: Check this shape to be consistent when getPattern() returns a multi-dimensional matrix. int dims[2] = { static_cast(bunch_size), ds->patternSize() }; SharedPtr output_mat( new MatrixFloat(2, dims) ); TokenMatrixFloat *output_mat_token = new TokenMatrixFloat(output_mat.get()); SharedPtr result( output_mat_token ); // the dims vector will be used to rewrap the matrices to have the same // structure dims[0] = ds->patternSize(); SharedPtr submat; for (int i=0; i(bunch_size); ++i) { if (i>0) aux_token = ds->getPattern(indexes[i]); TokenMatrixFloat *mat_token = aux_token->convertTo(); SharedPtr mat( mat_token->getMatrix() ); SharedPtr mat_rewrapped( mat->rewrap(dims, 1) ); submat = output_mat->select(0, i, submat.get()); matCopy(submat.get(), mat_rewrapped.get()); } return result; } SharedPtr buildSparseMatrixFloatBunch(DataSetToken *ds, const int *indexes, unsigned int bunch_size, SharedPtr aux_token) { if (aux_token.empty()) aux_token = ds->getPattern(indexes[0]); TokenSparseMatrixFloat *sparse_token = aux_token->convertTo(); SparseMatrixFloat *sparse_matrix = sparse_token->getMatrix(); int dims[2] = { static_cast(bunch_size), ds->patternSize() }; unsigned int nnz = sparse_matrix->nonZeroSize(); vector< SharedPtr > matrices(bunch_size); matrices[0] = sparse_matrix; for (unsigned int i=1; igetPattern(indexes[i]); sparse_token = aux_token->convertTo(); sparse_matrix = sparse_token->getMatrix(); matrices[i] = sparse_matrix; nnz += sparse_matrix->nonZeroSize(); } // build a sparse matrix with nnz values in CSR format SharedPtr< FloatGPUMirroredMemoryBlock > values(new FloatGPUMirroredMemoryBlock(nnz)); SharedPtr< Int32GPUMirroredMemoryBlock > indices(new Int32GPUMirroredMemoryBlock(nnz)); SharedPtr< Int32GPUMirroredMemoryBlock > first_index(new Int32GPUMirroredMemoryBlock(bunch_size + 1)); (*first_index)[0] = 0; size_t pos=0; for (unsigned int i=0; inonZeroSize(); if (sparse_matrix->getSparseFormat() != CSR_FORMAT) { ERROR_EXIT(128, "Only implemented for CSR sparse matrices"); } values->copyFromBlock(pos, sparse_matrix->getRawValuesAccess(), 0, sz); indices->copyFromBlock(pos, sparse_matrix->getRawIndicesAccess(), 0, sz); pos += sz; (*first_index)[i+1] = pos; } SparseMatrixFloat *result = new SparseMatrixFloat(dims[0], dims[1], values.get(), indices.get(), first_index.get()); return new TokenSparseMatrixFloat(result); } // SharedPtr buildTokenVectorBunch(DataSetToken *ds, // const int *indexes, // unsigned int bunch_size) // { // TokenBunchVector *result_token_vector = new TokenBunchVector(bunch_size); // SharedPtr result( result_token_vector ); // for (unsigned int i = 0; igetPattern(indexes[i]); // TokenCode token_code = tk->getTokenCode(); // SharedPtr current; // switch(token_code) { // case table_of_token_codes::token_matrix: // current = buildMatrixFloatBunch(ds, indexes, bunch_size); // break; // case table_of_token_codes::token_sparse_matrix: // current = buildSparseMatrixFloatBunch(ds, indexes, bunch_size); // break; // default: // current = tk; // break; // } // (*result_token_vector)[i] = current.weakRelease(); // } // return result; // } } // namespace DataSetTokenUtils } // namespace Basics using namespace Basics::DataSetTokenUtils; namespace Basics { /// Get the pattern index to the vector pat Token *DataSetToken::getPatternBunch(const int *indexes, unsigned int bunch_size) { SharedPtr result; SharedPtr aux_token( getPattern(indexes[0]) ); TokenCode token_code = aux_token->getTokenCode(); switch(token_code) { case table_of_token_codes::token_matrix: result = buildMatrixFloatBunch(this, indexes, bunch_size, aux_token); break; case table_of_token_codes::token_sparse_matrix: result = buildSparseMatrixFloatBunch(this, indexes, bunch_size, aux_token); break; default: ERROR_EXIT(128, "Not implemented\n"); // result = buildTokenVectorBunch(this, indexes, bunch_size); break; } return result.weakRelease(); } Token *SparseMatrixDataSetToken::getPatternBunch(const int *indexes, unsigned int bunch_size) { unsigned int nnz = 0; const FloatGPUMirroredMemoryBlock *data_values = data->getRawValuesAccess(); const Int32GPUMirroredMemoryBlock *data_indices = data->getRawIndicesAccess(); const Int32GPUMirroredMemoryBlock *data_first_index = data->getRawFirstIndexAccess(); for (unsigned int i=0; i= numPatterns()) { ERROR_EXIT2(128, "Out-of-bounds index, expected in " "range [0,%d], found %d\n", numPatterns(), p); } nnz += (*data_first_index)[p+1] - (*data_first_index)[p]; } int dims[2] = { static_cast(bunch_size), patternSize() }; // build a sparse matrix with nnz values in CSR format SharedPtr< FloatGPUMirroredMemoryBlock > values(new FloatGPUMirroredMemoryBlock(nnz)); SharedPtr< Int32GPUMirroredMemoryBlock > indices(new Int32GPUMirroredMemoryBlock(nnz)); SharedPtr< Int32GPUMirroredMemoryBlock > first_index(new Int32GPUMirroredMemoryBlock(bunch_size + 1)); (*first_index)[0] = 0; size_t pos=0; for (unsigned int i=0; icopyFromBlock(pos, data_values, from, sz); indices->copyFromBlock(pos, data_indices, from, sz); pos += sz; (*first_index)[i+1] = pos; } SparseMatrixFloat *result = new SparseMatrixFloat(dims[0], dims[1], values.get(), indices.get(), first_index.get()); return new TokenSparseMatrixFloat(result); } } // namespace Basics april-ann-0.4.1/packages/basics/dataset/c_src/datasetToken.h000066400000000000000000000332251263004425400237410ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Francisco Zamora-Martinez, Jorge * Gorbe-Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef UTILDATASETTOKEN_H #define UTILDATASETTOKEN_H #include "dataset.h" #include "datasetFloat.h" #include "function_interface.h" #include "matrixFloat.h" #include "matrix_ext.h" #include "smart_ptr.h" #include "token_base.h" #include "token_matrix.h" #include "token_sparse_matrix.h" #include "token_vector.h" #include "table_of_token_codes.h" #include "unused_variable.h" #include "vector.h" namespace Basics { class DataSetToken : public Referenced { public: virtual ~DataSetToken() { } /// Number of patterns in the set virtual int numPatterns()=0; /// Size of each pattern. virtual int patternSize()=0; /// Get the pattern index to the vector pat virtual Token *getPattern(int index)=0; /// Get the pattern index to the vector pat virtual Token *getPatternBunch(const int *indexes,unsigned int bunch_size); /// Put the given vector pat at pattern index virtual void putPattern(int index, Token *pat)=0; /// Put the pattern bunch virtual void putPatternBunch(const int *indexes,unsigned int bunch_size, Token *pat)=0; }; class DataSetTokenVector : public DataSetToken { AprilUtils::vector data; int pattern_size; public: DataSetTokenVector(int pattern_size) : pattern_size(pattern_size) { } virtual ~DataSetTokenVector() { for (unsigned int i=0; i(data.size()); } /// Size of each pattern. virtual int patternSize() { return pattern_size; } /// Get the pattern index to the vector pat virtual Token *getPattern(int index) { if (index < 0 || index >= numPatterns()) return 0; return data[index]->clone(); } /// Put the given vector pat at pattern index virtual void putPattern(int index, Token *pat) { if (index < 0 || index >= numPatterns()) return; AssignRef(data[index], pat); } /// Put the pattern bunch virtual void putPatternBunch(const int *indexes,unsigned int bunch_size, Token *pat) { UNUSED_VARIABLE(indexes); UNUSED_VARIABLE(bunch_size); UNUSED_VARIABLE(pat); ERROR_EXIT(128, "Not implemented!!!\n"); } }; class UnionDataSetToken : public DataSetToken { AprilUtils::vector ds_array; AprilUtils::vector sum_patterns; int pattern_size; public: UnionDataSetToken(DataSetToken **ds_array, unsigned int size) : pattern_size(0) { sum_patterns.push_back(0); for (unsigned int i=0; ipatternSize(); else if (pattern_size != ds->patternSize()) ERROR_EXIT2(128, "Incorrect pattern size, expected %d, found %d\n", pattern_size, ds->patternSize()); sum_patterns.push_back(sum_patterns.back() + ds->numPatterns()); } /// Number of patterns in the set virtual int numPatterns() { return sum_patterns.back(); } /// Size of each pattern. virtual int patternSize() { return pattern_size; } /// Get the pattern index to the vector pat virtual Token *getPattern(int index) { if (index < 0 || index >= numPatterns()) return 0; int izq,der,m; izq = 0; der = static_cast(sum_patterns.size()); do { m = (izq+der)/2; if (sum_patterns[m] <= index) izq = m; else der = m; } while (izq < der-1); return ds_array[izq]->getPattern(index-sum_patterns[izq]); } /// Put the given vector pat at pattern index virtual void putPattern(int index, Token *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); ERROR_EXIT(128, "Not implemented!!!\n"); } /// Put the pattern bunch virtual void putPatternBunch(const int *indexes,unsigned int bunch_size, Token *pat) { UNUSED_VARIABLE(indexes); UNUSED_VARIABLE(bunch_size); UNUSED_VARIABLE(pat); ERROR_EXIT(128, "Not implemented!!!\n"); } }; class DataSetFloat2TokenWrapper : public DataSetToken { AprilUtils::SharedPtr aux_mat; AprilUtils::SharedPtr ds; public: DataSetFloat2TokenWrapper(DataSetFloat *ds) : ds(ds) { int dims[2] = { 1, ds->patternSize() }; aux_mat = new MatrixFloat(2, dims); #ifdef USE_CUDA aux_mat->setUseCuda(false); #endif } virtual ~DataSetFloat2TokenWrapper() { } int numPatterns() { return ds->numPatterns(); } int patternSize() { return ds->patternSize(); } Token *getPattern(int index) { int dims[2] = { 1, patternSize() }; MatrixFloat *mat = new MatrixFloat(2, dims); TokenMatrixFloat *token = new TokenMatrixFloat(mat); AprilMath::FloatGPUMirroredMemoryBlock *mem_block = mat->getRawDataAccess(); float *mem_ptr = mem_block->getPPALForWrite(); ds->getPattern(index, mem_ptr); return token; } Token *getPatternBunch(const int *indexes, unsigned int bunch_size) { int dims[2], major_dim=0; dims[0] = static_cast(bunch_size); dims[1] = patternSize(); MatrixFloat *mat = new MatrixFloat(2, dims); #ifdef USE_CUDA bool old_use_cuda = mat->getCudaFlag(); mat->setUseCuda(false); #endif // The TokenMatrixFloat takes increases reference counter of Matrix. TokenMatrixFloat *token = new TokenMatrixFloat(mat); // The memory block given to ds->getPattern(...). AprilMath::FloatGPUMirroredMemoryBlock *aux_mem_block = aux_mat->getRawDataAccess(); float *aux_mem = aux_mem_block->getPPALForWrite(); // int pattern_size = patternSize(); int num_patterns = numPatterns(); dims[major_dim] = 1; AprilUtils::SharedPtr submat; for (unsigned int i=0; igetPattern(indexes[i], aux_mem); submat = mat->select(0, i, submat.get()); AprilMath::MatrixExt::BLAS::matCopy(submat.get(),aux_mat.get()); } #ifdef USE_CUDA mat->setUseCuda(old_use_cuda); #endif return token; } void putPattern(int index, Token *pat) { if (pat->getTokenCode() != table_of_token_codes::token_matrix) ERROR_EXIT(128, "Incorrect token type, expected token matrix\n"); TokenMatrixFloat *token_matrix = pat->convertTo(); MatrixFloat *mat = token_matrix->getMatrix(); AprilMath::FloatGPUMirroredMemoryBlock *mem_block = mat->getRawDataAccess(); const float *v = mem_block->getPPALForRead(); ds->putPattern(index, v); } void putPatternBunch(const int *indexes,unsigned int bunch_size, Token *pat) { if (pat->getTokenCode() != table_of_token_codes::token_matrix) ERROR_EXIT(128, "Incorrect token type, expected token matrix\n"); TokenMatrixFloat *token_matrix = pat->convertTo(); MatrixFloat *mat = token_matrix->getMatrix(); #ifdef USE_CUDA bool old_use_cuda = mat->getCudaFlag(); mat->setUseCuda(false); #endif if (mat->getNumDim() != 2) ERROR_EXIT(128, "Only allowed for 2-dim matrices\n"); AprilMath::FloatGPUMirroredMemoryBlock *aux_mem_block = aux_mat->getRawDataAccess(); float *aux_mem = aux_mem_block->getPPALForWrite(); int pattern_size = patternSize(); int coords[2], major_dim; int sizes[2]; major_dim = 0; coords[1] = 0; sizes[0] = 1; sizes[1] = pattern_size; AprilUtils::SharedPtr submat; for (unsigned int i=0; i(i); submat = mat->select(0, i, submat.get()); AprilMath::MatrixExt::BLAS::matCopy(aux_mat.get(),submat.get()); ds->putPattern(indexes[i], aux_mem); } #ifdef USE_CUDA mat->setUseCuda(old_use_cuda); #endif } }; class DataSetTokenFilter : public DataSetToken { // the underlying dataset DataSetToken *ds; Functions::FunctionInterface *filter; public: DataSetTokenFilter(DataSetToken *ds, Functions::FunctionInterface *filter) : ds(ds), filter(filter) { IncRef(ds); IncRef(filter); } virtual ~DataSetTokenFilter() { DecRef(ds); DecRef(filter); } /// Number of patterns in the set virtual int numPatterns() { return ds->numPatterns(); } /// Size of each pattern. virtual int patternSize() { return ( (filter->getOutputSize() > 0) ? filter->getOutputSize() : ds->patternSize() ); } /// Get the pattern index to the vector pat virtual Token *getPattern(int index) { return filter->calculate(ds->getPattern(index)); } /// Get the pattern index to the vector pat virtual Token *getPatternBunch(const int *indexes,unsigned int bunch_size) { return filter->calculate(ds->getPatternBunch(indexes,bunch_size)); } /// Put the given vector pat at pattern index virtual void putPattern(int index, Token *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); ERROR_EXIT(128, "Not implemented\n"); } /// Put the pattern bunch virtual void putPatternBunch(const int *indexes,unsigned int bunch_size, Token *pat) { UNUSED_VARIABLE(indexes); UNUSED_VARIABLE(bunch_size); UNUSED_VARIABLE(pat); ERROR_EXIT(128, "Not implemented\n"); } }; class SparseMatrixDataSetToken : public DataSetToken { AprilUtils::SharedPtr< SparseMatrixFloat > data; public: SparseMatrixDataSetToken(SparseMatrixFloat *data) : data(data) { if (data->getSparseFormat() != CSR_FORMAT) { ERROR_EXIT(128, "Only valid for CSR matrices\n"); } } virtual ~SparseMatrixDataSetToken() { } virtual int numPatterns() { return data->getDimSize(0); } virtual int patternSize() { return data->getDimSize(1); } virtual Token *getPattern(int index) { int coords[2] = { index, 0 }; int sizes[2] = {1, patternSize() }; SparseMatrixFloat *sparse_matrix; sparse_matrix = new SparseMatrixFloat(data.get(), coords, sizes); return new TokenSparseMatrixFloat(sparse_matrix); } virtual Token *getPatternBunch(const int *indexes, unsigned int bunch_size); virtual void putPattern(int index, Token *pat) { UNUSED_VARIABLE(index); UNUSED_VARIABLE(pat); ERROR_EXIT(128, "Not implemented\n"); } virtual void putPatternBunch(const int *indexes,unsigned int bunch_size, Token *pat) { UNUSED_VARIABLE(indexes); UNUSED_VARIABLE(bunch_size); UNUSED_VARIABLE(pat); ERROR_EXIT(128, "Not implemented!!!\n"); } }; namespace DataSetTokenUtils { /** * @brief Builds a Basics::TokenMatrixFloat from a given array of indices * taken from the given Basics::DataSetToken * * @param ds - The dataset where patterns are stored. * @param indexes - An array of pattern indices. * @param bunch_size - The size of the @c indexes array (mini-batch). * @param aux_token - The first token in the list, or it can be 0. This * parameter is given by algorithms which need one token look-ahead to * determine the token type. */ AprilUtils::SharedPtr buildMatrixFloatBunch(Basics::DataSetToken *ds, const int *indexes, unsigned int bunch_size, AprilUtils::SharedPtr aux_token = 0); /** * @brief Builds a Basics::TokenSparseMatrixFloat from a given array of * indices taken from the given Basics::DataSetToken * * @param ds - The dataset where patterns are stored. * @param indexes - An array of pattern indices. * @param bunch_size - The size of the @c indexes array (mini-batch). * @param aux_token - The first token in the list, or it can be 0. This * parameter is given by algorithms which need one token look-ahead to * determine the token type. */ AprilUtils::SharedPtr buildSparseMatrixFloatBunch(Basics::DataSetToken *ds, const int *indexes, unsigned int bunch_size, AprilUtils::SharedPtr aux_token = 0); } } // namespace Basics #endif // UTILDATASETFLOAT_H april-ann-0.4.1/packages/basics/dataset/c_src/fmeasure.cc000066400000000000000000000051631263004425400232600ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Francisco Zamora-Martinez, Jorge * Gorbe-Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "error_print.h" #include "fmeasure.h" namespace Basics { float Fmeasure(DataSetFloat *ds, DataSetFloat *GT, float &PR, float &RC) { // Error control if (ds->numPatterns() != GT->numPatterns()) { ERROR_PRINT2("F measure: diferent numPatterns(): %d != %d\n", ds->numPatterns(), GT->numPatterns()); exit(128); } if (ds->patternSize() != GT->patternSize()) { ERROR_PRINT2("F measure: diferent patternSize(): %d != %d\n", ds->patternSize(), GT->patternSize()); exit(128); } if (ds->patternSize() != 1) { ERROR_PRINT1("F measure: patternSize must be 1, and is %d\n", ds->patternSize()); exit(128); } /////////////////////////////////////////////////////////////// const int patSize = ds->patternSize(); const int numPats = ds->numPatterns(); if (patSize != 1) { ERROR_PRINT("F measure: patternSize different of 1\n"); exit(128); } // int Ctp=0; // number of true positives int Cfp=0; // number of false positives int Cfn=0; // number of false negatives // float *pat_ds = new float[patSize], *pat_GT = new float[patSize]; for (int i=0; igetPattern(i, pat_ds); GT->getPattern(i, pat_GT); if (positive(pat_ds[0])) { // true positive if (positive(pat_GT[0])) ++Ctp; // false positive else ++Cfp; } // false negative else if (positive(pat_GT[0])) ++Cfn; } // RC = float(Ctp)/(Cfn + Ctp); PR = float(Ctp)/(Cfp + Ctp); float FM = (2*RC*PR / (RC+PR)) * 100; delete[] pat_ds; delete[] pat_GT; return FM; } } // namespace Basics april-ann-0.4.1/packages/basics/dataset/c_src/fmeasure.h000066400000000000000000000022171263004425400231170ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Francisco Zamora-Martinez, Jorge * Gorbe-Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef FMEASURE_H #define FMEASURE_H #include "datasetFloat.h" #define positive(v) (v)<=0.1f namespace Basics { /// This function computes Fmeasure given two DataSetFloat. float Fmeasure(DataSetFloat *ds, DataSetFloat *GT, float &PR, float &RC); } #endif april-ann-0.4.1/packages/basics/dataset/doc/000077500000000000000000000000001263004425400206115ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/dataset/doc/dataset_user.dox000066400000000000000000000255461263004425400240240ustar00rootroot00000000000000 /** \page dataset Dataset Las matrices por sí mismas no son directamente utilizables desde los algoritmos de aprendizaje automático, ya que estos utilizan una abstracción de un conjunto de datos denominada \c dataset Un \c dataset responde a los métodos siguientes: - \b numPatterns, devuelve el número de patrones. - \b patternSize, devuelve el tamaño máximo de los patrones. - \b getPattern, recibe un índice numérico (un valor entre 1 y numPatterns) y devuelve un vector (tabla \nom{Lua}) con el índice-ésimo patrón. - \b putPattern, recibe un índice numérico (un valor entre 1 y \nom{numPatterns}) y un vector de tamaño \nom{patternSize} y modifica el \nom{dataset} para dar cuenta de esta información. No todas las clases \nom{dataset} permiten modificarse, y en tal caso avisan devolviendo 0 en lugar de \nom{patternSize}. \end{itemize} . \section dataset_matrix dataset.matrix La forma más convencional de crear un \c dataset es a partir de una matriz: \verbatim --> recordemos que xor_in es una matriz de 4x2 ds_xor_in = dataset.matrix(xor_in) --> 4 patrones de tamaño 2 --> recordemos que xor_out es una matriz de 4x1 ds_xor_out = dataset.matrix(xor_out) --> 4 patrones de tamaño 1 \endverbatim Cuando creamos un dataset a partir de una matriz de dimensiones \f$n_1 \times n_2 \times \cdots \times n_k\f$ se crea un dataset con \f$n_1\f$ patrones de tamaño \f$n_2 \cdots \times n_{k}\f$. Para una matriz de dimensión 2 corresponde con lo esperado de manera intuitiva, mientras que para una matriz tiene una sola dimensión (un vector) se corresponde con el recorrido de todos sus valores, como se aprecia en el siguiente ejemplo, donde además vemos que el método \c patterns() devuelve un iterador que se puede utlizar en un bucle \c for: \verbatim a = matrix(2, 2, {1,2,3,4}) b = dataset.matrix(a) for i,j in b:patterns() do print(table.concat(j,",")) end --> 1,2 --> 3,4 a = matrix(2,2,2,{1,2,3,4,5,6,7,8}) b = dataset.matrix(a) for i,j in b:patterns() do print(table.concat(j,",")) end --> 1,2,3,4 --> 5,6,7,8 a = matrix(4,{1,2,3,4}) b = dataset.matrix(a) for i,j in b:patterns() do print(table.concat(j,",")) end --> 1 --> 2 --> 3 --> 4 \endverbatim Hasta aquí no se aprecia ninguna ventaja del uso de \c dataset respecto de las matrices. Vamos a ver que sobre una misma matriz podemos generar varios datasets variando algunos parámetros que, hasta el momento, se han tomado por defecto. Si creamos un dataset con \c dataset.matrix y el primer argumento es una matriz de tamaño \f$n_1 \times n_2 \times \cdots \times n_k\f$, podemos pasar un segundo argumento que es una tabla con los siguientes campos: - \b patternSize, Es una tabla de \f$k\f$ enteros estrictamente positivos. Indica el tamaño del sub-patrón. Su valor por defecto es \f$\{ 1, n_2, n_3, \ldots{}, n_k\}\f$. - \b offset, Es una tabla de \f$k\f$ enteros. Indica la posición inicial del primer subpatrón que se va a extraer. Esta es una mejora respecto al \nom{SNNS}, por ejemplo. Además, los valores pueden ser negativos o pueden salirse de las coordenadas límite de la matriz. Atención porque la posición inicial en una coordenada es 0 (como en C) y no 1 (como en \nom{Lua}). El valor por defecto de este campo es \f$\{0,\ldots{},0\}\f$. - \b numSteps, Es una tabla de \f$k\f$ enteros estrictamente positivos. Indica el número de pasos que se utilizan en cada dimensión para generar todos los subpatrones. Su valor por defecto es \f$\{n_1, 1, \ldots{}, 1\}\f$. El número total de patrones del dataset será siempre igual al productorio de los valores de este campo. - \b stepSize, Es una tabla de \f$k\f$ valores enteros, pueden ser negativos o incluso cero. Indica el número de coordenadas que avanzamos en cada dimensión cuando generamos los subpatrones. Su valor por defecto es \f$\{1,\ldots{},1\}\f$. Evidentemente, en aquellas coordenadas donde \c numSteps sea 1, no se utiliza el valor correspondiente de \c stepSize, así que da igual el valor que le demos en esas coordenadas. Existen muchas formas de recorrer una matriz, pero hay dos muy habituales denominadas modo \emph{particionamiento} (denominado también teselación o ``tiling'') y el modo \emph{desplazamiento} (o ``shifting''). Para crear un dataset que recorra la matriz en modo particionamiento basta con poner el valor \nom{stepSize} igual a \nom{patternSize} en aquellas coordenadas donde \nom{patternSize} sea inferior al número de elementos en esa dimensión, y poner 1 en las restantes. - \b orderStep, Indica el orden en que se utilizan las \f$k\f$ coordenadas de la matriz para recorrer todos los subpatrones que se van a generar. Su valor por defecto es \f$k-1,k-2,\ldots{},2,1,0\f$ que corresponde a recorrer una matriz bidimensional por filas. Variando este campo se puede lograr un recorrido por columnas, por ejemplo. - \b defaultValue, Es un valor numérico (no necesariamente entero) que se utiliza para rellenar un patrón en aquellas zonas que se salen de los límites de la matriz por cualquiera de sus extremos. Su valor por defecto es 0. - \b circular, Es una tabla de \f$k\f$ valores \emph{booleanos} (en \nom{Lua} existen los literales \lstinline{true} y \lstinline{false}) que indican, para cada coordenada de la matriz, si ésta es circular o no. Su valor por defecto es todo a \lstinline{false} (es decir, no circular). Cuando una coordenada no es circular, al salirnos fuera de la matriz nos encontraremos con el valor por defecto \nom{defaultValue}, mientras que si la coordenada sí es circular, en lugar de salirnos volveremos a la coordenada inicial. Por ejemplo, si creamos una matriz de dimensión 2 y hacemos circular una de las coordenadas, tendríamos algo similar a un cilindro sin tapas. Si hacemos las 2 coordenadas circulares tendríamos un toro (un donut). Veamos un ejemplo sencillo del uso de estos valores. Queremos generar los datasets para aprender la or exclusiva utilizando una sola matriz: \verbatim m_xor = matrix.fromString[[ 4 3 ascii 0 0 0 0 1 1 1 0 1 1 1 0 ]] ds_input = dataset.matrix(m_xor,{patternSize={1,2}}) ds_output = dataset.matrix(m_xor,{offset={0,2},patternSize={1,1}}) for i = 1,ds_input:numPatterns() do printf("Index %d -> Input: %s Output: %s\n",i, table.concat(ds_input:getPattern(i),","), table.concat(ds_output:getPattern(i),",")) end --[[ Salida: Index 1 -> Input: 0,0 Output: 0 Index 2 -> Input: 0,1 Output: 1 Index 3 -> Input: 1,0 Output: 1 Index 4 -> Input: 1,1 Output: 0 ]]-- \endverbatim Como esta forma de utilizar una matriz es tan general, podemos definir la siguiente funcion: \verbatim function dataset_pair(m,sizein,sizeout) local d_in = dataset.matrix(m,{patternSize = {1,sizein}}) local d_out = dataset.matrix(m,{offset={0,sizein},patternSize = {1,sizeout}}) return d_in,d_out end -- se puede utilizar así: ds_input,ds_output = dataset_pair(m_xor,2,1) \endverbatim \section dataset_union dataset.union Permite que varios datasets que tienen el mismo \c patternSize se vean como uno solo con un \c numPatterns igual al sumatorio de los \c numPatterns de los \c datasets que lo componen. Requiere un único argumento que es una tabla con los \c datasets necesarios. \section dataset_indexed dataset.indexed El formato indexado permite crear un mapping de indices a patterns. Puede ser útil para especificar la salida de una clasificación, en tal caso el \c dataset sobre el que se basa el \c dataset.indexed representa la salida asociada a cada una de las clases. Requiere 2 argumentos. El primero es el dataset base. El segundo es una tabla con tantos \c datasets como \c patternSize tenga el dataset base, cada uno de ellos actuará como diccionario. El \c patternSize del \c dataset.indexed resultante es igual a la suma de los \c patternSize de cada diccionario. \section dataset_slice dataset.slice Permite seleccionar un subconjunto de patterns de un dataset, este subconjunto debe ser un intervalo (para subconjuntos más generales se puede utilizar la clase \c dataset.index) Requiere 3 argumentos. El primero es el dataset y luego necesita 2 argumentos que son los indices inicial y final de los patrones que se eligen como subconjunto. \section dataset_split dataset.split Permite seleccionar un subconjunto de los elementos de salida de un dataset. Es decir, el dataset resultante tiene el mismo numero de patrones (\c numPatterns) pero un \c patternSize menor. El subconjunto de salida es un intervalo del original. \section dataset_linearcomb dataset.linearcomb Permite realizar una combinación lineal de los elementos de un \c dataset. Se trata de una forma mucho más general que el \c dataset.split anteriormente descrito puesto que, aunque de manera algo complicada, es posible simular un \c dataset.split mediante un \c dataset.linearcomb. Un \c dataset.linearcomb requiere dos argumentos: un \c dataset y una tabla. La tabla es un vector con tantas componentes como queramos que sea el \c patternSize del \c dataset.linearcomb resultante. Obsérvese que el \c numPatterns del dataset resultante será el mismo. Cada componente correspondiente a cada posición de los patrones generados por el \c dataset.linearcomb es una combinación lineal expresada como una lista de pares (índice,valor). El índice \f$0\f$ está reservado a la constante numérica \f$1\f$. Veamos mediante un ejemplo cómo se utiliza. Tenemos un dataset de \f$4\f$ patrones de tamaño \f$4\f$. Queremos generar otro dataset con \f$4\f$ patrones de tamaño \f$3\f$, donde cada uno de los 3 elementos del patrón es una combinación lineal del dataset de partida. La primera componente es el \f$1^{er}\f$ elemento del patrón original más dos veces el segundo elemento. La segunda componente es la constante numérica \f$5\f$ más dos veces el tercer elemento del patrón original. Por último, la tercera componente es la segunda componente del patrón original: \verbatim -- creamos una matriz m = matrix.fromString[[ 4 4 ascii 1 2 3 4 4 5 6 8 9 10 11 12 13 14 15 16 ]] d = dataset.matrix(m) - 4 patrones: cada fila de la matriz linearc = { -- 3 combinaciones lineales: { {1,1.0}, {2, 2.0} }, { {0,5.0} , {3, 2.0} }, -- 5.0 + 2*posicion_3 del patrón { {2,1.0} }, } dlc = dataset.linearcomb(d,linearc) print("dataset d:") for index,pattern in d:patterns() do print(index,string.join(pattern,",")) end print("dataset dlc:") for index,pattern in dlc:patterns() do print(index,string.join(pattern,",")) end --[[ La salida sería: dataset d: 1 1,2,3,4 2 4,5,6,8 3 9,10,11,12 4 13,14,15,16 dataset dlc: 1 5,11,2 2 14,17,5 3 29,27,10 4 41,35,14 ]] \endverbatim \section dataset_join dataset.join Permite juntar las salidas de varios dataset que tienen el mismo numero de patrones (\c numPatterns). El \c patternSize del dataset resultante es igual al sumatorio de los \c patternSize de los datasets que lo componen. Requiere un único argumento que es una tabla con los datasets necesarios. */ april-ann-0.4.1/packages/basics/dataset/doc/saveFileBinary.txt000066400000000000000000000033241263004425400242570ustar00rootroot00000000000000$ april-mlp Lua 5.1.4 Copyright (C) 1994-2008 Lua.org, PUC-Rio > a = dataset.identity(10) > a:saveFileBinary("pepito") > a:saveFileAscii("pepitoascii") I després en python: python Python 2.7.1+ (r271:86832, Apr 11 2011, 18:13:53) [GCC 4.5.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. > > > import numpy > > > a = numpy.fromfile("pepito",dtype=numpy.float32,count=-1,sep="") > > > a array([ 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.], dtype=float32) > > > len(a) 100 numpy.reshape(a,(len(a)/col,col)) array([[ 1., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0.], [ 0., 1., 0., 0., 0.], [ 0., 0., 0., 0., 0.], [ 0., 0., 1., 0., 0.], [ 0., 0., 0., 0., 0.], [ 0., 0., 0., 1., 0.], [ 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 1.], [ 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0.], [ 1., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0.], [ 0., 1., 0., 0., 0.], [ 0., 0., 0., 0., 0.], [ 0., 0., 1., 0., 0.], [ 0., 0., 0., 0., 0.], [ 0., 0., 0., 1., 0.], [ 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 1.]], dtype=float32) april-ann-0.4.1/packages/basics/dataset/lua_src/000077500000000000000000000000001263004425400214745ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/dataset/lua_src/dataset.lua000066400000000000000000000036431263004425400236320ustar00rootroot00000000000000function dataset.to_fann_file_format(input_dataset, output_dataset) local numpat = input_dataset:numPatterns() if (output_dataset:numPatterns() ~= numpat) then error("dataset.to_fann_file_format input and output dataset has different number of patterns") end local resul = {} table.insert(resul,string.format("%d %d %d",numpat, input_dataset:patternSize(), output_dataset:patternSize())) for i=1,numpat do table.insert(resul,table.concat(input_dataset:getPattern(i)," ")) table.insert(resul,table.concat(output_dataset:getPattern(i)," ")) end return table.concat(resul,"\n") end function dataset.create_fann_file(filename, input_dataset, output_dataset) local str = dataset.to_fann_file_format(input_dataset,output_dataset) local fich = io.open(filename,"w") fich:write(str) fich:close() end ----------------------------------------------------------------------------- local lua_filter,lua_filter_methods = class("dataset.token.lua_filter") get_table_from_dotted_string("dataset.token", true) -- global environment dataset.token.lua_filter = lua_filter -- global environment function lua_filter:constructor(t) local params = get_table_fields({ dataset = { mandatory=true }, filter = { mandatory=true, type_match="function" }, pattern_size = { type_match="number" }, }, t) self.ds=params.dataset self.filter=params.filter self.pattern_size=params.pattern_size or self.ds:patternSize() if class.is_a(ds,dataset) then self.ds = dataset.token_wrapper(self.ds) end end function lua_filter_methods:numPatterns() return self.ds:numPatterns() end function lua_filter_methods:patternSize() return self.pattern_size end function lua_filter_methods:getPattern(idx) return self.filter( self.ds:getPattern(idx) ) end function lua_filter_methods:getPatternBunch(idxs) return self.filter( self.ds:getPatternBunch(idxs) ) end april-ann-0.4.1/packages/basics/dataset/package.lua000066400000000000000000000023411263004425400221420ustar00rootroot00000000000000 package{ name = "dataset", version = "1.0", depends = { "util", "matrix", "random", "tokens", "functions" }, keywords = { "dataset" }, description = "no description available", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test.lua", }, }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, copy{ file= "c_src/dataset.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_dataset.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_dataset.lua.cc", dest_dir = "build", } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/dataset/test/000077500000000000000000000000001263004425400210235ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/dataset/test/ground_truth.png000066400000000000000000000003261263004425400242560ustar00rootroot00000000000000PNG  IHDR PXsRGB pHYs  tIME ֒tEXtCommentCreated with GIMPWCIDATӅOA L1]0$$qL"Rsׅ2)ܕf[Y3%mJ)*EIIENDB`april-ann-0.4.1/packages/basics/dataset/test/ground_truth.txt000066400000000000000000000000211263004425400243010ustar00rootroot00000000000000ground_truth.png april-ann-0.4.1/packages/basics/dataset/test/result.png000066400000000000000000000003311263004425400230440ustar00rootroot00000000000000PNG  IHDR PXsRGB pHYs  tIME %tEXtCommentCreated with GIMPWFIDATeI@ŚXIVe$Ջ(GCs gvsvc1$fTçh-;\IENDB`april-ann-0.4.1/packages/basics/dataset/test/result.txt000066400000000000000000000000131263004425400230740ustar00rootroot00000000000000result.png april-ann-0.4.1/packages/basics/dataset/test/test.lua000066400000000000000000000026751263004425400225170ustar00rootroot00000000000000local check = utest.check local T = utest.test T("SparseMatrixDataSet", function() local ds = dataset.token.sparse_matrix(matrix.sparse.diag{6,5,4,3,2,1}) check.eq( ds:getPattern(1), matrix.sparse(matrix(1, 6, { 6, 0, 0, 0, 0, 0 })) ) check.eq( ds:getPattern(2), matrix.sparse(matrix(1, 6, { 0, 5, 0, 0, 0, 0 })) ) check.eq( ds:getPattern(3), matrix.sparse(matrix(1, 6, { 0, 0, 4, 0, 0, 0 })) ) check.eq( ds:getPattern(4), matrix.sparse(matrix(1, 6, { 0, 0, 0, 3, 0, 0 })) ) check.eq( ds:getPattern(5), matrix.sparse(matrix(1, 6, { 0, 0, 0, 0, 2, 0 })) ) check.eq( ds:getPattern(6), matrix.sparse(matrix(1, 6, { 0, 0, 0, 0, 0, 1 })) ) check.eq( ds:getPatternBunch{6, 1, 3}, matrix.sparse(matrix(3, 6, { 0, 0, 0, 0, 0, 1, 6, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, })) ) local uds = dataset.token.union{ ds, ds } check.eq( uds:getPattern(4), matrix.sparse(matrix(1, 6, { 0, 0, 0, 3, 0, 0 })) ) check.eq( uds:getPattern(11), matrix.sparse(matrix(1, 6, { 0, 0, 0, 0, 2, 0 })) ) check.eq( uds:getPatternBunch{6, 7, 3}, matrix.sparse(matrix(3, 6, { 0, 0, 0, 0, 0, 1, 6, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, })) ) end) april-ann-0.4.1/packages/basics/dataset/test/test_bitdataset.lua000066400000000000000000000016371263004425400247200ustar00rootroot00000000000000numPatterns = 100 patternSize = 100 m = matrix(numPatterns, patternSize) ds = dataset.matrix(m) dsbit = dataset.bit{ patternSize = patternSize, numPatterns = numPatterns } rnd = random(1234) for i=1,numPatterns do t = {} for j=1,patternSize do v = rnd:randInt(0,1) t[j] = v end ds:putPattern(i, t) dsbit:putPattern(i, t) -- print(table.concat(t, " ")) end for i=1,numPatterns do local t1 = ds:getPattern(i) local t2 = dsbit:getPattern(i) for j=1,#t1 do if t1[j] ~= t2[j] then print(i, j, t1[j], t2[j]) error("ERROR") end end end print("Test1 OK!") --------------------------------------------------- dsbit = dataset.bit{ dataset = ds } for i=1,numPatterns do local t1 = ds:getPattern(i) local t2 = dsbit:getPattern(i) for j=1,#t1 do if t1[j] ~= t2[j] then print(i, j, t1[j], t2[j]) error("ERROR") end end end print("Test2 OK!") april-ann-0.4.1/packages/basics/dataset/test/test_dataset.lua000066400000000000000000000005161263004425400242140ustar00rootroot00000000000000print("Empieza el programa") m = matrix(10,{1,0,0,0,0,0,0,0,0,0}) print(m) ds = dataset.matrix(m,{patternSize={10}, offset={0}, numSteps={20}, stepSize={-1}, circular = {true}}) print(ds) -- for index,pattern in ds:patterns() do -- print(index,"{"..table.concat(pattern,",").."}") -- end print("Termina el programa") april-ann-0.4.1/packages/basics/dataset/test/test_dataset4.lua000066400000000000000000000023511263004425400242770ustar00rootroot00000000000000-- vamos a probar matrices 3 dimensionales -- matrix de talla 4x3x2 viene a ser 2 capas de: -- -- col1 col2 col3 -- fila1 -- fila2 -- fila3 -- fila4 mat = matrix(4,3,2) -- un dataset que recorre la matriz por capas de profundidad: ds = dataset.matrix(mat,{ patternSize={4,3,1}, offset={0,0,0}, stepSize={0,0,1}, numSteps={1,1,2}, }) ds:putPattern(1,{1,2,3,4,5,6,7,8,9,10,11,12}) -- primera capa: -- 1 2 3 -- 4 5 6 -- 7 8 9 -- 10 11 12 ds:putPattern(2,{13,14,15,16,17,18,19,20,21,22,23,24}) -- segunda capa: -- 13 14 15 -- 16 17 18 -- 19 20 21 -- 22 23 24 -- recorremos la matriz pero por filas dsfilas = dataset.matrix(mat,{ patternSize={1,3,2}, offset={0,0,0}, stepSize={1,0,0}, numSteps={4,1,1}, }) -- vamos a imprimir cada fila: for i,pat in dsfilas:patterns() do printf("Patron %d -> %s\n",i,table.concat(pat,",")) end -- salida que pensamos que deberia de dar: -- Patron 1 -> 1,13,2,14,3,15 -- Patron 2 -> 4,16,5,17,6,18 -- Patron 3 -> 7,19,8,20,9,21 -- Patron 4 -> 10,22,11,23,12,24 -- salida del programa -- Patron 1 -> 1,13,2,14,4,16 -- Patron 2 -> 4,16,5,17,7,19 -- Patron 3 -> 7,19,8,20,10,22 -- Patron 4 -> 10,22,11,23,12,24 <- curiosamente esta bien april-ann-0.4.1/packages/basics/dataset/test/test_dataset_2.lua000066400000000000000000000006421263004425400244350ustar00rootroot00000000000000print("empezamos") a = matrix(2,2,{1,2,3,4}) b = dataset.matrix(a) print("UNO",a,b) for i,j in b:patterns() do print(table.concat(j,",")) end a = matrix(2,2,2,{1,2,3,4,5,6,7,8}) b = dataset.matrix(a) print("DOS",a,b) for i,j in b:patterns() do print(table.concat(j,",")) end a = matrix(4,{1,2,3,4}) b = dataset.matrix(a) print("TRES",a,b) for i,j in b:patterns() do print(table.concat(j,",")) end print("finalizamos") april-ann-0.4.1/packages/basics/dataset/test/test_dataset_3.lua000066400000000000000000000015021263004425400244320ustar00rootroot00000000000000print("empezamos") m_xor = matrix.fromString[[ 4 3 ascii 0 0 0 0 1 1 1 0 1 1 1 0 ]] ds_input = dataset.matrix(m_xor,{patternSize={1,2}}) ds_output = dataset.matrix(m_xor,{offset={0,2},patternSize={1,1}}) for i = 1,ds_input:numPatterns() do printf("Index %d -> Input: %s Output: %s\n",i, table.concat(ds_input:getPattern(i),","), table.concat(ds_output:getPattern(i),",")) end function dataset_pair(m,sizein,sizeout) local d_in = dataset.matrix(m,{patternSize = {1,sizein}}) local d_out = dataset.matrix(m,{offset={0,sizein},patternSize = {1,sizeout}}) return d_in,d_out end ds_input,ds_output = dataset_pair(m_xor,2,1) for i = 1,ds_input:numPatterns() do printf("Index %d -> Input: %s Output: %s\n",i, table.concat(ds_input:getPattern(i),","), table.concat(ds_output:getPattern(i),",")) end print("finalizamos") april-ann-0.4.1/packages/basics/dataset/test/test_deriv.lua000066400000000000000000000005151263004425400236770ustar00rootroot00000000000000d = dataset.identity(10) print("Dataset original:") for i,j in d:patterns() do print(table.concat(j,",")) end p = dataset.deriv{ dataset = d, deriv0 = false; deriv1 = true; -- default value deriv2 = false; } print("Dataset con derivadas y aceleraciones:") for i,j in p:patterns() do print(table.concat(j,",")) end april-ann-0.4.1/packages/basics/dataset/test/test_fmeasure.lua000066400000000000000000000014751263004425400244030ustar00rootroot00000000000000result_images_filename=arg[1] target_images_filename=arg[2] result_images_ds = {} for line in io.lines(result_images_filename) do local m = ImageIO.read(line):to_grayscale():info() table.insert(result_images_ds, dataset.matrix(m,{ stepSize = {1, 1}, patternSize = {1, 1}, numSteps = {m:dim()[1], m:dim()[2]} })) end target_images_ds = {} for line in io.lines(target_images_filename) do local m = ImageIO.read(line):to_grayscale():info() table.insert(target_images_ds, dataset.matrix(m,{ stepSize = {1, 1}, patternSize = {1, 1}, numSteps = {m:dim()[1], m:dim()[2]} })) end fm, pr, rc = dataset.fmeasure{ result_dataset = dataset.union(result_images_ds), target_dataset = dataset.union(target_images_ds), } print(fm, pr, rc) april-ann-0.4.1/packages/basics/dataset/test/test_indexed.lua000066400000000000000000000016071263004425400242110ustar00rootroot00000000000000 id5 = dataset.identity(5) id10 = dataset.identity(10) dsBase = dataset.matrix(matrix(3,2,{1,4, 2,2, 5,10})) print("Base dataset") for ipat,pat in dsBase:patterns() do print(ipat,table.concat(pat,",")) end -- patternSize of dsBase is 2, so there are 2 datasets used as -- dictionaries in the second argument: dsIndexed = dataset.indexed(dsBase, {id5,id10}) print("Indexed dataset") for ipat,pat in dsIndexed:patterns() do print(ipat,table.concat(pat,",")) end -- The output is: -- Base dataset -- 1 1,4 -- 2 2,2 -- 3 5,10 -- Indexed dataset -- 1 1,0,0,0,0,0,0,0,1,0,0,0,0,0,0 -- 2 0,1,0,0,0,0,1,0,0,0,0,0,0,0,0 -- 3 0,0,0,0,1,0,0,0,0,0,0,0,0,0,1 -- Observe the indexed dataset if we artificially separate its -- patterns in two blocks of sizes 5 and 10: -- Indexed dataset -- 1 1,0,0,0,0, 0,0,0,1,0,0,0,0,0,0 -- 2 0,1,0,0,0, 0,1,0,0,0,0,0,0,0,0 -- 3 0,0,0,0,1, 0,0,0,0,0,0,0,0,0,1 april-ann-0.4.1/packages/basics/dataset/test/test_linear_comb.lua000066400000000000000000000024261263004425400250430ustar00rootroot00000000000000 -- This test illustrates how to use a dataset.linearcomb -- first, we have to create a dataset.linear_comb_conf -- which receives a vector of tables -- (one table per output of the final dataset). -- Each table contains a list of tuples (index,weight). -- Let us create a dataset with 2 patterns of size 3: ds = dataset.matrix(matrix(2,3, {1,2,3, 4,5,6})) -- now, we create a dataset.linear_comb_conf to linearly combine -- patterns of size 3 into patterns of size 2 so that: -- the first one is 0.5 + 8*pattern(1) + 10*pattern(3) -- the second one is -1 + pattern(2) + 5*pattern(3) dlc = dataset.linear_comb_conf{ -- first output pattern: { {0,0.5},{1,8},{3,10} }, -- second output pattern: { {0,-1},{2,1},{3,5} }, } -- finally, we apply "dlc" to obtain a dataset.linearcomb from ds: resul = dataset.linearcomb(ds,dlc) print("Original dataset") for ipat,pat in ds:patterns() do print(ipat,table.concat(pat,",")) end print("Linear combination dataset") for ipat,pat in resul:patterns() do print(ipat,table.concat(pat,",")) end -- The output is as follows: -- Original dataset -- 1 1,2,3 -- 2 4,5,6 -- Linear combination dataset -- 1 38.5,16 -- 2 92.5,34 -- Observe that -- 38.5 = 0.5+8*1+10*3 -- 16 = -1 + 2 + 5*3 -- 92.5 = 0.5+8*4+10*6 -- 34 = -1 + 5 + 5*6 april-ann-0.4.1/packages/basics/dataset/test/test_perturbation.lua000066400000000000000000000006061263004425400253050ustar00rootroot00000000000000d = dataset.identity(5) print("Dataset sin perturbar:") for i,j in d:patterns() do print(table.concat(j,",")) end p = dataset.perturbation{ dataset = d, random = random(123), mean = 0, -- de la gaussiana variance = 0.1, -- de la gaussiana } for veces = 1,4 do print("Dataset perturbado:") for i,j in p:patterns() do print(table.concat(j,",")) end end april-ann-0.4.1/packages/basics/ee5_base64/000077500000000000000000000000001263004425400202415ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/ee5_base64/lua_src/000077500000000000000000000000001263004425400216715ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/ee5_base64/lua_src/ee5_base64.lua000066400000000000000000000531001263004425400242150ustar00rootroot00000000000000--[[**************************************************************************]] -- base64.lua -- Copyright 2014 Ernest R. Ewert -- -- This Lua module contains the implementation of a Lua base64 encode -- and decode library. -- -- The library exposes these methods. -- -- Method Args -- ----------- ---------------------------------------------- -- encode String in / out -- decode String in / out -- -- encode String, function(value) predicate -- decode String, function(value) predicate -- -- encode file, function(value) predicate -- deocde file, function(value) predicate -- -- encode file, file -- deocde file, file -- -- alpha alphabet, term char -- if package.loaded["ee5_base64"] then local ee5_base64 = require "ee5_base64" _G.ee5_base64 = ee5_base64 return ee5_base64 end -------------------------------------------------------------------------------- -- known_base64_alphabets -- -- local known_base64_alphabets= { base64= -- RFC 2045 (Ignores max line length restrictions) { _alpha="ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/", _strip="[^%a%d%+%/%=]", _term="=" }, base64noterm= -- RFC 2045 (Ignores max line length restrictions) { _alpha="ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/", _strip="[^%a%d%+%/]", _term="" }, base64url= -- RFC 4648 'base64url' { _alpha="ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789-_", _strip="[^%a%d%+%-%_=]", _term="" }, } local c_alpha=known_base64_alphabets.base64 local pattern_strip --[[**************************************************************************]] --[[****************************** Encoding **********************************]] --[[**************************************************************************]] -------------------------------------------------------------------------------- -- base64 encoding table -- -- Each (zero based, six bit) index is matched against the ASCII -- value that represents the six bit pattern. -- -- [6 bit encoding]=ASCII value -- -- This table varies from normal Lua one based indexing to avoid -- extra math during the fix-ups. This is a performance improvement -- for very long encoding runs. -- local b64e= { [ 0]= 65, [ 1]= 66, [ 2]= 67, [ 3]= 68, [ 4]= 69, [ 5]= 70, [ 6]= 71, [ 7]= 72, [ 8]= 73, [ 9]= 74, [10]= 75, [11]= 76, [12]= 77, [13]= 78, [14]= 79, [15]= 80, [16]= 81, [17]= 82, [18]= 83, [19]= 84, [20]= 85, [21]= 86, [22]= 87, [23]= 88, [24]= 89, [25]= 90, [26]= 97, [27]= 98, [28]= 99, [29]=100, [30]=101, [31]=102, [32]=103, [33]=104, [34]=105, [35]=106, [36]=107, [37]=108, [38]=109, [39]=110, [40]=111, [41]=112, [42]=113, [43]=114, [44]=115, [45]=116, [46]=117, [47]=118, [48]=119, [49]=120, [50]=121, [51]=122, [52]= 48, [53]= 49, [54]= 50, [55]= 51, [56]= 52, [57]= 53, [58]= 54, [59]= 55, [60]= 56, [61]= 57, [62]= 43, [63]= 47 } -- Precomputed tables (compromise using more memory for speed) local b64e_a -- ready to use local b64e_a2 -- byte addend local b64e_b1 -- byte addend local b64e_b2 -- byte addend local b64e_c1 -- byte addend local b64e_c -- ready to use -- Tail padding values local tail_padd64= { "==", -- two bytes modulo "=" -- one byte modulo } -------------------------------------------------------------------------------- -- m64 -- -- Helper function to convert three eight bit values into four encoded -- 6 (significant) bit values. -- -- 7 0 7 0 7 0 -- m64(a a a a a a a a,b b b b b b b b,c c c c c c c c) -- | | | | -- return [ a a a a a a]| | | -- [ a a b b b b]| | -- [ b b b b c c]| -- [ c c c c c c] -- local ext = bit32.extract -- slight speed, vast visual (IMO) local function m64( a, b, c ) -- Return pre-calculated values for encoded value 1 and 4 -- Get the pre-calculated extractions for value 2 and 3, look them -- up and return the proper value. -- return b64e_a[a], b64e[ b64e_a2[a]+b64e_b1[b] ], b64e[ b64e_b2[b]+b64e_c1[c] ], b64e_c[c] end -------------------------------------------------------------------------------- -- encode_tail64 -- -- Send a tail pad value to the output predicate provided. -- local function encode_tail64( out, x, y ) -- If we have a number of input bytes that isn't exactly divisible -- by 3 then we need to pad the tail if x ~= nil then local a,b,r = x,0,1 if y ~= nil then r = 2 b = y end -- Encode three bytes of info, with the tail byte as zeros and -- ignore any fourth encoded ASCII value. (We should NOT have a -- forth byte at this point.) local b1, b2, b3 = m64( a, b, 0 ) -- always add the first 2 six bit values to the res table -- 1 remainder input byte needs 8 output bits local tail_value = string.char( b1, b2 ) -- two remainder input bytes will need 18 output bits (2 as pad) if r == 2 then tail_value=tail_value..string.char( b3 ) end -- send the last 4 byte sequence with appropriate tail padding out( tail_value .. tail_padd64[r] ) end end -------------------------------------------------------------------------------- -- encode64_io_iterator -- -- Create an io input iterator to read an input file and split values for -- proper encoding. -- local function encode64_io_iterator(file) assert( io.type(file) == "file" or class.is_a(file,aprilio.stream), "argument must be readable file handle" ) assert( file.read ~= nil, "argument must be readable file handle" ) local ii = { } -- Table for the input iterator setmetatable(ii,{ __tostring=function() return "base64.io_iterator" end}) -- Begin returns an input read iterator -- function ii.begin() local sb = string.byte -- The iterator returns three bytes from the file for encoding or nil -- when the end of the file has been reached. -- return function() s = file:read(3) if s ~= nil and #s == 3 then return sb(s,1,3) end return nil end end -- The tail method on the iterator allows the routines to run faster -- because each sequence of bytes doesn't have to test for EOF. -- function ii.tail() -- If one or two "overflow" bytes exist, return those. -- if s ~= nil then return s:byte(1,2) end end return ii end -------------------------------------------------------------------------------- -- encode64_with_ii -- -- Convert the value provided by an encode iterator that provides a begin -- method, a tail method, and an iterator that returns three bytes for -- each call until at the end. The tail method should return either 1 or 2 -- tail bytes (for source values that are not evenly divisible by three). -- local function encode64_with_ii( ii, out ) local sc=string.char for a, b, c in ii.begin() do out( sc( m64( a, b, c ) ) ) end encode_tail64( out, ii.tail() ) end -------------------------------------------------------------------------------- -- encode64_with_predicate -- -- Implements the basic raw data --> base64 conversion. Each three byte -- sequence in the input string is converted to the encoded string and -- given to the predicate provided in 4 output byte chunks. This method -- is slightly faster for traversing existing strings in memory. -- local function encode64_with_predicate( raw, out ) local rem=#raw%3 -- remainder local len=#raw-rem -- 3 byte input adjusted local sb=string.byte -- Mostly notational (slight performance) local sc=string.char -- Mostly notational (slight performance) -- Main encode loop converts three input bytes to 4 base64 encoded -- ACSII values and calls the predicate with the value. for i=1,len,3 do -- This really isn't intended as obfuscation. It is more about -- loop optimization and removing temporaries. -- out( sc( m64( sb( raw ,i , i+3 ) ) ) ) -- | | | -- | | byte i to i + 3 -- | | -- | returns 4 encoded values -- | -- creates a string with the 4 returned values end -- If we have a number of input bytes that isn't exactly divisible -- by 3 then we need to pad the tail if rem > 0 then local x, y = sb( raw, len+1 ) if rem > 1 then y = sb( raw, len+2 ) end encode_tail64( out, x, y ) end end -------------------------------------------------------------------------------- -- encode64_tostring -- -- Convenience method that accepts a string value and returns the -- encoded version of that string. -- local function encode64_tostring(raw) local sb={} -- table to build string local function collection_predicate(v) sb[#sb+1]=v end -- Test with an 818K string in memory. Result is 1.1M of data. -- -- lua_base64 base64 (gnu 8.21) -- 202ms 54ms -- 203ms 48ms -- 204ms 50ms -- 203ms 42ms -- 205ms 46ms -- encode64_with_predicate( raw, collection_predicate ) return table.concat(sb) end --[[**************************************************************************]] --[[****************************** Decoding **********************************]] --[[**************************************************************************]] -------------------------------------------------------------------------------- -- base64 decoding table -- -- Each ASCII encoded value index is matched against the zero based, six bit -- bit pattern. -- -- [ASCII value]=6 bit encoding value -- local b64d= { [ 65]= 0, [ 66]= 1, [ 67]= 2, [ 68]= 3, [ 69]= 4, [ 70]= 5, [ 71]= 6, [ 72]= 7, [ 73]= 8, [ 74]= 9, [ 75]=10, [ 76]=11, [ 77]=12, [ 78]=13, [ 79]=14, [ 80]=15, [ 81]=16, [ 82]=17, [ 83]=18, [ 84]=19, [ 85]=20, [ 86]=21, [ 87]=22, [ 88]=23, [ 89]=24, [ 90]=25, [ 97]=26, [ 98]=27, [ 99]=28, [100]=29, [101]=30, [102]=31, [103]=32, [104]=33, [105]=34, [106]=35, [107]=36, [108]=37, [109]=38, [110]=39, [111]=40, [112]=41, [113]=42, [114]=43, [115]=44, [116]=45, [117]=46, [118]=47, [119]=48, [120]=49, [121]=50, [122]=51, [ 48]=52, [ 49]=53, [ 50]=54, [ 51]=55, [ 52]=56, [ 53]=57, [ 54]=58, [ 55]=59, [ 56]=60, [ 57]=61, [ 43]=62, [ 47]=63 } -- Precomputed tables (compromise using more memory for speed) local b64d_a1 -- byte addend local b64d_a2 -- byte addend local b64d_b1 -- byte addend local b64d_b2 -- byte addend local b64d_c1 -- byte addend -------------------------------------------------------------------------------- -- u64 -- -- Helper function to convert four six bit values into three full eight -- bit values. Input values are the integer expression of the six bit value -- encoded in the original base64 encoded string. -- -- u64( _ _1 1 1 1 1 1, -- | _ _ 2 2 2 2 2 2, -- | | _ _ 3 3 3 3 3 3, -- | | | _ _ 4 4 4 4 4 4) -- | | | | -- return ', [1 1 1 1 1 1 2 2] | | -- ', [2 2 2 2 3 3 3 3] | -- ' [3 3 4 4 4 4 4 4] -- local function u64( b1, b2, b3, b4 ) -- We can get away with addition instead of anding the values together -- because there are no overlapping bit patterns. -- return b64d_a1[b1] + b64d_a2[b2], b64d_b1[b2] + b64d_b2[b3], b64d_c1[b3] + b64d[b4] end -------------------------------------------------------------------------------- -- decode_tail64 -- -- Send the end of stream bytes that didn't get decoded via the main loop. -- local function decode_tail64( out, e1, e2 ,e3, e4 ) if tail_padd64[2] == "" or e4 == tail_padd64[2]:byte() then local n3 = b64e[0] if e3 ~= nil and e3 ~= tail_padd64[2]:byte() then n3 = e3 end -- Unpack the six bit values into the 8 bit values local b1, b2 = u64( e1, e2, n3, b64e[0] ) -- And add them to the res table if e3 ~= nil and e3 ~= tail_padd64[2]:byte() then out( string.char( b1, b2 ) ) else out( string.char( b1 ) ) end end end -------------------------------------------------------------------------------- -- decode64_io_iterator -- -- Create an io input iterator to read an input file and split values for -- proper decoding. -- local function decode64_io_iterator( file ) local ii = { } -- An enumeration coroutine that handles the reading of an input file -- to break data into proper pieces for building the original string. -- local function enummerate( file ) local sc=string.char local sb=string.byte local ll="" -- last line storage local len -- Read a "reasonable amount" of data into the line buffer. Line by -- line is not used so that a file with no line breaks doesn't -- cause an inordinate amount of memory usage. -- for cl in file:lines(2048) do -- Reset the current line to contain valid chars and any previous -- "leftover" bytes from the previous read -- cl = ll .. cl:gsub(pattern_strip,"") -- | | -- | Remove "Invalid" chars (white space etc) -- | -- Left over from last line -- len = (#cl-4)-(#cl%4) -- see the comments in decode64_with_predicate for a rundown of -- the results of this loop (sans the coroutine) for i=1,len,4 do coroutine.yield ( sc( u64( sb( cl, i, i+4 ) ) ) ) end ll = cl:sub( len +1, #cl ) end local l = #ll if l >= 4 and ll:sub(-1) ~= tail_padd64[2] then coroutine.yield ( sc( u64( sb( ll, 1, 4 ) ) ) ) l=l-4 end if l > 0 then local e1,e2,e3,e4 = ll:byte( 0 - l, -1 ) if e1 ~= nil then decode_tail64( function(s) coroutine.yield( s ) end, e1, e2, e3, e4 ) end end end -- Returns an input iterator that is implemented as a coroutine. Each -- yield of the co-routine sends reconstructed bytes to the lopp handling -- the iteration. -- function ii.begin() local co = coroutine.create( function() enummerate(file) end ) return function() local code,res = coroutine.resume(co) assert(code == true) return res end end return ii end -------------------------------------------------------------------------------- -- decode64_with_ii -- -- Convert the value provided by a decode iterator that provides a begin -- method, a tail method, and an iterator that returns four (usable!) bytes -- for each call until at the end. -- local function decode64_with_ii( ii, out ) -- Uses the iterator to pull values. Each reconstructed string -- is sent to the output predicate. -- for l in ii.begin() do out( l ) end end -------------------------------------------------------------------------------- -- decode64_with_predicate -- -- Decode an entire base64 encoded string in memory using the predicate for -- output. -- local function decode64_with_predicate( raw, out ) -- Sanitize the input to strip characters that are not in the alphabet. -- -- Note: This is a deviation from strict implementations where "bad data" -- in the input stream is unsupported. -- local san = raw:gsub(pattern_strip,"") local len = #san-#san%4 -- local rem = #san-len local sc = string.char local sb = string.byte if san:sub(-1,-1) == tail_padd64[2] then rem = rem + 4 len = len - 4 end for i=1,len,4 do out( sc( u64( sb( san, i, i+4 ) ) ) ) end if rem > 0 then decode_tail64( out, sb( san, 0-rem, -1 ) ) end end -------------------------------------------------------------------------------- -- decode64_tostring -- -- Takes a string that is encoded in base64 and returns the decoded value in -- a new string. -- local function decode64_tostring( raw ) local sb={} -- table to build string local function collection_predicate(v) sb[#sb+1]=v end decode64_with_predicate( raw, collection_predicate ) return table.concat(sb) end -------------------------------------------------------------------------------- -- set_and_get_alphabet -- -- Sets and returns the encode / decode alphabet. -- -- local function set_and_get_alphabet(alpha,term) if alpha ~= nil then local magic= { -- ["%"]="%%", [" "]="% ", ["^"]="%^", ["$"]="%$", ["("]="%(", [")"]="%)", ["."]="%.", ["["]="%[", ["]"]="%]", ["*"]="%*", ["+"]="%+", ["-"]="%-", ["?"]="%?", } c_alpha=known_base64_alphabets[alpha] if c_alpha == nil then c_alpha={ _alpha=alpha, _term=term } end assert( #c_alpha._alpha == 64, "The alphabet ~must~ be 64 unique values." ) assert( #c_alpha._term <= 1, "Specify zero or one termination character.") b64d={} b64e={} local s="" for i = 1,64 do local byte = c_alpha._alpha:byte(i) local str = string.char(byte) b64e[i-1]=byte assert( b64d[byte] == nil, "Duplicate value '"..str.."'" ) b64d[byte]=i-1 s=s..str end -- preload encode lookup tables b64e_a = {} b64e_a2 = {} b64e_b1 = {} b64e_b2 = {} b64e_c1 = {} b64e_c = {} for f = 0,255 do b64e_a [f]=b64e[ext(f,2,6)] b64e_a2 [f]=ext(f,0,2)*16 b64e_b1 [f]=ext(f,4,4) b64e_b2 [f]=ext(f,0,4)*4 b64e_c1 [f]=ext(f,6,2) b64e_c [f]=b64e[ext(f,0,6)] end -- preload decode lookup tables b64d_a1 = {} b64d_a2 = {} b64d_b1 = {} b64d_b2 = {} b64d_c1 = {} for k,v in pairs(b64d) do -- Each comment shows the rough C expression that would be used to -- generate the returned triple. -- b64d_a1 [k] = v*4 -- ([b1] ) << 2 b64d_a2 [k] = math.floor( v / 16 ) -- ([b2] & 0x30) >> 4 b64d_b1 [k] = ext( v, 0, 4 ) * 16 -- ([b2] & 0x0F) << 4 b64d_b2 [k] = math.floor( v / 4 ) -- ([b3] & 0x3c) >> 2 b64d_c1 [k] = ext( v, 0, 2 ) * 64 -- ([b3] & 0x03) << 6 end if c_alpha._term ~= "" then tail_padd64[1]=string.char(c_alpha._term:byte(),c_alpha._term:byte()) tail_padd64[2]=string.char(c_alpha._term:byte()) else tail_padd64[1]="" tail_padd64[2]="" end local esc_term if magic[c_alpha._term] ~= nil then esc_term=c_alpha._term:gsub(magic[c_alpha._term],function (s) return magic[s] end) elseif c_alpha._term == "%" then esc_term = "%%" else esc_term=c_alpha._term end if not c_alpha._strip then local p=s:gsub("%%",function (s) return "__unique__" end) for k,v in pairs(magic) do p=p:gsub(v,function (s) return magic[s] end ) end local mr=p:gsub("__unique__",function() return "%%" end) c_alpha._strip = string.format("[^%s%s]",mr,esc_term) end assert( c_alpha._strip ) pattern_strip = c_alpha._strip local c =0 for i in pairs(b64d) do c=c+1 end assert( c_alpha._alpha == s, "Integrity error." ) assert( c == 64, "The alphabet must be 64 unique values." ) if esc_term ~= "" then assert( not c_alpha._alpha:find(esc_term), "Tail characters must not exist in alphabet." ) end if known_base64_alphabets[alpha] == nil then known_base64_alphabets[alpha]=c_alpha end end return c_alpha._alpha,c_alpha._term end -------------------------------------------------------------------------------- -- encode64 -- -- Entry point mode selector. -- -- local function encode64(i,o) local method if o ~= nil and (io.type(o) == "file" or class.is_a(o,aprilio.stream)) then local file_out = o o = function(s) file_out:write(s) end end if type(i) == "string" then if type(o) == "function" then method = encode64_with_predicate else assert( o == nil, "unsupported request") method = encode64_tostring end elseif io.type(i) == "file" or class.is_a(i,aprilio.string) then assert( type(o) == "function", "file source requires output predicate") i = encode64_io_iterator(i) method = encode64_with_ii else assert( false, "unsupported mode" ) end return method(i,o) end -------------------------------------------------------------------------------- -- decode64 -- -- Entry point mode selector. -- -- local function decode64(i,o) local method if o ~= nil and (io.type(o) == "file" or class.is_a(o,aprilio.stream)) then local file_out = o o = function(s) file_out:write(s) end end if type(i) == "string" then if type(o) == "function" then method = decode64_with_predicate else assert( o == nil, "unsupported request") method = decode64_tostring end elseif io.type(i) == "file" or class.is_a(i,aprilio.stream) then assert( type(o) == "function", "file source requires output predicate") i = decode64_io_iterator(i) method = decode64_with_ii else assert( false, "unsupported mode" ) end return method(i,o) end set_and_get_alphabet("base64") --[[**************************************************************************]] --[[****************************** Module **********************************]] --[[**************************************************************************]] local ee5_base64 = { encode = encode64, decode = decode64, alpha = set_and_get_alphabet, } package.loaded["ee5_base64"] = ee5_base64 _G.ee5_base64 = ee5_base64 return ee5_base64 april-ann-0.4.1/packages/basics/ee5_base64/package.lua000066400000000000000000000024351263004425400223430ustar00rootroot00000000000000 package{ name = "ee5_base64", version = "1.0", depends = { "aprilio" }, keywords = { "base64" }, description = "base64 encoder/decoder", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, -- target{ -- name = "test", -- lua_unit_test{ -- file={ -- "test/test_april_io.lua", -- }, -- }, -- c_unit_test{ -- file = { "test/test_april_io.cc" }, -- }, -- }, target{ name = "provide", depends = "init", -- copy{ file= "c_src/*.h", dest_dir = "include" }, -- provide_bind{ file = "binding/bind_april_io.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, -- object{ -- file = "c_src/*.cc", -- include_dirs = "${include_dirs}", -- dest_dir = "build", -- }, luac{ orig_dir = "lua_src", dest_dir = "build", }, -- build_bind{ -- file = "binding/bind_april_io.lua.cc", -- dest_dir = "build", -- } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/field_manager/000077500000000000000000000000001263004425400211745ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/field_manager/lua_src/000077500000000000000000000000001263004425400226245ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/field_manager/lua_src/field_manager.lua000066400000000000000000000046421263004425400261120ustar00rootroot00000000000000-- wrapper para field_manager local field_manager,field_manager_methods = class("field_manager") _G.field_manager = field_manager -- constructor function field_manager:constructor() self.fields = {} end -- devuelve un campo del field_manager function field_manager_methods:get_field(name) return self.fields[name] end -- function field_manager_methods:load_lines(s) if type(s) ~= 'table' or type(s.filename) ~= 'string' or type(s.field) ~= 'string' then error("Error in field_manager load_lines method incorrect arguments\n") end local aux = {} for line in io.lines(s.filename) do table.insert(aux, line) end self.fields[s.field] = aux end -- function field_manager_methods:apply(s) -- comprobar argumentos if type(s) ~= 'table' or type(s.output_fields)~= 'table' or type(s.input_fields) ~= 'table' or type(s.the_function) ~= 'function' then error("Error in field_manager apply method incorrect arguments\n") end -- comprobar que el campo input_fields tiene al menos un campo local num_fields = table.getn(s.input_fields) if num_fields == 0 then error("Error in field_manager apply method at least one input field is needed\n") end -- comprobar que todos los campos de input_fields son adecuados for i,fieldname in ipairs(s.input_fields) do if type(self.fields[fieldname]) ~= 'table' then error(string.format("Error in field_manager apply method ".. "data_field %s not found incorrect arguments\n",fieldname)) end end local num_results = table.getn(s.output_fields) -- crear las tablas de resultados si hace falta: for j=1,num_results do if self.fields[s.output_fields[j]] == nil then self.fields[s.output_fields[j]] = {} end end -- iterar sobre los datos local size_data = table.getn(self.fields[s.input_fields[1]]) for i = 1,size_data do -- aplicar funcion al dato i-esimo local argumentos = {} for j=1,num_fields do table.insert(argumentos,self.fields[s.input_fields[j]][i]) end table.insert(argumentos,i) local resul = {s.the_function(table.unpack(argumentos))} if table.getn(resul) ~= num_results then error(string.format("Error in field_manager apply method at index %d",i)) end -- meter los datos for j=1,num_results do self.fields[s.output_fields[j]][i] = resul[j] end end end function field_manager_methods:delete_field(fieldname) self.fields[fieldname] = nil end april-ann-0.4.1/packages/basics/field_manager/package.lua000066400000000000000000000017271263004425400233010ustar00rootroot00000000000000package{ name = "field_manager", version = "1.0", depends = { }, keywords = { }, description = "", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, -- provide_bind{ file = "binding/bind_util.lua.cc" , dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", dest_dir = "build", -- flags = "-std=c99", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, -- build_bind{ file = "binding/bind_util.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/gtest/000077500000000000000000000000001263004425400175455ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/gtest/c_src/000077500000000000000000000000001263004425400206365ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/gtest/c_src/gtest-all.cc000066400000000000000000012640621263004425400230540ustar00rootroot00000000000000// Copyright 2008, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: mheule@google.com (Markus Heule) // // Google C++ Testing Framework (Google Test) // // Sometimes it's desirable to build Google Test by compiling a single file. // This file serves this purpose. // This line ensures that gtest.h can be compiled on its own, even // when it's fused. #include "gtest.h" // The following lines pull in the real gtest *.cc files. // Copyright 2005, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: wan@google.com (Zhanyong Wan) // // The Google C++ Testing Framework (Google Test) // Copyright 2007, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: wan@google.com (Zhanyong Wan) // // Utilities for testing Google Test itself and code that uses Google Test // (e.g. frameworks built on top of Google Test). #ifndef GTEST_INCLUDE_GTEST_GTEST_SPI_H_ #define GTEST_INCLUDE_GTEST_GTEST_SPI_H_ namespace testing { // This helper class can be used to mock out Google Test failure reporting // so that we can test Google Test or code that builds on Google Test. // // An object of this class appends a TestPartResult object to the // TestPartResultArray object given in the constructor whenever a Google Test // failure is reported. It can either intercept only failures that are // generated in the same thread that created this object or it can intercept // all generated failures. The scope of this mock object can be controlled with // the second argument to the two arguments constructor. class GTEST_API_ ScopedFakeTestPartResultReporter : public TestPartResultReporterInterface { public: // The two possible mocking modes of this object. enum InterceptMode { INTERCEPT_ONLY_CURRENT_THREAD, // Intercepts only thread local failures. INTERCEPT_ALL_THREADS // Intercepts all failures. }; // The c'tor sets this object as the test part result reporter used // by Google Test. The 'result' parameter specifies where to report the // results. This reporter will only catch failures generated in the current // thread. DEPRECATED explicit ScopedFakeTestPartResultReporter(TestPartResultArray* result); // Same as above, but you can choose the interception scope of this object. ScopedFakeTestPartResultReporter(InterceptMode intercept_mode, TestPartResultArray* result); // The d'tor restores the previous test part result reporter. virtual ~ScopedFakeTestPartResultReporter(); // Appends the TestPartResult object to the TestPartResultArray // received in the constructor. // // This method is from the TestPartResultReporterInterface // interface. virtual void ReportTestPartResult(const TestPartResult& result); private: void Init(); const InterceptMode intercept_mode_; TestPartResultReporterInterface* old_reporter_; TestPartResultArray* const result_; GTEST_DISALLOW_COPY_AND_ASSIGN_(ScopedFakeTestPartResultReporter); }; namespace internal { // A helper class for implementing EXPECT_FATAL_FAILURE() and // EXPECT_NONFATAL_FAILURE(). Its destructor verifies that the given // TestPartResultArray contains exactly one failure that has the given // type and contains the given substring. If that's not the case, a // non-fatal failure will be generated. class GTEST_API_ SingleFailureChecker { public: // The constructor remembers the arguments. SingleFailureChecker(const TestPartResultArray* results, TestPartResult::Type type, const string& substr); ~SingleFailureChecker(); private: const TestPartResultArray* const results_; const TestPartResult::Type type_; const string substr_; GTEST_DISALLOW_COPY_AND_ASSIGN_(SingleFailureChecker); }; } // namespace internal } // namespace testing // A set of macros for testing Google Test assertions or code that's expected // to generate Google Test fatal failures. It verifies that the given // statement will cause exactly one fatal Google Test failure with 'substr' // being part of the failure message. // // There are two different versions of this macro. EXPECT_FATAL_FAILURE only // affects and considers failures generated in the current thread and // EXPECT_FATAL_FAILURE_ON_ALL_THREADS does the same but for all threads. // // The verification of the assertion is done correctly even when the statement // throws an exception or aborts the current function. // // Known restrictions: // - 'statement' cannot reference local non-static variables or // non-static members of the current object. // - 'statement' cannot return a value. // - You cannot stream a failure message to this macro. // // Note that even though the implementations of the following two // macros are much alike, we cannot refactor them to use a common // helper macro, due to some peculiarity in how the preprocessor // works. The AcceptsMacroThatExpandsToUnprotectedComma test in // gtest_unittest.cc will fail to compile if we do that. #define EXPECT_FATAL_FAILURE(statement, substr) \ do { \ class GTestExpectFatalFailureHelper {\ public:\ static void Execute() { statement; }\ };\ ::testing::TestPartResultArray gtest_failures;\ ::testing::internal::SingleFailureChecker gtest_checker(\ >est_failures, ::testing::TestPartResult::kFatalFailure, (substr));\ {\ ::testing::ScopedFakeTestPartResultReporter gtest_reporter(\ ::testing::ScopedFakeTestPartResultReporter:: \ INTERCEPT_ONLY_CURRENT_THREAD, >est_failures);\ GTestExpectFatalFailureHelper::Execute();\ }\ } while (::testing::internal::AlwaysFalse()) #define EXPECT_FATAL_FAILURE_ON_ALL_THREADS(statement, substr) \ do { \ class GTestExpectFatalFailureHelper {\ public:\ static void Execute() { statement; }\ };\ ::testing::TestPartResultArray gtest_failures;\ ::testing::internal::SingleFailureChecker gtest_checker(\ >est_failures, ::testing::TestPartResult::kFatalFailure, (substr));\ {\ ::testing::ScopedFakeTestPartResultReporter gtest_reporter(\ ::testing::ScopedFakeTestPartResultReporter:: \ INTERCEPT_ALL_THREADS, >est_failures);\ GTestExpectFatalFailureHelper::Execute();\ }\ } while (::testing::internal::AlwaysFalse()) // A macro for testing Google Test assertions or code that's expected to // generate Google Test non-fatal failures. It asserts that the given // statement will cause exactly one non-fatal Google Test failure with 'substr' // being part of the failure message. // // There are two different versions of this macro. EXPECT_NONFATAL_FAILURE only // affects and considers failures generated in the current thread and // EXPECT_NONFATAL_FAILURE_ON_ALL_THREADS does the same but for all threads. // // 'statement' is allowed to reference local variables and members of // the current object. // // The verification of the assertion is done correctly even when the statement // throws an exception or aborts the current function. // // Known restrictions: // - You cannot stream a failure message to this macro. // // Note that even though the implementations of the following two // macros are much alike, we cannot refactor them to use a common // helper macro, due to some peculiarity in how the preprocessor // works. If we do that, the code won't compile when the user gives // EXPECT_NONFATAL_FAILURE() a statement that contains a macro that // expands to code containing an unprotected comma. The // AcceptsMacroThatExpandsToUnprotectedComma test in gtest_unittest.cc // catches that. // // For the same reason, we have to write // if (::testing::internal::AlwaysTrue()) { statement; } // instead of // GTEST_SUPPRESS_UNREACHABLE_CODE_WARNING_BELOW_(statement) // to avoid an MSVC warning on unreachable code. #define EXPECT_NONFATAL_FAILURE(statement, substr) \ do {\ ::testing::TestPartResultArray gtest_failures;\ ::testing::internal::SingleFailureChecker gtest_checker(\ >est_failures, ::testing::TestPartResult::kNonFatalFailure, \ (substr));\ {\ ::testing::ScopedFakeTestPartResultReporter gtest_reporter(\ ::testing::ScopedFakeTestPartResultReporter:: \ INTERCEPT_ONLY_CURRENT_THREAD, >est_failures);\ if (::testing::internal::AlwaysTrue()) { statement; }\ }\ } while (::testing::internal::AlwaysFalse()) #define EXPECT_NONFATAL_FAILURE_ON_ALL_THREADS(statement, substr) \ do {\ ::testing::TestPartResultArray gtest_failures;\ ::testing::internal::SingleFailureChecker gtest_checker(\ >est_failures, ::testing::TestPartResult::kNonFatalFailure, \ (substr));\ {\ ::testing::ScopedFakeTestPartResultReporter gtest_reporter(\ ::testing::ScopedFakeTestPartResultReporter::INTERCEPT_ALL_THREADS, \ >est_failures);\ if (::testing::internal::AlwaysTrue()) { statement; }\ }\ } while (::testing::internal::AlwaysFalse()) #endif // GTEST_INCLUDE_GTEST_GTEST_SPI_H_ #include #include #include #include #include #include #include #include #include #include #include #include // NOLINT #include #include #if GTEST_OS_LINUX // TODO(kenton@google.com): Use autoconf to detect availability of // gettimeofday(). # define GTEST_HAS_GETTIMEOFDAY_ 1 # include // NOLINT # include // NOLINT # include // NOLINT // Declares vsnprintf(). This header is not available on Windows. # include // NOLINT # include // NOLINT # include // NOLINT # include // NOLINT # include #elif GTEST_OS_SYMBIAN # define GTEST_HAS_GETTIMEOFDAY_ 1 # include // NOLINT #elif GTEST_OS_ZOS # define GTEST_HAS_GETTIMEOFDAY_ 1 # include // NOLINT // On z/OS we additionally need strings.h for strcasecmp. # include // NOLINT #elif GTEST_OS_WINDOWS_MOBILE // We are on Windows CE. # include // NOLINT #elif GTEST_OS_WINDOWS // We are on Windows proper. # include // NOLINT # include // NOLINT # include // NOLINT # include // NOLINT # if GTEST_OS_WINDOWS_MINGW // MinGW has gettimeofday() but not _ftime64(). // TODO(kenton@google.com): Use autoconf to detect availability of // gettimeofday(). // TODO(kenton@google.com): There are other ways to get the time on // Windows, like GetTickCount() or GetSystemTimeAsFileTime(). MinGW // supports these. consider using them instead. # define GTEST_HAS_GETTIMEOFDAY_ 1 # include // NOLINT # endif // GTEST_OS_WINDOWS_MINGW // cpplint thinks that the header is already included, so we want to // silence it. # include // NOLINT #else // Assume other platforms have gettimeofday(). // TODO(kenton@google.com): Use autoconf to detect availability of // gettimeofday(). # define GTEST_HAS_GETTIMEOFDAY_ 1 // cpplint thinks that the header is already included, so we want to // silence it. # include // NOLINT # include // NOLINT #endif // GTEST_OS_LINUX #if GTEST_HAS_EXCEPTIONS # include #endif #if GTEST_CAN_STREAM_RESULTS_ # include // NOLINT # include // NOLINT #endif // Indicates that this translation unit is part of Google Test's // implementation. It must come before gtest-internal-inl.h is // included, or there will be a compiler error. This trick is to // prevent a user from accidentally including gtest-internal-inl.h in // his code. #define GTEST_IMPLEMENTATION_ 1 // Copyright 2005, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // Utility functions and classes used by the Google C++ testing framework. // // Author: wan@google.com (Zhanyong Wan) // // This file contains purely Google Test's internal implementation. Please // DO NOT #INCLUDE IT IN A USER PROGRAM. #ifndef GTEST_SRC_GTEST_INTERNAL_INL_H_ #define GTEST_SRC_GTEST_INTERNAL_INL_H_ // GTEST_IMPLEMENTATION_ is defined to 1 iff the current translation unit is // part of Google Test's implementation; otherwise it's undefined. #if !GTEST_IMPLEMENTATION_ // A user is trying to include this from his code - just say no. # error "gtest-internal-inl.h is part of Google Test's internal implementation." # error "It must not be included except by Google Test itself." #endif // GTEST_IMPLEMENTATION_ #ifndef _WIN32_WCE # include #endif // !_WIN32_WCE #include #include // For strtoll/_strtoul64/malloc/free. #include // For memmove. #include #include #include #if GTEST_CAN_STREAM_RESULTS_ # include // NOLINT # include // NOLINT #endif #if GTEST_OS_WINDOWS # include // NOLINT #endif // GTEST_OS_WINDOWS namespace testing { // Declares the flags. // // We don't want the users to modify this flag in the code, but want // Google Test's own unit tests to be able to access it. Therefore we // declare it here as opposed to in gtest.h. GTEST_DECLARE_bool_(death_test_use_fork); namespace internal { // The value of GetTestTypeId() as seen from within the Google Test // library. This is solely for testing GetTestTypeId(). GTEST_API_ extern const TypeId kTestTypeIdInGoogleTest; // Names of the flags (needed for parsing Google Test flags). const char kAlsoRunDisabledTestsFlag[] = "also_run_disabled_tests"; const char kBreakOnFailureFlag[] = "break_on_failure"; const char kCatchExceptionsFlag[] = "catch_exceptions"; const char kColorFlag[] = "color"; const char kFilterFlag[] = "filter"; const char kListTestsFlag[] = "list_tests"; const char kOutputFlag[] = "output"; const char kPrintTimeFlag[] = "print_time"; const char kRandomSeedFlag[] = "random_seed"; const char kRepeatFlag[] = "repeat"; const char kShuffleFlag[] = "shuffle"; const char kStackTraceDepthFlag[] = "stack_trace_depth"; const char kStreamResultToFlag[] = "stream_result_to"; const char kThrowOnFailureFlag[] = "throw_on_failure"; // A valid random seed must be in [1, kMaxRandomSeed]. const int kMaxRandomSeed = 99999; // g_help_flag is true iff the --help flag or an equivalent form is // specified on the command line. GTEST_API_ extern bool g_help_flag; // Returns the current time in milliseconds. GTEST_API_ TimeInMillis GetTimeInMillis(); // Returns true iff Google Test should use colors in the output. GTEST_API_ bool ShouldUseColor(bool stdout_is_tty); // Formats the given time in milliseconds as seconds. GTEST_API_ std::string FormatTimeInMillisAsSeconds(TimeInMillis ms); // Converts the given time in milliseconds to a date string in the ISO 8601 // format, without the timezone information. N.B.: due to the use the // non-reentrant localtime() function, this function is not thread safe. Do // not use it in any code that can be called from multiple threads. GTEST_API_ std::string FormatEpochTimeInMillisAsIso8601(TimeInMillis ms); // Parses a string for an Int32 flag, in the form of "--flag=value". // // On success, stores the value of the flag in *value, and returns // true. On failure, returns false without changing *value. GTEST_API_ bool ParseInt32Flag( const char* str, const char* flag, Int32* value); // Returns a random seed in range [1, kMaxRandomSeed] based on the // given --gtest_random_seed flag value. inline int GetRandomSeedFromFlag(Int32 random_seed_flag) { const unsigned int raw_seed = (random_seed_flag == 0) ? static_cast(GetTimeInMillis()) : static_cast(random_seed_flag); // Normalizes the actual seed to range [1, kMaxRandomSeed] such that // it's easy to type. const int normalized_seed = static_cast((raw_seed - 1U) % static_cast(kMaxRandomSeed)) + 1; return normalized_seed; } // Returns the first valid random seed after 'seed'. The behavior is // undefined if 'seed' is invalid. The seed after kMaxRandomSeed is // considered to be 1. inline int GetNextRandomSeed(int seed) { GTEST_CHECK_(1 <= seed && seed <= kMaxRandomSeed) << "Invalid random seed " << seed << " - must be in [1, " << kMaxRandomSeed << "]."; const int next_seed = seed + 1; return (next_seed > kMaxRandomSeed) ? 1 : next_seed; } // This class saves the values of all Google Test flags in its c'tor, and // restores them in its d'tor. class GTestFlagSaver { public: // The c'tor. GTestFlagSaver() { also_run_disabled_tests_ = GTEST_FLAG(also_run_disabled_tests); break_on_failure_ = GTEST_FLAG(break_on_failure); catch_exceptions_ = GTEST_FLAG(catch_exceptions); color_ = GTEST_FLAG(color); death_test_style_ = GTEST_FLAG(death_test_style); death_test_use_fork_ = GTEST_FLAG(death_test_use_fork); filter_ = GTEST_FLAG(filter); internal_run_death_test_ = GTEST_FLAG(internal_run_death_test); list_tests_ = GTEST_FLAG(list_tests); output_ = GTEST_FLAG(output); print_time_ = GTEST_FLAG(print_time); random_seed_ = GTEST_FLAG(random_seed); repeat_ = GTEST_FLAG(repeat); shuffle_ = GTEST_FLAG(shuffle); stack_trace_depth_ = GTEST_FLAG(stack_trace_depth); stream_result_to_ = GTEST_FLAG(stream_result_to); throw_on_failure_ = GTEST_FLAG(throw_on_failure); } // The d'tor is not virtual. DO NOT INHERIT FROM THIS CLASS. ~GTestFlagSaver() { GTEST_FLAG(also_run_disabled_tests) = also_run_disabled_tests_; GTEST_FLAG(break_on_failure) = break_on_failure_; GTEST_FLAG(catch_exceptions) = catch_exceptions_; GTEST_FLAG(color) = color_; GTEST_FLAG(death_test_style) = death_test_style_; GTEST_FLAG(death_test_use_fork) = death_test_use_fork_; GTEST_FLAG(filter) = filter_; GTEST_FLAG(internal_run_death_test) = internal_run_death_test_; GTEST_FLAG(list_tests) = list_tests_; GTEST_FLAG(output) = output_; GTEST_FLAG(print_time) = print_time_; GTEST_FLAG(random_seed) = random_seed_; GTEST_FLAG(repeat) = repeat_; GTEST_FLAG(shuffle) = shuffle_; GTEST_FLAG(stack_trace_depth) = stack_trace_depth_; GTEST_FLAG(stream_result_to) = stream_result_to_; GTEST_FLAG(throw_on_failure) = throw_on_failure_; } private: // Fields for saving the original values of flags. bool also_run_disabled_tests_; bool break_on_failure_; bool catch_exceptions_; std::string color_; std::string death_test_style_; bool death_test_use_fork_; std::string filter_; std::string internal_run_death_test_; bool list_tests_; std::string output_; bool print_time_; internal::Int32 random_seed_; internal::Int32 repeat_; bool shuffle_; internal::Int32 stack_trace_depth_; std::string stream_result_to_; bool throw_on_failure_; } GTEST_ATTRIBUTE_UNUSED_; // Converts a Unicode code point to a narrow string in UTF-8 encoding. // code_point parameter is of type UInt32 because wchar_t may not be // wide enough to contain a code point. // If the code_point is not a valid Unicode code point // (i.e. outside of Unicode range U+0 to U+10FFFF) it will be converted // to "(Invalid Unicode 0xXXXXXXXX)". GTEST_API_ std::string CodePointToUtf8(UInt32 code_point); // Converts a wide string to a narrow string in UTF-8 encoding. // The wide string is assumed to have the following encoding: // UTF-16 if sizeof(wchar_t) == 2 (on Windows, Cygwin, Symbian OS) // UTF-32 if sizeof(wchar_t) == 4 (on Linux) // Parameter str points to a null-terminated wide string. // Parameter num_chars may additionally limit the number // of wchar_t characters processed. -1 is used when the entire string // should be processed. // If the string contains code points that are not valid Unicode code points // (i.e. outside of Unicode range U+0 to U+10FFFF) they will be output // as '(Invalid Unicode 0xXXXXXXXX)'. If the string is in UTF16 encoding // and contains invalid UTF-16 surrogate pairs, values in those pairs // will be encoded as individual Unicode characters from Basic Normal Plane. GTEST_API_ std::string WideStringToUtf8(const wchar_t* str, int num_chars); // Reads the GTEST_SHARD_STATUS_FILE environment variable, and creates the file // if the variable is present. If a file already exists at this location, this // function will write over it. If the variable is present, but the file cannot // be created, prints an error and exits. void WriteToShardStatusFileIfNeeded(); // Checks whether sharding is enabled by examining the relevant // environment variable values. If the variables are present, // but inconsistent (e.g., shard_index >= total_shards), prints // an error and exits. If in_subprocess_for_death_test, sharding is // disabled because it must only be applied to the original test // process. Otherwise, we could filter out death tests we intended to execute. GTEST_API_ bool ShouldShard(const char* total_shards_str, const char* shard_index_str, bool in_subprocess_for_death_test); // Parses the environment variable var as an Int32. If it is unset, // returns default_val. If it is not an Int32, prints an error and // and aborts. GTEST_API_ Int32 Int32FromEnvOrDie(const char* env_var, Int32 default_val); // Given the total number of shards, the shard index, and the test id, // returns true iff the test should be run on this shard. The test id is // some arbitrary but unique non-negative integer assigned to each test // method. Assumes that 0 <= shard_index < total_shards. GTEST_API_ bool ShouldRunTestOnShard( int total_shards, int shard_index, int test_id); // STL container utilities. // Returns the number of elements in the given container that satisfy // the given predicate. template inline int CountIf(const Container& c, Predicate predicate) { // Implemented as an explicit loop since std::count_if() in libCstd on // Solaris has a non-standard signature. int count = 0; for (typename Container::const_iterator it = c.begin(); it != c.end(); ++it) { if (predicate(*it)) ++count; } return count; } // Applies a function/functor to each element in the container. template void ForEach(const Container& c, Functor functor) { std::for_each(c.begin(), c.end(), functor); } // Returns the i-th element of the vector, or default_value if i is not // in range [0, v.size()). template inline E GetElementOr(const std::vector& v, int i, E default_value) { return (i < 0 || i >= static_cast(v.size())) ? default_value : v[i]; } // Performs an in-place shuffle of a range of the vector's elements. // 'begin' and 'end' are element indices as an STL-style range; // i.e. [begin, end) are shuffled, where 'end' == size() means to // shuffle to the end of the vector. template void ShuffleRange(internal::Random* random, int begin, int end, std::vector* v) { const int size = static_cast(v->size()); GTEST_CHECK_(0 <= begin && begin <= size) << "Invalid shuffle range start " << begin << ": must be in range [0, " << size << "]."; GTEST_CHECK_(begin <= end && end <= size) << "Invalid shuffle range finish " << end << ": must be in range [" << begin << ", " << size << "]."; // Fisher-Yates shuffle, from // http://en.wikipedia.org/wiki/Fisher-Yates_shuffle for (int range_width = end - begin; range_width >= 2; range_width--) { const int last_in_range = begin + range_width - 1; const int selected = begin + random->Generate(range_width); std::swap((*v)[selected], (*v)[last_in_range]); } } // Performs an in-place shuffle of the vector's elements. template inline void Shuffle(internal::Random* random, std::vector* v) { ShuffleRange(random, 0, static_cast(v->size()), v); } // A function for deleting an object. Handy for being used as a // functor. template static void Delete(T* x) { delete x; } // A predicate that checks the key of a TestProperty against a known key. // // TestPropertyKeyIs is copyable. class TestPropertyKeyIs { public: // Constructor. // // TestPropertyKeyIs has NO default constructor. explicit TestPropertyKeyIs(const std::string& key) : key_(key) {} // Returns true iff the test name of test property matches on key_. bool operator()(const TestProperty& test_property) const { return test_property.key() == key_; } private: std::string key_; }; // Class UnitTestOptions. // // This class contains functions for processing options the user // specifies when running the tests. It has only static members. // // In most cases, the user can specify an option using either an // environment variable or a command line flag. E.g. you can set the // test filter using either GTEST_FILTER or --gtest_filter. If both // the variable and the flag are present, the latter overrides the // former. class GTEST_API_ UnitTestOptions { public: // Functions for processing the gtest_output flag. // Returns the output format, or "" for normal printed output. static std::string GetOutputFormat(); // Returns the absolute path of the requested output file, or the // default (test_detail.xml in the original working directory) if // none was explicitly specified. static std::string GetAbsolutePathToOutputFile(); // Functions for processing the gtest_filter flag. // Returns true iff the wildcard pattern matches the string. The // first ':' or '\0' character in pattern marks the end of it. // // This recursive algorithm isn't very efficient, but is clear and // works well enough for matching test names, which are short. static bool PatternMatchesString(const char *pattern, const char *str); // Returns true iff the user-specified filter matches the test case // name and the test name. static bool FilterMatchesTest(const std::string &test_case_name, const std::string &test_name); #if GTEST_OS_WINDOWS // Function for supporting the gtest_catch_exception flag. // Returns EXCEPTION_EXECUTE_HANDLER if Google Test should handle the // given SEH exception, or EXCEPTION_CONTINUE_SEARCH otherwise. // This function is useful as an __except condition. static int GTestShouldProcessSEH(DWORD exception_code); #endif // GTEST_OS_WINDOWS // Returns true if "name" matches the ':' separated list of glob-style // filters in "filter". static bool MatchesFilter(const std::string& name, const char* filter); }; // Returns the current application's name, removing directory path if that // is present. Used by UnitTestOptions::GetOutputFile. GTEST_API_ FilePath GetCurrentExecutableName(); // The role interface for getting the OS stack trace as a string. class OsStackTraceGetterInterface { public: OsStackTraceGetterInterface() {} virtual ~OsStackTraceGetterInterface() {} // Returns the current OS stack trace as an std::string. Parameters: // // max_depth - the maximum number of stack frames to be included // in the trace. // skip_count - the number of top frames to be skipped; doesn't count // against max_depth. virtual string CurrentStackTrace(int max_depth, int skip_count) = 0; // UponLeavingGTest() should be called immediately before Google Test calls // user code. It saves some information about the current stack that // CurrentStackTrace() will use to find and hide Google Test stack frames. virtual void UponLeavingGTest() = 0; private: GTEST_DISALLOW_COPY_AND_ASSIGN_(OsStackTraceGetterInterface); }; // A working implementation of the OsStackTraceGetterInterface interface. class OsStackTraceGetter : public OsStackTraceGetterInterface { public: OsStackTraceGetter() : caller_frame_(NULL) {} virtual string CurrentStackTrace(int max_depth, int skip_count) GTEST_LOCK_EXCLUDED_(mutex_); virtual void UponLeavingGTest() GTEST_LOCK_EXCLUDED_(mutex_); // This string is inserted in place of stack frames that are part of // Google Test's implementation. static const char* const kElidedFramesMarker; private: Mutex mutex_; // protects all internal state // We save the stack frame below the frame that calls user code. // We do this because the address of the frame immediately below // the user code changes between the call to UponLeavingGTest() // and any calls to CurrentStackTrace() from within the user code. void* caller_frame_; GTEST_DISALLOW_COPY_AND_ASSIGN_(OsStackTraceGetter); }; // Information about a Google Test trace point. struct TraceInfo { const char* file; int line; std::string message; }; // This is the default global test part result reporter used in UnitTestImpl. // This class should only be used by UnitTestImpl. class DefaultGlobalTestPartResultReporter : public TestPartResultReporterInterface { public: explicit DefaultGlobalTestPartResultReporter(UnitTestImpl* unit_test); // Implements the TestPartResultReporterInterface. Reports the test part // result in the current test. virtual void ReportTestPartResult(const TestPartResult& result); private: UnitTestImpl* const unit_test_; GTEST_DISALLOW_COPY_AND_ASSIGN_(DefaultGlobalTestPartResultReporter); }; // This is the default per thread test part result reporter used in // UnitTestImpl. This class should only be used by UnitTestImpl. class DefaultPerThreadTestPartResultReporter : public TestPartResultReporterInterface { public: explicit DefaultPerThreadTestPartResultReporter(UnitTestImpl* unit_test); // Implements the TestPartResultReporterInterface. The implementation just // delegates to the current global test part result reporter of *unit_test_. virtual void ReportTestPartResult(const TestPartResult& result); private: UnitTestImpl* const unit_test_; GTEST_DISALLOW_COPY_AND_ASSIGN_(DefaultPerThreadTestPartResultReporter); }; // The private implementation of the UnitTest class. We don't protect // the methods under a mutex, as this class is not accessible by a // user and the UnitTest class that delegates work to this class does // proper locking. class GTEST_API_ UnitTestImpl { public: explicit UnitTestImpl(UnitTest* parent); virtual ~UnitTestImpl(); // There are two different ways to register your own TestPartResultReporter. // You can register your own repoter to listen either only for test results // from the current thread or for results from all threads. // By default, each per-thread test result repoter just passes a new // TestPartResult to the global test result reporter, which registers the // test part result for the currently running test. // Returns the global test part result reporter. TestPartResultReporterInterface* GetGlobalTestPartResultReporter(); // Sets the global test part result reporter. void SetGlobalTestPartResultReporter( TestPartResultReporterInterface* reporter); // Returns the test part result reporter for the current thread. TestPartResultReporterInterface* GetTestPartResultReporterForCurrentThread(); // Sets the test part result reporter for the current thread. void SetTestPartResultReporterForCurrentThread( TestPartResultReporterInterface* reporter); // Gets the number of successful test cases. int successful_test_case_count() const; // Gets the number of failed test cases. int failed_test_case_count() const; // Gets the number of all test cases. int total_test_case_count() const; // Gets the number of all test cases that contain at least one test // that should run. int test_case_to_run_count() const; // Gets the number of successful tests. int successful_test_count() const; // Gets the number of failed tests. int failed_test_count() const; // Gets the number of disabled tests that will be reported in the XML report. int reportable_disabled_test_count() const; // Gets the number of disabled tests. int disabled_test_count() const; // Gets the number of tests to be printed in the XML report. int reportable_test_count() const; // Gets the number of all tests. int total_test_count() const; // Gets the number of tests that should run. int test_to_run_count() const; // Gets the time of the test program start, in ms from the start of the // UNIX epoch. TimeInMillis start_timestamp() const { return start_timestamp_; } // Gets the elapsed time, in milliseconds. TimeInMillis elapsed_time() const { return elapsed_time_; } // Returns true iff the unit test passed (i.e. all test cases passed). bool Passed() const { return !Failed(); } // Returns true iff the unit test failed (i.e. some test case failed // or something outside of all tests failed). bool Failed() const { return failed_test_case_count() > 0 || ad_hoc_test_result()->Failed(); } // Gets the i-th test case among all the test cases. i can range from 0 to // total_test_case_count() - 1. If i is not in that range, returns NULL. const TestCase* GetTestCase(int i) const { const int index = GetElementOr(test_case_indices_, i, -1); return index < 0 ? NULL : test_cases_[i]; } // Gets the i-th test case among all the test cases. i can range from 0 to // total_test_case_count() - 1. If i is not in that range, returns NULL. TestCase* GetMutableTestCase(int i) { const int index = GetElementOr(test_case_indices_, i, -1); return index < 0 ? NULL : test_cases_[index]; } // Provides access to the event listener list. TestEventListeners* listeners() { return &listeners_; } // Returns the TestResult for the test that's currently running, or // the TestResult for the ad hoc test if no test is running. TestResult* current_test_result(); // Returns the TestResult for the ad hoc test. const TestResult* ad_hoc_test_result() const { return &ad_hoc_test_result_; } // Sets the OS stack trace getter. // // Does nothing if the input and the current OS stack trace getter // are the same; otherwise, deletes the old getter and makes the // input the current getter. void set_os_stack_trace_getter(OsStackTraceGetterInterface* getter); // Returns the current OS stack trace getter if it is not NULL; // otherwise, creates an OsStackTraceGetter, makes it the current // getter, and returns it. OsStackTraceGetterInterface* os_stack_trace_getter(); // Returns the current OS stack trace as an std::string. // // The maximum number of stack frames to be included is specified by // the gtest_stack_trace_depth flag. The skip_count parameter // specifies the number of top frames to be skipped, which doesn't // count against the number of frames to be included. // // For example, if Foo() calls Bar(), which in turn calls // CurrentOsStackTraceExceptTop(1), Foo() will be included in the // trace but Bar() and CurrentOsStackTraceExceptTop() won't. std::string CurrentOsStackTraceExceptTop(int skip_count) GTEST_NO_INLINE_; // Finds and returns a TestCase with the given name. If one doesn't // exist, creates one and returns it. // // Arguments: // // test_case_name: name of the test case // type_param: the name of the test's type parameter, or NULL if // this is not a typed or a type-parameterized test. // set_up_tc: pointer to the function that sets up the test case // tear_down_tc: pointer to the function that tears down the test case TestCase* GetTestCase(const char* test_case_name, const char* type_param, Test::SetUpTestCaseFunc set_up_tc, Test::TearDownTestCaseFunc tear_down_tc); // Adds a TestInfo to the unit test. // // Arguments: // // set_up_tc: pointer to the function that sets up the test case // tear_down_tc: pointer to the function that tears down the test case // test_info: the TestInfo object void AddTestInfo(Test::SetUpTestCaseFunc set_up_tc, Test::TearDownTestCaseFunc tear_down_tc, TestInfo* test_info) { // In order to support thread-safe death tests, we need to // remember the original working directory when the test program // was first invoked. We cannot do this in RUN_ALL_TESTS(), as // the user may have changed the current directory before calling // RUN_ALL_TESTS(). Therefore we capture the current directory in // AddTestInfo(), which is called to register a TEST or TEST_F // before main() is reached. if (original_working_dir_.IsEmpty()) { original_working_dir_.Set(FilePath::GetCurrentDir()); GTEST_CHECK_(!original_working_dir_.IsEmpty()) << "Failed to get the current working directory."; } GetTestCase(test_info->test_case_name(), test_info->type_param(), set_up_tc, tear_down_tc)->AddTestInfo(test_info); } #if GTEST_HAS_PARAM_TEST // Returns ParameterizedTestCaseRegistry object used to keep track of // value-parameterized tests and instantiate and register them. internal::ParameterizedTestCaseRegistry& parameterized_test_registry() { return parameterized_test_registry_; } #endif // GTEST_HAS_PARAM_TEST // Sets the TestCase object for the test that's currently running. void set_current_test_case(TestCase* a_current_test_case) { current_test_case_ = a_current_test_case; } // Sets the TestInfo object for the test that's currently running. If // current_test_info is NULL, the assertion results will be stored in // ad_hoc_test_result_. void set_current_test_info(TestInfo* a_current_test_info) { current_test_info_ = a_current_test_info; } // Registers all parameterized tests defined using TEST_P and // INSTANTIATE_TEST_CASE_P, creating regular tests for each test/parameter // combination. This method can be called more then once; it has guards // protecting from registering the tests more then once. If // value-parameterized tests are disabled, RegisterParameterizedTests is // present but does nothing. void RegisterParameterizedTests(); // Runs all tests in this UnitTest object, prints the result, and // returns true if all tests are successful. If any exception is // thrown during a test, this test is considered to be failed, but // the rest of the tests will still be run. bool RunAllTests(); // Clears the results of all tests, except the ad hoc tests. void ClearNonAdHocTestResult() { ForEach(test_cases_, TestCase::ClearTestCaseResult); } // Clears the results of ad-hoc test assertions. void ClearAdHocTestResult() { ad_hoc_test_result_.Clear(); } // Adds a TestProperty to the current TestResult object when invoked in a // context of a test or a test case, or to the global property set. If the // result already contains a property with the same key, the value will be // updated. void RecordProperty(const TestProperty& test_property); enum ReactionToSharding { HONOR_SHARDING_PROTOCOL, IGNORE_SHARDING_PROTOCOL }; // Matches the full name of each test against the user-specified // filter to decide whether the test should run, then records the // result in each TestCase and TestInfo object. // If shard_tests == HONOR_SHARDING_PROTOCOL, further filters tests // based on sharding variables in the environment. // Returns the number of tests that should run. int FilterTests(ReactionToSharding shard_tests); // Prints the names of the tests matching the user-specified filter flag. void ListTestsMatchingFilter(); const TestCase* current_test_case() const { return current_test_case_; } TestInfo* current_test_info() { return current_test_info_; } const TestInfo* current_test_info() const { return current_test_info_; } // Returns the vector of environments that need to be set-up/torn-down // before/after the tests are run. std::vector& environments() { return environments_; } // Getters for the per-thread Google Test trace stack. std::vector& gtest_trace_stack() { return *(gtest_trace_stack_.pointer()); } const std::vector& gtest_trace_stack() const { return gtest_trace_stack_.get(); } #if GTEST_HAS_DEATH_TEST void InitDeathTestSubprocessControlInfo() { internal_run_death_test_flag_.reset(ParseInternalRunDeathTestFlag()); } // Returns a pointer to the parsed --gtest_internal_run_death_test // flag, or NULL if that flag was not specified. // This information is useful only in a death test child process. // Must not be called before a call to InitGoogleTest. const InternalRunDeathTestFlag* internal_run_death_test_flag() const { return internal_run_death_test_flag_.get(); } // Returns a pointer to the current death test factory. internal::DeathTestFactory* death_test_factory() { return death_test_factory_.get(); } void SuppressTestEventsIfInSubprocess(); friend class ReplaceDeathTestFactory; #endif // GTEST_HAS_DEATH_TEST // Initializes the event listener performing XML output as specified by // UnitTestOptions. Must not be called before InitGoogleTest. void ConfigureXmlOutput(); #if GTEST_CAN_STREAM_RESULTS_ // Initializes the event listener for streaming test results to a socket. // Must not be called before InitGoogleTest. void ConfigureStreamingOutput(); #endif // Performs initialization dependent upon flag values obtained in // ParseGoogleTestFlagsOnly. Is called from InitGoogleTest after the call to // ParseGoogleTestFlagsOnly. In case a user neglects to call InitGoogleTest // this function is also called from RunAllTests. Since this function can be // called more than once, it has to be idempotent. void PostFlagParsingInit(); // Gets the random seed used at the start of the current test iteration. int random_seed() const { return random_seed_; } // Gets the random number generator. internal::Random* random() { return &random_; } // Shuffles all test cases, and the tests within each test case, // making sure that death tests are still run first. void ShuffleTests(); // Restores the test cases and tests to their order before the first shuffle. void UnshuffleTests(); // Returns the value of GTEST_FLAG(catch_exceptions) at the moment // UnitTest::Run() starts. bool catch_exceptions() const { return catch_exceptions_; } private: friend class ::testing::UnitTest; // Used by UnitTest::Run() to capture the state of // GTEST_FLAG(catch_exceptions) at the moment it starts. void set_catch_exceptions(bool value) { catch_exceptions_ = value; } // The UnitTest object that owns this implementation object. UnitTest* const parent_; // The working directory when the first TEST() or TEST_F() was // executed. internal::FilePath original_working_dir_; // The default test part result reporters. DefaultGlobalTestPartResultReporter default_global_test_part_result_reporter_; DefaultPerThreadTestPartResultReporter default_per_thread_test_part_result_reporter_; // Points to (but doesn't own) the global test part result reporter. TestPartResultReporterInterface* global_test_part_result_repoter_; // Protects read and write access to global_test_part_result_reporter_. internal::Mutex global_test_part_result_reporter_mutex_; // Points to (but doesn't own) the per-thread test part result reporter. internal::ThreadLocal per_thread_test_part_result_reporter_; // The vector of environments that need to be set-up/torn-down // before/after the tests are run. std::vector environments_; // The vector of TestCases in their original order. It owns the // elements in the vector. std::vector test_cases_; // Provides a level of indirection for the test case list to allow // easy shuffling and restoring the test case order. The i-th // element of this vector is the index of the i-th test case in the // shuffled order. std::vector test_case_indices_; #if GTEST_HAS_PARAM_TEST // ParameterizedTestRegistry object used to register value-parameterized // tests. internal::ParameterizedTestCaseRegistry parameterized_test_registry_; // Indicates whether RegisterParameterizedTests() has been called already. bool parameterized_tests_registered_; #endif // GTEST_HAS_PARAM_TEST // Index of the last death test case registered. Initially -1. int last_death_test_case_; // This points to the TestCase for the currently running test. It // changes as Google Test goes through one test case after another. // When no test is running, this is set to NULL and Google Test // stores assertion results in ad_hoc_test_result_. Initially NULL. TestCase* current_test_case_; // This points to the TestInfo for the currently running test. It // changes as Google Test goes through one test after another. When // no test is running, this is set to NULL and Google Test stores // assertion results in ad_hoc_test_result_. Initially NULL. TestInfo* current_test_info_; // Normally, a user only writes assertions inside a TEST or TEST_F, // or inside a function called by a TEST or TEST_F. Since Google // Test keeps track of which test is current running, it can // associate such an assertion with the test it belongs to. // // If an assertion is encountered when no TEST or TEST_F is running, // Google Test attributes the assertion result to an imaginary "ad hoc" // test, and records the result in ad_hoc_test_result_. TestResult ad_hoc_test_result_; // The list of event listeners that can be used to track events inside // Google Test. TestEventListeners listeners_; // The OS stack trace getter. Will be deleted when the UnitTest // object is destructed. By default, an OsStackTraceGetter is used, // but the user can set this field to use a custom getter if that is // desired. OsStackTraceGetterInterface* os_stack_trace_getter_; // True iff PostFlagParsingInit() has been called. bool post_flag_parse_init_performed_; // The random number seed used at the beginning of the test run. int random_seed_; // Our random number generator. internal::Random random_; // The time of the test program start, in ms from the start of the // UNIX epoch. TimeInMillis start_timestamp_; // How long the test took to run, in milliseconds. TimeInMillis elapsed_time_; #if GTEST_HAS_DEATH_TEST // The decomposed components of the gtest_internal_run_death_test flag, // parsed when RUN_ALL_TESTS is called. internal::scoped_ptr internal_run_death_test_flag_; internal::scoped_ptr death_test_factory_; #endif // GTEST_HAS_DEATH_TEST // A per-thread stack of traces created by the SCOPED_TRACE() macro. internal::ThreadLocal > gtest_trace_stack_; // The value of GTEST_FLAG(catch_exceptions) at the moment RunAllTests() // starts. bool catch_exceptions_; GTEST_DISALLOW_COPY_AND_ASSIGN_(UnitTestImpl); }; // class UnitTestImpl // Convenience function for accessing the global UnitTest // implementation object. inline UnitTestImpl* GetUnitTestImpl() { return UnitTest::GetInstance()->impl(); } #if GTEST_USES_SIMPLE_RE // Internal helper functions for implementing the simple regular // expression matcher. GTEST_API_ bool IsInSet(char ch, const char* str); GTEST_API_ bool IsAsciiDigit(char ch); GTEST_API_ bool IsAsciiPunct(char ch); GTEST_API_ bool IsRepeat(char ch); GTEST_API_ bool IsAsciiWhiteSpace(char ch); GTEST_API_ bool IsAsciiWordChar(char ch); GTEST_API_ bool IsValidEscape(char ch); GTEST_API_ bool AtomMatchesChar(bool escaped, char pattern, char ch); GTEST_API_ bool ValidateRegex(const char* regex); GTEST_API_ bool MatchRegexAtHead(const char* regex, const char* str); GTEST_API_ bool MatchRepetitionAndRegexAtHead( bool escaped, char ch, char repeat, const char* regex, const char* str); GTEST_API_ bool MatchRegexAnywhere(const char* regex, const char* str); #endif // GTEST_USES_SIMPLE_RE // Parses the command line for Google Test flags, without initializing // other parts of Google Test. GTEST_API_ void ParseGoogleTestFlagsOnly(int* argc, char** argv); GTEST_API_ void ParseGoogleTestFlagsOnly(int* argc, wchar_t** argv); #if GTEST_HAS_DEATH_TEST // Returns the message describing the last system error, regardless of the // platform. GTEST_API_ std::string GetLastErrnoDescription(); # if GTEST_OS_WINDOWS // Provides leak-safe Windows kernel handle ownership. class AutoHandle { public: AutoHandle() : handle_(INVALID_HANDLE_VALUE) {} explicit AutoHandle(HANDLE handle) : handle_(handle) {} ~AutoHandle() { Reset(); } HANDLE Get() const { return handle_; } void Reset() { Reset(INVALID_HANDLE_VALUE); } void Reset(HANDLE handle) { if (handle != handle_) { if (handle_ != INVALID_HANDLE_VALUE) ::CloseHandle(handle_); handle_ = handle; } } private: HANDLE handle_; GTEST_DISALLOW_COPY_AND_ASSIGN_(AutoHandle); }; # endif // GTEST_OS_WINDOWS // Attempts to parse a string into a positive integer pointed to by the // number parameter. Returns true if that is possible. // GTEST_HAS_DEATH_TEST implies that we have ::std::string, so we can use // it here. template bool ParseNaturalNumber(const ::std::string& str, Integer* number) { // Fail fast if the given string does not begin with a digit; // this bypasses strtoXXX's "optional leading whitespace and plus // or minus sign" semantics, which are undesirable here. if (str.empty() || !IsDigit(str[0])) { return false; } errno = 0; char* end; // BiggestConvertible is the largest integer type that system-provided // string-to-number conversion routines can return. # if GTEST_OS_WINDOWS && !defined(__GNUC__) // MSVC and C++ Builder define __int64 instead of the standard long long. typedef unsigned __int64 BiggestConvertible; const BiggestConvertible parsed = _strtoui64(str.c_str(), &end, 10); # else typedef unsigned long long BiggestConvertible; // NOLINT const BiggestConvertible parsed = strtoull(str.c_str(), &end, 10); # endif // GTEST_OS_WINDOWS && !defined(__GNUC__) const bool parse_success = *end == '\0' && errno == 0; // TODO(vladl@google.com): Convert this to compile time assertion when it is // available. GTEST_CHECK_(sizeof(Integer) <= sizeof(parsed)); const Integer result = static_cast(parsed); if (parse_success && static_cast(result) == parsed) { *number = result; return true; } return false; } #endif // GTEST_HAS_DEATH_TEST // TestResult contains some private methods that should be hidden from // Google Test user but are required for testing. This class allow our tests // to access them. // // This class is supplied only for the purpose of testing Google Test's own // constructs. Do not use it in user tests, either directly or indirectly. class TestResultAccessor { public: static void RecordProperty(TestResult* test_result, const std::string& xml_element, const TestProperty& property) { test_result->RecordProperty(xml_element, property); } static void ClearTestPartResults(TestResult* test_result) { test_result->ClearTestPartResults(); } static const std::vector& test_part_results( const TestResult& test_result) { return test_result.test_part_results(); } }; #if GTEST_CAN_STREAM_RESULTS_ // Streams test results to the given port on the given host machine. class StreamingListener : public EmptyTestEventListener { public: // Abstract base class for writing strings to a socket. class AbstractSocketWriter { public: virtual ~AbstractSocketWriter() {} // Sends a string to the socket. virtual void Send(const string& message) = 0; // Closes the socket. virtual void CloseConnection() {} // Sends a string and a newline to the socket. void SendLn(const string& message) { Send(message + "\n"); } }; // Concrete class for actually writing strings to a socket. class SocketWriter : public AbstractSocketWriter { public: SocketWriter(const string& host, const string& port) : sockfd_(-1), host_name_(host), port_num_(port) { MakeConnection(); } virtual ~SocketWriter() { if (sockfd_ != -1) CloseConnection(); } // Sends a string to the socket. virtual void Send(const string& message) { GTEST_CHECK_(sockfd_ != -1) << "Send() can be called only when there is a connection."; const int len = static_cast(message.length()); if (write(sockfd_, message.c_str(), len) != len) { GTEST_LOG_(WARNING) << "stream_result_to: failed to stream to " << host_name_ << ":" << port_num_; } } private: // Creates a client socket and connects to the server. void MakeConnection(); // Closes the socket. void CloseConnection() { GTEST_CHECK_(sockfd_ != -1) << "CloseConnection() can be called only when there is a connection."; close(sockfd_); sockfd_ = -1; } int sockfd_; // socket file descriptor const string host_name_; const string port_num_; GTEST_DISALLOW_COPY_AND_ASSIGN_(SocketWriter); }; // class SocketWriter // Escapes '=', '&', '%', and '\n' characters in str as "%xx". static string UrlEncode(const char* str); StreamingListener(const string& host, const string& port) : socket_writer_(new SocketWriter(host, port)) { Start(); } explicit StreamingListener(AbstractSocketWriter* socket_writer) : socket_writer_(socket_writer) { Start(); } void OnTestProgramStart(const UnitTest& /* unit_test */) { SendLn("event=TestProgramStart"); } void OnTestProgramEnd(const UnitTest& unit_test) { // Note that Google Test current only report elapsed time for each // test iteration, not for the entire test program. SendLn("event=TestProgramEnd&passed=" + FormatBool(unit_test.Passed())); // Notify the streaming server to stop. socket_writer_->CloseConnection(); } void OnTestIterationStart(const UnitTest& /* unit_test */, int iteration) { SendLn("event=TestIterationStart&iteration=" + StreamableToString(iteration)); } void OnTestIterationEnd(const UnitTest& unit_test, int /* iteration */) { SendLn("event=TestIterationEnd&passed=" + FormatBool(unit_test.Passed()) + "&elapsed_time=" + StreamableToString(unit_test.elapsed_time()) + "ms"); } void OnTestCaseStart(const TestCase& test_case) { SendLn(std::string("event=TestCaseStart&name=") + test_case.name()); } void OnTestCaseEnd(const TestCase& test_case) { SendLn("event=TestCaseEnd&passed=" + FormatBool(test_case.Passed()) + "&elapsed_time=" + StreamableToString(test_case.elapsed_time()) + "ms"); } void OnTestStart(const TestInfo& test_info) { SendLn(std::string("event=TestStart&name=") + test_info.name()); } void OnTestEnd(const TestInfo& test_info) { SendLn("event=TestEnd&passed=" + FormatBool((test_info.result())->Passed()) + "&elapsed_time=" + StreamableToString((test_info.result())->elapsed_time()) + "ms"); } void OnTestPartResult(const TestPartResult& test_part_result) { const char* file_name = test_part_result.file_name(); if (file_name == NULL) file_name = ""; SendLn("event=TestPartResult&file=" + UrlEncode(file_name) + "&line=" + StreamableToString(test_part_result.line_number()) + "&message=" + UrlEncode(test_part_result.message())); } private: // Sends the given message and a newline to the socket. void SendLn(const string& message) { socket_writer_->SendLn(message); } // Called at the start of streaming to notify the receiver what // protocol we are using. void Start() { SendLn("gtest_streaming_protocol_version=1.0"); } string FormatBool(bool value) { return value ? "1" : "0"; } const scoped_ptr socket_writer_; GTEST_DISALLOW_COPY_AND_ASSIGN_(StreamingListener); }; // class StreamingListener #endif // GTEST_CAN_STREAM_RESULTS_ } // namespace internal } // namespace testing #endif // GTEST_SRC_GTEST_INTERNAL_INL_H_ #undef GTEST_IMPLEMENTATION_ #if GTEST_OS_WINDOWS # define vsnprintf _vsnprintf #endif // GTEST_OS_WINDOWS namespace testing { using internal::CountIf; using internal::ForEach; using internal::GetElementOr; using internal::Shuffle; // Constants. // A test whose test case name or test name matches this filter is // disabled and not run. static const char kDisableTestFilter[] = "DISABLED_*:*/DISABLED_*"; // A test case whose name matches this filter is considered a death // test case and will be run before test cases whose name doesn't // match this filter. static const char kDeathTestCaseFilter[] = "*DeathTest:*DeathTest/*"; // A test filter that matches everything. static const char kUniversalFilter[] = "*"; // The default output file for XML output. static const char kDefaultOutputFile[] = "test_detail.xml"; // The environment variable name for the test shard index. static const char kTestShardIndex[] = "GTEST_SHARD_INDEX"; // The environment variable name for the total number of test shards. static const char kTestTotalShards[] = "GTEST_TOTAL_SHARDS"; // The environment variable name for the test shard status file. static const char kTestShardStatusFile[] = "GTEST_SHARD_STATUS_FILE"; namespace internal { // The text used in failure messages to indicate the start of the // stack trace. const char kStackTraceMarker[] = "\nStack trace:\n"; // g_help_flag is true iff the --help flag or an equivalent form is // specified on the command line. bool g_help_flag = false; } // namespace internal static const char* GetDefaultFilter() { return kUniversalFilter; } GTEST_DEFINE_bool_( also_run_disabled_tests, internal::BoolFromGTestEnv("also_run_disabled_tests", false), "Run disabled tests too, in addition to the tests normally being run."); GTEST_DEFINE_bool_( break_on_failure, internal::BoolFromGTestEnv("break_on_failure", false), "True iff a failed assertion should be a debugger break-point."); GTEST_DEFINE_bool_( catch_exceptions, internal::BoolFromGTestEnv("catch_exceptions", true), "True iff " GTEST_NAME_ " should catch exceptions and treat them as test failures."); GTEST_DEFINE_string_( color, internal::StringFromGTestEnv("color", "auto"), "Whether to use colors in the output. Valid values: yes, no, " "and auto. 'auto' means to use colors if the output is " "being sent to a terminal and the TERM environment variable " "is set to a terminal type that supports colors."); GTEST_DEFINE_string_( filter, internal::StringFromGTestEnv("filter", GetDefaultFilter()), "A colon-separated list of glob (not regex) patterns " "for filtering the tests to run, optionally followed by a " "'-' and a : separated list of negative patterns (tests to " "exclude). A test is run if it matches one of the positive " "patterns and does not match any of the negative patterns."); GTEST_DEFINE_bool_(list_tests, false, "List all tests without running them."); GTEST_DEFINE_string_( output, internal::StringFromGTestEnv("output", ""), "A format (currently must be \"xml\"), optionally followed " "by a colon and an output file name or directory. A directory " "is indicated by a trailing pathname separator. " "Examples: \"xml:filename.xml\", \"xml::directoryname/\". " "If a directory is specified, output files will be created " "within that directory, with file-names based on the test " "executable's name and, if necessary, made unique by adding " "digits."); GTEST_DEFINE_bool_( print_time, internal::BoolFromGTestEnv("print_time", true), "True iff " GTEST_NAME_ " should display elapsed time in text output."); GTEST_DEFINE_int32_( random_seed, internal::Int32FromGTestEnv("random_seed", 0), "Random number seed to use when shuffling test orders. Must be in range " "[1, 99999], or 0 to use a seed based on the current time."); GTEST_DEFINE_int32_( repeat, internal::Int32FromGTestEnv("repeat", 1), "How many times to repeat each test. Specify a negative number " "for repeating forever. Useful for shaking out flaky tests."); GTEST_DEFINE_bool_( show_internal_stack_frames, false, "True iff " GTEST_NAME_ " should include internal stack frames when " "printing test failure stack traces."); GTEST_DEFINE_bool_( shuffle, internal::BoolFromGTestEnv("shuffle", false), "True iff " GTEST_NAME_ " should randomize tests' order on every run."); GTEST_DEFINE_int32_( stack_trace_depth, internal::Int32FromGTestEnv("stack_trace_depth", kMaxStackTraceDepth), "The maximum number of stack frames to print when an " "assertion fails. The valid range is 0 through 100, inclusive."); GTEST_DEFINE_string_( stream_result_to, internal::StringFromGTestEnv("stream_result_to", ""), "This flag specifies the host name and the port number on which to stream " "test results. Example: \"localhost:555\". The flag is effective only on " "Linux."); GTEST_DEFINE_bool_( throw_on_failure, internal::BoolFromGTestEnv("throw_on_failure", false), "When this flag is specified, a failed assertion will throw an exception " "if exceptions are enabled or exit the program with a non-zero code " "otherwise."); namespace internal { // Generates a random number from [0, range), using a Linear // Congruential Generator (LCG). Crashes if 'range' is 0 or greater // than kMaxRange. UInt32 Random::Generate(UInt32 range) { // These constants are the same as are used in glibc's rand(3). state_ = (1103515245U*state_ + 12345U) % kMaxRange; GTEST_CHECK_(range > 0) << "Cannot generate a number in the range [0, 0)."; GTEST_CHECK_(range <= kMaxRange) << "Generation of a number in [0, " << range << ") was requested, " << "but this can only generate numbers in [0, " << kMaxRange << ")."; // Converting via modulus introduces a bit of downward bias, but // it's simple, and a linear congruential generator isn't too good // to begin with. return state_ % range; } // GTestIsInitialized() returns true iff the user has initialized // Google Test. Useful for catching the user mistake of not initializing // Google Test before calling RUN_ALL_TESTS(). // // A user must call testing::InitGoogleTest() to initialize Google // Test. g_init_gtest_count is set to the number of times // InitGoogleTest() has been called. We don't protect this variable // under a mutex as it is only accessed in the main thread. GTEST_API_ int g_init_gtest_count = 0; static bool GTestIsInitialized() { return g_init_gtest_count != 0; } // Iterates over a vector of TestCases, keeping a running sum of the // results of calling a given int-returning method on each. // Returns the sum. static int SumOverTestCaseList(const std::vector& case_list, int (TestCase::*method)() const) { int sum = 0; for (size_t i = 0; i < case_list.size(); i++) { sum += (case_list[i]->*method)(); } return sum; } // Returns true iff the test case passed. static bool TestCasePassed(const TestCase* test_case) { return test_case->should_run() && test_case->Passed(); } // Returns true iff the test case failed. static bool TestCaseFailed(const TestCase* test_case) { return test_case->should_run() && test_case->Failed(); } // Returns true iff test_case contains at least one test that should // run. static bool ShouldRunTestCase(const TestCase* test_case) { return test_case->should_run(); } // AssertHelper constructor. AssertHelper::AssertHelper(TestPartResult::Type type, const char* file, int line, const char* message) : data_(new AssertHelperData(type, file, line, message)) { } AssertHelper::~AssertHelper() { delete data_; } // Message assignment, for assertion streaming support. void AssertHelper::operator=(const Message& message) const { UnitTest::GetInstance()-> AddTestPartResult(data_->type, data_->file, data_->line, AppendUserMessage(data_->message, message), UnitTest::GetInstance()->impl() ->CurrentOsStackTraceExceptTop(1) // Skips the stack frame for this function itself. ); // NOLINT } // Mutex for linked pointers. GTEST_API_ GTEST_DEFINE_STATIC_MUTEX_(g_linked_ptr_mutex); // Application pathname gotten in InitGoogleTest. std::string g_executable_path; // Returns the current application's name, removing directory path if that // is present. FilePath GetCurrentExecutableName() { FilePath result; #if GTEST_OS_WINDOWS result.Set(FilePath(g_executable_path).RemoveExtension("exe")); #else result.Set(FilePath(g_executable_path)); #endif // GTEST_OS_WINDOWS return result.RemoveDirectoryName(); } // Functions for processing the gtest_output flag. // Returns the output format, or "" for normal printed output. std::string UnitTestOptions::GetOutputFormat() { const char* const gtest_output_flag = GTEST_FLAG(output).c_str(); if (gtest_output_flag == NULL) return std::string(""); const char* const colon = strchr(gtest_output_flag, ':'); return (colon == NULL) ? std::string(gtest_output_flag) : std::string(gtest_output_flag, colon - gtest_output_flag); } // Returns the name of the requested output file, or the default if none // was explicitly specified. std::string UnitTestOptions::GetAbsolutePathToOutputFile() { const char* const gtest_output_flag = GTEST_FLAG(output).c_str(); if (gtest_output_flag == NULL) return ""; const char* const colon = strchr(gtest_output_flag, ':'); if (colon == NULL) return internal::FilePath::ConcatPaths( internal::FilePath( UnitTest::GetInstance()->original_working_dir()), internal::FilePath(kDefaultOutputFile)).string(); internal::FilePath output_name(colon + 1); if (!output_name.IsAbsolutePath()) // TODO(wan@google.com): on Windows \some\path is not an absolute // path (as its meaning depends on the current drive), yet the // following logic for turning it into an absolute path is wrong. // Fix it. output_name = internal::FilePath::ConcatPaths( internal::FilePath(UnitTest::GetInstance()->original_working_dir()), internal::FilePath(colon + 1)); if (!output_name.IsDirectory()) return output_name.string(); internal::FilePath result(internal::FilePath::GenerateUniqueFileName( output_name, internal::GetCurrentExecutableName(), GetOutputFormat().c_str())); return result.string(); } // Returns true iff the wildcard pattern matches the string. The // first ':' or '\0' character in pattern marks the end of it. // // This recursive algorithm isn't very efficient, but is clear and // works well enough for matching test names, which are short. bool UnitTestOptions::PatternMatchesString(const char *pattern, const char *str) { switch (*pattern) { case '\0': case ':': // Either ':' or '\0' marks the end of the pattern. return *str == '\0'; case '?': // Matches any single character. return *str != '\0' && PatternMatchesString(pattern + 1, str + 1); case '*': // Matches any string (possibly empty) of characters. return (*str != '\0' && PatternMatchesString(pattern, str + 1)) || PatternMatchesString(pattern + 1, str); default: // Non-special character. Matches itself. return *pattern == *str && PatternMatchesString(pattern + 1, str + 1); } } bool UnitTestOptions::MatchesFilter( const std::string& name, const char* filter) { const char *cur_pattern = filter; for (;;) { if (PatternMatchesString(cur_pattern, name.c_str())) { return true; } // Finds the next pattern in the filter. cur_pattern = strchr(cur_pattern, ':'); // Returns if no more pattern can be found. if (cur_pattern == NULL) { return false; } // Skips the pattern separater (the ':' character). cur_pattern++; } } // Returns true iff the user-specified filter matches the test case // name and the test name. bool UnitTestOptions::FilterMatchesTest(const std::string &test_case_name, const std::string &test_name) { const std::string& full_name = test_case_name + "." + test_name.c_str(); // Split --gtest_filter at '-', if there is one, to separate into // positive filter and negative filter portions const char* const p = GTEST_FLAG(filter).c_str(); const char* const dash = strchr(p, '-'); std::string positive; std::string negative; if (dash == NULL) { positive = GTEST_FLAG(filter).c_str(); // Whole string is a positive filter negative = ""; } else { positive = std::string(p, dash); // Everything up to the dash negative = std::string(dash + 1); // Everything after the dash if (positive.empty()) { // Treat '-test1' as the same as '*-test1' positive = kUniversalFilter; } } // A filter is a colon-separated list of patterns. It matches a // test if any pattern in it matches the test. return (MatchesFilter(full_name, positive.c_str()) && !MatchesFilter(full_name, negative.c_str())); } #if GTEST_HAS_SEH // Returns EXCEPTION_EXECUTE_HANDLER if Google Test should handle the // given SEH exception, or EXCEPTION_CONTINUE_SEARCH otherwise. // This function is useful as an __except condition. int UnitTestOptions::GTestShouldProcessSEH(DWORD exception_code) { // Google Test should handle a SEH exception if: // 1. the user wants it to, AND // 2. this is not a breakpoint exception, AND // 3. this is not a C++ exception (VC++ implements them via SEH, // apparently). // // SEH exception code for C++ exceptions. // (see http://support.microsoft.com/kb/185294 for more information). const DWORD kCxxExceptionCode = 0xe06d7363; bool should_handle = true; if (!GTEST_FLAG(catch_exceptions)) should_handle = false; else if (exception_code == EXCEPTION_BREAKPOINT) should_handle = false; else if (exception_code == kCxxExceptionCode) should_handle = false; return should_handle ? EXCEPTION_EXECUTE_HANDLER : EXCEPTION_CONTINUE_SEARCH; } #endif // GTEST_HAS_SEH } // namespace internal // The c'tor sets this object as the test part result reporter used by // Google Test. The 'result' parameter specifies where to report the // results. Intercepts only failures from the current thread. ScopedFakeTestPartResultReporter::ScopedFakeTestPartResultReporter( TestPartResultArray* result) : intercept_mode_(INTERCEPT_ONLY_CURRENT_THREAD), result_(result) { Init(); } // The c'tor sets this object as the test part result reporter used by // Google Test. The 'result' parameter specifies where to report the // results. ScopedFakeTestPartResultReporter::ScopedFakeTestPartResultReporter( InterceptMode intercept_mode, TestPartResultArray* result) : intercept_mode_(intercept_mode), result_(result) { Init(); } void ScopedFakeTestPartResultReporter::Init() { internal::UnitTestImpl* const impl = internal::GetUnitTestImpl(); if (intercept_mode_ == INTERCEPT_ALL_THREADS) { old_reporter_ = impl->GetGlobalTestPartResultReporter(); impl->SetGlobalTestPartResultReporter(this); } else { old_reporter_ = impl->GetTestPartResultReporterForCurrentThread(); impl->SetTestPartResultReporterForCurrentThread(this); } } // The d'tor restores the test part result reporter used by Google Test // before. ScopedFakeTestPartResultReporter::~ScopedFakeTestPartResultReporter() { internal::UnitTestImpl* const impl = internal::GetUnitTestImpl(); if (intercept_mode_ == INTERCEPT_ALL_THREADS) { impl->SetGlobalTestPartResultReporter(old_reporter_); } else { impl->SetTestPartResultReporterForCurrentThread(old_reporter_); } } // Increments the test part result count and remembers the result. // This method is from the TestPartResultReporterInterface interface. void ScopedFakeTestPartResultReporter::ReportTestPartResult( const TestPartResult& result) { result_->Append(result); } namespace internal { // Returns the type ID of ::testing::Test. We should always call this // instead of GetTypeId< ::testing::Test>() to get the type ID of // testing::Test. This is to work around a suspected linker bug when // using Google Test as a framework on Mac OS X. The bug causes // GetTypeId< ::testing::Test>() to return different values depending // on whether the call is from the Google Test framework itself or // from user test code. GetTestTypeId() is guaranteed to always // return the same value, as it always calls GetTypeId<>() from the // gtest.cc, which is within the Google Test framework. TypeId GetTestTypeId() { return GetTypeId(); } // The value of GetTestTypeId() as seen from within the Google Test // library. This is solely for testing GetTestTypeId(). extern const TypeId kTestTypeIdInGoogleTest = GetTestTypeId(); // This predicate-formatter checks that 'results' contains a test part // failure of the given type and that the failure message contains the // given substring. AssertionResult HasOneFailure(const char* /* results_expr */, const char* /* type_expr */, const char* /* substr_expr */, const TestPartResultArray& results, TestPartResult::Type type, const string& substr) { const std::string expected(type == TestPartResult::kFatalFailure ? "1 fatal failure" : "1 non-fatal failure"); Message msg; if (results.size() != 1) { msg << "Expected: " << expected << "\n" << " Actual: " << results.size() << " failures"; for (int i = 0; i < results.size(); i++) { msg << "\n" << results.GetTestPartResult(i); } return AssertionFailure() << msg; } const TestPartResult& r = results.GetTestPartResult(0); if (r.type() != type) { return AssertionFailure() << "Expected: " << expected << "\n" << " Actual:\n" << r; } if (strstr(r.message(), substr.c_str()) == NULL) { return AssertionFailure() << "Expected: " << expected << " containing \"" << substr << "\"\n" << " Actual:\n" << r; } return AssertionSuccess(); } // The constructor of SingleFailureChecker remembers where to look up // test part results, what type of failure we expect, and what // substring the failure message should contain. SingleFailureChecker:: SingleFailureChecker( const TestPartResultArray* results, TestPartResult::Type type, const string& substr) : results_(results), type_(type), substr_(substr) {} // The destructor of SingleFailureChecker verifies that the given // TestPartResultArray contains exactly one failure that has the given // type and contains the given substring. If that's not the case, a // non-fatal failure will be generated. SingleFailureChecker::~SingleFailureChecker() { EXPECT_PRED_FORMAT3(HasOneFailure, *results_, type_, substr_); } DefaultGlobalTestPartResultReporter::DefaultGlobalTestPartResultReporter( UnitTestImpl* unit_test) : unit_test_(unit_test) {} void DefaultGlobalTestPartResultReporter::ReportTestPartResult( const TestPartResult& result) { unit_test_->current_test_result()->AddTestPartResult(result); unit_test_->listeners()->repeater()->OnTestPartResult(result); } DefaultPerThreadTestPartResultReporter::DefaultPerThreadTestPartResultReporter( UnitTestImpl* unit_test) : unit_test_(unit_test) {} void DefaultPerThreadTestPartResultReporter::ReportTestPartResult( const TestPartResult& result) { unit_test_->GetGlobalTestPartResultReporter()->ReportTestPartResult(result); } // Returns the global test part result reporter. TestPartResultReporterInterface* UnitTestImpl::GetGlobalTestPartResultReporter() { internal::MutexLock lock(&global_test_part_result_reporter_mutex_); return global_test_part_result_repoter_; } // Sets the global test part result reporter. void UnitTestImpl::SetGlobalTestPartResultReporter( TestPartResultReporterInterface* reporter) { internal::MutexLock lock(&global_test_part_result_reporter_mutex_); global_test_part_result_repoter_ = reporter; } // Returns the test part result reporter for the current thread. TestPartResultReporterInterface* UnitTestImpl::GetTestPartResultReporterForCurrentThread() { return per_thread_test_part_result_reporter_.get(); } // Sets the test part result reporter for the current thread. void UnitTestImpl::SetTestPartResultReporterForCurrentThread( TestPartResultReporterInterface* reporter) { per_thread_test_part_result_reporter_.set(reporter); } // Gets the number of successful test cases. int UnitTestImpl::successful_test_case_count() const { return CountIf(test_cases_, TestCasePassed); } // Gets the number of failed test cases. int UnitTestImpl::failed_test_case_count() const { return CountIf(test_cases_, TestCaseFailed); } // Gets the number of all test cases. int UnitTestImpl::total_test_case_count() const { return static_cast(test_cases_.size()); } // Gets the number of all test cases that contain at least one test // that should run. int UnitTestImpl::test_case_to_run_count() const { return CountIf(test_cases_, ShouldRunTestCase); } // Gets the number of successful tests. int UnitTestImpl::successful_test_count() const { return SumOverTestCaseList(test_cases_, &TestCase::successful_test_count); } // Gets the number of failed tests. int UnitTestImpl::failed_test_count() const { return SumOverTestCaseList(test_cases_, &TestCase::failed_test_count); } // Gets the number of disabled tests that will be reported in the XML report. int UnitTestImpl::reportable_disabled_test_count() const { return SumOverTestCaseList(test_cases_, &TestCase::reportable_disabled_test_count); } // Gets the number of disabled tests. int UnitTestImpl::disabled_test_count() const { return SumOverTestCaseList(test_cases_, &TestCase::disabled_test_count); } // Gets the number of tests to be printed in the XML report. int UnitTestImpl::reportable_test_count() const { return SumOverTestCaseList(test_cases_, &TestCase::reportable_test_count); } // Gets the number of all tests. int UnitTestImpl::total_test_count() const { return SumOverTestCaseList(test_cases_, &TestCase::total_test_count); } // Gets the number of tests that should run. int UnitTestImpl::test_to_run_count() const { return SumOverTestCaseList(test_cases_, &TestCase::test_to_run_count); } // Returns the current OS stack trace as an std::string. // // The maximum number of stack frames to be included is specified by // the gtest_stack_trace_depth flag. The skip_count parameter // specifies the number of top frames to be skipped, which doesn't // count against the number of frames to be included. // // For example, if Foo() calls Bar(), which in turn calls // CurrentOsStackTraceExceptTop(1), Foo() will be included in the // trace but Bar() and CurrentOsStackTraceExceptTop() won't. std::string UnitTestImpl::CurrentOsStackTraceExceptTop(int skip_count) { (void)skip_count; return ""; } // Returns the current time in milliseconds. TimeInMillis GetTimeInMillis() { #if GTEST_OS_WINDOWS_MOBILE || defined(__BORLANDC__) // Difference between 1970-01-01 and 1601-01-01 in milliseconds. // http://analogous.blogspot.com/2005/04/epoch.html const TimeInMillis kJavaEpochToWinFileTimeDelta = static_cast(116444736UL) * 100000UL; const DWORD kTenthMicrosInMilliSecond = 10000; SYSTEMTIME now_systime; FILETIME now_filetime; ULARGE_INTEGER now_int64; // TODO(kenton@google.com): Shouldn't this just use // GetSystemTimeAsFileTime()? GetSystemTime(&now_systime); if (SystemTimeToFileTime(&now_systime, &now_filetime)) { now_int64.LowPart = now_filetime.dwLowDateTime; now_int64.HighPart = now_filetime.dwHighDateTime; now_int64.QuadPart = (now_int64.QuadPart / kTenthMicrosInMilliSecond) - kJavaEpochToWinFileTimeDelta; return now_int64.QuadPart; } return 0; #elif GTEST_OS_WINDOWS && !GTEST_HAS_GETTIMEOFDAY_ __timeb64 now; # ifdef _MSC_VER // MSVC 8 deprecates _ftime64(), so we want to suppress warning 4996 // (deprecated function) there. // TODO(kenton@google.com): Use GetTickCount()? Or use // SystemTimeToFileTime() # pragma warning(push) // Saves the current warning state. # pragma warning(disable:4996) // Temporarily disables warning 4996. _ftime64(&now); # pragma warning(pop) // Restores the warning state. # else _ftime64(&now); # endif // _MSC_VER return static_cast(now.time) * 1000 + now.millitm; #elif GTEST_HAS_GETTIMEOFDAY_ struct timeval now; gettimeofday(&now, NULL); return static_cast(now.tv_sec) * 1000 + now.tv_usec / 1000; #else # error "Don't know how to get the current time on your system." #endif } // Utilities // class String. #if GTEST_OS_WINDOWS_MOBILE // Creates a UTF-16 wide string from the given ANSI string, allocating // memory using new. The caller is responsible for deleting the return // value using delete[]. Returns the wide string, or NULL if the // input is NULL. LPCWSTR String::AnsiToUtf16(const char* ansi) { if (!ansi) return NULL; const int length = strlen(ansi); const int unicode_length = MultiByteToWideChar(CP_ACP, 0, ansi, length, NULL, 0); WCHAR* unicode = new WCHAR[unicode_length + 1]; MultiByteToWideChar(CP_ACP, 0, ansi, length, unicode, unicode_length); unicode[unicode_length] = 0; return unicode; } // Creates an ANSI string from the given wide string, allocating // memory using new. The caller is responsible for deleting the return // value using delete[]. Returns the ANSI string, or NULL if the // input is NULL. const char* String::Utf16ToAnsi(LPCWSTR utf16_str) { if (!utf16_str) return NULL; const int ansi_length = WideCharToMultiByte(CP_ACP, 0, utf16_str, -1, NULL, 0, NULL, NULL); char* ansi = new char[ansi_length + 1]; WideCharToMultiByte(CP_ACP, 0, utf16_str, -1, ansi, ansi_length, NULL, NULL); ansi[ansi_length] = 0; return ansi; } #endif // GTEST_OS_WINDOWS_MOBILE // Compares two C strings. Returns true iff they have the same content. // // Unlike strcmp(), this function can handle NULL argument(s). A NULL // C string is considered different to any non-NULL C string, // including the empty string. bool String::CStringEquals(const char * lhs, const char * rhs) { if ( lhs == NULL ) return rhs == NULL; if ( rhs == NULL ) return false; return strcmp(lhs, rhs) == 0; } #if GTEST_HAS_STD_WSTRING || GTEST_HAS_GLOBAL_WSTRING // Converts an array of wide chars to a narrow string using the UTF-8 // encoding, and streams the result to the given Message object. static void StreamWideCharsToMessage(const wchar_t* wstr, size_t length, Message* msg) { for (size_t i = 0; i != length; ) { // NOLINT if (wstr[i] != L'\0') { *msg << WideStringToUtf8(wstr + i, static_cast(length - i)); while (i != length && wstr[i] != L'\0') i++; } else { *msg << '\0'; i++; } } } #endif // GTEST_HAS_STD_WSTRING || GTEST_HAS_GLOBAL_WSTRING } // namespace internal // Constructs an empty Message. // We allocate the stringstream separately because otherwise each use of // ASSERT/EXPECT in a procedure adds over 200 bytes to the procedure's // stack frame leading to huge stack frames in some cases; gcc does not reuse // the stack space. Message::Message() : ss_(new ::std::stringstream) { // By default, we want there to be enough precision when printing // a double to a Message. *ss_ << std::setprecision(std::numeric_limits::digits10 + 2); } // These two overloads allow streaming a wide C string to a Message // using the UTF-8 encoding. Message& Message::operator <<(const wchar_t* wide_c_str) { return *this << internal::String::ShowWideCString(wide_c_str); } Message& Message::operator <<(wchar_t* wide_c_str) { return *this << internal::String::ShowWideCString(wide_c_str); } #if GTEST_HAS_STD_WSTRING // Converts the given wide string to a narrow string using the UTF-8 // encoding, and streams the result to this Message object. Message& Message::operator <<(const ::std::wstring& wstr) { internal::StreamWideCharsToMessage(wstr.c_str(), wstr.length(), this); return *this; } #endif // GTEST_HAS_STD_WSTRING #if GTEST_HAS_GLOBAL_WSTRING // Converts the given wide string to a narrow string using the UTF-8 // encoding, and streams the result to this Message object. Message& Message::operator <<(const ::wstring& wstr) { internal::StreamWideCharsToMessage(wstr.c_str(), wstr.length(), this); return *this; } #endif // GTEST_HAS_GLOBAL_WSTRING // Gets the text streamed to this object so far as an std::string. // Each '\0' character in the buffer is replaced with "\\0". std::string Message::GetString() const { return internal::StringStreamToString(ss_.get()); } // AssertionResult constructors. // Used in EXPECT_TRUE/FALSE(assertion_result). AssertionResult::AssertionResult(const AssertionResult& other) : success_(other.success_), message_(other.message_.get() != NULL ? new ::std::string(*other.message_) : static_cast< ::std::string*>(NULL)) { } // Returns the assertion's negation. Used with EXPECT/ASSERT_FALSE. AssertionResult AssertionResult::operator!() const { AssertionResult negation(!success_); if (message_.get() != NULL) negation << *message_; return negation; } // Makes a successful assertion result. AssertionResult AssertionSuccess() { return AssertionResult(true); } // Makes a failed assertion result. AssertionResult AssertionFailure() { return AssertionResult(false); } // Makes a failed assertion result with the given failure message. // Deprecated; use AssertionFailure() << message. AssertionResult AssertionFailure(const Message& message) { return AssertionFailure() << message; } namespace internal { // Constructs and returns the message for an equality assertion // (e.g. ASSERT_EQ, EXPECT_STREQ, etc) failure. // // The first four parameters are the expressions used in the assertion // and their values, as strings. For example, for ASSERT_EQ(foo, bar) // where foo is 5 and bar is 6, we have: // // expected_expression: "foo" // actual_expression: "bar" // expected_value: "5" // actual_value: "6" // // The ignoring_case parameter is true iff the assertion is a // *_STRCASEEQ*. When it's true, the string " (ignoring case)" will // be inserted into the message. AssertionResult EqFailure(const char* expected_expression, const char* actual_expression, const std::string& expected_value, const std::string& actual_value, bool ignoring_case) { Message msg; msg << "Value of: " << actual_expression; if (actual_value != actual_expression) { msg << "\n Actual: " << actual_value; } msg << "\nExpected: " << expected_expression; if (ignoring_case) { msg << " (ignoring case)"; } if (expected_value != expected_expression) { msg << "\nWhich is: " << expected_value; } return AssertionFailure() << msg; } // Constructs a failure message for Boolean assertions such as EXPECT_TRUE. std::string GetBoolAssertionFailureMessage( const AssertionResult& assertion_result, const char* expression_text, const char* actual_predicate_value, const char* expected_predicate_value) { const char* actual_message = assertion_result.message(); Message msg; msg << "Value of: " << expression_text << "\n Actual: " << actual_predicate_value; if (actual_message[0] != '\0') msg << " (" << actual_message << ")"; msg << "\nExpected: " << expected_predicate_value; return msg.GetString(); } // Helper function for implementing ASSERT_NEAR. AssertionResult DoubleNearPredFormat(const char* expr1, const char* expr2, const char* abs_error_expr, double val1, double val2, double abs_error) { const double diff = fabs(val1 - val2); if (diff <= abs_error) return AssertionSuccess(); // TODO(wan): do not print the value of an expression if it's // already a literal. return AssertionFailure() << "The difference between " << expr1 << " and " << expr2 << " is " << diff << ", which exceeds " << abs_error_expr << ", where\n" << expr1 << " evaluates to " << val1 << ",\n" << expr2 << " evaluates to " << val2 << ", and\n" << abs_error_expr << " evaluates to " << abs_error << "."; } // Helper template for implementing FloatLE() and DoubleLE(). template AssertionResult FloatingPointLE(const char* expr1, const char* expr2, RawType val1, RawType val2) { // Returns success if val1 is less than val2, if (val1 < val2) { return AssertionSuccess(); } // or if val1 is almost equal to val2. const FloatingPoint lhs(val1), rhs(val2); if (lhs.AlmostEquals(rhs)) { return AssertionSuccess(); } // Note that the above two checks will both fail if either val1 or // val2 is NaN, as the IEEE floating-point standard requires that // any predicate involving a NaN must return false. ::std::stringstream val1_ss; val1_ss << std::setprecision(std::numeric_limits::digits10 + 2) << val1; ::std::stringstream val2_ss; val2_ss << std::setprecision(std::numeric_limits::digits10 + 2) << val2; return AssertionFailure() << "Expected: (" << expr1 << ") <= (" << expr2 << ")\n" << " Actual: " << StringStreamToString(&val1_ss) << " vs " << StringStreamToString(&val2_ss); } } // namespace internal // Asserts that val1 is less than, or almost equal to, val2. Fails // otherwise. In particular, it fails if either val1 or val2 is NaN. AssertionResult FloatLE(const char* expr1, const char* expr2, float val1, float val2) { return internal::FloatingPointLE(expr1, expr2, val1, val2); } // Asserts that val1 is less than, or almost equal to, val2. Fails // otherwise. In particular, it fails if either val1 or val2 is NaN. AssertionResult DoubleLE(const char* expr1, const char* expr2, double val1, double val2) { return internal::FloatingPointLE(expr1, expr2, val1, val2); } namespace internal { // The helper function for {ASSERT|EXPECT}_EQ with int or enum // arguments. AssertionResult CmpHelperEQ(const char* expected_expression, const char* actual_expression, BiggestInt expected, BiggestInt actual) { if (expected == actual) { return AssertionSuccess(); } return EqFailure(expected_expression, actual_expression, FormatForComparisonFailureMessage(expected, actual), FormatForComparisonFailureMessage(actual, expected), false); } // A macro for implementing the helper functions needed to implement // ASSERT_?? and EXPECT_?? with integer or enum arguments. It is here // just to avoid copy-and-paste of similar code. #define GTEST_IMPL_CMP_HELPER_(op_name, op)\ AssertionResult CmpHelper##op_name(const char* expr1, const char* expr2, \ BiggestInt val1, BiggestInt val2) {\ if (val1 op val2) {\ return AssertionSuccess();\ } else {\ return AssertionFailure() \ << "Expected: (" << expr1 << ") " #op " (" << expr2\ << "), actual: " << FormatForComparisonFailureMessage(val1, val2)\ << " vs " << FormatForComparisonFailureMessage(val2, val1);\ }\ } // Implements the helper function for {ASSERT|EXPECT}_NE with int or // enum arguments. GTEST_IMPL_CMP_HELPER_(NE, !=) // Implements the helper function for {ASSERT|EXPECT}_LE with int or // enum arguments. GTEST_IMPL_CMP_HELPER_(LE, <=) // Implements the helper function for {ASSERT|EXPECT}_LT with int or // enum arguments. GTEST_IMPL_CMP_HELPER_(LT, < ) // Implements the helper function for {ASSERT|EXPECT}_GE with int or // enum arguments. GTEST_IMPL_CMP_HELPER_(GE, >=) // Implements the helper function for {ASSERT|EXPECT}_GT with int or // enum arguments. GTEST_IMPL_CMP_HELPER_(GT, > ) #undef GTEST_IMPL_CMP_HELPER_ // The helper function for {ASSERT|EXPECT}_STREQ. AssertionResult CmpHelperSTREQ(const char* expected_expression, const char* actual_expression, const char* expected, const char* actual) { if (String::CStringEquals(expected, actual)) { return AssertionSuccess(); } return EqFailure(expected_expression, actual_expression, PrintToString(expected), PrintToString(actual), false); } // The helper function for {ASSERT|EXPECT}_STRCASEEQ. AssertionResult CmpHelperSTRCASEEQ(const char* expected_expression, const char* actual_expression, const char* expected, const char* actual) { if (String::CaseInsensitiveCStringEquals(expected, actual)) { return AssertionSuccess(); } return EqFailure(expected_expression, actual_expression, PrintToString(expected), PrintToString(actual), true); } // The helper function for {ASSERT|EXPECT}_STRNE. AssertionResult CmpHelperSTRNE(const char* s1_expression, const char* s2_expression, const char* s1, const char* s2) { if (!String::CStringEquals(s1, s2)) { return AssertionSuccess(); } else { return AssertionFailure() << "Expected: (" << s1_expression << ") != (" << s2_expression << "), actual: \"" << s1 << "\" vs \"" << s2 << "\""; } } // The helper function for {ASSERT|EXPECT}_STRCASENE. AssertionResult CmpHelperSTRCASENE(const char* s1_expression, const char* s2_expression, const char* s1, const char* s2) { if (!String::CaseInsensitiveCStringEquals(s1, s2)) { return AssertionSuccess(); } else { return AssertionFailure() << "Expected: (" << s1_expression << ") != (" << s2_expression << ") (ignoring case), actual: \"" << s1 << "\" vs \"" << s2 << "\""; } } } // namespace internal namespace { // Helper functions for implementing IsSubString() and IsNotSubstring(). // This group of overloaded functions return true iff needle is a // substring of haystack. NULL is considered a substring of itself // only. bool IsSubstringPred(const char* needle, const char* haystack) { if (needle == NULL || haystack == NULL) return needle == haystack; return strstr(haystack, needle) != NULL; } bool IsSubstringPred(const wchar_t* needle, const wchar_t* haystack) { if (needle == NULL || haystack == NULL) return needle == haystack; return wcsstr(haystack, needle) != NULL; } // StringType here can be either ::std::string or ::std::wstring. template bool IsSubstringPred(const StringType& needle, const StringType& haystack) { return haystack.find(needle) != StringType::npos; } // This function implements either IsSubstring() or IsNotSubstring(), // depending on the value of the expected_to_be_substring parameter. // StringType here can be const char*, const wchar_t*, ::std::string, // or ::std::wstring. template AssertionResult IsSubstringImpl( bool expected_to_be_substring, const char* needle_expr, const char* haystack_expr, const StringType& needle, const StringType& haystack) { if (IsSubstringPred(needle, haystack) == expected_to_be_substring) return AssertionSuccess(); const bool is_wide_string = sizeof(needle[0]) > 1; const char* const begin_string_quote = is_wide_string ? "L\"" : "\""; return AssertionFailure() << "Value of: " << needle_expr << "\n" << " Actual: " << begin_string_quote << needle << "\"\n" << "Expected: " << (expected_to_be_substring ? "" : "not ") << "a substring of " << haystack_expr << "\n" << "Which is: " << begin_string_quote << haystack << "\""; } } // namespace // IsSubstring() and IsNotSubstring() check whether needle is a // substring of haystack (NULL is considered a substring of itself // only), and return an appropriate error message when they fail. AssertionResult IsSubstring( const char* needle_expr, const char* haystack_expr, const char* needle, const char* haystack) { return IsSubstringImpl(true, needle_expr, haystack_expr, needle, haystack); } AssertionResult IsSubstring( const char* needle_expr, const char* haystack_expr, const wchar_t* needle, const wchar_t* haystack) { return IsSubstringImpl(true, needle_expr, haystack_expr, needle, haystack); } AssertionResult IsNotSubstring( const char* needle_expr, const char* haystack_expr, const char* needle, const char* haystack) { return IsSubstringImpl(false, needle_expr, haystack_expr, needle, haystack); } AssertionResult IsNotSubstring( const char* needle_expr, const char* haystack_expr, const wchar_t* needle, const wchar_t* haystack) { return IsSubstringImpl(false, needle_expr, haystack_expr, needle, haystack); } AssertionResult IsSubstring( const char* needle_expr, const char* haystack_expr, const ::std::string& needle, const ::std::string& haystack) { return IsSubstringImpl(true, needle_expr, haystack_expr, needle, haystack); } AssertionResult IsNotSubstring( const char* needle_expr, const char* haystack_expr, const ::std::string& needle, const ::std::string& haystack) { return IsSubstringImpl(false, needle_expr, haystack_expr, needle, haystack); } #if GTEST_HAS_STD_WSTRING AssertionResult IsSubstring( const char* needle_expr, const char* haystack_expr, const ::std::wstring& needle, const ::std::wstring& haystack) { return IsSubstringImpl(true, needle_expr, haystack_expr, needle, haystack); } AssertionResult IsNotSubstring( const char* needle_expr, const char* haystack_expr, const ::std::wstring& needle, const ::std::wstring& haystack) { return IsSubstringImpl(false, needle_expr, haystack_expr, needle, haystack); } #endif // GTEST_HAS_STD_WSTRING namespace internal { #if GTEST_OS_WINDOWS namespace { // Helper function for IsHRESULT{SuccessFailure} predicates AssertionResult HRESULTFailureHelper(const char* expr, const char* expected, long hr) { // NOLINT # if GTEST_OS_WINDOWS_MOBILE // Windows CE doesn't support FormatMessage. const char error_text[] = ""; # else // Looks up the human-readable system message for the HRESULT code // and since we're not passing any params to FormatMessage, we don't // want inserts expanded. const DWORD kFlags = FORMAT_MESSAGE_FROM_SYSTEM | FORMAT_MESSAGE_IGNORE_INSERTS; const DWORD kBufSize = 4096; // Gets the system's human readable message string for this HRESULT. char error_text[kBufSize] = { '\0' }; DWORD message_length = ::FormatMessageA(kFlags, 0, // no source, we're asking system hr, // the error 0, // no line width restrictions error_text, // output buffer kBufSize, // buf size NULL); // no arguments for inserts // Trims tailing white space (FormatMessage leaves a trailing CR-LF) for (; message_length && IsSpace(error_text[message_length - 1]); --message_length) { error_text[message_length - 1] = '\0'; } # endif // GTEST_OS_WINDOWS_MOBILE const std::string error_hex("0x" + String::FormatHexInt(hr)); return ::testing::AssertionFailure() << "Expected: " << expr << " " << expected << ".\n" << " Actual: " << error_hex << " " << error_text << "\n"; } } // namespace AssertionResult IsHRESULTSuccess(const char* expr, long hr) { // NOLINT if (SUCCEEDED(hr)) { return AssertionSuccess(); } return HRESULTFailureHelper(expr, "succeeds", hr); } AssertionResult IsHRESULTFailure(const char* expr, long hr) { // NOLINT if (FAILED(hr)) { return AssertionSuccess(); } return HRESULTFailureHelper(expr, "fails", hr); } #endif // GTEST_OS_WINDOWS // Utility functions for encoding Unicode text (wide strings) in // UTF-8. // A Unicode code-point can have upto 21 bits, and is encoded in UTF-8 // like this: // // Code-point length Encoding // 0 - 7 bits 0xxxxxxx // 8 - 11 bits 110xxxxx 10xxxxxx // 12 - 16 bits 1110xxxx 10xxxxxx 10xxxxxx // 17 - 21 bits 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx // The maximum code-point a one-byte UTF-8 sequence can represent. const UInt32 kMaxCodePoint1 = (static_cast(1) << 7) - 1; // The maximum code-point a two-byte UTF-8 sequence can represent. const UInt32 kMaxCodePoint2 = (static_cast(1) << (5 + 6)) - 1; // The maximum code-point a three-byte UTF-8 sequence can represent. const UInt32 kMaxCodePoint3 = (static_cast(1) << (4 + 2*6)) - 1; // The maximum code-point a four-byte UTF-8 sequence can represent. const UInt32 kMaxCodePoint4 = (static_cast(1) << (3 + 3*6)) - 1; // Chops off the n lowest bits from a bit pattern. Returns the n // lowest bits. As a side effect, the original bit pattern will be // shifted to the right by n bits. inline UInt32 ChopLowBits(UInt32* bits, int n) { const UInt32 low_bits = *bits & ((static_cast(1) << n) - 1); *bits >>= n; return low_bits; } // Converts a Unicode code point to a narrow string in UTF-8 encoding. // code_point parameter is of type UInt32 because wchar_t may not be // wide enough to contain a code point. // If the code_point is not a valid Unicode code point // (i.e. outside of Unicode range U+0 to U+10FFFF) it will be converted // to "(Invalid Unicode 0xXXXXXXXX)". std::string CodePointToUtf8(UInt32 code_point) { if (code_point > kMaxCodePoint4) { return "(Invalid Unicode 0x" + String::FormatHexInt(code_point) + ")"; } char str[5]; // Big enough for the largest valid code point. if (code_point <= kMaxCodePoint1) { str[1] = '\0'; str[0] = static_cast(code_point); // 0xxxxxxx } else if (code_point <= kMaxCodePoint2) { str[2] = '\0'; str[1] = static_cast(0x80 | ChopLowBits(&code_point, 6)); // 10xxxxxx str[0] = static_cast(0xC0 | code_point); // 110xxxxx } else if (code_point <= kMaxCodePoint3) { str[3] = '\0'; str[2] = static_cast(0x80 | ChopLowBits(&code_point, 6)); // 10xxxxxx str[1] = static_cast(0x80 | ChopLowBits(&code_point, 6)); // 10xxxxxx str[0] = static_cast(0xE0 | code_point); // 1110xxxx } else { // code_point <= kMaxCodePoint4 str[4] = '\0'; str[3] = static_cast(0x80 | ChopLowBits(&code_point, 6)); // 10xxxxxx str[2] = static_cast(0x80 | ChopLowBits(&code_point, 6)); // 10xxxxxx str[1] = static_cast(0x80 | ChopLowBits(&code_point, 6)); // 10xxxxxx str[0] = static_cast(0xF0 | code_point); // 11110xxx } return str; } // The following two functions only make sense if the the system // uses UTF-16 for wide string encoding. All supported systems // with 16 bit wchar_t (Windows, Cygwin, Symbian OS) do use UTF-16. // Determines if the arguments constitute UTF-16 surrogate pair // and thus should be combined into a single Unicode code point // using CreateCodePointFromUtf16SurrogatePair. inline bool IsUtf16SurrogatePair(wchar_t first, wchar_t second) { return sizeof(wchar_t) == 2 && (first & 0xFC00) == 0xD800 && (second & 0xFC00) == 0xDC00; } // Creates a Unicode code point from UTF16 surrogate pair. inline UInt32 CreateCodePointFromUtf16SurrogatePair(wchar_t first, wchar_t second) { const UInt32 mask = (1 << 10) - 1; return (sizeof(wchar_t) == 2) ? (((first & mask) << 10) | (second & mask)) + 0x10000 : // This function should not be called when the condition is // false, but we provide a sensible default in case it is. static_cast(first); } // Converts a wide string to a narrow string in UTF-8 encoding. // The wide string is assumed to have the following encoding: // UTF-16 if sizeof(wchar_t) == 2 (on Windows, Cygwin, Symbian OS) // UTF-32 if sizeof(wchar_t) == 4 (on Linux) // Parameter str points to a null-terminated wide string. // Parameter num_chars may additionally limit the number // of wchar_t characters processed. -1 is used when the entire string // should be processed. // If the string contains code points that are not valid Unicode code points // (i.e. outside of Unicode range U+0 to U+10FFFF) they will be output // as '(Invalid Unicode 0xXXXXXXXX)'. If the string is in UTF16 encoding // and contains invalid UTF-16 surrogate pairs, values in those pairs // will be encoded as individual Unicode characters from Basic Normal Plane. std::string WideStringToUtf8(const wchar_t* str, int num_chars) { if (num_chars == -1) num_chars = static_cast(wcslen(str)); ::std::stringstream stream; for (int i = 0; i < num_chars; ++i) { UInt32 unicode_code_point; if (str[i] == L'\0') { break; } else if (i + 1 < num_chars && IsUtf16SurrogatePair(str[i], str[i + 1])) { unicode_code_point = CreateCodePointFromUtf16SurrogatePair(str[i], str[i + 1]); i++; } else { unicode_code_point = static_cast(str[i]); } stream << CodePointToUtf8(unicode_code_point); } return StringStreamToString(&stream); } // Converts a wide C string to an std::string using the UTF-8 encoding. // NULL will be converted to "(null)". std::string String::ShowWideCString(const wchar_t * wide_c_str) { if (wide_c_str == NULL) return "(null)"; return internal::WideStringToUtf8(wide_c_str, -1); } // Compares two wide C strings. Returns true iff they have the same // content. // // Unlike wcscmp(), this function can handle NULL argument(s). A NULL // C string is considered different to any non-NULL C string, // including the empty string. bool String::WideCStringEquals(const wchar_t * lhs, const wchar_t * rhs) { if (lhs == NULL) return rhs == NULL; if (rhs == NULL) return false; return wcscmp(lhs, rhs) == 0; } // Helper function for *_STREQ on wide strings. AssertionResult CmpHelperSTREQ(const char* expected_expression, const char* actual_expression, const wchar_t* expected, const wchar_t* actual) { if (String::WideCStringEquals(expected, actual)) { return AssertionSuccess(); } return EqFailure(expected_expression, actual_expression, PrintToString(expected), PrintToString(actual), false); } // Helper function for *_STRNE on wide strings. AssertionResult CmpHelperSTRNE(const char* s1_expression, const char* s2_expression, const wchar_t* s1, const wchar_t* s2) { if (!String::WideCStringEquals(s1, s2)) { return AssertionSuccess(); } return AssertionFailure() << "Expected: (" << s1_expression << ") != (" << s2_expression << "), actual: " << PrintToString(s1) << " vs " << PrintToString(s2); } // Compares two C strings, ignoring case. Returns true iff they have // the same content. // // Unlike strcasecmp(), this function can handle NULL argument(s). A // NULL C string is considered different to any non-NULL C string, // including the empty string. bool String::CaseInsensitiveCStringEquals(const char * lhs, const char * rhs) { if (lhs == NULL) return rhs == NULL; if (rhs == NULL) return false; return posix::StrCaseCmp(lhs, rhs) == 0; } // Compares two wide C strings, ignoring case. Returns true iff they // have the same content. // // Unlike wcscasecmp(), this function can handle NULL argument(s). // A NULL C string is considered different to any non-NULL wide C string, // including the empty string. // NB: The implementations on different platforms slightly differ. // On windows, this method uses _wcsicmp which compares according to LC_CTYPE // environment variable. On GNU platform this method uses wcscasecmp // which compares according to LC_CTYPE category of the current locale. // On MacOS X, it uses towlower, which also uses LC_CTYPE category of the // current locale. bool String::CaseInsensitiveWideCStringEquals(const wchar_t* lhs, const wchar_t* rhs) { if (lhs == NULL) return rhs == NULL; if (rhs == NULL) return false; #if GTEST_OS_WINDOWS return _wcsicmp(lhs, rhs) == 0; #elif GTEST_OS_LINUX && !GTEST_OS_LINUX_ANDROID return wcscasecmp(lhs, rhs) == 0; #else // Android, Mac OS X and Cygwin don't define wcscasecmp. // Other unknown OSes may not define it either. wint_t left, right; do { left = towlower(*lhs++); right = towlower(*rhs++); } while (left && left == right); return left == right; #endif // OS selector } // Returns true iff str ends with the given suffix, ignoring case. // Any string is considered to end with an empty suffix. bool String::EndsWithCaseInsensitive( const std::string& str, const std::string& suffix) { const size_t str_len = str.length(); const size_t suffix_len = suffix.length(); return (str_len >= suffix_len) && CaseInsensitiveCStringEquals(str.c_str() + str_len - suffix_len, suffix.c_str()); } // Formats an int value as "%02d". std::string String::FormatIntWidth2(int value) { std::stringstream ss; ss << std::setfill('0') << std::setw(2) << value; return ss.str(); } // Formats an int value as "%X". std::string String::FormatHexInt(int value) { std::stringstream ss; ss << std::hex << std::uppercase << value; return ss.str(); } // Formats a byte as "%02X". std::string String::FormatByte(unsigned char value) { std::stringstream ss; ss << std::setfill('0') << std::setw(2) << std::hex << std::uppercase << static_cast(value); return ss.str(); } // Converts the buffer in a stringstream to an std::string, converting NUL // bytes to "\\0" along the way. std::string StringStreamToString(::std::stringstream* ss) { const ::std::string& str = ss->str(); const char* const start = str.c_str(); const char* const end = start + str.length(); std::string result; result.reserve(2 * (end - start)); for (const char* ch = start; ch != end; ++ch) { if (*ch == '\0') { result += "\\0"; // Replaces NUL with "\\0"; } else { result += *ch; } } return result; } // Appends the user-supplied message to the Google-Test-generated message. std::string AppendUserMessage(const std::string& gtest_msg, const Message& user_msg) { // Appends the user message if it's non-empty. const std::string user_msg_string = user_msg.GetString(); if (user_msg_string.empty()) { return gtest_msg; } return gtest_msg + "\n" + user_msg_string; } } // namespace internal // class TestResult // Creates an empty TestResult. TestResult::TestResult() : death_test_count_(0), elapsed_time_(0) { } // D'tor. TestResult::~TestResult() { } // Returns the i-th test part result among all the results. i can // range from 0 to total_part_count() - 1. If i is not in that range, // aborts the program. const TestPartResult& TestResult::GetTestPartResult(int i) const { if (i < 0 || i >= total_part_count()) internal::posix::Abort(); return test_part_results_.at(i); } // Returns the i-th test property. i can range from 0 to // test_property_count() - 1. If i is not in that range, aborts the // program. const TestProperty& TestResult::GetTestProperty(int i) const { if (i < 0 || i >= test_property_count()) internal::posix::Abort(); return test_properties_.at(i); } // Clears the test part results. void TestResult::ClearTestPartResults() { test_part_results_.clear(); } // Adds a test part result to the list. void TestResult::AddTestPartResult(const TestPartResult& test_part_result) { test_part_results_.push_back(test_part_result); } // Adds a test property to the list. If a property with the same key as the // supplied property is already represented, the value of this test_property // replaces the old value for that key. void TestResult::RecordProperty(const std::string& xml_element, const TestProperty& test_property) { if (!ValidateTestProperty(xml_element, test_property)) { return; } internal::MutexLock lock(&test_properites_mutex_); const std::vector::iterator property_with_matching_key = std::find_if(test_properties_.begin(), test_properties_.end(), internal::TestPropertyKeyIs(test_property.key())); if (property_with_matching_key == test_properties_.end()) { test_properties_.push_back(test_property); return; } property_with_matching_key->SetValue(test_property.value()); } // The list of reserved attributes used in the element of XML // output. static const char* const kReservedTestSuitesAttributes[] = { "disabled", "errors", "failures", "name", "random_seed", "tests", "time", "timestamp" }; // The list of reserved attributes used in the element of XML // output. static const char* const kReservedTestSuiteAttributes[] = { "disabled", "errors", "failures", "name", "tests", "time" }; // The list of reserved attributes used in the element of XML output. static const char* const kReservedTestCaseAttributes[] = { "classname", "name", "status", "time", "type_param", "value_param" }; template std::vector ArrayAsVector(const char* const (&array)[kSize]) { return std::vector(array, array + kSize); } static std::vector GetReservedAttributesForElement( const std::string& xml_element) { if (xml_element == "testsuites") { return ArrayAsVector(kReservedTestSuitesAttributes); } else if (xml_element == "testsuite") { return ArrayAsVector(kReservedTestSuiteAttributes); } else if (xml_element == "testcase") { return ArrayAsVector(kReservedTestCaseAttributes); } else { GTEST_CHECK_(false) << "Unrecognized xml_element provided: " << xml_element; } // This code is unreachable but some compilers may not realizes that. return std::vector(); } static std::string FormatWordList(const std::vector& words) { Message word_list; for (size_t i = 0; i < words.size(); ++i) { if (i > 0 && words.size() > 2) { word_list << ", "; } if (i == words.size() - 1) { word_list << "and "; } word_list << "'" << words[i] << "'"; } return word_list.GetString(); } bool ValidateTestPropertyName(const std::string& property_name, const std::vector& reserved_names) { if (std::find(reserved_names.begin(), reserved_names.end(), property_name) != reserved_names.end()) { ADD_FAILURE() << "Reserved key used in RecordProperty(): " << property_name << " (" << FormatWordList(reserved_names) << " are reserved by " << GTEST_NAME_ << ")"; return false; } return true; } // Adds a failure if the key is a reserved attribute of the element named // xml_element. Returns true if the property is valid. bool TestResult::ValidateTestProperty(const std::string& xml_element, const TestProperty& test_property) { return ValidateTestPropertyName(test_property.key(), GetReservedAttributesForElement(xml_element)); } // Clears the object. void TestResult::Clear() { test_part_results_.clear(); test_properties_.clear(); death_test_count_ = 0; elapsed_time_ = 0; } // Returns true iff the test failed. bool TestResult::Failed() const { for (int i = 0; i < total_part_count(); ++i) { if (GetTestPartResult(i).failed()) return true; } return false; } // Returns true iff the test part fatally failed. static bool TestPartFatallyFailed(const TestPartResult& result) { return result.fatally_failed(); } // Returns true iff the test fatally failed. bool TestResult::HasFatalFailure() const { return CountIf(test_part_results_, TestPartFatallyFailed) > 0; } // Returns true iff the test part non-fatally failed. static bool TestPartNonfatallyFailed(const TestPartResult& result) { return result.nonfatally_failed(); } // Returns true iff the test has a non-fatal failure. bool TestResult::HasNonfatalFailure() const { return CountIf(test_part_results_, TestPartNonfatallyFailed) > 0; } // Gets the number of all test parts. This is the sum of the number // of successful test parts and the number of failed test parts. int TestResult::total_part_count() const { return static_cast(test_part_results_.size()); } // Returns the number of the test properties. int TestResult::test_property_count() const { return static_cast(test_properties_.size()); } // class Test // Creates a Test object. // The c'tor saves the values of all Google Test flags. Test::Test() : gtest_flag_saver_(new internal::GTestFlagSaver) { } // The d'tor restores the values of all Google Test flags. Test::~Test() { delete gtest_flag_saver_; } // Sets up the test fixture. // // A sub-class may override this. void Test::SetUp() { } // Tears down the test fixture. // // A sub-class may override this. void Test::TearDown() { } // Allows user supplied key value pairs to be recorded for later output. void Test::RecordProperty(const std::string& key, const std::string& value) { UnitTest::GetInstance()->RecordProperty(key, value); } // Allows user supplied key value pairs to be recorded for later output. void Test::RecordProperty(const std::string& key, int value) { Message value_message; value_message << value; RecordProperty(key, value_message.GetString().c_str()); } namespace internal { void ReportFailureInUnknownLocation(TestPartResult::Type result_type, const std::string& message) { // This function is a friend of UnitTest and as such has access to // AddTestPartResult. UnitTest::GetInstance()->AddTestPartResult( result_type, NULL, // No info about the source file where the exception occurred. -1, // We have no info on which line caused the exception. message, ""); // No stack trace, either. } } // namespace internal // Google Test requires all tests in the same test case to use the same test // fixture class. This function checks if the current test has the // same fixture class as the first test in the current test case. If // yes, it returns true; otherwise it generates a Google Test failure and // returns false. bool Test::HasSameFixtureClass() { internal::UnitTestImpl* const impl = internal::GetUnitTestImpl(); const TestCase* const test_case = impl->current_test_case(); // Info about the first test in the current test case. const TestInfo* const first_test_info = test_case->test_info_list()[0]; const internal::TypeId first_fixture_id = first_test_info->fixture_class_id_; const char* const first_test_name = first_test_info->name(); // Info about the current test. const TestInfo* const this_test_info = impl->current_test_info(); const internal::TypeId this_fixture_id = this_test_info->fixture_class_id_; const char* const this_test_name = this_test_info->name(); if (this_fixture_id != first_fixture_id) { // Is the first test defined using TEST? const bool first_is_TEST = first_fixture_id == internal::GetTestTypeId(); // Is this test defined using TEST? const bool this_is_TEST = this_fixture_id == internal::GetTestTypeId(); if (first_is_TEST || this_is_TEST) { // The user mixed TEST and TEST_F in this test case - we'll tell // him/her how to fix it. // Gets the name of the TEST and the name of the TEST_F. Note // that first_is_TEST and this_is_TEST cannot both be true, as // the fixture IDs are different for the two tests. const char* const TEST_name = first_is_TEST ? first_test_name : this_test_name; const char* const TEST_F_name = first_is_TEST ? this_test_name : first_test_name; ADD_FAILURE() << "All tests in the same test case must use the same test fixture\n" << "class, so mixing TEST_F and TEST in the same test case is\n" << "illegal. In test case " << this_test_info->test_case_name() << ",\n" << "test " << TEST_F_name << " is defined using TEST_F but\n" << "test " << TEST_name << " is defined using TEST. You probably\n" << "want to change the TEST to TEST_F or move it to another test\n" << "case."; } else { // The user defined two fixture classes with the same name in // two namespaces - we'll tell him/her how to fix it. ADD_FAILURE() << "All tests in the same test case must use the same test fixture\n" << "class. However, in test case " << this_test_info->test_case_name() << ",\n" << "you defined test " << first_test_name << " and test " << this_test_name << "\n" << "using two different test fixture classes. This can happen if\n" << "the two classes are from different namespaces or translation\n" << "units and have the same name. You should probably rename one\n" << "of the classes to put the tests into different test cases."; } return false; } return true; } #if GTEST_HAS_SEH // Adds an "exception thrown" fatal failure to the current test. This // function returns its result via an output parameter pointer because VC++ // prohibits creation of objects with destructors on stack in functions // using __try (see error C2712). static std::string* FormatSehExceptionMessage(DWORD exception_code, const char* location) { Message message; message << "SEH exception with code 0x" << std::setbase(16) << exception_code << std::setbase(10) << " thrown in " << location << "."; return new std::string(message.GetString()); } #endif // GTEST_HAS_SEH namespace internal { #if GTEST_HAS_EXCEPTIONS // Adds an "exception thrown" fatal failure to the current test. static std::string FormatCxxExceptionMessage(const char* description, const char* location) { Message message; if (description != NULL) { message << "C++ exception with description \"" << description << "\""; } else { message << "Unknown C++ exception"; } message << " thrown in " << location << "."; return message.GetString(); } static std::string PrintTestPartResultToString( const TestPartResult& test_part_result); GoogleTestFailureException::GoogleTestFailureException( const TestPartResult& failure) : ::std::runtime_error(PrintTestPartResultToString(failure).c_str()) {} #endif // GTEST_HAS_EXCEPTIONS // We put these helper functions in the internal namespace as IBM's xlC // compiler rejects the code if they were declared static. // Runs the given method and handles SEH exceptions it throws, when // SEH is supported; returns the 0-value for type Result in case of an // SEH exception. (Microsoft compilers cannot handle SEH and C++ // exceptions in the same function. Therefore, we provide a separate // wrapper function for handling SEH exceptions.) template Result HandleSehExceptionsInMethodIfSupported( T* object, Result (T::*method)(), const char* location) { #if GTEST_HAS_SEH __try { return (object->*method)(); } __except (internal::UnitTestOptions::GTestShouldProcessSEH( // NOLINT GetExceptionCode())) { // We create the exception message on the heap because VC++ prohibits // creation of objects with destructors on stack in functions using __try // (see error C2712). std::string* exception_message = FormatSehExceptionMessage( GetExceptionCode(), location); internal::ReportFailureInUnknownLocation(TestPartResult::kFatalFailure, *exception_message); delete exception_message; return static_cast(0); } #else (void)location; return (object->*method)(); #endif // GTEST_HAS_SEH } // Runs the given method and catches and reports C++ and/or SEH-style // exceptions, if they are supported; returns the 0-value for type // Result in case of an SEH exception. template Result HandleExceptionsInMethodIfSupported( T* object, Result (T::*method)(), const char* location) { // NOTE: The user code can affect the way in which Google Test handles // exceptions by setting GTEST_FLAG(catch_exceptions), but only before // RUN_ALL_TESTS() starts. It is technically possible to check the flag // after the exception is caught and either report or re-throw the // exception based on the flag's value: // // try { // // Perform the test method. // } catch (...) { // if (GTEST_FLAG(catch_exceptions)) // // Report the exception as failure. // else // throw; // Re-throws the original exception. // } // // However, the purpose of this flag is to allow the program to drop into // the debugger when the exception is thrown. On most platforms, once the // control enters the catch block, the exception origin information is // lost and the debugger will stop the program at the point of the // re-throw in this function -- instead of at the point of the original // throw statement in the code under test. For this reason, we perform // the check early, sacrificing the ability to affect Google Test's // exception handling in the method where the exception is thrown. if (internal::GetUnitTestImpl()->catch_exceptions()) { #if GTEST_HAS_EXCEPTIONS try { return HandleSehExceptionsInMethodIfSupported(object, method, location); } catch (const internal::GoogleTestFailureException&) { // NOLINT // This exception type can only be thrown by a failed Google // Test assertion with the intention of letting another testing // framework catch it. Therefore we just re-throw it. throw; } catch (const std::exception& e) { // NOLINT internal::ReportFailureInUnknownLocation( TestPartResult::kFatalFailure, FormatCxxExceptionMessage(e.what(), location)); } catch (...) { // NOLINT internal::ReportFailureInUnknownLocation( TestPartResult::kFatalFailure, FormatCxxExceptionMessage(NULL, location)); } return static_cast(0); #else return HandleSehExceptionsInMethodIfSupported(object, method, location); #endif // GTEST_HAS_EXCEPTIONS } else { return (object->*method)(); } } } // namespace internal // Runs the test and updates the test result. void Test::Run() { if (!HasSameFixtureClass()) return; internal::UnitTestImpl* const impl = internal::GetUnitTestImpl(); impl->os_stack_trace_getter()->UponLeavingGTest(); internal::HandleExceptionsInMethodIfSupported(this, &Test::SetUp, "SetUp()"); // We will run the test only if SetUp() was successful. if (!HasFatalFailure()) { impl->os_stack_trace_getter()->UponLeavingGTest(); internal::HandleExceptionsInMethodIfSupported( this, &Test::TestBody, "the test body"); } // However, we want to clean up as much as possible. Hence we will // always call TearDown(), even if SetUp() or the test body has // failed. impl->os_stack_trace_getter()->UponLeavingGTest(); internal::HandleExceptionsInMethodIfSupported( this, &Test::TearDown, "TearDown()"); } // Returns true iff the current test has a fatal failure. bool Test::HasFatalFailure() { return internal::GetUnitTestImpl()->current_test_result()->HasFatalFailure(); } // Returns true iff the current test has a non-fatal failure. bool Test::HasNonfatalFailure() { return internal::GetUnitTestImpl()->current_test_result()-> HasNonfatalFailure(); } // class TestInfo // Constructs a TestInfo object. It assumes ownership of the test factory // object. TestInfo::TestInfo(const std::string& a_test_case_name, const std::string& a_name, const char* a_type_param, const char* a_value_param, internal::TypeId fixture_class_id, internal::TestFactoryBase* factory) : test_case_name_(a_test_case_name), name_(a_name), type_param_(a_type_param ? new std::string(a_type_param) : NULL), value_param_(a_value_param ? new std::string(a_value_param) : NULL), fixture_class_id_(fixture_class_id), should_run_(false), is_disabled_(false), matches_filter_(false), factory_(factory), result_() {} // Destructs a TestInfo object. TestInfo::~TestInfo() { delete factory_; } namespace internal { // Creates a new TestInfo object and registers it with Google Test; // returns the created object. // // Arguments: // // test_case_name: name of the test case // name: name of the test // type_param: the name of the test's type parameter, or NULL if // this is not a typed or a type-parameterized test. // value_param: text representation of the test's value parameter, // or NULL if this is not a value-parameterized test. // fixture_class_id: ID of the test fixture class // set_up_tc: pointer to the function that sets up the test case // tear_down_tc: pointer to the function that tears down the test case // factory: pointer to the factory that creates a test object. // The newly created TestInfo instance will assume // ownership of the factory object. TestInfo* MakeAndRegisterTestInfo( const char* test_case_name, const char* name, const char* type_param, const char* value_param, TypeId fixture_class_id, SetUpTestCaseFunc set_up_tc, TearDownTestCaseFunc tear_down_tc, TestFactoryBase* factory) { TestInfo* const test_info = new TestInfo(test_case_name, name, type_param, value_param, fixture_class_id, factory); GetUnitTestImpl()->AddTestInfo(set_up_tc, tear_down_tc, test_info); return test_info; } #if GTEST_HAS_PARAM_TEST void ReportInvalidTestCaseType(const char* test_case_name, const char* file, int line) { Message errors; errors << "Attempted redefinition of test case " << test_case_name << ".\n" << "All tests in the same test case must use the same test fixture\n" << "class. However, in test case " << test_case_name << ", you tried\n" << "to define a test using a fixture class different from the one\n" << "used earlier. This can happen if the two fixture classes are\n" << "from different namespaces and have the same name. You should\n" << "probably rename one of the classes to put the tests into different\n" << "test cases."; fprintf(stderr, "%s %s", FormatFileLocation(file, line).c_str(), errors.GetString().c_str()); } #endif // GTEST_HAS_PARAM_TEST } // namespace internal namespace { // A predicate that checks the test name of a TestInfo against a known // value. // // This is used for implementation of the TestCase class only. We put // it in the anonymous namespace to prevent polluting the outer // namespace. // // TestNameIs is copyable. class TestNameIs { public: // Constructor. // // TestNameIs has NO default constructor. explicit TestNameIs(const char* name) : name_(name) {} // Returns true iff the test name of test_info matches name_. bool operator()(const TestInfo * test_info) const { return test_info && test_info->name() == name_; } private: std::string name_; }; } // namespace namespace internal { // This method expands all parameterized tests registered with macros TEST_P // and INSTANTIATE_TEST_CASE_P into regular tests and registers those. // This will be done just once during the program runtime. void UnitTestImpl::RegisterParameterizedTests() { #if GTEST_HAS_PARAM_TEST if (!parameterized_tests_registered_) { parameterized_test_registry_.RegisterTests(); parameterized_tests_registered_ = true; } #endif } } // namespace internal // Creates the test object, runs it, records its result, and then // deletes it. void TestInfo::Run() { if (!should_run_) return; // Tells UnitTest where to store test result. internal::UnitTestImpl* const impl = internal::GetUnitTestImpl(); impl->set_current_test_info(this); TestEventListener* repeater = UnitTest::GetInstance()->listeners().repeater(); // Notifies the unit test event listeners that a test is about to start. repeater->OnTestStart(*this); const TimeInMillis start = internal::GetTimeInMillis(); impl->os_stack_trace_getter()->UponLeavingGTest(); // Creates the test object. Test* const test = internal::HandleExceptionsInMethodIfSupported( factory_, &internal::TestFactoryBase::CreateTest, "the test fixture's constructor"); // Runs the test only if the test object was created and its // constructor didn't generate a fatal failure. if ((test != NULL) && !Test::HasFatalFailure()) { // This doesn't throw as all user code that can throw are wrapped into // exception handling code. test->Run(); } // Deletes the test object. impl->os_stack_trace_getter()->UponLeavingGTest(); internal::HandleExceptionsInMethodIfSupported( test, &Test::DeleteSelf_, "the test fixture's destructor"); result_.set_elapsed_time(internal::GetTimeInMillis() - start); // Notifies the unit test event listener that a test has just finished. repeater->OnTestEnd(*this); // Tells UnitTest to stop associating assertion results to this // test. impl->set_current_test_info(NULL); } // class TestCase // Gets the number of successful tests in this test case. int TestCase::successful_test_count() const { return CountIf(test_info_list_, TestPassed); } // Gets the number of failed tests in this test case. int TestCase::failed_test_count() const { return CountIf(test_info_list_, TestFailed); } // Gets the number of disabled tests that will be reported in the XML report. int TestCase::reportable_disabled_test_count() const { return CountIf(test_info_list_, TestReportableDisabled); } // Gets the number of disabled tests in this test case. int TestCase::disabled_test_count() const { return CountIf(test_info_list_, TestDisabled); } // Gets the number of tests to be printed in the XML report. int TestCase::reportable_test_count() const { return CountIf(test_info_list_, TestReportable); } // Get the number of tests in this test case that should run. int TestCase::test_to_run_count() const { return CountIf(test_info_list_, ShouldRunTest); } // Gets the number of all tests. int TestCase::total_test_count() const { return static_cast(test_info_list_.size()); } // Creates a TestCase with the given name. // // Arguments: // // name: name of the test case // a_type_param: the name of the test case's type parameter, or NULL if // this is not a typed or a type-parameterized test case. // set_up_tc: pointer to the function that sets up the test case // tear_down_tc: pointer to the function that tears down the test case TestCase::TestCase(const char* a_name, const char* a_type_param, Test::SetUpTestCaseFunc set_up_tc, Test::TearDownTestCaseFunc tear_down_tc) : name_(a_name), type_param_(a_type_param ? new std::string(a_type_param) : NULL), set_up_tc_(set_up_tc), tear_down_tc_(tear_down_tc), should_run_(false), elapsed_time_(0) { } // Destructor of TestCase. TestCase::~TestCase() { // Deletes every Test in the collection. ForEach(test_info_list_, internal::Delete); } // Returns the i-th test among all the tests. i can range from 0 to // total_test_count() - 1. If i is not in that range, returns NULL. const TestInfo* TestCase::GetTestInfo(int i) const { const int index = GetElementOr(test_indices_, i, -1); return index < 0 ? NULL : test_info_list_[index]; } // Returns the i-th test among all the tests. i can range from 0 to // total_test_count() - 1. If i is not in that range, returns NULL. TestInfo* TestCase::GetMutableTestInfo(int i) { const int index = GetElementOr(test_indices_, i, -1); return index < 0 ? NULL : test_info_list_[index]; } // Adds a test to this test case. Will delete the test upon // destruction of the TestCase object. void TestCase::AddTestInfo(TestInfo * test_info) { test_info_list_.push_back(test_info); test_indices_.push_back(static_cast(test_indices_.size())); } // Runs every test in this TestCase. void TestCase::Run() { if (!should_run_) return; internal::UnitTestImpl* const impl = internal::GetUnitTestImpl(); impl->set_current_test_case(this); TestEventListener* repeater = UnitTest::GetInstance()->listeners().repeater(); repeater->OnTestCaseStart(*this); impl->os_stack_trace_getter()->UponLeavingGTest(); internal::HandleExceptionsInMethodIfSupported( this, &TestCase::RunSetUpTestCase, "SetUpTestCase()"); const internal::TimeInMillis start = internal::GetTimeInMillis(); for (int i = 0; i < total_test_count(); i++) { GetMutableTestInfo(i)->Run(); } elapsed_time_ = internal::GetTimeInMillis() - start; impl->os_stack_trace_getter()->UponLeavingGTest(); internal::HandleExceptionsInMethodIfSupported( this, &TestCase::RunTearDownTestCase, "TearDownTestCase()"); repeater->OnTestCaseEnd(*this); impl->set_current_test_case(NULL); } // Clears the results of all tests in this test case. void TestCase::ClearResult() { ad_hoc_test_result_.Clear(); ForEach(test_info_list_, TestInfo::ClearTestResult); } // Shuffles the tests in this test case. void TestCase::ShuffleTests(internal::Random* random) { Shuffle(random, &test_indices_); } // Restores the test order to before the first shuffle. void TestCase::UnshuffleTests() { for (size_t i = 0; i < test_indices_.size(); i++) { test_indices_[i] = static_cast(i); } } // Formats a countable noun. Depending on its quantity, either the // singular form or the plural form is used. e.g. // // FormatCountableNoun(1, "formula", "formuli") returns "1 formula". // FormatCountableNoun(5, "book", "books") returns "5 books". static std::string FormatCountableNoun(int count, const char * singular_form, const char * plural_form) { return internal::StreamableToString(count) + " " + (count == 1 ? singular_form : plural_form); } // Formats the count of tests. static std::string FormatTestCount(int test_count) { return FormatCountableNoun(test_count, "test", "tests"); } // Formats the count of test cases. static std::string FormatTestCaseCount(int test_case_count) { return FormatCountableNoun(test_case_count, "test case", "test cases"); } // Converts a TestPartResult::Type enum to human-friendly string // representation. Both kNonFatalFailure and kFatalFailure are translated // to "Failure", as the user usually doesn't care about the difference // between the two when viewing the test result. static const char * TestPartResultTypeToString(TestPartResult::Type type) { switch (type) { case TestPartResult::kSuccess: return "Success"; case TestPartResult::kNonFatalFailure: case TestPartResult::kFatalFailure: #ifdef _MSC_VER return "error: "; #else return "Failure\n"; #endif default: return "Unknown result type"; } } namespace internal { // Prints a TestPartResult to an std::string. static std::string PrintTestPartResultToString( const TestPartResult& test_part_result) { return (Message() << internal::FormatFileLocation(test_part_result.file_name(), test_part_result.line_number()) << " " << TestPartResultTypeToString(test_part_result.type()) << test_part_result.message()).GetString(); } // Prints a TestPartResult. static void PrintTestPartResult(const TestPartResult& test_part_result) { const std::string& result = PrintTestPartResultToString(test_part_result); printf("%s\n", result.c_str()); fflush(stdout); // If the test program runs in Visual Studio or a debugger, the // following statements add the test part result message to the Output // window such that the user can double-click on it to jump to the // corresponding source code location; otherwise they do nothing. #if GTEST_OS_WINDOWS && !GTEST_OS_WINDOWS_MOBILE // We don't call OutputDebugString*() on Windows Mobile, as printing // to stdout is done by OutputDebugString() there already - we don't // want the same message printed twice. ::OutputDebugStringA(result.c_str()); ::OutputDebugStringA("\n"); #endif } // class PrettyUnitTestResultPrinter enum GTestColor { COLOR_DEFAULT, COLOR_RED, COLOR_GREEN, COLOR_YELLOW }; #if GTEST_OS_WINDOWS && !GTEST_OS_WINDOWS_MOBILE // Returns the character attribute for the given color. WORD GetColorAttribute(GTestColor color) { switch (color) { case COLOR_RED: return FOREGROUND_RED; case COLOR_GREEN: return FOREGROUND_GREEN; case COLOR_YELLOW: return FOREGROUND_RED | FOREGROUND_GREEN; default: return 0; } } #else // Returns the ANSI color code for the given color. COLOR_DEFAULT is // an invalid input. const char* GetAnsiColorCode(GTestColor color) { switch (color) { case COLOR_RED: return "1"; case COLOR_GREEN: return "2"; case COLOR_YELLOW: return "3"; default: return NULL; }; } #endif // GTEST_OS_WINDOWS && !GTEST_OS_WINDOWS_MOBILE // Returns true iff Google Test should use colors in the output. bool ShouldUseColor(bool stdout_is_tty) { const char* const gtest_color = GTEST_FLAG(color).c_str(); if (String::CaseInsensitiveCStringEquals(gtest_color, "auto")) { #if GTEST_OS_WINDOWS // On Windows the TERM variable is usually not set, but the // console there does support colors. return stdout_is_tty; #else // On non-Windows platforms, we rely on the TERM variable. const char* const term = posix::GetEnv("TERM"); const bool term_supports_color = String::CStringEquals(term, "xterm") || String::CStringEquals(term, "xterm-color") || String::CStringEquals(term, "xterm-256color") || String::CStringEquals(term, "screen") || String::CStringEquals(term, "screen-256color") || String::CStringEquals(term, "linux") || String::CStringEquals(term, "cygwin"); return stdout_is_tty && term_supports_color; #endif // GTEST_OS_WINDOWS } return String::CaseInsensitiveCStringEquals(gtest_color, "yes") || String::CaseInsensitiveCStringEquals(gtest_color, "true") || String::CaseInsensitiveCStringEquals(gtest_color, "t") || String::CStringEquals(gtest_color, "1"); // We take "yes", "true", "t", and "1" as meaning "yes". If the // value is neither one of these nor "auto", we treat it as "no" to // be conservative. } // Helpers for printing colored strings to stdout. Note that on Windows, we // cannot simply emit special characters and have the terminal change colors. // This routine must actually emit the characters rather than return a string // that would be colored when printed, as can be done on Linux. void ColoredPrintf(GTestColor color, const char* fmt, ...) { va_list args; va_start(args, fmt); #if GTEST_OS_WINDOWS_MOBILE || GTEST_OS_SYMBIAN || GTEST_OS_ZOS || GTEST_OS_IOS const bool use_color = false; #else static const bool in_color_mode = ShouldUseColor(posix::IsATTY(posix::FileNo(stdout)) != 0); const bool use_color = in_color_mode && (color != COLOR_DEFAULT); #endif // GTEST_OS_WINDOWS_MOBILE || GTEST_OS_SYMBIAN || GTEST_OS_ZOS // The '!= 0' comparison is necessary to satisfy MSVC 7.1. if (!use_color) { vprintf(fmt, args); va_end(args); return; } #if GTEST_OS_WINDOWS && !GTEST_OS_WINDOWS_MOBILE const HANDLE stdout_handle = GetStdHandle(STD_OUTPUT_HANDLE); // Gets the current text color. CONSOLE_SCREEN_BUFFER_INFO buffer_info; GetConsoleScreenBufferInfo(stdout_handle, &buffer_info); const WORD old_color_attrs = buffer_info.wAttributes; // We need to flush the stream buffers into the console before each // SetConsoleTextAttribute call lest it affect the text that is already // printed but has not yet reached the console. fflush(stdout); SetConsoleTextAttribute(stdout_handle, GetColorAttribute(color) | FOREGROUND_INTENSITY); vprintf(fmt, args); fflush(stdout); // Restores the text color. SetConsoleTextAttribute(stdout_handle, old_color_attrs); #else printf("\033[0;3%sm", GetAnsiColorCode(color)); vprintf(fmt, args); printf("\033[m"); // Resets the terminal to default. #endif // GTEST_OS_WINDOWS && !GTEST_OS_WINDOWS_MOBILE va_end(args); } // Text printed in Google Test's text output and --gunit_list_tests // output to label the type parameter and value parameter for a test. static const char kTypeParamLabel[] = "TypeParam"; static const char kValueParamLabel[] = "GetParam()"; void PrintFullTestCommentIfPresent(const TestInfo& test_info) { const char* const type_param = test_info.type_param(); const char* const value_param = test_info.value_param(); if (type_param != NULL || value_param != NULL) { printf(", where "); if (type_param != NULL) { printf("%s = %s", kTypeParamLabel, type_param); if (value_param != NULL) printf(" and "); } if (value_param != NULL) { printf("%s = %s", kValueParamLabel, value_param); } } } // This class implements the TestEventListener interface. // // Class PrettyUnitTestResultPrinter is copyable. class PrettyUnitTestResultPrinter : public TestEventListener { public: PrettyUnitTestResultPrinter() {} static void PrintTestName(const char * test_case, const char * test) { printf("%s.%s", test_case, test); } // The following methods override what's in the TestEventListener class. virtual void OnTestProgramStart(const UnitTest& /*unit_test*/) {} virtual void OnTestIterationStart(const UnitTest& unit_test, int iteration); virtual void OnEnvironmentsSetUpStart(const UnitTest& unit_test); virtual void OnEnvironmentsSetUpEnd(const UnitTest& /*unit_test*/) {} virtual void OnTestCaseStart(const TestCase& test_case); virtual void OnTestStart(const TestInfo& test_info); virtual void OnTestPartResult(const TestPartResult& result); virtual void OnTestEnd(const TestInfo& test_info); virtual void OnTestCaseEnd(const TestCase& test_case); virtual void OnEnvironmentsTearDownStart(const UnitTest& unit_test); virtual void OnEnvironmentsTearDownEnd(const UnitTest& /*unit_test*/) {} virtual void OnTestIterationEnd(const UnitTest& unit_test, int iteration); virtual void OnTestProgramEnd(const UnitTest& /*unit_test*/) {} private: static void PrintFailedTests(const UnitTest& unit_test); }; // Fired before each iteration of tests starts. void PrettyUnitTestResultPrinter::OnTestIterationStart( const UnitTest& unit_test, int iteration) { if (GTEST_FLAG(repeat) != 1) printf("\nRepeating all tests (iteration %d) . . .\n\n", iteration + 1); const char* const filter = GTEST_FLAG(filter).c_str(); // Prints the filter if it's not *. This reminds the user that some // tests may be skipped. if (!String::CStringEquals(filter, kUniversalFilter)) { ColoredPrintf(COLOR_YELLOW, "Note: %s filter = %s\n", GTEST_NAME_, filter); } if (internal::ShouldShard(kTestTotalShards, kTestShardIndex, false)) { const Int32 shard_index = Int32FromEnvOrDie(kTestShardIndex, -1); ColoredPrintf(COLOR_YELLOW, "Note: This is test shard %d of %s.\n", static_cast(shard_index) + 1, internal::posix::GetEnv(kTestTotalShards)); } if (GTEST_FLAG(shuffle)) { ColoredPrintf(COLOR_YELLOW, "Note: Randomizing tests' orders with a seed of %d .\n", unit_test.random_seed()); } ColoredPrintf(COLOR_GREEN, "[==========] "); printf("Running %s from %s.\n", FormatTestCount(unit_test.test_to_run_count()).c_str(), FormatTestCaseCount(unit_test.test_case_to_run_count()).c_str()); fflush(stdout); } void PrettyUnitTestResultPrinter::OnEnvironmentsSetUpStart( const UnitTest& /*unit_test*/) { ColoredPrintf(COLOR_GREEN, "[----------] "); printf("Global test environment set-up.\n"); fflush(stdout); } void PrettyUnitTestResultPrinter::OnTestCaseStart(const TestCase& test_case) { const std::string counts = FormatCountableNoun(test_case.test_to_run_count(), "test", "tests"); ColoredPrintf(COLOR_GREEN, "[----------] "); printf("%s from %s", counts.c_str(), test_case.name()); if (test_case.type_param() == NULL) { printf("\n"); } else { printf(", where %s = %s\n", kTypeParamLabel, test_case.type_param()); } fflush(stdout); } void PrettyUnitTestResultPrinter::OnTestStart(const TestInfo& test_info) { ColoredPrintf(COLOR_GREEN, "[ RUN ] "); PrintTestName(test_info.test_case_name(), test_info.name()); printf("\n"); fflush(stdout); } // Called after an assertion failure. void PrettyUnitTestResultPrinter::OnTestPartResult( const TestPartResult& result) { // If the test part succeeded, we don't need to do anything. if (result.type() == TestPartResult::kSuccess) return; // Print failure message from the assertion (e.g. expected this and got that). PrintTestPartResult(result); fflush(stdout); } void PrettyUnitTestResultPrinter::OnTestEnd(const TestInfo& test_info) { if (test_info.result()->Passed()) { ColoredPrintf(COLOR_GREEN, "[ OK ] "); } else { ColoredPrintf(COLOR_RED, "[ FAILED ] "); } PrintTestName(test_info.test_case_name(), test_info.name()); if (test_info.result()->Failed()) PrintFullTestCommentIfPresent(test_info); if (GTEST_FLAG(print_time)) { printf(" (%s ms)\n", internal::StreamableToString( test_info.result()->elapsed_time()).c_str()); } else { printf("\n"); } fflush(stdout); } void PrettyUnitTestResultPrinter::OnTestCaseEnd(const TestCase& test_case) { if (!GTEST_FLAG(print_time)) return; const std::string counts = FormatCountableNoun(test_case.test_to_run_count(), "test", "tests"); ColoredPrintf(COLOR_GREEN, "[----------] "); printf("%s from %s (%s ms total)\n\n", counts.c_str(), test_case.name(), internal::StreamableToString(test_case.elapsed_time()).c_str()); fflush(stdout); } void PrettyUnitTestResultPrinter::OnEnvironmentsTearDownStart( const UnitTest& /*unit_test*/) { ColoredPrintf(COLOR_GREEN, "[----------] "); printf("Global test environment tear-down\n"); fflush(stdout); } // Internal helper for printing the list of failed tests. void PrettyUnitTestResultPrinter::PrintFailedTests(const UnitTest& unit_test) { const int failed_test_count = unit_test.failed_test_count(); if (failed_test_count == 0) { return; } for (int i = 0; i < unit_test.total_test_case_count(); ++i) { const TestCase& test_case = *unit_test.GetTestCase(i); if (!test_case.should_run() || (test_case.failed_test_count() == 0)) { continue; } for (int j = 0; j < test_case.total_test_count(); ++j) { const TestInfo& test_info = *test_case.GetTestInfo(j); if (!test_info.should_run() || test_info.result()->Passed()) { continue; } ColoredPrintf(COLOR_RED, "[ FAILED ] "); printf("%s.%s", test_case.name(), test_info.name()); PrintFullTestCommentIfPresent(test_info); printf("\n"); } } } void PrettyUnitTestResultPrinter::OnTestIterationEnd(const UnitTest& unit_test, int /*iteration*/) { ColoredPrintf(COLOR_GREEN, "[==========] "); printf("%s from %s ran.", FormatTestCount(unit_test.test_to_run_count()).c_str(), FormatTestCaseCount(unit_test.test_case_to_run_count()).c_str()); if (GTEST_FLAG(print_time)) { printf(" (%s ms total)", internal::StreamableToString(unit_test.elapsed_time()).c_str()); } printf("\n"); ColoredPrintf(COLOR_GREEN, "[ PASSED ] "); printf("%s.\n", FormatTestCount(unit_test.successful_test_count()).c_str()); int num_failures = unit_test.failed_test_count(); if (!unit_test.Passed()) { const int failed_test_count = unit_test.failed_test_count(); ColoredPrintf(COLOR_RED, "[ FAILED ] "); printf("%s, listed below:\n", FormatTestCount(failed_test_count).c_str()); PrintFailedTests(unit_test); printf("\n%2d FAILED %s\n", num_failures, num_failures == 1 ? "TEST" : "TESTS"); } int num_disabled = unit_test.reportable_disabled_test_count(); if (num_disabled && !GTEST_FLAG(also_run_disabled_tests)) { if (!num_failures) { printf("\n"); // Add a spacer if no FAILURE banner is displayed. } ColoredPrintf(COLOR_YELLOW, " YOU HAVE %d DISABLED %s\n\n", num_disabled, num_disabled == 1 ? "TEST" : "TESTS"); } // Ensure that Google Test output is printed before, e.g., heapchecker output. fflush(stdout); } // End PrettyUnitTestResultPrinter // class TestEventRepeater // // This class forwards events to other event listeners. class TestEventRepeater : public TestEventListener { public: TestEventRepeater() : forwarding_enabled_(true) {} virtual ~TestEventRepeater(); void Append(TestEventListener *listener); TestEventListener* Release(TestEventListener* listener); // Controls whether events will be forwarded to listeners_. Set to false // in death test child processes. bool forwarding_enabled() const { return forwarding_enabled_; } void set_forwarding_enabled(bool enable) { forwarding_enabled_ = enable; } virtual void OnTestProgramStart(const UnitTest& unit_test); virtual void OnTestIterationStart(const UnitTest& unit_test, int iteration); virtual void OnEnvironmentsSetUpStart(const UnitTest& unit_test); virtual void OnEnvironmentsSetUpEnd(const UnitTest& unit_test); virtual void OnTestCaseStart(const TestCase& test_case); virtual void OnTestStart(const TestInfo& test_info); virtual void OnTestPartResult(const TestPartResult& result); virtual void OnTestEnd(const TestInfo& test_info); virtual void OnTestCaseEnd(const TestCase& test_case); virtual void OnEnvironmentsTearDownStart(const UnitTest& unit_test); virtual void OnEnvironmentsTearDownEnd(const UnitTest& unit_test); virtual void OnTestIterationEnd(const UnitTest& unit_test, int iteration); virtual void OnTestProgramEnd(const UnitTest& unit_test); private: // Controls whether events will be forwarded to listeners_. Set to false // in death test child processes. bool forwarding_enabled_; // The list of listeners that receive events. std::vector listeners_; GTEST_DISALLOW_COPY_AND_ASSIGN_(TestEventRepeater); }; TestEventRepeater::~TestEventRepeater() { ForEach(listeners_, Delete); } void TestEventRepeater::Append(TestEventListener *listener) { listeners_.push_back(listener); } // TODO(vladl@google.com): Factor the search functionality into Vector::Find. TestEventListener* TestEventRepeater::Release(TestEventListener *listener) { for (size_t i = 0; i < listeners_.size(); ++i) { if (listeners_[i] == listener) { listeners_.erase(listeners_.begin() + i); return listener; } } return NULL; } // Since most methods are very similar, use macros to reduce boilerplate. // This defines a member that forwards the call to all listeners. #define GTEST_REPEATER_METHOD_(Name, Type) \ void TestEventRepeater::Name(const Type& parameter) { \ if (forwarding_enabled_) { \ for (size_t i = 0; i < listeners_.size(); i++) { \ listeners_[i]->Name(parameter); \ } \ } \ } // This defines a member that forwards the call to all listeners in reverse // order. #define GTEST_REVERSE_REPEATER_METHOD_(Name, Type) \ void TestEventRepeater::Name(const Type& parameter) { \ if (forwarding_enabled_) { \ for (int i = static_cast(listeners_.size()) - 1; i >= 0; i--) { \ listeners_[i]->Name(parameter); \ } \ } \ } GTEST_REPEATER_METHOD_(OnTestProgramStart, UnitTest) GTEST_REPEATER_METHOD_(OnEnvironmentsSetUpStart, UnitTest) GTEST_REPEATER_METHOD_(OnTestCaseStart, TestCase) GTEST_REPEATER_METHOD_(OnTestStart, TestInfo) GTEST_REPEATER_METHOD_(OnTestPartResult, TestPartResult) GTEST_REPEATER_METHOD_(OnEnvironmentsTearDownStart, UnitTest) GTEST_REVERSE_REPEATER_METHOD_(OnEnvironmentsSetUpEnd, UnitTest) GTEST_REVERSE_REPEATER_METHOD_(OnEnvironmentsTearDownEnd, UnitTest) GTEST_REVERSE_REPEATER_METHOD_(OnTestEnd, TestInfo) GTEST_REVERSE_REPEATER_METHOD_(OnTestCaseEnd, TestCase) GTEST_REVERSE_REPEATER_METHOD_(OnTestProgramEnd, UnitTest) #undef GTEST_REPEATER_METHOD_ #undef GTEST_REVERSE_REPEATER_METHOD_ void TestEventRepeater::OnTestIterationStart(const UnitTest& unit_test, int iteration) { if (forwarding_enabled_) { for (size_t i = 0; i < listeners_.size(); i++) { listeners_[i]->OnTestIterationStart(unit_test, iteration); } } } void TestEventRepeater::OnTestIterationEnd(const UnitTest& unit_test, int iteration) { if (forwarding_enabled_) { for (int i = static_cast(listeners_.size()) - 1; i >= 0; i--) { listeners_[i]->OnTestIterationEnd(unit_test, iteration); } } } // End TestEventRepeater // This class generates an XML output file. class XmlUnitTestResultPrinter : public EmptyTestEventListener { public: explicit XmlUnitTestResultPrinter(const char* output_file); virtual void OnTestIterationEnd(const UnitTest& unit_test, int iteration); private: // Is c a whitespace character that is normalized to a space character // when it appears in an XML attribute value? static bool IsNormalizableWhitespace(char c) { return c == 0x9 || c == 0xA || c == 0xD; } // May c appear in a well-formed XML document? static bool IsValidXmlCharacter(char c) { return IsNormalizableWhitespace(c) || c >= 0x20; } // Returns an XML-escaped copy of the input string str. If // is_attribute is true, the text is meant to appear as an attribute // value, and normalizable whitespace is preserved by replacing it // with character references. static std::string EscapeXml(const std::string& str, bool is_attribute); // Returns the given string with all characters invalid in XML removed. static std::string RemoveInvalidXmlCharacters(const std::string& str); // Convenience wrapper around EscapeXml when str is an attribute value. static std::string EscapeXmlAttribute(const std::string& str) { return EscapeXml(str, true); } // Convenience wrapper around EscapeXml when str is not an attribute value. static std::string EscapeXmlText(const char* str) { return EscapeXml(str, false); } // Verifies that the given attribute belongs to the given element and // streams the attribute as XML. static void OutputXmlAttribute(std::ostream* stream, const std::string& element_name, const std::string& name, const std::string& value); // Streams an XML CDATA section, escaping invalid CDATA sequences as needed. static void OutputXmlCDataSection(::std::ostream* stream, const char* data); // Streams an XML representation of a TestInfo object. static void OutputXmlTestInfo(::std::ostream* stream, const char* test_case_name, const TestInfo& test_info); // Prints an XML representation of a TestCase object static void PrintXmlTestCase(::std::ostream* stream, const TestCase& test_case); // Prints an XML summary of unit_test to output stream out. static void PrintXmlUnitTest(::std::ostream* stream, const UnitTest& unit_test); // Produces a string representing the test properties in a result as space // delimited XML attributes based on the property key="value" pairs. // When the std::string is not empty, it includes a space at the beginning, // to delimit this attribute from prior attributes. static std::string TestPropertiesAsXmlAttributes(const TestResult& result); // The output file. const std::string output_file_; GTEST_DISALLOW_COPY_AND_ASSIGN_(XmlUnitTestResultPrinter); }; // Creates a new XmlUnitTestResultPrinter. XmlUnitTestResultPrinter::XmlUnitTestResultPrinter(const char* output_file) : output_file_(output_file) { if (output_file_.c_str() == NULL || output_file_.empty()) { fprintf(stderr, "XML output file may not be null\n"); fflush(stderr); exit(EXIT_FAILURE); } } // Called after the unit test ends. void XmlUnitTestResultPrinter::OnTestIterationEnd(const UnitTest& unit_test, int /*iteration*/) { FILE* xmlout = NULL; FilePath output_file(output_file_); FilePath output_dir(output_file.RemoveFileName()); if (output_dir.CreateDirectoriesRecursively()) { xmlout = posix::FOpen(output_file_.c_str(), "w"); } if (xmlout == NULL) { // TODO(wan): report the reason of the failure. // // We don't do it for now as: // // 1. There is no urgent need for it. // 2. It's a bit involved to make the errno variable thread-safe on // all three operating systems (Linux, Windows, and Mac OS). // 3. To interpret the meaning of errno in a thread-safe way, // we need the strerror_r() function, which is not available on // Windows. fprintf(stderr, "Unable to open file \"%s\"\n", output_file_.c_str()); fflush(stderr); exit(EXIT_FAILURE); } std::stringstream stream; PrintXmlUnitTest(&stream, unit_test); fprintf(xmlout, "%s", StringStreamToString(&stream).c_str()); fclose(xmlout); } // Returns an XML-escaped copy of the input string str. If is_attribute // is true, the text is meant to appear as an attribute value, and // normalizable whitespace is preserved by replacing it with character // references. // // Invalid XML characters in str, if any, are stripped from the output. // It is expected that most, if not all, of the text processed by this // module will consist of ordinary English text. // If this module is ever modified to produce version 1.1 XML output, // most invalid characters can be retained using character references. // TODO(wan): It might be nice to have a minimally invasive, human-readable // escaping scheme for invalid characters, rather than dropping them. std::string XmlUnitTestResultPrinter::EscapeXml( const std::string& str, bool is_attribute) { Message m; for (size_t i = 0; i < str.size(); ++i) { const char ch = str[i]; switch (ch) { case '<': m << "<"; break; case '>': m << ">"; break; case '&': m << "&"; break; case '\'': if (is_attribute) m << "'"; else m << '\''; break; case '"': if (is_attribute) m << """; else m << '"'; break; default: if (IsValidXmlCharacter(ch)) { if (is_attribute && IsNormalizableWhitespace(ch)) m << "&#x" << String::FormatByte(static_cast(ch)) << ";"; else m << ch; } break; } } return m.GetString(); } // Returns the given string with all characters invalid in XML removed. // Currently invalid characters are dropped from the string. An // alternative is to replace them with certain characters such as . or ?. std::string XmlUnitTestResultPrinter::RemoveInvalidXmlCharacters( const std::string& str) { std::string output; output.reserve(str.size()); for (std::string::const_iterator it = str.begin(); it != str.end(); ++it) if (IsValidXmlCharacter(*it)) output.push_back(*it); return output; } // The following routines generate an XML representation of a UnitTest // object. // // This is how Google Test concepts map to the DTD: // // <-- corresponds to a UnitTest object // <-- corresponds to a TestCase object // <-- corresponds to a TestInfo object // ... // ... // ... // <-- individual assertion failures // // // // Formats the given time in milliseconds as seconds. std::string FormatTimeInMillisAsSeconds(TimeInMillis ms) { ::std::stringstream ss; ss << ms/1000.0; return ss.str(); } // Converts the given epoch time in milliseconds to a date string in the ISO // 8601 format, without the timezone information. std::string FormatEpochTimeInMillisAsIso8601(TimeInMillis ms) { // Using non-reentrant version as localtime_r is not portable. time_t seconds = static_cast(ms / 1000); #ifdef _MSC_VER # pragma warning(push) // Saves the current warning state. # pragma warning(disable:4996) // Temporarily disables warning 4996 // (function or variable may be unsafe). const struct tm* const time_struct = localtime(&seconds); // NOLINT # pragma warning(pop) // Restores the warning state again. #else const struct tm* const time_struct = localtime(&seconds); // NOLINT #endif if (time_struct == NULL) return ""; // Invalid ms value // YYYY-MM-DDThh:mm:ss return StreamableToString(time_struct->tm_year + 1900) + "-" + String::FormatIntWidth2(time_struct->tm_mon + 1) + "-" + String::FormatIntWidth2(time_struct->tm_mday) + "T" + String::FormatIntWidth2(time_struct->tm_hour) + ":" + String::FormatIntWidth2(time_struct->tm_min) + ":" + String::FormatIntWidth2(time_struct->tm_sec); } // Streams an XML CDATA section, escaping invalid CDATA sequences as needed. void XmlUnitTestResultPrinter::OutputXmlCDataSection(::std::ostream* stream, const char* data) { const char* segment = data; *stream << ""); if (next_segment != NULL) { stream->write( segment, static_cast(next_segment - segment)); *stream << "]]>]]>"); } else { *stream << segment; break; } } *stream << "]]>"; } void XmlUnitTestResultPrinter::OutputXmlAttribute( std::ostream* stream, const std::string& element_name, const std::string& name, const std::string& value) { const std::vector& allowed_names = GetReservedAttributesForElement(element_name); GTEST_CHECK_(std::find(allowed_names.begin(), allowed_names.end(), name) != allowed_names.end()) << "Attribute " << name << " is not allowed for element <" << element_name << ">."; *stream << " " << name << "=\"" << EscapeXmlAttribute(value) << "\""; } // Prints an XML representation of a TestInfo object. // TODO(wan): There is also value in printing properties with the plain printer. void XmlUnitTestResultPrinter::OutputXmlTestInfo(::std::ostream* stream, const char* test_case_name, const TestInfo& test_info) { const TestResult& result = *test_info.result(); const std::string kTestcase = "testcase"; *stream << " \n"; } const string location = internal::FormatCompilerIndependentFileLocation( part.file_name(), part.line_number()); const string summary = location + "\n" + part.summary(); *stream << " "; const string detail = location + "\n" + part.message(); OutputXmlCDataSection(stream, RemoveInvalidXmlCharacters(detail).c_str()); *stream << "\n"; } } if (failures == 0) *stream << " />\n"; else *stream << " \n"; } // Prints an XML representation of a TestCase object void XmlUnitTestResultPrinter::PrintXmlTestCase(std::ostream* stream, const TestCase& test_case) { const std::string kTestsuite = "testsuite"; *stream << " <" << kTestsuite; OutputXmlAttribute(stream, kTestsuite, "name", test_case.name()); OutputXmlAttribute(stream, kTestsuite, "tests", StreamableToString(test_case.reportable_test_count())); OutputXmlAttribute(stream, kTestsuite, "failures", StreamableToString(test_case.failed_test_count())); OutputXmlAttribute( stream, kTestsuite, "disabled", StreamableToString(test_case.reportable_disabled_test_count())); OutputXmlAttribute(stream, kTestsuite, "errors", "0"); OutputXmlAttribute(stream, kTestsuite, "time", FormatTimeInMillisAsSeconds(test_case.elapsed_time())); *stream << TestPropertiesAsXmlAttributes(test_case.ad_hoc_test_result()) << ">\n"; for (int i = 0; i < test_case.total_test_count(); ++i) { if (test_case.GetTestInfo(i)->is_reportable()) OutputXmlTestInfo(stream, test_case.name(), *test_case.GetTestInfo(i)); } *stream << " \n"; } // Prints an XML summary of unit_test to output stream out. void XmlUnitTestResultPrinter::PrintXmlUnitTest(std::ostream* stream, const UnitTest& unit_test) { const std::string kTestsuites = "testsuites"; *stream << "\n"; *stream << "<" << kTestsuites; OutputXmlAttribute(stream, kTestsuites, "tests", StreamableToString(unit_test.reportable_test_count())); OutputXmlAttribute(stream, kTestsuites, "failures", StreamableToString(unit_test.failed_test_count())); OutputXmlAttribute( stream, kTestsuites, "disabled", StreamableToString(unit_test.reportable_disabled_test_count())); OutputXmlAttribute(stream, kTestsuites, "errors", "0"); OutputXmlAttribute( stream, kTestsuites, "timestamp", FormatEpochTimeInMillisAsIso8601(unit_test.start_timestamp())); OutputXmlAttribute(stream, kTestsuites, "time", FormatTimeInMillisAsSeconds(unit_test.elapsed_time())); if (GTEST_FLAG(shuffle)) { OutputXmlAttribute(stream, kTestsuites, "random_seed", StreamableToString(unit_test.random_seed())); } *stream << TestPropertiesAsXmlAttributes(unit_test.ad_hoc_test_result()); OutputXmlAttribute(stream, kTestsuites, "name", "AllTests"); *stream << ">\n"; for (int i = 0; i < unit_test.total_test_case_count(); ++i) { if (unit_test.GetTestCase(i)->reportable_test_count() > 0) PrintXmlTestCase(stream, *unit_test.GetTestCase(i)); } *stream << "\n"; } // Produces a string representing the test properties in a result as space // delimited XML attributes based on the property key="value" pairs. std::string XmlUnitTestResultPrinter::TestPropertiesAsXmlAttributes( const TestResult& result) { Message attributes; for (int i = 0; i < result.test_property_count(); ++i) { const TestProperty& property = result.GetTestProperty(i); attributes << " " << property.key() << "=" << "\"" << EscapeXmlAttribute(property.value()) << "\""; } return attributes.GetString(); } // End XmlUnitTestResultPrinter #if GTEST_CAN_STREAM_RESULTS_ // Checks if str contains '=', '&', '%' or '\n' characters. If yes, // replaces them by "%xx" where xx is their hexadecimal value. For // example, replaces "=" with "%3D". This algorithm is O(strlen(str)) // in both time and space -- important as the input str may contain an // arbitrarily long test failure message and stack trace. string StreamingListener::UrlEncode(const char* str) { string result; result.reserve(strlen(str) + 1); for (char ch = *str; ch != '\0'; ch = *++str) { switch (ch) { case '%': case '=': case '&': case '\n': result.append("%" + String::FormatByte(static_cast(ch))); break; default: result.push_back(ch); break; } } return result; } void StreamingListener::SocketWriter::MakeConnection() { GTEST_CHECK_(sockfd_ == -1) << "MakeConnection() can't be called when there is already a connection."; addrinfo hints; memset(&hints, 0, sizeof(hints)); hints.ai_family = AF_UNSPEC; // To allow both IPv4 and IPv6 addresses. hints.ai_socktype = SOCK_STREAM; addrinfo* servinfo = NULL; // Use the getaddrinfo() to get a linked list of IP addresses for // the given host name. const int error_num = getaddrinfo( host_name_.c_str(), port_num_.c_str(), &hints, &servinfo); if (error_num != 0) { GTEST_LOG_(WARNING) << "stream_result_to: getaddrinfo() failed: " << gai_strerror(error_num); } // Loop through all the results and connect to the first we can. for (addrinfo* cur_addr = servinfo; sockfd_ == -1 && cur_addr != NULL; cur_addr = cur_addr->ai_next) { sockfd_ = socket( cur_addr->ai_family, cur_addr->ai_socktype, cur_addr->ai_protocol); if (sockfd_ != -1) { // Connect the client socket to the server socket. if (connect(sockfd_, cur_addr->ai_addr, cur_addr->ai_addrlen) == -1) { close(sockfd_); sockfd_ = -1; } } } freeaddrinfo(servinfo); // all done with this structure if (sockfd_ == -1) { GTEST_LOG_(WARNING) << "stream_result_to: failed to connect to " << host_name_ << ":" << port_num_; } } // End of class Streaming Listener #endif // GTEST_CAN_STREAM_RESULTS__ // Class ScopedTrace // Pushes the given source file location and message onto a per-thread // trace stack maintained by Google Test. ScopedTrace::ScopedTrace(const char* file, int line, const Message& message) GTEST_LOCK_EXCLUDED_(&UnitTest::mutex_) { TraceInfo trace; trace.file = file; trace.line = line; trace.message = message.GetString(); UnitTest::GetInstance()->PushGTestTrace(trace); } // Pops the info pushed by the c'tor. ScopedTrace::~ScopedTrace() GTEST_LOCK_EXCLUDED_(&UnitTest::mutex_) { UnitTest::GetInstance()->PopGTestTrace(); } // class OsStackTraceGetter // Returns the current OS stack trace as an std::string. Parameters: // // max_depth - the maximum number of stack frames to be included // in the trace. // skip_count - the number of top frames to be skipped; doesn't count // against max_depth. // string OsStackTraceGetter::CurrentStackTrace(int /* max_depth */, int /* skip_count */) GTEST_LOCK_EXCLUDED_(mutex_) { return ""; } void OsStackTraceGetter::UponLeavingGTest() GTEST_LOCK_EXCLUDED_(mutex_) { } const char* const OsStackTraceGetter::kElidedFramesMarker = "... " GTEST_NAME_ " internal frames ..."; // A helper class that creates the premature-exit file in its // constructor and deletes the file in its destructor. class ScopedPrematureExitFile { public: explicit ScopedPrematureExitFile(const char* premature_exit_filepath) : premature_exit_filepath_(premature_exit_filepath) { // If a path to the premature-exit file is specified... if (premature_exit_filepath != NULL && *premature_exit_filepath != '\0') { // create the file with a single "0" character in it. I/O // errors are ignored as there's nothing better we can do and we // don't want to fail the test because of this. FILE* pfile = posix::FOpen(premature_exit_filepath, "w"); fwrite("0", 1, 1, pfile); fclose(pfile); } } ~ScopedPrematureExitFile() { if (premature_exit_filepath_ != NULL && *premature_exit_filepath_ != '\0') { remove(premature_exit_filepath_); } } private: const char* const premature_exit_filepath_; GTEST_DISALLOW_COPY_AND_ASSIGN_(ScopedPrematureExitFile); }; } // namespace internal // class TestEventListeners TestEventListeners::TestEventListeners() : repeater_(new internal::TestEventRepeater()), default_result_printer_(NULL), default_xml_generator_(NULL) { } TestEventListeners::~TestEventListeners() { delete repeater_; } // Returns the standard listener responsible for the default console // output. Can be removed from the listeners list to shut down default // console output. Note that removing this object from the listener list // with Release transfers its ownership to the user. void TestEventListeners::Append(TestEventListener* listener) { repeater_->Append(listener); } // Removes the given event listener from the list and returns it. It then // becomes the caller's responsibility to delete the listener. Returns // NULL if the listener is not found in the list. TestEventListener* TestEventListeners::Release(TestEventListener* listener) { if (listener == default_result_printer_) default_result_printer_ = NULL; else if (listener == default_xml_generator_) default_xml_generator_ = NULL; return repeater_->Release(listener); } // Returns repeater that broadcasts the TestEventListener events to all // subscribers. TestEventListener* TestEventListeners::repeater() { return repeater_; } // Sets the default_result_printer attribute to the provided listener. // The listener is also added to the listener list and previous // default_result_printer is removed from it and deleted. The listener can // also be NULL in which case it will not be added to the list. Does // nothing if the previous and the current listener objects are the same. void TestEventListeners::SetDefaultResultPrinter(TestEventListener* listener) { if (default_result_printer_ != listener) { // It is an error to pass this method a listener that is already in the // list. delete Release(default_result_printer_); default_result_printer_ = listener; if (listener != NULL) Append(listener); } } // Sets the default_xml_generator attribute to the provided listener. The // listener is also added to the listener list and previous // default_xml_generator is removed from it and deleted. The listener can // also be NULL in which case it will not be added to the list. Does // nothing if the previous and the current listener objects are the same. void TestEventListeners::SetDefaultXmlGenerator(TestEventListener* listener) { if (default_xml_generator_ != listener) { // It is an error to pass this method a listener that is already in the // list. delete Release(default_xml_generator_); default_xml_generator_ = listener; if (listener != NULL) Append(listener); } } // Controls whether events will be forwarded by the repeater to the // listeners in the list. bool TestEventListeners::EventForwardingEnabled() const { return repeater_->forwarding_enabled(); } void TestEventListeners::SuppressEventForwarding() { repeater_->set_forwarding_enabled(false); } // class UnitTest // Gets the singleton UnitTest object. The first time this method is // called, a UnitTest object is constructed and returned. Consecutive // calls will return the same object. // // We don't protect this under mutex_ as a user is not supposed to // call this before main() starts, from which point on the return // value will never change. UnitTest* UnitTest::GetInstance() { // When compiled with MSVC 7.1 in optimized mode, destroying the // UnitTest object upon exiting the program messes up the exit code, // causing successful tests to appear failed. We have to use a // different implementation in this case to bypass the compiler bug. // This implementation makes the compiler happy, at the cost of // leaking the UnitTest object. // CodeGear C++Builder insists on a public destructor for the // default implementation. Use this implementation to keep good OO // design with private destructor. #if (_MSC_VER == 1310 && !defined(_DEBUG)) || defined(__BORLANDC__) static UnitTest* const instance = new UnitTest; return instance; #else static UnitTest instance; return &instance; #endif // (_MSC_VER == 1310 && !defined(_DEBUG)) || defined(__BORLANDC__) } // Gets the number of successful test cases. int UnitTest::successful_test_case_count() const { return impl()->successful_test_case_count(); } // Gets the number of failed test cases. int UnitTest::failed_test_case_count() const { return impl()->failed_test_case_count(); } // Gets the number of all test cases. int UnitTest::total_test_case_count() const { return impl()->total_test_case_count(); } // Gets the number of all test cases that contain at least one test // that should run. int UnitTest::test_case_to_run_count() const { return impl()->test_case_to_run_count(); } // Gets the number of successful tests. int UnitTest::successful_test_count() const { return impl()->successful_test_count(); } // Gets the number of failed tests. int UnitTest::failed_test_count() const { return impl()->failed_test_count(); } // Gets the number of disabled tests that will be reported in the XML report. int UnitTest::reportable_disabled_test_count() const { return impl()->reportable_disabled_test_count(); } // Gets the number of disabled tests. int UnitTest::disabled_test_count() const { return impl()->disabled_test_count(); } // Gets the number of tests to be printed in the XML report. int UnitTest::reportable_test_count() const { return impl()->reportable_test_count(); } // Gets the number of all tests. int UnitTest::total_test_count() const { return impl()->total_test_count(); } // Gets the number of tests that should run. int UnitTest::test_to_run_count() const { return impl()->test_to_run_count(); } // Gets the time of the test program start, in ms from the start of the // UNIX epoch. internal::TimeInMillis UnitTest::start_timestamp() const { return impl()->start_timestamp(); } // Gets the elapsed time, in milliseconds. internal::TimeInMillis UnitTest::elapsed_time() const { return impl()->elapsed_time(); } // Returns true iff the unit test passed (i.e. all test cases passed). bool UnitTest::Passed() const { return impl()->Passed(); } // Returns true iff the unit test failed (i.e. some test case failed // or something outside of all tests failed). bool UnitTest::Failed() const { return impl()->Failed(); } // Gets the i-th test case among all the test cases. i can range from 0 to // total_test_case_count() - 1. If i is not in that range, returns NULL. const TestCase* UnitTest::GetTestCase(int i) const { return impl()->GetTestCase(i); } // Returns the TestResult containing information on test failures and // properties logged outside of individual test cases. const TestResult& UnitTest::ad_hoc_test_result() const { return *impl()->ad_hoc_test_result(); } // Gets the i-th test case among all the test cases. i can range from 0 to // total_test_case_count() - 1. If i is not in that range, returns NULL. TestCase* UnitTest::GetMutableTestCase(int i) { return impl()->GetMutableTestCase(i); } // Returns the list of event listeners that can be used to track events // inside Google Test. TestEventListeners& UnitTest::listeners() { return *impl()->listeners(); } // Registers and returns a global test environment. When a test // program is run, all global test environments will be set-up in the // order they were registered. After all tests in the program have // finished, all global test environments will be torn-down in the // *reverse* order they were registered. // // The UnitTest object takes ownership of the given environment. // // We don't protect this under mutex_, as we only support calling it // from the main thread. Environment* UnitTest::AddEnvironment(Environment* env) { if (env == NULL) { return NULL; } impl_->environments().push_back(env); return env; } // Adds a TestPartResult to the current TestResult object. All Google Test // assertion macros (e.g. ASSERT_TRUE, EXPECT_EQ, etc) eventually call // this to report their results. The user code should use the // assertion macros instead of calling this directly. void UnitTest::AddTestPartResult( TestPartResult::Type result_type, const char* file_name, int line_number, const std::string& message, const std::string& os_stack_trace) GTEST_LOCK_EXCLUDED_(mutex_) { Message msg; msg << message; internal::MutexLock lock(&mutex_); if (impl_->gtest_trace_stack().size() > 0) { msg << "\n" << GTEST_NAME_ << " trace:"; for (int i = static_cast(impl_->gtest_trace_stack().size()); i > 0; --i) { const internal::TraceInfo& trace = impl_->gtest_trace_stack()[i - 1]; msg << "\n" << internal::FormatFileLocation(trace.file, trace.line) << " " << trace.message; } } if (os_stack_trace.c_str() != NULL && !os_stack_trace.empty()) { msg << internal::kStackTraceMarker << os_stack_trace; } const TestPartResult result = TestPartResult(result_type, file_name, line_number, msg.GetString().c_str()); impl_->GetTestPartResultReporterForCurrentThread()-> ReportTestPartResult(result); if (result_type != TestPartResult::kSuccess) { // gtest_break_on_failure takes precedence over // gtest_throw_on_failure. This allows a user to set the latter // in the code (perhaps in order to use Google Test assertions // with another testing framework) and specify the former on the // command line for debugging. if (GTEST_FLAG(break_on_failure)) { #if GTEST_OS_WINDOWS // Using DebugBreak on Windows allows gtest to still break into a debugger // when a failure happens and both the --gtest_break_on_failure and // the --gtest_catch_exceptions flags are specified. DebugBreak(); #else // Dereference NULL through a volatile pointer to prevent the compiler // from removing. We use this rather than abort() or __builtin_trap() for // portability: Symbian doesn't implement abort() well, and some debuggers // don't correctly trap abort(). *static_cast(NULL) = 1; #endif // GTEST_OS_WINDOWS } else if (GTEST_FLAG(throw_on_failure)) { #if GTEST_HAS_EXCEPTIONS throw internal::GoogleTestFailureException(result); #else // We cannot call abort() as it generates a pop-up in debug mode // that cannot be suppressed in VC 7.1 or below. exit(1); #endif } } } // Adds a TestProperty to the current TestResult object when invoked from // inside a test, to current TestCase's ad_hoc_test_result_ when invoked // from SetUpTestCase or TearDownTestCase, or to the global property set // when invoked elsewhere. If the result already contains a property with // the same key, the value will be updated. void UnitTest::RecordProperty(const std::string& key, const std::string& value) { impl_->RecordProperty(TestProperty(key, value)); } // Runs all tests in this UnitTest object and prints the result. // Returns 0 if successful, or 1 otherwise. // // We don't protect this under mutex_, as we only support calling it // from the main thread. int UnitTest::Run() { const bool in_death_test_child_process = internal::GTEST_FLAG(internal_run_death_test).length() > 0; // Google Test implements this protocol for catching that a test // program exits before returning control to Google Test: // // 1. Upon start, Google Test creates a file whose absolute path // is specified by the environment variable // TEST_PREMATURE_EXIT_FILE. // 2. When Google Test has finished its work, it deletes the file. // // This allows a test runner to set TEST_PREMATURE_EXIT_FILE before // running a Google-Test-based test program and check the existence // of the file at the end of the test execution to see if it has // exited prematurely. // If we are in the child process of a death test, don't // create/delete the premature exit file, as doing so is unnecessary // and will confuse the parent process. Otherwise, create/delete // the file upon entering/leaving this function. If the program // somehow exits before this function has a chance to return, the // premature-exit file will be left undeleted, causing a test runner // that understands the premature-exit-file protocol to report the // test as having failed. const internal::ScopedPrematureExitFile premature_exit_file( in_death_test_child_process ? NULL : internal::posix::GetEnv("TEST_PREMATURE_EXIT_FILE")); // Captures the value of GTEST_FLAG(catch_exceptions). This value will be // used for the duration of the program. impl()->set_catch_exceptions(GTEST_FLAG(catch_exceptions)); #if GTEST_HAS_SEH // Either the user wants Google Test to catch exceptions thrown by the // tests or this is executing in the context of death test child // process. In either case the user does not want to see pop-up dialogs // about crashes - they are expected. if (impl()->catch_exceptions() || in_death_test_child_process) { # if !GTEST_OS_WINDOWS_MOBILE // SetErrorMode doesn't exist on CE. SetErrorMode(SEM_FAILCRITICALERRORS | SEM_NOALIGNMENTFAULTEXCEPT | SEM_NOGPFAULTERRORBOX | SEM_NOOPENFILEERRORBOX); # endif // !GTEST_OS_WINDOWS_MOBILE # if (defined(_MSC_VER) || GTEST_OS_WINDOWS_MINGW) && !GTEST_OS_WINDOWS_MOBILE // Death test children can be terminated with _abort(). On Windows, // _abort() can show a dialog with a warning message. This forces the // abort message to go to stderr instead. _set_error_mode(_OUT_TO_STDERR); # endif # if _MSC_VER >= 1400 && !GTEST_OS_WINDOWS_MOBILE // In the debug version, Visual Studio pops up a separate dialog // offering a choice to debug the aborted program. We need to suppress // this dialog or it will pop up for every EXPECT/ASSERT_DEATH statement // executed. Google Test will notify the user of any unexpected // failure via stderr. // // VC++ doesn't define _set_abort_behavior() prior to the version 8.0. // Users of prior VC versions shall suffer the agony and pain of // clicking through the countless debug dialogs. // TODO(vladl@google.com): find a way to suppress the abort dialog() in the // debug mode when compiled with VC 7.1 or lower. if (!GTEST_FLAG(break_on_failure)) _set_abort_behavior( 0x0, // Clear the following flags: _WRITE_ABORT_MSG | _CALL_REPORTFAULT); // pop-up window, core dump. # endif } #endif // GTEST_HAS_SEH return internal::HandleExceptionsInMethodIfSupported( impl(), &internal::UnitTestImpl::RunAllTests, "auxiliary test code (environments or event listeners)") ? 0 : 1; } // Returns the working directory when the first TEST() or TEST_F() was // executed. const char* UnitTest::original_working_dir() const { return impl_->original_working_dir_.c_str(); } // Returns the TestCase object for the test that's currently running, // or NULL if no test is running. const TestCase* UnitTest::current_test_case() const GTEST_LOCK_EXCLUDED_(mutex_) { internal::MutexLock lock(&mutex_); return impl_->current_test_case(); } // Returns the TestInfo object for the test that's currently running, // or NULL if no test is running. const TestInfo* UnitTest::current_test_info() const GTEST_LOCK_EXCLUDED_(mutex_) { internal::MutexLock lock(&mutex_); return impl_->current_test_info(); } // Returns the random seed used at the start of the current test run. int UnitTest::random_seed() const { return impl_->random_seed(); } #if GTEST_HAS_PARAM_TEST // Returns ParameterizedTestCaseRegistry object used to keep track of // value-parameterized tests and instantiate and register them. internal::ParameterizedTestCaseRegistry& UnitTest::parameterized_test_registry() GTEST_LOCK_EXCLUDED_(mutex_) { return impl_->parameterized_test_registry(); } #endif // GTEST_HAS_PARAM_TEST // Creates an empty UnitTest. UnitTest::UnitTest() { impl_ = new internal::UnitTestImpl(this); } // Destructor of UnitTest. UnitTest::~UnitTest() { delete impl_; } // Pushes a trace defined by SCOPED_TRACE() on to the per-thread // Google Test trace stack. void UnitTest::PushGTestTrace(const internal::TraceInfo& trace) GTEST_LOCK_EXCLUDED_(mutex_) { internal::MutexLock lock(&mutex_); impl_->gtest_trace_stack().push_back(trace); } // Pops a trace from the per-thread Google Test trace stack. void UnitTest::PopGTestTrace() GTEST_LOCK_EXCLUDED_(mutex_) { internal::MutexLock lock(&mutex_); impl_->gtest_trace_stack().pop_back(); } namespace internal { UnitTestImpl::UnitTestImpl(UnitTest* parent) : parent_(parent), #ifdef _MSC_VER # pragma warning(push) // Saves the current warning state. # pragma warning(disable:4355) // Temporarily disables warning 4355 // (using this in initializer). default_global_test_part_result_reporter_(this), default_per_thread_test_part_result_reporter_(this), # pragma warning(pop) // Restores the warning state again. #else default_global_test_part_result_reporter_(this), default_per_thread_test_part_result_reporter_(this), #endif // _MSC_VER global_test_part_result_repoter_( &default_global_test_part_result_reporter_), per_thread_test_part_result_reporter_( &default_per_thread_test_part_result_reporter_), #if GTEST_HAS_PARAM_TEST parameterized_test_registry_(), parameterized_tests_registered_(false), #endif // GTEST_HAS_PARAM_TEST last_death_test_case_(-1), current_test_case_(NULL), current_test_info_(NULL), ad_hoc_test_result_(), os_stack_trace_getter_(NULL), post_flag_parse_init_performed_(false), random_seed_(0), // Will be overridden by the flag before first use. random_(0), // Will be reseeded before first use. start_timestamp_(0), elapsed_time_(0), #if GTEST_HAS_DEATH_TEST death_test_factory_(new DefaultDeathTestFactory), #endif // Will be overridden by the flag before first use. catch_exceptions_(false) { listeners()->SetDefaultResultPrinter(new PrettyUnitTestResultPrinter); } UnitTestImpl::~UnitTestImpl() { // Deletes every TestCase. ForEach(test_cases_, internal::Delete); // Deletes every Environment. ForEach(environments_, internal::Delete); delete os_stack_trace_getter_; } // Adds a TestProperty to the current TestResult object when invoked in a // context of a test, to current test case's ad_hoc_test_result when invoke // from SetUpTestCase/TearDownTestCase, or to the global property set // otherwise. If the result already contains a property with the same key, // the value will be updated. void UnitTestImpl::RecordProperty(const TestProperty& test_property) { std::string xml_element; TestResult* test_result; // TestResult appropriate for property recording. if (current_test_info_ != NULL) { xml_element = "testcase"; test_result = &(current_test_info_->result_); } else if (current_test_case_ != NULL) { xml_element = "testsuite"; test_result = &(current_test_case_->ad_hoc_test_result_); } else { xml_element = "testsuites"; test_result = &ad_hoc_test_result_; } test_result->RecordProperty(xml_element, test_property); } #if GTEST_HAS_DEATH_TEST // Disables event forwarding if the control is currently in a death test // subprocess. Must not be called before InitGoogleTest. void UnitTestImpl::SuppressTestEventsIfInSubprocess() { if (internal_run_death_test_flag_.get() != NULL) listeners()->SuppressEventForwarding(); } #endif // GTEST_HAS_DEATH_TEST // Initializes event listeners performing XML output as specified by // UnitTestOptions. Must not be called before InitGoogleTest. void UnitTestImpl::ConfigureXmlOutput() { const std::string& output_format = UnitTestOptions::GetOutputFormat(); if (output_format == "xml") { listeners()->SetDefaultXmlGenerator(new XmlUnitTestResultPrinter( UnitTestOptions::GetAbsolutePathToOutputFile().c_str())); } else if (output_format != "") { printf("WARNING: unrecognized output format \"%s\" ignored.\n", output_format.c_str()); fflush(stdout); } } #if GTEST_CAN_STREAM_RESULTS_ // Initializes event listeners for streaming test results in string form. // Must not be called before InitGoogleTest. void UnitTestImpl::ConfigureStreamingOutput() { const std::string& target = GTEST_FLAG(stream_result_to); if (!target.empty()) { const size_t pos = target.find(':'); if (pos != std::string::npos) { listeners()->Append(new StreamingListener(target.substr(0, pos), target.substr(pos+1))); } else { printf("WARNING: unrecognized streaming target \"%s\" ignored.\n", target.c_str()); fflush(stdout); } } } #endif // GTEST_CAN_STREAM_RESULTS_ // Performs initialization dependent upon flag values obtained in // ParseGoogleTestFlagsOnly. Is called from InitGoogleTest after the call to // ParseGoogleTestFlagsOnly. In case a user neglects to call InitGoogleTest // this function is also called from RunAllTests. Since this function can be // called more than once, it has to be idempotent. void UnitTestImpl::PostFlagParsingInit() { // Ensures that this function does not execute more than once. if (!post_flag_parse_init_performed_) { post_flag_parse_init_performed_ = true; #if GTEST_HAS_DEATH_TEST InitDeathTestSubprocessControlInfo(); SuppressTestEventsIfInSubprocess(); #endif // GTEST_HAS_DEATH_TEST // Registers parameterized tests. This makes parameterized tests // available to the UnitTest reflection API without running // RUN_ALL_TESTS. RegisterParameterizedTests(); // Configures listeners for XML output. This makes it possible for users // to shut down the default XML output before invoking RUN_ALL_TESTS. ConfigureXmlOutput(); #if GTEST_CAN_STREAM_RESULTS_ // Configures listeners for streaming test results to the specified server. ConfigureStreamingOutput(); #endif // GTEST_CAN_STREAM_RESULTS_ } } // A predicate that checks the name of a TestCase against a known // value. // // This is used for implementation of the UnitTest class only. We put // it in the anonymous namespace to prevent polluting the outer // namespace. // // TestCaseNameIs is copyable. class TestCaseNameIs { public: // Constructor. explicit TestCaseNameIs(const std::string& name) : name_(name) {} // Returns true iff the name of test_case matches name_. bool operator()(const TestCase* test_case) const { return test_case != NULL && strcmp(test_case->name(), name_.c_str()) == 0; } private: std::string name_; }; // Finds and returns a TestCase with the given name. If one doesn't // exist, creates one and returns it. It's the CALLER'S // RESPONSIBILITY to ensure that this function is only called WHEN THE // TESTS ARE NOT SHUFFLED. // // Arguments: // // test_case_name: name of the test case // type_param: the name of the test case's type parameter, or NULL if // this is not a typed or a type-parameterized test case. // set_up_tc: pointer to the function that sets up the test case // tear_down_tc: pointer to the function that tears down the test case TestCase* UnitTestImpl::GetTestCase(const char* test_case_name, const char* type_param, Test::SetUpTestCaseFunc set_up_tc, Test::TearDownTestCaseFunc tear_down_tc) { // Can we find a TestCase with the given name? const std::vector::const_iterator test_case = std::find_if(test_cases_.begin(), test_cases_.end(), TestCaseNameIs(test_case_name)); if (test_case != test_cases_.end()) return *test_case; // No. Let's create one. TestCase* const new_test_case = new TestCase(test_case_name, type_param, set_up_tc, tear_down_tc); // Is this a death test case? if (internal::UnitTestOptions::MatchesFilter(test_case_name, kDeathTestCaseFilter)) { // Yes. Inserts the test case after the last death test case // defined so far. This only works when the test cases haven't // been shuffled. Otherwise we may end up running a death test // after a non-death test. ++last_death_test_case_; test_cases_.insert(test_cases_.begin() + last_death_test_case_, new_test_case); } else { // No. Appends to the end of the list. test_cases_.push_back(new_test_case); } test_case_indices_.push_back(static_cast(test_case_indices_.size())); return new_test_case; } // Helpers for setting up / tearing down the given environment. They // are for use in the ForEach() function. static void SetUpEnvironment(Environment* env) { env->SetUp(); } static void TearDownEnvironment(Environment* env) { env->TearDown(); } // Runs all tests in this UnitTest object, prints the result, and // returns true if all tests are successful. If any exception is // thrown during a test, the test is considered to be failed, but the // rest of the tests will still be run. // // When parameterized tests are enabled, it expands and registers // parameterized tests first in RegisterParameterizedTests(). // All other functions called from RunAllTests() may safely assume that // parameterized tests are ready to be counted and run. bool UnitTestImpl::RunAllTests() { // Makes sure InitGoogleTest() was called. if (!GTestIsInitialized()) { printf("%s", "\nThis test program did NOT call ::testing::InitGoogleTest " "before calling RUN_ALL_TESTS(). Please fix it.\n"); return false; } // Do not run any test if the --help flag was specified. if (g_help_flag) return true; // Repeats the call to the post-flag parsing initialization in case the // user didn't call InitGoogleTest. PostFlagParsingInit(); // Even if sharding is not on, test runners may want to use the // GTEST_SHARD_STATUS_FILE to query whether the test supports the sharding // protocol. internal::WriteToShardStatusFileIfNeeded(); // True iff we are in a subprocess for running a thread-safe-style // death test. bool in_subprocess_for_death_test = false; #if GTEST_HAS_DEATH_TEST in_subprocess_for_death_test = (internal_run_death_test_flag_.get() != NULL); #endif // GTEST_HAS_DEATH_TEST const bool should_shard = ShouldShard(kTestTotalShards, kTestShardIndex, in_subprocess_for_death_test); // Compares the full test names with the filter to decide which // tests to run. const bool has_tests_to_run = FilterTests(should_shard ? HONOR_SHARDING_PROTOCOL : IGNORE_SHARDING_PROTOCOL) > 0; // Lists the tests and exits if the --gtest_list_tests flag was specified. if (GTEST_FLAG(list_tests)) { // This must be called *after* FilterTests() has been called. ListTestsMatchingFilter(); return true; } random_seed_ = GTEST_FLAG(shuffle) ? GetRandomSeedFromFlag(GTEST_FLAG(random_seed)) : 0; // True iff at least one test has failed. bool failed = false; TestEventListener* repeater = listeners()->repeater(); start_timestamp_ = GetTimeInMillis(); repeater->OnTestProgramStart(*parent_); // How many times to repeat the tests? We don't want to repeat them // when we are inside the subprocess of a death test. const int repeat = in_subprocess_for_death_test ? 1 : GTEST_FLAG(repeat); // Repeats forever if the repeat count is negative. const bool forever = repeat < 0; for (int i = 0; forever || i != repeat; i++) { // We want to preserve failures generated by ad-hoc test // assertions executed before RUN_ALL_TESTS(). ClearNonAdHocTestResult(); const TimeInMillis start = GetTimeInMillis(); // Shuffles test cases and tests if requested. if (has_tests_to_run && GTEST_FLAG(shuffle)) { random()->Reseed(random_seed_); // This should be done before calling OnTestIterationStart(), // such that a test event listener can see the actual test order // in the event. ShuffleTests(); } // Tells the unit test event listeners that the tests are about to start. repeater->OnTestIterationStart(*parent_, i); // Runs each test case if there is at least one test to run. if (has_tests_to_run) { // Sets up all environments beforehand. repeater->OnEnvironmentsSetUpStart(*parent_); ForEach(environments_, SetUpEnvironment); repeater->OnEnvironmentsSetUpEnd(*parent_); // Runs the tests only if there was no fatal failure during global // set-up. if (!Test::HasFatalFailure()) { for (int test_index = 0; test_index < total_test_case_count(); test_index++) { GetMutableTestCase(test_index)->Run(); } } // Tears down all environments in reverse order afterwards. repeater->OnEnvironmentsTearDownStart(*parent_); std::for_each(environments_.rbegin(), environments_.rend(), TearDownEnvironment); repeater->OnEnvironmentsTearDownEnd(*parent_); } elapsed_time_ = GetTimeInMillis() - start; // Tells the unit test event listener that the tests have just finished. repeater->OnTestIterationEnd(*parent_, i); // Gets the result and clears it. if (!Passed()) { failed = true; } // Restores the original test order after the iteration. This // allows the user to quickly repro a failure that happens in the // N-th iteration without repeating the first (N - 1) iterations. // This is not enclosed in "if (GTEST_FLAG(shuffle)) { ... }", in // case the user somehow changes the value of the flag somewhere // (it's always safe to unshuffle the tests). UnshuffleTests(); if (GTEST_FLAG(shuffle)) { // Picks a new random seed for each iteration. random_seed_ = GetNextRandomSeed(random_seed_); } } repeater->OnTestProgramEnd(*parent_); return !failed; } // Reads the GTEST_SHARD_STATUS_FILE environment variable, and creates the file // if the variable is present. If a file already exists at this location, this // function will write over it. If the variable is present, but the file cannot // be created, prints an error and exits. void WriteToShardStatusFileIfNeeded() { const char* const test_shard_file = posix::GetEnv(kTestShardStatusFile); if (test_shard_file != NULL) { FILE* const file = posix::FOpen(test_shard_file, "w"); if (file == NULL) { ColoredPrintf(COLOR_RED, "Could not write to the test shard status file \"%s\" " "specified by the %s environment variable.\n", test_shard_file, kTestShardStatusFile); fflush(stdout); exit(EXIT_FAILURE); } fclose(file); } } // Checks whether sharding is enabled by examining the relevant // environment variable values. If the variables are present, // but inconsistent (i.e., shard_index >= total_shards), prints // an error and exits. If in_subprocess_for_death_test, sharding is // disabled because it must only be applied to the original test // process. Otherwise, we could filter out death tests we intended to execute. bool ShouldShard(const char* total_shards_env, const char* shard_index_env, bool in_subprocess_for_death_test) { if (in_subprocess_for_death_test) { return false; } const Int32 total_shards = Int32FromEnvOrDie(total_shards_env, -1); const Int32 shard_index = Int32FromEnvOrDie(shard_index_env, -1); if (total_shards == -1 && shard_index == -1) { return false; } else if (total_shards == -1 && shard_index != -1) { const Message msg = Message() << "Invalid environment variables: you have " << kTestShardIndex << " = " << shard_index << ", but have left " << kTestTotalShards << " unset.\n"; ColoredPrintf(COLOR_RED, msg.GetString().c_str()); fflush(stdout); exit(EXIT_FAILURE); } else if (total_shards != -1 && shard_index == -1) { const Message msg = Message() << "Invalid environment variables: you have " << kTestTotalShards << " = " << total_shards << ", but have left " << kTestShardIndex << " unset.\n"; ColoredPrintf(COLOR_RED, msg.GetString().c_str()); fflush(stdout); exit(EXIT_FAILURE); } else if (shard_index < 0 || shard_index >= total_shards) { const Message msg = Message() << "Invalid environment variables: we require 0 <= " << kTestShardIndex << " < " << kTestTotalShards << ", but you have " << kTestShardIndex << "=" << shard_index << ", " << kTestTotalShards << "=" << total_shards << ".\n"; ColoredPrintf(COLOR_RED, msg.GetString().c_str()); fflush(stdout); exit(EXIT_FAILURE); } return total_shards > 1; } // Parses the environment variable var as an Int32. If it is unset, // returns default_val. If it is not an Int32, prints an error // and aborts. Int32 Int32FromEnvOrDie(const char* var, Int32 default_val) { const char* str_val = posix::GetEnv(var); if (str_val == NULL) { return default_val; } Int32 result; if (!ParseInt32(Message() << "The value of environment variable " << var, str_val, &result)) { exit(EXIT_FAILURE); } return result; } // Given the total number of shards, the shard index, and the test id, // returns true iff the test should be run on this shard. The test id is // some arbitrary but unique non-negative integer assigned to each test // method. Assumes that 0 <= shard_index < total_shards. bool ShouldRunTestOnShard(int total_shards, int shard_index, int test_id) { return (test_id % total_shards) == shard_index; } // Compares the name of each test with the user-specified filter to // decide whether the test should be run, then records the result in // each TestCase and TestInfo object. // If shard_tests == true, further filters tests based on sharding // variables in the environment - see // http://code.google.com/p/googletest/wiki/GoogleTestAdvancedGuide. // Returns the number of tests that should run. int UnitTestImpl::FilterTests(ReactionToSharding shard_tests) { const Int32 total_shards = shard_tests == HONOR_SHARDING_PROTOCOL ? Int32FromEnvOrDie(kTestTotalShards, -1) : -1; const Int32 shard_index = shard_tests == HONOR_SHARDING_PROTOCOL ? Int32FromEnvOrDie(kTestShardIndex, -1) : -1; // num_runnable_tests are the number of tests that will // run across all shards (i.e., match filter and are not disabled). // num_selected_tests are the number of tests to be run on // this shard. int num_runnable_tests = 0; int num_selected_tests = 0; for (size_t i = 0; i < test_cases_.size(); i++) { TestCase* const test_case = test_cases_[i]; const std::string &test_case_name = test_case->name(); test_case->set_should_run(false); for (size_t j = 0; j < test_case->test_info_list().size(); j++) { TestInfo* const test_info = test_case->test_info_list()[j]; const std::string test_name(test_info->name()); // A test is disabled if test case name or test name matches // kDisableTestFilter. const bool is_disabled = internal::UnitTestOptions::MatchesFilter(test_case_name, kDisableTestFilter) || internal::UnitTestOptions::MatchesFilter(test_name, kDisableTestFilter); test_info->is_disabled_ = is_disabled; const bool matches_filter = internal::UnitTestOptions::FilterMatchesTest(test_case_name, test_name); test_info->matches_filter_ = matches_filter; const bool is_runnable = (GTEST_FLAG(also_run_disabled_tests) || !is_disabled) && matches_filter; const bool is_selected = is_runnable && (shard_tests == IGNORE_SHARDING_PROTOCOL || ShouldRunTestOnShard(total_shards, shard_index, num_runnable_tests)); num_runnable_tests += is_runnable; num_selected_tests += is_selected; test_info->should_run_ = is_selected; test_case->set_should_run(test_case->should_run() || is_selected); } } return num_selected_tests; } // Prints the given C-string on a single line by replacing all '\n' // characters with string "\\n". If the output takes more than // max_length characters, only prints the first max_length characters // and "...". static void PrintOnOneLine(const char* str, int max_length) { if (str != NULL) { for (int i = 0; *str != '\0'; ++str) { if (i >= max_length) { printf("..."); break; } if (*str == '\n') { printf("\\n"); i += 2; } else { printf("%c", *str); ++i; } } } } // Prints the names of the tests matching the user-specified filter flag. void UnitTestImpl::ListTestsMatchingFilter() { // Print at most this many characters for each type/value parameter. const int kMaxParamLength = 250; for (size_t i = 0; i < test_cases_.size(); i++) { const TestCase* const test_case = test_cases_[i]; bool printed_test_case_name = false; for (size_t j = 0; j < test_case->test_info_list().size(); j++) { const TestInfo* const test_info = test_case->test_info_list()[j]; if (test_info->matches_filter_) { if (!printed_test_case_name) { printed_test_case_name = true; printf("%s.", test_case->name()); if (test_case->type_param() != NULL) { printf(" # %s = ", kTypeParamLabel); // We print the type parameter on a single line to make // the output easy to parse by a program. PrintOnOneLine(test_case->type_param(), kMaxParamLength); } printf("\n"); } printf(" %s", test_info->name()); if (test_info->value_param() != NULL) { printf(" # %s = ", kValueParamLabel); // We print the value parameter on a single line to make the // output easy to parse by a program. PrintOnOneLine(test_info->value_param(), kMaxParamLength); } printf("\n"); } } } fflush(stdout); } // Sets the OS stack trace getter. // // Does nothing if the input and the current OS stack trace getter are // the same; otherwise, deletes the old getter and makes the input the // current getter. void UnitTestImpl::set_os_stack_trace_getter( OsStackTraceGetterInterface* getter) { if (os_stack_trace_getter_ != getter) { delete os_stack_trace_getter_; os_stack_trace_getter_ = getter; } } // Returns the current OS stack trace getter if it is not NULL; // otherwise, creates an OsStackTraceGetter, makes it the current // getter, and returns it. OsStackTraceGetterInterface* UnitTestImpl::os_stack_trace_getter() { if (os_stack_trace_getter_ == NULL) { os_stack_trace_getter_ = new OsStackTraceGetter; } return os_stack_trace_getter_; } // Returns the TestResult for the test that's currently running, or // the TestResult for the ad hoc test if no test is running. TestResult* UnitTestImpl::current_test_result() { return current_test_info_ ? &(current_test_info_->result_) : &ad_hoc_test_result_; } // Shuffles all test cases, and the tests within each test case, // making sure that death tests are still run first. void UnitTestImpl::ShuffleTests() { // Shuffles the death test cases. ShuffleRange(random(), 0, last_death_test_case_ + 1, &test_case_indices_); // Shuffles the non-death test cases. ShuffleRange(random(), last_death_test_case_ + 1, static_cast(test_cases_.size()), &test_case_indices_); // Shuffles the tests inside each test case. for (size_t i = 0; i < test_cases_.size(); i++) { test_cases_[i]->ShuffleTests(random()); } } // Restores the test cases and tests to their order before the first shuffle. void UnitTestImpl::UnshuffleTests() { for (size_t i = 0; i < test_cases_.size(); i++) { // Unshuffles the tests in each test case. test_cases_[i]->UnshuffleTests(); // Resets the index of each test case. test_case_indices_[i] = static_cast(i); } } // Returns the current OS stack trace as an std::string. // // The maximum number of stack frames to be included is specified by // the gtest_stack_trace_depth flag. The skip_count parameter // specifies the number of top frames to be skipped, which doesn't // count against the number of frames to be included. // // For example, if Foo() calls Bar(), which in turn calls // GetCurrentOsStackTraceExceptTop(..., 1), Foo() will be included in // the trace but Bar() and GetCurrentOsStackTraceExceptTop() won't. std::string GetCurrentOsStackTraceExceptTop(UnitTest* /*unit_test*/, int skip_count) { // We pass skip_count + 1 to skip this wrapper function in addition // to what the user really wants to skip. return GetUnitTestImpl()->CurrentOsStackTraceExceptTop(skip_count + 1); } // Used by the GTEST_SUPPRESS_UNREACHABLE_CODE_WARNING_BELOW_ macro to // suppress unreachable code warnings. namespace { class ClassUniqueToAlwaysTrue {}; } bool IsTrue(bool condition) { return condition; } bool AlwaysTrue() { #if GTEST_HAS_EXCEPTIONS // This condition is always false so AlwaysTrue() never actually throws, // but it makes the compiler think that it may throw. if (IsTrue(false)) throw ClassUniqueToAlwaysTrue(); #endif // GTEST_HAS_EXCEPTIONS return true; } // If *pstr starts with the given prefix, modifies *pstr to be right // past the prefix and returns true; otherwise leaves *pstr unchanged // and returns false. None of pstr, *pstr, and prefix can be NULL. bool SkipPrefix(const char* prefix, const char** pstr) { const size_t prefix_len = strlen(prefix); if (strncmp(*pstr, prefix, prefix_len) == 0) { *pstr += prefix_len; return true; } return false; } // Parses a string as a command line flag. The string should have // the format "--flag=value". When def_optional is true, the "=value" // part can be omitted. // // Returns the value of the flag, or NULL if the parsing failed. const char* ParseFlagValue(const char* str, const char* flag, bool def_optional) { // str and flag must not be NULL. if (str == NULL || flag == NULL) return NULL; // The flag must start with "--" followed by GTEST_FLAG_PREFIX_. const std::string flag_str = std::string("--") + GTEST_FLAG_PREFIX_ + flag; const size_t flag_len = flag_str.length(); if (strncmp(str, flag_str.c_str(), flag_len) != 0) return NULL; // Skips the flag name. const char* flag_end = str + flag_len; // When def_optional is true, it's OK to not have a "=value" part. if (def_optional && (flag_end[0] == '\0')) { return flag_end; } // If def_optional is true and there are more characters after the // flag name, or if def_optional is false, there must be a '=' after // the flag name. if (flag_end[0] != '=') return NULL; // Returns the string after "=". return flag_end + 1; } // Parses a string for a bool flag, in the form of either // "--flag=value" or "--flag". // // In the former case, the value is taken as true as long as it does // not start with '0', 'f', or 'F'. // // In the latter case, the value is taken as true. // // On success, stores the value of the flag in *value, and returns // true. On failure, returns false without changing *value. bool ParseBoolFlag(const char* str, const char* flag, bool* value) { // Gets the value of the flag as a string. const char* const value_str = ParseFlagValue(str, flag, true); // Aborts if the parsing failed. if (value_str == NULL) return false; // Converts the string value to a bool. *value = !(*value_str == '0' || *value_str == 'f' || *value_str == 'F'); return true; } // Parses a string for an Int32 flag, in the form of // "--flag=value". // // On success, stores the value of the flag in *value, and returns // true. On failure, returns false without changing *value. bool ParseInt32Flag(const char* str, const char* flag, Int32* value) { // Gets the value of the flag as a string. const char* const value_str = ParseFlagValue(str, flag, false); // Aborts if the parsing failed. if (value_str == NULL) return false; // Sets *value to the value of the flag. return ParseInt32(Message() << "The value of flag --" << flag, value_str, value); } // Parses a string for a string flag, in the form of // "--flag=value". // // On success, stores the value of the flag in *value, and returns // true. On failure, returns false without changing *value. bool ParseStringFlag(const char* str, const char* flag, std::string* value) { // Gets the value of the flag as a string. const char* const value_str = ParseFlagValue(str, flag, false); // Aborts if the parsing failed. if (value_str == NULL) return false; // Sets *value to the value of the flag. *value = value_str; return true; } // Determines whether a string has a prefix that Google Test uses for its // flags, i.e., starts with GTEST_FLAG_PREFIX_ or GTEST_FLAG_PREFIX_DASH_. // If Google Test detects that a command line flag has its prefix but is not // recognized, it will print its help message. Flags starting with // GTEST_INTERNAL_PREFIX_ followed by "internal_" are considered Google Test // internal flags and do not trigger the help message. static bool HasGoogleTestFlagPrefix(const char* str) { return (SkipPrefix("--", &str) || SkipPrefix("-", &str) || SkipPrefix("/", &str)) && !SkipPrefix(GTEST_FLAG_PREFIX_ "internal_", &str) && (SkipPrefix(GTEST_FLAG_PREFIX_, &str) || SkipPrefix(GTEST_FLAG_PREFIX_DASH_, &str)); } // Prints a string containing code-encoded text. The following escape // sequences can be used in the string to control the text color: // // @@ prints a single '@' character. // @R changes the color to red. // @G changes the color to green. // @Y changes the color to yellow. // @D changes to the default terminal text color. // // TODO(wan@google.com): Write tests for this once we add stdout // capturing to Google Test. static void PrintColorEncoded(const char* str) { GTestColor color = COLOR_DEFAULT; // The current color. // Conceptually, we split the string into segments divided by escape // sequences. Then we print one segment at a time. At the end of // each iteration, the str pointer advances to the beginning of the // next segment. for (;;) { const char* p = strchr(str, '@'); if (p == NULL) { ColoredPrintf(color, "%s", str); return; } ColoredPrintf(color, "%s", std::string(str, p).c_str()); const char ch = p[1]; str = p + 2; if (ch == '@') { ColoredPrintf(color, "@"); } else if (ch == 'D') { color = COLOR_DEFAULT; } else if (ch == 'R') { color = COLOR_RED; } else if (ch == 'G') { color = COLOR_GREEN; } else if (ch == 'Y') { color = COLOR_YELLOW; } else { --str; } } } static const char kColorEncodedHelpMessage[] = "This program contains tests written using " GTEST_NAME_ ". You can use the\n" "following command line flags to control its behavior:\n" "\n" "Test Selection:\n" " @G--" GTEST_FLAG_PREFIX_ "list_tests@D\n" " List the names of all tests instead of running them. The name of\n" " TEST(Foo, Bar) is \"Foo.Bar\".\n" " @G--" GTEST_FLAG_PREFIX_ "filter=@YPOSTIVE_PATTERNS" "[@G-@YNEGATIVE_PATTERNS]@D\n" " Run only the tests whose name matches one of the positive patterns but\n" " none of the negative patterns. '?' matches any single character; '*'\n" " matches any substring; ':' separates two patterns.\n" " @G--" GTEST_FLAG_PREFIX_ "also_run_disabled_tests@D\n" " Run all disabled tests too.\n" "\n" "Test Execution:\n" " @G--" GTEST_FLAG_PREFIX_ "repeat=@Y[COUNT]@D\n" " Run the tests repeatedly; use a negative count to repeat forever.\n" " @G--" GTEST_FLAG_PREFIX_ "shuffle@D\n" " Randomize tests' orders on every iteration.\n" " @G--" GTEST_FLAG_PREFIX_ "random_seed=@Y[NUMBER]@D\n" " Random number seed to use for shuffling test orders (between 1 and\n" " 99999, or 0 to use a seed based on the current time).\n" "\n" "Test Output:\n" " @G--" GTEST_FLAG_PREFIX_ "color=@Y(@Gyes@Y|@Gno@Y|@Gauto@Y)@D\n" " Enable/disable colored output. The default is @Gauto@D.\n" " -@G-" GTEST_FLAG_PREFIX_ "print_time=0@D\n" " Don't print the elapsed time of each test.\n" " @G--" GTEST_FLAG_PREFIX_ "output=xml@Y[@G:@YDIRECTORY_PATH@G" GTEST_PATH_SEP_ "@Y|@G:@YFILE_PATH]@D\n" " Generate an XML report in the given directory or with the given file\n" " name. @YFILE_PATH@D defaults to @Gtest_details.xml@D.\n" #if GTEST_CAN_STREAM_RESULTS_ " @G--" GTEST_FLAG_PREFIX_ "stream_result_to=@YHOST@G:@YPORT@D\n" " Stream test results to the given server.\n" #endif // GTEST_CAN_STREAM_RESULTS_ "\n" "Assertion Behavior:\n" #if GTEST_HAS_DEATH_TEST && !GTEST_OS_WINDOWS " @G--" GTEST_FLAG_PREFIX_ "death_test_style=@Y(@Gfast@Y|@Gthreadsafe@Y)@D\n" " Set the default death test style.\n" #endif // GTEST_HAS_DEATH_TEST && !GTEST_OS_WINDOWS " @G--" GTEST_FLAG_PREFIX_ "break_on_failure@D\n" " Turn assertion failures into debugger break-points.\n" " @G--" GTEST_FLAG_PREFIX_ "throw_on_failure@D\n" " Turn assertion failures into C++ exceptions.\n" " @G--" GTEST_FLAG_PREFIX_ "catch_exceptions=0@D\n" " Do not report exceptions as test failures. Instead, allow them\n" " to crash the program or throw a pop-up (on Windows).\n" "\n" "Except for @G--" GTEST_FLAG_PREFIX_ "list_tests@D, you can alternatively set " "the corresponding\n" "environment variable of a flag (all letters in upper-case). For example, to\n" "disable colored text output, you can either specify @G--" GTEST_FLAG_PREFIX_ "color=no@D or set\n" "the @G" GTEST_FLAG_PREFIX_UPPER_ "COLOR@D environment variable to @Gno@D.\n" "\n" "For more information, please read the " GTEST_NAME_ " documentation at\n" "@G" GTEST_PROJECT_URL_ "@D. If you find a bug in " GTEST_NAME_ "\n" "(not one in your own code or tests), please report it to\n" "@G<" GTEST_DEV_EMAIL_ ">@D.\n"; // Parses the command line for Google Test flags, without initializing // other parts of Google Test. The type parameter CharType can be // instantiated to either char or wchar_t. template void ParseGoogleTestFlagsOnlyImpl(int* argc, CharType** argv) { for (int i = 1; i < *argc; i++) { const std::string arg_string = StreamableToString(argv[i]); const char* const arg = arg_string.c_str(); using internal::ParseBoolFlag; using internal::ParseInt32Flag; using internal::ParseStringFlag; // Do we see a Google Test flag? if (ParseBoolFlag(arg, kAlsoRunDisabledTestsFlag, >EST_FLAG(also_run_disabled_tests)) || ParseBoolFlag(arg, kBreakOnFailureFlag, >EST_FLAG(break_on_failure)) || ParseBoolFlag(arg, kCatchExceptionsFlag, >EST_FLAG(catch_exceptions)) || ParseStringFlag(arg, kColorFlag, >EST_FLAG(color)) || ParseStringFlag(arg, kDeathTestStyleFlag, >EST_FLAG(death_test_style)) || ParseBoolFlag(arg, kDeathTestUseFork, >EST_FLAG(death_test_use_fork)) || ParseStringFlag(arg, kFilterFlag, >EST_FLAG(filter)) || ParseStringFlag(arg, kInternalRunDeathTestFlag, >EST_FLAG(internal_run_death_test)) || ParseBoolFlag(arg, kListTestsFlag, >EST_FLAG(list_tests)) || ParseStringFlag(arg, kOutputFlag, >EST_FLAG(output)) || ParseBoolFlag(arg, kPrintTimeFlag, >EST_FLAG(print_time)) || ParseInt32Flag(arg, kRandomSeedFlag, >EST_FLAG(random_seed)) || ParseInt32Flag(arg, kRepeatFlag, >EST_FLAG(repeat)) || ParseBoolFlag(arg, kShuffleFlag, >EST_FLAG(shuffle)) || ParseInt32Flag(arg, kStackTraceDepthFlag, >EST_FLAG(stack_trace_depth)) || ParseStringFlag(arg, kStreamResultToFlag, >EST_FLAG(stream_result_to)) || ParseBoolFlag(arg, kThrowOnFailureFlag, >EST_FLAG(throw_on_failure)) ) { // Yes. Shift the remainder of the argv list left by one. Note // that argv has (*argc + 1) elements, the last one always being // NULL. The following loop moves the trailing NULL element as // well. for (int j = i; j != *argc; j++) { argv[j] = argv[j + 1]; } // Decrements the argument count. (*argc)--; // We also need to decrement the iterator as we just removed // an element. i--; } else if (arg_string == "--help" || arg_string == "-h" || arg_string == "-?" || arg_string == "/?" || HasGoogleTestFlagPrefix(arg)) { // Both help flag and unrecognized Google Test flags (excluding // internal ones) trigger help display. g_help_flag = true; } } if (g_help_flag) { // We print the help here instead of in RUN_ALL_TESTS(), as the // latter may not be called at all if the user is using Google // Test with another testing framework. PrintColorEncoded(kColorEncodedHelpMessage); } } // Parses the command line for Google Test flags, without initializing // other parts of Google Test. void ParseGoogleTestFlagsOnly(int* argc, char** argv) { ParseGoogleTestFlagsOnlyImpl(argc, argv); } void ParseGoogleTestFlagsOnly(int* argc, wchar_t** argv) { ParseGoogleTestFlagsOnlyImpl(argc, argv); } // The internal implementation of InitGoogleTest(). // // The type parameter CharType can be instantiated to either char or // wchar_t. template void InitGoogleTestImpl(int* argc, CharType** argv) { g_init_gtest_count++; // We don't want to run the initialization code twice. if (g_init_gtest_count != 1) return; if (*argc <= 0) return; internal::g_executable_path = internal::StreamableToString(argv[0]); #if GTEST_HAS_DEATH_TEST g_argvs.clear(); for (int i = 0; i != *argc; i++) { g_argvs.push_back(StreamableToString(argv[i])); } #endif // GTEST_HAS_DEATH_TEST ParseGoogleTestFlagsOnly(argc, argv); GetUnitTestImpl()->PostFlagParsingInit(); } } // namespace internal // Initializes Google Test. This must be called before calling // RUN_ALL_TESTS(). In particular, it parses a command line for the // flags that Google Test recognizes. Whenever a Google Test flag is // seen, it is removed from argv, and *argc is decremented. // // No value is returned. Instead, the Google Test flag variables are // updated. // // Calling the function for the second time has no user-visible effect. void InitGoogleTest(int* argc, char** argv) { internal::InitGoogleTestImpl(argc, argv); } // This overloaded version can be used in Windows programs compiled in // UNICODE mode. void InitGoogleTest(int* argc, wchar_t** argv) { internal::InitGoogleTestImpl(argc, argv); } } // namespace testing // Copyright 2005, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: wan@google.com (Zhanyong Wan), vladl@google.com (Vlad Losev) // // This file implements death tests. #if GTEST_HAS_DEATH_TEST # if GTEST_OS_MAC # include # endif // GTEST_OS_MAC # include # include # include # if GTEST_OS_LINUX # include # endif // GTEST_OS_LINUX # include # if GTEST_OS_WINDOWS # include # else # include # include # endif // GTEST_OS_WINDOWS # if GTEST_OS_QNX # include # endif // GTEST_OS_QNX #endif // GTEST_HAS_DEATH_TEST // Indicates that this translation unit is part of Google Test's // implementation. It must come before gtest-internal-inl.h is // included, or there will be a compiler error. This trick is to // prevent a user from accidentally including gtest-internal-inl.h in // his code. #define GTEST_IMPLEMENTATION_ 1 #undef GTEST_IMPLEMENTATION_ namespace testing { // Constants. // The default death test style. static const char kDefaultDeathTestStyle[] = "fast"; GTEST_DEFINE_string_( death_test_style, internal::StringFromGTestEnv("death_test_style", kDefaultDeathTestStyle), "Indicates how to run a death test in a forked child process: " "\"threadsafe\" (child process re-executes the test binary " "from the beginning, running only the specific death test) or " "\"fast\" (child process runs the death test immediately " "after forking)."); GTEST_DEFINE_bool_( death_test_use_fork, internal::BoolFromGTestEnv("death_test_use_fork", false), "Instructs to use fork()/_exit() instead of clone() in death tests. " "Ignored and always uses fork() on POSIX systems where clone() is not " "implemented. Useful when running under valgrind or similar tools if " "those do not support clone(). Valgrind 3.3.1 will just fail if " "it sees an unsupported combination of clone() flags. " "It is not recommended to use this flag w/o valgrind though it will " "work in 99% of the cases. Once valgrind is fixed, this flag will " "most likely be removed."); namespace internal { GTEST_DEFINE_string_( internal_run_death_test, "", "Indicates the file, line number, temporal index of " "the single death test to run, and a file descriptor to " "which a success code may be sent, all separated by " "the '|' characters. This flag is specified if and only if the current " "process is a sub-process launched for running a thread-safe " "death test. FOR INTERNAL USE ONLY."); } // namespace internal #if GTEST_HAS_DEATH_TEST namespace internal { // Valid only for fast death tests. Indicates the code is running in the // child process of a fast style death test. static bool g_in_fast_death_test_child = false; // Returns a Boolean value indicating whether the caller is currently // executing in the context of the death test child process. Tools such as // Valgrind heap checkers may need this to modify their behavior in death // tests. IMPORTANT: This is an internal utility. Using it may break the // implementation of death tests. User code MUST NOT use it. bool InDeathTestChild() { # if GTEST_OS_WINDOWS // On Windows, death tests are thread-safe regardless of the value of the // death_test_style flag. return !GTEST_FLAG(internal_run_death_test).empty(); # else if (GTEST_FLAG(death_test_style) == "threadsafe") return !GTEST_FLAG(internal_run_death_test).empty(); else return g_in_fast_death_test_child; #endif } } // namespace internal // ExitedWithCode constructor. ExitedWithCode::ExitedWithCode(int exit_code) : exit_code_(exit_code) { } // ExitedWithCode function-call operator. bool ExitedWithCode::operator()(int exit_status) const { # if GTEST_OS_WINDOWS return exit_status == exit_code_; # else return WIFEXITED(exit_status) && WEXITSTATUS(exit_status) == exit_code_; # endif // GTEST_OS_WINDOWS } # if !GTEST_OS_WINDOWS // KilledBySignal constructor. KilledBySignal::KilledBySignal(int signum) : signum_(signum) { } // KilledBySignal function-call operator. bool KilledBySignal::operator()(int exit_status) const { return WIFSIGNALED(exit_status) && WTERMSIG(exit_status) == signum_; } # endif // !GTEST_OS_WINDOWS namespace internal { // Utilities needed for death tests. // Generates a textual description of a given exit code, in the format // specified by wait(2). static std::string ExitSummary(int exit_code) { Message m; # if GTEST_OS_WINDOWS m << "Exited with exit status " << exit_code; # else if (WIFEXITED(exit_code)) { m << "Exited with exit status " << WEXITSTATUS(exit_code); } else if (WIFSIGNALED(exit_code)) { m << "Terminated by signal " << WTERMSIG(exit_code); } # ifdef WCOREDUMP if (WCOREDUMP(exit_code)) { m << " (core dumped)"; } # endif # endif // GTEST_OS_WINDOWS return m.GetString(); } // Returns true if exit_status describes a process that was terminated // by a signal, or exited normally with a nonzero exit code. bool ExitedUnsuccessfully(int exit_status) { return !ExitedWithCode(0)(exit_status); } # if !GTEST_OS_WINDOWS // Generates a textual failure message when a death test finds more than // one thread running, or cannot determine the number of threads, prior // to executing the given statement. It is the responsibility of the // caller not to pass a thread_count of 1. static std::string DeathTestThreadWarning(size_t thread_count) { Message msg; msg << "Death tests use fork(), which is unsafe particularly" << " in a threaded context. For this test, " << GTEST_NAME_ << " "; if (thread_count == 0) msg << "couldn't detect the number of threads."; else msg << "detected " << thread_count << " threads."; return msg.GetString(); } # endif // !GTEST_OS_WINDOWS // Flag characters for reporting a death test that did not die. static const char kDeathTestLived = 'L'; static const char kDeathTestReturned = 'R'; static const char kDeathTestThrew = 'T'; static const char kDeathTestInternalError = 'I'; // An enumeration describing all of the possible ways that a death test can // conclude. DIED means that the process died while executing the test // code; LIVED means that process lived beyond the end of the test code; // RETURNED means that the test statement attempted to execute a return // statement, which is not allowed; THREW means that the test statement // returned control by throwing an exception. IN_PROGRESS means the test // has not yet concluded. // TODO(vladl@google.com): Unify names and possibly values for // AbortReason, DeathTestOutcome, and flag characters above. enum DeathTestOutcome { IN_PROGRESS, DIED, LIVED, RETURNED, THREW }; // Routine for aborting the program which is safe to call from an // exec-style death test child process, in which case the error // message is propagated back to the parent process. Otherwise, the // message is simply printed to stderr. In either case, the program // then exits with status 1. void DeathTestAbort(const std::string& message) { // On a POSIX system, this function may be called from a threadsafe-style // death test child process, which operates on a very small stack. Use // the heap for any additional non-minuscule memory requirements. const InternalRunDeathTestFlag* const flag = GetUnitTestImpl()->internal_run_death_test_flag(); if (flag != NULL) { FILE* parent = posix::FDOpen(flag->write_fd(), "w"); fputc(kDeathTestInternalError, parent); fprintf(parent, "%s", message.c_str()); fflush(parent); _exit(1); } else { fprintf(stderr, "%s", message.c_str()); fflush(stderr); posix::Abort(); } } // A replacement for CHECK that calls DeathTestAbort if the assertion // fails. # define GTEST_DEATH_TEST_CHECK_(expression) \ do { \ if (!::testing::internal::IsTrue(expression)) { \ DeathTestAbort( \ ::std::string("CHECK failed: File ") + __FILE__ + ", line " \ + ::testing::internal::StreamableToString(__LINE__) + ": " \ + #expression); \ } \ } while (::testing::internal::AlwaysFalse()) // This macro is similar to GTEST_DEATH_TEST_CHECK_, but it is meant for // evaluating any system call that fulfills two conditions: it must return // -1 on failure, and set errno to EINTR when it is interrupted and // should be tried again. The macro expands to a loop that repeatedly // evaluates the expression as long as it evaluates to -1 and sets // errno to EINTR. If the expression evaluates to -1 but errno is // something other than EINTR, DeathTestAbort is called. # define GTEST_DEATH_TEST_CHECK_SYSCALL_(expression) \ do { \ int gtest_retval; \ do { \ gtest_retval = (expression); \ } while (gtest_retval == -1 && errno == EINTR); \ if (gtest_retval == -1) { \ DeathTestAbort( \ ::std::string("CHECK failed: File ") + __FILE__ + ", line " \ + ::testing::internal::StreamableToString(__LINE__) + ": " \ + #expression + " != -1"); \ } \ } while (::testing::internal::AlwaysFalse()) // Returns the message describing the last system error in errno. std::string GetLastErrnoDescription() { return errno == 0 ? "" : posix::StrError(errno); } // This is called from a death test parent process to read a failure // message from the death test child process and log it with the FATAL // severity. On Windows, the message is read from a pipe handle. On other // platforms, it is read from a file descriptor. static void FailFromInternalError(int fd) { Message error; char buffer[256]; int num_read; do { while ((num_read = posix::Read(fd, buffer, 255)) > 0) { buffer[num_read] = '\0'; error << buffer; } } while (num_read == -1 && errno == EINTR); if (num_read == 0) { GTEST_LOG_(FATAL) << error.GetString(); } else { const int last_error = errno; GTEST_LOG_(FATAL) << "Error while reading death test internal: " << GetLastErrnoDescription() << " [" << last_error << "]"; } } // Death test constructor. Increments the running death test count // for the current test. DeathTest::DeathTest() { TestInfo* const info = GetUnitTestImpl()->current_test_info(); if (info == NULL) { DeathTestAbort("Cannot run a death test outside of a TEST or " "TEST_F construct"); } } // Creates and returns a death test by dispatching to the current // death test factory. bool DeathTest::Create(const char* statement, const RE* regex, const char* file, int line, DeathTest** test) { return GetUnitTestImpl()->death_test_factory()->Create( statement, regex, file, line, test); } const char* DeathTest::LastMessage() { return last_death_test_message_.c_str(); } void DeathTest::set_last_death_test_message(const std::string& message) { last_death_test_message_ = message; } std::string DeathTest::last_death_test_message_; // Provides cross platform implementation for some death functionality. class DeathTestImpl : public DeathTest { protected: DeathTestImpl(const char* a_statement, const RE* a_regex) : statement_(a_statement), regex_(a_regex), spawned_(false), status_(-1), outcome_(IN_PROGRESS), read_fd_(-1), write_fd_(-1) {} // read_fd_ is expected to be closed and cleared by a derived class. ~DeathTestImpl() { GTEST_DEATH_TEST_CHECK_(read_fd_ == -1); } void Abort(AbortReason reason); virtual bool Passed(bool status_ok); const char* statement() const { return statement_; } const RE* regex() const { return regex_; } bool spawned() const { return spawned_; } void set_spawned(bool is_spawned) { spawned_ = is_spawned; } int status() const { return status_; } void set_status(int a_status) { status_ = a_status; } DeathTestOutcome outcome() const { return outcome_; } void set_outcome(DeathTestOutcome an_outcome) { outcome_ = an_outcome; } int read_fd() const { return read_fd_; } void set_read_fd(int fd) { read_fd_ = fd; } int write_fd() const { return write_fd_; } void set_write_fd(int fd) { write_fd_ = fd; } // Called in the parent process only. Reads the result code of the death // test child process via a pipe, interprets it to set the outcome_ // member, and closes read_fd_. Outputs diagnostics and terminates in // case of unexpected codes. void ReadAndInterpretStatusByte(); private: // The textual content of the code this object is testing. This class // doesn't own this string and should not attempt to delete it. const char* const statement_; // The regular expression which test output must match. DeathTestImpl // doesn't own this object and should not attempt to delete it. const RE* const regex_; // True if the death test child process has been successfully spawned. bool spawned_; // The exit status of the child process. int status_; // How the death test concluded. DeathTestOutcome outcome_; // Descriptor to the read end of the pipe to the child process. It is // always -1 in the child process. The child keeps its write end of the // pipe in write_fd_. int read_fd_; // Descriptor to the child's write end of the pipe to the parent process. // It is always -1 in the parent process. The parent keeps its end of the // pipe in read_fd_. int write_fd_; }; // Called in the parent process only. Reads the result code of the death // test child process via a pipe, interprets it to set the outcome_ // member, and closes read_fd_. Outputs diagnostics and terminates in // case of unexpected codes. void DeathTestImpl::ReadAndInterpretStatusByte() { char flag; int bytes_read; // The read() here blocks until data is available (signifying the // failure of the death test) or until the pipe is closed (signifying // its success), so it's okay to call this in the parent before // the child process has exited. do { bytes_read = posix::Read(read_fd(), &flag, 1); } while (bytes_read == -1 && errno == EINTR); if (bytes_read == 0) { set_outcome(DIED); } else if (bytes_read == 1) { switch (flag) { case kDeathTestReturned: set_outcome(RETURNED); break; case kDeathTestThrew: set_outcome(THREW); break; case kDeathTestLived: set_outcome(LIVED); break; case kDeathTestInternalError: FailFromInternalError(read_fd()); // Does not return. break; default: GTEST_LOG_(FATAL) << "Death test child process reported " << "unexpected status byte (" << static_cast(flag) << ")"; } } else { GTEST_LOG_(FATAL) << "Read from death test child process failed: " << GetLastErrnoDescription(); } GTEST_DEATH_TEST_CHECK_SYSCALL_(posix::Close(read_fd())); set_read_fd(-1); } // Signals that the death test code which should have exited, didn't. // Should be called only in a death test child process. // Writes a status byte to the child's status file descriptor, then // calls _exit(1). void DeathTestImpl::Abort(AbortReason reason) { // The parent process considers the death test to be a failure if // it finds any data in our pipe. So, here we write a single flag byte // to the pipe, then exit. const char status_ch = reason == TEST_DID_NOT_DIE ? kDeathTestLived : reason == TEST_THREW_EXCEPTION ? kDeathTestThrew : kDeathTestReturned; GTEST_DEATH_TEST_CHECK_SYSCALL_(posix::Write(write_fd(), &status_ch, 1)); // We are leaking the descriptor here because on some platforms (i.e., // when built as Windows DLL), destructors of global objects will still // run after calling _exit(). On such systems, write_fd_ will be // indirectly closed from the destructor of UnitTestImpl, causing double // close if it is also closed here. On debug configurations, double close // may assert. As there are no in-process buffers to flush here, we are // relying on the OS to close the descriptor after the process terminates // when the destructors are not run. _exit(1); // Exits w/o any normal exit hooks (we were supposed to crash) } // Returns an indented copy of stderr output for a death test. // This makes distinguishing death test output lines from regular log lines // much easier. static ::std::string FormatDeathTestOutput(const ::std::string& output) { ::std::string ret; for (size_t at = 0; ; ) { const size_t line_end = output.find('\n', at); ret += "[ DEATH ] "; if (line_end == ::std::string::npos) { ret += output.substr(at); break; } ret += output.substr(at, line_end + 1 - at); at = line_end + 1; } return ret; } // Assesses the success or failure of a death test, using both private // members which have previously been set, and one argument: // // Private data members: // outcome: An enumeration describing how the death test // concluded: DIED, LIVED, THREW, or RETURNED. The death test // fails in the latter three cases. // status: The exit status of the child process. On *nix, it is in the // in the format specified by wait(2). On Windows, this is the // value supplied to the ExitProcess() API or a numeric code // of the exception that terminated the program. // regex: A regular expression object to be applied to // the test's captured standard error output; the death test // fails if it does not match. // // Argument: // status_ok: true if exit_status is acceptable in the context of // this particular death test, which fails if it is false // // Returns true iff all of the above conditions are met. Otherwise, the // first failing condition, in the order given above, is the one that is // reported. Also sets the last death test message string. bool DeathTestImpl::Passed(bool status_ok) { if (!spawned()) return false; const std::string error_message = GetCapturedStderr(); bool success = false; Message buffer; buffer << "Death test: " << statement() << "\n"; switch (outcome()) { case LIVED: buffer << " Result: failed to die.\n" << " Error msg:\n" << FormatDeathTestOutput(error_message); break; case THREW: buffer << " Result: threw an exception.\n" << " Error msg:\n" << FormatDeathTestOutput(error_message); break; case RETURNED: buffer << " Result: illegal return in test statement.\n" << " Error msg:\n" << FormatDeathTestOutput(error_message); break; case DIED: if (status_ok) { const bool matched = RE::PartialMatch(error_message.c_str(), *regex()); if (matched) { success = true; } else { buffer << " Result: died but not with expected error.\n" << " Expected: " << regex()->pattern() << "\n" << "Actual msg:\n" << FormatDeathTestOutput(error_message); } } else { buffer << " Result: died but not with expected exit code:\n" << " " << ExitSummary(status()) << "\n" << "Actual msg:\n" << FormatDeathTestOutput(error_message); } break; case IN_PROGRESS: default: GTEST_LOG_(FATAL) << "DeathTest::Passed somehow called before conclusion of test"; } DeathTest::set_last_death_test_message(buffer.GetString()); return success; } # if GTEST_OS_WINDOWS // WindowsDeathTest implements death tests on Windows. Due to the // specifics of starting new processes on Windows, death tests there are // always threadsafe, and Google Test considers the // --gtest_death_test_style=fast setting to be equivalent to // --gtest_death_test_style=threadsafe there. // // A few implementation notes: Like the Linux version, the Windows // implementation uses pipes for child-to-parent communication. But due to // the specifics of pipes on Windows, some extra steps are required: // // 1. The parent creates a communication pipe and stores handles to both // ends of it. // 2. The parent starts the child and provides it with the information // necessary to acquire the handle to the write end of the pipe. // 3. The child acquires the write end of the pipe and signals the parent // using a Windows event. // 4. Now the parent can release the write end of the pipe on its side. If // this is done before step 3, the object's reference count goes down to // 0 and it is destroyed, preventing the child from acquiring it. The // parent now has to release it, or read operations on the read end of // the pipe will not return when the child terminates. // 5. The parent reads child's output through the pipe (outcome code and // any possible error messages) from the pipe, and its stderr and then // determines whether to fail the test. // // Note: to distinguish Win32 API calls from the local method and function // calls, the former are explicitly resolved in the global namespace. // class WindowsDeathTest : public DeathTestImpl { public: WindowsDeathTest(const char* a_statement, const RE* a_regex, const char* file, int line) : DeathTestImpl(a_statement, a_regex), file_(file), line_(line) {} // All of these virtual functions are inherited from DeathTest. virtual int Wait(); virtual TestRole AssumeRole(); private: // The name of the file in which the death test is located. const char* const file_; // The line number on which the death test is located. const int line_; // Handle to the write end of the pipe to the child process. AutoHandle write_handle_; // Child process handle. AutoHandle child_handle_; // Event the child process uses to signal the parent that it has // acquired the handle to the write end of the pipe. After seeing this // event the parent can release its own handles to make sure its // ReadFile() calls return when the child terminates. AutoHandle event_handle_; }; // Waits for the child in a death test to exit, returning its exit // status, or 0 if no child process exists. As a side effect, sets the // outcome data member. int WindowsDeathTest::Wait() { if (!spawned()) return 0; // Wait until the child either signals that it has acquired the write end // of the pipe or it dies. const HANDLE wait_handles[2] = { child_handle_.Get(), event_handle_.Get() }; switch (::WaitForMultipleObjects(2, wait_handles, FALSE, // Waits for any of the handles. INFINITE)) { case WAIT_OBJECT_0: case WAIT_OBJECT_0 + 1: break; default: GTEST_DEATH_TEST_CHECK_(false); // Should not get here. } // The child has acquired the write end of the pipe or exited. // We release the handle on our side and continue. write_handle_.Reset(); event_handle_.Reset(); ReadAndInterpretStatusByte(); // Waits for the child process to exit if it haven't already. This // returns immediately if the child has already exited, regardless of // whether previous calls to WaitForMultipleObjects synchronized on this // handle or not. GTEST_DEATH_TEST_CHECK_( WAIT_OBJECT_0 == ::WaitForSingleObject(child_handle_.Get(), INFINITE)); DWORD status_code; GTEST_DEATH_TEST_CHECK_( ::GetExitCodeProcess(child_handle_.Get(), &status_code) != FALSE); child_handle_.Reset(); set_status(static_cast(status_code)); return status(); } // The AssumeRole process for a Windows death test. It creates a child // process with the same executable as the current process to run the // death test. The child process is given the --gtest_filter and // --gtest_internal_run_death_test flags such that it knows to run the // current death test only. DeathTest::TestRole WindowsDeathTest::AssumeRole() { const UnitTestImpl* const impl = GetUnitTestImpl(); const InternalRunDeathTestFlag* const flag = impl->internal_run_death_test_flag(); const TestInfo* const info = impl->current_test_info(); const int death_test_index = info->result()->death_test_count(); if (flag != NULL) { // ParseInternalRunDeathTestFlag() has performed all the necessary // processing. set_write_fd(flag->write_fd()); return EXECUTE_TEST; } // WindowsDeathTest uses an anonymous pipe to communicate results of // a death test. SECURITY_ATTRIBUTES handles_are_inheritable = { sizeof(SECURITY_ATTRIBUTES), NULL, TRUE }; HANDLE read_handle, write_handle; GTEST_DEATH_TEST_CHECK_( ::CreatePipe(&read_handle, &write_handle, &handles_are_inheritable, 0) // Default buffer size. != FALSE); set_read_fd(::_open_osfhandle(reinterpret_cast(read_handle), O_RDONLY)); write_handle_.Reset(write_handle); event_handle_.Reset(::CreateEvent( &handles_are_inheritable, TRUE, // The event will automatically reset to non-signaled state. FALSE, // The initial state is non-signalled. NULL)); // The even is unnamed. GTEST_DEATH_TEST_CHECK_(event_handle_.Get() != NULL); const std::string filter_flag = std::string("--") + GTEST_FLAG_PREFIX_ + kFilterFlag + "=" + info->test_case_name() + "." + info->name(); const std::string internal_flag = std::string("--") + GTEST_FLAG_PREFIX_ + kInternalRunDeathTestFlag + "=" + file_ + "|" + StreamableToString(line_) + "|" + StreamableToString(death_test_index) + "|" + StreamableToString(static_cast(::GetCurrentProcessId())) + // size_t has the same width as pointers on both 32-bit and 64-bit // Windows platforms. // See http://msdn.microsoft.com/en-us/library/tcxf1dw6.aspx. "|" + StreamableToString(reinterpret_cast(write_handle)) + "|" + StreamableToString(reinterpret_cast(event_handle_.Get())); char executable_path[_MAX_PATH + 1]; // NOLINT GTEST_DEATH_TEST_CHECK_( _MAX_PATH + 1 != ::GetModuleFileNameA(NULL, executable_path, _MAX_PATH)); std::string command_line = std::string(::GetCommandLineA()) + " " + filter_flag + " \"" + internal_flag + "\""; DeathTest::set_last_death_test_message(""); CaptureStderr(); // Flush the log buffers since the log streams are shared with the child. FlushInfoLog(); // The child process will share the standard handles with the parent. STARTUPINFOA startup_info; memset(&startup_info, 0, sizeof(STARTUPINFO)); startup_info.dwFlags = STARTF_USESTDHANDLES; startup_info.hStdInput = ::GetStdHandle(STD_INPUT_HANDLE); startup_info.hStdOutput = ::GetStdHandle(STD_OUTPUT_HANDLE); startup_info.hStdError = ::GetStdHandle(STD_ERROR_HANDLE); PROCESS_INFORMATION process_info; GTEST_DEATH_TEST_CHECK_(::CreateProcessA( executable_path, const_cast(command_line.c_str()), NULL, // Retuned process handle is not inheritable. NULL, // Retuned thread handle is not inheritable. TRUE, // Child inherits all inheritable handles (for write_handle_). 0x0, // Default creation flags. NULL, // Inherit the parent's environment. UnitTest::GetInstance()->original_working_dir(), &startup_info, &process_info) != FALSE); child_handle_.Reset(process_info.hProcess); ::CloseHandle(process_info.hThread); set_spawned(true); return OVERSEE_TEST; } # else // We are not on Windows. // ForkingDeathTest provides implementations for most of the abstract // methods of the DeathTest interface. Only the AssumeRole method is // left undefined. class ForkingDeathTest : public DeathTestImpl { public: ForkingDeathTest(const char* statement, const RE* regex); // All of these virtual functions are inherited from DeathTest. virtual int Wait(); protected: void set_child_pid(pid_t child_pid) { child_pid_ = child_pid; } private: // PID of child process during death test; 0 in the child process itself. pid_t child_pid_; }; // Constructs a ForkingDeathTest. ForkingDeathTest::ForkingDeathTest(const char* a_statement, const RE* a_regex) : DeathTestImpl(a_statement, a_regex), child_pid_(-1) {} // Waits for the child in a death test to exit, returning its exit // status, or 0 if no child process exists. As a side effect, sets the // outcome data member. int ForkingDeathTest::Wait() { if (!spawned()) return 0; ReadAndInterpretStatusByte(); int status_value; GTEST_DEATH_TEST_CHECK_SYSCALL_(waitpid(child_pid_, &status_value, 0)); set_status(status_value); return status_value; } // A concrete death test class that forks, then immediately runs the test // in the child process. class NoExecDeathTest : public ForkingDeathTest { public: NoExecDeathTest(const char* a_statement, const RE* a_regex) : ForkingDeathTest(a_statement, a_regex) { } virtual TestRole AssumeRole(); }; // The AssumeRole process for a fork-and-run death test. It implements a // straightforward fork, with a simple pipe to transmit the status byte. DeathTest::TestRole NoExecDeathTest::AssumeRole() { const size_t thread_count = GetThreadCount(); if (thread_count != 1) { GTEST_LOG_(WARNING) << DeathTestThreadWarning(thread_count); } int pipe_fd[2]; GTEST_DEATH_TEST_CHECK_(pipe(pipe_fd) != -1); DeathTest::set_last_death_test_message(""); CaptureStderr(); // When we fork the process below, the log file buffers are copied, but the // file descriptors are shared. We flush all log files here so that closing // the file descriptors in the child process doesn't throw off the // synchronization between descriptors and buffers in the parent process. // This is as close to the fork as possible to avoid a race condition in case // there are multiple threads running before the death test, and another // thread writes to the log file. FlushInfoLog(); const pid_t child_pid = fork(); GTEST_DEATH_TEST_CHECK_(child_pid != -1); set_child_pid(child_pid); if (child_pid == 0) { GTEST_DEATH_TEST_CHECK_SYSCALL_(close(pipe_fd[0])); set_write_fd(pipe_fd[1]); // Redirects all logging to stderr in the child process to prevent // concurrent writes to the log files. We capture stderr in the parent // process and append the child process' output to a log. LogToStderr(); // Event forwarding to the listeners of event listener API mush be shut // down in death test subprocesses. GetUnitTestImpl()->listeners()->SuppressEventForwarding(); g_in_fast_death_test_child = true; return EXECUTE_TEST; } else { GTEST_DEATH_TEST_CHECK_SYSCALL_(close(pipe_fd[1])); set_read_fd(pipe_fd[0]); set_spawned(true); return OVERSEE_TEST; } } // A concrete death test class that forks and re-executes the main // program from the beginning, with command-line flags set that cause // only this specific death test to be run. class ExecDeathTest : public ForkingDeathTest { public: ExecDeathTest(const char* a_statement, const RE* a_regex, const char* file, int line) : ForkingDeathTest(a_statement, a_regex), file_(file), line_(line) { } virtual TestRole AssumeRole(); private: static ::std::vector GetArgvsForDeathTestChildProcess() { ::std::vector args = GetInjectableArgvs(); return args; } // The name of the file in which the death test is located. const char* const file_; // The line number on which the death test is located. const int line_; }; // Utility class for accumulating command-line arguments. class Arguments { public: Arguments() { args_.push_back(NULL); } ~Arguments() { for (std::vector::iterator i = args_.begin(); i != args_.end(); ++i) { free(*i); } } void AddArgument(const char* argument) { args_.insert(args_.end() - 1, posix::StrDup(argument)); } template void AddArguments(const ::std::vector& arguments) { for (typename ::std::vector::const_iterator i = arguments.begin(); i != arguments.end(); ++i) { args_.insert(args_.end() - 1, posix::StrDup(i->c_str())); } } char* const* Argv() { return &args_[0]; } private: std::vector args_; }; // A struct that encompasses the arguments to the child process of a // threadsafe-style death test process. struct ExecDeathTestArgs { char* const* argv; // Command-line arguments for the child's call to exec int close_fd; // File descriptor to close; the read end of a pipe }; # if GTEST_OS_MAC inline char** GetEnviron() { // When Google Test is built as a framework on MacOS X, the environ variable // is unavailable. Apple's documentation (man environ) recommends using // _NSGetEnviron() instead. return *_NSGetEnviron(); } # else // Some POSIX platforms expect you to declare environ. extern "C" makes // it reside in the global namespace. extern "C" char** environ; inline char** GetEnviron() { return environ; } # endif // GTEST_OS_MAC # if !GTEST_OS_QNX // The main function for a threadsafe-style death test child process. // This function is called in a clone()-ed process and thus must avoid // any potentially unsafe operations like malloc or libc functions. static int ExecDeathTestChildMain(void* child_arg) { ExecDeathTestArgs* const args = static_cast(child_arg); GTEST_DEATH_TEST_CHECK_SYSCALL_(close(args->close_fd)); // We need to execute the test program in the same environment where // it was originally invoked. Therefore we change to the original // working directory first. const char* const original_dir = UnitTest::GetInstance()->original_working_dir(); // We can safely call chdir() as it's a direct system call. if (chdir(original_dir) != 0) { DeathTestAbort(std::string("chdir(\"") + original_dir + "\") failed: " + GetLastErrnoDescription()); return EXIT_FAILURE; } // We can safely call execve() as it's a direct system call. We // cannot use execvp() as it's a libc function and thus potentially // unsafe. Since execve() doesn't search the PATH, the user must // invoke the test program via a valid path that contains at least // one path separator. execve(args->argv[0], args->argv, GetEnviron()); DeathTestAbort(std::string("execve(") + args->argv[0] + ", ...) in " + original_dir + " failed: " + GetLastErrnoDescription()); return EXIT_FAILURE; } # endif // !GTEST_OS_QNX // Two utility routines that together determine the direction the stack // grows. // This could be accomplished more elegantly by a single recursive // function, but we want to guard against the unlikely possibility of // a smart compiler optimizing the recursion away. // // GTEST_NO_INLINE_ is required to prevent GCC 4.6 from inlining // StackLowerThanAddress into StackGrowsDown, which then doesn't give // correct answer. void StackLowerThanAddress(const void* ptr, bool* result) GTEST_NO_INLINE_; void StackLowerThanAddress(const void* ptr, bool* result) { int dummy; *result = (&dummy < ptr); } bool StackGrowsDown() { int dummy; bool result; StackLowerThanAddress(&dummy, &result); return result; } // Spawns a child process with the same executable as the current process in // a thread-safe manner and instructs it to run the death test. The // implementation uses fork(2) + exec. On systems where clone(2) is // available, it is used instead, being slightly more thread-safe. On QNX, // fork supports only single-threaded environments, so this function uses // spawn(2) there instead. The function dies with an error message if // anything goes wrong. static pid_t ExecDeathTestSpawnChild(char* const* argv, int close_fd) { ExecDeathTestArgs args = { argv, close_fd }; pid_t child_pid = -1; # if GTEST_OS_QNX // Obtains the current directory and sets it to be closed in the child // process. const int cwd_fd = open(".", O_RDONLY); GTEST_DEATH_TEST_CHECK_(cwd_fd != -1); GTEST_DEATH_TEST_CHECK_SYSCALL_(fcntl(cwd_fd, F_SETFD, FD_CLOEXEC)); // We need to execute the test program in the same environment where // it was originally invoked. Therefore we change to the original // working directory first. const char* const original_dir = UnitTest::GetInstance()->original_working_dir(); // We can safely call chdir() as it's a direct system call. if (chdir(original_dir) != 0) { DeathTestAbort(std::string("chdir(\"") + original_dir + "\") failed: " + GetLastErrnoDescription()); return EXIT_FAILURE; } int fd_flags; // Set close_fd to be closed after spawn. GTEST_DEATH_TEST_CHECK_SYSCALL_(fd_flags = fcntl(close_fd, F_GETFD)); GTEST_DEATH_TEST_CHECK_SYSCALL_(fcntl(close_fd, F_SETFD, fd_flags | FD_CLOEXEC)); struct inheritance inherit = {0}; // spawn is a system call. child_pid = spawn(args.argv[0], 0, NULL, &inherit, args.argv, GetEnviron()); // Restores the current working directory. GTEST_DEATH_TEST_CHECK_(fchdir(cwd_fd) != -1); GTEST_DEATH_TEST_CHECK_SYSCALL_(close(cwd_fd)); # else // GTEST_OS_QNX # if GTEST_OS_LINUX // When a SIGPROF signal is received while fork() or clone() are executing, // the process may hang. To avoid this, we ignore SIGPROF here and re-enable // it after the call to fork()/clone() is complete. struct sigaction saved_sigprof_action; struct sigaction ignore_sigprof_action; memset(&ignore_sigprof_action, 0, sizeof(ignore_sigprof_action)); sigemptyset(&ignore_sigprof_action.sa_mask); ignore_sigprof_action.sa_handler = SIG_IGN; GTEST_DEATH_TEST_CHECK_SYSCALL_(sigaction( SIGPROF, &ignore_sigprof_action, &saved_sigprof_action)); # endif // GTEST_OS_LINUX # if GTEST_HAS_CLONE const bool use_fork = GTEST_FLAG(death_test_use_fork); if (!use_fork) { static const bool stack_grows_down = StackGrowsDown(); const size_t stack_size = getpagesize(); // MMAP_ANONYMOUS is not defined on Mac, so we use MAP_ANON instead. void* const stack = mmap(NULL, stack_size, PROT_READ | PROT_WRITE, MAP_ANON | MAP_PRIVATE, -1, 0); GTEST_DEATH_TEST_CHECK_(stack != MAP_FAILED); // Maximum stack alignment in bytes: For a downward-growing stack, this // amount is subtracted from size of the stack space to get an address // that is within the stack space and is aligned on all systems we care // about. As far as I know there is no ABI with stack alignment greater // than 64. We assume stack and stack_size already have alignment of // kMaxStackAlignment. const size_t kMaxStackAlignment = 64; void* const stack_top = static_cast(stack) + (stack_grows_down ? stack_size - kMaxStackAlignment : 0); GTEST_DEATH_TEST_CHECK_(stack_size > kMaxStackAlignment && reinterpret_cast(stack_top) % kMaxStackAlignment == 0); child_pid = clone(&ExecDeathTestChildMain, stack_top, SIGCHLD, &args); GTEST_DEATH_TEST_CHECK_(munmap(stack, stack_size) != -1); } # else const bool use_fork = true; # endif // GTEST_HAS_CLONE if (use_fork && (child_pid = fork()) == 0) { ExecDeathTestChildMain(&args); _exit(0); } # endif // GTEST_OS_QNX # if GTEST_OS_LINUX GTEST_DEATH_TEST_CHECK_SYSCALL_( sigaction(SIGPROF, &saved_sigprof_action, NULL)); # endif // GTEST_OS_LINUX GTEST_DEATH_TEST_CHECK_(child_pid != -1); return child_pid; } // The AssumeRole process for a fork-and-exec death test. It re-executes the // main program from the beginning, setting the --gtest_filter // and --gtest_internal_run_death_test flags to cause only the current // death test to be re-run. DeathTest::TestRole ExecDeathTest::AssumeRole() { const UnitTestImpl* const impl = GetUnitTestImpl(); const InternalRunDeathTestFlag* const flag = impl->internal_run_death_test_flag(); const TestInfo* const info = impl->current_test_info(); const int death_test_index = info->result()->death_test_count(); if (flag != NULL) { set_write_fd(flag->write_fd()); return EXECUTE_TEST; } int pipe_fd[2]; GTEST_DEATH_TEST_CHECK_(pipe(pipe_fd) != -1); // Clear the close-on-exec flag on the write end of the pipe, lest // it be closed when the child process does an exec: GTEST_DEATH_TEST_CHECK_(fcntl(pipe_fd[1], F_SETFD, 0) != -1); const std::string filter_flag = std::string("--") + GTEST_FLAG_PREFIX_ + kFilterFlag + "=" + info->test_case_name() + "." + info->name(); const std::string internal_flag = std::string("--") + GTEST_FLAG_PREFIX_ + kInternalRunDeathTestFlag + "=" + file_ + "|" + StreamableToString(line_) + "|" + StreamableToString(death_test_index) + "|" + StreamableToString(pipe_fd[1]); Arguments args; args.AddArguments(GetArgvsForDeathTestChildProcess()); args.AddArgument(filter_flag.c_str()); args.AddArgument(internal_flag.c_str()); DeathTest::set_last_death_test_message(""); CaptureStderr(); // See the comment in NoExecDeathTest::AssumeRole for why the next line // is necessary. FlushInfoLog(); const pid_t child_pid = ExecDeathTestSpawnChild(args.Argv(), pipe_fd[0]); GTEST_DEATH_TEST_CHECK_SYSCALL_(close(pipe_fd[1])); set_child_pid(child_pid); set_read_fd(pipe_fd[0]); set_spawned(true); return OVERSEE_TEST; } # endif // !GTEST_OS_WINDOWS // Creates a concrete DeathTest-derived class that depends on the // --gtest_death_test_style flag, and sets the pointer pointed to // by the "test" argument to its address. If the test should be // skipped, sets that pointer to NULL. Returns true, unless the // flag is set to an invalid value. bool DefaultDeathTestFactory::Create(const char* statement, const RE* regex, const char* file, int line, DeathTest** test) { UnitTestImpl* const impl = GetUnitTestImpl(); const InternalRunDeathTestFlag* const flag = impl->internal_run_death_test_flag(); const int death_test_index = impl->current_test_info() ->increment_death_test_count(); if (flag != NULL) { if (death_test_index > flag->index()) { DeathTest::set_last_death_test_message( "Death test count (" + StreamableToString(death_test_index) + ") somehow exceeded expected maximum (" + StreamableToString(flag->index()) + ")"); return false; } if (!(flag->file() == file && flag->line() == line && flag->index() == death_test_index)) { *test = NULL; return true; } } # if GTEST_OS_WINDOWS if (GTEST_FLAG(death_test_style) == "threadsafe" || GTEST_FLAG(death_test_style) == "fast") { *test = new WindowsDeathTest(statement, regex, file, line); } # else if (GTEST_FLAG(death_test_style) == "threadsafe") { *test = new ExecDeathTest(statement, regex, file, line); } else if (GTEST_FLAG(death_test_style) == "fast") { *test = new NoExecDeathTest(statement, regex); } # endif // GTEST_OS_WINDOWS else { // NOLINT - this is more readable than unbalanced brackets inside #if. DeathTest::set_last_death_test_message( "Unknown death test style \"" + GTEST_FLAG(death_test_style) + "\" encountered"); return false; } return true; } // Splits a given string on a given delimiter, populating a given // vector with the fields. GTEST_HAS_DEATH_TEST implies that we have // ::std::string, so we can use it here. static void SplitString(const ::std::string& str, char delimiter, ::std::vector< ::std::string>* dest) { ::std::vector< ::std::string> parsed; ::std::string::size_type pos = 0; while (::testing::internal::AlwaysTrue()) { const ::std::string::size_type colon = str.find(delimiter, pos); if (colon == ::std::string::npos) { parsed.push_back(str.substr(pos)); break; } else { parsed.push_back(str.substr(pos, colon - pos)); pos = colon + 1; } } dest->swap(parsed); } # if GTEST_OS_WINDOWS // Recreates the pipe and event handles from the provided parameters, // signals the event, and returns a file descriptor wrapped around the pipe // handle. This function is called in the child process only. int GetStatusFileDescriptor(unsigned int parent_process_id, size_t write_handle_as_size_t, size_t event_handle_as_size_t) { AutoHandle parent_process_handle(::OpenProcess(PROCESS_DUP_HANDLE, FALSE, // Non-inheritable. parent_process_id)); if (parent_process_handle.Get() == INVALID_HANDLE_VALUE) { DeathTestAbort("Unable to open parent process " + StreamableToString(parent_process_id)); } // TODO(vladl@google.com): Replace the following check with a // compile-time assertion when available. GTEST_CHECK_(sizeof(HANDLE) <= sizeof(size_t)); const HANDLE write_handle = reinterpret_cast(write_handle_as_size_t); HANDLE dup_write_handle; // The newly initialized handle is accessible only in in the parent // process. To obtain one accessible within the child, we need to use // DuplicateHandle. if (!::DuplicateHandle(parent_process_handle.Get(), write_handle, ::GetCurrentProcess(), &dup_write_handle, 0x0, // Requested privileges ignored since // DUPLICATE_SAME_ACCESS is used. FALSE, // Request non-inheritable handler. DUPLICATE_SAME_ACCESS)) { DeathTestAbort("Unable to duplicate the pipe handle " + StreamableToString(write_handle_as_size_t) + " from the parent process " + StreamableToString(parent_process_id)); } const HANDLE event_handle = reinterpret_cast(event_handle_as_size_t); HANDLE dup_event_handle; if (!::DuplicateHandle(parent_process_handle.Get(), event_handle, ::GetCurrentProcess(), &dup_event_handle, 0x0, FALSE, DUPLICATE_SAME_ACCESS)) { DeathTestAbort("Unable to duplicate the event handle " + StreamableToString(event_handle_as_size_t) + " from the parent process " + StreamableToString(parent_process_id)); } const int write_fd = ::_open_osfhandle(reinterpret_cast(dup_write_handle), O_APPEND); if (write_fd == -1) { DeathTestAbort("Unable to convert pipe handle " + StreamableToString(write_handle_as_size_t) + " to a file descriptor"); } // Signals the parent that the write end of the pipe has been acquired // so the parent can release its own write end. ::SetEvent(dup_event_handle); return write_fd; } # endif // GTEST_OS_WINDOWS // Returns a newly created InternalRunDeathTestFlag object with fields // initialized from the GTEST_FLAG(internal_run_death_test) flag if // the flag is specified; otherwise returns NULL. InternalRunDeathTestFlag* ParseInternalRunDeathTestFlag() { if (GTEST_FLAG(internal_run_death_test) == "") return NULL; // GTEST_HAS_DEATH_TEST implies that we have ::std::string, so we // can use it here. int line = -1; int index = -1; ::std::vector< ::std::string> fields; SplitString(GTEST_FLAG(internal_run_death_test).c_str(), '|', &fields); int write_fd = -1; # if GTEST_OS_WINDOWS unsigned int parent_process_id = 0; size_t write_handle_as_size_t = 0; size_t event_handle_as_size_t = 0; if (fields.size() != 6 || !ParseNaturalNumber(fields[1], &line) || !ParseNaturalNumber(fields[2], &index) || !ParseNaturalNumber(fields[3], &parent_process_id) || !ParseNaturalNumber(fields[4], &write_handle_as_size_t) || !ParseNaturalNumber(fields[5], &event_handle_as_size_t)) { DeathTestAbort("Bad --gtest_internal_run_death_test flag: " + GTEST_FLAG(internal_run_death_test)); } write_fd = GetStatusFileDescriptor(parent_process_id, write_handle_as_size_t, event_handle_as_size_t); # else if (fields.size() != 4 || !ParseNaturalNumber(fields[1], &line) || !ParseNaturalNumber(fields[2], &index) || !ParseNaturalNumber(fields[3], &write_fd)) { DeathTestAbort("Bad --gtest_internal_run_death_test flag: " + GTEST_FLAG(internal_run_death_test)); } # endif // GTEST_OS_WINDOWS return new InternalRunDeathTestFlag(fields[0], line, index, write_fd); } } // namespace internal #endif // GTEST_HAS_DEATH_TEST } // namespace testing // Copyright 2008, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Authors: keith.ray@gmail.com (Keith Ray) #include #if GTEST_OS_WINDOWS_MOBILE # include #elif GTEST_OS_WINDOWS # include # include #elif GTEST_OS_SYMBIAN // Symbian OpenC has PATH_MAX in sys/syslimits.h # include #else # include # include // Some Linux distributions define PATH_MAX here. #endif // GTEST_OS_WINDOWS_MOBILE #if GTEST_OS_WINDOWS # define GTEST_PATH_MAX_ _MAX_PATH #elif defined(PATH_MAX) # define GTEST_PATH_MAX_ PATH_MAX #elif defined(_XOPEN_PATH_MAX) # define GTEST_PATH_MAX_ _XOPEN_PATH_MAX #else # define GTEST_PATH_MAX_ _POSIX_PATH_MAX #endif // GTEST_OS_WINDOWS namespace testing { namespace internal { #if GTEST_OS_WINDOWS // On Windows, '\\' is the standard path separator, but many tools and the // Windows API also accept '/' as an alternate path separator. Unless otherwise // noted, a file path can contain either kind of path separators, or a mixture // of them. const char kPathSeparator = '\\'; const char kAlternatePathSeparator = '/'; const char kPathSeparatorString[] = "\\"; const char kAlternatePathSeparatorString[] = "/"; # if GTEST_OS_WINDOWS_MOBILE // Windows CE doesn't have a current directory. You should not use // the current directory in tests on Windows CE, but this at least // provides a reasonable fallback. const char kCurrentDirectoryString[] = "\\"; // Windows CE doesn't define INVALID_FILE_ATTRIBUTES const DWORD kInvalidFileAttributes = 0xffffffff; # else const char kCurrentDirectoryString[] = ".\\"; # endif // GTEST_OS_WINDOWS_MOBILE #else const char kPathSeparator = '/'; const char kPathSeparatorString[] = "/"; const char kCurrentDirectoryString[] = "./"; #endif // GTEST_OS_WINDOWS // Returns whether the given character is a valid path separator. static bool IsPathSeparator(char c) { #if GTEST_HAS_ALT_PATH_SEP_ return (c == kPathSeparator) || (c == kAlternatePathSeparator); #else return c == kPathSeparator; #endif } // Returns the current working directory, or "" if unsuccessful. FilePath FilePath::GetCurrentDir() { #if GTEST_OS_WINDOWS_MOBILE // Windows CE doesn't have a current directory, so we just return // something reasonable. return FilePath(kCurrentDirectoryString); #elif GTEST_OS_WINDOWS char cwd[GTEST_PATH_MAX_ + 1] = { '\0' }; return FilePath(_getcwd(cwd, sizeof(cwd)) == NULL ? "" : cwd); #else char cwd[GTEST_PATH_MAX_ + 1] = { '\0' }; return FilePath(getcwd(cwd, sizeof(cwd)) == NULL ? "" : cwd); #endif // GTEST_OS_WINDOWS_MOBILE } // Returns a copy of the FilePath with the case-insensitive extension removed. // Example: FilePath("dir/file.exe").RemoveExtension("EXE") returns // FilePath("dir/file"). If a case-insensitive extension is not // found, returns a copy of the original FilePath. FilePath FilePath::RemoveExtension(const char* extension) const { const std::string dot_extension = std::string(".") + extension; if (String::EndsWithCaseInsensitive(pathname_, dot_extension)) { return FilePath(pathname_.substr( 0, pathname_.length() - dot_extension.length())); } return *this; } // Returns a pointer to the last occurence of a valid path separator in // the FilePath. On Windows, for example, both '/' and '\' are valid path // separators. Returns NULL if no path separator was found. const char* FilePath::FindLastPathSeparator() const { const char* const last_sep = strrchr(c_str(), kPathSeparator); #if GTEST_HAS_ALT_PATH_SEP_ const char* const last_alt_sep = strrchr(c_str(), kAlternatePathSeparator); // Comparing two pointers of which only one is NULL is undefined. if (last_alt_sep != NULL && (last_sep == NULL || last_alt_sep > last_sep)) { return last_alt_sep; } #endif return last_sep; } // Returns a copy of the FilePath with the directory part removed. // Example: FilePath("path/to/file").RemoveDirectoryName() returns // FilePath("file"). If there is no directory part ("just_a_file"), it returns // the FilePath unmodified. If there is no file part ("just_a_dir/") it // returns an empty FilePath (""). // On Windows platform, '\' is the path separator, otherwise it is '/'. FilePath FilePath::RemoveDirectoryName() const { const char* const last_sep = FindLastPathSeparator(); return last_sep ? FilePath(last_sep + 1) : *this; } // RemoveFileName returns the directory path with the filename removed. // Example: FilePath("path/to/file").RemoveFileName() returns "path/to/". // If the FilePath is "a_file" or "/a_file", RemoveFileName returns // FilePath("./") or, on Windows, FilePath(".\\"). If the filepath does // not have a file, like "just/a/dir/", it returns the FilePath unmodified. // On Windows platform, '\' is the path separator, otherwise it is '/'. FilePath FilePath::RemoveFileName() const { const char* const last_sep = FindLastPathSeparator(); std::string dir; if (last_sep) { dir = std::string(c_str(), last_sep + 1 - c_str()); } else { dir = kCurrentDirectoryString; } return FilePath(dir); } // Helper functions for naming files in a directory for xml output. // Given directory = "dir", base_name = "test", number = 0, // extension = "xml", returns "dir/test.xml". If number is greater // than zero (e.g., 12), returns "dir/test_12.xml". // On Windows platform, uses \ as the separator rather than /. FilePath FilePath::MakeFileName(const FilePath& directory, const FilePath& base_name, int number, const char* extension) { std::string file; if (number == 0) { file = base_name.string() + "." + extension; } else { file = base_name.string() + "_" + StreamableToString(number) + "." + extension; } return ConcatPaths(directory, FilePath(file)); } // Given directory = "dir", relative_path = "test.xml", returns "dir/test.xml". // On Windows, uses \ as the separator rather than /. FilePath FilePath::ConcatPaths(const FilePath& directory, const FilePath& relative_path) { if (directory.IsEmpty()) return relative_path; const FilePath dir(directory.RemoveTrailingPathSeparator()); return FilePath(dir.string() + kPathSeparator + relative_path.string()); } // Returns true if pathname describes something findable in the file-system, // either a file, directory, or whatever. bool FilePath::FileOrDirectoryExists() const { #if GTEST_OS_WINDOWS_MOBILE LPCWSTR unicode = String::AnsiToUtf16(pathname_.c_str()); const DWORD attributes = GetFileAttributes(unicode); delete [] unicode; return attributes != kInvalidFileAttributes; #else posix::StatStruct file_stat; return posix::Stat(pathname_.c_str(), &file_stat) == 0; #endif // GTEST_OS_WINDOWS_MOBILE } // Returns true if pathname describes a directory in the file-system // that exists. bool FilePath::DirectoryExists() const { bool result = false; #if GTEST_OS_WINDOWS // Don't strip off trailing separator if path is a root directory on // Windows (like "C:\\"). const FilePath& path(IsRootDirectory() ? *this : RemoveTrailingPathSeparator()); #else const FilePath& path(*this); #endif #if GTEST_OS_WINDOWS_MOBILE LPCWSTR unicode = String::AnsiToUtf16(path.c_str()); const DWORD attributes = GetFileAttributes(unicode); delete [] unicode; if ((attributes != kInvalidFileAttributes) && (attributes & FILE_ATTRIBUTE_DIRECTORY)) { result = true; } #else posix::StatStruct file_stat; result = posix::Stat(path.c_str(), &file_stat) == 0 && posix::IsDir(file_stat); #endif // GTEST_OS_WINDOWS_MOBILE return result; } // Returns true if pathname describes a root directory. (Windows has one // root directory per disk drive.) bool FilePath::IsRootDirectory() const { #if GTEST_OS_WINDOWS // TODO(wan@google.com): on Windows a network share like // \\server\share can be a root directory, although it cannot be the // current directory. Handle this properly. return pathname_.length() == 3 && IsAbsolutePath(); #else return pathname_.length() == 1 && IsPathSeparator(pathname_.c_str()[0]); #endif } // Returns true if pathname describes an absolute path. bool FilePath::IsAbsolutePath() const { const char* const name = pathname_.c_str(); #if GTEST_OS_WINDOWS return pathname_.length() >= 3 && ((name[0] >= 'a' && name[0] <= 'z') || (name[0] >= 'A' && name[0] <= 'Z')) && name[1] == ':' && IsPathSeparator(name[2]); #else return IsPathSeparator(name[0]); #endif } // Returns a pathname for a file that does not currently exist. The pathname // will be directory/base_name.extension or // directory/base_name_.extension if directory/base_name.extension // already exists. The number will be incremented until a pathname is found // that does not already exist. // Examples: 'dir/foo_test.xml' or 'dir/foo_test_1.xml'. // There could be a race condition if two or more processes are calling this // function at the same time -- they could both pick the same filename. FilePath FilePath::GenerateUniqueFileName(const FilePath& directory, const FilePath& base_name, const char* extension) { FilePath full_pathname; int number = 0; do { full_pathname.Set(MakeFileName(directory, base_name, number++, extension)); } while (full_pathname.FileOrDirectoryExists()); return full_pathname; } // Returns true if FilePath ends with a path separator, which indicates that // it is intended to represent a directory. Returns false otherwise. // This does NOT check that a directory (or file) actually exists. bool FilePath::IsDirectory() const { return !pathname_.empty() && IsPathSeparator(pathname_.c_str()[pathname_.length() - 1]); } // Create directories so that path exists. Returns true if successful or if // the directories already exist; returns false if unable to create directories // for any reason. bool FilePath::CreateDirectoriesRecursively() const { if (!this->IsDirectory()) { return false; } if (pathname_.length() == 0 || this->DirectoryExists()) { return true; } const FilePath parent(this->RemoveTrailingPathSeparator().RemoveFileName()); return parent.CreateDirectoriesRecursively() && this->CreateFolder(); } // Create the directory so that path exists. Returns true if successful or // if the directory already exists; returns false if unable to create the // directory for any reason, including if the parent directory does not // exist. Not named "CreateDirectory" because that's a macro on Windows. bool FilePath::CreateFolder() const { #if GTEST_OS_WINDOWS_MOBILE FilePath removed_sep(this->RemoveTrailingPathSeparator()); LPCWSTR unicode = String::AnsiToUtf16(removed_sep.c_str()); int result = CreateDirectory(unicode, NULL) ? 0 : -1; delete [] unicode; #elif GTEST_OS_WINDOWS int result = _mkdir(pathname_.c_str()); #else int result = mkdir(pathname_.c_str(), 0777); #endif // GTEST_OS_WINDOWS_MOBILE if (result == -1) { return this->DirectoryExists(); // An error is OK if the directory exists. } return true; // No error. } // If input name has a trailing separator character, remove it and return the // name, otherwise return the name string unmodified. // On Windows platform, uses \ as the separator, other platforms use /. FilePath FilePath::RemoveTrailingPathSeparator() const { return IsDirectory() ? FilePath(pathname_.substr(0, pathname_.length() - 1)) : *this; } // Removes any redundant separators that might be in the pathname. // For example, "bar///foo" becomes "bar/foo". Does not eliminate other // redundancies that might be in a pathname involving "." or "..". // TODO(wan@google.com): handle Windows network shares (e.g. \\server\share). void FilePath::Normalize() { if (pathname_.c_str() == NULL) { pathname_ = ""; return; } const char* src = pathname_.c_str(); char* const dest = new char[pathname_.length() + 1]; char* dest_ptr = dest; memset(dest_ptr, 0, pathname_.length() + 1); while (*src != '\0') { *dest_ptr = *src; if (!IsPathSeparator(*src)) { src++; } else { #if GTEST_HAS_ALT_PATH_SEP_ if (*dest_ptr == kAlternatePathSeparator) { *dest_ptr = kPathSeparator; } #endif while (IsPathSeparator(*src)) src++; } dest_ptr++; } *dest_ptr = '\0'; pathname_ = dest; delete[] dest; } } // namespace internal } // namespace testing // Copyright 2008, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: wan@google.com (Zhanyong Wan) #include #include #include #include #if GTEST_OS_WINDOWS_MOBILE # include // For TerminateProcess() #elif GTEST_OS_WINDOWS # include # include #else # include #endif // GTEST_OS_WINDOWS_MOBILE #if GTEST_OS_MAC # include # include # include #endif // GTEST_OS_MAC #if GTEST_OS_QNX # include # include #endif // GTEST_OS_QNX // Indicates that this translation unit is part of Google Test's // implementation. It must come before gtest-internal-inl.h is // included, or there will be a compiler error. This trick is to // prevent a user from accidentally including gtest-internal-inl.h in // his code. #define GTEST_IMPLEMENTATION_ 1 #undef GTEST_IMPLEMENTATION_ namespace testing { namespace internal { #if defined(_MSC_VER) || defined(__BORLANDC__) // MSVC and C++Builder do not provide a definition of STDERR_FILENO. const int kStdOutFileno = 1; const int kStdErrFileno = 2; #else const int kStdOutFileno = STDOUT_FILENO; const int kStdErrFileno = STDERR_FILENO; #endif // _MSC_VER #if GTEST_OS_MAC // Returns the number of threads running in the process, or 0 to indicate that // we cannot detect it. size_t GetThreadCount() { const task_t task = mach_task_self(); mach_msg_type_number_t thread_count; thread_act_array_t thread_list; const kern_return_t status = task_threads(task, &thread_list, &thread_count); if (status == KERN_SUCCESS) { // task_threads allocates resources in thread_list and we need to free them // to avoid leaks. vm_deallocate(task, reinterpret_cast(thread_list), sizeof(thread_t) * thread_count); return static_cast(thread_count); } else { return 0; } } #elif GTEST_OS_QNX // Returns the number of threads running in the process, or 0 to indicate that // we cannot detect it. size_t GetThreadCount() { const int fd = open("/proc/self/as", O_RDONLY); if (fd < 0) { return 0; } procfs_info process_info; const int status = devctl(fd, DCMD_PROC_INFO, &process_info, sizeof(process_info), NULL); close(fd); if (status == EOK) { return static_cast(process_info.num_threads); } else { return 0; } } #else size_t GetThreadCount() { // There's no portable way to detect the number of threads, so we just // return 0 to indicate that we cannot detect it. return 0; } #endif // GTEST_OS_MAC #if GTEST_USES_POSIX_RE // Implements RE. Currently only needed for death tests. RE::~RE() { if (is_valid_) { // regfree'ing an invalid regex might crash because the content // of the regex is undefined. Since the regex's are essentially // the same, one cannot be valid (or invalid) without the other // being so too. regfree(&partial_regex_); regfree(&full_regex_); } free(const_cast(pattern_)); } // Returns true iff regular expression re matches the entire str. bool RE::FullMatch(const char* str, const RE& re) { if (!re.is_valid_) return false; regmatch_t match; return regexec(&re.full_regex_, str, 1, &match, 0) == 0; } // Returns true iff regular expression re matches a substring of str // (including str itself). bool RE::PartialMatch(const char* str, const RE& re) { if (!re.is_valid_) return false; regmatch_t match; return regexec(&re.partial_regex_, str, 1, &match, 0) == 0; } // Initializes an RE from its string representation. void RE::Init(const char* regex) { pattern_ = posix::StrDup(regex); // Reserves enough bytes to hold the regular expression used for a // full match. const size_t full_regex_len = strlen(regex) + 10; char* const full_pattern = new char[full_regex_len]; snprintf(full_pattern, full_regex_len, "^(%s)$", regex); is_valid_ = regcomp(&full_regex_, full_pattern, REG_EXTENDED) == 0; // We want to call regcomp(&partial_regex_, ...) even if the // previous expression returns false. Otherwise partial_regex_ may // not be properly initialized can may cause trouble when it's // freed. // // Some implementation of POSIX regex (e.g. on at least some // versions of Cygwin) doesn't accept the empty string as a valid // regex. We change it to an equivalent form "()" to be safe. if (is_valid_) { const char* const partial_regex = (*regex == '\0') ? "()" : regex; is_valid_ = regcomp(&partial_regex_, partial_regex, REG_EXTENDED) == 0; } EXPECT_TRUE(is_valid_) << "Regular expression \"" << regex << "\" is not a valid POSIX Extended regular expression."; delete[] full_pattern; } #elif GTEST_USES_SIMPLE_RE // Returns true iff ch appears anywhere in str (excluding the // terminating '\0' character). bool IsInSet(char ch, const char* str) { return ch != '\0' && strchr(str, ch) != NULL; } // Returns true iff ch belongs to the given classification. Unlike // similar functions in , these aren't affected by the // current locale. bool IsAsciiDigit(char ch) { return '0' <= ch && ch <= '9'; } bool IsAsciiPunct(char ch) { return IsInSet(ch, "^-!\"#$%&'()*+,./:;<=>?@[\\]_`{|}~"); } bool IsRepeat(char ch) { return IsInSet(ch, "?*+"); } bool IsAsciiWhiteSpace(char ch) { return IsInSet(ch, " \f\n\r\t\v"); } bool IsAsciiWordChar(char ch) { return ('a' <= ch && ch <= 'z') || ('A' <= ch && ch <= 'Z') || ('0' <= ch && ch <= '9') || ch == '_'; } // Returns true iff "\\c" is a supported escape sequence. bool IsValidEscape(char c) { return (IsAsciiPunct(c) || IsInSet(c, "dDfnrsStvwW")); } // Returns true iff the given atom (specified by escaped and pattern) // matches ch. The result is undefined if the atom is invalid. bool AtomMatchesChar(bool escaped, char pattern_char, char ch) { if (escaped) { // "\\p" where p is pattern_char. switch (pattern_char) { case 'd': return IsAsciiDigit(ch); case 'D': return !IsAsciiDigit(ch); case 'f': return ch == '\f'; case 'n': return ch == '\n'; case 'r': return ch == '\r'; case 's': return IsAsciiWhiteSpace(ch); case 'S': return !IsAsciiWhiteSpace(ch); case 't': return ch == '\t'; case 'v': return ch == '\v'; case 'w': return IsAsciiWordChar(ch); case 'W': return !IsAsciiWordChar(ch); } return IsAsciiPunct(pattern_char) && pattern_char == ch; } return (pattern_char == '.' && ch != '\n') || pattern_char == ch; } // Helper function used by ValidateRegex() to format error messages. std::string FormatRegexSyntaxError(const char* regex, int index) { return (Message() << "Syntax error at index " << index << " in simple regular expression \"" << regex << "\": ").GetString(); } // Generates non-fatal failures and returns false if regex is invalid; // otherwise returns true. bool ValidateRegex(const char* regex) { if (regex == NULL) { // TODO(wan@google.com): fix the source file location in the // assertion failures to match where the regex is used in user // code. ADD_FAILURE() << "NULL is not a valid simple regular expression."; return false; } bool is_valid = true; // True iff ?, *, or + can follow the previous atom. bool prev_repeatable = false; for (int i = 0; regex[i]; i++) { if (regex[i] == '\\') { // An escape sequence i++; if (regex[i] == '\0') { ADD_FAILURE() << FormatRegexSyntaxError(regex, i - 1) << "'\\' cannot appear at the end."; return false; } if (!IsValidEscape(regex[i])) { ADD_FAILURE() << FormatRegexSyntaxError(regex, i - 1) << "invalid escape sequence \"\\" << regex[i] << "\"."; is_valid = false; } prev_repeatable = true; } else { // Not an escape sequence. const char ch = regex[i]; if (ch == '^' && i > 0) { ADD_FAILURE() << FormatRegexSyntaxError(regex, i) << "'^' can only appear at the beginning."; is_valid = false; } else if (ch == '$' && regex[i + 1] != '\0') { ADD_FAILURE() << FormatRegexSyntaxError(regex, i) << "'$' can only appear at the end."; is_valid = false; } else if (IsInSet(ch, "()[]{}|")) { ADD_FAILURE() << FormatRegexSyntaxError(regex, i) << "'" << ch << "' is unsupported."; is_valid = false; } else if (IsRepeat(ch) && !prev_repeatable) { ADD_FAILURE() << FormatRegexSyntaxError(regex, i) << "'" << ch << "' can only follow a repeatable token."; is_valid = false; } prev_repeatable = !IsInSet(ch, "^$?*+"); } } return is_valid; } // Matches a repeated regex atom followed by a valid simple regular // expression. The regex atom is defined as c if escaped is false, // or \c otherwise. repeat is the repetition meta character (?, *, // or +). The behavior is undefined if str contains too many // characters to be indexable by size_t, in which case the test will // probably time out anyway. We are fine with this limitation as // std::string has it too. bool MatchRepetitionAndRegexAtHead( bool escaped, char c, char repeat, const char* regex, const char* str) { const size_t min_count = (repeat == '+') ? 1 : 0; const size_t max_count = (repeat == '?') ? 1 : static_cast(-1) - 1; // We cannot call numeric_limits::max() as it conflicts with the // max() macro on Windows. for (size_t i = 0; i <= max_count; ++i) { // We know that the atom matches each of the first i characters in str. if (i >= min_count && MatchRegexAtHead(regex, str + i)) { // We have enough matches at the head, and the tail matches too. // Since we only care about *whether* the pattern matches str // (as opposed to *how* it matches), there is no need to find a // greedy match. return true; } if (str[i] == '\0' || !AtomMatchesChar(escaped, c, str[i])) return false; } return false; } // Returns true iff regex matches a prefix of str. regex must be a // valid simple regular expression and not start with "^", or the // result is undefined. bool MatchRegexAtHead(const char* regex, const char* str) { if (*regex == '\0') // An empty regex matches a prefix of anything. return true; // "$" only matches the end of a string. Note that regex being // valid guarantees that there's nothing after "$" in it. if (*regex == '$') return *str == '\0'; // Is the first thing in regex an escape sequence? const bool escaped = *regex == '\\'; if (escaped) ++regex; if (IsRepeat(regex[1])) { // MatchRepetitionAndRegexAtHead() calls MatchRegexAtHead(), so // here's an indirect recursion. It terminates as the regex gets // shorter in each recursion. return MatchRepetitionAndRegexAtHead( escaped, regex[0], regex[1], regex + 2, str); } else { // regex isn't empty, isn't "$", and doesn't start with a // repetition. We match the first atom of regex with the first // character of str and recurse. return (*str != '\0') && AtomMatchesChar(escaped, *regex, *str) && MatchRegexAtHead(regex + 1, str + 1); } } // Returns true iff regex matches any substring of str. regex must be // a valid simple regular expression, or the result is undefined. // // The algorithm is recursive, but the recursion depth doesn't exceed // the regex length, so we won't need to worry about running out of // stack space normally. In rare cases the time complexity can be // exponential with respect to the regex length + the string length, // but usually it's must faster (often close to linear). bool MatchRegexAnywhere(const char* regex, const char* str) { if (regex == NULL || str == NULL) return false; if (*regex == '^') return MatchRegexAtHead(regex + 1, str); // A successful match can be anywhere in str. do { if (MatchRegexAtHead(regex, str)) return true; } while (*str++ != '\0'); return false; } // Implements the RE class. RE::~RE() { free(const_cast(pattern_)); free(const_cast(full_pattern_)); } // Returns true iff regular expression re matches the entire str. bool RE::FullMatch(const char* str, const RE& re) { return re.is_valid_ && MatchRegexAnywhere(re.full_pattern_, str); } // Returns true iff regular expression re matches a substring of str // (including str itself). bool RE::PartialMatch(const char* str, const RE& re) { return re.is_valid_ && MatchRegexAnywhere(re.pattern_, str); } // Initializes an RE from its string representation. void RE::Init(const char* regex) { pattern_ = full_pattern_ = NULL; if (regex != NULL) { pattern_ = posix::StrDup(regex); } is_valid_ = ValidateRegex(regex); if (!is_valid_) { // No need to calculate the full pattern when the regex is invalid. return; } const size_t len = strlen(regex); // Reserves enough bytes to hold the regular expression used for a // full match: we need space to prepend a '^', append a '$', and // terminate the string with '\0'. char* buffer = static_cast(malloc(len + 3)); full_pattern_ = buffer; if (*regex != '^') *buffer++ = '^'; // Makes sure full_pattern_ starts with '^'. // We don't use snprintf or strncpy, as they trigger a warning when // compiled with VC++ 8.0. memcpy(buffer, regex, len); buffer += len; if (len == 0 || regex[len - 1] != '$') *buffer++ = '$'; // Makes sure full_pattern_ ends with '$'. *buffer = '\0'; } #endif // GTEST_USES_POSIX_RE const char kUnknownFile[] = "unknown file"; // Formats a source file path and a line number as they would appear // in an error message from the compiler used to compile this code. GTEST_API_ ::std::string FormatFileLocation(const char* file, int line) { const std::string file_name(file == NULL ? kUnknownFile : file); if (line < 0) { return file_name + ":"; } #ifdef _MSC_VER return file_name + "(" + StreamableToString(line) + "):"; #else return file_name + ":" + StreamableToString(line) + ":"; #endif // _MSC_VER } // Formats a file location for compiler-independent XML output. // Although this function is not platform dependent, we put it next to // FormatFileLocation in order to contrast the two functions. // Note that FormatCompilerIndependentFileLocation() does NOT append colon // to the file location it produces, unlike FormatFileLocation(). GTEST_API_ ::std::string FormatCompilerIndependentFileLocation( const char* file, int line) { const std::string file_name(file == NULL ? kUnknownFile : file); if (line < 0) return file_name; else return file_name + ":" + StreamableToString(line); } GTestLog::GTestLog(GTestLogSeverity severity, const char* file, int line) : severity_(severity) { const char* const marker = severity == GTEST_INFO ? "[ INFO ]" : severity == GTEST_WARNING ? "[WARNING]" : severity == GTEST_ERROR ? "[ ERROR ]" : "[ FATAL ]"; GetStream() << ::std::endl << marker << " " << FormatFileLocation(file, line).c_str() << ": "; } // Flushes the buffers and, if severity is GTEST_FATAL, aborts the program. GTestLog::~GTestLog() { GetStream() << ::std::endl; if (severity_ == GTEST_FATAL) { fflush(stderr); posix::Abort(); } } // Disable Microsoft deprecation warnings for POSIX functions called from // this class (creat, dup, dup2, and close) #ifdef _MSC_VER # pragma warning(push) # pragma warning(disable: 4996) #endif // _MSC_VER #if GTEST_HAS_STREAM_REDIRECTION // Object that captures an output stream (stdout/stderr). class CapturedStream { public: // The ctor redirects the stream to a temporary file. explicit CapturedStream(int fd) : fd_(fd), uncaptured_fd_(dup(fd)) { # if GTEST_OS_WINDOWS char temp_dir_path[MAX_PATH + 1] = { '\0' }; // NOLINT char temp_file_path[MAX_PATH + 1] = { '\0' }; // NOLINT ::GetTempPathA(sizeof(temp_dir_path), temp_dir_path); const UINT success = ::GetTempFileNameA(temp_dir_path, "gtest_redir", 0, // Generate unique file name. temp_file_path); GTEST_CHECK_(success != 0) << "Unable to create a temporary file in " << temp_dir_path; const int captured_fd = creat(temp_file_path, _S_IREAD | _S_IWRITE); GTEST_CHECK_(captured_fd != -1) << "Unable to open temporary file " << temp_file_path; filename_ = temp_file_path; # else // There's no guarantee that a test has write access to the current // directory, so we create the temporary file in the /tmp directory // instead. We use /tmp on most systems, and /sdcard on Android. // That's because Android doesn't have /tmp. # if GTEST_OS_LINUX_ANDROID // Note: Android applications are expected to call the framework's // Context.getExternalStorageDirectory() method through JNI to get // the location of the world-writable SD Card directory. However, // this requires a Context handle, which cannot be retrieved // globally from native code. Doing so also precludes running the // code as part of a regular standalone executable, which doesn't // run in a Dalvik process (e.g. when running it through 'adb shell'). // // The location /sdcard is directly accessible from native code // and is the only location (unofficially) supported by the Android // team. It's generally a symlink to the real SD Card mount point // which can be /mnt/sdcard, /mnt/sdcard0, /system/media/sdcard, or // other OEM-customized locations. Never rely on these, and always // use /sdcard. char name_template[] = "/sdcard/gtest_captured_stream.XXXXXX"; # else char name_template[] = "/tmp/captured_stream.XXXXXX"; # endif // GTEST_OS_LINUX_ANDROID const int captured_fd = mkstemp(name_template); filename_ = name_template; # endif // GTEST_OS_WINDOWS fflush(NULL); dup2(captured_fd, fd_); close(captured_fd); } ~CapturedStream() { remove(filename_.c_str()); } std::string GetCapturedString() { if (uncaptured_fd_ != -1) { // Restores the original stream. fflush(NULL); dup2(uncaptured_fd_, fd_); close(uncaptured_fd_); uncaptured_fd_ = -1; } FILE* const file = posix::FOpen(filename_.c_str(), "r"); const std::string content = ReadEntireFile(file); posix::FClose(file); return content; } private: // Reads the entire content of a file as an std::string. static std::string ReadEntireFile(FILE* file); // Returns the size (in bytes) of a file. static size_t GetFileSize(FILE* file); const int fd_; // A stream to capture. int uncaptured_fd_; // Name of the temporary file holding the stderr output. ::std::string filename_; GTEST_DISALLOW_COPY_AND_ASSIGN_(CapturedStream); }; // Returns the size (in bytes) of a file. size_t CapturedStream::GetFileSize(FILE* file) { fseek(file, 0, SEEK_END); return static_cast(ftell(file)); } // Reads the entire content of a file as a string. std::string CapturedStream::ReadEntireFile(FILE* file) { const size_t file_size = GetFileSize(file); char* const buffer = new char[file_size]; size_t bytes_last_read = 0; // # of bytes read in the last fread() size_t bytes_read = 0; // # of bytes read so far fseek(file, 0, SEEK_SET); // Keeps reading the file until we cannot read further or the // pre-determined file size is reached. do { bytes_last_read = fread(buffer+bytes_read, 1, file_size-bytes_read, file); bytes_read += bytes_last_read; } while (bytes_last_read > 0 && bytes_read < file_size); const std::string content(buffer, bytes_read); delete[] buffer; return content; } # ifdef _MSC_VER # pragma warning(pop) # endif // _MSC_VER static CapturedStream* g_captured_stderr = NULL; static CapturedStream* g_captured_stdout = NULL; // Starts capturing an output stream (stdout/stderr). void CaptureStream(int fd, const char* stream_name, CapturedStream** stream) { if (*stream != NULL) { GTEST_LOG_(FATAL) << "Only one " << stream_name << " capturer can exist at a time."; } *stream = new CapturedStream(fd); } // Stops capturing the output stream and returns the captured string. std::string GetCapturedStream(CapturedStream** captured_stream) { const std::string content = (*captured_stream)->GetCapturedString(); delete *captured_stream; *captured_stream = NULL; return content; } // Starts capturing stdout. void CaptureStdout() { CaptureStream(kStdOutFileno, "stdout", &g_captured_stdout); } // Starts capturing stderr. void CaptureStderr() { CaptureStream(kStdErrFileno, "stderr", &g_captured_stderr); } // Stops capturing stdout and returns the captured string. std::string GetCapturedStdout() { return GetCapturedStream(&g_captured_stdout); } // Stops capturing stderr and returns the captured string. std::string GetCapturedStderr() { return GetCapturedStream(&g_captured_stderr); } #endif // GTEST_HAS_STREAM_REDIRECTION #if GTEST_HAS_DEATH_TEST // A copy of all command line arguments. Set by InitGoogleTest(). ::std::vector g_argvs; static const ::std::vector* g_injected_test_argvs = NULL; // Owned. void SetInjectableArgvs(const ::std::vector* argvs) { if (g_injected_test_argvs != argvs) delete g_injected_test_argvs; g_injected_test_argvs = argvs; } const ::std::vector& GetInjectableArgvs() { if (g_injected_test_argvs != NULL) { return *g_injected_test_argvs; } return g_argvs; } #endif // GTEST_HAS_DEATH_TEST #if GTEST_OS_WINDOWS_MOBILE namespace posix { void Abort() { DebugBreak(); TerminateProcess(GetCurrentProcess(), 1); } } // namespace posix #endif // GTEST_OS_WINDOWS_MOBILE // Returns the name of the environment variable corresponding to the // given flag. For example, FlagToEnvVar("foo") will return // "GTEST_FOO" in the open-source version. static std::string FlagToEnvVar(const char* flag) { const std::string full_flag = (Message() << GTEST_FLAG_PREFIX_ << flag).GetString(); Message env_var; for (size_t i = 0; i != full_flag.length(); i++) { env_var << ToUpper(full_flag.c_str()[i]); } return env_var.GetString(); } // Parses 'str' for a 32-bit signed integer. If successful, writes // the result to *value and returns true; otherwise leaves *value // unchanged and returns false. bool ParseInt32(const Message& src_text, const char* str, Int32* value) { // Parses the environment variable as a decimal integer. char* end = NULL; const long long_value = strtol(str, &end, 10); // NOLINT // Has strtol() consumed all characters in the string? if (*end != '\0') { // No - an invalid character was encountered. Message msg; msg << "WARNING: " << src_text << " is expected to be a 32-bit integer, but actually" << " has value \"" << str << "\".\n"; printf("%s", msg.GetString().c_str()); fflush(stdout); return false; } // Is the parsed value in the range of an Int32? const Int32 result = static_cast(long_value); if (long_value == LONG_MAX || long_value == LONG_MIN || // The parsed value overflows as a long. (strtol() returns // LONG_MAX or LONG_MIN when the input overflows.) result != long_value // The parsed value overflows as an Int32. ) { Message msg; msg << "WARNING: " << src_text << " is expected to be a 32-bit integer, but actually" << " has value " << str << ", which overflows.\n"; printf("%s", msg.GetString().c_str()); fflush(stdout); return false; } *value = result; return true; } // Reads and returns the Boolean environment variable corresponding to // the given flag; if it's not set, returns default_value. // // The value is considered true iff it's not "0". bool BoolFromGTestEnv(const char* flag, bool default_value) { const std::string env_var = FlagToEnvVar(flag); const char* const string_value = posix::GetEnv(env_var.c_str()); return string_value == NULL ? default_value : strcmp(string_value, "0") != 0; } // Reads and returns a 32-bit integer stored in the environment // variable corresponding to the given flag; if it isn't set or // doesn't represent a valid 32-bit integer, returns default_value. Int32 Int32FromGTestEnv(const char* flag, Int32 default_value) { const std::string env_var = FlagToEnvVar(flag); const char* const string_value = posix::GetEnv(env_var.c_str()); if (string_value == NULL) { // The environment variable is not set. return default_value; } Int32 result = default_value; if (!ParseInt32(Message() << "Environment variable " << env_var, string_value, &result)) { printf("The default value %s is used.\n", (Message() << default_value).GetString().c_str()); fflush(stdout); return default_value; } return result; } // Reads and returns the string environment variable corresponding to // the given flag; if it's not set, returns default_value. const char* StringFromGTestEnv(const char* flag, const char* default_value) { const std::string env_var = FlagToEnvVar(flag); const char* const value = posix::GetEnv(env_var.c_str()); return value == NULL ? default_value : value; } } // namespace internal } // namespace testing // Copyright 2007, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: wan@google.com (Zhanyong Wan) // Google Test - The Google C++ Testing Framework // // This file implements a universal value printer that can print a // value of any type T: // // void ::testing::internal::UniversalPrinter::Print(value, ostream_ptr); // // It uses the << operator when possible, and prints the bytes in the // object otherwise. A user can override its behavior for a class // type Foo by defining either operator<<(::std::ostream&, const Foo&) // or void PrintTo(const Foo&, ::std::ostream*) in the namespace that // defines Foo. #include #include #include // NOLINT #include namespace testing { namespace { using ::std::ostream; // Prints a segment of bytes in the given object. void PrintByteSegmentInObjectTo(const unsigned char* obj_bytes, size_t start, size_t count, ostream* os) { char text[5] = ""; for (size_t i = 0; i != count; i++) { const size_t j = start + i; if (i != 0) { // Organizes the bytes into groups of 2 for easy parsing by // human. if ((j % 2) == 0) *os << ' '; else *os << '-'; } GTEST_SNPRINTF_(text, sizeof(text), "%02X", obj_bytes[j]); *os << text; } } // Prints the bytes in the given value to the given ostream. void PrintBytesInObjectToImpl(const unsigned char* obj_bytes, size_t count, ostream* os) { // Tells the user how big the object is. *os << count << "-byte object <"; const size_t kThreshold = 132; const size_t kChunkSize = 64; // If the object size is bigger than kThreshold, we'll have to omit // some details by printing only the first and the last kChunkSize // bytes. // TODO(wan): let the user control the threshold using a flag. if (count < kThreshold) { PrintByteSegmentInObjectTo(obj_bytes, 0, count, os); } else { PrintByteSegmentInObjectTo(obj_bytes, 0, kChunkSize, os); *os << " ... "; // Rounds up to 2-byte boundary. const size_t resume_pos = (count - kChunkSize + 1)/2*2; PrintByteSegmentInObjectTo(obj_bytes, resume_pos, count - resume_pos, os); } *os << ">"; } } // namespace namespace internal2 { // Delegates to PrintBytesInObjectToImpl() to print the bytes in the // given object. The delegation simplifies the implementation, which // uses the << operator and thus is easier done outside of the // ::testing::internal namespace, which contains a << operator that // sometimes conflicts with the one in STL. void PrintBytesInObjectTo(const unsigned char* obj_bytes, size_t count, ostream* os) { PrintBytesInObjectToImpl(obj_bytes, count, os); } } // namespace internal2 namespace internal { // Depending on the value of a char (or wchar_t), we print it in one // of three formats: // - as is if it's a printable ASCII (e.g. 'a', '2', ' '), // - as a hexidecimal escape sequence (e.g. '\x7F'), or // - as a special escape sequence (e.g. '\r', '\n'). enum CharFormat { kAsIs, kHexEscape, kSpecialEscape }; // Returns true if c is a printable ASCII character. We test the // value of c directly instead of calling isprint(), which is buggy on // Windows Mobile. inline bool IsPrintableAscii(wchar_t c) { return 0x20 <= c && c <= 0x7E; } // Prints a wide or narrow char c as a character literal without the // quotes, escaping it when necessary; returns how c was formatted. // The template argument UnsignedChar is the unsigned version of Char, // which is the type of c. template static CharFormat PrintAsCharLiteralTo(Char c, ostream* os) { switch (static_cast(c)) { case L'\0': *os << "\\0"; break; case L'\'': *os << "\\'"; break; case L'\\': *os << "\\\\"; break; case L'\a': *os << "\\a"; break; case L'\b': *os << "\\b"; break; case L'\f': *os << "\\f"; break; case L'\n': *os << "\\n"; break; case L'\r': *os << "\\r"; break; case L'\t': *os << "\\t"; break; case L'\v': *os << "\\v"; break; default: if (IsPrintableAscii(c)) { *os << static_cast(c); return kAsIs; } else { *os << "\\x" + String::FormatHexInt(static_cast(c)); return kHexEscape; } } return kSpecialEscape; } // Prints a wchar_t c as if it's part of a string literal, escaping it when // necessary; returns how c was formatted. static CharFormat PrintAsStringLiteralTo(wchar_t c, ostream* os) { switch (c) { case L'\'': *os << "'"; return kAsIs; case L'"': *os << "\\\""; return kSpecialEscape; default: return PrintAsCharLiteralTo(c, os); } } // Prints a char c as if it's part of a string literal, escaping it when // necessary; returns how c was formatted. static CharFormat PrintAsStringLiteralTo(char c, ostream* os) { return PrintAsStringLiteralTo( static_cast(static_cast(c)), os); } // Prints a wide or narrow character c and its code. '\0' is printed // as "'\\0'", other unprintable characters are also properly escaped // using the standard C++ escape sequence. The template argument // UnsignedChar is the unsigned version of Char, which is the type of c. template void PrintCharAndCodeTo(Char c, ostream* os) { // First, print c as a literal in the most readable form we can find. *os << ((sizeof(c) > 1) ? "L'" : "'"); const CharFormat format = PrintAsCharLiteralTo(c, os); *os << "'"; // To aid user debugging, we also print c's code in decimal, unless // it's 0 (in which case c was printed as '\\0', making the code // obvious). if (c == 0) return; *os << " (" << static_cast(c); // For more convenience, we print c's code again in hexidecimal, // unless c was already printed in the form '\x##' or the code is in // [1, 9]. if (format == kHexEscape || (1 <= c && c <= 9)) { // Do nothing. } else { *os << ", 0x" << String::FormatHexInt(static_cast(c)); } *os << ")"; } void PrintTo(unsigned char c, ::std::ostream* os) { PrintCharAndCodeTo(c, os); } void PrintTo(signed char c, ::std::ostream* os) { PrintCharAndCodeTo(c, os); } // Prints a wchar_t as a symbol if it is printable or as its internal // code otherwise and also as its code. L'\0' is printed as "L'\\0'". void PrintTo(wchar_t wc, ostream* os) { PrintCharAndCodeTo(wc, os); } // Prints the given array of characters to the ostream. CharType must be either // char or wchar_t. // The array starts at begin, the length is len, it may include '\0' characters // and may not be NUL-terminated. template static void PrintCharsAsStringTo( const CharType* begin, size_t len, ostream* os) { const char* const kQuoteBegin = sizeof(CharType) == 1 ? "\"" : "L\""; *os << kQuoteBegin; bool is_previous_hex = false; for (size_t index = 0; index < len; ++index) { const CharType cur = begin[index]; if (is_previous_hex && IsXDigit(cur)) { // Previous character is of '\x..' form and this character can be // interpreted as another hexadecimal digit in its number. Break string to // disambiguate. *os << "\" " << kQuoteBegin; } is_previous_hex = PrintAsStringLiteralTo(cur, os) == kHexEscape; } *os << "\""; } // Prints a (const) char/wchar_t array of 'len' elements, starting at address // 'begin'. CharType must be either char or wchar_t. template static void UniversalPrintCharArray( const CharType* begin, size_t len, ostream* os) { // The code // const char kFoo[] = "foo"; // generates an array of 4, not 3, elements, with the last one being '\0'. // // Therefore when printing a char array, we don't print the last element if // it's '\0', such that the output matches the string literal as it's // written in the source code. if (len > 0 && begin[len - 1] == '\0') { PrintCharsAsStringTo(begin, len - 1, os); return; } // If, however, the last element in the array is not '\0', e.g. // const char kFoo[] = { 'f', 'o', 'o' }; // we must print the entire array. We also print a message to indicate // that the array is not NUL-terminated. PrintCharsAsStringTo(begin, len, os); *os << " (no terminating NUL)"; } // Prints a (const) char array of 'len' elements, starting at address 'begin'. void UniversalPrintArray(const char* begin, size_t len, ostream* os) { UniversalPrintCharArray(begin, len, os); } // Prints a (const) wchar_t array of 'len' elements, starting at address // 'begin'. void UniversalPrintArray(const wchar_t* begin, size_t len, ostream* os) { UniversalPrintCharArray(begin, len, os); } // Prints the given C string to the ostream. void PrintTo(const char* s, ostream* os) { if (s == NULL) { *os << "NULL"; } else { *os << ImplicitCast_(s) << " pointing to "; PrintCharsAsStringTo(s, strlen(s), os); } } // MSVC compiler can be configured to define whar_t as a typedef // of unsigned short. Defining an overload for const wchar_t* in that case // would cause pointers to unsigned shorts be printed as wide strings, // possibly accessing more memory than intended and causing invalid // memory accesses. MSVC defines _NATIVE_WCHAR_T_DEFINED symbol when // wchar_t is implemented as a native type. #if !defined(_MSC_VER) || defined(_NATIVE_WCHAR_T_DEFINED) // Prints the given wide C string to the ostream. void PrintTo(const wchar_t* s, ostream* os) { if (s == NULL) { *os << "NULL"; } else { *os << ImplicitCast_(s) << " pointing to "; PrintCharsAsStringTo(s, wcslen(s), os); } } #endif // wchar_t is native // Prints a ::string object. #if GTEST_HAS_GLOBAL_STRING void PrintStringTo(const ::string& s, ostream* os) { PrintCharsAsStringTo(s.data(), s.size(), os); } #endif // GTEST_HAS_GLOBAL_STRING void PrintStringTo(const ::std::string& s, ostream* os) { PrintCharsAsStringTo(s.data(), s.size(), os); } // Prints a ::wstring object. #if GTEST_HAS_GLOBAL_WSTRING void PrintWideStringTo(const ::wstring& s, ostream* os) { PrintCharsAsStringTo(s.data(), s.size(), os); } #endif // GTEST_HAS_GLOBAL_WSTRING #if GTEST_HAS_STD_WSTRING void PrintWideStringTo(const ::std::wstring& s, ostream* os) { PrintCharsAsStringTo(s.data(), s.size(), os); } #endif // GTEST_HAS_STD_WSTRING } // namespace internal } // namespace testing // Copyright 2008, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: mheule@google.com (Markus Heule) // // The Google C++ Testing Framework (Google Test) // Indicates that this translation unit is part of Google Test's // implementation. It must come before gtest-internal-inl.h is // included, or there will be a compiler error. This trick is to // prevent a user from accidentally including gtest-internal-inl.h in // his code. #define GTEST_IMPLEMENTATION_ 1 #undef GTEST_IMPLEMENTATION_ namespace testing { using internal::GetUnitTestImpl; // Gets the summary of the failure message by omitting the stack trace // in it. std::string TestPartResult::ExtractSummary(const char* message) { const char* const stack_trace = strstr(message, internal::kStackTraceMarker); return stack_trace == NULL ? message : std::string(message, stack_trace); } // Prints a TestPartResult object. std::ostream& operator<<(std::ostream& os, const TestPartResult& result) { return os << result.file_name() << ":" << result.line_number() << ": " << (result.type() == TestPartResult::kSuccess ? "Success" : result.type() == TestPartResult::kFatalFailure ? "Fatal failure" : "Non-fatal failure") << ":\n" << result.message() << std::endl; } // Appends a TestPartResult to the array. void TestPartResultArray::Append(const TestPartResult& result) { array_.push_back(result); } // Returns the TestPartResult at the given index (0-based). const TestPartResult& TestPartResultArray::GetTestPartResult(int index) const { if (index < 0 || index >= size()) { printf("\nInvalid index (%d) into TestPartResultArray.\n", index); internal::posix::Abort(); } return array_[index]; } // Returns the number of TestPartResult objects in the array. int TestPartResultArray::size() const { return static_cast(array_.size()); } namespace internal { HasNewFatalFailureHelper::HasNewFatalFailureHelper() : has_new_fatal_failure_(false), original_reporter_(GetUnitTestImpl()-> GetTestPartResultReporterForCurrentThread()) { GetUnitTestImpl()->SetTestPartResultReporterForCurrentThread(this); } HasNewFatalFailureHelper::~HasNewFatalFailureHelper() { GetUnitTestImpl()->SetTestPartResultReporterForCurrentThread( original_reporter_); } void HasNewFatalFailureHelper::ReportTestPartResult( const TestPartResult& result) { if (result.fatally_failed()) has_new_fatal_failure_ = true; original_reporter_->ReportTestPartResult(result); } } // namespace internal } // namespace testing // Copyright 2008 Google Inc. // All Rights Reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: wan@google.com (Zhanyong Wan) namespace testing { namespace internal { #if GTEST_HAS_TYPED_TEST_P // Skips to the first non-space char in str. Returns an empty string if str // contains only whitespace characters. static const char* SkipSpaces(const char* str) { while (IsSpace(*str)) str++; return str; } // Verifies that registered_tests match the test names in // defined_test_names_; returns registered_tests if successful, or // aborts the program otherwise. const char* TypedTestCasePState::VerifyRegisteredTestNames( const char* file, int line, const char* registered_tests) { typedef ::std::set::const_iterator DefinedTestIter; registered_ = true; // Skip initial whitespace in registered_tests since some // preprocessors prefix stringizied literals with whitespace. registered_tests = SkipSpaces(registered_tests); Message errors; ::std::set tests; for (const char* names = registered_tests; names != NULL; names = SkipComma(names)) { const std::string name = GetPrefixUntilComma(names); if (tests.count(name) != 0) { errors << "Test " << name << " is listed more than once.\n"; continue; } bool found = false; for (DefinedTestIter it = defined_test_names_.begin(); it != defined_test_names_.end(); ++it) { if (name == *it) { found = true; break; } } if (found) { tests.insert(name); } else { errors << "No test named " << name << " can be found in this test case.\n"; } } for (DefinedTestIter it = defined_test_names_.begin(); it != defined_test_names_.end(); ++it) { if (tests.count(*it) == 0) { errors << "You forgot to list test " << *it << ".\n"; } } const std::string& errors_str = errors.GetString(); if (errors_str != "") { fprintf(stderr, "%s %s", FormatFileLocation(file, line).c_str(), errors_str.c_str()); fflush(stderr); posix::Abort(); } return registered_tests; } #endif // GTEST_HAS_TYPED_TEST_P } // namespace internal } // namespace testing april-ann-0.4.1/packages/basics/gtest/c_src/gtest.h000066400000000000000000031271131263004425400221450ustar00rootroot00000000000000// Adapted by Francisco Zamora-Martinez, 2014 // // Copyright 2005, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: wan@google.com (Zhanyong Wan) // // The Google C++ Testing Framework (Google Test) // // This header file defines the public API for Google Test. It should be // included by any test program that uses Google Test. // // IMPORTANT NOTE: Due to limitation of the C++ language, we have to // leave some internal implementation details in this header file. // They are clearly marked by comments like this: // // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. // // Such code is NOT meant to be used by a user directly, and is subject // to CHANGE WITHOUT NOTICE. Therefore DO NOT DEPEND ON IT in a user // program! // // Acknowledgment: Google Test borrowed the idea of automatic test // registration from Barthelemy Dagenais' (barthelemy@prologique.com) // easyUnit framework. #ifndef GTEST_INCLUDE_GTEST_GTEST_H_ #define GTEST_INCLUDE_GTEST_GTEST_H_ #define GTEST_HAS_PTHREAD 0 // #define GTEST_HAS_STD_STRING 1 // #define GTEST_HAS_STD_WSTRING 1 // #define GTEST_HAS_TR1_TUPLE 1 #include #include #include // Copyright 2005, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Authors: wan@google.com (Zhanyong Wan), eefacm@gmail.com (Sean Mcafee) // // The Google C++ Testing Framework (Google Test) // // This header file declares functions and macros used internally by // Google Test. They are subject to change without notice. #ifndef GTEST_INCLUDE_GTEST_INTERNAL_GTEST_INTERNAL_H_ #define GTEST_INCLUDE_GTEST_INTERNAL_GTEST_INTERNAL_H_ // Copyright 2005, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Authors: wan@google.com (Zhanyong Wan) // // Low-level types and utilities for porting Google Test to various // platforms. They are subject to change without notice. DO NOT USE // THEM IN USER CODE. // // This file is fundamental to Google Test. All other Google Test source // files are expected to #include this. Therefore, it cannot #include // any other Google Test header. #ifndef GTEST_INCLUDE_GTEST_INTERNAL_GTEST_PORT_H_ #define GTEST_INCLUDE_GTEST_INTERNAL_GTEST_PORT_H_ // The user can define the following macros in the build script to // control Google Test's behavior. If the user doesn't define a macro // in this list, Google Test will define it. // // GTEST_HAS_CLONE - Define it to 1/0 to indicate that clone(2) // is/isn't available. // GTEST_HAS_EXCEPTIONS - Define it to 1/0 to indicate that exceptions // are enabled. // GTEST_HAS_GLOBAL_STRING - Define it to 1/0 to indicate that ::string // is/isn't available (some systems define // ::string, which is different to std::string). // GTEST_HAS_GLOBAL_WSTRING - Define it to 1/0 to indicate that ::string // is/isn't available (some systems define // ::wstring, which is different to std::wstring). // GTEST_HAS_POSIX_RE - Define it to 1/0 to indicate that POSIX regular // expressions are/aren't available. // GTEST_HAS_PTHREAD - Define it to 1/0 to indicate that // is/isn't available. // GTEST_HAS_RTTI - Define it to 1/0 to indicate that RTTI is/isn't // enabled. // GTEST_HAS_STD_WSTRING - Define it to 1/0 to indicate that // std::wstring does/doesn't work (Google Test can // be used where std::wstring is unavailable). // GTEST_HAS_TR1_TUPLE - Define it to 1/0 to indicate tr1::tuple // is/isn't available. // GTEST_HAS_SEH - Define it to 1/0 to indicate whether the // compiler supports Microsoft's "Structured // Exception Handling". // GTEST_HAS_STREAM_REDIRECTION // - Define it to 1/0 to indicate whether the // platform supports I/O stream redirection using // dup() and dup2(). // GTEST_USE_OWN_TR1_TUPLE - Define it to 1/0 to indicate whether Google // Test's own tr1 tuple implementation should be // used. Unused when the user sets // GTEST_HAS_TR1_TUPLE to 0. // GTEST_LANG_CXX11 - Define it to 1/0 to indicate that Google Test // is building in C++11/C++98 mode. // GTEST_LINKED_AS_SHARED_LIBRARY // - Define to 1 when compiling tests that use // Google Test as a shared library (known as // DLL on Windows). // GTEST_CREATE_SHARED_LIBRARY // - Define to 1 when compiling Google Test itself // as a shared library. // This header defines the following utilities: // // Macros indicating the current platform (defined to 1 if compiled on // the given platform; otherwise undefined): // GTEST_OS_AIX - IBM AIX // GTEST_OS_CYGWIN - Cygwin // GTEST_OS_HPUX - HP-UX // GTEST_OS_LINUX - Linux // GTEST_OS_LINUX_ANDROID - Google Android // GTEST_OS_MAC - Mac OS X // GTEST_OS_IOS - iOS // GTEST_OS_IOS_SIMULATOR - iOS simulator // GTEST_OS_NACL - Google Native Client (NaCl) // GTEST_OS_OPENBSD - OpenBSD // GTEST_OS_QNX - QNX // GTEST_OS_SOLARIS - Sun Solaris // GTEST_OS_SYMBIAN - Symbian // GTEST_OS_WINDOWS - Windows (Desktop, MinGW, or Mobile) // GTEST_OS_WINDOWS_DESKTOP - Windows Desktop // GTEST_OS_WINDOWS_MINGW - MinGW // GTEST_OS_WINDOWS_MOBILE - Windows Mobile // GTEST_OS_ZOS - z/OS // // Among the platforms, Cygwin, Linux, Max OS X, and Windows have the // most stable support. Since core members of the Google Test project // don't have access to other platforms, support for them may be less // stable. If you notice any problems on your platform, please notify // googletestframework@googlegroups.com (patches for fixing them are // even more welcome!). // // Note that it is possible that none of the GTEST_OS_* macros are defined. // // Macros indicating available Google Test features (defined to 1 if // the corresponding feature is supported; otherwise undefined): // GTEST_HAS_COMBINE - the Combine() function (for value-parameterized // tests) // GTEST_HAS_DEATH_TEST - death tests // GTEST_HAS_PARAM_TEST - value-parameterized tests // GTEST_HAS_TYPED_TEST - typed tests // GTEST_HAS_TYPED_TEST_P - type-parameterized tests // GTEST_USES_POSIX_RE - enhanced POSIX regex is used. Do not confuse with // GTEST_HAS_POSIX_RE (see above) which users can // define themselves. // GTEST_USES_SIMPLE_RE - our own simple regex is used; // the above two are mutually exclusive. // GTEST_CAN_COMPARE_NULL - accepts untyped NULL in EXPECT_EQ(). // // Macros for basic C++ coding: // GTEST_AMBIGUOUS_ELSE_BLOCKER_ - for disabling a gcc warning. // GTEST_ATTRIBUTE_UNUSED_ - declares that a class' instances or a // variable don't have to be used. // GTEST_DISALLOW_ASSIGN_ - disables operator=. // GTEST_DISALLOW_COPY_AND_ASSIGN_ - disables copy ctor and operator=. // GTEST_MUST_USE_RESULT_ - declares that a function's result must be used. // // Synchronization: // Mutex, MutexLock, ThreadLocal, GetThreadCount() // - synchronization primitives. // GTEST_IS_THREADSAFE - defined to 1 to indicate that the above // synchronization primitives have real implementations // and Google Test is thread-safe; or 0 otherwise. // // Template meta programming: // is_pointer - as in TR1; needed on Symbian and IBM XL C/C++ only. // IteratorTraits - partial implementation of std::iterator_traits, which // is not available in libCstd when compiled with Sun C++. // // Smart pointers: // scoped_ptr - as in TR2. // // Regular expressions: // RE - a simple regular expression class using the POSIX // Extended Regular Expression syntax on UNIX-like // platforms, or a reduced regular exception syntax on // other platforms, including Windows. // // Logging: // GTEST_LOG_() - logs messages at the specified severity level. // LogToStderr() - directs all log messages to stderr. // FlushInfoLog() - flushes informational log messages. // // Stdout and stderr capturing: // CaptureStdout() - starts capturing stdout. // GetCapturedStdout() - stops capturing stdout and returns the captured // string. // CaptureStderr() - starts capturing stderr. // GetCapturedStderr() - stops capturing stderr and returns the captured // string. // // Integer types: // TypeWithSize - maps an integer to a int type. // Int32, UInt32, Int64, UInt64, TimeInMillis // - integers of known sizes. // BiggestInt - the biggest signed integer type. // // Command-line utilities: // GTEST_FLAG() - references a flag. // GTEST_DECLARE_*() - declares a flag. // GTEST_DEFINE_*() - defines a flag. // GetInjectableArgvs() - returns the command line as a vector of strings. // // Environment variable utilities: // GetEnv() - gets the value of an environment variable. // BoolFromGTestEnv() - parses a bool environment variable. // Int32FromGTestEnv() - parses an Int32 environment variable. // StringFromGTestEnv() - parses a string environment variable. #include // for isspace, etc #include // for ptrdiff_t #include #include #include #ifndef _WIN32_WCE # include # include #endif // !_WIN32_WCE #if defined __APPLE__ # include # include #endif #include // NOLINT #include // NOLINT #include // NOLINT #define GTEST_DEV_EMAIL_ "googletestframework@@googlegroups.com" #define GTEST_FLAG_PREFIX_ "gtest_" #define GTEST_FLAG_PREFIX_DASH_ "gtest-" #define GTEST_FLAG_PREFIX_UPPER_ "GTEST_" #define GTEST_NAME_ "Google Test" #define GTEST_PROJECT_URL_ "http://code.google.com/p/googletest/" // Determines the version of gcc that is used to compile this. #ifdef __GNUC__ // 40302 means version 4.3.2. # define GTEST_GCC_VER_ \ (__GNUC__*10000 + __GNUC_MINOR__*100 + __GNUC_PATCHLEVEL__) #endif // __GNUC__ // Determines the platform on which Google Test is compiled. #ifdef __CYGWIN__ # define GTEST_OS_CYGWIN 1 #elif defined __SYMBIAN32__ # define GTEST_OS_SYMBIAN 1 #elif defined _WIN32 # define GTEST_OS_WINDOWS 1 # ifdef _WIN32_WCE # define GTEST_OS_WINDOWS_MOBILE 1 # elif defined(__MINGW__) || defined(__MINGW32__) # define GTEST_OS_WINDOWS_MINGW 1 # else # define GTEST_OS_WINDOWS_DESKTOP 1 # endif // _WIN32_WCE #elif defined __APPLE__ # define GTEST_OS_MAC 1 # if TARGET_OS_IPHONE # define GTEST_OS_IOS 1 # if TARGET_IPHONE_SIMULATOR # define GTEST_OS_IOS_SIMULATOR 1 # endif # endif #elif defined __linux__ # define GTEST_OS_LINUX 1 # if defined __ANDROID__ # define GTEST_OS_LINUX_ANDROID 1 # endif #elif defined __MVS__ # define GTEST_OS_ZOS 1 #elif defined(__sun) && defined(__SVR4) # define GTEST_OS_SOLARIS 1 #elif defined(_AIX) # define GTEST_OS_AIX 1 #elif defined(__hpux) # define GTEST_OS_HPUX 1 #elif defined __native_client__ # define GTEST_OS_NACL 1 #elif defined __OpenBSD__ # define GTEST_OS_OPENBSD 1 #elif defined __QNX__ # define GTEST_OS_QNX 1 #endif // __CYGWIN__ #ifndef GTEST_LANG_CXX11 // gcc and clang define __GXX_EXPERIMENTAL_CXX0X__ when // -std={c,gnu}++{0x,11} is passed. The C++11 standard specifies a // value for __cplusplus, and recent versions of clang, gcc, and // probably other compilers set that too in C++11 mode. # if __GXX_EXPERIMENTAL_CXX0X__ || __cplusplus >= 201103L // Compiling in at least C++11 mode. # define GTEST_LANG_CXX11 1 # else # define GTEST_LANG_CXX11 0 # endif #endif // Brings in definitions for functions used in the testing::internal::posix // namespace (read, write, close, chdir, isatty, stat). We do not currently // use them on Windows Mobile. #if !GTEST_OS_WINDOWS // This assumes that non-Windows OSes provide unistd.h. For OSes where this // is not the case, we need to include headers that provide the functions // mentioned above. # include # include #elif !GTEST_OS_WINDOWS_MOBILE # include # include #endif #if GTEST_OS_LINUX_ANDROID // Used to define __ANDROID_API__ matching the target NDK API level. # include // NOLINT #endif // Defines this to true iff Google Test can use POSIX regular expressions. #ifndef GTEST_HAS_POSIX_RE # if GTEST_OS_LINUX_ANDROID // On Android, is only available starting with Gingerbread. # define GTEST_HAS_POSIX_RE (__ANDROID_API__ >= 9) # else # define GTEST_HAS_POSIX_RE (!GTEST_OS_WINDOWS) # endif #endif #if GTEST_HAS_POSIX_RE // On some platforms, needs someone to define size_t, and // won't compile otherwise. We can #include it here as we already // included , which is guaranteed to define size_t through // . # include // NOLINT # define GTEST_USES_POSIX_RE 1 #elif GTEST_OS_WINDOWS // is not available on Windows. Use our own simple regex // implementation instead. # define GTEST_USES_SIMPLE_RE 1 #else // may not be available on this platform. Use our own // simple regex implementation instead. # define GTEST_USES_SIMPLE_RE 1 #endif // GTEST_HAS_POSIX_RE #ifndef GTEST_HAS_EXCEPTIONS // The user didn't tell us whether exceptions are enabled, so we need // to figure it out. # if defined(_MSC_VER) || defined(__BORLANDC__) // MSVC's and C++Builder's implementations of the STL use the _HAS_EXCEPTIONS // macro to enable exceptions, so we'll do the same. // Assumes that exceptions are enabled by default. # ifndef _HAS_EXCEPTIONS # define _HAS_EXCEPTIONS 1 # endif // _HAS_EXCEPTIONS # define GTEST_HAS_EXCEPTIONS _HAS_EXCEPTIONS # elif defined(__GNUC__) && __EXCEPTIONS // gcc defines __EXCEPTIONS to 1 iff exceptions are enabled. # define GTEST_HAS_EXCEPTIONS 1 # elif defined(__SUNPRO_CC) // Sun Pro CC supports exceptions. However, there is no compile-time way of // detecting whether they are enabled or not. Therefore, we assume that // they are enabled unless the user tells us otherwise. # define GTEST_HAS_EXCEPTIONS 1 # elif defined(__IBMCPP__) && __EXCEPTIONS // xlC defines __EXCEPTIONS to 1 iff exceptions are enabled. # define GTEST_HAS_EXCEPTIONS 1 # elif defined(__HP_aCC) // Exception handling is in effect by default in HP aCC compiler. It has to // be turned of by +noeh compiler option if desired. # define GTEST_HAS_EXCEPTIONS 1 # else // For other compilers, we assume exceptions are disabled to be // conservative. # define GTEST_HAS_EXCEPTIONS 0 # endif // defined(_MSC_VER) || defined(__BORLANDC__) #endif // GTEST_HAS_EXCEPTIONS #if !defined(GTEST_HAS_STD_STRING) // Even though we don't use this macro any longer, we keep it in case // some clients still depend on it. # define GTEST_HAS_STD_STRING 1 #elif !GTEST_HAS_STD_STRING // The user told us that ::std::string isn't available. # error "Google Test cannot be used where ::std::string isn't available." #endif // !defined(GTEST_HAS_STD_STRING) #ifndef GTEST_HAS_GLOBAL_STRING // The user didn't tell us whether ::string is available, so we need // to figure it out. # define GTEST_HAS_GLOBAL_STRING 0 #endif // GTEST_HAS_GLOBAL_STRING #ifndef GTEST_HAS_STD_WSTRING // The user didn't tell us whether ::std::wstring is available, so we need // to figure it out. // TODO(wan@google.com): uses autoconf to detect whether ::std::wstring // is available. // Cygwin 1.7 and below doesn't support ::std::wstring. // Solaris' libc++ doesn't support it either. Android has // no support for it at least as recent as Froyo (2.2). # define GTEST_HAS_STD_WSTRING \ (!(GTEST_OS_LINUX_ANDROID || GTEST_OS_CYGWIN || GTEST_OS_SOLARIS)) #endif // GTEST_HAS_STD_WSTRING #ifndef GTEST_HAS_GLOBAL_WSTRING // The user didn't tell us whether ::wstring is available, so we need // to figure it out. # define GTEST_HAS_GLOBAL_WSTRING \ (GTEST_HAS_STD_WSTRING && GTEST_HAS_GLOBAL_STRING) #endif // GTEST_HAS_GLOBAL_WSTRING // Determines whether RTTI is available. #ifndef GTEST_HAS_RTTI // The user didn't tell us whether RTTI is enabled, so we need to // figure it out. # ifdef _MSC_VER # ifdef _CPPRTTI // MSVC defines this macro iff RTTI is enabled. # define GTEST_HAS_RTTI 1 # else # define GTEST_HAS_RTTI 0 # endif // Starting with version 4.3.2, gcc defines __GXX_RTTI iff RTTI is enabled. # elif defined(__GNUC__) && (GTEST_GCC_VER_ >= 40302) # ifdef __GXX_RTTI // When building against STLport with the Android NDK and with // -frtti -fno-exceptions, the build fails at link time with undefined // references to __cxa_bad_typeid. Note sure if STL or toolchain bug, // so disable RTTI when detected. # if GTEST_OS_LINUX_ANDROID && defined(_STLPORT_MAJOR) && \ !defined(__EXCEPTIONS) # define GTEST_HAS_RTTI 0 # else # define GTEST_HAS_RTTI 1 # endif // GTEST_OS_LINUX_ANDROID && __STLPORT_MAJOR && !__EXCEPTIONS # else # define GTEST_HAS_RTTI 0 # endif // __GXX_RTTI // Clang defines __GXX_RTTI starting with version 3.0, but its manual recommends // using has_feature instead. has_feature(cxx_rtti) is supported since 2.7, the // first version with C++ support. # elif defined(__clang__) # define GTEST_HAS_RTTI __has_feature(cxx_rtti) // Starting with version 9.0 IBM Visual Age defines __RTTI_ALL__ to 1 if // both the typeid and dynamic_cast features are present. # elif defined(__IBMCPP__) && (__IBMCPP__ >= 900) # ifdef __RTTI_ALL__ # define GTEST_HAS_RTTI 1 # else # define GTEST_HAS_RTTI 0 # endif # else // For all other compilers, we assume RTTI is enabled. # define GTEST_HAS_RTTI 1 # endif // _MSC_VER #endif // GTEST_HAS_RTTI // It's this header's responsibility to #include when RTTI // is enabled. #if GTEST_HAS_RTTI # include #endif // Determines whether Google Test can use the pthreads library. #ifndef GTEST_HAS_PTHREAD // The user didn't tell us explicitly, so we assume pthreads support is // available on Linux and Mac. // // To disable threading support in Google Test, add -DGTEST_HAS_PTHREAD=0 // to your compiler flags. # define GTEST_HAS_PTHREAD (GTEST_OS_LINUX || GTEST_OS_MAC || GTEST_OS_HPUX \ || GTEST_OS_QNX) #endif // GTEST_HAS_PTHREAD #if GTEST_HAS_PTHREAD // gtest-port.h guarantees to #include when GTEST_HAS_PTHREAD is // true. # include // NOLINT // For timespec and nanosleep, used below. # include // NOLINT #endif // Determines whether Google Test can use tr1/tuple. You can define // this macro to 0 to prevent Google Test from using tuple (any // feature depending on tuple with be disabled in this mode). #ifndef GTEST_HAS_TR1_TUPLE # if GTEST_OS_LINUX_ANDROID && defined(_STLPORT_MAJOR) // STLport, provided with the Android NDK, has neither or . # define GTEST_HAS_TR1_TUPLE 0 # else // The user didn't tell us not to do it, so we assume it's OK. # define GTEST_HAS_TR1_TUPLE 1 # endif #endif // GTEST_HAS_TR1_TUPLE // Determines whether Google Test's own tr1 tuple implementation // should be used. #ifndef GTEST_USE_OWN_TR1_TUPLE // The user didn't tell us, so we need to figure it out. // We use our own TR1 tuple if we aren't sure the user has an // implementation of it already. At this time, libstdc++ 4.0.0+ and // MSVC 2010 are the only mainstream standard libraries that come // with a TR1 tuple implementation. NVIDIA's CUDA NVCC compiler // pretends to be GCC by defining __GNUC__ and friends, but cannot // compile GCC's tuple implementation. MSVC 2008 (9.0) provides TR1 // tuple in a 323 MB Feature Pack download, which we cannot assume the // user has. QNX's QCC compiler is a modified GCC but it doesn't // support TR1 tuple. libc++ only provides std::tuple, in C++11 mode, // and it can be used with some compilers that define __GNUC__. # if (defined(__GNUC__) && !defined(__CUDACC__) && (GTEST_GCC_VER_ >= 40000) \ && !GTEST_OS_QNX && !defined(_LIBCPP_VERSION)) || _MSC_VER >= 1600 # define GTEST_ENV_HAS_TR1_TUPLE_ 1 # endif // C++11 specifies that provides std::tuple. Use that if gtest is used // in C++11 mode and libstdc++ isn't very old (binaries targeting OS X 10.6 // can build with clang but need to use gcc4.2's libstdc++). # if GTEST_LANG_CXX11 && (!defined(__GLIBCXX__) || __GLIBCXX__ > 20110325) # define GTEST_ENV_HAS_STD_TUPLE_ 1 # endif # if GTEST_ENV_HAS_TR1_TUPLE_ || GTEST_ENV_HAS_STD_TUPLE_ # define GTEST_USE_OWN_TR1_TUPLE 0 # else # define GTEST_USE_OWN_TR1_TUPLE 1 # endif #endif // GTEST_USE_OWN_TR1_TUPLE // To avoid conditional compilation everywhere, we make it // gtest-port.h's responsibility to #include the header implementing // tr1/tuple. #if GTEST_HAS_TR1_TUPLE # if GTEST_USE_OWN_TR1_TUPLE // This file was GENERATED by command: // pump.py gtest-tuple.h.pump // DO NOT EDIT BY HAND!!! // Copyright 2009 Google Inc. // All Rights Reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: wan@google.com (Zhanyong Wan) // Implements a subset of TR1 tuple needed by Google Test and Google Mock. #ifndef GTEST_INCLUDE_GTEST_INTERNAL_GTEST_TUPLE_H_ #define GTEST_INCLUDE_GTEST_INTERNAL_GTEST_TUPLE_H_ #include // For ::std::pair. // The compiler used in Symbian has a bug that prevents us from declaring the // tuple template as a friend (it complains that tuple is redefined). This // hack bypasses the bug by declaring the members that should otherwise be // private as public. // Sun Studio versions < 12 also have the above bug. #if defined(__SYMBIAN32__) || (defined(__SUNPRO_CC) && __SUNPRO_CC < 0x590) # define GTEST_DECLARE_TUPLE_AS_FRIEND_ public: #else # define GTEST_DECLARE_TUPLE_AS_FRIEND_ \ template friend class tuple; \ private: #endif // GTEST_n_TUPLE_(T) is the type of an n-tuple. #define GTEST_0_TUPLE_(T) tuple<> #define GTEST_1_TUPLE_(T) tuple #define GTEST_2_TUPLE_(T) tuple #define GTEST_3_TUPLE_(T) tuple #define GTEST_4_TUPLE_(T) tuple #define GTEST_5_TUPLE_(T) tuple #define GTEST_6_TUPLE_(T) tuple #define GTEST_7_TUPLE_(T) tuple #define GTEST_8_TUPLE_(T) tuple #define GTEST_9_TUPLE_(T) tuple #define GTEST_10_TUPLE_(T) tuple // GTEST_n_TYPENAMES_(T) declares a list of n typenames. #define GTEST_0_TYPENAMES_(T) #define GTEST_1_TYPENAMES_(T) typename T##0 #define GTEST_2_TYPENAMES_(T) typename T##0, typename T##1 #define GTEST_3_TYPENAMES_(T) typename T##0, typename T##1, typename T##2 #define GTEST_4_TYPENAMES_(T) typename T##0, typename T##1, typename T##2, \ typename T##3 #define GTEST_5_TYPENAMES_(T) typename T##0, typename T##1, typename T##2, \ typename T##3, typename T##4 #define GTEST_6_TYPENAMES_(T) typename T##0, typename T##1, typename T##2, \ typename T##3, typename T##4, typename T##5 #define GTEST_7_TYPENAMES_(T) typename T##0, typename T##1, typename T##2, \ typename T##3, typename T##4, typename T##5, typename T##6 #define GTEST_8_TYPENAMES_(T) typename T##0, typename T##1, typename T##2, \ typename T##3, typename T##4, typename T##5, typename T##6, typename T##7 #define GTEST_9_TYPENAMES_(T) typename T##0, typename T##1, typename T##2, \ typename T##3, typename T##4, typename T##5, typename T##6, \ typename T##7, typename T##8 #define GTEST_10_TYPENAMES_(T) typename T##0, typename T##1, typename T##2, \ typename T##3, typename T##4, typename T##5, typename T##6, \ typename T##7, typename T##8, typename T##9 // In theory, defining stuff in the ::std namespace is undefined // behavior. We can do this as we are playing the role of a standard // library vendor. namespace std { namespace tr1 { template class tuple; // Anything in namespace gtest_internal is Google Test's INTERNAL // IMPLEMENTATION DETAIL and MUST NOT BE USED DIRECTLY in user code. namespace gtest_internal { // ByRef::type is T if T is a reference; otherwise it's const T&. template struct ByRef { typedef const T& type; }; // NOLINT template struct ByRef { typedef T& type; }; // NOLINT // A handy wrapper for ByRef. #define GTEST_BY_REF_(T) typename ::std::tr1::gtest_internal::ByRef::type // AddRef::type is T if T is a reference; otherwise it's T&. This // is the same as tr1::add_reference::type. template struct AddRef { typedef T& type; }; // NOLINT template struct AddRef { typedef T& type; }; // NOLINT // A handy wrapper for AddRef. #define GTEST_ADD_REF_(T) typename ::std::tr1::gtest_internal::AddRef::type // A helper for implementing get(). template class Get; // A helper for implementing tuple_element. kIndexValid is true // iff k < the number of fields in tuple type T. template struct TupleElement; template struct TupleElement { typedef T0 type; }; template struct TupleElement { typedef T1 type; }; template struct TupleElement { typedef T2 type; }; template struct TupleElement { typedef T3 type; }; template struct TupleElement { typedef T4 type; }; template struct TupleElement { typedef T5 type; }; template struct TupleElement { typedef T6 type; }; template struct TupleElement { typedef T7 type; }; template struct TupleElement { typedef T8 type; }; template struct TupleElement { typedef T9 type; }; } // namespace gtest_internal template <> class tuple<> { public: tuple() {} tuple(const tuple& /* t */) {} tuple& operator=(const tuple& /* t */) { return *this; } }; template class GTEST_1_TUPLE_(T) { public: template friend class gtest_internal::Get; tuple() : f0_() {} explicit tuple(GTEST_BY_REF_(T0) f0) : f0_(f0) {} tuple(const tuple& t) : f0_(t.f0_) {} template tuple(const GTEST_1_TUPLE_(U)& t) : f0_(t.f0_) {} tuple& operator=(const tuple& t) { return CopyFrom(t); } template tuple& operator=(const GTEST_1_TUPLE_(U)& t) { return CopyFrom(t); } GTEST_DECLARE_TUPLE_AS_FRIEND_ template tuple& CopyFrom(const GTEST_1_TUPLE_(U)& t) { f0_ = t.f0_; return *this; } T0 f0_; }; template class GTEST_2_TUPLE_(T) { public: template friend class gtest_internal::Get; tuple() : f0_(), f1_() {} explicit tuple(GTEST_BY_REF_(T0) f0, GTEST_BY_REF_(T1) f1) : f0_(f0), f1_(f1) {} tuple(const tuple& t) : f0_(t.f0_), f1_(t.f1_) {} template tuple(const GTEST_2_TUPLE_(U)& t) : f0_(t.f0_), f1_(t.f1_) {} template tuple(const ::std::pair& p) : f0_(p.first), f1_(p.second) {} tuple& operator=(const tuple& t) { return CopyFrom(t); } template tuple& operator=(const GTEST_2_TUPLE_(U)& t) { return CopyFrom(t); } template tuple& operator=(const ::std::pair& p) { f0_ = p.first; f1_ = p.second; return *this; } GTEST_DECLARE_TUPLE_AS_FRIEND_ template tuple& CopyFrom(const GTEST_2_TUPLE_(U)& t) { f0_ = t.f0_; f1_ = t.f1_; return *this; } T0 f0_; T1 f1_; }; template class GTEST_3_TUPLE_(T) { public: template friend class gtest_internal::Get; tuple() : f0_(), f1_(), f2_() {} explicit tuple(GTEST_BY_REF_(T0) f0, GTEST_BY_REF_(T1) f1, GTEST_BY_REF_(T2) f2) : f0_(f0), f1_(f1), f2_(f2) {} tuple(const tuple& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_) {} template tuple(const GTEST_3_TUPLE_(U)& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_) {} tuple& operator=(const tuple& t) { return CopyFrom(t); } template tuple& operator=(const GTEST_3_TUPLE_(U)& t) { return CopyFrom(t); } GTEST_DECLARE_TUPLE_AS_FRIEND_ template tuple& CopyFrom(const GTEST_3_TUPLE_(U)& t) { f0_ = t.f0_; f1_ = t.f1_; f2_ = t.f2_; return *this; } T0 f0_; T1 f1_; T2 f2_; }; template class GTEST_4_TUPLE_(T) { public: template friend class gtest_internal::Get; tuple() : f0_(), f1_(), f2_(), f3_() {} explicit tuple(GTEST_BY_REF_(T0) f0, GTEST_BY_REF_(T1) f1, GTEST_BY_REF_(T2) f2, GTEST_BY_REF_(T3) f3) : f0_(f0), f1_(f1), f2_(f2), f3_(f3) {} tuple(const tuple& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_), f3_(t.f3_) {} template tuple(const GTEST_4_TUPLE_(U)& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_), f3_(t.f3_) {} tuple& operator=(const tuple& t) { return CopyFrom(t); } template tuple& operator=(const GTEST_4_TUPLE_(U)& t) { return CopyFrom(t); } GTEST_DECLARE_TUPLE_AS_FRIEND_ template tuple& CopyFrom(const GTEST_4_TUPLE_(U)& t) { f0_ = t.f0_; f1_ = t.f1_; f2_ = t.f2_; f3_ = t.f3_; return *this; } T0 f0_; T1 f1_; T2 f2_; T3 f3_; }; template class GTEST_5_TUPLE_(T) { public: template friend class gtest_internal::Get; tuple() : f0_(), f1_(), f2_(), f3_(), f4_() {} explicit tuple(GTEST_BY_REF_(T0) f0, GTEST_BY_REF_(T1) f1, GTEST_BY_REF_(T2) f2, GTEST_BY_REF_(T3) f3, GTEST_BY_REF_(T4) f4) : f0_(f0), f1_(f1), f2_(f2), f3_(f3), f4_(f4) {} tuple(const tuple& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_), f3_(t.f3_), f4_(t.f4_) {} template tuple(const GTEST_5_TUPLE_(U)& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_), f3_(t.f3_), f4_(t.f4_) {} tuple& operator=(const tuple& t) { return CopyFrom(t); } template tuple& operator=(const GTEST_5_TUPLE_(U)& t) { return CopyFrom(t); } GTEST_DECLARE_TUPLE_AS_FRIEND_ template tuple& CopyFrom(const GTEST_5_TUPLE_(U)& t) { f0_ = t.f0_; f1_ = t.f1_; f2_ = t.f2_; f3_ = t.f3_; f4_ = t.f4_; return *this; } T0 f0_; T1 f1_; T2 f2_; T3 f3_; T4 f4_; }; template class GTEST_6_TUPLE_(T) { public: template friend class gtest_internal::Get; tuple() : f0_(), f1_(), f2_(), f3_(), f4_(), f5_() {} explicit tuple(GTEST_BY_REF_(T0) f0, GTEST_BY_REF_(T1) f1, GTEST_BY_REF_(T2) f2, GTEST_BY_REF_(T3) f3, GTEST_BY_REF_(T4) f4, GTEST_BY_REF_(T5) f5) : f0_(f0), f1_(f1), f2_(f2), f3_(f3), f4_(f4), f5_(f5) {} tuple(const tuple& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_), f3_(t.f3_), f4_(t.f4_), f5_(t.f5_) {} template tuple(const GTEST_6_TUPLE_(U)& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_), f3_(t.f3_), f4_(t.f4_), f5_(t.f5_) {} tuple& operator=(const tuple& t) { return CopyFrom(t); } template tuple& operator=(const GTEST_6_TUPLE_(U)& t) { return CopyFrom(t); } GTEST_DECLARE_TUPLE_AS_FRIEND_ template tuple& CopyFrom(const GTEST_6_TUPLE_(U)& t) { f0_ = t.f0_; f1_ = t.f1_; f2_ = t.f2_; f3_ = t.f3_; f4_ = t.f4_; f5_ = t.f5_; return *this; } T0 f0_; T1 f1_; T2 f2_; T3 f3_; T4 f4_; T5 f5_; }; template class GTEST_7_TUPLE_(T) { public: template friend class gtest_internal::Get; tuple() : f0_(), f1_(), f2_(), f3_(), f4_(), f5_(), f6_() {} explicit tuple(GTEST_BY_REF_(T0) f0, GTEST_BY_REF_(T1) f1, GTEST_BY_REF_(T2) f2, GTEST_BY_REF_(T3) f3, GTEST_BY_REF_(T4) f4, GTEST_BY_REF_(T5) f5, GTEST_BY_REF_(T6) f6) : f0_(f0), f1_(f1), f2_(f2), f3_(f3), f4_(f4), f5_(f5), f6_(f6) {} tuple(const tuple& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_), f3_(t.f3_), f4_(t.f4_), f5_(t.f5_), f6_(t.f6_) {} template tuple(const GTEST_7_TUPLE_(U)& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_), f3_(t.f3_), f4_(t.f4_), f5_(t.f5_), f6_(t.f6_) {} tuple& operator=(const tuple& t) { return CopyFrom(t); } template tuple& operator=(const GTEST_7_TUPLE_(U)& t) { return CopyFrom(t); } GTEST_DECLARE_TUPLE_AS_FRIEND_ template tuple& CopyFrom(const GTEST_7_TUPLE_(U)& t) { f0_ = t.f0_; f1_ = t.f1_; f2_ = t.f2_; f3_ = t.f3_; f4_ = t.f4_; f5_ = t.f5_; f6_ = t.f6_; return *this; } T0 f0_; T1 f1_; T2 f2_; T3 f3_; T4 f4_; T5 f5_; T6 f6_; }; template class GTEST_8_TUPLE_(T) { public: template friend class gtest_internal::Get; tuple() : f0_(), f1_(), f2_(), f3_(), f4_(), f5_(), f6_(), f7_() {} explicit tuple(GTEST_BY_REF_(T0) f0, GTEST_BY_REF_(T1) f1, GTEST_BY_REF_(T2) f2, GTEST_BY_REF_(T3) f3, GTEST_BY_REF_(T4) f4, GTEST_BY_REF_(T5) f5, GTEST_BY_REF_(T6) f6, GTEST_BY_REF_(T7) f7) : f0_(f0), f1_(f1), f2_(f2), f3_(f3), f4_(f4), f5_(f5), f6_(f6), f7_(f7) {} tuple(const tuple& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_), f3_(t.f3_), f4_(t.f4_), f5_(t.f5_), f6_(t.f6_), f7_(t.f7_) {} template tuple(const GTEST_8_TUPLE_(U)& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_), f3_(t.f3_), f4_(t.f4_), f5_(t.f5_), f6_(t.f6_), f7_(t.f7_) {} tuple& operator=(const tuple& t) { return CopyFrom(t); } template tuple& operator=(const GTEST_8_TUPLE_(U)& t) { return CopyFrom(t); } GTEST_DECLARE_TUPLE_AS_FRIEND_ template tuple& CopyFrom(const GTEST_8_TUPLE_(U)& t) { f0_ = t.f0_; f1_ = t.f1_; f2_ = t.f2_; f3_ = t.f3_; f4_ = t.f4_; f5_ = t.f5_; f6_ = t.f6_; f7_ = t.f7_; return *this; } T0 f0_; T1 f1_; T2 f2_; T3 f3_; T4 f4_; T5 f5_; T6 f6_; T7 f7_; }; template class GTEST_9_TUPLE_(T) { public: template friend class gtest_internal::Get; tuple() : f0_(), f1_(), f2_(), f3_(), f4_(), f5_(), f6_(), f7_(), f8_() {} explicit tuple(GTEST_BY_REF_(T0) f0, GTEST_BY_REF_(T1) f1, GTEST_BY_REF_(T2) f2, GTEST_BY_REF_(T3) f3, GTEST_BY_REF_(T4) f4, GTEST_BY_REF_(T5) f5, GTEST_BY_REF_(T6) f6, GTEST_BY_REF_(T7) f7, GTEST_BY_REF_(T8) f8) : f0_(f0), f1_(f1), f2_(f2), f3_(f3), f4_(f4), f5_(f5), f6_(f6), f7_(f7), f8_(f8) {} tuple(const tuple& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_), f3_(t.f3_), f4_(t.f4_), f5_(t.f5_), f6_(t.f6_), f7_(t.f7_), f8_(t.f8_) {} template tuple(const GTEST_9_TUPLE_(U)& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_), f3_(t.f3_), f4_(t.f4_), f5_(t.f5_), f6_(t.f6_), f7_(t.f7_), f8_(t.f8_) {} tuple& operator=(const tuple& t) { return CopyFrom(t); } template tuple& operator=(const GTEST_9_TUPLE_(U)& t) { return CopyFrom(t); } GTEST_DECLARE_TUPLE_AS_FRIEND_ template tuple& CopyFrom(const GTEST_9_TUPLE_(U)& t) { f0_ = t.f0_; f1_ = t.f1_; f2_ = t.f2_; f3_ = t.f3_; f4_ = t.f4_; f5_ = t.f5_; f6_ = t.f6_; f7_ = t.f7_; f8_ = t.f8_; return *this; } T0 f0_; T1 f1_; T2 f2_; T3 f3_; T4 f4_; T5 f5_; T6 f6_; T7 f7_; T8 f8_; }; template class tuple { public: template friend class gtest_internal::Get; tuple() : f0_(), f1_(), f2_(), f3_(), f4_(), f5_(), f6_(), f7_(), f8_(), f9_() {} explicit tuple(GTEST_BY_REF_(T0) f0, GTEST_BY_REF_(T1) f1, GTEST_BY_REF_(T2) f2, GTEST_BY_REF_(T3) f3, GTEST_BY_REF_(T4) f4, GTEST_BY_REF_(T5) f5, GTEST_BY_REF_(T6) f6, GTEST_BY_REF_(T7) f7, GTEST_BY_REF_(T8) f8, GTEST_BY_REF_(T9) f9) : f0_(f0), f1_(f1), f2_(f2), f3_(f3), f4_(f4), f5_(f5), f6_(f6), f7_(f7), f8_(f8), f9_(f9) {} tuple(const tuple& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_), f3_(t.f3_), f4_(t.f4_), f5_(t.f5_), f6_(t.f6_), f7_(t.f7_), f8_(t.f8_), f9_(t.f9_) {} template tuple(const GTEST_10_TUPLE_(U)& t) : f0_(t.f0_), f1_(t.f1_), f2_(t.f2_), f3_(t.f3_), f4_(t.f4_), f5_(t.f5_), f6_(t.f6_), f7_(t.f7_), f8_(t.f8_), f9_(t.f9_) {} tuple& operator=(const tuple& t) { return CopyFrom(t); } template tuple& operator=(const GTEST_10_TUPLE_(U)& t) { return CopyFrom(t); } GTEST_DECLARE_TUPLE_AS_FRIEND_ template tuple& CopyFrom(const GTEST_10_TUPLE_(U)& t) { f0_ = t.f0_; f1_ = t.f1_; f2_ = t.f2_; f3_ = t.f3_; f4_ = t.f4_; f5_ = t.f5_; f6_ = t.f6_; f7_ = t.f7_; f8_ = t.f8_; f9_ = t.f9_; return *this; } T0 f0_; T1 f1_; T2 f2_; T3 f3_; T4 f4_; T5 f5_; T6 f6_; T7 f7_; T8 f8_; T9 f9_; }; // 6.1.3.2 Tuple creation functions. // Known limitations: we don't support passing an // std::tr1::reference_wrapper to make_tuple(). And we don't // implement tie(). inline tuple<> make_tuple() { return tuple<>(); } template inline GTEST_1_TUPLE_(T) make_tuple(const T0& f0) { return GTEST_1_TUPLE_(T)(f0); } template inline GTEST_2_TUPLE_(T) make_tuple(const T0& f0, const T1& f1) { return GTEST_2_TUPLE_(T)(f0, f1); } template inline GTEST_3_TUPLE_(T) make_tuple(const T0& f0, const T1& f1, const T2& f2) { return GTEST_3_TUPLE_(T)(f0, f1, f2); } template inline GTEST_4_TUPLE_(T) make_tuple(const T0& f0, const T1& f1, const T2& f2, const T3& f3) { return GTEST_4_TUPLE_(T)(f0, f1, f2, f3); } template inline GTEST_5_TUPLE_(T) make_tuple(const T0& f0, const T1& f1, const T2& f2, const T3& f3, const T4& f4) { return GTEST_5_TUPLE_(T)(f0, f1, f2, f3, f4); } template inline GTEST_6_TUPLE_(T) make_tuple(const T0& f0, const T1& f1, const T2& f2, const T3& f3, const T4& f4, const T5& f5) { return GTEST_6_TUPLE_(T)(f0, f1, f2, f3, f4, f5); } template inline GTEST_7_TUPLE_(T) make_tuple(const T0& f0, const T1& f1, const T2& f2, const T3& f3, const T4& f4, const T5& f5, const T6& f6) { return GTEST_7_TUPLE_(T)(f0, f1, f2, f3, f4, f5, f6); } template inline GTEST_8_TUPLE_(T) make_tuple(const T0& f0, const T1& f1, const T2& f2, const T3& f3, const T4& f4, const T5& f5, const T6& f6, const T7& f7) { return GTEST_8_TUPLE_(T)(f0, f1, f2, f3, f4, f5, f6, f7); } template inline GTEST_9_TUPLE_(T) make_tuple(const T0& f0, const T1& f1, const T2& f2, const T3& f3, const T4& f4, const T5& f5, const T6& f6, const T7& f7, const T8& f8) { return GTEST_9_TUPLE_(T)(f0, f1, f2, f3, f4, f5, f6, f7, f8); } template inline GTEST_10_TUPLE_(T) make_tuple(const T0& f0, const T1& f1, const T2& f2, const T3& f3, const T4& f4, const T5& f5, const T6& f6, const T7& f7, const T8& f8, const T9& f9) { return GTEST_10_TUPLE_(T)(f0, f1, f2, f3, f4, f5, f6, f7, f8, f9); } // 6.1.3.3 Tuple helper classes. template struct tuple_size; template struct tuple_size { static const int value = 0; }; template struct tuple_size { static const int value = 1; }; template struct tuple_size { static const int value = 2; }; template struct tuple_size { static const int value = 3; }; template struct tuple_size { static const int value = 4; }; template struct tuple_size { static const int value = 5; }; template struct tuple_size { static const int value = 6; }; template struct tuple_size { static const int value = 7; }; template struct tuple_size { static const int value = 8; }; template struct tuple_size { static const int value = 9; }; template struct tuple_size { static const int value = 10; }; template struct tuple_element { typedef typename gtest_internal::TupleElement< k < (tuple_size::value), k, Tuple>::type type; }; #define GTEST_TUPLE_ELEMENT_(k, Tuple) typename tuple_element::type // 6.1.3.4 Element access. namespace gtest_internal { template <> class Get<0> { public: template static GTEST_ADD_REF_(GTEST_TUPLE_ELEMENT_(0, Tuple)) Field(Tuple& t) { return t.f0_; } // NOLINT template static GTEST_BY_REF_(GTEST_TUPLE_ELEMENT_(0, Tuple)) ConstField(const Tuple& t) { return t.f0_; } }; template <> class Get<1> { public: template static GTEST_ADD_REF_(GTEST_TUPLE_ELEMENT_(1, Tuple)) Field(Tuple& t) { return t.f1_; } // NOLINT template static GTEST_BY_REF_(GTEST_TUPLE_ELEMENT_(1, Tuple)) ConstField(const Tuple& t) { return t.f1_; } }; template <> class Get<2> { public: template static GTEST_ADD_REF_(GTEST_TUPLE_ELEMENT_(2, Tuple)) Field(Tuple& t) { return t.f2_; } // NOLINT template static GTEST_BY_REF_(GTEST_TUPLE_ELEMENT_(2, Tuple)) ConstField(const Tuple& t) { return t.f2_; } }; template <> class Get<3> { public: template static GTEST_ADD_REF_(GTEST_TUPLE_ELEMENT_(3, Tuple)) Field(Tuple& t) { return t.f3_; } // NOLINT template static GTEST_BY_REF_(GTEST_TUPLE_ELEMENT_(3, Tuple)) ConstField(const Tuple& t) { return t.f3_; } }; template <> class Get<4> { public: template static GTEST_ADD_REF_(GTEST_TUPLE_ELEMENT_(4, Tuple)) Field(Tuple& t) { return t.f4_; } // NOLINT template static GTEST_BY_REF_(GTEST_TUPLE_ELEMENT_(4, Tuple)) ConstField(const Tuple& t) { return t.f4_; } }; template <> class Get<5> { public: template static GTEST_ADD_REF_(GTEST_TUPLE_ELEMENT_(5, Tuple)) Field(Tuple& t) { return t.f5_; } // NOLINT template static GTEST_BY_REF_(GTEST_TUPLE_ELEMENT_(5, Tuple)) ConstField(const Tuple& t) { return t.f5_; } }; template <> class Get<6> { public: template static GTEST_ADD_REF_(GTEST_TUPLE_ELEMENT_(6, Tuple)) Field(Tuple& t) { return t.f6_; } // NOLINT template static GTEST_BY_REF_(GTEST_TUPLE_ELEMENT_(6, Tuple)) ConstField(const Tuple& t) { return t.f6_; } }; template <> class Get<7> { public: template static GTEST_ADD_REF_(GTEST_TUPLE_ELEMENT_(7, Tuple)) Field(Tuple& t) { return t.f7_; } // NOLINT template static GTEST_BY_REF_(GTEST_TUPLE_ELEMENT_(7, Tuple)) ConstField(const Tuple& t) { return t.f7_; } }; template <> class Get<8> { public: template static GTEST_ADD_REF_(GTEST_TUPLE_ELEMENT_(8, Tuple)) Field(Tuple& t) { return t.f8_; } // NOLINT template static GTEST_BY_REF_(GTEST_TUPLE_ELEMENT_(8, Tuple)) ConstField(const Tuple& t) { return t.f8_; } }; template <> class Get<9> { public: template static GTEST_ADD_REF_(GTEST_TUPLE_ELEMENT_(9, Tuple)) Field(Tuple& t) { return t.f9_; } // NOLINT template static GTEST_BY_REF_(GTEST_TUPLE_ELEMENT_(9, Tuple)) ConstField(const Tuple& t) { return t.f9_; } }; } // namespace gtest_internal template GTEST_ADD_REF_(GTEST_TUPLE_ELEMENT_(k, GTEST_10_TUPLE_(T))) get(GTEST_10_TUPLE_(T)& t) { return gtest_internal::Get::Field(t); } template GTEST_BY_REF_(GTEST_TUPLE_ELEMENT_(k, GTEST_10_TUPLE_(T))) get(const GTEST_10_TUPLE_(T)& t) { return gtest_internal::Get::ConstField(t); } // 6.1.3.5 Relational operators // We only implement == and !=, as we don't have a need for the rest yet. namespace gtest_internal { // SameSizeTuplePrefixComparator::Eq(t1, t2) returns true if the // first k fields of t1 equals the first k fields of t2. // SameSizeTuplePrefixComparator(k1, k2) would be a compiler error if // k1 != k2. template struct SameSizeTuplePrefixComparator; template <> struct SameSizeTuplePrefixComparator<0, 0> { template static bool Eq(const Tuple1& /* t1 */, const Tuple2& /* t2 */) { return true; } }; template struct SameSizeTuplePrefixComparator { template static bool Eq(const Tuple1& t1, const Tuple2& t2) { return SameSizeTuplePrefixComparator::Eq(t1, t2) && ::std::tr1::get(t1) == ::std::tr1::get(t2); } }; } // namespace gtest_internal template inline bool operator==(const GTEST_10_TUPLE_(T)& t, const GTEST_10_TUPLE_(U)& u) { return gtest_internal::SameSizeTuplePrefixComparator< tuple_size::value, tuple_size::value>::Eq(t, u); } template inline bool operator!=(const GTEST_10_TUPLE_(T)& t, const GTEST_10_TUPLE_(U)& u) { return !(t == u); } // 6.1.4 Pairs. // Unimplemented. } // namespace tr1 } // namespace std #undef GTEST_0_TUPLE_ #undef GTEST_1_TUPLE_ #undef GTEST_2_TUPLE_ #undef GTEST_3_TUPLE_ #undef GTEST_4_TUPLE_ #undef GTEST_5_TUPLE_ #undef GTEST_6_TUPLE_ #undef GTEST_7_TUPLE_ #undef GTEST_8_TUPLE_ #undef GTEST_9_TUPLE_ #undef GTEST_10_TUPLE_ #undef GTEST_0_TYPENAMES_ #undef GTEST_1_TYPENAMES_ #undef GTEST_2_TYPENAMES_ #undef GTEST_3_TYPENAMES_ #undef GTEST_4_TYPENAMES_ #undef GTEST_5_TYPENAMES_ #undef GTEST_6_TYPENAMES_ #undef GTEST_7_TYPENAMES_ #undef GTEST_8_TYPENAMES_ #undef GTEST_9_TYPENAMES_ #undef GTEST_10_TYPENAMES_ #undef GTEST_DECLARE_TUPLE_AS_FRIEND_ #undef GTEST_BY_REF_ #undef GTEST_ADD_REF_ #undef GTEST_TUPLE_ELEMENT_ #endif // GTEST_INCLUDE_GTEST_INTERNAL_GTEST_TUPLE_H_ # elif GTEST_ENV_HAS_STD_TUPLE_ # include // C++11 puts its tuple into the ::std namespace rather than // ::std::tr1. gtest expects tuple to live in ::std::tr1, so put it there. // This causes undefined behavior, but supported compilers react in // the way we intend. namespace std { namespace tr1 { using ::std::get; using ::std::make_tuple; using ::std::tuple; using ::std::tuple_element; using ::std::tuple_size; } } # elif GTEST_OS_SYMBIAN // On Symbian, BOOST_HAS_TR1_TUPLE causes Boost's TR1 tuple library to // use STLport's tuple implementation, which unfortunately doesn't // work as the copy of STLport distributed with Symbian is incomplete. // By making sure BOOST_HAS_TR1_TUPLE is undefined, we force Boost to // use its own tuple implementation. # ifdef BOOST_HAS_TR1_TUPLE # undef BOOST_HAS_TR1_TUPLE # endif // BOOST_HAS_TR1_TUPLE // This prevents , which defines // BOOST_HAS_TR1_TUPLE, from being #included by Boost's . # define BOOST_TR1_DETAIL_CONFIG_HPP_INCLUDED # include # elif defined(__GNUC__) && (GTEST_GCC_VER_ >= 40000) // GCC 4.0+ implements tr1/tuple in the header. This does // not conform to the TR1 spec, which requires the header to be . # if !GTEST_HAS_RTTI && GTEST_GCC_VER_ < 40302 // Until version 4.3.2, gcc has a bug that causes , // which is #included by , to not compile when RTTI is // disabled. _TR1_FUNCTIONAL is the header guard for // . Hence the following #define is a hack to prevent // from being included. # define _TR1_FUNCTIONAL 1 # include # undef _TR1_FUNCTIONAL // Allows the user to #include // if he chooses to. # else # include // NOLINT # endif // !GTEST_HAS_RTTI && GTEST_GCC_VER_ < 40302 # else // If the compiler is not GCC 4.0+, we assume the user is using a // spec-conforming TR1 implementation. # include // NOLINT # endif // GTEST_USE_OWN_TR1_TUPLE #endif // GTEST_HAS_TR1_TUPLE // Determines whether clone(2) is supported. // Usually it will only be available on Linux, excluding // Linux on the Itanium architecture. // Also see http://linux.die.net/man/2/clone. #ifndef GTEST_HAS_CLONE // The user didn't tell us, so we need to figure it out. # if GTEST_OS_LINUX && !defined(__ia64__) # if GTEST_OS_LINUX_ANDROID // On Android, clone() is only available on ARM starting with Gingerbread. # if defined(__arm__) && __ANDROID_API__ >= 9 # define GTEST_HAS_CLONE 1 # else # define GTEST_HAS_CLONE 0 # endif # else # define GTEST_HAS_CLONE 1 # endif # else # define GTEST_HAS_CLONE 0 # endif // GTEST_OS_LINUX && !defined(__ia64__) #endif // GTEST_HAS_CLONE // Determines whether to support stream redirection. This is used to test // output correctness and to implement death tests. #ifndef GTEST_HAS_STREAM_REDIRECTION // By default, we assume that stream redirection is supported on all // platforms except known mobile ones. # if GTEST_OS_WINDOWS_MOBILE || GTEST_OS_SYMBIAN # define GTEST_HAS_STREAM_REDIRECTION 0 # else # define GTEST_HAS_STREAM_REDIRECTION 1 # endif // !GTEST_OS_WINDOWS_MOBILE && !GTEST_OS_SYMBIAN #endif // GTEST_HAS_STREAM_REDIRECTION // Determines whether to support death tests. // Google Test does not support death tests for VC 7.1 and earlier as // abort() in a VC 7.1 application compiled as GUI in debug config // pops up a dialog window that cannot be suppressed programmatically. #if (GTEST_OS_LINUX || GTEST_OS_CYGWIN || GTEST_OS_SOLARIS || \ (GTEST_OS_MAC && !GTEST_OS_IOS) || GTEST_OS_IOS_SIMULATOR || \ (GTEST_OS_WINDOWS_DESKTOP && _MSC_VER >= 1400) || \ GTEST_OS_WINDOWS_MINGW || GTEST_OS_AIX || GTEST_OS_HPUX || \ GTEST_OS_OPENBSD || GTEST_OS_QNX) # define GTEST_HAS_DEATH_TEST 1 # include // NOLINT #endif // We don't support MSVC 7.1 with exceptions disabled now. Therefore // all the compilers we care about are adequate for supporting // value-parameterized tests. #define GTEST_HAS_PARAM_TEST 1 // Determines whether to support type-driven tests. // Typed tests need and variadic macros, which GCC, VC++ 8.0, // Sun Pro CC, IBM Visual Age, and HP aCC support. #if defined(__GNUC__) || (_MSC_VER >= 1400) || defined(__SUNPRO_CC) || \ defined(__IBMCPP__) || defined(__HP_aCC) # define GTEST_HAS_TYPED_TEST 1 # define GTEST_HAS_TYPED_TEST_P 1 #endif // Determines whether to support Combine(). This only makes sense when // value-parameterized tests are enabled. The implementation doesn't // work on Sun Studio since it doesn't understand templated conversion // operators. #if GTEST_HAS_PARAM_TEST && GTEST_HAS_TR1_TUPLE && !defined(__SUNPRO_CC) # define GTEST_HAS_COMBINE 1 #endif // Determines whether the system compiler uses UTF-16 for encoding wide strings. #define GTEST_WIDE_STRING_USES_UTF16_ \ (GTEST_OS_WINDOWS || GTEST_OS_CYGWIN || GTEST_OS_SYMBIAN || GTEST_OS_AIX) // Determines whether test results can be streamed to a socket. #if GTEST_OS_LINUX # define GTEST_CAN_STREAM_RESULTS_ 1 #endif // Defines some utility macros. // The GNU compiler emits a warning if nested "if" statements are followed by // an "else" statement and braces are not used to explicitly disambiguate the // "else" binding. This leads to problems with code like: // // if (gate) // ASSERT_*(condition) << "Some message"; // // The "switch (0) case 0:" idiom is used to suppress this. #ifdef __INTEL_COMPILER # define GTEST_AMBIGUOUS_ELSE_BLOCKER_ #else # define GTEST_AMBIGUOUS_ELSE_BLOCKER_ switch (0) case 0: default: // NOLINT #endif // Use this annotation at the end of a struct/class definition to // prevent the compiler from optimizing away instances that are never // used. This is useful when all interesting logic happens inside the // c'tor and / or d'tor. Example: // // struct Foo { // Foo() { ... } // } GTEST_ATTRIBUTE_UNUSED_; // // Also use it after a variable or parameter declaration to tell the // compiler the variable/parameter does not have to be used. #if defined(__GNUC__) && !defined(COMPILER_ICC) # define GTEST_ATTRIBUTE_UNUSED_ __attribute__ ((unused)) #else # define GTEST_ATTRIBUTE_UNUSED_ #endif // A macro to disallow operator= // This should be used in the private: declarations for a class. #define GTEST_DISALLOW_ASSIGN_(type)\ void operator=(type const &) // A macro to disallow copy constructor and operator= // This should be used in the private: declarations for a class. #define GTEST_DISALLOW_COPY_AND_ASSIGN_(type)\ type(type const &);\ GTEST_DISALLOW_ASSIGN_(type) // Tell the compiler to warn about unused return values for functions declared // with this macro. The macro should be used on function declarations // following the argument list: // // Sprocket* AllocateSprocket() GTEST_MUST_USE_RESULT_; #if defined(__GNUC__) && (GTEST_GCC_VER_ >= 30400) && !defined(COMPILER_ICC) # define GTEST_MUST_USE_RESULT_ __attribute__ ((warn_unused_result)) #else # define GTEST_MUST_USE_RESULT_ #endif // __GNUC__ && (GTEST_GCC_VER_ >= 30400) && !COMPILER_ICC // Determine whether the compiler supports Microsoft's Structured Exception // Handling. This is supported by several Windows compilers but generally // does not exist on any other system. #ifndef GTEST_HAS_SEH // The user didn't tell us, so we need to figure it out. # if defined(_MSC_VER) || defined(__BORLANDC__) // These two compilers are known to support SEH. # define GTEST_HAS_SEH 1 # else // Assume no SEH. # define GTEST_HAS_SEH 0 # endif #endif // GTEST_HAS_SEH #ifdef _MSC_VER # if GTEST_LINKED_AS_SHARED_LIBRARY # define GTEST_API_ __declspec(dllimport) # elif GTEST_CREATE_SHARED_LIBRARY # define GTEST_API_ __declspec(dllexport) # endif #endif // _MSC_VER #ifndef GTEST_API_ # define GTEST_API_ #endif #ifdef __GNUC__ // Ask the compiler to never inline a given function. # define GTEST_NO_INLINE_ __attribute__((noinline)) #else # define GTEST_NO_INLINE_ #endif // _LIBCPP_VERSION is defined by the libc++ library from the LLVM project. #if defined(__GLIBCXX__) || defined(_LIBCPP_VERSION) # define GTEST_HAS_CXXABI_H_ 1 #else # define GTEST_HAS_CXXABI_H_ 0 #endif namespace testing { class Message; namespace internal { // A secret type that Google Test users don't know about. It has no // definition on purpose. Therefore it's impossible to create a // Secret object, which is what we want. class Secret; // The GTEST_COMPILE_ASSERT_ macro can be used to verify that a compile time // expression is true. For example, you could use it to verify the // size of a static array: // // GTEST_COMPILE_ASSERT_(ARRAYSIZE(content_type_names) == CONTENT_NUM_TYPES, // content_type_names_incorrect_size); // // or to make sure a struct is smaller than a certain size: // // GTEST_COMPILE_ASSERT_(sizeof(foo) < 128, foo_too_large); // // The second argument to the macro is the name of the variable. If // the expression is false, most compilers will issue a warning/error // containing the name of the variable. template struct CompileAssert { }; #define GTEST_COMPILE_ASSERT_(expr, msg) \ typedef ::testing::internal::CompileAssert<(static_cast(expr))> \ msg[static_cast(expr) ? 1 : -1] GTEST_ATTRIBUTE_UNUSED_ // Implementation details of GTEST_COMPILE_ASSERT_: // // - GTEST_COMPILE_ASSERT_ works by defining an array type that has -1 // elements (and thus is invalid) when the expression is false. // // - The simpler definition // // #define GTEST_COMPILE_ASSERT_(expr, msg) typedef char msg[(expr) ? 1 : -1] // // does not work, as gcc supports variable-length arrays whose sizes // are determined at run-time (this is gcc's extension and not part // of the C++ standard). As a result, gcc fails to reject the // following code with the simple definition: // // int foo; // GTEST_COMPILE_ASSERT_(foo, msg); // not supposed to compile as foo is // // not a compile-time constant. // // - By using the type CompileAssert<(bool(expr))>, we ensures that // expr is a compile-time constant. (Template arguments must be // determined at compile-time.) // // - The outter parentheses in CompileAssert<(bool(expr))> are necessary // to work around a bug in gcc 3.4.4 and 4.0.1. If we had written // // CompileAssert // // instead, these compilers will refuse to compile // // GTEST_COMPILE_ASSERT_(5 > 0, some_message); // // (They seem to think the ">" in "5 > 0" marks the end of the // template argument list.) // // - The array size is (bool(expr) ? 1 : -1), instead of simply // // ((expr) ? 1 : -1). // // This is to avoid running into a bug in MS VC 7.1, which // causes ((0.0) ? 1 : -1) to incorrectly evaluate to 1. // StaticAssertTypeEqHelper is used by StaticAssertTypeEq defined in gtest.h. // // This template is declared, but intentionally undefined. template struct StaticAssertTypeEqHelper; template struct StaticAssertTypeEqHelper {}; #if GTEST_HAS_GLOBAL_STRING typedef ::string string; #else typedef ::std::string string; #endif // GTEST_HAS_GLOBAL_STRING #if GTEST_HAS_GLOBAL_WSTRING typedef ::wstring wstring; #elif GTEST_HAS_STD_WSTRING typedef ::std::wstring wstring; #endif // GTEST_HAS_GLOBAL_WSTRING // A helper for suppressing warnings on constant condition. It just // returns 'condition'. GTEST_API_ bool IsTrue(bool condition); // Defines scoped_ptr. // This implementation of scoped_ptr is PARTIAL - it only contains // enough stuff to satisfy Google Test's need. template class scoped_ptr { public: typedef T element_type; explicit scoped_ptr(T* p = NULL) : ptr_(p) {} ~scoped_ptr() { reset(); } T& operator*() const { return *ptr_; } T* operator->() const { return ptr_; } T* get() const { return ptr_; } T* release() { T* const ptr = ptr_; ptr_ = NULL; return ptr; } void reset(T* p = NULL) { if (p != ptr_) { if (IsTrue(sizeof(T) > 0)) { // Makes sure T is a complete type. delete ptr_; } ptr_ = p; } } private: T* ptr_; GTEST_DISALLOW_COPY_AND_ASSIGN_(scoped_ptr); }; // Defines RE. // A simple C++ wrapper for . It uses the POSIX Extended // Regular Expression syntax. class GTEST_API_ RE { public: // A copy constructor is required by the Standard to initialize object // references from r-values. RE(const RE& other) { Init(other.pattern()); } // Constructs an RE from a string. RE(const ::std::string& regex) { Init(regex.c_str()); } // NOLINT #if GTEST_HAS_GLOBAL_STRING RE(const ::string& regex) { Init(regex.c_str()); } // NOLINT #endif // GTEST_HAS_GLOBAL_STRING RE(const char* regex) { Init(regex); } // NOLINT ~RE(); // Returns the string representation of the regex. const char* pattern() const { return pattern_; } // FullMatch(str, re) returns true iff regular expression re matches // the entire str. // PartialMatch(str, re) returns true iff regular expression re // matches a substring of str (including str itself). // // TODO(wan@google.com): make FullMatch() and PartialMatch() work // when str contains NUL characters. static bool FullMatch(const ::std::string& str, const RE& re) { return FullMatch(str.c_str(), re); } static bool PartialMatch(const ::std::string& str, const RE& re) { return PartialMatch(str.c_str(), re); } #if GTEST_HAS_GLOBAL_STRING static bool FullMatch(const ::string& str, const RE& re) { return FullMatch(str.c_str(), re); } static bool PartialMatch(const ::string& str, const RE& re) { return PartialMatch(str.c_str(), re); } #endif // GTEST_HAS_GLOBAL_STRING static bool FullMatch(const char* str, const RE& re); static bool PartialMatch(const char* str, const RE& re); private: void Init(const char* regex); // We use a const char* instead of an std::string, as Google Test used to be // used where std::string is not available. TODO(wan@google.com): change to // std::string. const char* pattern_; bool is_valid_; #if GTEST_USES_POSIX_RE regex_t full_regex_; // For FullMatch(). regex_t partial_regex_; // For PartialMatch(). #else // GTEST_USES_SIMPLE_RE const char* full_pattern_; // For FullMatch(); #endif GTEST_DISALLOW_ASSIGN_(RE); }; // Formats a source file path and a line number as they would appear // in an error message from the compiler used to compile this code. GTEST_API_ ::std::string FormatFileLocation(const char* file, int line); // Formats a file location for compiler-independent XML output. // Although this function is not platform dependent, we put it next to // FormatFileLocation in order to contrast the two functions. GTEST_API_ ::std::string FormatCompilerIndependentFileLocation(const char* file, int line); // Defines logging utilities: // GTEST_LOG_(severity) - logs messages at the specified severity level. The // message itself is streamed into the macro. // LogToStderr() - directs all log messages to stderr. // FlushInfoLog() - flushes informational log messages. enum GTestLogSeverity { GTEST_INFO, GTEST_WARNING, GTEST_ERROR, GTEST_FATAL }; // Formats log entry severity, provides a stream object for streaming the // log message, and terminates the message with a newline when going out of // scope. class GTEST_API_ GTestLog { public: GTestLog(GTestLogSeverity severity, const char* file, int line); // Flushes the buffers and, if severity is GTEST_FATAL, aborts the program. ~GTestLog(); ::std::ostream& GetStream() { return ::std::cerr; } private: const GTestLogSeverity severity_; GTEST_DISALLOW_COPY_AND_ASSIGN_(GTestLog); }; #define GTEST_LOG_(severity) \ ::testing::internal::GTestLog(::testing::internal::GTEST_##severity, \ __FILE__, __LINE__).GetStream() inline void LogToStderr() {} inline void FlushInfoLog() { fflush(NULL); } // INTERNAL IMPLEMENTATION - DO NOT USE. // // GTEST_CHECK_ is an all-mode assert. It aborts the program if the condition // is not satisfied. // Synopsys: // GTEST_CHECK_(boolean_condition); // or // GTEST_CHECK_(boolean_condition) << "Additional message"; // // This checks the condition and if the condition is not satisfied // it prints message about the condition violation, including the // condition itself, plus additional message streamed into it, if any, // and then it aborts the program. It aborts the program irrespective of // whether it is built in the debug mode or not. #define GTEST_CHECK_(condition) \ GTEST_AMBIGUOUS_ELSE_BLOCKER_ \ if (::testing::internal::IsTrue(condition)) \ ; \ else \ GTEST_LOG_(FATAL) << "Condition " #condition " failed. " // An all-mode assert to verify that the given POSIX-style function // call returns 0 (indicating success). Known limitation: this // doesn't expand to a balanced 'if' statement, so enclose the macro // in {} if you need to use it as the only statement in an 'if' // branch. #define GTEST_CHECK_POSIX_SUCCESS_(posix_call) \ if (const int gtest_error = (posix_call)) \ GTEST_LOG_(FATAL) << #posix_call << "failed with error " \ << gtest_error // INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE. // // Use ImplicitCast_ as a safe version of static_cast for upcasting in // the type hierarchy (e.g. casting a Foo* to a SuperclassOfFoo* or a // const Foo*). When you use ImplicitCast_, the compiler checks that // the cast is safe. Such explicit ImplicitCast_s are necessary in // surprisingly many situations where C++ demands an exact type match // instead of an argument type convertable to a target type. // // The syntax for using ImplicitCast_ is the same as for static_cast: // // ImplicitCast_(expr) // // ImplicitCast_ would have been part of the C++ standard library, // but the proposal was submitted too late. It will probably make // its way into the language in the future. // // This relatively ugly name is intentional. It prevents clashes with // similar functions users may have (e.g., implicit_cast). The internal // namespace alone is not enough because the function can be found by ADL. template inline To ImplicitCast_(To x) { return x; } // When you upcast (that is, cast a pointer from type Foo to type // SuperclassOfFoo), it's fine to use ImplicitCast_<>, since upcasts // always succeed. When you downcast (that is, cast a pointer from // type Foo to type SubclassOfFoo), static_cast<> isn't safe, because // how do you know the pointer is really of type SubclassOfFoo? It // could be a bare Foo, or of type DifferentSubclassOfFoo. Thus, // when you downcast, you should use this macro. In debug mode, we // use dynamic_cast<> to double-check the downcast is legal (we die // if it's not). In normal mode, we do the efficient static_cast<> // instead. Thus, it's important to test in debug mode to make sure // the cast is legal! // This is the only place in the code we should use dynamic_cast<>. // In particular, you SHOULDN'T be using dynamic_cast<> in order to // do RTTI (eg code like this: // if (dynamic_cast(foo)) HandleASubclass1Object(foo); // if (dynamic_cast(foo)) HandleASubclass2Object(foo); // You should design the code some other way not to need this. // // This relatively ugly name is intentional. It prevents clashes with // similar functions users may have (e.g., down_cast). The internal // namespace alone is not enough because the function can be found by ADL. template // use like this: DownCast_(foo); inline To DownCast_(From* f) { // so we only accept pointers // Ensures that To is a sub-type of From *. This test is here only // for compile-time type checking, and has no overhead in an // optimized build at run-time, as it will be optimized away // completely. if (false) { const To to = NULL; ::testing::internal::ImplicitCast_(to); } #if GTEST_HAS_RTTI // RTTI: debug mode only! GTEST_CHECK_(f == NULL || dynamic_cast(f) != NULL); #endif return static_cast(f); } // Downcasts the pointer of type Base to Derived. // Derived must be a subclass of Base. The parameter MUST // point to a class of type Derived, not any subclass of it. // When RTTI is available, the function performs a runtime // check to enforce this. template Derived* CheckedDowncastToActualType(Base* base) { #if GTEST_HAS_RTTI GTEST_CHECK_(typeid(*base) == typeid(Derived)); return dynamic_cast(base); // NOLINT #else return static_cast(base); // Poor man's downcast. #endif } #if GTEST_HAS_STREAM_REDIRECTION // Defines the stderr capturer: // CaptureStdout - starts capturing stdout. // GetCapturedStdout - stops capturing stdout and returns the captured string. // CaptureStderr - starts capturing stderr. // GetCapturedStderr - stops capturing stderr and returns the captured string. // GTEST_API_ void CaptureStdout(); GTEST_API_ std::string GetCapturedStdout(); GTEST_API_ void CaptureStderr(); GTEST_API_ std::string GetCapturedStderr(); #endif // GTEST_HAS_STREAM_REDIRECTION #if GTEST_HAS_DEATH_TEST const ::std::vector& GetInjectableArgvs(); void SetInjectableArgvs(const ::std::vector* new_argvs); // A copy of all command line arguments. Set by InitGoogleTest(). extern ::std::vector g_argvs; #endif // GTEST_HAS_DEATH_TEST // Defines synchronization primitives. #if GTEST_HAS_PTHREAD // Sleeps for (roughly) n milli-seconds. This function is only for // testing Google Test's own constructs. Don't use it in user tests, // either directly or indirectly. inline void SleepMilliseconds(int n) { const timespec time = { 0, // 0 seconds. n * 1000L * 1000L, // And n ms. }; nanosleep(&time, NULL); } // Allows a controller thread to pause execution of newly created // threads until notified. Instances of this class must be created // and destroyed in the controller thread. // // This class is only for testing Google Test's own constructs. Do not // use it in user tests, either directly or indirectly. class Notification { public: Notification() : notified_(false) { GTEST_CHECK_POSIX_SUCCESS_(pthread_mutex_init(&mutex_, NULL)); } ~Notification() { pthread_mutex_destroy(&mutex_); } // Notifies all threads created with this notification to start. Must // be called from the controller thread. void Notify() { pthread_mutex_lock(&mutex_); notified_ = true; pthread_mutex_unlock(&mutex_); } // Blocks until the controller thread notifies. Must be called from a test // thread. void WaitForNotification() { for (;;) { pthread_mutex_lock(&mutex_); const bool notified = notified_; pthread_mutex_unlock(&mutex_); if (notified) break; SleepMilliseconds(10); } } private: pthread_mutex_t mutex_; bool notified_; GTEST_DISALLOW_COPY_AND_ASSIGN_(Notification); }; // As a C-function, ThreadFuncWithCLinkage cannot be templated itself. // Consequently, it cannot select a correct instantiation of ThreadWithParam // in order to call its Run(). Introducing ThreadWithParamBase as a // non-templated base class for ThreadWithParam allows us to bypass this // problem. class ThreadWithParamBase { public: virtual ~ThreadWithParamBase() {} virtual void Run() = 0; }; // pthread_create() accepts a pointer to a function type with the C linkage. // According to the Standard (7.5/1), function types with different linkages // are different even if they are otherwise identical. Some compilers (for // example, SunStudio) treat them as different types. Since class methods // cannot be defined with C-linkage we need to define a free C-function to // pass into pthread_create(). extern "C" inline void* ThreadFuncWithCLinkage(void* thread) { static_cast(thread)->Run(); return NULL; } // Helper class for testing Google Test's multi-threading constructs. // To use it, write: // // void ThreadFunc(int param) { /* Do things with param */ } // Notification thread_can_start; // ... // // The thread_can_start parameter is optional; you can supply NULL. // ThreadWithParam thread(&ThreadFunc, 5, &thread_can_start); // thread_can_start.Notify(); // // These classes are only for testing Google Test's own constructs. Do // not use them in user tests, either directly or indirectly. template class ThreadWithParam : public ThreadWithParamBase { public: typedef void (*UserThreadFunc)(T); ThreadWithParam( UserThreadFunc func, T param, Notification* thread_can_start) : func_(func), param_(param), thread_can_start_(thread_can_start), finished_(false) { ThreadWithParamBase* const base = this; // The thread can be created only after all fields except thread_ // have been initialized. GTEST_CHECK_POSIX_SUCCESS_( pthread_create(&thread_, 0, &ThreadFuncWithCLinkage, base)); } ~ThreadWithParam() { Join(); } void Join() { if (!finished_) { GTEST_CHECK_POSIX_SUCCESS_(pthread_join(thread_, 0)); finished_ = true; } } virtual void Run() { if (thread_can_start_ != NULL) thread_can_start_->WaitForNotification(); func_(param_); } private: const UserThreadFunc func_; // User-supplied thread function. const T param_; // User-supplied parameter to the thread function. // When non-NULL, used to block execution until the controller thread // notifies. Notification* const thread_can_start_; bool finished_; // true iff we know that the thread function has finished. pthread_t thread_; // The native thread object. GTEST_DISALLOW_COPY_AND_ASSIGN_(ThreadWithParam); }; // MutexBase and Mutex implement mutex on pthreads-based platforms. They // are used in conjunction with class MutexLock: // // Mutex mutex; // ... // MutexLock lock(&mutex); // Acquires the mutex and releases it at the end // // of the current scope. // // MutexBase implements behavior for both statically and dynamically // allocated mutexes. Do not use MutexBase directly. Instead, write // the following to define a static mutex: // // GTEST_DEFINE_STATIC_MUTEX_(g_some_mutex); // // You can forward declare a static mutex like this: // // GTEST_DECLARE_STATIC_MUTEX_(g_some_mutex); // // To create a dynamic mutex, just define an object of type Mutex. class MutexBase { public: // Acquires this mutex. void Lock() { GTEST_CHECK_POSIX_SUCCESS_(pthread_mutex_lock(&mutex_)); owner_ = pthread_self(); has_owner_ = true; } // Releases this mutex. void Unlock() { // Since the lock is being released the owner_ field should no longer be // considered valid. We don't protect writing to has_owner_ here, as it's // the caller's responsibility to ensure that the current thread holds the // mutex when this is called. has_owner_ = false; GTEST_CHECK_POSIX_SUCCESS_(pthread_mutex_unlock(&mutex_)); } // Does nothing if the current thread holds the mutex. Otherwise, crashes // with high probability. void AssertHeld() const { GTEST_CHECK_(has_owner_ && pthread_equal(owner_, pthread_self())) << "The current thread is not holding the mutex @" << this; } // A static mutex may be used before main() is entered. It may even // be used before the dynamic initialization stage. Therefore we // must be able to initialize a static mutex object at link time. // This means MutexBase has to be a POD and its member variables // have to be public. public: pthread_mutex_t mutex_; // The underlying pthread mutex. // has_owner_ indicates whether the owner_ field below contains a valid thread // ID and is therefore safe to inspect (e.g., to use in pthread_equal()). All // accesses to the owner_ field should be protected by a check of this field. // An alternative might be to memset() owner_ to all zeros, but there's no // guarantee that a zero'd pthread_t is necessarily invalid or even different // from pthread_self(). bool has_owner_; pthread_t owner_; // The thread holding the mutex. }; // Forward-declares a static mutex. # define GTEST_DECLARE_STATIC_MUTEX_(mutex) \ extern ::testing::internal::MutexBase mutex // Defines and statically (i.e. at link time) initializes a static mutex. // The initialization list here does not explicitly initialize each field, // instead relying on default initialization for the unspecified fields. In // particular, the owner_ field (a pthread_t) is not explicitly initialized. // This allows initialization to work whether pthread_t is a scalar or struct. // The flag -Wmissing-field-initializers must not be specified for this to work. # define GTEST_DEFINE_STATIC_MUTEX_(mutex) \ ::testing::internal::MutexBase mutex = { PTHREAD_MUTEX_INITIALIZER, false } // The Mutex class can only be used for mutexes created at runtime. It // shares its API with MutexBase otherwise. class Mutex : public MutexBase { public: Mutex() { GTEST_CHECK_POSIX_SUCCESS_(pthread_mutex_init(&mutex_, NULL)); has_owner_ = false; } ~Mutex() { GTEST_CHECK_POSIX_SUCCESS_(pthread_mutex_destroy(&mutex_)); } private: GTEST_DISALLOW_COPY_AND_ASSIGN_(Mutex); }; // We cannot name this class MutexLock as the ctor declaration would // conflict with a macro named MutexLock, which is defined on some // platforms. Hence the typedef trick below. class GTestMutexLock { public: explicit GTestMutexLock(MutexBase* mutex) : mutex_(mutex) { mutex_->Lock(); } ~GTestMutexLock() { mutex_->Unlock(); } private: MutexBase* const mutex_; GTEST_DISALLOW_COPY_AND_ASSIGN_(GTestMutexLock); }; typedef GTestMutexLock MutexLock; // Helpers for ThreadLocal. // pthread_key_create() requires DeleteThreadLocalValue() to have // C-linkage. Therefore it cannot be templatized to access // ThreadLocal. Hence the need for class // ThreadLocalValueHolderBase. class ThreadLocalValueHolderBase { public: virtual ~ThreadLocalValueHolderBase() {} }; // Called by pthread to delete thread-local data stored by // pthread_setspecific(). extern "C" inline void DeleteThreadLocalValue(void* value_holder) { delete static_cast(value_holder); } // Implements thread-local storage on pthreads-based systems. // // // Thread 1 // ThreadLocal tl(100); // 100 is the default value for each thread. // // // Thread 2 // tl.set(150); // Changes the value for thread 2 only. // EXPECT_EQ(150, tl.get()); // // // Thread 1 // EXPECT_EQ(100, tl.get()); // In thread 1, tl has the original value. // tl.set(200); // EXPECT_EQ(200, tl.get()); // // The template type argument T must have a public copy constructor. // In addition, the default ThreadLocal constructor requires T to have // a public default constructor. // // An object managed for a thread by a ThreadLocal instance is deleted // when the thread exits. Or, if the ThreadLocal instance dies in // that thread, when the ThreadLocal dies. It's the user's // responsibility to ensure that all other threads using a ThreadLocal // have exited when it dies, or the per-thread objects for those // threads will not be deleted. // // Google Test only uses global ThreadLocal objects. That means they // will die after main() has returned. Therefore, no per-thread // object managed by Google Test will be leaked as long as all threads // using Google Test have exited when main() returns. template class ThreadLocal { public: ThreadLocal() : key_(CreateKey()), default_() {} explicit ThreadLocal(const T& value) : key_(CreateKey()), default_(value) {} ~ThreadLocal() { // Destroys the managed object for the current thread, if any. DeleteThreadLocalValue(pthread_getspecific(key_)); // Releases resources associated with the key. This will *not* // delete managed objects for other threads. GTEST_CHECK_POSIX_SUCCESS_(pthread_key_delete(key_)); } T* pointer() { return GetOrCreateValue(); } const T* pointer() const { return GetOrCreateValue(); } const T& get() const { return *pointer(); } void set(const T& value) { *pointer() = value; } private: // Holds a value of type T. class ValueHolder : public ThreadLocalValueHolderBase { public: explicit ValueHolder(const T& value) : value_(value) {} T* pointer() { return &value_; } private: T value_; GTEST_DISALLOW_COPY_AND_ASSIGN_(ValueHolder); }; static pthread_key_t CreateKey() { pthread_key_t key; // When a thread exits, DeleteThreadLocalValue() will be called on // the object managed for that thread. GTEST_CHECK_POSIX_SUCCESS_( pthread_key_create(&key, &DeleteThreadLocalValue)); return key; } T* GetOrCreateValue() const { ThreadLocalValueHolderBase* const holder = static_cast(pthread_getspecific(key_)); if (holder != NULL) { return CheckedDowncastToActualType(holder)->pointer(); } ValueHolder* const new_holder = new ValueHolder(default_); ThreadLocalValueHolderBase* const holder_base = new_holder; GTEST_CHECK_POSIX_SUCCESS_(pthread_setspecific(key_, holder_base)); return new_holder->pointer(); } // A key pthreads uses for looking up per-thread values. const pthread_key_t key_; const T default_; // The default value for each thread. GTEST_DISALLOW_COPY_AND_ASSIGN_(ThreadLocal); }; # define GTEST_IS_THREADSAFE 1 #else // GTEST_HAS_PTHREAD // A dummy implementation of synchronization primitives (mutex, lock, // and thread-local variable). Necessary for compiling Google Test where // mutex is not supported - using Google Test in multiple threads is not // supported on such platforms. class Mutex { public: Mutex() {} void Lock() {} void Unlock() {} void AssertHeld() const {} }; # define GTEST_DECLARE_STATIC_MUTEX_(mutex) \ extern ::testing::internal::Mutex mutex # define GTEST_DEFINE_STATIC_MUTEX_(mutex) ::testing::internal::Mutex mutex class GTestMutexLock { public: explicit GTestMutexLock(Mutex*) {} // NOLINT }; typedef GTestMutexLock MutexLock; template class ThreadLocal { public: ThreadLocal() : value_() {} explicit ThreadLocal(const T& value) : value_(value) {} T* pointer() { return &value_; } const T* pointer() const { return &value_; } const T& get() const { return value_; } void set(const T& value) { value_ = value; } private: T value_; }; // The above synchronization primitives have dummy implementations. // Therefore Google Test is not thread-safe. # define GTEST_IS_THREADSAFE 0 #endif // GTEST_HAS_PTHREAD // Returns the number of threads running in the process, or 0 to indicate that // we cannot detect it. GTEST_API_ size_t GetThreadCount(); // Passing non-POD classes through ellipsis (...) crashes the ARM // compiler and generates a warning in Sun Studio. The Nokia Symbian // and the IBM XL C/C++ compiler try to instantiate a copy constructor // for objects passed through ellipsis (...), failing for uncopyable // objects. We define this to ensure that only POD is passed through // ellipsis on these systems. #if defined(__SYMBIAN32__) || defined(__IBMCPP__) || defined(__SUNPRO_CC) // We lose support for NULL detection where the compiler doesn't like // passing non-POD classes through ellipsis (...). # define GTEST_ELLIPSIS_NEEDS_POD_ 1 #else # define GTEST_CAN_COMPARE_NULL 1 #endif // The Nokia Symbian and IBM XL C/C++ compilers cannot decide between // const T& and const T* in a function template. These compilers // _can_ decide between class template specializations for T and T*, // so a tr1::type_traits-like is_pointer works. #if defined(__SYMBIAN32__) || defined(__IBMCPP__) # define GTEST_NEEDS_IS_POINTER_ 1 #endif template struct bool_constant { typedef bool_constant type; static const bool value = bool_value; }; template const bool bool_constant::value; typedef bool_constant false_type; typedef bool_constant true_type; template struct is_pointer : public false_type {}; template struct is_pointer : public true_type {}; template struct IteratorTraits { typedef typename Iterator::value_type value_type; }; template struct IteratorTraits { typedef T value_type; }; template struct IteratorTraits { typedef T value_type; }; #if GTEST_OS_WINDOWS # define GTEST_PATH_SEP_ "\\" # define GTEST_HAS_ALT_PATH_SEP_ 1 // The biggest signed integer type the compiler supports. typedef __int64 BiggestInt; #else # define GTEST_PATH_SEP_ "/" # define GTEST_HAS_ALT_PATH_SEP_ 0 typedef long long BiggestInt; // NOLINT #endif // GTEST_OS_WINDOWS // Utilities for char. // isspace(int ch) and friends accept an unsigned char or EOF. char // may be signed, depending on the compiler (or compiler flags). // Therefore we need to cast a char to unsigned char before calling // isspace(), etc. inline bool IsAlpha(char ch) { return isalpha(static_cast(ch)) != 0; } inline bool IsAlNum(char ch) { return isalnum(static_cast(ch)) != 0; } inline bool IsDigit(char ch) { return isdigit(static_cast(ch)) != 0; } inline bool IsLower(char ch) { return islower(static_cast(ch)) != 0; } inline bool IsSpace(char ch) { return isspace(static_cast(ch)) != 0; } inline bool IsUpper(char ch) { return isupper(static_cast(ch)) != 0; } inline bool IsXDigit(char ch) { return isxdigit(static_cast(ch)) != 0; } inline bool IsXDigit(wchar_t ch) { const unsigned char low_byte = static_cast(ch); return ch == low_byte && isxdigit(low_byte) != 0; } inline char ToLower(char ch) { return static_cast(tolower(static_cast(ch))); } inline char ToUpper(char ch) { return static_cast(toupper(static_cast(ch))); } // The testing::internal::posix namespace holds wrappers for common // POSIX functions. These wrappers hide the differences between // Windows/MSVC and POSIX systems. Since some compilers define these // standard functions as macros, the wrapper cannot have the same name // as the wrapped function. namespace posix { // Functions with a different name on Windows. #if GTEST_OS_WINDOWS typedef struct _stat StatStruct; # ifdef __BORLANDC__ inline int IsATTY(int fd) { return isatty(fd); } inline int StrCaseCmp(const char* s1, const char* s2) { return stricmp(s1, s2); } inline char* StrDup(const char* src) { return strdup(src); } # else // !__BORLANDC__ # if GTEST_OS_WINDOWS_MOBILE inline int IsATTY(int /* fd */) { return 0; } # else inline int IsATTY(int fd) { return _isatty(fd); } # endif // GTEST_OS_WINDOWS_MOBILE inline int StrCaseCmp(const char* s1, const char* s2) { return _stricmp(s1, s2); } inline char* StrDup(const char* src) { return _strdup(src); } # endif // __BORLANDC__ # if GTEST_OS_WINDOWS_MOBILE inline int FileNo(FILE* file) { return reinterpret_cast(_fileno(file)); } // Stat(), RmDir(), and IsDir() are not needed on Windows CE at this // time and thus not defined there. # else inline int FileNo(FILE* file) { return _fileno(file); } inline int Stat(const char* path, StatStruct* buf) { return _stat(path, buf); } inline int RmDir(const char* dir) { return _rmdir(dir); } inline bool IsDir(const StatStruct& st) { return (_S_IFDIR & st.st_mode) != 0; } # endif // GTEST_OS_WINDOWS_MOBILE #else typedef struct stat StatStruct; inline int FileNo(FILE* file) { return fileno(file); } inline int IsATTY(int fd) { return isatty(fd); } inline int Stat(const char* path, StatStruct* buf) { return stat(path, buf); } inline int StrCaseCmp(const char* s1, const char* s2) { return strcasecmp(s1, s2); } inline char* StrDup(const char* src) { return strdup(src); } inline int RmDir(const char* dir) { return rmdir(dir); } inline bool IsDir(const StatStruct& st) { return S_ISDIR(st.st_mode); } #endif // GTEST_OS_WINDOWS // Functions deprecated by MSVC 8.0. #ifdef _MSC_VER // Temporarily disable warning 4996 (deprecated function). # pragma warning(push) # pragma warning(disable:4996) #endif inline const char* StrNCpy(char* dest, const char* src, size_t n) { return strncpy(dest, src, n); } // ChDir(), FReopen(), FDOpen(), Read(), Write(), Close(), and // StrError() aren't needed on Windows CE at this time and thus not // defined there. #if !GTEST_OS_WINDOWS_MOBILE inline int ChDir(const char* dir) { return chdir(dir); } #endif inline FILE* FOpen(const char* path, const char* mode) { return fopen(path, mode); } #if !GTEST_OS_WINDOWS_MOBILE inline FILE *FReopen(const char* path, const char* mode, FILE* stream) { return freopen(path, mode, stream); } inline FILE* FDOpen(int fd, const char* mode) { return fdopen(fd, mode); } #endif inline int FClose(FILE* fp) { return fclose(fp); } #if !GTEST_OS_WINDOWS_MOBILE inline int Read(int fd, void* buf, unsigned int count) { return static_cast(read(fd, buf, count)); } inline int Write(int fd, const void* buf, unsigned int count) { return static_cast(write(fd, buf, count)); } inline int Close(int fd) { return close(fd); } inline const char* StrError(int errnum) { return strerror(errnum); } #endif inline const char* GetEnv(const char* name) { #if GTEST_OS_WINDOWS_MOBILE // We are on Windows CE, which has no environment variables. return NULL; #elif defined(__BORLANDC__) || defined(__SunOS_5_8) || defined(__SunOS_5_9) // Environment variables which we programmatically clear will be set to the // empty string rather than unset (NULL). Handle that case. const char* const env = getenv(name); return (env != NULL && env[0] != '\0') ? env : NULL; #else return getenv(name); #endif } #ifdef _MSC_VER # pragma warning(pop) // Restores the warning state. #endif #if GTEST_OS_WINDOWS_MOBILE // Windows CE has no C library. The abort() function is used in // several places in Google Test. This implementation provides a reasonable // imitation of standard behaviour. void Abort(); #else inline void Abort() { abort(); } #endif // GTEST_OS_WINDOWS_MOBILE } // namespace posix // MSVC "deprecates" snprintf and issues warnings wherever it is used. In // order to avoid these warnings, we need to use _snprintf or _snprintf_s on // MSVC-based platforms. We map the GTEST_SNPRINTF_ macro to the appropriate // function in order to achieve that. We use macro definition here because // snprintf is a variadic function. #if _MSC_VER >= 1400 && !GTEST_OS_WINDOWS_MOBILE // MSVC 2005 and above support variadic macros. # define GTEST_SNPRINTF_(buffer, size, format, ...) \ _snprintf_s(buffer, size, size, format, __VA_ARGS__) #elif defined(_MSC_VER) // Windows CE does not define _snprintf_s and MSVC prior to 2005 doesn't // complain about _snprintf. # define GTEST_SNPRINTF_ _snprintf #else # define GTEST_SNPRINTF_ snprintf #endif // The maximum number a BiggestInt can represent. This definition // works no matter BiggestInt is represented in one's complement or // two's complement. // // We cannot rely on numeric_limits in STL, as __int64 and long long // are not part of standard C++ and numeric_limits doesn't need to be // defined for them. const BiggestInt kMaxBiggestInt = ~(static_cast(1) << (8*sizeof(BiggestInt) - 1)); // This template class serves as a compile-time function from size to // type. It maps a size in bytes to a primitive type with that // size. e.g. // // TypeWithSize<4>::UInt // // is typedef-ed to be unsigned int (unsigned integer made up of 4 // bytes). // // Such functionality should belong to STL, but I cannot find it // there. // // Google Test uses this class in the implementation of floating-point // comparison. // // For now it only handles UInt (unsigned int) as that's all Google Test // needs. Other types can be easily added in the future if need // arises. template class TypeWithSize { public: // This prevents the user from using TypeWithSize with incorrect // values of N. typedef void UInt; }; // The specialization for size 4. template <> class TypeWithSize<4> { public: // unsigned int has size 4 in both gcc and MSVC. // // As base/basictypes.h doesn't compile on Windows, we cannot use // uint32, uint64, and etc here. typedef int Int; typedef unsigned int UInt; }; // The specialization for size 8. template <> class TypeWithSize<8> { public: #if GTEST_OS_WINDOWS typedef __int64 Int; typedef unsigned __int64 UInt; #else typedef long long Int; // NOLINT typedef unsigned long long UInt; // NOLINT #endif // GTEST_OS_WINDOWS }; // Integer types of known sizes. typedef TypeWithSize<4>::Int Int32; typedef TypeWithSize<4>::UInt UInt32; typedef TypeWithSize<8>::Int Int64; typedef TypeWithSize<8>::UInt UInt64; typedef TypeWithSize<8>::Int TimeInMillis; // Represents time in milliseconds. // Utilities for command line flags and environment variables. // Macro for referencing flags. #define GTEST_FLAG(name) FLAGS_gtest_##name // Macros for declaring flags. #define GTEST_DECLARE_bool_(name) GTEST_API_ extern bool GTEST_FLAG(name) #define GTEST_DECLARE_int32_(name) \ GTEST_API_ extern ::testing::internal::Int32 GTEST_FLAG(name) #define GTEST_DECLARE_string_(name) \ GTEST_API_ extern ::std::string GTEST_FLAG(name) // Macros for defining flags. #define GTEST_DEFINE_bool_(name, default_val, doc) \ GTEST_API_ bool GTEST_FLAG(name) = (default_val) #define GTEST_DEFINE_int32_(name, default_val, doc) \ GTEST_API_ ::testing::internal::Int32 GTEST_FLAG(name) = (default_val) #define GTEST_DEFINE_string_(name, default_val, doc) \ GTEST_API_ ::std::string GTEST_FLAG(name) = (default_val) // Thread annotations #define GTEST_EXCLUSIVE_LOCK_REQUIRED_(locks) #define GTEST_LOCK_EXCLUDED_(locks) // Parses 'str' for a 32-bit signed integer. If successful, writes the result // to *value and returns true; otherwise leaves *value unchanged and returns // false. // TODO(chandlerc): Find a better way to refactor flag and environment parsing // out of both gtest-port.cc and gtest.cc to avoid exporting this utility // function. bool ParseInt32(const Message& src_text, const char* str, Int32* value); // Parses a bool/Int32/string from the environment variable // corresponding to the given Google Test flag. bool BoolFromGTestEnv(const char* flag, bool default_val); GTEST_API_ Int32 Int32FromGTestEnv(const char* flag, Int32 default_val); const char* StringFromGTestEnv(const char* flag, const char* default_val); } // namespace internal } // namespace testing #endif // GTEST_INCLUDE_GTEST_INTERNAL_GTEST_PORT_H_ #if GTEST_OS_LINUX # include # include # include # include #endif // GTEST_OS_LINUX #if GTEST_HAS_EXCEPTIONS # include #endif #include #include #include #include #include #include // Copyright 2005, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: wan@google.com (Zhanyong Wan) // // The Google C++ Testing Framework (Google Test) // // This header file defines the Message class. // // IMPORTANT NOTE: Due to limitation of the C++ language, we have to // leave some internal implementation details in this header file. // They are clearly marked by comments like this: // // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. // // Such code is NOT meant to be used by a user directly, and is subject // to CHANGE WITHOUT NOTICE. Therefore DO NOT DEPEND ON IT in a user // program! #ifndef GTEST_INCLUDE_GTEST_GTEST_MESSAGE_H_ #define GTEST_INCLUDE_GTEST_GTEST_MESSAGE_H_ #include // Ensures that there is at least one operator<< in the global namespace. // See Message& operator<<(...) below for why. void operator<<(const testing::internal::Secret&, int); namespace testing { // The Message class works like an ostream repeater. // // Typical usage: // // 1. You stream a bunch of values to a Message object. // It will remember the text in a stringstream. // 2. Then you stream the Message object to an ostream. // This causes the text in the Message to be streamed // to the ostream. // // For example; // // testing::Message foo; // foo << 1 << " != " << 2; // std::cout << foo; // // will print "1 != 2". // // Message is not intended to be inherited from. In particular, its // destructor is not virtual. // // Note that stringstream behaves differently in gcc and in MSVC. You // can stream a NULL char pointer to it in the former, but not in the // latter (it causes an access violation if you do). The Message // class hides this difference by treating a NULL char pointer as // "(null)". class GTEST_API_ Message { private: // The type of basic IO manipulators (endl, ends, and flush) for // narrow streams. typedef std::ostream& (*BasicNarrowIoManip)(std::ostream&); public: // Constructs an empty Message. Message(); // Copy constructor. Message(const Message& msg) : ss_(new ::std::stringstream) { // NOLINT *ss_ << msg.GetString(); } // Constructs a Message from a C-string. explicit Message(const char* str) : ss_(new ::std::stringstream) { *ss_ << str; } #if GTEST_OS_SYMBIAN // Streams a value (either a pointer or not) to this object. template inline Message& operator <<(const T& value) { StreamHelper(typename internal::is_pointer::type(), value); return *this; } #else // Streams a non-pointer value to this object. template inline Message& operator <<(const T& val) { // Some libraries overload << for STL containers. These // overloads are defined in the global namespace instead of ::std. // // C++'s symbol lookup rule (i.e. Koenig lookup) says that these // overloads are visible in either the std namespace or the global // namespace, but not other namespaces, including the testing // namespace which Google Test's Message class is in. // // To allow STL containers (and other types that has a << operator // defined in the global namespace) to be used in Google Test // assertions, testing::Message must access the custom << operator // from the global namespace. With this using declaration, // overloads of << defined in the global namespace and those // visible via Koenig lookup are both exposed in this function. using ::operator <<; *ss_ << val; return *this; } // Streams a pointer value to this object. // // This function is an overload of the previous one. When you // stream a pointer to a Message, this definition will be used as it // is more specialized. (The C++ Standard, section // [temp.func.order].) If you stream a non-pointer, then the // previous definition will be used. // // The reason for this overload is that streaming a NULL pointer to // ostream is undefined behavior. Depending on the compiler, you // may get "0", "(nil)", "(null)", or an access violation. To // ensure consistent result across compilers, we always treat NULL // as "(null)". template inline Message& operator <<(T* const& pointer) { // NOLINT if (pointer == NULL) { *ss_ << "(null)"; } else { *ss_ << pointer; } return *this; } #endif // GTEST_OS_SYMBIAN // Since the basic IO manipulators are overloaded for both narrow // and wide streams, we have to provide this specialized definition // of operator <<, even though its body is the same as the // templatized version above. Without this definition, streaming // endl or other basic IO manipulators to Message will confuse the // compiler. Message& operator <<(BasicNarrowIoManip val) { *ss_ << val; return *this; } // Instead of 1/0, we want to see true/false for bool values. Message& operator <<(bool b) { return *this << (b ? "true" : "false"); } // These two overloads allow streaming a wide C string to a Message // using the UTF-8 encoding. Message& operator <<(const wchar_t* wide_c_str); Message& operator <<(wchar_t* wide_c_str); #if GTEST_HAS_STD_WSTRING // Converts the given wide string to a narrow string using the UTF-8 // encoding, and streams the result to this Message object. Message& operator <<(const ::std::wstring& wstr); #endif // GTEST_HAS_STD_WSTRING #if GTEST_HAS_GLOBAL_WSTRING // Converts the given wide string to a narrow string using the UTF-8 // encoding, and streams the result to this Message object. Message& operator <<(const ::wstring& wstr); #endif // GTEST_HAS_GLOBAL_WSTRING // Gets the text streamed to this object so far as an std::string. // Each '\0' character in the buffer is replaced with "\\0". // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. std::string GetString() const; private: #if GTEST_OS_SYMBIAN // These are needed as the Nokia Symbian Compiler cannot decide between // const T& and const T* in a function template. The Nokia compiler _can_ // decide between class template specializations for T and T*, so a // tr1::type_traits-like is_pointer works, and we can overload on that. template inline void StreamHelper(internal::true_type /*is_pointer*/, T* pointer) { if (pointer == NULL) { *ss_ << "(null)"; } else { *ss_ << pointer; } } template inline void StreamHelper(internal::false_type /*is_pointer*/, const T& value) { // See the comments in Message& operator <<(const T&) above for why // we need this using statement. using ::operator <<; *ss_ << value; } #endif // GTEST_OS_SYMBIAN // We'll hold the text streamed to this object here. const internal::scoped_ptr< ::std::stringstream> ss_; // We declare (but don't implement) this to prevent the compiler // from implementing the assignment operator. void operator=(const Message&); }; // Streams a Message to an ostream. inline std::ostream& operator <<(std::ostream& os, const Message& sb) { return os << sb.GetString(); } namespace internal { // Converts a streamable value to an std::string. A NULL pointer is // converted to "(null)". When the input value is a ::string, // ::std::string, ::wstring, or ::std::wstring object, each NUL // character in it is replaced with "\\0". template std::string StreamableToString(const T& streamable) { return (Message() << streamable).GetString(); } } // namespace internal } // namespace testing #endif // GTEST_INCLUDE_GTEST_GTEST_MESSAGE_H_ // Copyright 2005, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Authors: wan@google.com (Zhanyong Wan), eefacm@gmail.com (Sean Mcafee) // // The Google C++ Testing Framework (Google Test) // // This header file declares the String class and functions used internally by // Google Test. They are subject to change without notice. They should not used // by code external to Google Test. // // This header file is #included by . // It should not be #included by other files. #ifndef GTEST_INCLUDE_GTEST_INTERNAL_GTEST_STRING_H_ #define GTEST_INCLUDE_GTEST_INTERNAL_GTEST_STRING_H_ #ifdef __BORLANDC__ // string.h is not guaranteed to provide strcpy on C++ Builder. # include #endif #include #include namespace testing { namespace internal { // String - an abstract class holding static string utilities. class GTEST_API_ String { public: // Static utility methods // Clones a 0-terminated C string, allocating memory using new. The // caller is responsible for deleting the return value using // delete[]. Returns the cloned string, or NULL if the input is // NULL. // // This is different from strdup() in string.h, which allocates // memory using malloc(). static const char* CloneCString(const char* c_str); #if GTEST_OS_WINDOWS_MOBILE // Windows CE does not have the 'ANSI' versions of Win32 APIs. To be // able to pass strings to Win32 APIs on CE we need to convert them // to 'Unicode', UTF-16. // Creates a UTF-16 wide string from the given ANSI string, allocating // memory using new. The caller is responsible for deleting the return // value using delete[]. Returns the wide string, or NULL if the // input is NULL. // // The wide string is created using the ANSI codepage (CP_ACP) to // match the behaviour of the ANSI versions of Win32 calls and the // C runtime. static LPCWSTR AnsiToUtf16(const char* c_str); // Creates an ANSI string from the given wide string, allocating // memory using new. The caller is responsible for deleting the return // value using delete[]. Returns the ANSI string, or NULL if the // input is NULL. // // The returned string is created using the ANSI codepage (CP_ACP) to // match the behaviour of the ANSI versions of Win32 calls and the // C runtime. static const char* Utf16ToAnsi(LPCWSTR utf16_str); #endif // Compares two C strings. Returns true iff they have the same content. // // Unlike strcmp(), this function can handle NULL argument(s). A // NULL C string is considered different to any non-NULL C string, // including the empty string. static bool CStringEquals(const char* lhs, const char* rhs); // Converts a wide C string to a String using the UTF-8 encoding. // NULL will be converted to "(null)". If an error occurred during // the conversion, "(failed to convert from wide string)" is // returned. static std::string ShowWideCString(const wchar_t* wide_c_str); // Compares two wide C strings. Returns true iff they have the same // content. // // Unlike wcscmp(), this function can handle NULL argument(s). A // NULL C string is considered different to any non-NULL C string, // including the empty string. static bool WideCStringEquals(const wchar_t* lhs, const wchar_t* rhs); // Compares two C strings, ignoring case. Returns true iff they // have the same content. // // Unlike strcasecmp(), this function can handle NULL argument(s). // A NULL C string is considered different to any non-NULL C string, // including the empty string. static bool CaseInsensitiveCStringEquals(const char* lhs, const char* rhs); // Compares two wide C strings, ignoring case. Returns true iff they // have the same content. // // Unlike wcscasecmp(), this function can handle NULL argument(s). // A NULL C string is considered different to any non-NULL wide C string, // including the empty string. // NB: The implementations on different platforms slightly differ. // On windows, this method uses _wcsicmp which compares according to LC_CTYPE // environment variable. On GNU platform this method uses wcscasecmp // which compares according to LC_CTYPE category of the current locale. // On MacOS X, it uses towlower, which also uses LC_CTYPE category of the // current locale. static bool CaseInsensitiveWideCStringEquals(const wchar_t* lhs, const wchar_t* rhs); // Returns true iff the given string ends with the given suffix, ignoring // case. Any string is considered to end with an empty suffix. static bool EndsWithCaseInsensitive( const std::string& str, const std::string& suffix); // Formats an int value as "%02d". static std::string FormatIntWidth2(int value); // "%02d" for width == 2 // Formats an int value as "%X". static std::string FormatHexInt(int value); // Formats a byte as "%02X". static std::string FormatByte(unsigned char value); private: String(); // Not meant to be instantiated. }; // class String // Gets the content of the stringstream's buffer as an std::string. Each '\0' // character in the buffer is replaced with "\\0". GTEST_API_ std::string StringStreamToString(::std::stringstream* stream); } // namespace internal } // namespace testing #endif // GTEST_INCLUDE_GTEST_INTERNAL_GTEST_STRING_H_ // Copyright 2008, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: keith.ray@gmail.com (Keith Ray) // // Google Test filepath utilities // // This header file declares classes and functions used internally by // Google Test. They are subject to change without notice. // // This file is #included in . // Do not include this header file separately! #ifndef GTEST_INCLUDE_GTEST_INTERNAL_GTEST_FILEPATH_H_ #define GTEST_INCLUDE_GTEST_INTERNAL_GTEST_FILEPATH_H_ namespace testing { namespace internal { // FilePath - a class for file and directory pathname manipulation which // handles platform-specific conventions (like the pathname separator). // Used for helper functions for naming files in a directory for xml output. // Except for Set methods, all methods are const or static, which provides an // "immutable value object" -- useful for peace of mind. // A FilePath with a value ending in a path separator ("like/this/") represents // a directory, otherwise it is assumed to represent a file. In either case, // it may or may not represent an actual file or directory in the file system. // Names are NOT checked for syntax correctness -- no checking for illegal // characters, malformed paths, etc. class GTEST_API_ FilePath { public: FilePath() : pathname_("") { } FilePath(const FilePath& rhs) : pathname_(rhs.pathname_) { } explicit FilePath(const std::string& pathname) : pathname_(pathname) { Normalize(); } FilePath& operator=(const FilePath& rhs) { Set(rhs); return *this; } void Set(const FilePath& rhs) { pathname_ = rhs.pathname_; } const std::string& string() const { return pathname_; } const char* c_str() const { return pathname_.c_str(); } // Returns the current working directory, or "" if unsuccessful. static FilePath GetCurrentDir(); // Given directory = "dir", base_name = "test", number = 0, // extension = "xml", returns "dir/test.xml". If number is greater // than zero (e.g., 12), returns "dir/test_12.xml". // On Windows platform, uses \ as the separator rather than /. static FilePath MakeFileName(const FilePath& directory, const FilePath& base_name, int number, const char* extension); // Given directory = "dir", relative_path = "test.xml", // returns "dir/test.xml". // On Windows, uses \ as the separator rather than /. static FilePath ConcatPaths(const FilePath& directory, const FilePath& relative_path); // Returns a pathname for a file that does not currently exist. The pathname // will be directory/base_name.extension or // directory/base_name_.extension if directory/base_name.extension // already exists. The number will be incremented until a pathname is found // that does not already exist. // Examples: 'dir/foo_test.xml' or 'dir/foo_test_1.xml'. // There could be a race condition if two or more processes are calling this // function at the same time -- they could both pick the same filename. static FilePath GenerateUniqueFileName(const FilePath& directory, const FilePath& base_name, const char* extension); // Returns true iff the path is "". bool IsEmpty() const { return pathname_.empty(); } // If input name has a trailing separator character, removes it and returns // the name, otherwise return the name string unmodified. // On Windows platform, uses \ as the separator, other platforms use /. FilePath RemoveTrailingPathSeparator() const; // Returns a copy of the FilePath with the directory part removed. // Example: FilePath("path/to/file").RemoveDirectoryName() returns // FilePath("file"). If there is no directory part ("just_a_file"), it returns // the FilePath unmodified. If there is no file part ("just_a_dir/") it // returns an empty FilePath (""). // On Windows platform, '\' is the path separator, otherwise it is '/'. FilePath RemoveDirectoryName() const; // RemoveFileName returns the directory path with the filename removed. // Example: FilePath("path/to/file").RemoveFileName() returns "path/to/". // If the FilePath is "a_file" or "/a_file", RemoveFileName returns // FilePath("./") or, on Windows, FilePath(".\\"). If the filepath does // not have a file, like "just/a/dir/", it returns the FilePath unmodified. // On Windows platform, '\' is the path separator, otherwise it is '/'. FilePath RemoveFileName() const; // Returns a copy of the FilePath with the case-insensitive extension removed. // Example: FilePath("dir/file.exe").RemoveExtension("EXE") returns // FilePath("dir/file"). If a case-insensitive extension is not // found, returns a copy of the original FilePath. FilePath RemoveExtension(const char* extension) const; // Creates directories so that path exists. Returns true if successful or if // the directories already exist; returns false if unable to create // directories for any reason. Will also return false if the FilePath does // not represent a directory (that is, it doesn't end with a path separator). bool CreateDirectoriesRecursively() const; // Create the directory so that path exists. Returns true if successful or // if the directory already exists; returns false if unable to create the // directory for any reason, including if the parent directory does not // exist. Not named "CreateDirectory" because that's a macro on Windows. bool CreateFolder() const; // Returns true if FilePath describes something in the file-system, // either a file, directory, or whatever, and that something exists. bool FileOrDirectoryExists() const; // Returns true if pathname describes a directory in the file-system // that exists. bool DirectoryExists() const; // Returns true if FilePath ends with a path separator, which indicates that // it is intended to represent a directory. Returns false otherwise. // This does NOT check that a directory (or file) actually exists. bool IsDirectory() const; // Returns true if pathname describes a root directory. (Windows has one // root directory per disk drive.) bool IsRootDirectory() const; // Returns true if pathname describes an absolute path. bool IsAbsolutePath() const; private: // Replaces multiple consecutive separators with a single separator. // For example, "bar///foo" becomes "bar/foo". Does not eliminate other // redundancies that might be in a pathname involving "." or "..". // // A pathname with multiple consecutive separators may occur either through // user error or as a result of some scripts or APIs that generate a pathname // with a trailing separator. On other platforms the same API or script // may NOT generate a pathname with a trailing "/". Then elsewhere that // pathname may have another "/" and pathname components added to it, // without checking for the separator already being there. // The script language and operating system may allow paths like "foo//bar" // but some of the functions in FilePath will not handle that correctly. In // particular, RemoveTrailingPathSeparator() only removes one separator, and // it is called in CreateDirectoriesRecursively() assuming that it will change // a pathname from directory syntax (trailing separator) to filename syntax. // // On Windows this method also replaces the alternate path separator '/' with // the primary path separator '\\', so that for example "bar\\/\\foo" becomes // "bar\\foo". void Normalize(); // Returns a pointer to the last occurence of a valid path separator in // the FilePath. On Windows, for example, both '/' and '\' are valid path // separators. Returns NULL if no path separator was found. const char* FindLastPathSeparator() const; std::string pathname_; }; // class FilePath } // namespace internal } // namespace testing #endif // GTEST_INCLUDE_GTEST_INTERNAL_GTEST_FILEPATH_H_ // This file was GENERATED by command: // pump.py gtest-type-util.h.pump // DO NOT EDIT BY HAND!!! // Copyright 2008 Google Inc. // All Rights Reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: wan@google.com (Zhanyong Wan) // Type utilities needed for implementing typed and type-parameterized // tests. This file is generated by a SCRIPT. DO NOT EDIT BY HAND! // // Currently we support at most 50 types in a list, and at most 50 // type-parameterized tests in one type-parameterized test case. // Please contact googletestframework@googlegroups.com if you need // more. #ifndef GTEST_INCLUDE_GTEST_INTERNAL_GTEST_TYPE_UTIL_H_ #define GTEST_INCLUDE_GTEST_INTERNAL_GTEST_TYPE_UTIL_H_ // #ifdef __GNUC__ is too general here. It is possible to use gcc without using // libstdc++ (which is where cxxabi.h comes from). # if GTEST_HAS_CXXABI_H_ # include # elif defined(__HP_aCC) # include # endif // GTEST_HASH_CXXABI_H_ namespace testing { namespace internal { // GetTypeName() returns a human-readable name of type T. // NB: This function is also used in Google Mock, so don't move it inside of // the typed-test-only section below. template std::string GetTypeName() { # if GTEST_HAS_RTTI const char* const name = typeid(T).name(); # if GTEST_HAS_CXXABI_H_ || defined(__HP_aCC) int status = 0; // gcc's implementation of typeid(T).name() mangles the type name, // so we have to demangle it. # if GTEST_HAS_CXXABI_H_ using abi::__cxa_demangle; # endif // GTEST_HAS_CXXABI_H_ char* const readable_name = __cxa_demangle(name, 0, 0, &status); const std::string name_str(status == 0 ? readable_name : name); free(readable_name); return name_str; # else return name; # endif // GTEST_HAS_CXXABI_H_ || __HP_aCC # else return ""; # endif // GTEST_HAS_RTTI } #if GTEST_HAS_TYPED_TEST || GTEST_HAS_TYPED_TEST_P // AssertyTypeEq::type is defined iff T1 and T2 are the same // type. This can be used as a compile-time assertion to ensure that // two types are equal. template struct AssertTypeEq; template struct AssertTypeEq { typedef bool type; }; // A unique type used as the default value for the arguments of class // template Types. This allows us to simulate variadic templates // (e.g. Types, Type, and etc), which C++ doesn't // support directly. struct None {}; // The following family of struct and struct templates are used to // represent type lists. In particular, TypesN // represents a type list with N types (T1, T2, ..., and TN) in it. // Except for Types0, every struct in the family has two member types: // Head for the first type in the list, and Tail for the rest of the // list. // The empty type list. struct Types0 {}; // Type lists of length 1, 2, 3, and so on. template struct Types1 { typedef T1 Head; typedef Types0 Tail; }; template struct Types2 { typedef T1 Head; typedef Types1 Tail; }; template struct Types3 { typedef T1 Head; typedef Types2 Tail; }; template struct Types4 { typedef T1 Head; typedef Types3 Tail; }; template struct Types5 { typedef T1 Head; typedef Types4 Tail; }; template struct Types6 { typedef T1 Head; typedef Types5 Tail; }; template struct Types7 { typedef T1 Head; typedef Types6 Tail; }; template struct Types8 { typedef T1 Head; typedef Types7 Tail; }; template struct Types9 { typedef T1 Head; typedef Types8 Tail; }; template struct Types10 { typedef T1 Head; typedef Types9 Tail; }; template struct Types11 { typedef T1 Head; typedef Types10 Tail; }; template struct Types12 { typedef T1 Head; typedef Types11 Tail; }; template struct Types13 { typedef T1 Head; typedef Types12 Tail; }; template struct Types14 { typedef T1 Head; typedef Types13 Tail; }; template struct Types15 { typedef T1 Head; typedef Types14 Tail; }; template struct Types16 { typedef T1 Head; typedef Types15 Tail; }; template struct Types17 { typedef T1 Head; typedef Types16 Tail; }; template struct Types18 { typedef T1 Head; typedef Types17 Tail; }; template struct Types19 { typedef T1 Head; typedef Types18 Tail; }; template struct Types20 { typedef T1 Head; typedef Types19 Tail; }; template struct Types21 { typedef T1 Head; typedef Types20 Tail; }; template struct Types22 { typedef T1 Head; typedef Types21 Tail; }; template struct Types23 { typedef T1 Head; typedef Types22 Tail; }; template struct Types24 { typedef T1 Head; typedef Types23 Tail; }; template struct Types25 { typedef T1 Head; typedef Types24 Tail; }; template struct Types26 { typedef T1 Head; typedef Types25 Tail; }; template struct Types27 { typedef T1 Head; typedef Types26 Tail; }; template struct Types28 { typedef T1 Head; typedef Types27 Tail; }; template struct Types29 { typedef T1 Head; typedef Types28 Tail; }; template struct Types30 { typedef T1 Head; typedef Types29 Tail; }; template struct Types31 { typedef T1 Head; typedef Types30 Tail; }; template struct Types32 { typedef T1 Head; typedef Types31 Tail; }; template struct Types33 { typedef T1 Head; typedef Types32 Tail; }; template struct Types34 { typedef T1 Head; typedef Types33 Tail; }; template struct Types35 { typedef T1 Head; typedef Types34 Tail; }; template struct Types36 { typedef T1 Head; typedef Types35 Tail; }; template struct Types37 { typedef T1 Head; typedef Types36 Tail; }; template struct Types38 { typedef T1 Head; typedef Types37 Tail; }; template struct Types39 { typedef T1 Head; typedef Types38 Tail; }; template struct Types40 { typedef T1 Head; typedef Types39 Tail; }; template struct Types41 { typedef T1 Head; typedef Types40 Tail; }; template struct Types42 { typedef T1 Head; typedef Types41 Tail; }; template struct Types43 { typedef T1 Head; typedef Types42 Tail; }; template struct Types44 { typedef T1 Head; typedef Types43 Tail; }; template struct Types45 { typedef T1 Head; typedef Types44 Tail; }; template struct Types46 { typedef T1 Head; typedef Types45 Tail; }; template struct Types47 { typedef T1 Head; typedef Types46 Tail; }; template struct Types48 { typedef T1 Head; typedef Types47 Tail; }; template struct Types49 { typedef T1 Head; typedef Types48 Tail; }; template struct Types50 { typedef T1 Head; typedef Types49 Tail; }; } // namespace internal // We don't want to require the users to write TypesN<...> directly, // as that would require them to count the length. Types<...> is much // easier to write, but generates horrible messages when there is a // compiler error, as gcc insists on printing out each template // argument, even if it has the default value (this means Types // will appear as Types in the compiler // errors). // // Our solution is to combine the best part of the two approaches: a // user would write Types, and Google Test will translate // that to TypesN internally to make error messages // readable. The translation is done by the 'type' member of the // Types template. template struct Types { typedef internal::Types50 type; }; template <> struct Types { typedef internal::Types0 type; }; template struct Types { typedef internal::Types1 type; }; template struct Types { typedef internal::Types2 type; }; template struct Types { typedef internal::Types3 type; }; template struct Types { typedef internal::Types4 type; }; template struct Types { typedef internal::Types5 type; }; template struct Types { typedef internal::Types6 type; }; template struct Types { typedef internal::Types7 type; }; template struct Types { typedef internal::Types8 type; }; template struct Types { typedef internal::Types9 type; }; template struct Types { typedef internal::Types10 type; }; template struct Types { typedef internal::Types11 type; }; template struct Types { typedef internal::Types12 type; }; template struct Types { typedef internal::Types13 type; }; template struct Types { typedef internal::Types14 type; }; template struct Types { typedef internal::Types15 type; }; template struct Types { typedef internal::Types16 type; }; template struct Types { typedef internal::Types17 type; }; template struct Types { typedef internal::Types18 type; }; template struct Types { typedef internal::Types19 type; }; template struct Types { typedef internal::Types20 type; }; template struct Types { typedef internal::Types21 type; }; template struct Types { typedef internal::Types22 type; }; template struct Types { typedef internal::Types23 type; }; template struct Types { typedef internal::Types24 type; }; template struct Types { typedef internal::Types25 type; }; template struct Types { typedef internal::Types26 type; }; template struct Types { typedef internal::Types27 type; }; template struct Types { typedef internal::Types28 type; }; template struct Types { typedef internal::Types29 type; }; template struct Types { typedef internal::Types30 type; }; template struct Types { typedef internal::Types31 type; }; template struct Types { typedef internal::Types32 type; }; template struct Types { typedef internal::Types33 type; }; template struct Types { typedef internal::Types34 type; }; template struct Types { typedef internal::Types35 type; }; template struct Types { typedef internal::Types36 type; }; template struct Types { typedef internal::Types37 type; }; template struct Types { typedef internal::Types38 type; }; template struct Types { typedef internal::Types39 type; }; template struct Types { typedef internal::Types40 type; }; template struct Types { typedef internal::Types41 type; }; template struct Types { typedef internal::Types42 type; }; template struct Types { typedef internal::Types43 type; }; template struct Types { typedef internal::Types44 type; }; template struct Types { typedef internal::Types45 type; }; template struct Types { typedef internal::Types46 type; }; template struct Types { typedef internal::Types47 type; }; template struct Types { typedef internal::Types48 type; }; template struct Types { typedef internal::Types49 type; }; namespace internal { # define GTEST_TEMPLATE_ template class // The template "selector" struct TemplateSel is used to // represent Tmpl, which must be a class template with one type // parameter, as a type. TemplateSel::Bind::type is defined // as the type Tmpl. This allows us to actually instantiate the // template "selected" by TemplateSel. // // This trick is necessary for simulating typedef for class templates, // which C++ doesn't support directly. template struct TemplateSel { template struct Bind { typedef Tmpl type; }; }; # define GTEST_BIND_(TmplSel, T) \ TmplSel::template Bind::type // A unique struct template used as the default value for the // arguments of class template Templates. This allows us to simulate // variadic templates (e.g. Templates, Templates, // and etc), which C++ doesn't support directly. template struct NoneT {}; // The following family of struct and struct templates are used to // represent template lists. In particular, TemplatesN represents a list of N templates (T1, T2, ..., and TN). Except // for Templates0, every struct in the family has two member types: // Head for the selector of the first template in the list, and Tail // for the rest of the list. // The empty template list. struct Templates0 {}; // Template lists of length 1, 2, 3, and so on. template struct Templates1 { typedef TemplateSel Head; typedef Templates0 Tail; }; template struct Templates2 { typedef TemplateSel Head; typedef Templates1 Tail; }; template struct Templates3 { typedef TemplateSel Head; typedef Templates2 Tail; }; template struct Templates4 { typedef TemplateSel Head; typedef Templates3 Tail; }; template struct Templates5 { typedef TemplateSel Head; typedef Templates4 Tail; }; template struct Templates6 { typedef TemplateSel Head; typedef Templates5 Tail; }; template struct Templates7 { typedef TemplateSel Head; typedef Templates6 Tail; }; template struct Templates8 { typedef TemplateSel Head; typedef Templates7 Tail; }; template struct Templates9 { typedef TemplateSel Head; typedef Templates8 Tail; }; template struct Templates10 { typedef TemplateSel Head; typedef Templates9 Tail; }; template struct Templates11 { typedef TemplateSel Head; typedef Templates10 Tail; }; template struct Templates12 { typedef TemplateSel Head; typedef Templates11 Tail; }; template struct Templates13 { typedef TemplateSel Head; typedef Templates12 Tail; }; template struct Templates14 { typedef TemplateSel Head; typedef Templates13 Tail; }; template struct Templates15 { typedef TemplateSel Head; typedef Templates14 Tail; }; template struct Templates16 { typedef TemplateSel Head; typedef Templates15 Tail; }; template struct Templates17 { typedef TemplateSel Head; typedef Templates16 Tail; }; template struct Templates18 { typedef TemplateSel Head; typedef Templates17 Tail; }; template struct Templates19 { typedef TemplateSel Head; typedef Templates18 Tail; }; template struct Templates20 { typedef TemplateSel Head; typedef Templates19 Tail; }; template struct Templates21 { typedef TemplateSel Head; typedef Templates20 Tail; }; template struct Templates22 { typedef TemplateSel Head; typedef Templates21 Tail; }; template struct Templates23 { typedef TemplateSel Head; typedef Templates22 Tail; }; template struct Templates24 { typedef TemplateSel Head; typedef Templates23 Tail; }; template struct Templates25 { typedef TemplateSel Head; typedef Templates24 Tail; }; template struct Templates26 { typedef TemplateSel Head; typedef Templates25 Tail; }; template struct Templates27 { typedef TemplateSel Head; typedef Templates26 Tail; }; template struct Templates28 { typedef TemplateSel Head; typedef Templates27 Tail; }; template struct Templates29 { typedef TemplateSel Head; typedef Templates28 Tail; }; template struct Templates30 { typedef TemplateSel Head; typedef Templates29 Tail; }; template struct Templates31 { typedef TemplateSel Head; typedef Templates30 Tail; }; template struct Templates32 { typedef TemplateSel Head; typedef Templates31 Tail; }; template struct Templates33 { typedef TemplateSel Head; typedef Templates32 Tail; }; template struct Templates34 { typedef TemplateSel Head; typedef Templates33 Tail; }; template struct Templates35 { typedef TemplateSel Head; typedef Templates34 Tail; }; template struct Templates36 { typedef TemplateSel Head; typedef Templates35 Tail; }; template struct Templates37 { typedef TemplateSel Head; typedef Templates36 Tail; }; template struct Templates38 { typedef TemplateSel Head; typedef Templates37 Tail; }; template struct Templates39 { typedef TemplateSel Head; typedef Templates38 Tail; }; template struct Templates40 { typedef TemplateSel Head; typedef Templates39 Tail; }; template struct Templates41 { typedef TemplateSel Head; typedef Templates40 Tail; }; template struct Templates42 { typedef TemplateSel Head; typedef Templates41 Tail; }; template struct Templates43 { typedef TemplateSel Head; typedef Templates42 Tail; }; template struct Templates44 { typedef TemplateSel Head; typedef Templates43 Tail; }; template struct Templates45 { typedef TemplateSel Head; typedef Templates44 Tail; }; template struct Templates46 { typedef TemplateSel Head; typedef Templates45 Tail; }; template struct Templates47 { typedef TemplateSel Head; typedef Templates46 Tail; }; template struct Templates48 { typedef TemplateSel Head; typedef Templates47 Tail; }; template struct Templates49 { typedef TemplateSel Head; typedef Templates48 Tail; }; template struct Templates50 { typedef TemplateSel Head; typedef Templates49 Tail; }; // We don't want to require the users to write TemplatesN<...> directly, // as that would require them to count the length. Templates<...> is much // easier to write, but generates horrible messages when there is a // compiler error, as gcc insists on printing out each template // argument, even if it has the default value (this means Templates // will appear as Templates in the compiler // errors). // // Our solution is to combine the best part of the two approaches: a // user would write Templates, and Google Test will translate // that to TemplatesN internally to make error messages // readable. The translation is done by the 'type' member of the // Templates template. template struct Templates { typedef Templates50 type; }; template <> struct Templates { typedef Templates0 type; }; template struct Templates { typedef Templates1 type; }; template struct Templates { typedef Templates2 type; }; template struct Templates { typedef Templates3 type; }; template struct Templates { typedef Templates4 type; }; template struct Templates { typedef Templates5 type; }; template struct Templates { typedef Templates6 type; }; template struct Templates { typedef Templates7 type; }; template struct Templates { typedef Templates8 type; }; template struct Templates { typedef Templates9 type; }; template struct Templates { typedef Templates10 type; }; template struct Templates { typedef Templates11 type; }; template struct Templates { typedef Templates12 type; }; template struct Templates { typedef Templates13 type; }; template struct Templates { typedef Templates14 type; }; template struct Templates { typedef Templates15 type; }; template struct Templates { typedef Templates16 type; }; template struct Templates { typedef Templates17 type; }; template struct Templates { typedef Templates18 type; }; template struct Templates { typedef Templates19 type; }; template struct Templates { typedef Templates20 type; }; template struct Templates { typedef Templates21 type; }; template struct Templates { typedef Templates22 type; }; template struct Templates { typedef Templates23 type; }; template struct Templates { typedef Templates24 type; }; template struct Templates { typedef Templates25 type; }; template struct Templates { typedef Templates26 type; }; template struct Templates { typedef Templates27 type; }; template struct Templates { typedef Templates28 type; }; template struct Templates { typedef Templates29 type; }; template struct Templates { typedef Templates30 type; }; template struct Templates { typedef Templates31 type; }; template struct Templates { typedef Templates32 type; }; template struct Templates { typedef Templates33 type; }; template struct Templates { typedef Templates34 type; }; template struct Templates { typedef Templates35 type; }; template struct Templates { typedef Templates36 type; }; template struct Templates { typedef Templates37 type; }; template struct Templates { typedef Templates38 type; }; template struct Templates { typedef Templates39 type; }; template struct Templates { typedef Templates40 type; }; template struct Templates { typedef Templates41 type; }; template struct Templates { typedef Templates42 type; }; template struct Templates { typedef Templates43 type; }; template struct Templates { typedef Templates44 type; }; template struct Templates { typedef Templates45 type; }; template struct Templates { typedef Templates46 type; }; template struct Templates { typedef Templates47 type; }; template struct Templates { typedef Templates48 type; }; template struct Templates { typedef Templates49 type; }; // The TypeList template makes it possible to use either a single type // or a Types<...> list in TYPED_TEST_CASE() and // INSTANTIATE_TYPED_TEST_CASE_P(). template struct TypeList { typedef Types1 type; }; template struct TypeList > { typedef typename Types::type type; }; #endif // GTEST_HAS_TYPED_TEST || GTEST_HAS_TYPED_TEST_P } // namespace internal } // namespace testing #endif // GTEST_INCLUDE_GTEST_INTERNAL_GTEST_TYPE_UTIL_H_ // Due to C++ preprocessor weirdness, we need double indirection to // concatenate two tokens when one of them is __LINE__. Writing // // foo ## __LINE__ // // will result in the token foo__LINE__, instead of foo followed by // the current line number. For more details, see // http://www.parashift.com/c++-faq-lite/misc-technical-issues.html#faq-39.6 #define GTEST_CONCAT_TOKEN_(foo, bar) GTEST_CONCAT_TOKEN_IMPL_(foo, bar) #define GTEST_CONCAT_TOKEN_IMPL_(foo, bar) foo ## bar class ProtocolMessage; namespace proto2 { class Message; } namespace testing { // Forward declarations. class AssertionResult; // Result of an assertion. class Message; // Represents a failure message. class Test; // Represents a test. class TestInfo; // Information about a test. class TestPartResult; // Result of a test part. class UnitTest; // A collection of test cases. template ::std::string PrintToString(const T& value); namespace internal { struct TraceInfo; // Information about a trace point. class ScopedTrace; // Implements scoped trace. class TestInfoImpl; // Opaque implementation of TestInfo class UnitTestImpl; // Opaque implementation of UnitTest // How many times InitGoogleTest() has been called. GTEST_API_ extern int g_init_gtest_count; // The text used in failure messages to indicate the start of the // stack trace. GTEST_API_ extern const char kStackTraceMarker[]; // Two overloaded helpers for checking at compile time whether an // expression is a null pointer literal (i.e. NULL or any 0-valued // compile-time integral constant). Their return values have // different sizes, so we can use sizeof() to test which version is // picked by the compiler. These helpers have no implementations, as // we only need their signatures. // // Given IsNullLiteralHelper(x), the compiler will pick the first // version if x can be implicitly converted to Secret*, and pick the // second version otherwise. Since Secret is a secret and incomplete // type, the only expression a user can write that has type Secret* is // a null pointer literal. Therefore, we know that x is a null // pointer literal if and only if the first version is picked by the // compiler. char IsNullLiteralHelper(Secret* p); char (&IsNullLiteralHelper(...))[2]; // NOLINT // A compile-time bool constant that is true if and only if x is a // null pointer literal (i.e. NULL or any 0-valued compile-time // integral constant). #ifdef GTEST_ELLIPSIS_NEEDS_POD_ // We lose support for NULL detection where the compiler doesn't like // passing non-POD classes through ellipsis (...). # define GTEST_IS_NULL_LITERAL_(x) false #else # define GTEST_IS_NULL_LITERAL_(x) \ (sizeof(::testing::internal::IsNullLiteralHelper(x)) == 1) #endif // GTEST_ELLIPSIS_NEEDS_POD_ // Appends the user-supplied message to the Google-Test-generated message. GTEST_API_ std::string AppendUserMessage( const std::string& gtest_msg, const Message& user_msg); #if GTEST_HAS_EXCEPTIONS // This exception is thrown by (and only by) a failed Google Test // assertion when GTEST_FLAG(throw_on_failure) is true (if exceptions // are enabled). We derive it from std::runtime_error, which is for // errors presumably detectable only at run time. Since // std::runtime_error inherits from std::exception, many testing // frameworks know how to extract and print the message inside it. class GTEST_API_ GoogleTestFailureException : public ::std::runtime_error { public: explicit GoogleTestFailureException(const TestPartResult& failure); }; #endif // GTEST_HAS_EXCEPTIONS // A helper class for creating scoped traces in user programs. class GTEST_API_ ScopedTrace { public: // The c'tor pushes the given source file location and message onto // a trace stack maintained by Google Test. ScopedTrace(const char* file, int line, const Message& message); // The d'tor pops the info pushed by the c'tor. // // Note that the d'tor is not virtual in order to be efficient. // Don't inherit from ScopedTrace! ~ScopedTrace(); private: GTEST_DISALLOW_COPY_AND_ASSIGN_(ScopedTrace); } GTEST_ATTRIBUTE_UNUSED_; // A ScopedTrace object does its job in its // c'tor and d'tor. Therefore it doesn't // need to be used otherwise. // Constructs and returns the message for an equality assertion // (e.g. ASSERT_EQ, EXPECT_STREQ, etc) failure. // // The first four parameters are the expressions used in the assertion // and their values, as strings. For example, for ASSERT_EQ(foo, bar) // where foo is 5 and bar is 6, we have: // // expected_expression: "foo" // actual_expression: "bar" // expected_value: "5" // actual_value: "6" // // The ignoring_case parameter is true iff the assertion is a // *_STRCASEEQ*. When it's true, the string " (ignoring case)" will // be inserted into the message. GTEST_API_ AssertionResult EqFailure(const char* expected_expression, const char* actual_expression, const std::string& expected_value, const std::string& actual_value, bool ignoring_case); // Constructs a failure message for Boolean assertions such as EXPECT_TRUE. GTEST_API_ std::string GetBoolAssertionFailureMessage( const AssertionResult& assertion_result, const char* expression_text, const char* actual_predicate_value, const char* expected_predicate_value); // This template class represents an IEEE floating-point number // (either single-precision or double-precision, depending on the // template parameters). // // The purpose of this class is to do more sophisticated number // comparison. (Due to round-off error, etc, it's very unlikely that // two floating-points will be equal exactly. Hence a naive // comparison by the == operation often doesn't work.) // // Format of IEEE floating-point: // // The most-significant bit being the leftmost, an IEEE // floating-point looks like // // sign_bit exponent_bits fraction_bits // // Here, sign_bit is a single bit that designates the sign of the // number. // // For float, there are 8 exponent bits and 23 fraction bits. // // For double, there are 11 exponent bits and 52 fraction bits. // // More details can be found at // http://en.wikipedia.org/wiki/IEEE_floating-point_standard. // // Template parameter: // // RawType: the raw floating-point type (either float or double) template class FloatingPoint { public: // Defines the unsigned integer type that has the same size as the // floating point number. typedef typename TypeWithSize::UInt Bits; // Constants. // # of bits in a number. static const size_t kBitCount = 8*sizeof(RawType); // # of fraction bits in a number. static const size_t kFractionBitCount = std::numeric_limits::digits - 1; // # of exponent bits in a number. static const size_t kExponentBitCount = kBitCount - 1 - kFractionBitCount; // The mask for the sign bit. static const Bits kSignBitMask = static_cast(1) << (kBitCount - 1); // The mask for the fraction bits. static const Bits kFractionBitMask = ~static_cast(0) >> (kExponentBitCount + 1); // The mask for the exponent bits. static const Bits kExponentBitMask = ~(kSignBitMask | kFractionBitMask); // How many ULP's (Units in the Last Place) we want to tolerate when // comparing two numbers. The larger the value, the more error we // allow. A 0 value means that two numbers must be exactly the same // to be considered equal. // // The maximum error of a single floating-point operation is 0.5 // units in the last place. On Intel CPU's, all floating-point // calculations are done with 80-bit precision, while double has 64 // bits. Therefore, 4 should be enough for ordinary use. // // See the following article for more details on ULP: // http://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/ static const size_t kMaxUlps = 4; // Constructs a FloatingPoint from a raw floating-point number. // // On an Intel CPU, passing a non-normalized NAN (Not a Number) // around may change its bits, although the new value is guaranteed // to be also a NAN. Therefore, don't expect this constructor to // preserve the bits in x when x is a NAN. explicit FloatingPoint(const RawType& x) { u_.value_ = x; } // Static methods // Reinterprets a bit pattern as a floating-point number. // // This function is needed to test the AlmostEquals() method. static RawType ReinterpretBits(const Bits bits) { FloatingPoint fp(0); fp.u_.bits_ = bits; return fp.u_.value_; } // Returns the floating-point number that represent positive infinity. static RawType Infinity() { return ReinterpretBits(kExponentBitMask); } // Returns the maximum representable finite floating-point number. static RawType Max(); // Non-static methods // Returns the bits that represents this number. const Bits &bits() const { return u_.bits_; } // Returns the exponent bits of this number. Bits exponent_bits() const { return kExponentBitMask & u_.bits_; } // Returns the fraction bits of this number. Bits fraction_bits() const { return kFractionBitMask & u_.bits_; } // Returns the sign bit of this number. Bits sign_bit() const { return kSignBitMask & u_.bits_; } // Returns true iff this is NAN (not a number). bool is_nan() const { // It's a NAN if the exponent bits are all ones and the fraction // bits are not entirely zeros. return (exponent_bits() == kExponentBitMask) && (fraction_bits() != 0); } // Returns true iff this number is at most kMaxUlps ULP's away from // rhs. In particular, this function: // // - returns false if either number is (or both are) NAN. // - treats really large numbers as almost equal to infinity. // - thinks +0.0 and -0.0 are 0 DLP's apart. bool AlmostEquals(const FloatingPoint& rhs) const { // The IEEE standard says that any comparison operation involving // a NAN must return false. if (is_nan() || rhs.is_nan()) return false; return DistanceBetweenSignAndMagnitudeNumbers(u_.bits_, rhs.u_.bits_) <= kMaxUlps; } private: // The data type used to store the actual floating-point number. union FloatingPointUnion { RawType value_; // The raw floating-point number. Bits bits_; // The bits that represent the number. }; // Converts an integer from the sign-and-magnitude representation to // the biased representation. More precisely, let N be 2 to the // power of (kBitCount - 1), an integer x is represented by the // unsigned number x + N. // // For instance, // // -N + 1 (the most negative number representable using // sign-and-magnitude) is represented by 1; // 0 is represented by N; and // N - 1 (the biggest number representable using // sign-and-magnitude) is represented by 2N - 1. // // Read http://en.wikipedia.org/wiki/Signed_number_representations // for more details on signed number representations. static Bits SignAndMagnitudeToBiased(const Bits &sam) { if (kSignBitMask & sam) { // sam represents a negative number. return ~sam + 1; } else { // sam represents a positive number. return kSignBitMask | sam; } } // Given two numbers in the sign-and-magnitude representation, // returns the distance between them as an unsigned number. static Bits DistanceBetweenSignAndMagnitudeNumbers(const Bits &sam1, const Bits &sam2) { const Bits biased1 = SignAndMagnitudeToBiased(sam1); const Bits biased2 = SignAndMagnitudeToBiased(sam2); return (biased1 >= biased2) ? (biased1 - biased2) : (biased2 - biased1); } FloatingPointUnion u_; }; // We cannot use std::numeric_limits::max() as it clashes with the max() // macro defined by . template <> inline float FloatingPoint::Max() { return FLT_MAX; } template <> inline double FloatingPoint::Max() { return DBL_MAX; } // Typedefs the instances of the FloatingPoint template class that we // care to use. typedef FloatingPoint Float; typedef FloatingPoint Double; // In order to catch the mistake of putting tests that use different // test fixture classes in the same test case, we need to assign // unique IDs to fixture classes and compare them. The TypeId type is // used to hold such IDs. The user should treat TypeId as an opaque // type: the only operation allowed on TypeId values is to compare // them for equality using the == operator. typedef const void* TypeId; template class TypeIdHelper { public: // dummy_ must not have a const type. Otherwise an overly eager // compiler (e.g. MSVC 7.1 & 8.0) may try to merge // TypeIdHelper::dummy_ for different Ts as an "optimization". static bool dummy_; }; template bool TypeIdHelper::dummy_ = false; // GetTypeId() returns the ID of type T. Different values will be // returned for different types. Calling the function twice with the // same type argument is guaranteed to return the same ID. template TypeId GetTypeId() { // The compiler is required to allocate a different // TypeIdHelper::dummy_ variable for each T used to instantiate // the template. Therefore, the address of dummy_ is guaranteed to // be unique. return &(TypeIdHelper::dummy_); } // Returns the type ID of ::testing::Test. Always call this instead // of GetTypeId< ::testing::Test>() to get the type ID of // ::testing::Test, as the latter may give the wrong result due to a // suspected linker bug when compiling Google Test as a Mac OS X // framework. GTEST_API_ TypeId GetTestTypeId(); // Defines the abstract factory interface that creates instances // of a Test object. class TestFactoryBase { public: virtual ~TestFactoryBase() {} // Creates a test instance to run. The instance is both created and destroyed // within TestInfoImpl::Run() virtual Test* CreateTest() = 0; protected: TestFactoryBase() {} private: GTEST_DISALLOW_COPY_AND_ASSIGN_(TestFactoryBase); }; // This class provides implementation of TeastFactoryBase interface. // It is used in TEST and TEST_F macros. template class TestFactoryImpl : public TestFactoryBase { public: virtual Test* CreateTest() { return new TestClass; } }; #if GTEST_OS_WINDOWS // Predicate-formatters for implementing the HRESULT checking macros // {ASSERT|EXPECT}_HRESULT_{SUCCEEDED|FAILED} // We pass a long instead of HRESULT to avoid causing an // include dependency for the HRESULT type. GTEST_API_ AssertionResult IsHRESULTSuccess(const char* expr, long hr); // NOLINT GTEST_API_ AssertionResult IsHRESULTFailure(const char* expr, long hr); // NOLINT #endif // GTEST_OS_WINDOWS // Types of SetUpTestCase() and TearDownTestCase() functions. typedef void (*SetUpTestCaseFunc)(); typedef void (*TearDownTestCaseFunc)(); // Creates a new TestInfo object and registers it with Google Test; // returns the created object. // // Arguments: // // test_case_name: name of the test case // name: name of the test // type_param the name of the test's type parameter, or NULL if // this is not a typed or a type-parameterized test. // value_param text representation of the test's value parameter, // or NULL if this is not a type-parameterized test. // fixture_class_id: ID of the test fixture class // set_up_tc: pointer to the function that sets up the test case // tear_down_tc: pointer to the function that tears down the test case // factory: pointer to the factory that creates a test object. // The newly created TestInfo instance will assume // ownership of the factory object. GTEST_API_ TestInfo* MakeAndRegisterTestInfo( const char* test_case_name, const char* name, const char* type_param, const char* value_param, TypeId fixture_class_id, SetUpTestCaseFunc set_up_tc, TearDownTestCaseFunc tear_down_tc, TestFactoryBase* factory); // If *pstr starts with the given prefix, modifies *pstr to be right // past the prefix and returns true; otherwise leaves *pstr unchanged // and returns false. None of pstr, *pstr, and prefix can be NULL. GTEST_API_ bool SkipPrefix(const char* prefix, const char** pstr); #if GTEST_HAS_TYPED_TEST || GTEST_HAS_TYPED_TEST_P // State of the definition of a type-parameterized test case. class GTEST_API_ TypedTestCasePState { public: TypedTestCasePState() : registered_(false) {} // Adds the given test name to defined_test_names_ and return true // if the test case hasn't been registered; otherwise aborts the // program. bool AddTestName(const char* file, int line, const char* case_name, const char* test_name) { if (registered_) { fprintf(stderr, "%s Test %s must be defined before " "REGISTER_TYPED_TEST_CASE_P(%s, ...).\n", FormatFileLocation(file, line).c_str(), test_name, case_name); fflush(stderr); posix::Abort(); } defined_test_names_.insert(test_name); return true; } // Verifies that registered_tests match the test names in // defined_test_names_; returns registered_tests if successful, or // aborts the program otherwise. const char* VerifyRegisteredTestNames( const char* file, int line, const char* registered_tests); private: bool registered_; ::std::set defined_test_names_; }; // Skips to the first non-space char after the first comma in 'str'; // returns NULL if no comma is found in 'str'. inline const char* SkipComma(const char* str) { const char* comma = strchr(str, ','); if (comma == NULL) { return NULL; } while (IsSpace(*(++comma))) {} return comma; } // Returns the prefix of 'str' before the first comma in it; returns // the entire string if it contains no comma. inline std::string GetPrefixUntilComma(const char* str) { const char* comma = strchr(str, ','); return comma == NULL ? str : std::string(str, comma); } // TypeParameterizedTest::Register() // registers a list of type-parameterized tests with Google Test. The // return value is insignificant - we just need to return something // such that we can call this function in a namespace scope. // // Implementation note: The GTEST_TEMPLATE_ macro declares a template // template parameter. It's defined in gtest-type-util.h. template class TypeParameterizedTest { public: // 'index' is the index of the test in the type list 'Types' // specified in INSTANTIATE_TYPED_TEST_CASE_P(Prefix, TestCase, // Types). Valid values for 'index' are [0, N - 1] where N is the // length of Types. static bool Register(const char* prefix, const char* case_name, const char* test_names, int index) { typedef typename Types::Head Type; typedef Fixture FixtureClass; typedef typename GTEST_BIND_(TestSel, Type) TestClass; // First, registers the first type-parameterized test in the type // list. MakeAndRegisterTestInfo( (std::string(prefix) + (prefix[0] == '\0' ? "" : "/") + case_name + "/" + StreamableToString(index)).c_str(), GetPrefixUntilComma(test_names).c_str(), GetTypeName().c_str(), NULL, // No value parameter. GetTypeId(), TestClass::SetUpTestCase, TestClass::TearDownTestCase, new TestFactoryImpl); // Next, recurses (at compile time) with the tail of the type list. return TypeParameterizedTest ::Register(prefix, case_name, test_names, index + 1); } }; // The base case for the compile time recursion. template class TypeParameterizedTest { public: static bool Register(const char* /*prefix*/, const char* /*case_name*/, const char* /*test_names*/, int /*index*/) { return true; } }; // TypeParameterizedTestCase::Register() // registers *all combinations* of 'Tests' and 'Types' with Google // Test. The return value is insignificant - we just need to return // something such that we can call this function in a namespace scope. template class TypeParameterizedTestCase { public: static bool Register(const char* prefix, const char* case_name, const char* test_names) { typedef typename Tests::Head Head; // First, register the first test in 'Test' for each type in 'Types'. TypeParameterizedTest::Register( prefix, case_name, test_names, 0); // Next, recurses (at compile time) with the tail of the test list. return TypeParameterizedTestCase ::Register(prefix, case_name, SkipComma(test_names)); } }; // The base case for the compile time recursion. template class TypeParameterizedTestCase { public: static bool Register(const char* /*prefix*/, const char* /*case_name*/, const char* /*test_names*/) { return true; } }; #endif // GTEST_HAS_TYPED_TEST || GTEST_HAS_TYPED_TEST_P // Returns the current OS stack trace as an std::string. // // The maximum number of stack frames to be included is specified by // the gtest_stack_trace_depth flag. The skip_count parameter // specifies the number of top frames to be skipped, which doesn't // count against the number of frames to be included. // // For example, if Foo() calls Bar(), which in turn calls // GetCurrentOsStackTraceExceptTop(..., 1), Foo() will be included in // the trace but Bar() and GetCurrentOsStackTraceExceptTop() won't. GTEST_API_ std::string GetCurrentOsStackTraceExceptTop( UnitTest* unit_test, int skip_count); // Helpers for suppressing warnings on unreachable code or constant // condition. // Always returns true. GTEST_API_ bool AlwaysTrue(); // Always returns false. inline bool AlwaysFalse() { return !AlwaysTrue(); } // Helper for suppressing false warning from Clang on a const char* // variable declared in a conditional expression always being NULL in // the else branch. struct GTEST_API_ ConstCharPtr { ConstCharPtr(const char* str) : value(str) {} operator bool() const { return true; } const char* value; }; // A simple Linear Congruential Generator for generating random // numbers with a uniform distribution. Unlike rand() and srand(), it // doesn't use global state (and therefore can't interfere with user // code). Unlike rand_r(), it's portable. An LCG isn't very random, // but it's good enough for our purposes. class GTEST_API_ Random { public: static const UInt32 kMaxRange = 1u << 31; explicit Random(UInt32 seed) : state_(seed) {} void Reseed(UInt32 seed) { state_ = seed; } // Generates a random number from [0, range). Crashes if 'range' is // 0 or greater than kMaxRange. UInt32 Generate(UInt32 range); private: UInt32 state_; GTEST_DISALLOW_COPY_AND_ASSIGN_(Random); }; // Defining a variable of type CompileAssertTypesEqual will cause a // compiler error iff T1 and T2 are different types. template struct CompileAssertTypesEqual; template struct CompileAssertTypesEqual { }; // Removes the reference from a type if it is a reference type, // otherwise leaves it unchanged. This is the same as // tr1::remove_reference, which is not widely available yet. template struct RemoveReference { typedef T type; }; // NOLINT template struct RemoveReference { typedef T type; }; // NOLINT // A handy wrapper around RemoveReference that works when the argument // T depends on template parameters. #define GTEST_REMOVE_REFERENCE_(T) \ typename ::testing::internal::RemoveReference::type // Removes const from a type if it is a const type, otherwise leaves // it unchanged. This is the same as tr1::remove_const, which is not // widely available yet. template struct RemoveConst { typedef T type; }; // NOLINT template struct RemoveConst { typedef T type; }; // NOLINT // MSVC 8.0, Sun C++, and IBM XL C++ have a bug which causes the above // definition to fail to remove the const in 'const int[3]' and 'const // char[3][4]'. The following specialization works around the bug. template struct RemoveConst { typedef typename RemoveConst::type type[N]; }; #if defined(_MSC_VER) && _MSC_VER < 1400 // This is the only specialization that allows VC++ 7.1 to remove const in // 'const int[3] and 'const int[3][4]'. However, it causes trouble with GCC // and thus needs to be conditionally compiled. template struct RemoveConst { typedef typename RemoveConst::type type[N]; }; #endif // A handy wrapper around RemoveConst that works when the argument // T depends on template parameters. #define GTEST_REMOVE_CONST_(T) \ typename ::testing::internal::RemoveConst::type // Turns const U&, U&, const U, and U all into U. #define GTEST_REMOVE_REFERENCE_AND_CONST_(T) \ GTEST_REMOVE_CONST_(GTEST_REMOVE_REFERENCE_(T)) // Adds reference to a type if it is not a reference type, // otherwise leaves it unchanged. This is the same as // tr1::add_reference, which is not widely available yet. template struct AddReference { typedef T& type; }; // NOLINT template struct AddReference { typedef T& type; }; // NOLINT // A handy wrapper around AddReference that works when the argument T // depends on template parameters. #define GTEST_ADD_REFERENCE_(T) \ typename ::testing::internal::AddReference::type // Adds a reference to const on top of T as necessary. For example, // it transforms // // char ==> const char& // const char ==> const char& // char& ==> const char& // const char& ==> const char& // // The argument T must depend on some template parameters. #define GTEST_REFERENCE_TO_CONST_(T) \ GTEST_ADD_REFERENCE_(const GTEST_REMOVE_REFERENCE_(T)) // ImplicitlyConvertible::value is a compile-time bool // constant that's true iff type From can be implicitly converted to // type To. template class ImplicitlyConvertible { private: // We need the following helper functions only for their types. // They have no implementations. // MakeFrom() is an expression whose type is From. We cannot simply // use From(), as the type From may not have a public default // constructor. static From MakeFrom(); // These two functions are overloaded. Given an expression // Helper(x), the compiler will pick the first version if x can be // implicitly converted to type To; otherwise it will pick the // second version. // // The first version returns a value of size 1, and the second // version returns a value of size 2. Therefore, by checking the // size of Helper(x), which can be done at compile time, we can tell // which version of Helper() is used, and hence whether x can be // implicitly converted to type To. static char Helper(To); static char (&Helper(...))[2]; // NOLINT // We have to put the 'public' section after the 'private' section, // or MSVC refuses to compile the code. public: // MSVC warns about implicitly converting from double to int for // possible loss of data, so we need to temporarily disable the // warning. #ifdef _MSC_VER # pragma warning(push) // Saves the current warning state. # pragma warning(disable:4244) // Temporarily disables warning 4244. static const bool value = sizeof(Helper(ImplicitlyConvertible::MakeFrom())) == 1; # pragma warning(pop) // Restores the warning state. #elif defined(__BORLANDC__) // C++Builder cannot use member overload resolution during template // instantiation. The simplest workaround is to use its C++0x type traits // functions (C++Builder 2009 and above only). static const bool value = __is_convertible(From, To); #else static const bool value = sizeof(Helper(ImplicitlyConvertible::MakeFrom())) == 1; #endif // _MSV_VER }; template const bool ImplicitlyConvertible::value; // IsAProtocolMessage::value is a compile-time bool constant that's // true iff T is type ProtocolMessage, proto2::Message, or a subclass // of those. template struct IsAProtocolMessage : public bool_constant< ImplicitlyConvertible::value || ImplicitlyConvertible::value> { }; // When the compiler sees expression IsContainerTest(0), if C is an // STL-style container class, the first overload of IsContainerTest // will be viable (since both C::iterator* and C::const_iterator* are // valid types and NULL can be implicitly converted to them). It will // be picked over the second overload as 'int' is a perfect match for // the type of argument 0. If C::iterator or C::const_iterator is not // a valid type, the first overload is not viable, and the second // overload will be picked. Therefore, we can determine whether C is // a container class by checking the type of IsContainerTest(0). // The value of the expression is insignificant. // // Note that we look for both C::iterator and C::const_iterator. The // reason is that C++ injects the name of a class as a member of the // class itself (e.g. you can refer to class iterator as either // 'iterator' or 'iterator::iterator'). If we look for C::iterator // only, for example, we would mistakenly think that a class named // iterator is an STL container. // // Also note that the simpler approach of overloading // IsContainerTest(typename C::const_iterator*) and // IsContainerTest(...) doesn't work with Visual Age C++ and Sun C++. typedef int IsContainer; template IsContainer IsContainerTest(int /* dummy */, typename C::iterator* /* it */ = NULL, typename C::const_iterator* /* const_it */ = NULL) { return 0; } typedef char IsNotContainer; template IsNotContainer IsContainerTest(long /* dummy */) { return '\0'; } // EnableIf::type is void when 'Cond' is true, and // undefined when 'Cond' is false. To use SFINAE to make a function // overload only apply when a particular expression is true, add // "typename EnableIf::type* = 0" as the last parameter. template struct EnableIf; template<> struct EnableIf { typedef void type; }; // NOLINT // Utilities for native arrays. // ArrayEq() compares two k-dimensional native arrays using the // elements' operator==, where k can be any integer >= 0. When k is // 0, ArrayEq() degenerates into comparing a single pair of values. template bool ArrayEq(const T* lhs, size_t size, const U* rhs); // This generic version is used when k is 0. template inline bool ArrayEq(const T& lhs, const U& rhs) { return lhs == rhs; } // This overload is used when k >= 1. template inline bool ArrayEq(const T(&lhs)[N], const U(&rhs)[N]) { return internal::ArrayEq(lhs, N, rhs); } // This helper reduces code bloat. If we instead put its logic inside // the previous ArrayEq() function, arrays with different sizes would // lead to different copies of the template code. template bool ArrayEq(const T* lhs, size_t size, const U* rhs) { for (size_t i = 0; i != size; i++) { if (!internal::ArrayEq(lhs[i], rhs[i])) return false; } return true; } // Finds the first element in the iterator range [begin, end) that // equals elem. Element may be a native array type itself. template Iter ArrayAwareFind(Iter begin, Iter end, const Element& elem) { for (Iter it = begin; it != end; ++it) { if (internal::ArrayEq(*it, elem)) return it; } return end; } // CopyArray() copies a k-dimensional native array using the elements' // operator=, where k can be any integer >= 0. When k is 0, // CopyArray() degenerates into copying a single value. template void CopyArray(const T* from, size_t size, U* to); // This generic version is used when k is 0. template inline void CopyArray(const T& from, U* to) { *to = from; } // This overload is used when k >= 1. template inline void CopyArray(const T(&from)[N], U(*to)[N]) { internal::CopyArray(from, N, *to); } // This helper reduces code bloat. If we instead put its logic inside // the previous CopyArray() function, arrays with different sizes // would lead to different copies of the template code. template void CopyArray(const T* from, size_t size, U* to) { for (size_t i = 0; i != size; i++) { internal::CopyArray(from[i], to + i); } } // The relation between an NativeArray object (see below) and the // native array it represents. enum RelationToSource { kReference, // The NativeArray references the native array. kCopy // The NativeArray makes a copy of the native array and // owns the copy. }; // Adapts a native array to a read-only STL-style container. Instead // of the complete STL container concept, this adaptor only implements // members useful for Google Mock's container matchers. New members // should be added as needed. To simplify the implementation, we only // support Element being a raw type (i.e. having no top-level const or // reference modifier). It's the client's responsibility to satisfy // this requirement. Element can be an array type itself (hence // multi-dimensional arrays are supported). template class NativeArray { public: // STL-style container typedefs. typedef Element value_type; typedef Element* iterator; typedef const Element* const_iterator; // Constructs from a native array. NativeArray(const Element* array, size_t count, RelationToSource relation) { Init(array, count, relation); } // Copy constructor. NativeArray(const NativeArray& rhs) { Init(rhs.array_, rhs.size_, rhs.relation_to_source_); } ~NativeArray() { // Ensures that the user doesn't instantiate NativeArray with a // const or reference type. static_cast(StaticAssertTypeEqHelper()); if (relation_to_source_ == kCopy) delete[] array_; } // STL-style container methods. size_t size() const { return size_; } const_iterator begin() const { return array_; } const_iterator end() const { return array_ + size_; } bool operator==(const NativeArray& rhs) const { return size() == rhs.size() && ArrayEq(begin(), size(), rhs.begin()); } private: // Initializes this object; makes a copy of the input array if // 'relation' is kCopy. void Init(const Element* array, size_t a_size, RelationToSource relation) { if (relation == kReference) { array_ = array; } else { Element* const copy = new Element[a_size]; CopyArray(array, a_size, copy); array_ = copy; } size_ = a_size; relation_to_source_ = relation; } const Element* array_; size_t size_; RelationToSource relation_to_source_; GTEST_DISALLOW_ASSIGN_(NativeArray); }; } // namespace internal } // namespace testing #define GTEST_MESSAGE_AT_(file, line, message, result_type) \ ::testing::internal::AssertHelper(result_type, file, line, message) \ = ::testing::Message() #define GTEST_MESSAGE_(message, result_type) \ GTEST_MESSAGE_AT_(__FILE__, __LINE__, message, result_type) #define GTEST_FATAL_FAILURE_(message) \ return GTEST_MESSAGE_(message, ::testing::TestPartResult::kFatalFailure) #define GTEST_NONFATAL_FAILURE_(message) \ GTEST_MESSAGE_(message, ::testing::TestPartResult::kNonFatalFailure) #define GTEST_SUCCESS_(message) \ GTEST_MESSAGE_(message, ::testing::TestPartResult::kSuccess) // Suppresses MSVC warnings 4072 (unreachable code) for the code following // statement if it returns or throws (or doesn't return or throw in some // situations). #define GTEST_SUPPRESS_UNREACHABLE_CODE_WARNING_BELOW_(statement) \ if (::testing::internal::AlwaysTrue()) { statement; } #define GTEST_TEST_THROW_(statement, expected_exception, fail) \ GTEST_AMBIGUOUS_ELSE_BLOCKER_ \ if (::testing::internal::ConstCharPtr gtest_msg = "") { \ bool gtest_caught_expected = false; \ try { \ GTEST_SUPPRESS_UNREACHABLE_CODE_WARNING_BELOW_(statement); \ } \ catch (expected_exception const&) { \ gtest_caught_expected = true; \ } \ catch (...) { \ gtest_msg.value = \ "Expected: " #statement " throws an exception of type " \ #expected_exception ".\n Actual: it throws a different type."; \ goto GTEST_CONCAT_TOKEN_(gtest_label_testthrow_, __LINE__); \ } \ if (!gtest_caught_expected) { \ gtest_msg.value = \ "Expected: " #statement " throws an exception of type " \ #expected_exception ".\n Actual: it throws nothing."; \ goto GTEST_CONCAT_TOKEN_(gtest_label_testthrow_, __LINE__); \ } \ } else \ GTEST_CONCAT_TOKEN_(gtest_label_testthrow_, __LINE__): \ fail(gtest_msg.value) #define GTEST_TEST_NO_THROW_(statement, fail) \ GTEST_AMBIGUOUS_ELSE_BLOCKER_ \ if (::testing::internal::AlwaysTrue()) { \ try { \ GTEST_SUPPRESS_UNREACHABLE_CODE_WARNING_BELOW_(statement); \ } \ catch (...) { \ goto GTEST_CONCAT_TOKEN_(gtest_label_testnothrow_, __LINE__); \ } \ } else \ GTEST_CONCAT_TOKEN_(gtest_label_testnothrow_, __LINE__): \ fail("Expected: " #statement " doesn't throw an exception.\n" \ " Actual: it throws.") #define GTEST_TEST_ANY_THROW_(statement, fail) \ GTEST_AMBIGUOUS_ELSE_BLOCKER_ \ if (::testing::internal::AlwaysTrue()) { \ bool gtest_caught_any = false; \ try { \ GTEST_SUPPRESS_UNREACHABLE_CODE_WARNING_BELOW_(statement); \ } \ catch (...) { \ gtest_caught_any = true; \ } \ if (!gtest_caught_any) { \ goto GTEST_CONCAT_TOKEN_(gtest_label_testanythrow_, __LINE__); \ } \ } else \ GTEST_CONCAT_TOKEN_(gtest_label_testanythrow_, __LINE__): \ fail("Expected: " #statement " throws an exception.\n" \ " Actual: it doesn't.") // Implements Boolean test assertions such as EXPECT_TRUE. expression can be // either a boolean expression or an AssertionResult. text is a textual // represenation of expression as it was passed into the EXPECT_TRUE. #define GTEST_TEST_BOOLEAN_(expression, text, actual, expected, fail) \ GTEST_AMBIGUOUS_ELSE_BLOCKER_ \ if (const ::testing::AssertionResult gtest_ar_ = \ ::testing::AssertionResult(expression)) \ ; \ else \ fail(::testing::internal::GetBoolAssertionFailureMessage(\ gtest_ar_, text, #actual, #expected).c_str()) #define GTEST_TEST_NO_FATAL_FAILURE_(statement, fail) \ GTEST_AMBIGUOUS_ELSE_BLOCKER_ \ if (::testing::internal::AlwaysTrue()) { \ ::testing::internal::HasNewFatalFailureHelper gtest_fatal_failure_checker; \ GTEST_SUPPRESS_UNREACHABLE_CODE_WARNING_BELOW_(statement); \ if (gtest_fatal_failure_checker.has_new_fatal_failure()) { \ goto GTEST_CONCAT_TOKEN_(gtest_label_testnofatal_, __LINE__); \ } \ } else \ GTEST_CONCAT_TOKEN_(gtest_label_testnofatal_, __LINE__): \ fail("Expected: " #statement " doesn't generate new fatal " \ "failures in the current thread.\n" \ " Actual: it does.") // Expands to the name of the class that implements the given test. #define GTEST_TEST_CLASS_NAME_(test_case_name, test_name) \ test_case_name##_##test_name##_Test // Helper macro for defining tests. #define GTEST_TEST_(test_case_name, test_name, parent_class, parent_id)\ class GTEST_TEST_CLASS_NAME_(test_case_name, test_name) : public parent_class {\ public:\ GTEST_TEST_CLASS_NAME_(test_case_name, test_name)() {}\ private:\ virtual void TestBody();\ static ::testing::TestInfo* const test_info_ GTEST_ATTRIBUTE_UNUSED_;\ GTEST_DISALLOW_COPY_AND_ASSIGN_(\ GTEST_TEST_CLASS_NAME_(test_case_name, test_name));\ };\ \ ::testing::TestInfo* const GTEST_TEST_CLASS_NAME_(test_case_name, test_name)\ ::test_info_ =\ ::testing::internal::MakeAndRegisterTestInfo(\ #test_case_name, #test_name, NULL, NULL, \ (parent_id), \ parent_class::SetUpTestCase, \ parent_class::TearDownTestCase, \ new ::testing::internal::TestFactoryImpl<\ GTEST_TEST_CLASS_NAME_(test_case_name, test_name)>);\ void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::TestBody() #endif // GTEST_INCLUDE_GTEST_INTERNAL_GTEST_INTERNAL_H_ // Copyright 2005, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: wan@google.com (Zhanyong Wan) // // The Google C++ Testing Framework (Google Test) // // This header file defines the public API for death tests. It is // #included by gtest.h so a user doesn't need to include this // directly. #ifndef GTEST_INCLUDE_GTEST_GTEST_DEATH_TEST_H_ #define GTEST_INCLUDE_GTEST_GTEST_DEATH_TEST_H_ // Copyright 2005, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Authors: wan@google.com (Zhanyong Wan), eefacm@gmail.com (Sean Mcafee) // // The Google C++ Testing Framework (Google Test) // // This header file defines internal utilities needed for implementing // death tests. They are subject to change without notice. #ifndef GTEST_INCLUDE_GTEST_INTERNAL_GTEST_DEATH_TEST_INTERNAL_H_ #define GTEST_INCLUDE_GTEST_INTERNAL_GTEST_DEATH_TEST_INTERNAL_H_ #include namespace testing { namespace internal { GTEST_DECLARE_string_(internal_run_death_test); // Names of the flags (needed for parsing Google Test flags). const char kDeathTestStyleFlag[] = "death_test_style"; const char kDeathTestUseFork[] = "death_test_use_fork"; const char kInternalRunDeathTestFlag[] = "internal_run_death_test"; #if GTEST_HAS_DEATH_TEST // DeathTest is a class that hides much of the complexity of the // GTEST_DEATH_TEST_ macro. It is abstract; its static Create method // returns a concrete class that depends on the prevailing death test // style, as defined by the --gtest_death_test_style and/or // --gtest_internal_run_death_test flags. // In describing the results of death tests, these terms are used with // the corresponding definitions: // // exit status: The integer exit information in the format specified // by wait(2) // exit code: The integer code passed to exit(3), _exit(2), or // returned from main() class GTEST_API_ DeathTest { public: // Create returns false if there was an error determining the // appropriate action to take for the current death test; for example, // if the gtest_death_test_style flag is set to an invalid value. // The LastMessage method will return a more detailed message in that // case. Otherwise, the DeathTest pointer pointed to by the "test" // argument is set. If the death test should be skipped, the pointer // is set to NULL; otherwise, it is set to the address of a new concrete // DeathTest object that controls the execution of the current test. static bool Create(const char* statement, const RE* regex, const char* file, int line, DeathTest** test); DeathTest(); virtual ~DeathTest() { } // A helper class that aborts a death test when it's deleted. class ReturnSentinel { public: explicit ReturnSentinel(DeathTest* test) : test_(test) { } ~ReturnSentinel() { test_->Abort(TEST_ENCOUNTERED_RETURN_STATEMENT); } private: DeathTest* const test_; GTEST_DISALLOW_COPY_AND_ASSIGN_(ReturnSentinel); } GTEST_ATTRIBUTE_UNUSED_; // An enumeration of possible roles that may be taken when a death // test is encountered. EXECUTE means that the death test logic should // be executed immediately. OVERSEE means that the program should prepare // the appropriate environment for a child process to execute the death // test, then wait for it to complete. enum TestRole { OVERSEE_TEST, EXECUTE_TEST }; // An enumeration of the three reasons that a test might be aborted. enum AbortReason { TEST_ENCOUNTERED_RETURN_STATEMENT, TEST_THREW_EXCEPTION, TEST_DID_NOT_DIE }; // Assumes one of the above roles. virtual TestRole AssumeRole() = 0; // Waits for the death test to finish and returns its status. virtual int Wait() = 0; // Returns true if the death test passed; that is, the test process // exited during the test, its exit status matches a user-supplied // predicate, and its stderr output matches a user-supplied regular // expression. // The user-supplied predicate may be a macro expression rather // than a function pointer or functor, or else Wait and Passed could // be combined. virtual bool Passed(bool exit_status_ok) = 0; // Signals that the death test did not die as expected. virtual void Abort(AbortReason reason) = 0; // Returns a human-readable outcome message regarding the outcome of // the last death test. static const char* LastMessage(); static void set_last_death_test_message(const std::string& message); private: // A string containing a description of the outcome of the last death test. static std::string last_death_test_message_; GTEST_DISALLOW_COPY_AND_ASSIGN_(DeathTest); }; // Factory interface for death tests. May be mocked out for testing. class DeathTestFactory { public: virtual ~DeathTestFactory() { } virtual bool Create(const char* statement, const RE* regex, const char* file, int line, DeathTest** test) = 0; }; // A concrete DeathTestFactory implementation for normal use. class DefaultDeathTestFactory : public DeathTestFactory { public: virtual bool Create(const char* statement, const RE* regex, const char* file, int line, DeathTest** test); }; // Returns true if exit_status describes a process that was terminated // by a signal, or exited normally with a nonzero exit code. GTEST_API_ bool ExitedUnsuccessfully(int exit_status); // Traps C++ exceptions escaping statement and reports them as test // failures. Note that trapping SEH exceptions is not implemented here. # if GTEST_HAS_EXCEPTIONS # define GTEST_EXECUTE_DEATH_TEST_STATEMENT_(statement, death_test) \ try { \ GTEST_SUPPRESS_UNREACHABLE_CODE_WARNING_BELOW_(statement); \ } catch (const ::std::exception& gtest_exception) { \ fprintf(\ stderr, \ "\n%s: Caught std::exception-derived exception escaping the " \ "death test statement. Exception message: %s\n", \ ::testing::internal::FormatFileLocation(__FILE__, __LINE__).c_str(), \ gtest_exception.what()); \ fflush(stderr); \ death_test->Abort(::testing::internal::DeathTest::TEST_THREW_EXCEPTION); \ } catch (...) { \ death_test->Abort(::testing::internal::DeathTest::TEST_THREW_EXCEPTION); \ } # else # define GTEST_EXECUTE_DEATH_TEST_STATEMENT_(statement, death_test) \ GTEST_SUPPRESS_UNREACHABLE_CODE_WARNING_BELOW_(statement) # endif // This macro is for implementing ASSERT_DEATH*, EXPECT_DEATH*, // ASSERT_EXIT*, and EXPECT_EXIT*. # define GTEST_DEATH_TEST_(statement, predicate, regex, fail) \ GTEST_AMBIGUOUS_ELSE_BLOCKER_ \ if (::testing::internal::AlwaysTrue()) { \ const ::testing::internal::RE& gtest_regex = (regex); \ ::testing::internal::DeathTest* gtest_dt; \ if (!::testing::internal::DeathTest::Create(#statement, >est_regex, \ __FILE__, __LINE__, >est_dt)) { \ goto GTEST_CONCAT_TOKEN_(gtest_label_, __LINE__); \ } \ if (gtest_dt != NULL) { \ ::testing::internal::scoped_ptr< ::testing::internal::DeathTest> \ gtest_dt_ptr(gtest_dt); \ switch (gtest_dt->AssumeRole()) { \ case ::testing::internal::DeathTest::OVERSEE_TEST: \ if (!gtest_dt->Passed(predicate(gtest_dt->Wait()))) { \ goto GTEST_CONCAT_TOKEN_(gtest_label_, __LINE__); \ } \ break; \ case ::testing::internal::DeathTest::EXECUTE_TEST: { \ ::testing::internal::DeathTest::ReturnSentinel \ gtest_sentinel(gtest_dt); \ GTEST_EXECUTE_DEATH_TEST_STATEMENT_(statement, gtest_dt); \ gtest_dt->Abort(::testing::internal::DeathTest::TEST_DID_NOT_DIE); \ break; \ } \ default: \ break; \ } \ } \ } else \ GTEST_CONCAT_TOKEN_(gtest_label_, __LINE__): \ fail(::testing::internal::DeathTest::LastMessage()) // The symbol "fail" here expands to something into which a message // can be streamed. // This macro is for implementing ASSERT/EXPECT_DEBUG_DEATH when compiled in // NDEBUG mode. In this case we need the statements to be executed, the regex is // ignored, and the macro must accept a streamed message even though the message // is never printed. # define GTEST_EXECUTE_STATEMENT_(statement, regex) \ GTEST_AMBIGUOUS_ELSE_BLOCKER_ \ if (::testing::internal::AlwaysTrue()) { \ GTEST_SUPPRESS_UNREACHABLE_CODE_WARNING_BELOW_(statement); \ } else \ ::testing::Message() // A class representing the parsed contents of the // --gtest_internal_run_death_test flag, as it existed when // RUN_ALL_TESTS was called. class InternalRunDeathTestFlag { public: InternalRunDeathTestFlag(const std::string& a_file, int a_line, int an_index, int a_write_fd) : file_(a_file), line_(a_line), index_(an_index), write_fd_(a_write_fd) {} ~InternalRunDeathTestFlag() { if (write_fd_ >= 0) posix::Close(write_fd_); } const std::string& file() const { return file_; } int line() const { return line_; } int index() const { return index_; } int write_fd() const { return write_fd_; } private: std::string file_; int line_; int index_; int write_fd_; GTEST_DISALLOW_COPY_AND_ASSIGN_(InternalRunDeathTestFlag); }; // Returns a newly created InternalRunDeathTestFlag object with fields // initialized from the GTEST_FLAG(internal_run_death_test) flag if // the flag is specified; otherwise returns NULL. InternalRunDeathTestFlag* ParseInternalRunDeathTestFlag(); #else // GTEST_HAS_DEATH_TEST // This macro is used for implementing macros such as // EXPECT_DEATH_IF_SUPPORTED and ASSERT_DEATH_IF_SUPPORTED on systems where // death tests are not supported. Those macros must compile on such systems // iff EXPECT_DEATH and ASSERT_DEATH compile with the same parameters on // systems that support death tests. This allows one to write such a macro // on a system that does not support death tests and be sure that it will // compile on a death-test supporting system. // // Parameters: // statement - A statement that a macro such as EXPECT_DEATH would test // for program termination. This macro has to make sure this // statement is compiled but not executed, to ensure that // EXPECT_DEATH_IF_SUPPORTED compiles with a certain // parameter iff EXPECT_DEATH compiles with it. // regex - A regex that a macro such as EXPECT_DEATH would use to test // the output of statement. This parameter has to be // compiled but not evaluated by this macro, to ensure that // this macro only accepts expressions that a macro such as // EXPECT_DEATH would accept. // terminator - Must be an empty statement for EXPECT_DEATH_IF_SUPPORTED // and a return statement for ASSERT_DEATH_IF_SUPPORTED. // This ensures that ASSERT_DEATH_IF_SUPPORTED will not // compile inside functions where ASSERT_DEATH doesn't // compile. // // The branch that has an always false condition is used to ensure that // statement and regex are compiled (and thus syntactically correct) but // never executed. The unreachable code macro protects the terminator // statement from generating an 'unreachable code' warning in case // statement unconditionally returns or throws. The Message constructor at // the end allows the syntax of streaming additional messages into the // macro, for compilational compatibility with EXPECT_DEATH/ASSERT_DEATH. # define GTEST_UNSUPPORTED_DEATH_TEST_(statement, regex, terminator) \ GTEST_AMBIGUOUS_ELSE_BLOCKER_ \ if (::testing::internal::AlwaysTrue()) { \ GTEST_LOG_(WARNING) \ << "Death tests are not supported on this platform.\n" \ << "Statement '" #statement "' cannot be verified."; \ } else if (::testing::internal::AlwaysFalse()) { \ ::testing::internal::RE::PartialMatch(".*", (regex)); \ GTEST_SUPPRESS_UNREACHABLE_CODE_WARNING_BELOW_(statement); \ terminator; \ } else \ ::testing::Message() #endif // GTEST_HAS_DEATH_TEST } // namespace internal } // namespace testing #endif // GTEST_INCLUDE_GTEST_INTERNAL_GTEST_DEATH_TEST_INTERNAL_H_ namespace testing { // This flag controls the style of death tests. Valid values are "threadsafe", // meaning that the death test child process will re-execute the test binary // from the start, running only a single death test, or "fast", // meaning that the child process will execute the test logic immediately // after forking. GTEST_DECLARE_string_(death_test_style); #if GTEST_HAS_DEATH_TEST namespace internal { // Returns a Boolean value indicating whether the caller is currently // executing in the context of the death test child process. Tools such as // Valgrind heap checkers may need this to modify their behavior in death // tests. IMPORTANT: This is an internal utility. Using it may break the // implementation of death tests. User code MUST NOT use it. GTEST_API_ bool InDeathTestChild(); } // namespace internal // The following macros are useful for writing death tests. // Here's what happens when an ASSERT_DEATH* or EXPECT_DEATH* is // executed: // // 1. It generates a warning if there is more than one active // thread. This is because it's safe to fork() or clone() only // when there is a single thread. // // 2. The parent process clone()s a sub-process and runs the death // test in it; the sub-process exits with code 0 at the end of the // death test, if it hasn't exited already. // // 3. The parent process waits for the sub-process to terminate. // // 4. The parent process checks the exit code and error message of // the sub-process. // // Examples: // // ASSERT_DEATH(server.SendMessage(56, "Hello"), "Invalid port number"); // for (int i = 0; i < 5; i++) { // EXPECT_DEATH(server.ProcessRequest(i), // "Invalid request .* in ProcessRequest()") // << "Failed to die on request " << i; // } // // ASSERT_EXIT(server.ExitNow(), ::testing::ExitedWithCode(0), "Exiting"); // // bool KilledBySIGHUP(int exit_code) { // return WIFSIGNALED(exit_code) && WTERMSIG(exit_code) == SIGHUP; // } // // ASSERT_EXIT(client.HangUpServer(), KilledBySIGHUP, "Hanging up!"); // // On the regular expressions used in death tests: // // On POSIX-compliant systems (*nix), we use the library, // which uses the POSIX extended regex syntax. // // On other platforms (e.g. Windows), we only support a simple regex // syntax implemented as part of Google Test. This limited // implementation should be enough most of the time when writing // death tests; though it lacks many features you can find in PCRE // or POSIX extended regex syntax. For example, we don't support // union ("x|y"), grouping ("(xy)"), brackets ("[xy]"), and // repetition count ("x{5,7}"), among others. // // Below is the syntax that we do support. We chose it to be a // subset of both PCRE and POSIX extended regex, so it's easy to // learn wherever you come from. In the following: 'A' denotes a // literal character, period (.), or a single \\ escape sequence; // 'x' and 'y' denote regular expressions; 'm' and 'n' are for // natural numbers. // // c matches any literal character c // \\d matches any decimal digit // \\D matches any character that's not a decimal digit // \\f matches \f // \\n matches \n // \\r matches \r // \\s matches any ASCII whitespace, including \n // \\S matches any character that's not a whitespace // \\t matches \t // \\v matches \v // \\w matches any letter, _, or decimal digit // \\W matches any character that \\w doesn't match // \\c matches any literal character c, which must be a punctuation // . matches any single character except \n // A? matches 0 or 1 occurrences of A // A* matches 0 or many occurrences of A // A+ matches 1 or many occurrences of A // ^ matches the beginning of a string (not that of each line) // $ matches the end of a string (not that of each line) // xy matches x followed by y // // If you accidentally use PCRE or POSIX extended regex features // not implemented by us, you will get a run-time failure. In that // case, please try to rewrite your regular expression within the // above syntax. // // This implementation is *not* meant to be as highly tuned or robust // as a compiled regex library, but should perform well enough for a // death test, which already incurs significant overhead by launching // a child process. // // Known caveats: // // A "threadsafe" style death test obtains the path to the test // program from argv[0] and re-executes it in the sub-process. For // simplicity, the current implementation doesn't search the PATH // when launching the sub-process. This means that the user must // invoke the test program via a path that contains at least one // path separator (e.g. path/to/foo_test and // /absolute/path/to/bar_test are fine, but foo_test is not). This // is rarely a problem as people usually don't put the test binary // directory in PATH. // // TODO(wan@google.com): make thread-safe death tests search the PATH. // Asserts that a given statement causes the program to exit, with an // integer exit status that satisfies predicate, and emitting error output // that matches regex. # define ASSERT_EXIT(statement, predicate, regex) \ GTEST_DEATH_TEST_(statement, predicate, regex, GTEST_FATAL_FAILURE_) // Like ASSERT_EXIT, but continues on to successive tests in the // test case, if any: # define EXPECT_EXIT(statement, predicate, regex) \ GTEST_DEATH_TEST_(statement, predicate, regex, GTEST_NONFATAL_FAILURE_) // Asserts that a given statement causes the program to exit, either by // explicitly exiting with a nonzero exit code or being killed by a // signal, and emitting error output that matches regex. # define ASSERT_DEATH(statement, regex) \ ASSERT_EXIT(statement, ::testing::internal::ExitedUnsuccessfully, regex) // Like ASSERT_DEATH, but continues on to successive tests in the // test case, if any: # define EXPECT_DEATH(statement, regex) \ EXPECT_EXIT(statement, ::testing::internal::ExitedUnsuccessfully, regex) // Two predicate classes that can be used in {ASSERT,EXPECT}_EXIT*: // Tests that an exit code describes a normal exit with a given exit code. class GTEST_API_ ExitedWithCode { public: explicit ExitedWithCode(int exit_code); bool operator()(int exit_status) const; private: // No implementation - assignment is unsupported. void operator=(const ExitedWithCode& other); const int exit_code_; }; # if !GTEST_OS_WINDOWS // Tests that an exit code describes an exit due to termination by a // given signal. class GTEST_API_ KilledBySignal { public: explicit KilledBySignal(int signum); bool operator()(int exit_status) const; private: const int signum_; }; # endif // !GTEST_OS_WINDOWS // EXPECT_DEBUG_DEATH asserts that the given statements die in debug mode. // The death testing framework causes this to have interesting semantics, // since the sideeffects of the call are only visible in opt mode, and not // in debug mode. // // In practice, this can be used to test functions that utilize the // LOG(DFATAL) macro using the following style: // // int DieInDebugOr12(int* sideeffect) { // if (sideeffect) { // *sideeffect = 12; // } // LOG(DFATAL) << "death"; // return 12; // } // // TEST(TestCase, TestDieOr12WorksInDgbAndOpt) { // int sideeffect = 0; // // Only asserts in dbg. // EXPECT_DEBUG_DEATH(DieInDebugOr12(&sideeffect), "death"); // // #ifdef NDEBUG // // opt-mode has sideeffect visible. // EXPECT_EQ(12, sideeffect); // #else // // dbg-mode no visible sideeffect. // EXPECT_EQ(0, sideeffect); // #endif // } // // This will assert that DieInDebugReturn12InOpt() crashes in debug // mode, usually due to a DCHECK or LOG(DFATAL), but returns the // appropriate fallback value (12 in this case) in opt mode. If you // need to test that a function has appropriate side-effects in opt // mode, include assertions against the side-effects. A general // pattern for this is: // // EXPECT_DEBUG_DEATH({ // // Side-effects here will have an effect after this statement in // // opt mode, but none in debug mode. // EXPECT_EQ(12, DieInDebugOr12(&sideeffect)); // }, "death"); // # ifdef NDEBUG # define EXPECT_DEBUG_DEATH(statement, regex) \ GTEST_EXECUTE_STATEMENT_(statement, regex) # define ASSERT_DEBUG_DEATH(statement, regex) \ GTEST_EXECUTE_STATEMENT_(statement, regex) # else # define EXPECT_DEBUG_DEATH(statement, regex) \ EXPECT_DEATH(statement, regex) # define ASSERT_DEBUG_DEATH(statement, regex) \ ASSERT_DEATH(statement, regex) # endif // NDEBUG for EXPECT_DEBUG_DEATH #endif // GTEST_HAS_DEATH_TEST // EXPECT_DEATH_IF_SUPPORTED(statement, regex) and // ASSERT_DEATH_IF_SUPPORTED(statement, regex) expand to real death tests if // death tests are supported; otherwise they just issue a warning. This is // useful when you are combining death test assertions with normal test // assertions in one test. #if GTEST_HAS_DEATH_TEST # define EXPECT_DEATH_IF_SUPPORTED(statement, regex) \ EXPECT_DEATH(statement, regex) # define ASSERT_DEATH_IF_SUPPORTED(statement, regex) \ ASSERT_DEATH(statement, regex) #else # define EXPECT_DEATH_IF_SUPPORTED(statement, regex) \ GTEST_UNSUPPORTED_DEATH_TEST_(statement, regex, ) # define ASSERT_DEATH_IF_SUPPORTED(statement, regex) \ GTEST_UNSUPPORTED_DEATH_TEST_(statement, regex, return) #endif } // namespace testing #endif // GTEST_INCLUDE_GTEST_GTEST_DEATH_TEST_H_ // This file was GENERATED by command: // pump.py gtest-param-test.h.pump // DO NOT EDIT BY HAND!!! // Copyright 2008, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Authors: vladl@google.com (Vlad Losev) // // Macros and functions for implementing parameterized tests // in Google C++ Testing Framework (Google Test) // // This file is generated by a SCRIPT. DO NOT EDIT BY HAND! // #ifndef GTEST_INCLUDE_GTEST_GTEST_PARAM_TEST_H_ #define GTEST_INCLUDE_GTEST_GTEST_PARAM_TEST_H_ // Value-parameterized tests allow you to test your code with different // parameters without writing multiple copies of the same test. // // Here is how you use value-parameterized tests: #if 0 // To write value-parameterized tests, first you should define a fixture // class. It is usually derived from testing::TestWithParam (see below for // another inheritance scheme that's sometimes useful in more complicated // class hierarchies), where the type of your parameter values. // TestWithParam is itself derived from testing::Test. T can be any // copyable type. If it's a raw pointer, you are responsible for managing the // lifespan of the pointed values. class FooTest : public ::testing::TestWithParam { // You can implement all the usual class fixture members here. }; // Then, use the TEST_P macro to define as many parameterized tests // for this fixture as you want. The _P suffix is for "parameterized" // or "pattern", whichever you prefer to think. TEST_P(FooTest, DoesBlah) { // Inside a test, access the test parameter with the GetParam() method // of the TestWithParam class: EXPECT_TRUE(foo.Blah(GetParam())); ... } TEST_P(FooTest, HasBlahBlah) { ... } // Finally, you can use INSTANTIATE_TEST_CASE_P to instantiate the test // case with any set of parameters you want. Google Test defines a number // of functions for generating test parameters. They return what we call // (surprise!) parameter generators. Here is a summary of them, which // are all in the testing namespace: // // // Range(begin, end [, step]) - Yields values {begin, begin+step, // begin+step+step, ...}. The values do not // include end. step defaults to 1. // Values(v1, v2, ..., vN) - Yields values {v1, v2, ..., vN}. // ValuesIn(container) - Yields values from a C-style array, an STL // ValuesIn(begin,end) container, or an iterator range [begin, end). // Bool() - Yields sequence {false, true}. // Combine(g1, g2, ..., gN) - Yields all combinations (the Cartesian product // for the math savvy) of the values generated // by the N generators. // // For more details, see comments at the definitions of these functions below // in this file. // // The following statement will instantiate tests from the FooTest test case // each with parameter values "meeny", "miny", and "moe". INSTANTIATE_TEST_CASE_P(InstantiationName, FooTest, Values("meeny", "miny", "moe")); // To distinguish different instances of the pattern, (yes, you // can instantiate it more then once) the first argument to the // INSTANTIATE_TEST_CASE_P macro is a prefix that will be added to the // actual test case name. Remember to pick unique prefixes for different // instantiations. The tests from the instantiation above will have // these names: // // * InstantiationName/FooTest.DoesBlah/0 for "meeny" // * InstantiationName/FooTest.DoesBlah/1 for "miny" // * InstantiationName/FooTest.DoesBlah/2 for "moe" // * InstantiationName/FooTest.HasBlahBlah/0 for "meeny" // * InstantiationName/FooTest.HasBlahBlah/1 for "miny" // * InstantiationName/FooTest.HasBlahBlah/2 for "moe" // // You can use these names in --gtest_filter. // // This statement will instantiate all tests from FooTest again, each // with parameter values "cat" and "dog": const char* pets[] = {"cat", "dog"}; INSTANTIATE_TEST_CASE_P(AnotherInstantiationName, FooTest, ValuesIn(pets)); // The tests from the instantiation above will have these names: // // * AnotherInstantiationName/FooTest.DoesBlah/0 for "cat" // * AnotherInstantiationName/FooTest.DoesBlah/1 for "dog" // * AnotherInstantiationName/FooTest.HasBlahBlah/0 for "cat" // * AnotherInstantiationName/FooTest.HasBlahBlah/1 for "dog" // // Please note that INSTANTIATE_TEST_CASE_P will instantiate all tests // in the given test case, whether their definitions come before or // AFTER the INSTANTIATE_TEST_CASE_P statement. // // Please also note that generator expressions (including parameters to the // generators) are evaluated in InitGoogleTest(), after main() has started. // This allows the user on one hand, to adjust generator parameters in order // to dynamically determine a set of tests to run and on the other hand, // give the user a chance to inspect the generated tests with Google Test // reflection API before RUN_ALL_TESTS() is executed. // // You can see samples/sample7_unittest.cc and samples/sample8_unittest.cc // for more examples. // // In the future, we plan to publish the API for defining new parameter // generators. But for now this interface remains part of the internal // implementation and is subject to change. // // // A parameterized test fixture must be derived from testing::Test and from // testing::WithParamInterface, where T is the type of the parameter // values. Inheriting from TestWithParam satisfies that requirement because // TestWithParam inherits from both Test and WithParamInterface. In more // complicated hierarchies, however, it is occasionally useful to inherit // separately from Test and WithParamInterface. For example: class BaseTest : public ::testing::Test { // You can inherit all the usual members for a non-parameterized test // fixture here. }; class DerivedTest : public BaseTest, public ::testing::WithParamInterface { // The usual test fixture members go here too. }; TEST_F(BaseTest, HasFoo) { // This is an ordinary non-parameterized test. } TEST_P(DerivedTest, DoesBlah) { // GetParam works just the same here as if you inherit from TestWithParam. EXPECT_TRUE(foo.Blah(GetParam())); } #endif // 0 #if !GTEST_OS_SYMBIAN # include #endif // scripts/fuse_gtest.py depends on gtest's own header being #included // *unconditionally*. Therefore these #includes cannot be moved // inside #if GTEST_HAS_PARAM_TEST. // Copyright 2008 Google Inc. // All Rights Reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: vladl@google.com (Vlad Losev) // Type and function utilities for implementing parameterized tests. #ifndef GTEST_INCLUDE_GTEST_INTERNAL_GTEST_PARAM_UTIL_H_ #define GTEST_INCLUDE_GTEST_INTERNAL_GTEST_PARAM_UTIL_H_ #include #include #include // scripts/fuse_gtest.py depends on gtest's own header being #included // *unconditionally*. Therefore these #includes cannot be moved // inside #if GTEST_HAS_PARAM_TEST. // Copyright 2003 Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Authors: Dan Egnor (egnor@google.com) // // A "smart" pointer type with reference tracking. Every pointer to a // particular object is kept on a circular linked list. When the last pointer // to an object is destroyed or reassigned, the object is deleted. // // Used properly, this deletes the object when the last reference goes away. // There are several caveats: // - Like all reference counting schemes, cycles lead to leaks. // - Each smart pointer is actually two pointers (8 bytes instead of 4). // - Every time a pointer is assigned, the entire list of pointers to that // object is traversed. This class is therefore NOT SUITABLE when there // will often be more than two or three pointers to a particular object. // - References are only tracked as long as linked_ptr<> objects are copied. // If a linked_ptr<> is converted to a raw pointer and back, BAD THINGS // will happen (double deletion). // // A good use of this class is storing object references in STL containers. // You can safely put linked_ptr<> in a vector<>. // Other uses may not be as good. // // Note: If you use an incomplete type with linked_ptr<>, the class // *containing* linked_ptr<> must have a constructor and destructor (even // if they do nothing!). // // Bill Gibbons suggested we use something like this. // // Thread Safety: // Unlike other linked_ptr implementations, in this implementation // a linked_ptr object is thread-safe in the sense that: // - it's safe to copy linked_ptr objects concurrently, // - it's safe to copy *from* a linked_ptr and read its underlying // raw pointer (e.g. via get()) concurrently, and // - it's safe to write to two linked_ptrs that point to the same // shared object concurrently. // TODO(wan@google.com): rename this to safe_linked_ptr to avoid // confusion with normal linked_ptr. #ifndef GTEST_INCLUDE_GTEST_INTERNAL_GTEST_LINKED_PTR_H_ #define GTEST_INCLUDE_GTEST_INTERNAL_GTEST_LINKED_PTR_H_ #include #include namespace testing { namespace internal { // Protects copying of all linked_ptr objects. GTEST_API_ GTEST_DECLARE_STATIC_MUTEX_(g_linked_ptr_mutex); // This is used internally by all instances of linked_ptr<>. It needs to be // a non-template class because different types of linked_ptr<> can refer to // the same object (linked_ptr(obj) vs linked_ptr(obj)). // So, it needs to be possible for different types of linked_ptr to participate // in the same circular linked list, so we need a single class type here. // // DO NOT USE THIS CLASS DIRECTLY YOURSELF. Use linked_ptr. class linked_ptr_internal { public: // Create a new circle that includes only this instance. void join_new() { next_ = this; } // Many linked_ptr operations may change p.link_ for some linked_ptr // variable p in the same circle as this object. Therefore we need // to prevent two such operations from occurring concurrently. // // Note that different types of linked_ptr objects can coexist in a // circle (e.g. linked_ptr, linked_ptr, and // linked_ptr). Therefore we must use a single mutex to // protect all linked_ptr objects. This can create serious // contention in production code, but is acceptable in a testing // framework. // Join an existing circle. void join(linked_ptr_internal const* ptr) GTEST_LOCK_EXCLUDED_(g_linked_ptr_mutex) { MutexLock lock(&g_linked_ptr_mutex); linked_ptr_internal const* p = ptr; while (p->next_ != ptr) p = p->next_; p->next_ = this; next_ = ptr; } // Leave whatever circle we're part of. Returns true if we were the // last member of the circle. Once this is done, you can join() another. bool depart() GTEST_LOCK_EXCLUDED_(g_linked_ptr_mutex) { MutexLock lock(&g_linked_ptr_mutex); if (next_ == this) return true; linked_ptr_internal const* p = next_; while (p->next_ != this) p = p->next_; p->next_ = next_; return false; } private: mutable linked_ptr_internal const* next_; }; template class linked_ptr { public: typedef T element_type; // Take over ownership of a raw pointer. This should happen as soon as // possible after the object is created. explicit linked_ptr(T* ptr = NULL) { capture(ptr); } ~linked_ptr() { depart(); } // Copy an existing linked_ptr<>, adding ourselves to the list of references. template linked_ptr(linked_ptr const& ptr) { copy(&ptr); } linked_ptr(linked_ptr const& ptr) { // NOLINT assert(&ptr != this); copy(&ptr); } // Assignment releases the old value and acquires the new. template linked_ptr& operator=(linked_ptr const& ptr) { depart(); copy(&ptr); return *this; } linked_ptr& operator=(linked_ptr const& ptr) { if (&ptr != this) { depart(); copy(&ptr); } return *this; } // Smart pointer members. void reset(T* ptr = NULL) { depart(); capture(ptr); } T* get() const { return value_; } T* operator->() const { return value_; } T& operator*() const { return *value_; } bool operator==(T* p) const { return value_ == p; } bool operator!=(T* p) const { return value_ != p; } template bool operator==(linked_ptr const& ptr) const { return value_ == ptr.get(); } template bool operator!=(linked_ptr const& ptr) const { return value_ != ptr.get(); } private: template friend class linked_ptr; T* value_; linked_ptr_internal link_; void depart() { if (link_.depart()) delete value_; } void capture(T* ptr) { value_ = ptr; link_.join_new(); } template void copy(linked_ptr const* ptr) { value_ = ptr->get(); if (value_) link_.join(&ptr->link_); else link_.join_new(); } }; template inline bool operator==(T* ptr, const linked_ptr& x) { return ptr == x.get(); } template inline bool operator!=(T* ptr, const linked_ptr& x) { return ptr != x.get(); } // A function to convert T* into linked_ptr // Doing e.g. make_linked_ptr(new FooBarBaz(arg)) is a shorter notation // for linked_ptr >(new FooBarBaz(arg)) template linked_ptr make_linked_ptr(T* ptr) { return linked_ptr(ptr); } } // namespace internal } // namespace testing #endif // GTEST_INCLUDE_GTEST_INTERNAL_GTEST_LINKED_PTR_H_ // Copyright 2007, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: wan@google.com (Zhanyong Wan) // Google Test - The Google C++ Testing Framework // // This file implements a universal value printer that can print a // value of any type T: // // void ::testing::internal::UniversalPrinter::Print(value, ostream_ptr); // // A user can teach this function how to print a class type T by // defining either operator<<() or PrintTo() in the namespace that // defines T. More specifically, the FIRST defined function in the // following list will be used (assuming T is defined in namespace // foo): // // 1. foo::PrintTo(const T&, ostream*) // 2. operator<<(ostream&, const T&) defined in either foo or the // global namespace. // // If none of the above is defined, it will print the debug string of // the value if it is a protocol buffer, or print the raw bytes in the // value otherwise. // // To aid debugging: when T is a reference type, the address of the // value is also printed; when T is a (const) char pointer, both the // pointer value and the NUL-terminated string it points to are // printed. // // We also provide some convenient wrappers: // // // Prints a value to a string. For a (const or not) char // // pointer, the NUL-terminated string (but not the pointer) is // // printed. // std::string ::testing::PrintToString(const T& value); // // // Prints a value tersely: for a reference type, the referenced // // value (but not the address) is printed; for a (const or not) char // // pointer, the NUL-terminated string (but not the pointer) is // // printed. // void ::testing::internal::UniversalTersePrint(const T& value, ostream*); // // // Prints value using the type inferred by the compiler. The difference // // from UniversalTersePrint() is that this function prints both the // // pointer and the NUL-terminated string for a (const or not) char pointer. // void ::testing::internal::UniversalPrint(const T& value, ostream*); // // // Prints the fields of a tuple tersely to a string vector, one // // element for each field. Tuple support must be enabled in // // gtest-port.h. // std::vector UniversalTersePrintTupleFieldsToStrings( // const Tuple& value); // // Known limitation: // // The print primitives print the elements of an STL-style container // using the compiler-inferred type of *iter where iter is a // const_iterator of the container. When const_iterator is an input // iterator but not a forward iterator, this inferred type may not // match value_type, and the print output may be incorrect. In // practice, this is rarely a problem as for most containers // const_iterator is a forward iterator. We'll fix this if there's an // actual need for it. Note that this fix cannot rely on value_type // being defined as many user-defined container types don't have // value_type. #ifndef GTEST_INCLUDE_GTEST_GTEST_PRINTERS_H_ #define GTEST_INCLUDE_GTEST_GTEST_PRINTERS_H_ #include // NOLINT #include #include #include #include namespace testing { // Definitions in the 'internal' and 'internal2' name spaces are // subject to change without notice. DO NOT USE THEM IN USER CODE! namespace internal2 { // Prints the given number of bytes in the given object to the given // ostream. GTEST_API_ void PrintBytesInObjectTo(const unsigned char* obj_bytes, size_t count, ::std::ostream* os); // For selecting which printer to use when a given type has neither << // nor PrintTo(). enum TypeKind { kProtobuf, // a protobuf type kConvertibleToInteger, // a type implicitly convertible to BiggestInt // (e.g. a named or unnamed enum type) kOtherType // anything else }; // TypeWithoutFormatter::PrintValue(value, os) is called // by the universal printer to print a value of type T when neither // operator<< nor PrintTo() is defined for T, where kTypeKind is the // "kind" of T as defined by enum TypeKind. template class TypeWithoutFormatter { public: // This default version is called when kTypeKind is kOtherType. static void PrintValue(const T& value, ::std::ostream* os) { PrintBytesInObjectTo(reinterpret_cast(&value), sizeof(value), os); } }; // We print a protobuf using its ShortDebugString() when the string // doesn't exceed this many characters; otherwise we print it using // DebugString() for better readability. const size_t kProtobufOneLinerMaxLength = 50; template class TypeWithoutFormatter { public: static void PrintValue(const T& value, ::std::ostream* os) { const ::testing::internal::string short_str = value.ShortDebugString(); const ::testing::internal::string pretty_str = short_str.length() <= kProtobufOneLinerMaxLength ? short_str : ("\n" + value.DebugString()); *os << ("<" + pretty_str + ">"); } }; template class TypeWithoutFormatter { public: // Since T has no << operator or PrintTo() but can be implicitly // converted to BiggestInt, we print it as a BiggestInt. // // Most likely T is an enum type (either named or unnamed), in which // case printing it as an integer is the desired behavior. In case // T is not an enum, printing it as an integer is the best we can do // given that it has no user-defined printer. static void PrintValue(const T& value, ::std::ostream* os) { const internal::BiggestInt kBigInt = value; *os << kBigInt; } }; // Prints the given value to the given ostream. If the value is a // protocol message, its debug string is printed; if it's an enum or // of a type implicitly convertible to BiggestInt, it's printed as an // integer; otherwise the bytes in the value are printed. This is // what UniversalPrinter::Print() does when it knows nothing about // type T and T has neither << operator nor PrintTo(). // // A user can override this behavior for a class type Foo by defining // a << operator in the namespace where Foo is defined. // // We put this operator in namespace 'internal2' instead of 'internal' // to simplify the implementation, as much code in 'internal' needs to // use << in STL, which would conflict with our own << were it defined // in 'internal'. // // Note that this operator<< takes a generic std::basic_ostream type instead of the more restricted std::ostream. If // we define it to take an std::ostream instead, we'll get an // "ambiguous overloads" compiler error when trying to print a type // Foo that supports streaming to std::basic_ostream, as the compiler cannot tell whether // operator<<(std::ostream&, const T&) or // operator<<(std::basic_stream, const Foo&) is more // specific. template ::std::basic_ostream& operator<<( ::std::basic_ostream& os, const T& x) { TypeWithoutFormatter::value ? kProtobuf : internal::ImplicitlyConvertible::value ? kConvertibleToInteger : kOtherType)>::PrintValue(x, &os); return os; } } // namespace internal2 } // namespace testing // This namespace MUST NOT BE NESTED IN ::testing, or the name look-up // magic needed for implementing UniversalPrinter won't work. namespace testing_internal { // Used to print a value that is not an STL-style container when the // user doesn't define PrintTo() for it. template void DefaultPrintNonContainerTo(const T& value, ::std::ostream* os) { // With the following statement, during unqualified name lookup, // testing::internal2::operator<< appears as if it was declared in // the nearest enclosing namespace that contains both // ::testing_internal and ::testing::internal2, i.e. the global // namespace. For more details, refer to the C++ Standard section // 7.3.4-1 [namespace.udir]. This allows us to fall back onto // testing::internal2::operator<< in case T doesn't come with a << // operator. // // We cannot write 'using ::testing::internal2::operator<<;', which // gcc 3.3 fails to compile due to a compiler bug. using namespace ::testing::internal2; // NOLINT // Assuming T is defined in namespace foo, in the next statement, // the compiler will consider all of: // // 1. foo::operator<< (thanks to Koenig look-up), // 2. ::operator<< (as the current namespace is enclosed in ::), // 3. testing::internal2::operator<< (thanks to the using statement above). // // The operator<< whose type matches T best will be picked. // // We deliberately allow #2 to be a candidate, as sometimes it's // impossible to define #1 (e.g. when foo is ::std, defining // anything in it is undefined behavior unless you are a compiler // vendor.). *os << value; } } // namespace testing_internal namespace testing { namespace internal { // UniversalPrinter::Print(value, ostream_ptr) prints the given // value to the given ostream. The caller must ensure that // 'ostream_ptr' is not NULL, or the behavior is undefined. // // We define UniversalPrinter as a class template (as opposed to a // function template), as we need to partially specialize it for // reference types, which cannot be done with function templates. template class UniversalPrinter; template void UniversalPrint(const T& value, ::std::ostream* os); // Used to print an STL-style container when the user doesn't define // a PrintTo() for it. template void DefaultPrintTo(IsContainer /* dummy */, false_type /* is not a pointer */, const C& container, ::std::ostream* os) { const size_t kMaxCount = 32; // The maximum number of elements to print. *os << '{'; size_t count = 0; for (typename C::const_iterator it = container.begin(); it != container.end(); ++it, ++count) { if (count > 0) { *os << ','; if (count == kMaxCount) { // Enough has been printed. *os << " ..."; break; } } *os << ' '; // We cannot call PrintTo(*it, os) here as PrintTo() doesn't // handle *it being a native array. internal::UniversalPrint(*it, os); } if (count > 0) { *os << ' '; } *os << '}'; } // Used to print a pointer that is neither a char pointer nor a member // pointer, when the user doesn't define PrintTo() for it. (A member // variable pointer or member function pointer doesn't really point to // a location in the address space. Their representation is // implementation-defined. Therefore they will be printed as raw // bytes.) template void DefaultPrintTo(IsNotContainer /* dummy */, true_type /* is a pointer */, T* p, ::std::ostream* os) { if (p == NULL) { *os << "NULL"; } else { // C++ doesn't allow casting from a function pointer to any object // pointer. // // IsTrue() silences warnings: "Condition is always true", // "unreachable code". if (IsTrue(ImplicitlyConvertible::value)) { // T is not a function type. We just call << to print p, // relying on ADL to pick up user-defined << for their pointer // types, if any. *os << p; } else { // T is a function type, so '*os << p' doesn't do what we want // (it just prints p as bool). We want to print p as a const // void*. However, we cannot cast it to const void* directly, // even using reinterpret_cast, as earlier versions of gcc // (e.g. 3.4.5) cannot compile the cast when p is a function // pointer. Casting to UInt64 first solves the problem. *os << reinterpret_cast( reinterpret_cast(p)); } } } // Used to print a non-container, non-pointer value when the user // doesn't define PrintTo() for it. template void DefaultPrintTo(IsNotContainer /* dummy */, false_type /* is not a pointer */, const T& value, ::std::ostream* os) { ::testing_internal::DefaultPrintNonContainerTo(value, os); } // Prints the given value using the << operator if it has one; // otherwise prints the bytes in it. This is what // UniversalPrinter::Print() does when PrintTo() is not specialized // or overloaded for type T. // // A user can override this behavior for a class type Foo by defining // an overload of PrintTo() in the namespace where Foo is defined. We // give the user this option as sometimes defining a << operator for // Foo is not desirable (e.g. the coding style may prevent doing it, // or there is already a << operator but it doesn't do what the user // wants). template void PrintTo(const T& value, ::std::ostream* os) { // DefaultPrintTo() is overloaded. The type of its first two // arguments determine which version will be picked. If T is an // STL-style container, the version for container will be called; if // T is a pointer, the pointer version will be called; otherwise the // generic version will be called. // // Note that we check for container types here, prior to we check // for protocol message types in our operator<<. The rationale is: // // For protocol messages, we want to give people a chance to // override Google Mock's format by defining a PrintTo() or // operator<<. For STL containers, other formats can be // incompatible with Google Mock's format for the container // elements; therefore we check for container types here to ensure // that our format is used. // // The second argument of DefaultPrintTo() is needed to bypass a bug // in Symbian's C++ compiler that prevents it from picking the right // overload between: // // PrintTo(const T& x, ...); // PrintTo(T* x, ...); DefaultPrintTo(IsContainerTest(0), is_pointer(), value, os); } // The following list of PrintTo() overloads tells // UniversalPrinter::Print() how to print standard types (built-in // types, strings, plain arrays, and pointers). // Overloads for various char types. GTEST_API_ void PrintTo(unsigned char c, ::std::ostream* os); GTEST_API_ void PrintTo(signed char c, ::std::ostream* os); inline void PrintTo(char c, ::std::ostream* os) { // When printing a plain char, we always treat it as unsigned. This // way, the output won't be affected by whether the compiler thinks // char is signed or not. PrintTo(static_cast(c), os); } // Overloads for other simple built-in types. inline void PrintTo(bool x, ::std::ostream* os) { *os << (x ? "true" : "false"); } // Overload for wchar_t type. // Prints a wchar_t as a symbol if it is printable or as its internal // code otherwise and also as its decimal code (except for L'\0'). // The L'\0' char is printed as "L'\\0'". The decimal code is printed // as signed integer when wchar_t is implemented by the compiler // as a signed type and is printed as an unsigned integer when wchar_t // is implemented as an unsigned type. GTEST_API_ void PrintTo(wchar_t wc, ::std::ostream* os); // Overloads for C strings. GTEST_API_ void PrintTo(const char* s, ::std::ostream* os); inline void PrintTo(char* s, ::std::ostream* os) { PrintTo(ImplicitCast_(s), os); } // signed/unsigned char is often used for representing binary data, so // we print pointers to it as void* to be safe. inline void PrintTo(const signed char* s, ::std::ostream* os) { PrintTo(ImplicitCast_(s), os); } inline void PrintTo(signed char* s, ::std::ostream* os) { PrintTo(ImplicitCast_(s), os); } inline void PrintTo(const unsigned char* s, ::std::ostream* os) { PrintTo(ImplicitCast_(s), os); } inline void PrintTo(unsigned char* s, ::std::ostream* os) { PrintTo(ImplicitCast_(s), os); } // MSVC can be configured to define wchar_t as a typedef of unsigned // short. It defines _NATIVE_WCHAR_T_DEFINED when wchar_t is a native // type. When wchar_t is a typedef, defining an overload for const // wchar_t* would cause unsigned short* be printed as a wide string, // possibly causing invalid memory accesses. #if !defined(_MSC_VER) || defined(_NATIVE_WCHAR_T_DEFINED) // Overloads for wide C strings GTEST_API_ void PrintTo(const wchar_t* s, ::std::ostream* os); inline void PrintTo(wchar_t* s, ::std::ostream* os) { PrintTo(ImplicitCast_(s), os); } #endif // Overload for C arrays. Multi-dimensional arrays are printed // properly. // Prints the given number of elements in an array, without printing // the curly braces. template void PrintRawArrayTo(const T a[], size_t count, ::std::ostream* os) { UniversalPrint(a[0], os); for (size_t i = 1; i != count; i++) { *os << ", "; UniversalPrint(a[i], os); } } // Overloads for ::string and ::std::string. #if GTEST_HAS_GLOBAL_STRING GTEST_API_ void PrintStringTo(const ::string&s, ::std::ostream* os); inline void PrintTo(const ::string& s, ::std::ostream* os) { PrintStringTo(s, os); } #endif // GTEST_HAS_GLOBAL_STRING GTEST_API_ void PrintStringTo(const ::std::string&s, ::std::ostream* os); inline void PrintTo(const ::std::string& s, ::std::ostream* os) { PrintStringTo(s, os); } // Overloads for ::wstring and ::std::wstring. #if GTEST_HAS_GLOBAL_WSTRING GTEST_API_ void PrintWideStringTo(const ::wstring&s, ::std::ostream* os); inline void PrintTo(const ::wstring& s, ::std::ostream* os) { PrintWideStringTo(s, os); } #endif // GTEST_HAS_GLOBAL_WSTRING #if GTEST_HAS_STD_WSTRING GTEST_API_ void PrintWideStringTo(const ::std::wstring&s, ::std::ostream* os); inline void PrintTo(const ::std::wstring& s, ::std::ostream* os) { PrintWideStringTo(s, os); } #endif // GTEST_HAS_STD_WSTRING #if GTEST_HAS_TR1_TUPLE // Overload for ::std::tr1::tuple. Needed for printing function arguments, // which are packed as tuples. // Helper function for printing a tuple. T must be instantiated with // a tuple type. template void PrintTupleTo(const T& t, ::std::ostream* os); // Overloaded PrintTo() for tuples of various arities. We support // tuples of up-to 10 fields. The following implementation works // regardless of whether tr1::tuple is implemented using the // non-standard variadic template feature or not. inline void PrintTo(const ::std::tr1::tuple<>& t, ::std::ostream* os) { PrintTupleTo(t, os); } template void PrintTo(const ::std::tr1::tuple& t, ::std::ostream* os) { PrintTupleTo(t, os); } template void PrintTo(const ::std::tr1::tuple& t, ::std::ostream* os) { PrintTupleTo(t, os); } template void PrintTo(const ::std::tr1::tuple& t, ::std::ostream* os) { PrintTupleTo(t, os); } template void PrintTo(const ::std::tr1::tuple& t, ::std::ostream* os) { PrintTupleTo(t, os); } template void PrintTo(const ::std::tr1::tuple& t, ::std::ostream* os) { PrintTupleTo(t, os); } template void PrintTo(const ::std::tr1::tuple& t, ::std::ostream* os) { PrintTupleTo(t, os); } template void PrintTo(const ::std::tr1::tuple& t, ::std::ostream* os) { PrintTupleTo(t, os); } template void PrintTo(const ::std::tr1::tuple& t, ::std::ostream* os) { PrintTupleTo(t, os); } template void PrintTo(const ::std::tr1::tuple& t, ::std::ostream* os) { PrintTupleTo(t, os); } template void PrintTo( const ::std::tr1::tuple& t, ::std::ostream* os) { PrintTupleTo(t, os); } #endif // GTEST_HAS_TR1_TUPLE // Overload for std::pair. template void PrintTo(const ::std::pair& value, ::std::ostream* os) { *os << '('; // We cannot use UniversalPrint(value.first, os) here, as T1 may be // a reference type. The same for printing value.second. UniversalPrinter::Print(value.first, os); *os << ", "; UniversalPrinter::Print(value.second, os); *os << ')'; } // Implements printing a non-reference type T by letting the compiler // pick the right overload of PrintTo() for T. template class UniversalPrinter { public: // MSVC warns about adding const to a function type, so we want to // disable the warning. #ifdef _MSC_VER # pragma warning(push) // Saves the current warning state. # pragma warning(disable:4180) // Temporarily disables warning 4180. #endif // _MSC_VER // Note: we deliberately don't call this PrintTo(), as that name // conflicts with ::testing::internal::PrintTo in the body of the // function. static void Print(const T& value, ::std::ostream* os) { // By default, ::testing::internal::PrintTo() is used for printing // the value. // // Thanks to Koenig look-up, if T is a class and has its own // PrintTo() function defined in its namespace, that function will // be visible here. Since it is more specific than the generic ones // in ::testing::internal, it will be picked by the compiler in the // following statement - exactly what we want. PrintTo(value, os); } #ifdef _MSC_VER # pragma warning(pop) // Restores the warning state. #endif // _MSC_VER }; // UniversalPrintArray(begin, len, os) prints an array of 'len' // elements, starting at address 'begin'. template void UniversalPrintArray(const T* begin, size_t len, ::std::ostream* os) { if (len == 0) { *os << "{}"; } else { *os << "{ "; const size_t kThreshold = 18; const size_t kChunkSize = 8; // If the array has more than kThreshold elements, we'll have to // omit some details by printing only the first and the last // kChunkSize elements. // TODO(wan@google.com): let the user control the threshold using a flag. if (len <= kThreshold) { PrintRawArrayTo(begin, len, os); } else { PrintRawArrayTo(begin, kChunkSize, os); *os << ", ..., "; PrintRawArrayTo(begin + len - kChunkSize, kChunkSize, os); } *os << " }"; } } // This overload prints a (const) char array compactly. GTEST_API_ void UniversalPrintArray( const char* begin, size_t len, ::std::ostream* os); // This overload prints a (const) wchar_t array compactly. GTEST_API_ void UniversalPrintArray( const wchar_t* begin, size_t len, ::std::ostream* os); // Implements printing an array type T[N]. template class UniversalPrinter { public: // Prints the given array, omitting some elements when there are too // many. static void Print(const T (&a)[N], ::std::ostream* os) { UniversalPrintArray(a, N, os); } }; // Implements printing a reference type T&. template class UniversalPrinter { public: // MSVC warns about adding const to a function type, so we want to // disable the warning. #ifdef _MSC_VER # pragma warning(push) // Saves the current warning state. # pragma warning(disable:4180) // Temporarily disables warning 4180. #endif // _MSC_VER static void Print(const T& value, ::std::ostream* os) { // Prints the address of the value. We use reinterpret_cast here // as static_cast doesn't compile when T is a function type. *os << "@" << reinterpret_cast(&value) << " "; // Then prints the value itself. UniversalPrint(value, os); } #ifdef _MSC_VER # pragma warning(pop) // Restores the warning state. #endif // _MSC_VER }; // Prints a value tersely: for a reference type, the referenced value // (but not the address) is printed; for a (const) char pointer, the // NUL-terminated string (but not the pointer) is printed. template class UniversalTersePrinter { public: static void Print(const T& value, ::std::ostream* os) { UniversalPrint(value, os); } }; template class UniversalTersePrinter { public: static void Print(const T& value, ::std::ostream* os) { UniversalPrint(value, os); } }; template class UniversalTersePrinter { public: static void Print(const T (&value)[N], ::std::ostream* os) { UniversalPrinter::Print(value, os); } }; template <> class UniversalTersePrinter { public: static void Print(const char* str, ::std::ostream* os) { if (str == NULL) { *os << "NULL"; } else { UniversalPrint(string(str), os); } } }; template <> class UniversalTersePrinter { public: static void Print(char* str, ::std::ostream* os) { UniversalTersePrinter::Print(str, os); } }; #if GTEST_HAS_STD_WSTRING template <> class UniversalTersePrinter { public: static void Print(const wchar_t* str, ::std::ostream* os) { if (str == NULL) { *os << "NULL"; } else { UniversalPrint(::std::wstring(str), os); } } }; #endif template <> class UniversalTersePrinter { public: static void Print(wchar_t* str, ::std::ostream* os) { UniversalTersePrinter::Print(str, os); } }; template void UniversalTersePrint(const T& value, ::std::ostream* os) { UniversalTersePrinter::Print(value, os); } // Prints a value using the type inferred by the compiler. The // difference between this and UniversalTersePrint() is that for a // (const) char pointer, this prints both the pointer and the // NUL-terminated string. template void UniversalPrint(const T& value, ::std::ostream* os) { // A workarond for the bug in VC++ 7.1 that prevents us from instantiating // UniversalPrinter with T directly. typedef T T1; UniversalPrinter::Print(value, os); } #if GTEST_HAS_TR1_TUPLE typedef ::std::vector Strings; // This helper template allows PrintTo() for tuples and // UniversalTersePrintTupleFieldsToStrings() to be defined by // induction on the number of tuple fields. The idea is that // TuplePrefixPrinter::PrintPrefixTo(t, os) prints the first N // fields in tuple t, and can be defined in terms of // TuplePrefixPrinter. // The inductive case. template struct TuplePrefixPrinter { // Prints the first N fields of a tuple. template static void PrintPrefixTo(const Tuple& t, ::std::ostream* os) { TuplePrefixPrinter::PrintPrefixTo(t, os); *os << ", "; UniversalPrinter::type> ::Print(::std::tr1::get(t), os); } // Tersely prints the first N fields of a tuple to a string vector, // one element for each field. template static void TersePrintPrefixToStrings(const Tuple& t, Strings* strings) { TuplePrefixPrinter::TersePrintPrefixToStrings(t, strings); ::std::stringstream ss; UniversalTersePrint(::std::tr1::get(t), &ss); strings->push_back(ss.str()); } }; // Base cases. template <> struct TuplePrefixPrinter<0> { template static void PrintPrefixTo(const Tuple&, ::std::ostream*) {} template static void TersePrintPrefixToStrings(const Tuple&, Strings*) {} }; // We have to specialize the entire TuplePrefixPrinter<> class // template here, even though the definition of // TersePrintPrefixToStrings() is the same as the generic version, as // Embarcadero (formerly CodeGear, formerly Borland) C++ doesn't // support specializing a method template of a class template. template <> struct TuplePrefixPrinter<1> { template static void PrintPrefixTo(const Tuple& t, ::std::ostream* os) { UniversalPrinter::type>:: Print(::std::tr1::get<0>(t), os); } template static void TersePrintPrefixToStrings(const Tuple& t, Strings* strings) { ::std::stringstream ss; UniversalTersePrint(::std::tr1::get<0>(t), &ss); strings->push_back(ss.str()); } }; // Helper function for printing a tuple. T must be instantiated with // a tuple type. template void PrintTupleTo(const T& t, ::std::ostream* os) { *os << "("; TuplePrefixPrinter< ::std::tr1::tuple_size::value>:: PrintPrefixTo(t, os); *os << ")"; } // Prints the fields of a tuple tersely to a string vector, one // element for each field. See the comment before // UniversalTersePrint() for how we define "tersely". template Strings UniversalTersePrintTupleFieldsToStrings(const Tuple& value) { Strings result; TuplePrefixPrinter< ::std::tr1::tuple_size::value>:: TersePrintPrefixToStrings(value, &result); return result; } #endif // GTEST_HAS_TR1_TUPLE } // namespace internal template ::std::string PrintToString(const T& value) { ::std::stringstream ss; internal::UniversalTersePrinter::Print(value, &ss); return ss.str(); } } // namespace testing #endif // GTEST_INCLUDE_GTEST_GTEST_PRINTERS_H_ #if GTEST_HAS_PARAM_TEST namespace testing { namespace internal { // INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE. // // Outputs a message explaining invalid registration of different // fixture class for the same test case. This may happen when // TEST_P macro is used to define two tests with the same name // but in different namespaces. GTEST_API_ void ReportInvalidTestCaseType(const char* test_case_name, const char* file, int line); template class ParamGeneratorInterface; template class ParamGenerator; // Interface for iterating over elements provided by an implementation // of ParamGeneratorInterface. template class ParamIteratorInterface { public: virtual ~ParamIteratorInterface() {} // A pointer to the base generator instance. // Used only for the purposes of iterator comparison // to make sure that two iterators belong to the same generator. virtual const ParamGeneratorInterface* BaseGenerator() const = 0; // Advances iterator to point to the next element // provided by the generator. The caller is responsible // for not calling Advance() on an iterator equal to // BaseGenerator()->End(). virtual void Advance() = 0; // Clones the iterator object. Used for implementing copy semantics // of ParamIterator. virtual ParamIteratorInterface* Clone() const = 0; // Dereferences the current iterator and provides (read-only) access // to the pointed value. It is the caller's responsibility not to call // Current() on an iterator equal to BaseGenerator()->End(). // Used for implementing ParamGenerator::operator*(). virtual const T* Current() const = 0; // Determines whether the given iterator and other point to the same // element in the sequence generated by the generator. // Used for implementing ParamGenerator::operator==(). virtual bool Equals(const ParamIteratorInterface& other) const = 0; }; // Class iterating over elements provided by an implementation of // ParamGeneratorInterface. It wraps ParamIteratorInterface // and implements the const forward iterator concept. template class ParamIterator { public: typedef T value_type; typedef const T& reference; typedef ptrdiff_t difference_type; // ParamIterator assumes ownership of the impl_ pointer. ParamIterator(const ParamIterator& other) : impl_(other.impl_->Clone()) {} ParamIterator& operator=(const ParamIterator& other) { if (this != &other) impl_.reset(other.impl_->Clone()); return *this; } const T& operator*() const { return *impl_->Current(); } const T* operator->() const { return impl_->Current(); } // Prefix version of operator++. ParamIterator& operator++() { impl_->Advance(); return *this; } // Postfix version of operator++. ParamIterator operator++(int /*unused*/) { ParamIteratorInterface* clone = impl_->Clone(); impl_->Advance(); return ParamIterator(clone); } bool operator==(const ParamIterator& other) const { return impl_.get() == other.impl_.get() || impl_->Equals(*other.impl_); } bool operator!=(const ParamIterator& other) const { return !(*this == other); } private: friend class ParamGenerator; explicit ParamIterator(ParamIteratorInterface* impl) : impl_(impl) {} scoped_ptr > impl_; }; // ParamGeneratorInterface is the binary interface to access generators // defined in other translation units. template class ParamGeneratorInterface { public: typedef T ParamType; virtual ~ParamGeneratorInterface() {} // Generator interface definition virtual ParamIteratorInterface* Begin() const = 0; virtual ParamIteratorInterface* End() const = 0; }; // Wraps ParamGeneratorInterface and provides general generator syntax // compatible with the STL Container concept. // This class implements copy initialization semantics and the contained // ParamGeneratorInterface instance is shared among all copies // of the original object. This is possible because that instance is immutable. template class ParamGenerator { public: typedef ParamIterator iterator; explicit ParamGenerator(ParamGeneratorInterface* impl) : impl_(impl) {} ParamGenerator(const ParamGenerator& other) : impl_(other.impl_) {} ParamGenerator& operator=(const ParamGenerator& other) { impl_ = other.impl_; return *this; } iterator begin() const { return iterator(impl_->Begin()); } iterator end() const { return iterator(impl_->End()); } private: linked_ptr > impl_; }; // Generates values from a range of two comparable values. Can be used to // generate sequences of user-defined types that implement operator+() and // operator<(). // This class is used in the Range() function. template class RangeGenerator : public ParamGeneratorInterface { public: RangeGenerator(T begin, T end, IncrementT step) : begin_(begin), end_(end), step_(step), end_index_(CalculateEndIndex(begin, end, step)) {} virtual ~RangeGenerator() {} virtual ParamIteratorInterface* Begin() const { return new Iterator(this, begin_, 0, step_); } virtual ParamIteratorInterface* End() const { return new Iterator(this, end_, end_index_, step_); } private: class Iterator : public ParamIteratorInterface { public: Iterator(const ParamGeneratorInterface* base, T value, int index, IncrementT step) : base_(base), value_(value), index_(index), step_(step) {} virtual ~Iterator() {} virtual const ParamGeneratorInterface* BaseGenerator() const { return base_; } virtual void Advance() { value_ = value_ + step_; index_++; } virtual ParamIteratorInterface* Clone() const { return new Iterator(*this); } virtual const T* Current() const { return &value_; } virtual bool Equals(const ParamIteratorInterface& other) const { // Having the same base generator guarantees that the other // iterator is of the same type and we can downcast. GTEST_CHECK_(BaseGenerator() == other.BaseGenerator()) << "The program attempted to compare iterators " << "from different generators." << std::endl; const int other_index = CheckedDowncastToActualType(&other)->index_; return index_ == other_index; } private: Iterator(const Iterator& other) : ParamIteratorInterface(), base_(other.base_), value_(other.value_), index_(other.index_), step_(other.step_) {} // No implementation - assignment is unsupported. void operator=(const Iterator& other); const ParamGeneratorInterface* const base_; T value_; int index_; const IncrementT step_; }; // class RangeGenerator::Iterator static int CalculateEndIndex(const T& begin, const T& end, const IncrementT& step) { int end_index = 0; for (T i = begin; i < end; i = i + step) end_index++; return end_index; } // No implementation - assignment is unsupported. void operator=(const RangeGenerator& other); const T begin_; const T end_; const IncrementT step_; // The index for the end() iterator. All the elements in the generated // sequence are indexed (0-based) to aid iterator comparison. const int end_index_; }; // class RangeGenerator // Generates values from a pair of STL-style iterators. Used in the // ValuesIn() function. The elements are copied from the source range // since the source can be located on the stack, and the generator // is likely to persist beyond that stack frame. template class ValuesInIteratorRangeGenerator : public ParamGeneratorInterface { public: template ValuesInIteratorRangeGenerator(ForwardIterator begin, ForwardIterator end) : container_(begin, end) {} virtual ~ValuesInIteratorRangeGenerator() {} virtual ParamIteratorInterface* Begin() const { return new Iterator(this, container_.begin()); } virtual ParamIteratorInterface* End() const { return new Iterator(this, container_.end()); } private: typedef typename ::std::vector ContainerType; class Iterator : public ParamIteratorInterface { public: Iterator(const ParamGeneratorInterface* base, typename ContainerType::const_iterator iterator) : base_(base), iterator_(iterator) {} virtual ~Iterator() {} virtual const ParamGeneratorInterface* BaseGenerator() const { return base_; } virtual void Advance() { ++iterator_; value_.reset(); } virtual ParamIteratorInterface* Clone() const { return new Iterator(*this); } // We need to use cached value referenced by iterator_ because *iterator_ // can return a temporary object (and of type other then T), so just // having "return &*iterator_;" doesn't work. // value_ is updated here and not in Advance() because Advance() // can advance iterator_ beyond the end of the range, and we cannot // detect that fact. The client code, on the other hand, is // responsible for not calling Current() on an out-of-range iterator. virtual const T* Current() const { if (value_.get() == NULL) value_.reset(new T(*iterator_)); return value_.get(); } virtual bool Equals(const ParamIteratorInterface& other) const { // Having the same base generator guarantees that the other // iterator is of the same type and we can downcast. GTEST_CHECK_(BaseGenerator() == other.BaseGenerator()) << "The program attempted to compare iterators " << "from different generators." << std::endl; return iterator_ == CheckedDowncastToActualType(&other)->iterator_; } private: Iterator(const Iterator& other) // The explicit constructor call suppresses a false warning // emitted by gcc when supplied with the -Wextra option. : ParamIteratorInterface(), base_(other.base_), iterator_(other.iterator_) {} const ParamGeneratorInterface* const base_; typename ContainerType::const_iterator iterator_; // A cached value of *iterator_. We keep it here to allow access by // pointer in the wrapping iterator's operator->(). // value_ needs to be mutable to be accessed in Current(). // Use of scoped_ptr helps manage cached value's lifetime, // which is bound by the lifespan of the iterator itself. mutable scoped_ptr value_; }; // class ValuesInIteratorRangeGenerator::Iterator // No implementation - assignment is unsupported. void operator=(const ValuesInIteratorRangeGenerator& other); const ContainerType container_; }; // class ValuesInIteratorRangeGenerator // INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE. // // Stores a parameter value and later creates tests parameterized with that // value. template class ParameterizedTestFactory : public TestFactoryBase { public: typedef typename TestClass::ParamType ParamType; explicit ParameterizedTestFactory(ParamType parameter) : parameter_(parameter) {} virtual Test* CreateTest() { TestClass::SetParam(¶meter_); return new TestClass(); } private: const ParamType parameter_; GTEST_DISALLOW_COPY_AND_ASSIGN_(ParameterizedTestFactory); }; // INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE. // // TestMetaFactoryBase is a base class for meta-factories that create // test factories for passing into MakeAndRegisterTestInfo function. template class TestMetaFactoryBase { public: virtual ~TestMetaFactoryBase() {} virtual TestFactoryBase* CreateTestFactory(ParamType parameter) = 0; }; // INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE. // // TestMetaFactory creates test factories for passing into // MakeAndRegisterTestInfo function. Since MakeAndRegisterTestInfo receives // ownership of test factory pointer, same factory object cannot be passed // into that method twice. But ParameterizedTestCaseInfo is going to call // it for each Test/Parameter value combination. Thus it needs meta factory // creator class. template class TestMetaFactory : public TestMetaFactoryBase { public: typedef typename TestCase::ParamType ParamType; TestMetaFactory() {} virtual TestFactoryBase* CreateTestFactory(ParamType parameter) { return new ParameterizedTestFactory(parameter); } private: GTEST_DISALLOW_COPY_AND_ASSIGN_(TestMetaFactory); }; // INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE. // // ParameterizedTestCaseInfoBase is a generic interface // to ParameterizedTestCaseInfo classes. ParameterizedTestCaseInfoBase // accumulates test information provided by TEST_P macro invocations // and generators provided by INSTANTIATE_TEST_CASE_P macro invocations // and uses that information to register all resulting test instances // in RegisterTests method. The ParameterizeTestCaseRegistry class holds // a collection of pointers to the ParameterizedTestCaseInfo objects // and calls RegisterTests() on each of them when asked. class ParameterizedTestCaseInfoBase { public: virtual ~ParameterizedTestCaseInfoBase() {} // Base part of test case name for display purposes. virtual const string& GetTestCaseName() const = 0; // Test case id to verify identity. virtual TypeId GetTestCaseTypeId() const = 0; // UnitTest class invokes this method to register tests in this // test case right before running them in RUN_ALL_TESTS macro. // This method should not be called more then once on any single // instance of a ParameterizedTestCaseInfoBase derived class. virtual void RegisterTests() = 0; protected: ParameterizedTestCaseInfoBase() {} private: GTEST_DISALLOW_COPY_AND_ASSIGN_(ParameterizedTestCaseInfoBase); }; // INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE. // // ParameterizedTestCaseInfo accumulates tests obtained from TEST_P // macro invocations for a particular test case and generators // obtained from INSTANTIATE_TEST_CASE_P macro invocations for that // test case. It registers tests with all values generated by all // generators when asked. template class ParameterizedTestCaseInfo : public ParameterizedTestCaseInfoBase { public: // ParamType and GeneratorCreationFunc are private types but are required // for declarations of public methods AddTestPattern() and // AddTestCaseInstantiation(). typedef typename TestCase::ParamType ParamType; // A function that returns an instance of appropriate generator type. typedef ParamGenerator(GeneratorCreationFunc)(); explicit ParameterizedTestCaseInfo(const char* name) : test_case_name_(name) {} // Test case base name for display purposes. virtual const string& GetTestCaseName() const { return test_case_name_; } // Test case id to verify identity. virtual TypeId GetTestCaseTypeId() const { return GetTypeId(); } // TEST_P macro uses AddTestPattern() to record information // about a single test in a LocalTestInfo structure. // test_case_name is the base name of the test case (without invocation // prefix). test_base_name is the name of an individual test without // parameter index. For the test SequenceA/FooTest.DoBar/1 FooTest is // test case base name and DoBar is test base name. void AddTestPattern(const char* test_case_name, const char* test_base_name, TestMetaFactoryBase* meta_factory) { tests_.push_back(linked_ptr(new TestInfo(test_case_name, test_base_name, meta_factory))); } // INSTANTIATE_TEST_CASE_P macro uses AddGenerator() to record information // about a generator. int AddTestCaseInstantiation(const string& instantiation_name, GeneratorCreationFunc* func, const char* /* file */, int /* line */) { instantiations_.push_back(::std::make_pair(instantiation_name, func)); return 0; // Return value used only to run this method in namespace scope. } // UnitTest class invokes this method to register tests in this test case // test cases right before running tests in RUN_ALL_TESTS macro. // This method should not be called more then once on any single // instance of a ParameterizedTestCaseInfoBase derived class. // UnitTest has a guard to prevent from calling this method more then once. virtual void RegisterTests() { for (typename TestInfoContainer::iterator test_it = tests_.begin(); test_it != tests_.end(); ++test_it) { linked_ptr test_info = *test_it; for (typename InstantiationContainer::iterator gen_it = instantiations_.begin(); gen_it != instantiations_.end(); ++gen_it) { const string& instantiation_name = gen_it->first; ParamGenerator generator((*gen_it->second)()); string test_case_name; if ( !instantiation_name.empty() ) test_case_name = instantiation_name + "/"; test_case_name += test_info->test_case_base_name; int i = 0; for (typename ParamGenerator::iterator param_it = generator.begin(); param_it != generator.end(); ++param_it, ++i) { Message test_name_stream; test_name_stream << test_info->test_base_name << "/" << i; MakeAndRegisterTestInfo( test_case_name.c_str(), test_name_stream.GetString().c_str(), NULL, // No type parameter. PrintToString(*param_it).c_str(), GetTestCaseTypeId(), TestCase::SetUpTestCase, TestCase::TearDownTestCase, test_info->test_meta_factory->CreateTestFactory(*param_it)); } // for param_it } // for gen_it } // for test_it } // RegisterTests private: // LocalTestInfo structure keeps information about a single test registered // with TEST_P macro. struct TestInfo { TestInfo(const char* a_test_case_base_name, const char* a_test_base_name, TestMetaFactoryBase* a_test_meta_factory) : test_case_base_name(a_test_case_base_name), test_base_name(a_test_base_name), test_meta_factory(a_test_meta_factory) {} const string test_case_base_name; const string test_base_name; const scoped_ptr > test_meta_factory; }; typedef ::std::vector > TestInfoContainer; // Keeps pairs of // received from INSTANTIATE_TEST_CASE_P macros. typedef ::std::vector > InstantiationContainer; const string test_case_name_; TestInfoContainer tests_; InstantiationContainer instantiations_; GTEST_DISALLOW_COPY_AND_ASSIGN_(ParameterizedTestCaseInfo); }; // class ParameterizedTestCaseInfo // INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE. // // ParameterizedTestCaseRegistry contains a map of ParameterizedTestCaseInfoBase // classes accessed by test case names. TEST_P and INSTANTIATE_TEST_CASE_P // macros use it to locate their corresponding ParameterizedTestCaseInfo // descriptors. class ParameterizedTestCaseRegistry { public: ParameterizedTestCaseRegistry() {} ~ParameterizedTestCaseRegistry() { for (TestCaseInfoContainer::iterator it = test_case_infos_.begin(); it != test_case_infos_.end(); ++it) { delete *it; } } // Looks up or creates and returns a structure containing information about // tests and instantiations of a particular test case. template ParameterizedTestCaseInfo* GetTestCasePatternHolder( const char* test_case_name, const char* file, int line) { ParameterizedTestCaseInfo* typed_test_info = NULL; for (TestCaseInfoContainer::iterator it = test_case_infos_.begin(); it != test_case_infos_.end(); ++it) { if ((*it)->GetTestCaseName() == test_case_name) { if ((*it)->GetTestCaseTypeId() != GetTypeId()) { // Complain about incorrect usage of Google Test facilities // and terminate the program since we cannot guaranty correct // test case setup and tear-down in this case. ReportInvalidTestCaseType(test_case_name, file, line); posix::Abort(); } else { // At this point we are sure that the object we found is of the same // type we are looking for, so we downcast it to that type // without further checks. typed_test_info = CheckedDowncastToActualType< ParameterizedTestCaseInfo >(*it); } break; } } if (typed_test_info == NULL) { typed_test_info = new ParameterizedTestCaseInfo(test_case_name); test_case_infos_.push_back(typed_test_info); } return typed_test_info; } void RegisterTests() { for (TestCaseInfoContainer::iterator it = test_case_infos_.begin(); it != test_case_infos_.end(); ++it) { (*it)->RegisterTests(); } } private: typedef ::std::vector TestCaseInfoContainer; TestCaseInfoContainer test_case_infos_; GTEST_DISALLOW_COPY_AND_ASSIGN_(ParameterizedTestCaseRegistry); }; } // namespace internal } // namespace testing #endif // GTEST_HAS_PARAM_TEST #endif // GTEST_INCLUDE_GTEST_INTERNAL_GTEST_PARAM_UTIL_H_ // This file was GENERATED by command: // pump.py gtest-param-util-generated.h.pump // DO NOT EDIT BY HAND!!! // Copyright 2008 Google Inc. // All Rights Reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: vladl@google.com (Vlad Losev) // Type and function utilities for implementing parameterized tests. // This file is generated by a SCRIPT. DO NOT EDIT BY HAND! // // Currently Google Test supports at most 50 arguments in Values, // and at most 10 arguments in Combine. Please contact // googletestframework@googlegroups.com if you need more. // Please note that the number of arguments to Combine is limited // by the maximum arity of the implementation of tr1::tuple which is // currently set at 10. #ifndef GTEST_INCLUDE_GTEST_INTERNAL_GTEST_PARAM_UTIL_GENERATED_H_ #define GTEST_INCLUDE_GTEST_INTERNAL_GTEST_PARAM_UTIL_GENERATED_H_ // scripts/fuse_gtest.py depends on gtest's own header being #included // *unconditionally*. Therefore these #includes cannot be moved // inside #if GTEST_HAS_PARAM_TEST. #if GTEST_HAS_PARAM_TEST namespace testing { // Forward declarations of ValuesIn(), which is implemented in // include/gtest/gtest-param-test.h. template internal::ParamGenerator< typename ::testing::internal::IteratorTraits::value_type> ValuesIn(ForwardIterator begin, ForwardIterator end); template internal::ParamGenerator ValuesIn(const T (&array)[N]); template internal::ParamGenerator ValuesIn( const Container& container); namespace internal { // Used in the Values() function to provide polymorphic capabilities. template class ValueArray1 { public: explicit ValueArray1(T1 v1) : v1_(v1) {} template operator ParamGenerator() const { return ValuesIn(&v1_, &v1_ + 1); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray1& other); const T1 v1_; }; template class ValueArray2 { public: ValueArray2(T1 v1, T2 v2) : v1_(v1), v2_(v2) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray2& other); const T1 v1_; const T2 v2_; }; template class ValueArray3 { public: ValueArray3(T1 v1, T2 v2, T3 v3) : v1_(v1), v2_(v2), v3_(v3) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray3& other); const T1 v1_; const T2 v2_; const T3 v3_; }; template class ValueArray4 { public: ValueArray4(T1 v1, T2 v2, T3 v3, T4 v4) : v1_(v1), v2_(v2), v3_(v3), v4_(v4) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray4& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; }; template class ValueArray5 { public: ValueArray5(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray5& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; }; template class ValueArray6 { public: ValueArray6(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray6& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; }; template class ValueArray7 { public: ValueArray7(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray7& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; }; template class ValueArray8 { public: ValueArray8(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray8& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; }; template class ValueArray9 { public: ValueArray9(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray9& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; }; template class ValueArray10 { public: ValueArray10(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray10& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; }; template class ValueArray11 { public: ValueArray11(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray11& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; }; template class ValueArray12 { public: ValueArray12(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray12& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; }; template class ValueArray13 { public: ValueArray13(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray13& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; }; template class ValueArray14 { public: ValueArray14(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray14& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; }; template class ValueArray15 { public: ValueArray15(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray15& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; }; template class ValueArray16 { public: ValueArray16(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray16& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; }; template class ValueArray17 { public: ValueArray17(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray17& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; }; template class ValueArray18 { public: ValueArray18(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray18& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; }; template class ValueArray19 { public: ValueArray19(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray19& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; }; template class ValueArray20 { public: ValueArray20(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray20& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; }; template class ValueArray21 { public: ValueArray21(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray21& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; }; template class ValueArray22 { public: ValueArray22(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray22& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; }; template class ValueArray23 { public: ValueArray23(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray23& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; }; template class ValueArray24 { public: ValueArray24(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray24& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; }; template class ValueArray25 { public: ValueArray25(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray25& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; }; template class ValueArray26 { public: ValueArray26(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray26& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; }; template class ValueArray27 { public: ValueArray27(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray27& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; }; template class ValueArray28 { public: ValueArray28(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray28& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; }; template class ValueArray29 { public: ValueArray29(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray29& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; }; template class ValueArray30 { public: ValueArray30(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray30& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; }; template class ValueArray31 { public: ValueArray31(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray31& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; }; template class ValueArray32 { public: ValueArray32(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray32& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; }; template class ValueArray33 { public: ValueArray33(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray33& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; }; template class ValueArray34 { public: ValueArray34(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray34& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; }; template class ValueArray35 { public: ValueArray35(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray35& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; }; template class ValueArray36 { public: ValueArray36(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35), v36_(v36) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_), static_cast(v36_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray36& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; const T36 v36_; }; template class ValueArray37 { public: ValueArray37(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35), v36_(v36), v37_(v37) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_), static_cast(v36_), static_cast(v37_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray37& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; const T36 v36_; const T37 v37_; }; template class ValueArray38 { public: ValueArray38(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35), v36_(v36), v37_(v37), v38_(v38) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_), static_cast(v36_), static_cast(v37_), static_cast(v38_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray38& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; const T36 v36_; const T37 v37_; const T38 v38_; }; template class ValueArray39 { public: ValueArray39(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35), v36_(v36), v37_(v37), v38_(v38), v39_(v39) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_), static_cast(v36_), static_cast(v37_), static_cast(v38_), static_cast(v39_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray39& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; const T36 v36_; const T37 v37_; const T38 v38_; const T39 v39_; }; template class ValueArray40 { public: ValueArray40(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35), v36_(v36), v37_(v37), v38_(v38), v39_(v39), v40_(v40) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_), static_cast(v36_), static_cast(v37_), static_cast(v38_), static_cast(v39_), static_cast(v40_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray40& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; const T36 v36_; const T37 v37_; const T38 v38_; const T39 v39_; const T40 v40_; }; template class ValueArray41 { public: ValueArray41(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35), v36_(v36), v37_(v37), v38_(v38), v39_(v39), v40_(v40), v41_(v41) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_), static_cast(v36_), static_cast(v37_), static_cast(v38_), static_cast(v39_), static_cast(v40_), static_cast(v41_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray41& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; const T36 v36_; const T37 v37_; const T38 v38_; const T39 v39_; const T40 v40_; const T41 v41_; }; template class ValueArray42 { public: ValueArray42(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35), v36_(v36), v37_(v37), v38_(v38), v39_(v39), v40_(v40), v41_(v41), v42_(v42) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_), static_cast(v36_), static_cast(v37_), static_cast(v38_), static_cast(v39_), static_cast(v40_), static_cast(v41_), static_cast(v42_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray42& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; const T36 v36_; const T37 v37_; const T38 v38_; const T39 v39_; const T40 v40_; const T41 v41_; const T42 v42_; }; template class ValueArray43 { public: ValueArray43(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35), v36_(v36), v37_(v37), v38_(v38), v39_(v39), v40_(v40), v41_(v41), v42_(v42), v43_(v43) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_), static_cast(v36_), static_cast(v37_), static_cast(v38_), static_cast(v39_), static_cast(v40_), static_cast(v41_), static_cast(v42_), static_cast(v43_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray43& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; const T36 v36_; const T37 v37_; const T38 v38_; const T39 v39_; const T40 v40_; const T41 v41_; const T42 v42_; const T43 v43_; }; template class ValueArray44 { public: ValueArray44(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43, T44 v44) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35), v36_(v36), v37_(v37), v38_(v38), v39_(v39), v40_(v40), v41_(v41), v42_(v42), v43_(v43), v44_(v44) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_), static_cast(v36_), static_cast(v37_), static_cast(v38_), static_cast(v39_), static_cast(v40_), static_cast(v41_), static_cast(v42_), static_cast(v43_), static_cast(v44_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray44& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; const T36 v36_; const T37 v37_; const T38 v38_; const T39 v39_; const T40 v40_; const T41 v41_; const T42 v42_; const T43 v43_; const T44 v44_; }; template class ValueArray45 { public: ValueArray45(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43, T44 v44, T45 v45) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35), v36_(v36), v37_(v37), v38_(v38), v39_(v39), v40_(v40), v41_(v41), v42_(v42), v43_(v43), v44_(v44), v45_(v45) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_), static_cast(v36_), static_cast(v37_), static_cast(v38_), static_cast(v39_), static_cast(v40_), static_cast(v41_), static_cast(v42_), static_cast(v43_), static_cast(v44_), static_cast(v45_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray45& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; const T36 v36_; const T37 v37_; const T38 v38_; const T39 v39_; const T40 v40_; const T41 v41_; const T42 v42_; const T43 v43_; const T44 v44_; const T45 v45_; }; template class ValueArray46 { public: ValueArray46(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43, T44 v44, T45 v45, T46 v46) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35), v36_(v36), v37_(v37), v38_(v38), v39_(v39), v40_(v40), v41_(v41), v42_(v42), v43_(v43), v44_(v44), v45_(v45), v46_(v46) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_), static_cast(v36_), static_cast(v37_), static_cast(v38_), static_cast(v39_), static_cast(v40_), static_cast(v41_), static_cast(v42_), static_cast(v43_), static_cast(v44_), static_cast(v45_), static_cast(v46_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray46& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; const T36 v36_; const T37 v37_; const T38 v38_; const T39 v39_; const T40 v40_; const T41 v41_; const T42 v42_; const T43 v43_; const T44 v44_; const T45 v45_; const T46 v46_; }; template class ValueArray47 { public: ValueArray47(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43, T44 v44, T45 v45, T46 v46, T47 v47) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35), v36_(v36), v37_(v37), v38_(v38), v39_(v39), v40_(v40), v41_(v41), v42_(v42), v43_(v43), v44_(v44), v45_(v45), v46_(v46), v47_(v47) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_), static_cast(v36_), static_cast(v37_), static_cast(v38_), static_cast(v39_), static_cast(v40_), static_cast(v41_), static_cast(v42_), static_cast(v43_), static_cast(v44_), static_cast(v45_), static_cast(v46_), static_cast(v47_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray47& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; const T36 v36_; const T37 v37_; const T38 v38_; const T39 v39_; const T40 v40_; const T41 v41_; const T42 v42_; const T43 v43_; const T44 v44_; const T45 v45_; const T46 v46_; const T47 v47_; }; template class ValueArray48 { public: ValueArray48(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43, T44 v44, T45 v45, T46 v46, T47 v47, T48 v48) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35), v36_(v36), v37_(v37), v38_(v38), v39_(v39), v40_(v40), v41_(v41), v42_(v42), v43_(v43), v44_(v44), v45_(v45), v46_(v46), v47_(v47), v48_(v48) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_), static_cast(v36_), static_cast(v37_), static_cast(v38_), static_cast(v39_), static_cast(v40_), static_cast(v41_), static_cast(v42_), static_cast(v43_), static_cast(v44_), static_cast(v45_), static_cast(v46_), static_cast(v47_), static_cast(v48_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray48& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; const T36 v36_; const T37 v37_; const T38 v38_; const T39 v39_; const T40 v40_; const T41 v41_; const T42 v42_; const T43 v43_; const T44 v44_; const T45 v45_; const T46 v46_; const T47 v47_; const T48 v48_; }; template class ValueArray49 { public: ValueArray49(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43, T44 v44, T45 v45, T46 v46, T47 v47, T48 v48, T49 v49) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35), v36_(v36), v37_(v37), v38_(v38), v39_(v39), v40_(v40), v41_(v41), v42_(v42), v43_(v43), v44_(v44), v45_(v45), v46_(v46), v47_(v47), v48_(v48), v49_(v49) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_), static_cast(v36_), static_cast(v37_), static_cast(v38_), static_cast(v39_), static_cast(v40_), static_cast(v41_), static_cast(v42_), static_cast(v43_), static_cast(v44_), static_cast(v45_), static_cast(v46_), static_cast(v47_), static_cast(v48_), static_cast(v49_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray49& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; const T36 v36_; const T37 v37_; const T38 v38_; const T39 v39_; const T40 v40_; const T41 v41_; const T42 v42_; const T43 v43_; const T44 v44_; const T45 v45_; const T46 v46_; const T47 v47_; const T48 v48_; const T49 v49_; }; template class ValueArray50 { public: ValueArray50(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43, T44 v44, T45 v45, T46 v46, T47 v47, T48 v48, T49 v49, T50 v50) : v1_(v1), v2_(v2), v3_(v3), v4_(v4), v5_(v5), v6_(v6), v7_(v7), v8_(v8), v9_(v9), v10_(v10), v11_(v11), v12_(v12), v13_(v13), v14_(v14), v15_(v15), v16_(v16), v17_(v17), v18_(v18), v19_(v19), v20_(v20), v21_(v21), v22_(v22), v23_(v23), v24_(v24), v25_(v25), v26_(v26), v27_(v27), v28_(v28), v29_(v29), v30_(v30), v31_(v31), v32_(v32), v33_(v33), v34_(v34), v35_(v35), v36_(v36), v37_(v37), v38_(v38), v39_(v39), v40_(v40), v41_(v41), v42_(v42), v43_(v43), v44_(v44), v45_(v45), v46_(v46), v47_(v47), v48_(v48), v49_(v49), v50_(v50) {} template operator ParamGenerator() const { const T array[] = {static_cast(v1_), static_cast(v2_), static_cast(v3_), static_cast(v4_), static_cast(v5_), static_cast(v6_), static_cast(v7_), static_cast(v8_), static_cast(v9_), static_cast(v10_), static_cast(v11_), static_cast(v12_), static_cast(v13_), static_cast(v14_), static_cast(v15_), static_cast(v16_), static_cast(v17_), static_cast(v18_), static_cast(v19_), static_cast(v20_), static_cast(v21_), static_cast(v22_), static_cast(v23_), static_cast(v24_), static_cast(v25_), static_cast(v26_), static_cast(v27_), static_cast(v28_), static_cast(v29_), static_cast(v30_), static_cast(v31_), static_cast(v32_), static_cast(v33_), static_cast(v34_), static_cast(v35_), static_cast(v36_), static_cast(v37_), static_cast(v38_), static_cast(v39_), static_cast(v40_), static_cast(v41_), static_cast(v42_), static_cast(v43_), static_cast(v44_), static_cast(v45_), static_cast(v46_), static_cast(v47_), static_cast(v48_), static_cast(v49_), static_cast(v50_)}; return ValuesIn(array); } private: // No implementation - assignment is unsupported. void operator=(const ValueArray50& other); const T1 v1_; const T2 v2_; const T3 v3_; const T4 v4_; const T5 v5_; const T6 v6_; const T7 v7_; const T8 v8_; const T9 v9_; const T10 v10_; const T11 v11_; const T12 v12_; const T13 v13_; const T14 v14_; const T15 v15_; const T16 v16_; const T17 v17_; const T18 v18_; const T19 v19_; const T20 v20_; const T21 v21_; const T22 v22_; const T23 v23_; const T24 v24_; const T25 v25_; const T26 v26_; const T27 v27_; const T28 v28_; const T29 v29_; const T30 v30_; const T31 v31_; const T32 v32_; const T33 v33_; const T34 v34_; const T35 v35_; const T36 v36_; const T37 v37_; const T38 v38_; const T39 v39_; const T40 v40_; const T41 v41_; const T42 v42_; const T43 v43_; const T44 v44_; const T45 v45_; const T46 v46_; const T47 v47_; const T48 v48_; const T49 v49_; const T50 v50_; }; # if GTEST_HAS_COMBINE // INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE. // // Generates values from the Cartesian product of values produced // by the argument generators. // template class CartesianProductGenerator2 : public ParamGeneratorInterface< ::std::tr1::tuple > { public: typedef ::std::tr1::tuple ParamType; CartesianProductGenerator2(const ParamGenerator& g1, const ParamGenerator& g2) : g1_(g1), g2_(g2) {} virtual ~CartesianProductGenerator2() {} virtual ParamIteratorInterface* Begin() const { return new Iterator(this, g1_, g1_.begin(), g2_, g2_.begin()); } virtual ParamIteratorInterface* End() const { return new Iterator(this, g1_, g1_.end(), g2_, g2_.end()); } private: class Iterator : public ParamIteratorInterface { public: Iterator(const ParamGeneratorInterface* base, const ParamGenerator& g1, const typename ParamGenerator::iterator& current1, const ParamGenerator& g2, const typename ParamGenerator::iterator& current2) : base_(base), begin1_(g1.begin()), end1_(g1.end()), current1_(current1), begin2_(g2.begin()), end2_(g2.end()), current2_(current2) { ComputeCurrentValue(); } virtual ~Iterator() {} virtual const ParamGeneratorInterface* BaseGenerator() const { return base_; } // Advance should not be called on beyond-of-range iterators // so no component iterators must be beyond end of range, either. virtual void Advance() { assert(!AtEnd()); ++current2_; if (current2_ == end2_) { current2_ = begin2_; ++current1_; } ComputeCurrentValue(); } virtual ParamIteratorInterface* Clone() const { return new Iterator(*this); } virtual const ParamType* Current() const { return ¤t_value_; } virtual bool Equals(const ParamIteratorInterface& other) const { // Having the same base generator guarantees that the other // iterator is of the same type and we can downcast. GTEST_CHECK_(BaseGenerator() == other.BaseGenerator()) << "The program attempted to compare iterators " << "from different generators." << std::endl; const Iterator* typed_other = CheckedDowncastToActualType(&other); // We must report iterators equal if they both point beyond their // respective ranges. That can happen in a variety of fashions, // so we have to consult AtEnd(). return (AtEnd() && typed_other->AtEnd()) || ( current1_ == typed_other->current1_ && current2_ == typed_other->current2_); } private: Iterator(const Iterator& other) : base_(other.base_), begin1_(other.begin1_), end1_(other.end1_), current1_(other.current1_), begin2_(other.begin2_), end2_(other.end2_), current2_(other.current2_) { ComputeCurrentValue(); } void ComputeCurrentValue() { if (!AtEnd()) current_value_ = ParamType(*current1_, *current2_); } bool AtEnd() const { // We must report iterator past the end of the range when either of the // component iterators has reached the end of its range. return current1_ == end1_ || current2_ == end2_; } // No implementation - assignment is unsupported. void operator=(const Iterator& other); const ParamGeneratorInterface* const base_; // begin[i]_ and end[i]_ define the i-th range that Iterator traverses. // current[i]_ is the actual traversing iterator. const typename ParamGenerator::iterator begin1_; const typename ParamGenerator::iterator end1_; typename ParamGenerator::iterator current1_; const typename ParamGenerator::iterator begin2_; const typename ParamGenerator::iterator end2_; typename ParamGenerator::iterator current2_; ParamType current_value_; }; // class CartesianProductGenerator2::Iterator // No implementation - assignment is unsupported. void operator=(const CartesianProductGenerator2& other); const ParamGenerator g1_; const ParamGenerator g2_; }; // class CartesianProductGenerator2 template class CartesianProductGenerator3 : public ParamGeneratorInterface< ::std::tr1::tuple > { public: typedef ::std::tr1::tuple ParamType; CartesianProductGenerator3(const ParamGenerator& g1, const ParamGenerator& g2, const ParamGenerator& g3) : g1_(g1), g2_(g2), g3_(g3) {} virtual ~CartesianProductGenerator3() {} virtual ParamIteratorInterface* Begin() const { return new Iterator(this, g1_, g1_.begin(), g2_, g2_.begin(), g3_, g3_.begin()); } virtual ParamIteratorInterface* End() const { return new Iterator(this, g1_, g1_.end(), g2_, g2_.end(), g3_, g3_.end()); } private: class Iterator : public ParamIteratorInterface { public: Iterator(const ParamGeneratorInterface* base, const ParamGenerator& g1, const typename ParamGenerator::iterator& current1, const ParamGenerator& g2, const typename ParamGenerator::iterator& current2, const ParamGenerator& g3, const typename ParamGenerator::iterator& current3) : base_(base), begin1_(g1.begin()), end1_(g1.end()), current1_(current1), begin2_(g2.begin()), end2_(g2.end()), current2_(current2), begin3_(g3.begin()), end3_(g3.end()), current3_(current3) { ComputeCurrentValue(); } virtual ~Iterator() {} virtual const ParamGeneratorInterface* BaseGenerator() const { return base_; } // Advance should not be called on beyond-of-range iterators // so no component iterators must be beyond end of range, either. virtual void Advance() { assert(!AtEnd()); ++current3_; if (current3_ == end3_) { current3_ = begin3_; ++current2_; } if (current2_ == end2_) { current2_ = begin2_; ++current1_; } ComputeCurrentValue(); } virtual ParamIteratorInterface* Clone() const { return new Iterator(*this); } virtual const ParamType* Current() const { return ¤t_value_; } virtual bool Equals(const ParamIteratorInterface& other) const { // Having the same base generator guarantees that the other // iterator is of the same type and we can downcast. GTEST_CHECK_(BaseGenerator() == other.BaseGenerator()) << "The program attempted to compare iterators " << "from different generators." << std::endl; const Iterator* typed_other = CheckedDowncastToActualType(&other); // We must report iterators equal if they both point beyond their // respective ranges. That can happen in a variety of fashions, // so we have to consult AtEnd(). return (AtEnd() && typed_other->AtEnd()) || ( current1_ == typed_other->current1_ && current2_ == typed_other->current2_ && current3_ == typed_other->current3_); } private: Iterator(const Iterator& other) : base_(other.base_), begin1_(other.begin1_), end1_(other.end1_), current1_(other.current1_), begin2_(other.begin2_), end2_(other.end2_), current2_(other.current2_), begin3_(other.begin3_), end3_(other.end3_), current3_(other.current3_) { ComputeCurrentValue(); } void ComputeCurrentValue() { if (!AtEnd()) current_value_ = ParamType(*current1_, *current2_, *current3_); } bool AtEnd() const { // We must report iterator past the end of the range when either of the // component iterators has reached the end of its range. return current1_ == end1_ || current2_ == end2_ || current3_ == end3_; } // No implementation - assignment is unsupported. void operator=(const Iterator& other); const ParamGeneratorInterface* const base_; // begin[i]_ and end[i]_ define the i-th range that Iterator traverses. // current[i]_ is the actual traversing iterator. const typename ParamGenerator::iterator begin1_; const typename ParamGenerator::iterator end1_; typename ParamGenerator::iterator current1_; const typename ParamGenerator::iterator begin2_; const typename ParamGenerator::iterator end2_; typename ParamGenerator::iterator current2_; const typename ParamGenerator::iterator begin3_; const typename ParamGenerator::iterator end3_; typename ParamGenerator::iterator current3_; ParamType current_value_; }; // class CartesianProductGenerator3::Iterator // No implementation - assignment is unsupported. void operator=(const CartesianProductGenerator3& other); const ParamGenerator g1_; const ParamGenerator g2_; const ParamGenerator g3_; }; // class CartesianProductGenerator3 template class CartesianProductGenerator4 : public ParamGeneratorInterface< ::std::tr1::tuple > { public: typedef ::std::tr1::tuple ParamType; CartesianProductGenerator4(const ParamGenerator& g1, const ParamGenerator& g2, const ParamGenerator& g3, const ParamGenerator& g4) : g1_(g1), g2_(g2), g3_(g3), g4_(g4) {} virtual ~CartesianProductGenerator4() {} virtual ParamIteratorInterface* Begin() const { return new Iterator(this, g1_, g1_.begin(), g2_, g2_.begin(), g3_, g3_.begin(), g4_, g4_.begin()); } virtual ParamIteratorInterface* End() const { return new Iterator(this, g1_, g1_.end(), g2_, g2_.end(), g3_, g3_.end(), g4_, g4_.end()); } private: class Iterator : public ParamIteratorInterface { public: Iterator(const ParamGeneratorInterface* base, const ParamGenerator& g1, const typename ParamGenerator::iterator& current1, const ParamGenerator& g2, const typename ParamGenerator::iterator& current2, const ParamGenerator& g3, const typename ParamGenerator::iterator& current3, const ParamGenerator& g4, const typename ParamGenerator::iterator& current4) : base_(base), begin1_(g1.begin()), end1_(g1.end()), current1_(current1), begin2_(g2.begin()), end2_(g2.end()), current2_(current2), begin3_(g3.begin()), end3_(g3.end()), current3_(current3), begin4_(g4.begin()), end4_(g4.end()), current4_(current4) { ComputeCurrentValue(); } virtual ~Iterator() {} virtual const ParamGeneratorInterface* BaseGenerator() const { return base_; } // Advance should not be called on beyond-of-range iterators // so no component iterators must be beyond end of range, either. virtual void Advance() { assert(!AtEnd()); ++current4_; if (current4_ == end4_) { current4_ = begin4_; ++current3_; } if (current3_ == end3_) { current3_ = begin3_; ++current2_; } if (current2_ == end2_) { current2_ = begin2_; ++current1_; } ComputeCurrentValue(); } virtual ParamIteratorInterface* Clone() const { return new Iterator(*this); } virtual const ParamType* Current() const { return ¤t_value_; } virtual bool Equals(const ParamIteratorInterface& other) const { // Having the same base generator guarantees that the other // iterator is of the same type and we can downcast. GTEST_CHECK_(BaseGenerator() == other.BaseGenerator()) << "The program attempted to compare iterators " << "from different generators." << std::endl; const Iterator* typed_other = CheckedDowncastToActualType(&other); // We must report iterators equal if they both point beyond their // respective ranges. That can happen in a variety of fashions, // so we have to consult AtEnd(). return (AtEnd() && typed_other->AtEnd()) || ( current1_ == typed_other->current1_ && current2_ == typed_other->current2_ && current3_ == typed_other->current3_ && current4_ == typed_other->current4_); } private: Iterator(const Iterator& other) : base_(other.base_), begin1_(other.begin1_), end1_(other.end1_), current1_(other.current1_), begin2_(other.begin2_), end2_(other.end2_), current2_(other.current2_), begin3_(other.begin3_), end3_(other.end3_), current3_(other.current3_), begin4_(other.begin4_), end4_(other.end4_), current4_(other.current4_) { ComputeCurrentValue(); } void ComputeCurrentValue() { if (!AtEnd()) current_value_ = ParamType(*current1_, *current2_, *current3_, *current4_); } bool AtEnd() const { // We must report iterator past the end of the range when either of the // component iterators has reached the end of its range. return current1_ == end1_ || current2_ == end2_ || current3_ == end3_ || current4_ == end4_; } // No implementation - assignment is unsupported. void operator=(const Iterator& other); const ParamGeneratorInterface* const base_; // begin[i]_ and end[i]_ define the i-th range that Iterator traverses. // current[i]_ is the actual traversing iterator. const typename ParamGenerator::iterator begin1_; const typename ParamGenerator::iterator end1_; typename ParamGenerator::iterator current1_; const typename ParamGenerator::iterator begin2_; const typename ParamGenerator::iterator end2_; typename ParamGenerator::iterator current2_; const typename ParamGenerator::iterator begin3_; const typename ParamGenerator::iterator end3_; typename ParamGenerator::iterator current3_; const typename ParamGenerator::iterator begin4_; const typename ParamGenerator::iterator end4_; typename ParamGenerator::iterator current4_; ParamType current_value_; }; // class CartesianProductGenerator4::Iterator // No implementation - assignment is unsupported. void operator=(const CartesianProductGenerator4& other); const ParamGenerator g1_; const ParamGenerator g2_; const ParamGenerator g3_; const ParamGenerator g4_; }; // class CartesianProductGenerator4 template class CartesianProductGenerator5 : public ParamGeneratorInterface< ::std::tr1::tuple > { public: typedef ::std::tr1::tuple ParamType; CartesianProductGenerator5(const ParamGenerator& g1, const ParamGenerator& g2, const ParamGenerator& g3, const ParamGenerator& g4, const ParamGenerator& g5) : g1_(g1), g2_(g2), g3_(g3), g4_(g4), g5_(g5) {} virtual ~CartesianProductGenerator5() {} virtual ParamIteratorInterface* Begin() const { return new Iterator(this, g1_, g1_.begin(), g2_, g2_.begin(), g3_, g3_.begin(), g4_, g4_.begin(), g5_, g5_.begin()); } virtual ParamIteratorInterface* End() const { return new Iterator(this, g1_, g1_.end(), g2_, g2_.end(), g3_, g3_.end(), g4_, g4_.end(), g5_, g5_.end()); } private: class Iterator : public ParamIteratorInterface { public: Iterator(const ParamGeneratorInterface* base, const ParamGenerator& g1, const typename ParamGenerator::iterator& current1, const ParamGenerator& g2, const typename ParamGenerator::iterator& current2, const ParamGenerator& g3, const typename ParamGenerator::iterator& current3, const ParamGenerator& g4, const typename ParamGenerator::iterator& current4, const ParamGenerator& g5, const typename ParamGenerator::iterator& current5) : base_(base), begin1_(g1.begin()), end1_(g1.end()), current1_(current1), begin2_(g2.begin()), end2_(g2.end()), current2_(current2), begin3_(g3.begin()), end3_(g3.end()), current3_(current3), begin4_(g4.begin()), end4_(g4.end()), current4_(current4), begin5_(g5.begin()), end5_(g5.end()), current5_(current5) { ComputeCurrentValue(); } virtual ~Iterator() {} virtual const ParamGeneratorInterface* BaseGenerator() const { return base_; } // Advance should not be called on beyond-of-range iterators // so no component iterators must be beyond end of range, either. virtual void Advance() { assert(!AtEnd()); ++current5_; if (current5_ == end5_) { current5_ = begin5_; ++current4_; } if (current4_ == end4_) { current4_ = begin4_; ++current3_; } if (current3_ == end3_) { current3_ = begin3_; ++current2_; } if (current2_ == end2_) { current2_ = begin2_; ++current1_; } ComputeCurrentValue(); } virtual ParamIteratorInterface* Clone() const { return new Iterator(*this); } virtual const ParamType* Current() const { return ¤t_value_; } virtual bool Equals(const ParamIteratorInterface& other) const { // Having the same base generator guarantees that the other // iterator is of the same type and we can downcast. GTEST_CHECK_(BaseGenerator() == other.BaseGenerator()) << "The program attempted to compare iterators " << "from different generators." << std::endl; const Iterator* typed_other = CheckedDowncastToActualType(&other); // We must report iterators equal if they both point beyond their // respective ranges. That can happen in a variety of fashions, // so we have to consult AtEnd(). return (AtEnd() && typed_other->AtEnd()) || ( current1_ == typed_other->current1_ && current2_ == typed_other->current2_ && current3_ == typed_other->current3_ && current4_ == typed_other->current4_ && current5_ == typed_other->current5_); } private: Iterator(const Iterator& other) : base_(other.base_), begin1_(other.begin1_), end1_(other.end1_), current1_(other.current1_), begin2_(other.begin2_), end2_(other.end2_), current2_(other.current2_), begin3_(other.begin3_), end3_(other.end3_), current3_(other.current3_), begin4_(other.begin4_), end4_(other.end4_), current4_(other.current4_), begin5_(other.begin5_), end5_(other.end5_), current5_(other.current5_) { ComputeCurrentValue(); } void ComputeCurrentValue() { if (!AtEnd()) current_value_ = ParamType(*current1_, *current2_, *current3_, *current4_, *current5_); } bool AtEnd() const { // We must report iterator past the end of the range when either of the // component iterators has reached the end of its range. return current1_ == end1_ || current2_ == end2_ || current3_ == end3_ || current4_ == end4_ || current5_ == end5_; } // No implementation - assignment is unsupported. void operator=(const Iterator& other); const ParamGeneratorInterface* const base_; // begin[i]_ and end[i]_ define the i-th range that Iterator traverses. // current[i]_ is the actual traversing iterator. const typename ParamGenerator::iterator begin1_; const typename ParamGenerator::iterator end1_; typename ParamGenerator::iterator current1_; const typename ParamGenerator::iterator begin2_; const typename ParamGenerator::iterator end2_; typename ParamGenerator::iterator current2_; const typename ParamGenerator::iterator begin3_; const typename ParamGenerator::iterator end3_; typename ParamGenerator::iterator current3_; const typename ParamGenerator::iterator begin4_; const typename ParamGenerator::iterator end4_; typename ParamGenerator::iterator current4_; const typename ParamGenerator::iterator begin5_; const typename ParamGenerator::iterator end5_; typename ParamGenerator::iterator current5_; ParamType current_value_; }; // class CartesianProductGenerator5::Iterator // No implementation - assignment is unsupported. void operator=(const CartesianProductGenerator5& other); const ParamGenerator g1_; const ParamGenerator g2_; const ParamGenerator g3_; const ParamGenerator g4_; const ParamGenerator g5_; }; // class CartesianProductGenerator5 template class CartesianProductGenerator6 : public ParamGeneratorInterface< ::std::tr1::tuple > { public: typedef ::std::tr1::tuple ParamType; CartesianProductGenerator6(const ParamGenerator& g1, const ParamGenerator& g2, const ParamGenerator& g3, const ParamGenerator& g4, const ParamGenerator& g5, const ParamGenerator& g6) : g1_(g1), g2_(g2), g3_(g3), g4_(g4), g5_(g5), g6_(g6) {} virtual ~CartesianProductGenerator6() {} virtual ParamIteratorInterface* Begin() const { return new Iterator(this, g1_, g1_.begin(), g2_, g2_.begin(), g3_, g3_.begin(), g4_, g4_.begin(), g5_, g5_.begin(), g6_, g6_.begin()); } virtual ParamIteratorInterface* End() const { return new Iterator(this, g1_, g1_.end(), g2_, g2_.end(), g3_, g3_.end(), g4_, g4_.end(), g5_, g5_.end(), g6_, g6_.end()); } private: class Iterator : public ParamIteratorInterface { public: Iterator(const ParamGeneratorInterface* base, const ParamGenerator& g1, const typename ParamGenerator::iterator& current1, const ParamGenerator& g2, const typename ParamGenerator::iterator& current2, const ParamGenerator& g3, const typename ParamGenerator::iterator& current3, const ParamGenerator& g4, const typename ParamGenerator::iterator& current4, const ParamGenerator& g5, const typename ParamGenerator::iterator& current5, const ParamGenerator& g6, const typename ParamGenerator::iterator& current6) : base_(base), begin1_(g1.begin()), end1_(g1.end()), current1_(current1), begin2_(g2.begin()), end2_(g2.end()), current2_(current2), begin3_(g3.begin()), end3_(g3.end()), current3_(current3), begin4_(g4.begin()), end4_(g4.end()), current4_(current4), begin5_(g5.begin()), end5_(g5.end()), current5_(current5), begin6_(g6.begin()), end6_(g6.end()), current6_(current6) { ComputeCurrentValue(); } virtual ~Iterator() {} virtual const ParamGeneratorInterface* BaseGenerator() const { return base_; } // Advance should not be called on beyond-of-range iterators // so no component iterators must be beyond end of range, either. virtual void Advance() { assert(!AtEnd()); ++current6_; if (current6_ == end6_) { current6_ = begin6_; ++current5_; } if (current5_ == end5_) { current5_ = begin5_; ++current4_; } if (current4_ == end4_) { current4_ = begin4_; ++current3_; } if (current3_ == end3_) { current3_ = begin3_; ++current2_; } if (current2_ == end2_) { current2_ = begin2_; ++current1_; } ComputeCurrentValue(); } virtual ParamIteratorInterface* Clone() const { return new Iterator(*this); } virtual const ParamType* Current() const { return ¤t_value_; } virtual bool Equals(const ParamIteratorInterface& other) const { // Having the same base generator guarantees that the other // iterator is of the same type and we can downcast. GTEST_CHECK_(BaseGenerator() == other.BaseGenerator()) << "The program attempted to compare iterators " << "from different generators." << std::endl; const Iterator* typed_other = CheckedDowncastToActualType(&other); // We must report iterators equal if they both point beyond their // respective ranges. That can happen in a variety of fashions, // so we have to consult AtEnd(). return (AtEnd() && typed_other->AtEnd()) || ( current1_ == typed_other->current1_ && current2_ == typed_other->current2_ && current3_ == typed_other->current3_ && current4_ == typed_other->current4_ && current5_ == typed_other->current5_ && current6_ == typed_other->current6_); } private: Iterator(const Iterator& other) : base_(other.base_), begin1_(other.begin1_), end1_(other.end1_), current1_(other.current1_), begin2_(other.begin2_), end2_(other.end2_), current2_(other.current2_), begin3_(other.begin3_), end3_(other.end3_), current3_(other.current3_), begin4_(other.begin4_), end4_(other.end4_), current4_(other.current4_), begin5_(other.begin5_), end5_(other.end5_), current5_(other.current5_), begin6_(other.begin6_), end6_(other.end6_), current6_(other.current6_) { ComputeCurrentValue(); } void ComputeCurrentValue() { if (!AtEnd()) current_value_ = ParamType(*current1_, *current2_, *current3_, *current4_, *current5_, *current6_); } bool AtEnd() const { // We must report iterator past the end of the range when either of the // component iterators has reached the end of its range. return current1_ == end1_ || current2_ == end2_ || current3_ == end3_ || current4_ == end4_ || current5_ == end5_ || current6_ == end6_; } // No implementation - assignment is unsupported. void operator=(const Iterator& other); const ParamGeneratorInterface* const base_; // begin[i]_ and end[i]_ define the i-th range that Iterator traverses. // current[i]_ is the actual traversing iterator. const typename ParamGenerator::iterator begin1_; const typename ParamGenerator::iterator end1_; typename ParamGenerator::iterator current1_; const typename ParamGenerator::iterator begin2_; const typename ParamGenerator::iterator end2_; typename ParamGenerator::iterator current2_; const typename ParamGenerator::iterator begin3_; const typename ParamGenerator::iterator end3_; typename ParamGenerator::iterator current3_; const typename ParamGenerator::iterator begin4_; const typename ParamGenerator::iterator end4_; typename ParamGenerator::iterator current4_; const typename ParamGenerator::iterator begin5_; const typename ParamGenerator::iterator end5_; typename ParamGenerator::iterator current5_; const typename ParamGenerator::iterator begin6_; const typename ParamGenerator::iterator end6_; typename ParamGenerator::iterator current6_; ParamType current_value_; }; // class CartesianProductGenerator6::Iterator // No implementation - assignment is unsupported. void operator=(const CartesianProductGenerator6& other); const ParamGenerator g1_; const ParamGenerator g2_; const ParamGenerator g3_; const ParamGenerator g4_; const ParamGenerator g5_; const ParamGenerator g6_; }; // class CartesianProductGenerator6 template class CartesianProductGenerator7 : public ParamGeneratorInterface< ::std::tr1::tuple > { public: typedef ::std::tr1::tuple ParamType; CartesianProductGenerator7(const ParamGenerator& g1, const ParamGenerator& g2, const ParamGenerator& g3, const ParamGenerator& g4, const ParamGenerator& g5, const ParamGenerator& g6, const ParamGenerator& g7) : g1_(g1), g2_(g2), g3_(g3), g4_(g4), g5_(g5), g6_(g6), g7_(g7) {} virtual ~CartesianProductGenerator7() {} virtual ParamIteratorInterface* Begin() const { return new Iterator(this, g1_, g1_.begin(), g2_, g2_.begin(), g3_, g3_.begin(), g4_, g4_.begin(), g5_, g5_.begin(), g6_, g6_.begin(), g7_, g7_.begin()); } virtual ParamIteratorInterface* End() const { return new Iterator(this, g1_, g1_.end(), g2_, g2_.end(), g3_, g3_.end(), g4_, g4_.end(), g5_, g5_.end(), g6_, g6_.end(), g7_, g7_.end()); } private: class Iterator : public ParamIteratorInterface { public: Iterator(const ParamGeneratorInterface* base, const ParamGenerator& g1, const typename ParamGenerator::iterator& current1, const ParamGenerator& g2, const typename ParamGenerator::iterator& current2, const ParamGenerator& g3, const typename ParamGenerator::iterator& current3, const ParamGenerator& g4, const typename ParamGenerator::iterator& current4, const ParamGenerator& g5, const typename ParamGenerator::iterator& current5, const ParamGenerator& g6, const typename ParamGenerator::iterator& current6, const ParamGenerator& g7, const typename ParamGenerator::iterator& current7) : base_(base), begin1_(g1.begin()), end1_(g1.end()), current1_(current1), begin2_(g2.begin()), end2_(g2.end()), current2_(current2), begin3_(g3.begin()), end3_(g3.end()), current3_(current3), begin4_(g4.begin()), end4_(g4.end()), current4_(current4), begin5_(g5.begin()), end5_(g5.end()), current5_(current5), begin6_(g6.begin()), end6_(g6.end()), current6_(current6), begin7_(g7.begin()), end7_(g7.end()), current7_(current7) { ComputeCurrentValue(); } virtual ~Iterator() {} virtual const ParamGeneratorInterface* BaseGenerator() const { return base_; } // Advance should not be called on beyond-of-range iterators // so no component iterators must be beyond end of range, either. virtual void Advance() { assert(!AtEnd()); ++current7_; if (current7_ == end7_) { current7_ = begin7_; ++current6_; } if (current6_ == end6_) { current6_ = begin6_; ++current5_; } if (current5_ == end5_) { current5_ = begin5_; ++current4_; } if (current4_ == end4_) { current4_ = begin4_; ++current3_; } if (current3_ == end3_) { current3_ = begin3_; ++current2_; } if (current2_ == end2_) { current2_ = begin2_; ++current1_; } ComputeCurrentValue(); } virtual ParamIteratorInterface* Clone() const { return new Iterator(*this); } virtual const ParamType* Current() const { return ¤t_value_; } virtual bool Equals(const ParamIteratorInterface& other) const { // Having the same base generator guarantees that the other // iterator is of the same type and we can downcast. GTEST_CHECK_(BaseGenerator() == other.BaseGenerator()) << "The program attempted to compare iterators " << "from different generators." << std::endl; const Iterator* typed_other = CheckedDowncastToActualType(&other); // We must report iterators equal if they both point beyond their // respective ranges. That can happen in a variety of fashions, // so we have to consult AtEnd(). return (AtEnd() && typed_other->AtEnd()) || ( current1_ == typed_other->current1_ && current2_ == typed_other->current2_ && current3_ == typed_other->current3_ && current4_ == typed_other->current4_ && current5_ == typed_other->current5_ && current6_ == typed_other->current6_ && current7_ == typed_other->current7_); } private: Iterator(const Iterator& other) : base_(other.base_), begin1_(other.begin1_), end1_(other.end1_), current1_(other.current1_), begin2_(other.begin2_), end2_(other.end2_), current2_(other.current2_), begin3_(other.begin3_), end3_(other.end3_), current3_(other.current3_), begin4_(other.begin4_), end4_(other.end4_), current4_(other.current4_), begin5_(other.begin5_), end5_(other.end5_), current5_(other.current5_), begin6_(other.begin6_), end6_(other.end6_), current6_(other.current6_), begin7_(other.begin7_), end7_(other.end7_), current7_(other.current7_) { ComputeCurrentValue(); } void ComputeCurrentValue() { if (!AtEnd()) current_value_ = ParamType(*current1_, *current2_, *current3_, *current4_, *current5_, *current6_, *current7_); } bool AtEnd() const { // We must report iterator past the end of the range when either of the // component iterators has reached the end of its range. return current1_ == end1_ || current2_ == end2_ || current3_ == end3_ || current4_ == end4_ || current5_ == end5_ || current6_ == end6_ || current7_ == end7_; } // No implementation - assignment is unsupported. void operator=(const Iterator& other); const ParamGeneratorInterface* const base_; // begin[i]_ and end[i]_ define the i-th range that Iterator traverses. // current[i]_ is the actual traversing iterator. const typename ParamGenerator::iterator begin1_; const typename ParamGenerator::iterator end1_; typename ParamGenerator::iterator current1_; const typename ParamGenerator::iterator begin2_; const typename ParamGenerator::iterator end2_; typename ParamGenerator::iterator current2_; const typename ParamGenerator::iterator begin3_; const typename ParamGenerator::iterator end3_; typename ParamGenerator::iterator current3_; const typename ParamGenerator::iterator begin4_; const typename ParamGenerator::iterator end4_; typename ParamGenerator::iterator current4_; const typename ParamGenerator::iterator begin5_; const typename ParamGenerator::iterator end5_; typename ParamGenerator::iterator current5_; const typename ParamGenerator::iterator begin6_; const typename ParamGenerator::iterator end6_; typename ParamGenerator::iterator current6_; const typename ParamGenerator::iterator begin7_; const typename ParamGenerator::iterator end7_; typename ParamGenerator::iterator current7_; ParamType current_value_; }; // class CartesianProductGenerator7::Iterator // No implementation - assignment is unsupported. void operator=(const CartesianProductGenerator7& other); const ParamGenerator g1_; const ParamGenerator g2_; const ParamGenerator g3_; const ParamGenerator g4_; const ParamGenerator g5_; const ParamGenerator g6_; const ParamGenerator g7_; }; // class CartesianProductGenerator7 template class CartesianProductGenerator8 : public ParamGeneratorInterface< ::std::tr1::tuple > { public: typedef ::std::tr1::tuple ParamType; CartesianProductGenerator8(const ParamGenerator& g1, const ParamGenerator& g2, const ParamGenerator& g3, const ParamGenerator& g4, const ParamGenerator& g5, const ParamGenerator& g6, const ParamGenerator& g7, const ParamGenerator& g8) : g1_(g1), g2_(g2), g3_(g3), g4_(g4), g5_(g5), g6_(g6), g7_(g7), g8_(g8) {} virtual ~CartesianProductGenerator8() {} virtual ParamIteratorInterface* Begin() const { return new Iterator(this, g1_, g1_.begin(), g2_, g2_.begin(), g3_, g3_.begin(), g4_, g4_.begin(), g5_, g5_.begin(), g6_, g6_.begin(), g7_, g7_.begin(), g8_, g8_.begin()); } virtual ParamIteratorInterface* End() const { return new Iterator(this, g1_, g1_.end(), g2_, g2_.end(), g3_, g3_.end(), g4_, g4_.end(), g5_, g5_.end(), g6_, g6_.end(), g7_, g7_.end(), g8_, g8_.end()); } private: class Iterator : public ParamIteratorInterface { public: Iterator(const ParamGeneratorInterface* base, const ParamGenerator& g1, const typename ParamGenerator::iterator& current1, const ParamGenerator& g2, const typename ParamGenerator::iterator& current2, const ParamGenerator& g3, const typename ParamGenerator::iterator& current3, const ParamGenerator& g4, const typename ParamGenerator::iterator& current4, const ParamGenerator& g5, const typename ParamGenerator::iterator& current5, const ParamGenerator& g6, const typename ParamGenerator::iterator& current6, const ParamGenerator& g7, const typename ParamGenerator::iterator& current7, const ParamGenerator& g8, const typename ParamGenerator::iterator& current8) : base_(base), begin1_(g1.begin()), end1_(g1.end()), current1_(current1), begin2_(g2.begin()), end2_(g2.end()), current2_(current2), begin3_(g3.begin()), end3_(g3.end()), current3_(current3), begin4_(g4.begin()), end4_(g4.end()), current4_(current4), begin5_(g5.begin()), end5_(g5.end()), current5_(current5), begin6_(g6.begin()), end6_(g6.end()), current6_(current6), begin7_(g7.begin()), end7_(g7.end()), current7_(current7), begin8_(g8.begin()), end8_(g8.end()), current8_(current8) { ComputeCurrentValue(); } virtual ~Iterator() {} virtual const ParamGeneratorInterface* BaseGenerator() const { return base_; } // Advance should not be called on beyond-of-range iterators // so no component iterators must be beyond end of range, either. virtual void Advance() { assert(!AtEnd()); ++current8_; if (current8_ == end8_) { current8_ = begin8_; ++current7_; } if (current7_ == end7_) { current7_ = begin7_; ++current6_; } if (current6_ == end6_) { current6_ = begin6_; ++current5_; } if (current5_ == end5_) { current5_ = begin5_; ++current4_; } if (current4_ == end4_) { current4_ = begin4_; ++current3_; } if (current3_ == end3_) { current3_ = begin3_; ++current2_; } if (current2_ == end2_) { current2_ = begin2_; ++current1_; } ComputeCurrentValue(); } virtual ParamIteratorInterface* Clone() const { return new Iterator(*this); } virtual const ParamType* Current() const { return ¤t_value_; } virtual bool Equals(const ParamIteratorInterface& other) const { // Having the same base generator guarantees that the other // iterator is of the same type and we can downcast. GTEST_CHECK_(BaseGenerator() == other.BaseGenerator()) << "The program attempted to compare iterators " << "from different generators." << std::endl; const Iterator* typed_other = CheckedDowncastToActualType(&other); // We must report iterators equal if they both point beyond their // respective ranges. That can happen in a variety of fashions, // so we have to consult AtEnd(). return (AtEnd() && typed_other->AtEnd()) || ( current1_ == typed_other->current1_ && current2_ == typed_other->current2_ && current3_ == typed_other->current3_ && current4_ == typed_other->current4_ && current5_ == typed_other->current5_ && current6_ == typed_other->current6_ && current7_ == typed_other->current7_ && current8_ == typed_other->current8_); } private: Iterator(const Iterator& other) : base_(other.base_), begin1_(other.begin1_), end1_(other.end1_), current1_(other.current1_), begin2_(other.begin2_), end2_(other.end2_), current2_(other.current2_), begin3_(other.begin3_), end3_(other.end3_), current3_(other.current3_), begin4_(other.begin4_), end4_(other.end4_), current4_(other.current4_), begin5_(other.begin5_), end5_(other.end5_), current5_(other.current5_), begin6_(other.begin6_), end6_(other.end6_), current6_(other.current6_), begin7_(other.begin7_), end7_(other.end7_), current7_(other.current7_), begin8_(other.begin8_), end8_(other.end8_), current8_(other.current8_) { ComputeCurrentValue(); } void ComputeCurrentValue() { if (!AtEnd()) current_value_ = ParamType(*current1_, *current2_, *current3_, *current4_, *current5_, *current6_, *current7_, *current8_); } bool AtEnd() const { // We must report iterator past the end of the range when either of the // component iterators has reached the end of its range. return current1_ == end1_ || current2_ == end2_ || current3_ == end3_ || current4_ == end4_ || current5_ == end5_ || current6_ == end6_ || current7_ == end7_ || current8_ == end8_; } // No implementation - assignment is unsupported. void operator=(const Iterator& other); const ParamGeneratorInterface* const base_; // begin[i]_ and end[i]_ define the i-th range that Iterator traverses. // current[i]_ is the actual traversing iterator. const typename ParamGenerator::iterator begin1_; const typename ParamGenerator::iterator end1_; typename ParamGenerator::iterator current1_; const typename ParamGenerator::iterator begin2_; const typename ParamGenerator::iterator end2_; typename ParamGenerator::iterator current2_; const typename ParamGenerator::iterator begin3_; const typename ParamGenerator::iterator end3_; typename ParamGenerator::iterator current3_; const typename ParamGenerator::iterator begin4_; const typename ParamGenerator::iterator end4_; typename ParamGenerator::iterator current4_; const typename ParamGenerator::iterator begin5_; const typename ParamGenerator::iterator end5_; typename ParamGenerator::iterator current5_; const typename ParamGenerator::iterator begin6_; const typename ParamGenerator::iterator end6_; typename ParamGenerator::iterator current6_; const typename ParamGenerator::iterator begin7_; const typename ParamGenerator::iterator end7_; typename ParamGenerator::iterator current7_; const typename ParamGenerator::iterator begin8_; const typename ParamGenerator::iterator end8_; typename ParamGenerator::iterator current8_; ParamType current_value_; }; // class CartesianProductGenerator8::Iterator // No implementation - assignment is unsupported. void operator=(const CartesianProductGenerator8& other); const ParamGenerator g1_; const ParamGenerator g2_; const ParamGenerator g3_; const ParamGenerator g4_; const ParamGenerator g5_; const ParamGenerator g6_; const ParamGenerator g7_; const ParamGenerator g8_; }; // class CartesianProductGenerator8 template class CartesianProductGenerator9 : public ParamGeneratorInterface< ::std::tr1::tuple > { public: typedef ::std::tr1::tuple ParamType; CartesianProductGenerator9(const ParamGenerator& g1, const ParamGenerator& g2, const ParamGenerator& g3, const ParamGenerator& g4, const ParamGenerator& g5, const ParamGenerator& g6, const ParamGenerator& g7, const ParamGenerator& g8, const ParamGenerator& g9) : g1_(g1), g2_(g2), g3_(g3), g4_(g4), g5_(g5), g6_(g6), g7_(g7), g8_(g8), g9_(g9) {} virtual ~CartesianProductGenerator9() {} virtual ParamIteratorInterface* Begin() const { return new Iterator(this, g1_, g1_.begin(), g2_, g2_.begin(), g3_, g3_.begin(), g4_, g4_.begin(), g5_, g5_.begin(), g6_, g6_.begin(), g7_, g7_.begin(), g8_, g8_.begin(), g9_, g9_.begin()); } virtual ParamIteratorInterface* End() const { return new Iterator(this, g1_, g1_.end(), g2_, g2_.end(), g3_, g3_.end(), g4_, g4_.end(), g5_, g5_.end(), g6_, g6_.end(), g7_, g7_.end(), g8_, g8_.end(), g9_, g9_.end()); } private: class Iterator : public ParamIteratorInterface { public: Iterator(const ParamGeneratorInterface* base, const ParamGenerator& g1, const typename ParamGenerator::iterator& current1, const ParamGenerator& g2, const typename ParamGenerator::iterator& current2, const ParamGenerator& g3, const typename ParamGenerator::iterator& current3, const ParamGenerator& g4, const typename ParamGenerator::iterator& current4, const ParamGenerator& g5, const typename ParamGenerator::iterator& current5, const ParamGenerator& g6, const typename ParamGenerator::iterator& current6, const ParamGenerator& g7, const typename ParamGenerator::iterator& current7, const ParamGenerator& g8, const typename ParamGenerator::iterator& current8, const ParamGenerator& g9, const typename ParamGenerator::iterator& current9) : base_(base), begin1_(g1.begin()), end1_(g1.end()), current1_(current1), begin2_(g2.begin()), end2_(g2.end()), current2_(current2), begin3_(g3.begin()), end3_(g3.end()), current3_(current3), begin4_(g4.begin()), end4_(g4.end()), current4_(current4), begin5_(g5.begin()), end5_(g5.end()), current5_(current5), begin6_(g6.begin()), end6_(g6.end()), current6_(current6), begin7_(g7.begin()), end7_(g7.end()), current7_(current7), begin8_(g8.begin()), end8_(g8.end()), current8_(current8), begin9_(g9.begin()), end9_(g9.end()), current9_(current9) { ComputeCurrentValue(); } virtual ~Iterator() {} virtual const ParamGeneratorInterface* BaseGenerator() const { return base_; } // Advance should not be called on beyond-of-range iterators // so no component iterators must be beyond end of range, either. virtual void Advance() { assert(!AtEnd()); ++current9_; if (current9_ == end9_) { current9_ = begin9_; ++current8_; } if (current8_ == end8_) { current8_ = begin8_; ++current7_; } if (current7_ == end7_) { current7_ = begin7_; ++current6_; } if (current6_ == end6_) { current6_ = begin6_; ++current5_; } if (current5_ == end5_) { current5_ = begin5_; ++current4_; } if (current4_ == end4_) { current4_ = begin4_; ++current3_; } if (current3_ == end3_) { current3_ = begin3_; ++current2_; } if (current2_ == end2_) { current2_ = begin2_; ++current1_; } ComputeCurrentValue(); } virtual ParamIteratorInterface* Clone() const { return new Iterator(*this); } virtual const ParamType* Current() const { return ¤t_value_; } virtual bool Equals(const ParamIteratorInterface& other) const { // Having the same base generator guarantees that the other // iterator is of the same type and we can downcast. GTEST_CHECK_(BaseGenerator() == other.BaseGenerator()) << "The program attempted to compare iterators " << "from different generators." << std::endl; const Iterator* typed_other = CheckedDowncastToActualType(&other); // We must report iterators equal if they both point beyond their // respective ranges. That can happen in a variety of fashions, // so we have to consult AtEnd(). return (AtEnd() && typed_other->AtEnd()) || ( current1_ == typed_other->current1_ && current2_ == typed_other->current2_ && current3_ == typed_other->current3_ && current4_ == typed_other->current4_ && current5_ == typed_other->current5_ && current6_ == typed_other->current6_ && current7_ == typed_other->current7_ && current8_ == typed_other->current8_ && current9_ == typed_other->current9_); } private: Iterator(const Iterator& other) : base_(other.base_), begin1_(other.begin1_), end1_(other.end1_), current1_(other.current1_), begin2_(other.begin2_), end2_(other.end2_), current2_(other.current2_), begin3_(other.begin3_), end3_(other.end3_), current3_(other.current3_), begin4_(other.begin4_), end4_(other.end4_), current4_(other.current4_), begin5_(other.begin5_), end5_(other.end5_), current5_(other.current5_), begin6_(other.begin6_), end6_(other.end6_), current6_(other.current6_), begin7_(other.begin7_), end7_(other.end7_), current7_(other.current7_), begin8_(other.begin8_), end8_(other.end8_), current8_(other.current8_), begin9_(other.begin9_), end9_(other.end9_), current9_(other.current9_) { ComputeCurrentValue(); } void ComputeCurrentValue() { if (!AtEnd()) current_value_ = ParamType(*current1_, *current2_, *current3_, *current4_, *current5_, *current6_, *current7_, *current8_, *current9_); } bool AtEnd() const { // We must report iterator past the end of the range when either of the // component iterators has reached the end of its range. return current1_ == end1_ || current2_ == end2_ || current3_ == end3_ || current4_ == end4_ || current5_ == end5_ || current6_ == end6_ || current7_ == end7_ || current8_ == end8_ || current9_ == end9_; } // No implementation - assignment is unsupported. void operator=(const Iterator& other); const ParamGeneratorInterface* const base_; // begin[i]_ and end[i]_ define the i-th range that Iterator traverses. // current[i]_ is the actual traversing iterator. const typename ParamGenerator::iterator begin1_; const typename ParamGenerator::iterator end1_; typename ParamGenerator::iterator current1_; const typename ParamGenerator::iterator begin2_; const typename ParamGenerator::iterator end2_; typename ParamGenerator::iterator current2_; const typename ParamGenerator::iterator begin3_; const typename ParamGenerator::iterator end3_; typename ParamGenerator::iterator current3_; const typename ParamGenerator::iterator begin4_; const typename ParamGenerator::iterator end4_; typename ParamGenerator::iterator current4_; const typename ParamGenerator::iterator begin5_; const typename ParamGenerator::iterator end5_; typename ParamGenerator::iterator current5_; const typename ParamGenerator::iterator begin6_; const typename ParamGenerator::iterator end6_; typename ParamGenerator::iterator current6_; const typename ParamGenerator::iterator begin7_; const typename ParamGenerator::iterator end7_; typename ParamGenerator::iterator current7_; const typename ParamGenerator::iterator begin8_; const typename ParamGenerator::iterator end8_; typename ParamGenerator::iterator current8_; const typename ParamGenerator::iterator begin9_; const typename ParamGenerator::iterator end9_; typename ParamGenerator::iterator current9_; ParamType current_value_; }; // class CartesianProductGenerator9::Iterator // No implementation - assignment is unsupported. void operator=(const CartesianProductGenerator9& other); const ParamGenerator g1_; const ParamGenerator g2_; const ParamGenerator g3_; const ParamGenerator g4_; const ParamGenerator g5_; const ParamGenerator g6_; const ParamGenerator g7_; const ParamGenerator g8_; const ParamGenerator g9_; }; // class CartesianProductGenerator9 template class CartesianProductGenerator10 : public ParamGeneratorInterface< ::std::tr1::tuple > { public: typedef ::std::tr1::tuple ParamType; CartesianProductGenerator10(const ParamGenerator& g1, const ParamGenerator& g2, const ParamGenerator& g3, const ParamGenerator& g4, const ParamGenerator& g5, const ParamGenerator& g6, const ParamGenerator& g7, const ParamGenerator& g8, const ParamGenerator& g9, const ParamGenerator& g10) : g1_(g1), g2_(g2), g3_(g3), g4_(g4), g5_(g5), g6_(g6), g7_(g7), g8_(g8), g9_(g9), g10_(g10) {} virtual ~CartesianProductGenerator10() {} virtual ParamIteratorInterface* Begin() const { return new Iterator(this, g1_, g1_.begin(), g2_, g2_.begin(), g3_, g3_.begin(), g4_, g4_.begin(), g5_, g5_.begin(), g6_, g6_.begin(), g7_, g7_.begin(), g8_, g8_.begin(), g9_, g9_.begin(), g10_, g10_.begin()); } virtual ParamIteratorInterface* End() const { return new Iterator(this, g1_, g1_.end(), g2_, g2_.end(), g3_, g3_.end(), g4_, g4_.end(), g5_, g5_.end(), g6_, g6_.end(), g7_, g7_.end(), g8_, g8_.end(), g9_, g9_.end(), g10_, g10_.end()); } private: class Iterator : public ParamIteratorInterface { public: Iterator(const ParamGeneratorInterface* base, const ParamGenerator& g1, const typename ParamGenerator::iterator& current1, const ParamGenerator& g2, const typename ParamGenerator::iterator& current2, const ParamGenerator& g3, const typename ParamGenerator::iterator& current3, const ParamGenerator& g4, const typename ParamGenerator::iterator& current4, const ParamGenerator& g5, const typename ParamGenerator::iterator& current5, const ParamGenerator& g6, const typename ParamGenerator::iterator& current6, const ParamGenerator& g7, const typename ParamGenerator::iterator& current7, const ParamGenerator& g8, const typename ParamGenerator::iterator& current8, const ParamGenerator& g9, const typename ParamGenerator::iterator& current9, const ParamGenerator& g10, const typename ParamGenerator::iterator& current10) : base_(base), begin1_(g1.begin()), end1_(g1.end()), current1_(current1), begin2_(g2.begin()), end2_(g2.end()), current2_(current2), begin3_(g3.begin()), end3_(g3.end()), current3_(current3), begin4_(g4.begin()), end4_(g4.end()), current4_(current4), begin5_(g5.begin()), end5_(g5.end()), current5_(current5), begin6_(g6.begin()), end6_(g6.end()), current6_(current6), begin7_(g7.begin()), end7_(g7.end()), current7_(current7), begin8_(g8.begin()), end8_(g8.end()), current8_(current8), begin9_(g9.begin()), end9_(g9.end()), current9_(current9), begin10_(g10.begin()), end10_(g10.end()), current10_(current10) { ComputeCurrentValue(); } virtual ~Iterator() {} virtual const ParamGeneratorInterface* BaseGenerator() const { return base_; } // Advance should not be called on beyond-of-range iterators // so no component iterators must be beyond end of range, either. virtual void Advance() { assert(!AtEnd()); ++current10_; if (current10_ == end10_) { current10_ = begin10_; ++current9_; } if (current9_ == end9_) { current9_ = begin9_; ++current8_; } if (current8_ == end8_) { current8_ = begin8_; ++current7_; } if (current7_ == end7_) { current7_ = begin7_; ++current6_; } if (current6_ == end6_) { current6_ = begin6_; ++current5_; } if (current5_ == end5_) { current5_ = begin5_; ++current4_; } if (current4_ == end4_) { current4_ = begin4_; ++current3_; } if (current3_ == end3_) { current3_ = begin3_; ++current2_; } if (current2_ == end2_) { current2_ = begin2_; ++current1_; } ComputeCurrentValue(); } virtual ParamIteratorInterface* Clone() const { return new Iterator(*this); } virtual const ParamType* Current() const { return ¤t_value_; } virtual bool Equals(const ParamIteratorInterface& other) const { // Having the same base generator guarantees that the other // iterator is of the same type and we can downcast. GTEST_CHECK_(BaseGenerator() == other.BaseGenerator()) << "The program attempted to compare iterators " << "from different generators." << std::endl; const Iterator* typed_other = CheckedDowncastToActualType(&other); // We must report iterators equal if they both point beyond their // respective ranges. That can happen in a variety of fashions, // so we have to consult AtEnd(). return (AtEnd() && typed_other->AtEnd()) || ( current1_ == typed_other->current1_ && current2_ == typed_other->current2_ && current3_ == typed_other->current3_ && current4_ == typed_other->current4_ && current5_ == typed_other->current5_ && current6_ == typed_other->current6_ && current7_ == typed_other->current7_ && current8_ == typed_other->current8_ && current9_ == typed_other->current9_ && current10_ == typed_other->current10_); } private: Iterator(const Iterator& other) : base_(other.base_), begin1_(other.begin1_), end1_(other.end1_), current1_(other.current1_), begin2_(other.begin2_), end2_(other.end2_), current2_(other.current2_), begin3_(other.begin3_), end3_(other.end3_), current3_(other.current3_), begin4_(other.begin4_), end4_(other.end4_), current4_(other.current4_), begin5_(other.begin5_), end5_(other.end5_), current5_(other.current5_), begin6_(other.begin6_), end6_(other.end6_), current6_(other.current6_), begin7_(other.begin7_), end7_(other.end7_), current7_(other.current7_), begin8_(other.begin8_), end8_(other.end8_), current8_(other.current8_), begin9_(other.begin9_), end9_(other.end9_), current9_(other.current9_), begin10_(other.begin10_), end10_(other.end10_), current10_(other.current10_) { ComputeCurrentValue(); } void ComputeCurrentValue() { if (!AtEnd()) current_value_ = ParamType(*current1_, *current2_, *current3_, *current4_, *current5_, *current6_, *current7_, *current8_, *current9_, *current10_); } bool AtEnd() const { // We must report iterator past the end of the range when either of the // component iterators has reached the end of its range. return current1_ == end1_ || current2_ == end2_ || current3_ == end3_ || current4_ == end4_ || current5_ == end5_ || current6_ == end6_ || current7_ == end7_ || current8_ == end8_ || current9_ == end9_ || current10_ == end10_; } // No implementation - assignment is unsupported. void operator=(const Iterator& other); const ParamGeneratorInterface* const base_; // begin[i]_ and end[i]_ define the i-th range that Iterator traverses. // current[i]_ is the actual traversing iterator. const typename ParamGenerator::iterator begin1_; const typename ParamGenerator::iterator end1_; typename ParamGenerator::iterator current1_; const typename ParamGenerator::iterator begin2_; const typename ParamGenerator::iterator end2_; typename ParamGenerator::iterator current2_; const typename ParamGenerator::iterator begin3_; const typename ParamGenerator::iterator end3_; typename ParamGenerator::iterator current3_; const typename ParamGenerator::iterator begin4_; const typename ParamGenerator::iterator end4_; typename ParamGenerator::iterator current4_; const typename ParamGenerator::iterator begin5_; const typename ParamGenerator::iterator end5_; typename ParamGenerator::iterator current5_; const typename ParamGenerator::iterator begin6_; const typename ParamGenerator::iterator end6_; typename ParamGenerator::iterator current6_; const typename ParamGenerator::iterator begin7_; const typename ParamGenerator::iterator end7_; typename ParamGenerator::iterator current7_; const typename ParamGenerator::iterator begin8_; const typename ParamGenerator::iterator end8_; typename ParamGenerator::iterator current8_; const typename ParamGenerator::iterator begin9_; const typename ParamGenerator::iterator end9_; typename ParamGenerator::iterator current9_; const typename ParamGenerator::iterator begin10_; const typename ParamGenerator::iterator end10_; typename ParamGenerator::iterator current10_; ParamType current_value_; }; // class CartesianProductGenerator10::Iterator // No implementation - assignment is unsupported. void operator=(const CartesianProductGenerator10& other); const ParamGenerator g1_; const ParamGenerator g2_; const ParamGenerator g3_; const ParamGenerator g4_; const ParamGenerator g5_; const ParamGenerator g6_; const ParamGenerator g7_; const ParamGenerator g8_; const ParamGenerator g9_; const ParamGenerator g10_; }; // class CartesianProductGenerator10 // INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE. // // Helper classes providing Combine() with polymorphic features. They allow // casting CartesianProductGeneratorN to ParamGenerator if T is // convertible to U. // template class CartesianProductHolder2 { public: CartesianProductHolder2(const Generator1& g1, const Generator2& g2) : g1_(g1), g2_(g2) {} template operator ParamGenerator< ::std::tr1::tuple >() const { return ParamGenerator< ::std::tr1::tuple >( new CartesianProductGenerator2( static_cast >(g1_), static_cast >(g2_))); } private: // No implementation - assignment is unsupported. void operator=(const CartesianProductHolder2& other); const Generator1 g1_; const Generator2 g2_; }; // class CartesianProductHolder2 template class CartesianProductHolder3 { public: CartesianProductHolder3(const Generator1& g1, const Generator2& g2, const Generator3& g3) : g1_(g1), g2_(g2), g3_(g3) {} template operator ParamGenerator< ::std::tr1::tuple >() const { return ParamGenerator< ::std::tr1::tuple >( new CartesianProductGenerator3( static_cast >(g1_), static_cast >(g2_), static_cast >(g3_))); } private: // No implementation - assignment is unsupported. void operator=(const CartesianProductHolder3& other); const Generator1 g1_; const Generator2 g2_; const Generator3 g3_; }; // class CartesianProductHolder3 template class CartesianProductHolder4 { public: CartesianProductHolder4(const Generator1& g1, const Generator2& g2, const Generator3& g3, const Generator4& g4) : g1_(g1), g2_(g2), g3_(g3), g4_(g4) {} template operator ParamGenerator< ::std::tr1::tuple >() const { return ParamGenerator< ::std::tr1::tuple >( new CartesianProductGenerator4( static_cast >(g1_), static_cast >(g2_), static_cast >(g3_), static_cast >(g4_))); } private: // No implementation - assignment is unsupported. void operator=(const CartesianProductHolder4& other); const Generator1 g1_; const Generator2 g2_; const Generator3 g3_; const Generator4 g4_; }; // class CartesianProductHolder4 template class CartesianProductHolder5 { public: CartesianProductHolder5(const Generator1& g1, const Generator2& g2, const Generator3& g3, const Generator4& g4, const Generator5& g5) : g1_(g1), g2_(g2), g3_(g3), g4_(g4), g5_(g5) {} template operator ParamGenerator< ::std::tr1::tuple >() const { return ParamGenerator< ::std::tr1::tuple >( new CartesianProductGenerator5( static_cast >(g1_), static_cast >(g2_), static_cast >(g3_), static_cast >(g4_), static_cast >(g5_))); } private: // No implementation - assignment is unsupported. void operator=(const CartesianProductHolder5& other); const Generator1 g1_; const Generator2 g2_; const Generator3 g3_; const Generator4 g4_; const Generator5 g5_; }; // class CartesianProductHolder5 template class CartesianProductHolder6 { public: CartesianProductHolder6(const Generator1& g1, const Generator2& g2, const Generator3& g3, const Generator4& g4, const Generator5& g5, const Generator6& g6) : g1_(g1), g2_(g2), g3_(g3), g4_(g4), g5_(g5), g6_(g6) {} template operator ParamGenerator< ::std::tr1::tuple >() const { return ParamGenerator< ::std::tr1::tuple >( new CartesianProductGenerator6( static_cast >(g1_), static_cast >(g2_), static_cast >(g3_), static_cast >(g4_), static_cast >(g5_), static_cast >(g6_))); } private: // No implementation - assignment is unsupported. void operator=(const CartesianProductHolder6& other); const Generator1 g1_; const Generator2 g2_; const Generator3 g3_; const Generator4 g4_; const Generator5 g5_; const Generator6 g6_; }; // class CartesianProductHolder6 template class CartesianProductHolder7 { public: CartesianProductHolder7(const Generator1& g1, const Generator2& g2, const Generator3& g3, const Generator4& g4, const Generator5& g5, const Generator6& g6, const Generator7& g7) : g1_(g1), g2_(g2), g3_(g3), g4_(g4), g5_(g5), g6_(g6), g7_(g7) {} template operator ParamGenerator< ::std::tr1::tuple >() const { return ParamGenerator< ::std::tr1::tuple >( new CartesianProductGenerator7( static_cast >(g1_), static_cast >(g2_), static_cast >(g3_), static_cast >(g4_), static_cast >(g5_), static_cast >(g6_), static_cast >(g7_))); } private: // No implementation - assignment is unsupported. void operator=(const CartesianProductHolder7& other); const Generator1 g1_; const Generator2 g2_; const Generator3 g3_; const Generator4 g4_; const Generator5 g5_; const Generator6 g6_; const Generator7 g7_; }; // class CartesianProductHolder7 template class CartesianProductHolder8 { public: CartesianProductHolder8(const Generator1& g1, const Generator2& g2, const Generator3& g3, const Generator4& g4, const Generator5& g5, const Generator6& g6, const Generator7& g7, const Generator8& g8) : g1_(g1), g2_(g2), g3_(g3), g4_(g4), g5_(g5), g6_(g6), g7_(g7), g8_(g8) {} template operator ParamGenerator< ::std::tr1::tuple >() const { return ParamGenerator< ::std::tr1::tuple >( new CartesianProductGenerator8( static_cast >(g1_), static_cast >(g2_), static_cast >(g3_), static_cast >(g4_), static_cast >(g5_), static_cast >(g6_), static_cast >(g7_), static_cast >(g8_))); } private: // No implementation - assignment is unsupported. void operator=(const CartesianProductHolder8& other); const Generator1 g1_; const Generator2 g2_; const Generator3 g3_; const Generator4 g4_; const Generator5 g5_; const Generator6 g6_; const Generator7 g7_; const Generator8 g8_; }; // class CartesianProductHolder8 template class CartesianProductHolder9 { public: CartesianProductHolder9(const Generator1& g1, const Generator2& g2, const Generator3& g3, const Generator4& g4, const Generator5& g5, const Generator6& g6, const Generator7& g7, const Generator8& g8, const Generator9& g9) : g1_(g1), g2_(g2), g3_(g3), g4_(g4), g5_(g5), g6_(g6), g7_(g7), g8_(g8), g9_(g9) {} template operator ParamGenerator< ::std::tr1::tuple >() const { return ParamGenerator< ::std::tr1::tuple >( new CartesianProductGenerator9( static_cast >(g1_), static_cast >(g2_), static_cast >(g3_), static_cast >(g4_), static_cast >(g5_), static_cast >(g6_), static_cast >(g7_), static_cast >(g8_), static_cast >(g9_))); } private: // No implementation - assignment is unsupported. void operator=(const CartesianProductHolder9& other); const Generator1 g1_; const Generator2 g2_; const Generator3 g3_; const Generator4 g4_; const Generator5 g5_; const Generator6 g6_; const Generator7 g7_; const Generator8 g8_; const Generator9 g9_; }; // class CartesianProductHolder9 template class CartesianProductHolder10 { public: CartesianProductHolder10(const Generator1& g1, const Generator2& g2, const Generator3& g3, const Generator4& g4, const Generator5& g5, const Generator6& g6, const Generator7& g7, const Generator8& g8, const Generator9& g9, const Generator10& g10) : g1_(g1), g2_(g2), g3_(g3), g4_(g4), g5_(g5), g6_(g6), g7_(g7), g8_(g8), g9_(g9), g10_(g10) {} template operator ParamGenerator< ::std::tr1::tuple >() const { return ParamGenerator< ::std::tr1::tuple >( new CartesianProductGenerator10( static_cast >(g1_), static_cast >(g2_), static_cast >(g3_), static_cast >(g4_), static_cast >(g5_), static_cast >(g6_), static_cast >(g7_), static_cast >(g8_), static_cast >(g9_), static_cast >(g10_))); } private: // No implementation - assignment is unsupported. void operator=(const CartesianProductHolder10& other); const Generator1 g1_; const Generator2 g2_; const Generator3 g3_; const Generator4 g4_; const Generator5 g5_; const Generator6 g6_; const Generator7 g7_; const Generator8 g8_; const Generator9 g9_; const Generator10 g10_; }; // class CartesianProductHolder10 # endif // GTEST_HAS_COMBINE } // namespace internal } // namespace testing #endif // GTEST_HAS_PARAM_TEST #endif // GTEST_INCLUDE_GTEST_INTERNAL_GTEST_PARAM_UTIL_GENERATED_H_ #if GTEST_HAS_PARAM_TEST namespace testing { // Functions producing parameter generators. // // Google Test uses these generators to produce parameters for value- // parameterized tests. When a parameterized test case is instantiated // with a particular generator, Google Test creates and runs tests // for each element in the sequence produced by the generator. // // In the following sample, tests from test case FooTest are instantiated // each three times with parameter values 3, 5, and 8: // // class FooTest : public TestWithParam { ... }; // // TEST_P(FooTest, TestThis) { // } // TEST_P(FooTest, TestThat) { // } // INSTANTIATE_TEST_CASE_P(TestSequence, FooTest, Values(3, 5, 8)); // // Range() returns generators providing sequences of values in a range. // // Synopsis: // Range(start, end) // - returns a generator producing a sequence of values {start, start+1, // start+2, ..., }. // Range(start, end, step) // - returns a generator producing a sequence of values {start, start+step, // start+step+step, ..., }. // Notes: // * The generated sequences never include end. For example, Range(1, 5) // returns a generator producing a sequence {1, 2, 3, 4}. Range(1, 9, 2) // returns a generator producing {1, 3, 5, 7}. // * start and end must have the same type. That type may be any integral or // floating-point type or a user defined type satisfying these conditions: // * It must be assignable (have operator=() defined). // * It must have operator+() (operator+(int-compatible type) for // two-operand version). // * It must have operator<() defined. // Elements in the resulting sequences will also have that type. // * Condition start < end must be satisfied in order for resulting sequences // to contain any elements. // template internal::ParamGenerator Range(T start, T end, IncrementT step) { return internal::ParamGenerator( new internal::RangeGenerator(start, end, step)); } template internal::ParamGenerator Range(T start, T end) { return Range(start, end, 1); } // ValuesIn() function allows generation of tests with parameters coming from // a container. // // Synopsis: // ValuesIn(const T (&array)[N]) // - returns a generator producing sequences with elements from // a C-style array. // ValuesIn(const Container& container) // - returns a generator producing sequences with elements from // an STL-style container. // ValuesIn(Iterator begin, Iterator end) // - returns a generator producing sequences with elements from // a range [begin, end) defined by a pair of STL-style iterators. These // iterators can also be plain C pointers. // // Please note that ValuesIn copies the values from the containers // passed in and keeps them to generate tests in RUN_ALL_TESTS(). // // Examples: // // This instantiates tests from test case StringTest // each with C-string values of "foo", "bar", and "baz": // // const char* strings[] = {"foo", "bar", "baz"}; // INSTANTIATE_TEST_CASE_P(StringSequence, SrtingTest, ValuesIn(strings)); // // This instantiates tests from test case StlStringTest // each with STL strings with values "a" and "b": // // ::std::vector< ::std::string> GetParameterStrings() { // ::std::vector< ::std::string> v; // v.push_back("a"); // v.push_back("b"); // return v; // } // // INSTANTIATE_TEST_CASE_P(CharSequence, // StlStringTest, // ValuesIn(GetParameterStrings())); // // // This will also instantiate tests from CharTest // each with parameter values 'a' and 'b': // // ::std::list GetParameterChars() { // ::std::list list; // list.push_back('a'); // list.push_back('b'); // return list; // } // ::std::list l = GetParameterChars(); // INSTANTIATE_TEST_CASE_P(CharSequence2, // CharTest, // ValuesIn(l.begin(), l.end())); // template internal::ParamGenerator< typename ::testing::internal::IteratorTraits::value_type> ValuesIn(ForwardIterator begin, ForwardIterator end) { typedef typename ::testing::internal::IteratorTraits ::value_type ParamType; return internal::ParamGenerator( new internal::ValuesInIteratorRangeGenerator(begin, end)); } template internal::ParamGenerator ValuesIn(const T (&array)[N]) { return ValuesIn(array, array + N); } template internal::ParamGenerator ValuesIn( const Container& container) { return ValuesIn(container.begin(), container.end()); } // Values() allows generating tests from explicitly specified list of // parameters. // // Synopsis: // Values(T v1, T v2, ..., T vN) // - returns a generator producing sequences with elements v1, v2, ..., vN. // // For example, this instantiates tests from test case BarTest each // with values "one", "two", and "three": // // INSTANTIATE_TEST_CASE_P(NumSequence, BarTest, Values("one", "two", "three")); // // This instantiates tests from test case BazTest each with values 1, 2, 3.5. // The exact type of values will depend on the type of parameter in BazTest. // // INSTANTIATE_TEST_CASE_P(FloatingNumbers, BazTest, Values(1, 2, 3.5)); // // Currently, Values() supports from 1 to 50 parameters. // template internal::ValueArray1 Values(T1 v1) { return internal::ValueArray1(v1); } template internal::ValueArray2 Values(T1 v1, T2 v2) { return internal::ValueArray2(v1, v2); } template internal::ValueArray3 Values(T1 v1, T2 v2, T3 v3) { return internal::ValueArray3(v1, v2, v3); } template internal::ValueArray4 Values(T1 v1, T2 v2, T3 v3, T4 v4) { return internal::ValueArray4(v1, v2, v3, v4); } template internal::ValueArray5 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5) { return internal::ValueArray5(v1, v2, v3, v4, v5); } template internal::ValueArray6 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6) { return internal::ValueArray6(v1, v2, v3, v4, v5, v6); } template internal::ValueArray7 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7) { return internal::ValueArray7(v1, v2, v3, v4, v5, v6, v7); } template internal::ValueArray8 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8) { return internal::ValueArray8(v1, v2, v3, v4, v5, v6, v7, v8); } template internal::ValueArray9 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9) { return internal::ValueArray9(v1, v2, v3, v4, v5, v6, v7, v8, v9); } template internal::ValueArray10 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10) { return internal::ValueArray10(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10); } template internal::ValueArray11 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11) { return internal::ValueArray11(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11); } template internal::ValueArray12 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12) { return internal::ValueArray12(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12); } template internal::ValueArray13 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13) { return internal::ValueArray13(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13); } template internal::ValueArray14 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14) { return internal::ValueArray14(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14); } template internal::ValueArray15 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15) { return internal::ValueArray15(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15); } template internal::ValueArray16 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16) { return internal::ValueArray16(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16); } template internal::ValueArray17 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17) { return internal::ValueArray17(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17); } template internal::ValueArray18 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18) { return internal::ValueArray18(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18); } template internal::ValueArray19 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19) { return internal::ValueArray19(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19); } template internal::ValueArray20 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20) { return internal::ValueArray20(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20); } template internal::ValueArray21 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21) { return internal::ValueArray21(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21); } template internal::ValueArray22 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22) { return internal::ValueArray22(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22); } template internal::ValueArray23 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23) { return internal::ValueArray23(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23); } template internal::ValueArray24 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24) { return internal::ValueArray24(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24); } template internal::ValueArray25 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25) { return internal::ValueArray25(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25); } template internal::ValueArray26 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26) { return internal::ValueArray26(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26); } template internal::ValueArray27 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27) { return internal::ValueArray27(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27); } template internal::ValueArray28 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28) { return internal::ValueArray28(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28); } template internal::ValueArray29 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29) { return internal::ValueArray29(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29); } template internal::ValueArray30 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30) { return internal::ValueArray30(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30); } template internal::ValueArray31 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31) { return internal::ValueArray31(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31); } template internal::ValueArray32 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32) { return internal::ValueArray32(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32); } template internal::ValueArray33 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33) { return internal::ValueArray33(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33); } template internal::ValueArray34 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34) { return internal::ValueArray34(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34); } template internal::ValueArray35 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35) { return internal::ValueArray35(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35); } template internal::ValueArray36 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36) { return internal::ValueArray36(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36); } template internal::ValueArray37 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37) { return internal::ValueArray37(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37); } template internal::ValueArray38 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38) { return internal::ValueArray38(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38); } template internal::ValueArray39 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39) { return internal::ValueArray39(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39); } template internal::ValueArray40 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40) { return internal::ValueArray40(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40); } template internal::ValueArray41 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41) { return internal::ValueArray41(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41); } template internal::ValueArray42 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42) { return internal::ValueArray42(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42); } template internal::ValueArray43 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43) { return internal::ValueArray43(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43); } template internal::ValueArray44 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43, T44 v44) { return internal::ValueArray44(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44); } template internal::ValueArray45 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43, T44 v44, T45 v45) { return internal::ValueArray45(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45); } template internal::ValueArray46 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43, T44 v44, T45 v45, T46 v46) { return internal::ValueArray46(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46); } template internal::ValueArray47 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43, T44 v44, T45 v45, T46 v46, T47 v47) { return internal::ValueArray47(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47); } template internal::ValueArray48 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43, T44 v44, T45 v45, T46 v46, T47 v47, T48 v48) { return internal::ValueArray48(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48); } template internal::ValueArray49 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43, T44 v44, T45 v45, T46 v46, T47 v47, T48 v48, T49 v49) { return internal::ValueArray49(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49); } template internal::ValueArray50 Values(T1 v1, T2 v2, T3 v3, T4 v4, T5 v5, T6 v6, T7 v7, T8 v8, T9 v9, T10 v10, T11 v11, T12 v12, T13 v13, T14 v14, T15 v15, T16 v16, T17 v17, T18 v18, T19 v19, T20 v20, T21 v21, T22 v22, T23 v23, T24 v24, T25 v25, T26 v26, T27 v27, T28 v28, T29 v29, T30 v30, T31 v31, T32 v32, T33 v33, T34 v34, T35 v35, T36 v36, T37 v37, T38 v38, T39 v39, T40 v40, T41 v41, T42 v42, T43 v43, T44 v44, T45 v45, T46 v46, T47 v47, T48 v48, T49 v49, T50 v50) { return internal::ValueArray50(v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50); } // Bool() allows generating tests with parameters in a set of (false, true). // // Synopsis: // Bool() // - returns a generator producing sequences with elements {false, true}. // // It is useful when testing code that depends on Boolean flags. Combinations // of multiple flags can be tested when several Bool()'s are combined using // Combine() function. // // In the following example all tests in the test case FlagDependentTest // will be instantiated twice with parameters false and true. // // class FlagDependentTest : public testing::TestWithParam { // virtual void SetUp() { // external_flag = GetParam(); // } // } // INSTANTIATE_TEST_CASE_P(BoolSequence, FlagDependentTest, Bool()); // inline internal::ParamGenerator Bool() { return Values(false, true); } # if GTEST_HAS_COMBINE // Combine() allows the user to combine two or more sequences to produce // values of a Cartesian product of those sequences' elements. // // Synopsis: // Combine(gen1, gen2, ..., genN) // - returns a generator producing sequences with elements coming from // the Cartesian product of elements from the sequences generated by // gen1, gen2, ..., genN. The sequence elements will have a type of // tuple where T1, T2, ..., TN are the types // of elements from sequences produces by gen1, gen2, ..., genN. // // Combine can have up to 10 arguments. This number is currently limited // by the maximum number of elements in the tuple implementation used by Google // Test. // // Example: // // This will instantiate tests in test case AnimalTest each one with // the parameter values tuple("cat", BLACK), tuple("cat", WHITE), // tuple("dog", BLACK), and tuple("dog", WHITE): // // enum Color { BLACK, GRAY, WHITE }; // class AnimalTest // : public testing::TestWithParam > {...}; // // TEST_P(AnimalTest, AnimalLooksNice) {...} // // INSTANTIATE_TEST_CASE_P(AnimalVariations, AnimalTest, // Combine(Values("cat", "dog"), // Values(BLACK, WHITE))); // // This will instantiate tests in FlagDependentTest with all variations of two // Boolean flags: // // class FlagDependentTest // : public testing::TestWithParam > { // virtual void SetUp() { // // Assigns external_flag_1 and external_flag_2 values from the tuple. // tie(external_flag_1, external_flag_2) = GetParam(); // } // }; // // TEST_P(FlagDependentTest, TestFeature1) { // // Test your code using external_flag_1 and external_flag_2 here. // } // INSTANTIATE_TEST_CASE_P(TwoBoolSequence, FlagDependentTest, // Combine(Bool(), Bool())); // template internal::CartesianProductHolder2 Combine( const Generator1& g1, const Generator2& g2) { return internal::CartesianProductHolder2( g1, g2); } template internal::CartesianProductHolder3 Combine( const Generator1& g1, const Generator2& g2, const Generator3& g3) { return internal::CartesianProductHolder3( g1, g2, g3); } template internal::CartesianProductHolder4 Combine( const Generator1& g1, const Generator2& g2, const Generator3& g3, const Generator4& g4) { return internal::CartesianProductHolder4( g1, g2, g3, g4); } template internal::CartesianProductHolder5 Combine( const Generator1& g1, const Generator2& g2, const Generator3& g3, const Generator4& g4, const Generator5& g5) { return internal::CartesianProductHolder5( g1, g2, g3, g4, g5); } template internal::CartesianProductHolder6 Combine( const Generator1& g1, const Generator2& g2, const Generator3& g3, const Generator4& g4, const Generator5& g5, const Generator6& g6) { return internal::CartesianProductHolder6( g1, g2, g3, g4, g5, g6); } template internal::CartesianProductHolder7 Combine( const Generator1& g1, const Generator2& g2, const Generator3& g3, const Generator4& g4, const Generator5& g5, const Generator6& g6, const Generator7& g7) { return internal::CartesianProductHolder7( g1, g2, g3, g4, g5, g6, g7); } template internal::CartesianProductHolder8 Combine( const Generator1& g1, const Generator2& g2, const Generator3& g3, const Generator4& g4, const Generator5& g5, const Generator6& g6, const Generator7& g7, const Generator8& g8) { return internal::CartesianProductHolder8( g1, g2, g3, g4, g5, g6, g7, g8); } template internal::CartesianProductHolder9 Combine( const Generator1& g1, const Generator2& g2, const Generator3& g3, const Generator4& g4, const Generator5& g5, const Generator6& g6, const Generator7& g7, const Generator8& g8, const Generator9& g9) { return internal::CartesianProductHolder9( g1, g2, g3, g4, g5, g6, g7, g8, g9); } template internal::CartesianProductHolder10 Combine( const Generator1& g1, const Generator2& g2, const Generator3& g3, const Generator4& g4, const Generator5& g5, const Generator6& g6, const Generator7& g7, const Generator8& g8, const Generator9& g9, const Generator10& g10) { return internal::CartesianProductHolder10( g1, g2, g3, g4, g5, g6, g7, g8, g9, g10); } # endif // GTEST_HAS_COMBINE # define TEST_P(test_case_name, test_name) \ class GTEST_TEST_CLASS_NAME_(test_case_name, test_name) \ : public test_case_name { \ public: \ GTEST_TEST_CLASS_NAME_(test_case_name, test_name)() {} \ virtual void TestBody(); \ private: \ static int AddToRegistry() { \ ::testing::UnitTest::GetInstance()->parameterized_test_registry(). \ GetTestCasePatternHolder(\ #test_case_name, __FILE__, __LINE__)->AddTestPattern(\ #test_case_name, \ #test_name, \ new ::testing::internal::TestMetaFactory< \ GTEST_TEST_CLASS_NAME_(test_case_name, test_name)>()); \ return 0; \ } \ static int gtest_registering_dummy_; \ GTEST_DISALLOW_COPY_AND_ASSIGN_(\ GTEST_TEST_CLASS_NAME_(test_case_name, test_name)); \ }; \ int GTEST_TEST_CLASS_NAME_(test_case_name, \ test_name)::gtest_registering_dummy_ = \ GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::AddToRegistry(); \ void GTEST_TEST_CLASS_NAME_(test_case_name, test_name)::TestBody() # define INSTANTIATE_TEST_CASE_P(prefix, test_case_name, generator) \ ::testing::internal::ParamGenerator \ gtest_##prefix##test_case_name##_EvalGenerator_() { return generator; } \ int gtest_##prefix##test_case_name##_dummy_ = \ ::testing::UnitTest::GetInstance()->parameterized_test_registry(). \ GetTestCasePatternHolder(\ #test_case_name, __FILE__, __LINE__)->AddTestCaseInstantiation(\ #prefix, \ >est_##prefix##test_case_name##_EvalGenerator_, \ __FILE__, __LINE__) } // namespace testing #endif // GTEST_HAS_PARAM_TEST #endif // GTEST_INCLUDE_GTEST_GTEST_PARAM_TEST_H_ // Copyright 2006, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: wan@google.com (Zhanyong Wan) // // Google C++ Testing Framework definitions useful in production code. #ifndef GTEST_INCLUDE_GTEST_GTEST_PROD_H_ #define GTEST_INCLUDE_GTEST_GTEST_PROD_H_ // When you need to test the private or protected members of a class, // use the FRIEND_TEST macro to declare your tests as friends of the // class. For example: // // class MyClass { // private: // void MyMethod(); // FRIEND_TEST(MyClassTest, MyMethod); // }; // // class MyClassTest : public testing::Test { // // ... // }; // // TEST_F(MyClassTest, MyMethod) { // // Can call MyClass::MyMethod() here. // } #define FRIEND_TEST(test_case_name, test_name)\ friend class test_case_name##_##test_name##_Test #endif // GTEST_INCLUDE_GTEST_GTEST_PROD_H_ // Copyright 2008, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: mheule@google.com (Markus Heule) // #ifndef GTEST_INCLUDE_GTEST_GTEST_TEST_PART_H_ #define GTEST_INCLUDE_GTEST_GTEST_TEST_PART_H_ #include #include namespace testing { // A copyable object representing the result of a test part (i.e. an // assertion or an explicit FAIL(), ADD_FAILURE(), or SUCCESS()). // // Don't inherit from TestPartResult as its destructor is not virtual. class GTEST_API_ TestPartResult { public: // The possible outcomes of a test part (i.e. an assertion or an // explicit SUCCEED(), FAIL(), or ADD_FAILURE()). enum Type { kSuccess, // Succeeded. kNonFatalFailure, // Failed but the test can continue. kFatalFailure // Failed and the test should be terminated. }; // C'tor. TestPartResult does NOT have a default constructor. // Always use this constructor (with parameters) to create a // TestPartResult object. TestPartResult(Type a_type, const char* a_file_name, int a_line_number, const char* a_message) : type_(a_type), file_name_(a_file_name == NULL ? "" : a_file_name), line_number_(a_line_number), summary_(ExtractSummary(a_message)), message_(a_message) { } // Gets the outcome of the test part. Type type() const { return type_; } // Gets the name of the source file where the test part took place, or // NULL if it's unknown. const char* file_name() const { return file_name_.empty() ? NULL : file_name_.c_str(); } // Gets the line in the source file where the test part took place, // or -1 if it's unknown. int line_number() const { return line_number_; } // Gets the summary of the failure message. const char* summary() const { return summary_.c_str(); } // Gets the message associated with the test part. const char* message() const { return message_.c_str(); } // Returns true iff the test part passed. bool passed() const { return type_ == kSuccess; } // Returns true iff the test part failed. bool failed() const { return type_ != kSuccess; } // Returns true iff the test part non-fatally failed. bool nonfatally_failed() const { return type_ == kNonFatalFailure; } // Returns true iff the test part fatally failed. bool fatally_failed() const { return type_ == kFatalFailure; } private: Type type_; // Gets the summary of the failure message by omitting the stack // trace in it. static std::string ExtractSummary(const char* message); // The name of the source file where the test part took place, or // "" if the source file is unknown. std::string file_name_; // The line in the source file where the test part took place, or -1 // if the line number is unknown. int line_number_; std::string summary_; // The test failure summary. std::string message_; // The test failure message. }; // Prints a TestPartResult object. std::ostream& operator<<(std::ostream& os, const TestPartResult& result); // An array of TestPartResult objects. // // Don't inherit from TestPartResultArray as its destructor is not // virtual. class GTEST_API_ TestPartResultArray { public: TestPartResultArray() {} // Appends the given TestPartResult to the array. void Append(const TestPartResult& result); // Returns the TestPartResult at the given index (0-based). const TestPartResult& GetTestPartResult(int index) const; // Returns the number of TestPartResult objects in the array. int size() const; private: std::vector array_; GTEST_DISALLOW_COPY_AND_ASSIGN_(TestPartResultArray); }; // This interface knows how to report a test part result. class TestPartResultReporterInterface { public: virtual ~TestPartResultReporterInterface() {} virtual void ReportTestPartResult(const TestPartResult& result) = 0; }; namespace internal { // This helper class is used by {ASSERT|EXPECT}_NO_FATAL_FAILURE to check if a // statement generates new fatal failures. To do so it registers itself as the // current test part result reporter. Besides checking if fatal failures were // reported, it only delegates the reporting to the former result reporter. // The original result reporter is restored in the destructor. // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. class GTEST_API_ HasNewFatalFailureHelper : public TestPartResultReporterInterface { public: HasNewFatalFailureHelper(); virtual ~HasNewFatalFailureHelper(); virtual void ReportTestPartResult(const TestPartResult& result); bool has_new_fatal_failure() const { return has_new_fatal_failure_; } private: bool has_new_fatal_failure_; TestPartResultReporterInterface* original_reporter_; GTEST_DISALLOW_COPY_AND_ASSIGN_(HasNewFatalFailureHelper); }; } // namespace internal } // namespace testing #endif // GTEST_INCLUDE_GTEST_GTEST_TEST_PART_H_ // Copyright 2008 Google Inc. // All Rights Reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Author: wan@google.com (Zhanyong Wan) #ifndef GTEST_INCLUDE_GTEST_GTEST_TYPED_TEST_H_ #define GTEST_INCLUDE_GTEST_GTEST_TYPED_TEST_H_ // This header implements typed tests and type-parameterized tests. // Typed (aka type-driven) tests repeat the same test for types in a // list. You must know which types you want to test with when writing // typed tests. Here's how you do it: #if 0 // First, define a fixture class template. It should be parameterized // by a type. Remember to derive it from testing::Test. template class FooTest : public testing::Test { public: ... typedef std::list List; static T shared_; T value_; }; // Next, associate a list of types with the test case, which will be // repeated for each type in the list. The typedef is necessary for // the macro to parse correctly. typedef testing::Types MyTypes; TYPED_TEST_CASE(FooTest, MyTypes); // If the type list contains only one type, you can write that type // directly without Types<...>: // TYPED_TEST_CASE(FooTest, int); // Then, use TYPED_TEST() instead of TEST_F() to define as many typed // tests for this test case as you want. TYPED_TEST(FooTest, DoesBlah) { // Inside a test, refer to TypeParam to get the type parameter. // Since we are inside a derived class template, C++ requires use to // visit the members of FooTest via 'this'. TypeParam n = this->value_; // To visit static members of the fixture, add the TestFixture:: // prefix. n += TestFixture::shared_; // To refer to typedefs in the fixture, add the "typename // TestFixture::" prefix. typename TestFixture::List values; values.push_back(n); ... } TYPED_TEST(FooTest, HasPropertyA) { ... } #endif // 0 // Type-parameterized tests are abstract test patterns parameterized // by a type. Compared with typed tests, type-parameterized tests // allow you to define the test pattern without knowing what the type // parameters are. The defined pattern can be instantiated with // different types any number of times, in any number of translation // units. // // If you are designing an interface or concept, you can define a // suite of type-parameterized tests to verify properties that any // valid implementation of the interface/concept should have. Then, // each implementation can easily instantiate the test suite to verify // that it conforms to the requirements, without having to write // similar tests repeatedly. Here's an example: #if 0 // First, define a fixture class template. It should be parameterized // by a type. Remember to derive it from testing::Test. template class FooTest : public testing::Test { ... }; // Next, declare that you will define a type-parameterized test case // (the _P suffix is for "parameterized" or "pattern", whichever you // prefer): TYPED_TEST_CASE_P(FooTest); // Then, use TYPED_TEST_P() to define as many type-parameterized tests // for this type-parameterized test case as you want. TYPED_TEST_P(FooTest, DoesBlah) { // Inside a test, refer to TypeParam to get the type parameter. TypeParam n = 0; ... } TYPED_TEST_P(FooTest, HasPropertyA) { ... } // Now the tricky part: you need to register all test patterns before // you can instantiate them. The first argument of the macro is the // test case name; the rest are the names of the tests in this test // case. REGISTER_TYPED_TEST_CASE_P(FooTest, DoesBlah, HasPropertyA); // Finally, you are free to instantiate the pattern with the types you // want. If you put the above code in a header file, you can #include // it in multiple C++ source files and instantiate it multiple times. // // To distinguish different instances of the pattern, the first // argument to the INSTANTIATE_* macro is a prefix that will be added // to the actual test case name. Remember to pick unique prefixes for // different instances. typedef testing::Types MyTypes; INSTANTIATE_TYPED_TEST_CASE_P(My, FooTest, MyTypes); // If the type list contains only one type, you can write that type // directly without Types<...>: // INSTANTIATE_TYPED_TEST_CASE_P(My, FooTest, int); #endif // 0 // Implements typed tests. #if GTEST_HAS_TYPED_TEST // INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE. // // Expands to the name of the typedef for the type parameters of the // given test case. # define GTEST_TYPE_PARAMS_(TestCaseName) gtest_type_params_##TestCaseName##_ // The 'Types' template argument below must have spaces around it // since some compilers may choke on '>>' when passing a template // instance (e.g. Types) # define TYPED_TEST_CASE(CaseName, Types) \ typedef ::testing::internal::TypeList< Types >::type \ GTEST_TYPE_PARAMS_(CaseName) # define TYPED_TEST(CaseName, TestName) \ template \ class GTEST_TEST_CLASS_NAME_(CaseName, TestName) \ : public CaseName { \ private: \ typedef CaseName TestFixture; \ typedef gtest_TypeParam_ TypeParam; \ virtual void TestBody(); \ }; \ bool gtest_##CaseName##_##TestName##_registered_ GTEST_ATTRIBUTE_UNUSED_ = \ ::testing::internal::TypeParameterizedTest< \ CaseName, \ ::testing::internal::TemplateSel< \ GTEST_TEST_CLASS_NAME_(CaseName, TestName)>, \ GTEST_TYPE_PARAMS_(CaseName)>::Register(\ "", #CaseName, #TestName, 0); \ template \ void GTEST_TEST_CLASS_NAME_(CaseName, TestName)::TestBody() #endif // GTEST_HAS_TYPED_TEST // Implements type-parameterized tests. #if GTEST_HAS_TYPED_TEST_P // INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE. // // Expands to the namespace name that the type-parameterized tests for // the given type-parameterized test case are defined in. The exact // name of the namespace is subject to change without notice. # define GTEST_CASE_NAMESPACE_(TestCaseName) \ gtest_case_##TestCaseName##_ // INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE. // // Expands to the name of the variable used to remember the names of // the defined tests in the given test case. # define GTEST_TYPED_TEST_CASE_P_STATE_(TestCaseName) \ gtest_typed_test_case_p_state_##TestCaseName##_ // INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE DIRECTLY. // // Expands to the name of the variable used to remember the names of // the registered tests in the given test case. # define GTEST_REGISTERED_TEST_NAMES_(TestCaseName) \ gtest_registered_test_names_##TestCaseName##_ // The variables defined in the type-parameterized test macros are // static as typically these macros are used in a .h file that can be // #included in multiple translation units linked together. # define TYPED_TEST_CASE_P(CaseName) \ static ::testing::internal::TypedTestCasePState \ GTEST_TYPED_TEST_CASE_P_STATE_(CaseName) # define TYPED_TEST_P(CaseName, TestName) \ namespace GTEST_CASE_NAMESPACE_(CaseName) { \ template \ class TestName : public CaseName { \ private: \ typedef CaseName TestFixture; \ typedef gtest_TypeParam_ TypeParam; \ virtual void TestBody(); \ }; \ static bool gtest_##TestName##_defined_ GTEST_ATTRIBUTE_UNUSED_ = \ GTEST_TYPED_TEST_CASE_P_STATE_(CaseName).AddTestName(\ __FILE__, __LINE__, #CaseName, #TestName); \ } \ template \ void GTEST_CASE_NAMESPACE_(CaseName)::TestName::TestBody() # define REGISTER_TYPED_TEST_CASE_P(CaseName, ...) \ namespace GTEST_CASE_NAMESPACE_(CaseName) { \ typedef ::testing::internal::Templates<__VA_ARGS__>::type gtest_AllTests_; \ } \ static const char* const GTEST_REGISTERED_TEST_NAMES_(CaseName) = \ GTEST_TYPED_TEST_CASE_P_STATE_(CaseName).VerifyRegisteredTestNames(\ __FILE__, __LINE__, #__VA_ARGS__) // The 'Types' template argument below must have spaces around it // since some compilers may choke on '>>' when passing a template // instance (e.g. Types) # define INSTANTIATE_TYPED_TEST_CASE_P(Prefix, CaseName, Types) \ bool gtest_##Prefix##_##CaseName GTEST_ATTRIBUTE_UNUSED_ = \ ::testing::internal::TypeParameterizedTestCase::type>::Register(\ #Prefix, #CaseName, GTEST_REGISTERED_TEST_NAMES_(CaseName)) #endif // GTEST_HAS_TYPED_TEST_P #endif // GTEST_INCLUDE_GTEST_GTEST_TYPED_TEST_H_ // Depending on the platform, different string classes are available. // On Linux, in addition to ::std::string, Google also makes use of // class ::string, which has the same interface as ::std::string, but // has a different implementation. // // The user can define GTEST_HAS_GLOBAL_STRING to 1 to indicate that // ::string is available AND is a distinct type to ::std::string, or // define it to 0 to indicate otherwise. // // If the user's ::std::string and ::string are the same class due to // aliasing, he should define GTEST_HAS_GLOBAL_STRING to 0. // // If the user doesn't define GTEST_HAS_GLOBAL_STRING, it is defined // heuristically. namespace testing { // Declares the flags. // This flag temporary enables the disabled tests. GTEST_DECLARE_bool_(also_run_disabled_tests); // This flag brings the debugger on an assertion failure. GTEST_DECLARE_bool_(break_on_failure); // This flag controls whether Google Test catches all test-thrown exceptions // and logs them as failures. GTEST_DECLARE_bool_(catch_exceptions); // This flag enables using colors in terminal output. Available values are // "yes" to enable colors, "no" (disable colors), or "auto" (the default) // to let Google Test decide. GTEST_DECLARE_string_(color); // This flag sets up the filter to select by name using a glob pattern // the tests to run. If the filter is not given all tests are executed. GTEST_DECLARE_string_(filter); // This flag causes the Google Test to list tests. None of the tests listed // are actually run if the flag is provided. GTEST_DECLARE_bool_(list_tests); // This flag controls whether Google Test emits a detailed XML report to a file // in addition to its normal textual output. GTEST_DECLARE_string_(output); // This flags control whether Google Test prints the elapsed time for each // test. GTEST_DECLARE_bool_(print_time); // This flag specifies the random number seed. GTEST_DECLARE_int32_(random_seed); // This flag sets how many times the tests are repeated. The default value // is 1. If the value is -1 the tests are repeating forever. GTEST_DECLARE_int32_(repeat); // This flag controls whether Google Test includes Google Test internal // stack frames in failure stack traces. GTEST_DECLARE_bool_(show_internal_stack_frames); // When this flag is specified, tests' order is randomized on every iteration. GTEST_DECLARE_bool_(shuffle); // This flag specifies the maximum number of stack frames to be // printed in a failure message. GTEST_DECLARE_int32_(stack_trace_depth); // When this flag is specified, a failed assertion will throw an // exception if exceptions are enabled, or exit the program with a // non-zero code otherwise. GTEST_DECLARE_bool_(throw_on_failure); // When this flag is set with a "host:port" string, on supported // platforms test results are streamed to the specified port on // the specified host machine. GTEST_DECLARE_string_(stream_result_to); // The upper limit for valid stack trace depths. const int kMaxStackTraceDepth = 100; namespace internal { class AssertHelper; class DefaultGlobalTestPartResultReporter; class ExecDeathTest; class NoExecDeathTest; class FinalSuccessChecker; class GTestFlagSaver; class StreamingListenerTest; class TestResultAccessor; class TestEventListenersAccessor; class TestEventRepeater; class UnitTestRecordPropertyTestHelper; class WindowsDeathTest; class UnitTestImpl* GetUnitTestImpl(); void ReportFailureInUnknownLocation(TestPartResult::Type result_type, const std::string& message); } // namespace internal // The friend relationship of some of these classes is cyclic. // If we don't forward declare them the compiler might confuse the classes // in friendship clauses with same named classes on the scope. class Test; class TestCase; class TestInfo; class UnitTest; // A class for indicating whether an assertion was successful. When // the assertion wasn't successful, the AssertionResult object // remembers a non-empty message that describes how it failed. // // To create an instance of this class, use one of the factory functions // (AssertionSuccess() and AssertionFailure()). // // This class is useful for two purposes: // 1. Defining predicate functions to be used with Boolean test assertions // EXPECT_TRUE/EXPECT_FALSE and their ASSERT_ counterparts // 2. Defining predicate-format functions to be // used with predicate assertions (ASSERT_PRED_FORMAT*, etc). // // For example, if you define IsEven predicate: // // testing::AssertionResult IsEven(int n) { // if ((n % 2) == 0) // return testing::AssertionSuccess(); // else // return testing::AssertionFailure() << n << " is odd"; // } // // Then the failed expectation EXPECT_TRUE(IsEven(Fib(5))) // will print the message // // Value of: IsEven(Fib(5)) // Actual: false (5 is odd) // Expected: true // // instead of a more opaque // // Value of: IsEven(Fib(5)) // Actual: false // Expected: true // // in case IsEven is a simple Boolean predicate. // // If you expect your predicate to be reused and want to support informative // messages in EXPECT_FALSE and ASSERT_FALSE (negative assertions show up // about half as often as positive ones in our tests), supply messages for // both success and failure cases: // // testing::AssertionResult IsEven(int n) { // if ((n % 2) == 0) // return testing::AssertionSuccess() << n << " is even"; // else // return testing::AssertionFailure() << n << " is odd"; // } // // Then a statement EXPECT_FALSE(IsEven(Fib(6))) will print // // Value of: IsEven(Fib(6)) // Actual: true (8 is even) // Expected: false // // NB: Predicates that support negative Boolean assertions have reduced // performance in positive ones so be careful not to use them in tests // that have lots (tens of thousands) of positive Boolean assertions. // // To use this class with EXPECT_PRED_FORMAT assertions such as: // // // Verifies that Foo() returns an even number. // EXPECT_PRED_FORMAT1(IsEven, Foo()); // // you need to define: // // testing::AssertionResult IsEven(const char* expr, int n) { // if ((n % 2) == 0) // return testing::AssertionSuccess(); // else // return testing::AssertionFailure() // << "Expected: " << expr << " is even\n Actual: it's " << n; // } // // If Foo() returns 5, you will see the following message: // // Expected: Foo() is even // Actual: it's 5 // class GTEST_API_ AssertionResult { public: // Copy constructor. // Used in EXPECT_TRUE/FALSE(assertion_result). AssertionResult(const AssertionResult& other); // Used in the EXPECT_TRUE/FALSE(bool_expression). explicit AssertionResult(bool success) : success_(success) {} // Returns true iff the assertion succeeded. operator bool() const { return success_; } // NOLINT // Returns the assertion's negation. Used with EXPECT/ASSERT_FALSE. AssertionResult operator!() const; // Returns the text streamed into this AssertionResult. Test assertions // use it when they fail (i.e., the predicate's outcome doesn't match the // assertion's expectation). When nothing has been streamed into the // object, returns an empty string. const char* message() const { return message_.get() != NULL ? message_->c_str() : ""; } // TODO(vladl@google.com): Remove this after making sure no clients use it. // Deprecated; please use message() instead. const char* failure_message() const { return message(); } // Streams a custom failure message into this object. template AssertionResult& operator<<(const T& value) { AppendMessage(Message() << value); return *this; } // Allows streaming basic output manipulators such as endl or flush into // this object. AssertionResult& operator<<( ::std::ostream& (*basic_manipulator)(::std::ostream& stream)) { AppendMessage(Message() << basic_manipulator); return *this; } private: // Appends the contents of message to message_. void AppendMessage(const Message& a_message) { if (message_.get() == NULL) message_.reset(new ::std::string); message_->append(a_message.GetString().c_str()); } // Stores result of the assertion predicate. bool success_; // Stores the message describing the condition in case the expectation // construct is not satisfied with the predicate's outcome. // Referenced via a pointer to avoid taking too much stack frame space // with test assertions. internal::scoped_ptr< ::std::string> message_; GTEST_DISALLOW_ASSIGN_(AssertionResult); }; // Makes a successful assertion result. GTEST_API_ AssertionResult AssertionSuccess(); // Makes a failed assertion result. GTEST_API_ AssertionResult AssertionFailure(); // Makes a failed assertion result with the given failure message. // Deprecated; use AssertionFailure() << msg. GTEST_API_ AssertionResult AssertionFailure(const Message& msg); // The abstract class that all tests inherit from. // // In Google Test, a unit test program contains one or many TestCases, and // each TestCase contains one or many Tests. // // When you define a test using the TEST macro, you don't need to // explicitly derive from Test - the TEST macro automatically does // this for you. // // The only time you derive from Test is when defining a test fixture // to be used a TEST_F. For example: // // class FooTest : public testing::Test { // protected: // virtual void SetUp() { ... } // virtual void TearDown() { ... } // ... // }; // // TEST_F(FooTest, Bar) { ... } // TEST_F(FooTest, Baz) { ... } // // Test is not copyable. class GTEST_API_ Test { public: friend class TestInfo; // Defines types for pointers to functions that set up and tear down // a test case. typedef internal::SetUpTestCaseFunc SetUpTestCaseFunc; typedef internal::TearDownTestCaseFunc TearDownTestCaseFunc; // The d'tor is virtual as we intend to inherit from Test. virtual ~Test(); // Sets up the stuff shared by all tests in this test case. // // Google Test will call Foo::SetUpTestCase() before running the first // test in test case Foo. Hence a sub-class can define its own // SetUpTestCase() method to shadow the one defined in the super // class. static void SetUpTestCase() {} // Tears down the stuff shared by all tests in this test case. // // Google Test will call Foo::TearDownTestCase() after running the last // test in test case Foo. Hence a sub-class can define its own // TearDownTestCase() method to shadow the one defined in the super // class. static void TearDownTestCase() {} // Returns true iff the current test has a fatal failure. static bool HasFatalFailure(); // Returns true iff the current test has a non-fatal failure. static bool HasNonfatalFailure(); // Returns true iff the current test has a (either fatal or // non-fatal) failure. static bool HasFailure() { return HasFatalFailure() || HasNonfatalFailure(); } // Logs a property for the current test, test case, or for the entire // invocation of the test program when used outside of the context of a // test case. Only the last value for a given key is remembered. These // are public static so they can be called from utility functions that are // not members of the test fixture. Calls to RecordProperty made during // lifespan of the test (from the moment its constructor starts to the // moment its destructor finishes) will be output in XML as attributes of // the element. Properties recorded from fixture's // SetUpTestCase or TearDownTestCase are logged as attributes of the // corresponding element. Calls to RecordProperty made in the // global context (before or after invocation of RUN_ALL_TESTS and from // SetUp/TearDown method of Environment objects registered with Google // Test) will be output as attributes of the element. static void RecordProperty(const std::string& key, const std::string& value); static void RecordProperty(const std::string& key, int value); protected: // Creates a Test object. Test(); // Sets up the test fixture. virtual void SetUp(); // Tears down the test fixture. virtual void TearDown(); private: // Returns true iff the current test has the same fixture class as // the first test in the current test case. static bool HasSameFixtureClass(); // Runs the test after the test fixture has been set up. // // A sub-class must implement this to define the test logic. // // DO NOT OVERRIDE THIS FUNCTION DIRECTLY IN A USER PROGRAM. // Instead, use the TEST or TEST_F macro. virtual void TestBody() = 0; // Sets up, executes, and tears down the test. void Run(); // Deletes self. We deliberately pick an unusual name for this // internal method to avoid clashing with names used in user TESTs. void DeleteSelf_() { delete this; } // Uses a GTestFlagSaver to save and restore all Google Test flags. const internal::GTestFlagSaver* const gtest_flag_saver_; // Often a user mis-spells SetUp() as Setup() and spends a long time // wondering why it is never called by Google Test. The declaration of // the following method is solely for catching such an error at // compile time: // // - The return type is deliberately chosen to be not void, so it // will be a conflict if a user declares void Setup() in his test // fixture. // // - This method is private, so it will be another compiler error // if a user calls it from his test fixture. // // DO NOT OVERRIDE THIS FUNCTION. // // If you see an error about overriding the following function or // about it being private, you have mis-spelled SetUp() as Setup(). struct Setup_should_be_spelled_SetUp {}; virtual Setup_should_be_spelled_SetUp* Setup() { return NULL; } // We disallow copying Tests. GTEST_DISALLOW_COPY_AND_ASSIGN_(Test); }; typedef internal::TimeInMillis TimeInMillis; // A copyable object representing a user specified test property which can be // output as a key/value string pair. // // Don't inherit from TestProperty as its destructor is not virtual. class TestProperty { public: // C'tor. TestProperty does NOT have a default constructor. // Always use this constructor (with parameters) to create a // TestProperty object. TestProperty(const std::string& a_key, const std::string& a_value) : key_(a_key), value_(a_value) { } // Gets the user supplied key. const char* key() const { return key_.c_str(); } // Gets the user supplied value. const char* value() const { return value_.c_str(); } // Sets a new value, overriding the one supplied in the constructor. void SetValue(const std::string& new_value) { value_ = new_value; } private: // The key supplied by the user. std::string key_; // The value supplied by the user. std::string value_; }; // The result of a single Test. This includes a list of // TestPartResults, a list of TestProperties, a count of how many // death tests there are in the Test, and how much time it took to run // the Test. // // TestResult is not copyable. class GTEST_API_ TestResult { public: // Creates an empty TestResult. TestResult(); // D'tor. Do not inherit from TestResult. ~TestResult(); // Gets the number of all test parts. This is the sum of the number // of successful test parts and the number of failed test parts. int total_part_count() const; // Returns the number of the test properties. int test_property_count() const; // Returns true iff the test passed (i.e. no test part failed). bool Passed() const { return !Failed(); } // Returns true iff the test failed. bool Failed() const; // Returns true iff the test fatally failed. bool HasFatalFailure() const; // Returns true iff the test has a non-fatal failure. bool HasNonfatalFailure() const; // Returns the elapsed time, in milliseconds. TimeInMillis elapsed_time() const { return elapsed_time_; } // Returns the i-th test part result among all the results. i can range // from 0 to test_property_count() - 1. If i is not in that range, aborts // the program. const TestPartResult& GetTestPartResult(int i) const; // Returns the i-th test property. i can range from 0 to // test_property_count() - 1. If i is not in that range, aborts the // program. const TestProperty& GetTestProperty(int i) const; private: friend class TestInfo; friend class TestCase; friend class UnitTest; friend class internal::DefaultGlobalTestPartResultReporter; friend class internal::ExecDeathTest; friend class internal::TestResultAccessor; friend class internal::UnitTestImpl; friend class internal::WindowsDeathTest; // Gets the vector of TestPartResults. const std::vector& test_part_results() const { return test_part_results_; } // Gets the vector of TestProperties. const std::vector& test_properties() const { return test_properties_; } // Sets the elapsed time. void set_elapsed_time(TimeInMillis elapsed) { elapsed_time_ = elapsed; } // Adds a test property to the list. The property is validated and may add // a non-fatal failure if invalid (e.g., if it conflicts with reserved // key names). If a property is already recorded for the same key, the // value will be updated, rather than storing multiple values for the same // key. xml_element specifies the element for which the property is being // recorded and is used for validation. void RecordProperty(const std::string& xml_element, const TestProperty& test_property); // Adds a failure if the key is a reserved attribute of Google Test // testcase tags. Returns true if the property is valid. // TODO(russr): Validate attribute names are legal and human readable. static bool ValidateTestProperty(const std::string& xml_element, const TestProperty& test_property); // Adds a test part result to the list. void AddTestPartResult(const TestPartResult& test_part_result); // Returns the death test count. int death_test_count() const { return death_test_count_; } // Increments the death test count, returning the new count. int increment_death_test_count() { return ++death_test_count_; } // Clears the test part results. void ClearTestPartResults(); // Clears the object. void Clear(); // Protects mutable state of the property vector and of owned // properties, whose values may be updated. internal::Mutex test_properites_mutex_; // The vector of TestPartResults std::vector test_part_results_; // The vector of TestProperties std::vector test_properties_; // Running count of death tests. int death_test_count_; // The elapsed time, in milliseconds. TimeInMillis elapsed_time_; // We disallow copying TestResult. GTEST_DISALLOW_COPY_AND_ASSIGN_(TestResult); }; // class TestResult // A TestInfo object stores the following information about a test: // // Test case name // Test name // Whether the test should be run // A function pointer that creates the test object when invoked // Test result // // The constructor of TestInfo registers itself with the UnitTest // singleton such that the RUN_ALL_TESTS() macro knows which tests to // run. class GTEST_API_ TestInfo { public: // Destructs a TestInfo object. This function is not virtual, so // don't inherit from TestInfo. ~TestInfo(); // Returns the test case name. const char* test_case_name() const { return test_case_name_.c_str(); } // Returns the test name. const char* name() const { return name_.c_str(); } // Returns the name of the parameter type, or NULL if this is not a typed // or a type-parameterized test. const char* type_param() const { if (type_param_.get() != NULL) return type_param_->c_str(); return NULL; } // Returns the text representation of the value parameter, or NULL if this // is not a value-parameterized test. const char* value_param() const { if (value_param_.get() != NULL) return value_param_->c_str(); return NULL; } // Returns true if this test should run, that is if the test is not // disabled (or it is disabled but the also_run_disabled_tests flag has // been specified) and its full name matches the user-specified filter. // // Google Test allows the user to filter the tests by their full names. // The full name of a test Bar in test case Foo is defined as // "Foo.Bar". Only the tests that match the filter will run. // // A filter is a colon-separated list of glob (not regex) patterns, // optionally followed by a '-' and a colon-separated list of // negative patterns (tests to exclude). A test is run if it // matches one of the positive patterns and does not match any of // the negative patterns. // // For example, *A*:Foo.* is a filter that matches any string that // contains the character 'A' or starts with "Foo.". bool should_run() const { return should_run_; } // Returns true iff this test will appear in the XML report. bool is_reportable() const { // For now, the XML report includes all tests matching the filter. // In the future, we may trim tests that are excluded because of // sharding. return matches_filter_; } // Returns the result of the test. const TestResult* result() const { return &result_; } private: #if GTEST_HAS_DEATH_TEST friend class internal::DefaultDeathTestFactory; #endif // GTEST_HAS_DEATH_TEST friend class Test; friend class TestCase; friend class internal::UnitTestImpl; friend class internal::StreamingListenerTest; friend TestInfo* internal::MakeAndRegisterTestInfo( const char* test_case_name, const char* name, const char* type_param, const char* value_param, internal::TypeId fixture_class_id, Test::SetUpTestCaseFunc set_up_tc, Test::TearDownTestCaseFunc tear_down_tc, internal::TestFactoryBase* factory); // Constructs a TestInfo object. The newly constructed instance assumes // ownership of the factory object. TestInfo(const std::string& test_case_name, const std::string& name, const char* a_type_param, // NULL if not a type-parameterized test const char* a_value_param, // NULL if not a value-parameterized test internal::TypeId fixture_class_id, internal::TestFactoryBase* factory); // Increments the number of death tests encountered in this test so // far. int increment_death_test_count() { return result_.increment_death_test_count(); } // Creates the test object, runs it, records its result, and then // deletes it. void Run(); static void ClearTestResult(TestInfo* test_info) { test_info->result_.Clear(); } // These fields are immutable properties of the test. const std::string test_case_name_; // Test case name const std::string name_; // Test name // Name of the parameter type, or NULL if this is not a typed or a // type-parameterized test. const internal::scoped_ptr type_param_; // Text representation of the value parameter, or NULL if this is not a // value-parameterized test. const internal::scoped_ptr value_param_; const internal::TypeId fixture_class_id_; // ID of the test fixture class bool should_run_; // True iff this test should run bool is_disabled_; // True iff this test is disabled bool matches_filter_; // True if this test matches the // user-specified filter. internal::TestFactoryBase* const factory_; // The factory that creates // the test object // This field is mutable and needs to be reset before running the // test for the second time. TestResult result_; GTEST_DISALLOW_COPY_AND_ASSIGN_(TestInfo); }; // A test case, which consists of a vector of TestInfos. // // TestCase is not copyable. class GTEST_API_ TestCase { public: // Creates a TestCase with the given name. // // TestCase does NOT have a default constructor. Always use this // constructor to create a TestCase object. // // Arguments: // // name: name of the test case // a_type_param: the name of the test's type parameter, or NULL if // this is not a type-parameterized test. // set_up_tc: pointer to the function that sets up the test case // tear_down_tc: pointer to the function that tears down the test case TestCase(const char* name, const char* a_type_param, Test::SetUpTestCaseFunc set_up_tc, Test::TearDownTestCaseFunc tear_down_tc); // Destructor of TestCase. virtual ~TestCase(); // Gets the name of the TestCase. const char* name() const { return name_.c_str(); } // Returns the name of the parameter type, or NULL if this is not a // type-parameterized test case. const char* type_param() const { if (type_param_.get() != NULL) return type_param_->c_str(); return NULL; } // Returns true if any test in this test case should run. bool should_run() const { return should_run_; } // Gets the number of successful tests in this test case. int successful_test_count() const; // Gets the number of failed tests in this test case. int failed_test_count() const; // Gets the number of disabled tests that will be reported in the XML report. int reportable_disabled_test_count() const; // Gets the number of disabled tests in this test case. int disabled_test_count() const; // Gets the number of tests to be printed in the XML report. int reportable_test_count() const; // Get the number of tests in this test case that should run. int test_to_run_count() const; // Gets the number of all tests in this test case. int total_test_count() const; // Returns true iff the test case passed. bool Passed() const { return !Failed(); } // Returns true iff the test case failed. bool Failed() const { return failed_test_count() > 0; } // Returns the elapsed time, in milliseconds. TimeInMillis elapsed_time() const { return elapsed_time_; } // Returns the i-th test among all the tests. i can range from 0 to // total_test_count() - 1. If i is not in that range, returns NULL. const TestInfo* GetTestInfo(int i) const; // Returns the TestResult that holds test properties recorded during // execution of SetUpTestCase and TearDownTestCase. const TestResult& ad_hoc_test_result() const { return ad_hoc_test_result_; } private: friend class Test; friend class internal::UnitTestImpl; // Gets the (mutable) vector of TestInfos in this TestCase. std::vector& test_info_list() { return test_info_list_; } // Gets the (immutable) vector of TestInfos in this TestCase. const std::vector& test_info_list() const { return test_info_list_; } // Returns the i-th test among all the tests. i can range from 0 to // total_test_count() - 1. If i is not in that range, returns NULL. TestInfo* GetMutableTestInfo(int i); // Sets the should_run member. void set_should_run(bool should) { should_run_ = should; } // Adds a TestInfo to this test case. Will delete the TestInfo upon // destruction of the TestCase object. void AddTestInfo(TestInfo * test_info); // Clears the results of all tests in this test case. void ClearResult(); // Clears the results of all tests in the given test case. static void ClearTestCaseResult(TestCase* test_case) { test_case->ClearResult(); } // Runs every test in this TestCase. void Run(); // Runs SetUpTestCase() for this TestCase. This wrapper is needed // for catching exceptions thrown from SetUpTestCase(). void RunSetUpTestCase() { (*set_up_tc_)(); } // Runs TearDownTestCase() for this TestCase. This wrapper is // needed for catching exceptions thrown from TearDownTestCase(). void RunTearDownTestCase() { (*tear_down_tc_)(); } // Returns true iff test passed. static bool TestPassed(const TestInfo* test_info) { return test_info->should_run() && test_info->result()->Passed(); } // Returns true iff test failed. static bool TestFailed(const TestInfo* test_info) { return test_info->should_run() && test_info->result()->Failed(); } // Returns true iff the test is disabled and will be reported in the XML // report. static bool TestReportableDisabled(const TestInfo* test_info) { return test_info->is_reportable() && test_info->is_disabled_; } // Returns true iff test is disabled. static bool TestDisabled(const TestInfo* test_info) { return test_info->is_disabled_; } // Returns true iff this test will appear in the XML report. static bool TestReportable(const TestInfo* test_info) { return test_info->is_reportable(); } // Returns true if the given test should run. static bool ShouldRunTest(const TestInfo* test_info) { return test_info->should_run(); } // Shuffles the tests in this test case. void ShuffleTests(internal::Random* random); // Restores the test order to before the first shuffle. void UnshuffleTests(); // Name of the test case. std::string name_; // Name of the parameter type, or NULL if this is not a typed or a // type-parameterized test. const internal::scoped_ptr type_param_; // The vector of TestInfos in their original order. It owns the // elements in the vector. std::vector test_info_list_; // Provides a level of indirection for the test list to allow easy // shuffling and restoring the test order. The i-th element in this // vector is the index of the i-th test in the shuffled test list. std::vector test_indices_; // Pointer to the function that sets up the test case. Test::SetUpTestCaseFunc set_up_tc_; // Pointer to the function that tears down the test case. Test::TearDownTestCaseFunc tear_down_tc_; // True iff any test in this test case should run. bool should_run_; // Elapsed time, in milliseconds. TimeInMillis elapsed_time_; // Holds test properties recorded during execution of SetUpTestCase and // TearDownTestCase. TestResult ad_hoc_test_result_; // We disallow copying TestCases. GTEST_DISALLOW_COPY_AND_ASSIGN_(TestCase); }; // An Environment object is capable of setting up and tearing down an // environment. The user should subclass this to define his own // environment(s). // // An Environment object does the set-up and tear-down in virtual // methods SetUp() and TearDown() instead of the constructor and the // destructor, as: // // 1. You cannot safely throw from a destructor. This is a problem // as in some cases Google Test is used where exceptions are enabled, and // we may want to implement ASSERT_* using exceptions where they are // available. // 2. You cannot use ASSERT_* directly in a constructor or // destructor. class Environment { public: // The d'tor is virtual as we need to subclass Environment. virtual ~Environment() {} // Override this to define how to set up the environment. virtual void SetUp() {} // Override this to define how to tear down the environment. virtual void TearDown() {} private: // If you see an error about overriding the following function or // about it being private, you have mis-spelled SetUp() as Setup(). struct Setup_should_be_spelled_SetUp {}; virtual Setup_should_be_spelled_SetUp* Setup() { return NULL; } }; // The interface for tracing execution of tests. The methods are organized in // the order the corresponding events are fired. class TestEventListener { public: virtual ~TestEventListener() {} // Fired before any test activity starts. virtual void OnTestProgramStart(const UnitTest& unit_test) = 0; // Fired before each iteration of tests starts. There may be more than // one iteration if GTEST_FLAG(repeat) is set. iteration is the iteration // index, starting from 0. virtual void OnTestIterationStart(const UnitTest& unit_test, int iteration) = 0; // Fired before environment set-up for each iteration of tests starts. virtual void OnEnvironmentsSetUpStart(const UnitTest& unit_test) = 0; // Fired after environment set-up for each iteration of tests ends. virtual void OnEnvironmentsSetUpEnd(const UnitTest& unit_test) = 0; // Fired before the test case starts. virtual void OnTestCaseStart(const TestCase& test_case) = 0; // Fired before the test starts. virtual void OnTestStart(const TestInfo& test_info) = 0; // Fired after a failed assertion or a SUCCEED() invocation. virtual void OnTestPartResult(const TestPartResult& test_part_result) = 0; // Fired after the test ends. virtual void OnTestEnd(const TestInfo& test_info) = 0; // Fired after the test case ends. virtual void OnTestCaseEnd(const TestCase& test_case) = 0; // Fired before environment tear-down for each iteration of tests starts. virtual void OnEnvironmentsTearDownStart(const UnitTest& unit_test) = 0; // Fired after environment tear-down for each iteration of tests ends. virtual void OnEnvironmentsTearDownEnd(const UnitTest& unit_test) = 0; // Fired after each iteration of tests finishes. virtual void OnTestIterationEnd(const UnitTest& unit_test, int iteration) = 0; // Fired after all test activities have ended. virtual void OnTestProgramEnd(const UnitTest& unit_test) = 0; }; // The convenience class for users who need to override just one or two // methods and are not concerned that a possible change to a signature of // the methods they override will not be caught during the build. For // comments about each method please see the definition of TestEventListener // above. class EmptyTestEventListener : public TestEventListener { public: virtual void OnTestProgramStart(const UnitTest& /*unit_test*/) {} virtual void OnTestIterationStart(const UnitTest& /*unit_test*/, int /*iteration*/) {} virtual void OnEnvironmentsSetUpStart(const UnitTest& /*unit_test*/) {} virtual void OnEnvironmentsSetUpEnd(const UnitTest& /*unit_test*/) {} virtual void OnTestCaseStart(const TestCase& /*test_case*/) {} virtual void OnTestStart(const TestInfo& /*test_info*/) {} virtual void OnTestPartResult(const TestPartResult& /*test_part_result*/) {} virtual void OnTestEnd(const TestInfo& /*test_info*/) {} virtual void OnTestCaseEnd(const TestCase& /*test_case*/) {} virtual void OnEnvironmentsTearDownStart(const UnitTest& /*unit_test*/) {} virtual void OnEnvironmentsTearDownEnd(const UnitTest& /*unit_test*/) {} virtual void OnTestIterationEnd(const UnitTest& /*unit_test*/, int /*iteration*/) {} virtual void OnTestProgramEnd(const UnitTest& /*unit_test*/) {} }; // TestEventListeners lets users add listeners to track events in Google Test. class GTEST_API_ TestEventListeners { public: TestEventListeners(); ~TestEventListeners(); // Appends an event listener to the end of the list. Google Test assumes // the ownership of the listener (i.e. it will delete the listener when // the test program finishes). void Append(TestEventListener* listener); // Removes the given event listener from the list and returns it. It then // becomes the caller's responsibility to delete the listener. Returns // NULL if the listener is not found in the list. TestEventListener* Release(TestEventListener* listener); // Returns the standard listener responsible for the default console // output. Can be removed from the listeners list to shut down default // console output. Note that removing this object from the listener list // with Release transfers its ownership to the caller and makes this // function return NULL the next time. TestEventListener* default_result_printer() const { return default_result_printer_; } // Returns the standard listener responsible for the default XML output // controlled by the --gtest_output=xml flag. Can be removed from the // listeners list by users who want to shut down the default XML output // controlled by this flag and substitute it with custom one. Note that // removing this object from the listener list with Release transfers its // ownership to the caller and makes this function return NULL the next // time. TestEventListener* default_xml_generator() const { return default_xml_generator_; } private: friend class TestCase; friend class TestInfo; friend class internal::DefaultGlobalTestPartResultReporter; friend class internal::NoExecDeathTest; friend class internal::TestEventListenersAccessor; friend class internal::UnitTestImpl; // Returns repeater that broadcasts the TestEventListener events to all // subscribers. TestEventListener* repeater(); // Sets the default_result_printer attribute to the provided listener. // The listener is also added to the listener list and previous // default_result_printer is removed from it and deleted. The listener can // also be NULL in which case it will not be added to the list. Does // nothing if the previous and the current listener objects are the same. void SetDefaultResultPrinter(TestEventListener* listener); // Sets the default_xml_generator attribute to the provided listener. The // listener is also added to the listener list and previous // default_xml_generator is removed from it and deleted. The listener can // also be NULL in which case it will not be added to the list. Does // nothing if the previous and the current listener objects are the same. void SetDefaultXmlGenerator(TestEventListener* listener); // Controls whether events will be forwarded by the repeater to the // listeners in the list. bool EventForwardingEnabled() const; void SuppressEventForwarding(); // The actual list of listeners. internal::TestEventRepeater* repeater_; // Listener responsible for the standard result output. TestEventListener* default_result_printer_; // Listener responsible for the creation of the XML output file. TestEventListener* default_xml_generator_; // We disallow copying TestEventListeners. GTEST_DISALLOW_COPY_AND_ASSIGN_(TestEventListeners); }; // A UnitTest consists of a vector of TestCases. // // This is a singleton class. The only instance of UnitTest is // created when UnitTest::GetInstance() is first called. This // instance is never deleted. // // UnitTest is not copyable. // // This class is thread-safe as long as the methods are called // according to their specification. class GTEST_API_ UnitTest { public: // Gets the singleton UnitTest object. The first time this method // is called, a UnitTest object is constructed and returned. // Consecutive calls will return the same object. static UnitTest* GetInstance(); // Runs all tests in this UnitTest object and prints the result. // Returns 0 if successful, or 1 otherwise. // // This method can only be called from the main thread. // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. int Run() GTEST_MUST_USE_RESULT_; // Returns the working directory when the first TEST() or TEST_F() // was executed. The UnitTest object owns the string. const char* original_working_dir() const; // Returns the TestCase object for the test that's currently running, // or NULL if no test is running. const TestCase* current_test_case() const GTEST_LOCK_EXCLUDED_(mutex_); // Returns the TestInfo object for the test that's currently running, // or NULL if no test is running. const TestInfo* current_test_info() const GTEST_LOCK_EXCLUDED_(mutex_); // Returns the random seed used at the start of the current test run. int random_seed() const; #if GTEST_HAS_PARAM_TEST // Returns the ParameterizedTestCaseRegistry object used to keep track of // value-parameterized tests and instantiate and register them. // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. internal::ParameterizedTestCaseRegistry& parameterized_test_registry() GTEST_LOCK_EXCLUDED_(mutex_); #endif // GTEST_HAS_PARAM_TEST // Gets the number of successful test cases. int successful_test_case_count() const; // Gets the number of failed test cases. int failed_test_case_count() const; // Gets the number of all test cases. int total_test_case_count() const; // Gets the number of all test cases that contain at least one test // that should run. int test_case_to_run_count() const; // Gets the number of successful tests. int successful_test_count() const; // Gets the number of failed tests. int failed_test_count() const; // Gets the number of disabled tests that will be reported in the XML report. int reportable_disabled_test_count() const; // Gets the number of disabled tests. int disabled_test_count() const; // Gets the number of tests to be printed in the XML report. int reportable_test_count() const; // Gets the number of all tests. int total_test_count() const; // Gets the number of tests that should run. int test_to_run_count() const; // Gets the time of the test program start, in ms from the start of the // UNIX epoch. TimeInMillis start_timestamp() const; // Gets the elapsed time, in milliseconds. TimeInMillis elapsed_time() const; // Returns true iff the unit test passed (i.e. all test cases passed). bool Passed() const; // Returns true iff the unit test failed (i.e. some test case failed // or something outside of all tests failed). bool Failed() const; // Gets the i-th test case among all the test cases. i can range from 0 to // total_test_case_count() - 1. If i is not in that range, returns NULL. const TestCase* GetTestCase(int i) const; // Returns the TestResult containing information on test failures and // properties logged outside of individual test cases. const TestResult& ad_hoc_test_result() const; // Returns the list of event listeners that can be used to track events // inside Google Test. TestEventListeners& listeners(); private: // Registers and returns a global test environment. When a test // program is run, all global test environments will be set-up in // the order they were registered. After all tests in the program // have finished, all global test environments will be torn-down in // the *reverse* order they were registered. // // The UnitTest object takes ownership of the given environment. // // This method can only be called from the main thread. Environment* AddEnvironment(Environment* env); // Adds a TestPartResult to the current TestResult object. All // Google Test assertion macros (e.g. ASSERT_TRUE, EXPECT_EQ, etc) // eventually call this to report their results. The user code // should use the assertion macros instead of calling this directly. void AddTestPartResult(TestPartResult::Type result_type, const char* file_name, int line_number, const std::string& message, const std::string& os_stack_trace) GTEST_LOCK_EXCLUDED_(mutex_); // Adds a TestProperty to the current TestResult object when invoked from // inside a test, to current TestCase's ad_hoc_test_result_ when invoked // from SetUpTestCase or TearDownTestCase, or to the global property set // when invoked elsewhere. If the result already contains a property with // the same key, the value will be updated. void RecordProperty(const std::string& key, const std::string& value); // Gets the i-th test case among all the test cases. i can range from 0 to // total_test_case_count() - 1. If i is not in that range, returns NULL. TestCase* GetMutableTestCase(int i); // Accessors for the implementation object. internal::UnitTestImpl* impl() { return impl_; } const internal::UnitTestImpl* impl() const { return impl_; } // These classes and funcions are friends as they need to access private // members of UnitTest. friend class Test; friend class internal::AssertHelper; friend class internal::ScopedTrace; friend class internal::StreamingListenerTest; friend class internal::UnitTestRecordPropertyTestHelper; friend Environment* AddGlobalTestEnvironment(Environment* env); friend internal::UnitTestImpl* internal::GetUnitTestImpl(); friend void internal::ReportFailureInUnknownLocation( TestPartResult::Type result_type, const std::string& message); // Creates an empty UnitTest. UnitTest(); // D'tor virtual ~UnitTest(); // Pushes a trace defined by SCOPED_TRACE() on to the per-thread // Google Test trace stack. void PushGTestTrace(const internal::TraceInfo& trace) GTEST_LOCK_EXCLUDED_(mutex_); // Pops a trace from the per-thread Google Test trace stack. void PopGTestTrace() GTEST_LOCK_EXCLUDED_(mutex_); // Protects mutable state in *impl_. This is mutable as some const // methods need to lock it too. mutable internal::Mutex mutex_; // Opaque implementation object. This field is never changed once // the object is constructed. We don't mark it as const here, as // doing so will cause a warning in the constructor of UnitTest. // Mutable state in *impl_ is protected by mutex_. internal::UnitTestImpl* impl_; // We disallow copying UnitTest. GTEST_DISALLOW_COPY_AND_ASSIGN_(UnitTest); }; // A convenient wrapper for adding an environment for the test // program. // // You should call this before RUN_ALL_TESTS() is called, probably in // main(). If you use gtest_main, you need to call this before main() // starts for it to take effect. For example, you can define a global // variable like this: // // testing::Environment* const foo_env = // testing::AddGlobalTestEnvironment(new FooEnvironment); // // However, we strongly recommend you to write your own main() and // call AddGlobalTestEnvironment() there, as relying on initialization // of global variables makes the code harder to read and may cause // problems when you register multiple environments from different // translation units and the environments have dependencies among them // (remember that the compiler doesn't guarantee the order in which // global variables from different translation units are initialized). inline Environment* AddGlobalTestEnvironment(Environment* env) { return UnitTest::GetInstance()->AddEnvironment(env); } // Initializes Google Test. This must be called before calling // RUN_ALL_TESTS(). In particular, it parses a command line for the // flags that Google Test recognizes. Whenever a Google Test flag is // seen, it is removed from argv, and *argc is decremented. // // No value is returned. Instead, the Google Test flag variables are // updated. // // Calling the function for the second time has no user-visible effect. GTEST_API_ void InitGoogleTest(int* argc, char** argv); // This overloaded version can be used in Windows programs compiled in // UNICODE mode. GTEST_API_ void InitGoogleTest(int* argc, wchar_t** argv); namespace internal { // FormatForComparison::Format(value) formats a // value of type ToPrint that is an operand of a comparison assertion // (e.g. ASSERT_EQ). OtherOperand is the type of the other operand in // the comparison, and is used to help determine the best way to // format the value. In particular, when the value is a C string // (char pointer) and the other operand is an STL string object, we // want to format the C string as a string, since we know it is // compared by value with the string object. If the value is a char // pointer but the other operand is not an STL string object, we don't // know whether the pointer is supposed to point to a NUL-terminated // string, and thus want to print it as a pointer to be safe. // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. // The default case. template class FormatForComparison { public: static ::std::string Format(const ToPrint& value) { return ::testing::PrintToString(value); } }; // Array. template class FormatForComparison { public: static ::std::string Format(const ToPrint* value) { return FormatForComparison::Format(value); } }; // By default, print C string as pointers to be safe, as we don't know // whether they actually point to a NUL-terminated string. #define GTEST_IMPL_FORMAT_C_STRING_AS_POINTER_(CharType) \ template \ class FormatForComparison { \ public: \ static ::std::string Format(CharType* value) { \ return ::testing::PrintToString(static_cast(value)); \ } \ } GTEST_IMPL_FORMAT_C_STRING_AS_POINTER_(char); GTEST_IMPL_FORMAT_C_STRING_AS_POINTER_(const char); GTEST_IMPL_FORMAT_C_STRING_AS_POINTER_(wchar_t); GTEST_IMPL_FORMAT_C_STRING_AS_POINTER_(const wchar_t); #undef GTEST_IMPL_FORMAT_C_STRING_AS_POINTER_ // If a C string is compared with an STL string object, we know it's meant // to point to a NUL-terminated string, and thus can print it as a string. #define GTEST_IMPL_FORMAT_C_STRING_AS_STRING_(CharType, OtherStringType) \ template <> \ class FormatForComparison { \ public: \ static ::std::string Format(CharType* value) { \ return ::testing::PrintToString(value); \ } \ } GTEST_IMPL_FORMAT_C_STRING_AS_STRING_(char, ::std::string); GTEST_IMPL_FORMAT_C_STRING_AS_STRING_(const char, ::std::string); #if GTEST_HAS_GLOBAL_STRING GTEST_IMPL_FORMAT_C_STRING_AS_STRING_(char, ::string); GTEST_IMPL_FORMAT_C_STRING_AS_STRING_(const char, ::string); #endif #if GTEST_HAS_GLOBAL_WSTRING GTEST_IMPL_FORMAT_C_STRING_AS_STRING_(wchar_t, ::wstring); GTEST_IMPL_FORMAT_C_STRING_AS_STRING_(const wchar_t, ::wstring); #endif #if GTEST_HAS_STD_WSTRING GTEST_IMPL_FORMAT_C_STRING_AS_STRING_(wchar_t, ::std::wstring); GTEST_IMPL_FORMAT_C_STRING_AS_STRING_(const wchar_t, ::std::wstring); #endif #undef GTEST_IMPL_FORMAT_C_STRING_AS_STRING_ // Formats a comparison assertion (e.g. ASSERT_EQ, EXPECT_LT, and etc) // operand to be used in a failure message. The type (but not value) // of the other operand may affect the format. This allows us to // print a char* as a raw pointer when it is compared against another // char* or void*, and print it as a C string when it is compared // against an std::string object, for example. // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. template std::string FormatForComparisonFailureMessage( const T1& value, const T2& /* other_operand */) { return FormatForComparison::Format(value); } // The helper function for {ASSERT|EXPECT}_EQ. template AssertionResult CmpHelperEQ(const char* expected_expression, const char* actual_expression, const T1& expected, const T2& actual) { #ifdef _MSC_VER # pragma warning(push) // Saves the current warning state. # pragma warning(disable:4389) // Temporarily disables warning on // signed/unsigned mismatch. #endif if (expected == actual) { return AssertionSuccess(); } #ifdef _MSC_VER # pragma warning(pop) // Restores the warning state. #endif return EqFailure(expected_expression, actual_expression, FormatForComparisonFailureMessage(expected, actual), FormatForComparisonFailureMessage(actual, expected), false); } // With this overloaded version, we allow anonymous enums to be used // in {ASSERT|EXPECT}_EQ when compiled with gcc 4, as anonymous enums // can be implicitly cast to BiggestInt. GTEST_API_ AssertionResult CmpHelperEQ(const char* expected_expression, const char* actual_expression, BiggestInt expected, BiggestInt actual); // The helper class for {ASSERT|EXPECT}_EQ. The template argument // lhs_is_null_literal is true iff the first argument to ASSERT_EQ() // is a null pointer literal. The following default implementation is // for lhs_is_null_literal being false. template class EqHelper { public: // This templatized version is for the general case. template static AssertionResult Compare(const char* expected_expression, const char* actual_expression, const T1& expected, const T2& actual) { return CmpHelperEQ(expected_expression, actual_expression, expected, actual); } // With this overloaded version, we allow anonymous enums to be used // in {ASSERT|EXPECT}_EQ when compiled with gcc 4, as anonymous // enums can be implicitly cast to BiggestInt. // // Even though its body looks the same as the above version, we // cannot merge the two, as it will make anonymous enums unhappy. static AssertionResult Compare(const char* expected_expression, const char* actual_expression, BiggestInt expected, BiggestInt actual) { return CmpHelperEQ(expected_expression, actual_expression, expected, actual); } }; // This specialization is used when the first argument to ASSERT_EQ() // is a null pointer literal, like NULL, false, or 0. template <> class EqHelper { public: // We define two overloaded versions of Compare(). The first // version will be picked when the second argument to ASSERT_EQ() is // NOT a pointer, e.g. ASSERT_EQ(0, AnIntFunction()) or // EXPECT_EQ(false, a_bool). template static AssertionResult Compare( const char* expected_expression, const char* actual_expression, const T1& expected, const T2& actual, // The following line prevents this overload from being considered if T2 // is not a pointer type. We need this because ASSERT_EQ(NULL, my_ptr) // expands to Compare("", "", NULL, my_ptr), which requires a conversion // to match the Secret* in the other overload, which would otherwise make // this template match better. typename EnableIf::value>::type* = 0) { return CmpHelperEQ(expected_expression, actual_expression, expected, actual); } // This version will be picked when the second argument to ASSERT_EQ() is a // pointer, e.g. ASSERT_EQ(NULL, a_pointer). template static AssertionResult Compare( const char* expected_expression, const char* actual_expression, // We used to have a second template parameter instead of Secret*. That // template parameter would deduce to 'long', making this a better match // than the first overload even without the first overload's EnableIf. // Unfortunately, gcc with -Wconversion-null warns when "passing NULL to // non-pointer argument" (even a deduced integral argument), so the old // implementation caused warnings in user code. Secret* /* expected (NULL) */, T* actual) { // We already know that 'expected' is a null pointer. return CmpHelperEQ(expected_expression, actual_expression, static_cast(NULL), actual); } }; // A macro for implementing the helper functions needed to implement // ASSERT_?? and EXPECT_??. It is here just to avoid copy-and-paste // of similar code. // // For each templatized helper function, we also define an overloaded // version for BiggestInt in order to reduce code bloat and allow // anonymous enums to be used with {ASSERT|EXPECT}_?? when compiled // with gcc 4. // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. #define GTEST_IMPL_CMP_HELPER_(op_name, op)\ template \ AssertionResult CmpHelper##op_name(const char* expr1, const char* expr2, \ const T1& val1, const T2& val2) {\ if (val1 op val2) {\ return AssertionSuccess();\ } else {\ return AssertionFailure() \ << "Expected: (" << expr1 << ") " #op " (" << expr2\ << "), actual: " << FormatForComparisonFailureMessage(val1, val2)\ << " vs " << FormatForComparisonFailureMessage(val2, val1);\ }\ }\ GTEST_API_ AssertionResult CmpHelper##op_name(\ const char* expr1, const char* expr2, BiggestInt val1, BiggestInt val2) // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. // Implements the helper function for {ASSERT|EXPECT}_NE GTEST_IMPL_CMP_HELPER_(NE, !=); // Implements the helper function for {ASSERT|EXPECT}_LE GTEST_IMPL_CMP_HELPER_(LE, <=); // Implements the helper function for {ASSERT|EXPECT}_LT GTEST_IMPL_CMP_HELPER_(LT, <); // Implements the helper function for {ASSERT|EXPECT}_GE GTEST_IMPL_CMP_HELPER_(GE, >=); // Implements the helper function for {ASSERT|EXPECT}_GT GTEST_IMPL_CMP_HELPER_(GT, >); #undef GTEST_IMPL_CMP_HELPER_ // The helper function for {ASSERT|EXPECT}_STREQ. // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. GTEST_API_ AssertionResult CmpHelperSTREQ(const char* expected_expression, const char* actual_expression, const char* expected, const char* actual); // The helper function for {ASSERT|EXPECT}_STRCASEEQ. // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. GTEST_API_ AssertionResult CmpHelperSTRCASEEQ(const char* expected_expression, const char* actual_expression, const char* expected, const char* actual); // The helper function for {ASSERT|EXPECT}_STRNE. // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. GTEST_API_ AssertionResult CmpHelperSTRNE(const char* s1_expression, const char* s2_expression, const char* s1, const char* s2); // The helper function for {ASSERT|EXPECT}_STRCASENE. // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. GTEST_API_ AssertionResult CmpHelperSTRCASENE(const char* s1_expression, const char* s2_expression, const char* s1, const char* s2); // Helper function for *_STREQ on wide strings. // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. GTEST_API_ AssertionResult CmpHelperSTREQ(const char* expected_expression, const char* actual_expression, const wchar_t* expected, const wchar_t* actual); // Helper function for *_STRNE on wide strings. // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. GTEST_API_ AssertionResult CmpHelperSTRNE(const char* s1_expression, const char* s2_expression, const wchar_t* s1, const wchar_t* s2); } // namespace internal // IsSubstring() and IsNotSubstring() are intended to be used as the // first argument to {EXPECT,ASSERT}_PRED_FORMAT2(), not by // themselves. They check whether needle is a substring of haystack // (NULL is considered a substring of itself only), and return an // appropriate error message when they fail. // // The {needle,haystack}_expr arguments are the stringified // expressions that generated the two real arguments. GTEST_API_ AssertionResult IsSubstring( const char* needle_expr, const char* haystack_expr, const char* needle, const char* haystack); GTEST_API_ AssertionResult IsSubstring( const char* needle_expr, const char* haystack_expr, const wchar_t* needle, const wchar_t* haystack); GTEST_API_ AssertionResult IsNotSubstring( const char* needle_expr, const char* haystack_expr, const char* needle, const char* haystack); GTEST_API_ AssertionResult IsNotSubstring( const char* needle_expr, const char* haystack_expr, const wchar_t* needle, const wchar_t* haystack); GTEST_API_ AssertionResult IsSubstring( const char* needle_expr, const char* haystack_expr, const ::std::string& needle, const ::std::string& haystack); GTEST_API_ AssertionResult IsNotSubstring( const char* needle_expr, const char* haystack_expr, const ::std::string& needle, const ::std::string& haystack); #if GTEST_HAS_STD_WSTRING GTEST_API_ AssertionResult IsSubstring( const char* needle_expr, const char* haystack_expr, const ::std::wstring& needle, const ::std::wstring& haystack); GTEST_API_ AssertionResult IsNotSubstring( const char* needle_expr, const char* haystack_expr, const ::std::wstring& needle, const ::std::wstring& haystack); #endif // GTEST_HAS_STD_WSTRING namespace internal { // Helper template function for comparing floating-points. // // Template parameter: // // RawType: the raw floating-point type (either float or double) // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. template AssertionResult CmpHelperFloatingPointEQ(const char* expected_expression, const char* actual_expression, RawType expected, RawType actual) { const FloatingPoint lhs(expected), rhs(actual); if (lhs.AlmostEquals(rhs)) { return AssertionSuccess(); } ::std::stringstream expected_ss; expected_ss << std::setprecision(std::numeric_limits::digits10 + 2) << expected; ::std::stringstream actual_ss; actual_ss << std::setprecision(std::numeric_limits::digits10 + 2) << actual; return EqFailure(expected_expression, actual_expression, StringStreamToString(&expected_ss), StringStreamToString(&actual_ss), false); } // Helper function for implementing ASSERT_NEAR. // // INTERNAL IMPLEMENTATION - DO NOT USE IN A USER PROGRAM. GTEST_API_ AssertionResult DoubleNearPredFormat(const char* expr1, const char* expr2, const char* abs_error_expr, double val1, double val2, double abs_error); // INTERNAL IMPLEMENTATION - DO NOT USE IN USER CODE. // A class that enables one to stream messages to assertion macros class GTEST_API_ AssertHelper { public: // Constructor. AssertHelper(TestPartResult::Type type, const char* file, int line, const char* message); ~AssertHelper(); // Message assignment is a semantic trick to enable assertion // streaming; see the GTEST_MESSAGE_ macro below. void operator=(const Message& message) const; private: // We put our data in a struct so that the size of the AssertHelper class can // be as small as possible. This is important because gcc is incapable of // re-using stack space even for temporary variables, so every EXPECT_EQ // reserves stack space for another AssertHelper. struct AssertHelperData { AssertHelperData(TestPartResult::Type t, const char* srcfile, int line_num, const char* msg) : type(t), file(srcfile), line(line_num), message(msg) { } TestPartResult::Type const type; const char* const file; int const line; std::string const message; private: GTEST_DISALLOW_COPY_AND_ASSIGN_(AssertHelperData); }; AssertHelperData* const data_; GTEST_DISALLOW_COPY_AND_ASSIGN_(AssertHelper); }; } // namespace internal #if GTEST_HAS_PARAM_TEST // The pure interface class that all value-parameterized tests inherit from. // A value-parameterized class must inherit from both ::testing::Test and // ::testing::WithParamInterface. In most cases that just means inheriting // from ::testing::TestWithParam, but more complicated test hierarchies // may need to inherit from Test and WithParamInterface at different levels. // // This interface has support for accessing the test parameter value via // the GetParam() method. // // Use it with one of the parameter generator defining functions, like Range(), // Values(), ValuesIn(), Bool(), and Combine(). // // class FooTest : public ::testing::TestWithParam { // protected: // FooTest() { // // Can use GetParam() here. // } // virtual ~FooTest() { // // Can use GetParam() here. // } // virtual void SetUp() { // // Can use GetParam() here. // } // virtual void TearDown { // // Can use GetParam() here. // } // }; // TEST_P(FooTest, DoesBar) { // // Can use GetParam() method here. // Foo foo; // ASSERT_TRUE(foo.DoesBar(GetParam())); // } // INSTANTIATE_TEST_CASE_P(OneToTenRange, FooTest, ::testing::Range(1, 10)); template class WithParamInterface { public: typedef T ParamType; virtual ~WithParamInterface() {} // The current parameter value. Is also available in the test fixture's // constructor. This member function is non-static, even though it only // references static data, to reduce the opportunity for incorrect uses // like writing 'WithParamInterface::GetParam()' for a test that // uses a fixture whose parameter type is int. const ParamType& GetParam() const { GTEST_CHECK_(parameter_ != NULL) << "GetParam() can only be called inside a value-parameterized test " << "-- did you intend to write TEST_P instead of TEST_F?"; return *parameter_; } private: // Sets parameter value. The caller is responsible for making sure the value // remains alive and unchanged throughout the current test. static void SetParam(const ParamType* parameter) { parameter_ = parameter; } // Static value used for accessing parameter during a test lifetime. static const ParamType* parameter_; // TestClass must be a subclass of WithParamInterface and Test. template friend class internal::ParameterizedTestFactory; }; template const T* WithParamInterface::parameter_ = NULL; // Most value-parameterized classes can ignore the existence of // WithParamInterface, and can just inherit from ::testing::TestWithParam. template class TestWithParam : public Test, public WithParamInterface { }; #endif // GTEST_HAS_PARAM_TEST // Macros for indicating success/failure in test code. // ADD_FAILURE unconditionally adds a failure to the current test. // SUCCEED generates a success - it doesn't automatically make the // current test successful, as a test is only successful when it has // no failure. // // EXPECT_* verifies that a certain condition is satisfied. If not, // it behaves like ADD_FAILURE. In particular: // // EXPECT_TRUE verifies that a Boolean condition is true. // EXPECT_FALSE verifies that a Boolean condition is false. // // FAIL and ASSERT_* are similar to ADD_FAILURE and EXPECT_*, except // that they will also abort the current function on failure. People // usually want the fail-fast behavior of FAIL and ASSERT_*, but those // writing data-driven tests often find themselves using ADD_FAILURE // and EXPECT_* more. // Generates a nonfatal failure with a generic message. #define ADD_FAILURE() GTEST_NONFATAL_FAILURE_("Failed") // Generates a nonfatal failure at the given source file location with // a generic message. #define ADD_FAILURE_AT(file, line) \ GTEST_MESSAGE_AT_(file, line, "Failed", \ ::testing::TestPartResult::kNonFatalFailure) // Generates a fatal failure with a generic message. #define GTEST_FAIL() GTEST_FATAL_FAILURE_("Failed") // Define this macro to 1 to omit the definition of FAIL(), which is a // generic name and clashes with some other libraries. #if !GTEST_DONT_DEFINE_FAIL # define FAIL() GTEST_FAIL() #endif // Generates a success with a generic message. #define GTEST_SUCCEED() GTEST_SUCCESS_("Succeeded") // Define this macro to 1 to omit the definition of SUCCEED(), which // is a generic name and clashes with some other libraries. #if !GTEST_DONT_DEFINE_SUCCEED # define SUCCEED() GTEST_SUCCEED() #endif // Macros for testing exceptions. // // * {ASSERT|EXPECT}_THROW(statement, expected_exception): // Tests that the statement throws the expected exception. // * {ASSERT|EXPECT}_NO_THROW(statement): // Tests that the statement doesn't throw any exception. // * {ASSERT|EXPECT}_ANY_THROW(statement): // Tests that the statement throws an exception. #define EXPECT_THROW(statement, expected_exception) \ GTEST_TEST_THROW_(statement, expected_exception, GTEST_NONFATAL_FAILURE_) #define EXPECT_NO_THROW(statement) \ GTEST_TEST_NO_THROW_(statement, GTEST_NONFATAL_FAILURE_) #define EXPECT_ANY_THROW(statement) \ GTEST_TEST_ANY_THROW_(statement, GTEST_NONFATAL_FAILURE_) #define ASSERT_THROW(statement, expected_exception) \ GTEST_TEST_THROW_(statement, expected_exception, GTEST_FATAL_FAILURE_) #define ASSERT_NO_THROW(statement) \ GTEST_TEST_NO_THROW_(statement, GTEST_FATAL_FAILURE_) #define ASSERT_ANY_THROW(statement) \ GTEST_TEST_ANY_THROW_(statement, GTEST_FATAL_FAILURE_) // Boolean assertions. Condition can be either a Boolean expression or an // AssertionResult. For more information on how to use AssertionResult with // these macros see comments on that class. #define EXPECT_TRUE(condition) \ GTEST_TEST_BOOLEAN_(condition, #condition, false, true, \ GTEST_NONFATAL_FAILURE_) #define EXPECT_FALSE(condition) \ GTEST_TEST_BOOLEAN_(!(condition), #condition, true, false, \ GTEST_NONFATAL_FAILURE_) #define ASSERT_TRUE(condition) \ GTEST_TEST_BOOLEAN_(condition, #condition, false, true, \ GTEST_FATAL_FAILURE_) #define ASSERT_FALSE(condition) \ GTEST_TEST_BOOLEAN_(!(condition), #condition, true, false, \ GTEST_FATAL_FAILURE_) // Includes the auto-generated header that implements a family of // generic predicate assertion macros. // Copyright 2006, Google Inc. // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions are // met: // // * Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // * Redistributions in binary form must reproduce the above // copyright notice, this list of conditions and the following disclaimer // in the documentation and/or other materials provided with the // distribution. // * Neither the name of Google Inc. nor the names of its // contributors may be used to endorse or promote products derived from // this software without specific prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT // OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT // LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, // DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY // THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT // (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE // OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // This file is AUTOMATICALLY GENERATED on 10/31/2011 by command // 'gen_gtest_pred_impl.py 5'. DO NOT EDIT BY HAND! // // Implements a family of generic predicate assertion macros. #ifndef GTEST_INCLUDE_GTEST_GTEST_PRED_IMPL_H_ #define GTEST_INCLUDE_GTEST_GTEST_PRED_IMPL_H_ // Makes sure this header is not included before gtest.h. #ifndef GTEST_INCLUDE_GTEST_GTEST_H_ # error Do not include gtest_pred_impl.h directly. Include gtest.h instead. #endif // GTEST_INCLUDE_GTEST_GTEST_H_ // This header implements a family of generic predicate assertion // macros: // // ASSERT_PRED_FORMAT1(pred_format, v1) // ASSERT_PRED_FORMAT2(pred_format, v1, v2) // ... // // where pred_format is a function or functor that takes n (in the // case of ASSERT_PRED_FORMATn) values and their source expression // text, and returns a testing::AssertionResult. See the definition // of ASSERT_EQ in gtest.h for an example. // // If you don't care about formatting, you can use the more // restrictive version: // // ASSERT_PRED1(pred, v1) // ASSERT_PRED2(pred, v1, v2) // ... // // where pred is an n-ary function or functor that returns bool, // and the values v1, v2, ..., must support the << operator for // streaming to std::ostream. // // We also define the EXPECT_* variations. // // For now we only support predicates whose arity is at most 5. // Please email googletestframework@googlegroups.com if you need // support for higher arities. // GTEST_ASSERT_ is the basic statement to which all of the assertions // in this file reduce. Don't use this in your code. #define GTEST_ASSERT_(expression, on_failure) \ GTEST_AMBIGUOUS_ELSE_BLOCKER_ \ if (const ::testing::AssertionResult gtest_ar = (expression)) \ ; \ else \ on_failure(gtest_ar.failure_message()) // Helper function for implementing {EXPECT|ASSERT}_PRED1. Don't use // this in your code. template AssertionResult AssertPred1Helper(const char* pred_text, const char* e1, Pred pred, const T1& v1) { if (pred(v1)) return AssertionSuccess(); return AssertionFailure() << pred_text << "(" << e1 << ") evaluates to false, where" << "\n" << e1 << " evaluates to " << v1; } // Internal macro for implementing {EXPECT|ASSERT}_PRED_FORMAT1. // Don't use this in your code. #define GTEST_PRED_FORMAT1_(pred_format, v1, on_failure)\ GTEST_ASSERT_(pred_format(#v1, v1), \ on_failure) // Internal macro for implementing {EXPECT|ASSERT}_PRED1. Don't use // this in your code. #define GTEST_PRED1_(pred, v1, on_failure)\ GTEST_ASSERT_(::testing::AssertPred1Helper(#pred, \ #v1, \ pred, \ v1), on_failure) // Unary predicate assertion macros. #define EXPECT_PRED_FORMAT1(pred_format, v1) \ GTEST_PRED_FORMAT1_(pred_format, v1, GTEST_NONFATAL_FAILURE_) #define EXPECT_PRED1(pred, v1) \ GTEST_PRED1_(pred, v1, GTEST_NONFATAL_FAILURE_) #define ASSERT_PRED_FORMAT1(pred_format, v1) \ GTEST_PRED_FORMAT1_(pred_format, v1, GTEST_FATAL_FAILURE_) #define ASSERT_PRED1(pred, v1) \ GTEST_PRED1_(pred, v1, GTEST_FATAL_FAILURE_) // Helper function for implementing {EXPECT|ASSERT}_PRED2. Don't use // this in your code. template AssertionResult AssertPred2Helper(const char* pred_text, const char* e1, const char* e2, Pred pred, const T1& v1, const T2& v2) { if (pred(v1, v2)) return AssertionSuccess(); return AssertionFailure() << pred_text << "(" << e1 << ", " << e2 << ") evaluates to false, where" << "\n" << e1 << " evaluates to " << v1 << "\n" << e2 << " evaluates to " << v2; } // Internal macro for implementing {EXPECT|ASSERT}_PRED_FORMAT2. // Don't use this in your code. #define GTEST_PRED_FORMAT2_(pred_format, v1, v2, on_failure)\ GTEST_ASSERT_(pred_format(#v1, #v2, v1, v2), \ on_failure) // Internal macro for implementing {EXPECT|ASSERT}_PRED2. Don't use // this in your code. #define GTEST_PRED2_(pred, v1, v2, on_failure)\ GTEST_ASSERT_(::testing::AssertPred2Helper(#pred, \ #v1, \ #v2, \ pred, \ v1, \ v2), on_failure) // Binary predicate assertion macros. #define EXPECT_PRED_FORMAT2(pred_format, v1, v2) \ GTEST_PRED_FORMAT2_(pred_format, v1, v2, GTEST_NONFATAL_FAILURE_) #define EXPECT_PRED2(pred, v1, v2) \ GTEST_PRED2_(pred, v1, v2, GTEST_NONFATAL_FAILURE_) #define ASSERT_PRED_FORMAT2(pred_format, v1, v2) \ GTEST_PRED_FORMAT2_(pred_format, v1, v2, GTEST_FATAL_FAILURE_) #define ASSERT_PRED2(pred, v1, v2) \ GTEST_PRED2_(pred, v1, v2, GTEST_FATAL_FAILURE_) // Helper function for implementing {EXPECT|ASSERT}_PRED3. Don't use // this in your code. template AssertionResult AssertPred3Helper(const char* pred_text, const char* e1, const char* e2, const char* e3, Pred pred, const T1& v1, const T2& v2, const T3& v3) { if (pred(v1, v2, v3)) return AssertionSuccess(); return AssertionFailure() << pred_text << "(" << e1 << ", " << e2 << ", " << e3 << ") evaluates to false, where" << "\n" << e1 << " evaluates to " << v1 << "\n" << e2 << " evaluates to " << v2 << "\n" << e3 << " evaluates to " << v3; } // Internal macro for implementing {EXPECT|ASSERT}_PRED_FORMAT3. // Don't use this in your code. #define GTEST_PRED_FORMAT3_(pred_format, v1, v2, v3, on_failure)\ GTEST_ASSERT_(pred_format(#v1, #v2, #v3, v1, v2, v3), \ on_failure) // Internal macro for implementing {EXPECT|ASSERT}_PRED3. Don't use // this in your code. #define GTEST_PRED3_(pred, v1, v2, v3, on_failure)\ GTEST_ASSERT_(::testing::AssertPred3Helper(#pred, \ #v1, \ #v2, \ #v3, \ pred, \ v1, \ v2, \ v3), on_failure) // Ternary predicate assertion macros. #define EXPECT_PRED_FORMAT3(pred_format, v1, v2, v3) \ GTEST_PRED_FORMAT3_(pred_format, v1, v2, v3, GTEST_NONFATAL_FAILURE_) #define EXPECT_PRED3(pred, v1, v2, v3) \ GTEST_PRED3_(pred, v1, v2, v3, GTEST_NONFATAL_FAILURE_) #define ASSERT_PRED_FORMAT3(pred_format, v1, v2, v3) \ GTEST_PRED_FORMAT3_(pred_format, v1, v2, v3, GTEST_FATAL_FAILURE_) #define ASSERT_PRED3(pred, v1, v2, v3) \ GTEST_PRED3_(pred, v1, v2, v3, GTEST_FATAL_FAILURE_) // Helper function for implementing {EXPECT|ASSERT}_PRED4. Don't use // this in your code. template AssertionResult AssertPred4Helper(const char* pred_text, const char* e1, const char* e2, const char* e3, const char* e4, Pred pred, const T1& v1, const T2& v2, const T3& v3, const T4& v4) { if (pred(v1, v2, v3, v4)) return AssertionSuccess(); return AssertionFailure() << pred_text << "(" << e1 << ", " << e2 << ", " << e3 << ", " << e4 << ") evaluates to false, where" << "\n" << e1 << " evaluates to " << v1 << "\n" << e2 << " evaluates to " << v2 << "\n" << e3 << " evaluates to " << v3 << "\n" << e4 << " evaluates to " << v4; } // Internal macro for implementing {EXPECT|ASSERT}_PRED_FORMAT4. // Don't use this in your code. #define GTEST_PRED_FORMAT4_(pred_format, v1, v2, v3, v4, on_failure)\ GTEST_ASSERT_(pred_format(#v1, #v2, #v3, #v4, v1, v2, v3, v4), \ on_failure) // Internal macro for implementing {EXPECT|ASSERT}_PRED4. Don't use // this in your code. #define GTEST_PRED4_(pred, v1, v2, v3, v4, on_failure)\ GTEST_ASSERT_(::testing::AssertPred4Helper(#pred, \ #v1, \ #v2, \ #v3, \ #v4, \ pred, \ v1, \ v2, \ v3, \ v4), on_failure) // 4-ary predicate assertion macros. #define EXPECT_PRED_FORMAT4(pred_format, v1, v2, v3, v4) \ GTEST_PRED_FORMAT4_(pred_format, v1, v2, v3, v4, GTEST_NONFATAL_FAILURE_) #define EXPECT_PRED4(pred, v1, v2, v3, v4) \ GTEST_PRED4_(pred, v1, v2, v3, v4, GTEST_NONFATAL_FAILURE_) #define ASSERT_PRED_FORMAT4(pred_format, v1, v2, v3, v4) \ GTEST_PRED_FORMAT4_(pred_format, v1, v2, v3, v4, GTEST_FATAL_FAILURE_) #define ASSERT_PRED4(pred, v1, v2, v3, v4) \ GTEST_PRED4_(pred, v1, v2, v3, v4, GTEST_FATAL_FAILURE_) // Helper function for implementing {EXPECT|ASSERT}_PRED5. Don't use // this in your code. template AssertionResult AssertPred5Helper(const char* pred_text, const char* e1, const char* e2, const char* e3, const char* e4, const char* e5, Pred pred, const T1& v1, const T2& v2, const T3& v3, const T4& v4, const T5& v5) { if (pred(v1, v2, v3, v4, v5)) return AssertionSuccess(); return AssertionFailure() << pred_text << "(" << e1 << ", " << e2 << ", " << e3 << ", " << e4 << ", " << e5 << ") evaluates to false, where" << "\n" << e1 << " evaluates to " << v1 << "\n" << e2 << " evaluates to " << v2 << "\n" << e3 << " evaluates to " << v3 << "\n" << e4 << " evaluates to " << v4 << "\n" << e5 << " evaluates to " << v5; } // Internal macro for implementing {EXPECT|ASSERT}_PRED_FORMAT5. // Don't use this in your code. #define GTEST_PRED_FORMAT5_(pred_format, v1, v2, v3, v4, v5, on_failure)\ GTEST_ASSERT_(pred_format(#v1, #v2, #v3, #v4, #v5, v1, v2, v3, v4, v5), \ on_failure) // Internal macro for implementing {EXPECT|ASSERT}_PRED5. Don't use // this in your code. #define GTEST_PRED5_(pred, v1, v2, v3, v4, v5, on_failure)\ GTEST_ASSERT_(::testing::AssertPred5Helper(#pred, \ #v1, \ #v2, \ #v3, \ #v4, \ #v5, \ pred, \ v1, \ v2, \ v3, \ v4, \ v5), on_failure) // 5-ary predicate assertion macros. #define EXPECT_PRED_FORMAT5(pred_format, v1, v2, v3, v4, v5) \ GTEST_PRED_FORMAT5_(pred_format, v1, v2, v3, v4, v5, GTEST_NONFATAL_FAILURE_) #define EXPECT_PRED5(pred, v1, v2, v3, v4, v5) \ GTEST_PRED5_(pred, v1, v2, v3, v4, v5, GTEST_NONFATAL_FAILURE_) #define ASSERT_PRED_FORMAT5(pred_format, v1, v2, v3, v4, v5) \ GTEST_PRED_FORMAT5_(pred_format, v1, v2, v3, v4, v5, GTEST_FATAL_FAILURE_) #define ASSERT_PRED5(pred, v1, v2, v3, v4, v5) \ GTEST_PRED5_(pred, v1, v2, v3, v4, v5, GTEST_FATAL_FAILURE_) #endif // GTEST_INCLUDE_GTEST_GTEST_PRED_IMPL_H_ // Macros for testing equalities and inequalities. // // * {ASSERT|EXPECT}_EQ(expected, actual): Tests that expected == actual // * {ASSERT|EXPECT}_NE(v1, v2): Tests that v1 != v2 // * {ASSERT|EXPECT}_LT(v1, v2): Tests that v1 < v2 // * {ASSERT|EXPECT}_LE(v1, v2): Tests that v1 <= v2 // * {ASSERT|EXPECT}_GT(v1, v2): Tests that v1 > v2 // * {ASSERT|EXPECT}_GE(v1, v2): Tests that v1 >= v2 // // When they are not, Google Test prints both the tested expressions and // their actual values. The values must be compatible built-in types, // or you will get a compiler error. By "compatible" we mean that the // values can be compared by the respective operator. // // Note: // // 1. It is possible to make a user-defined type work with // {ASSERT|EXPECT}_??(), but that requires overloading the // comparison operators and is thus discouraged by the Google C++ // Usage Guide. Therefore, you are advised to use the // {ASSERT|EXPECT}_TRUE() macro to assert that two objects are // equal. // // 2. The {ASSERT|EXPECT}_??() macros do pointer comparisons on // pointers (in particular, C strings). Therefore, if you use it // with two C strings, you are testing how their locations in memory // are related, not how their content is related. To compare two C // strings by content, use {ASSERT|EXPECT}_STR*(). // // 3. {ASSERT|EXPECT}_EQ(expected, actual) is preferred to // {ASSERT|EXPECT}_TRUE(expected == actual), as the former tells you // what the actual value is when it fails, and similarly for the // other comparisons. // // 4. Do not depend on the order in which {ASSERT|EXPECT}_??() // evaluate their arguments, which is undefined. // // 5. These macros evaluate their arguments exactly once. // // Examples: // // EXPECT_NE(5, Foo()); // EXPECT_EQ(NULL, a_pointer); // ASSERT_LT(i, array_size); // ASSERT_GT(records.size(), 0) << "There is no record left."; #define EXPECT_EQ(expected, actual) \ EXPECT_PRED_FORMAT2(::testing::internal:: \ EqHelper::Compare, \ expected, actual) #define EXPECT_NE(expected, actual) \ EXPECT_PRED_FORMAT2(::testing::internal::CmpHelperNE, expected, actual) #define EXPECT_LE(val1, val2) \ EXPECT_PRED_FORMAT2(::testing::internal::CmpHelperLE, val1, val2) #define EXPECT_LT(val1, val2) \ EXPECT_PRED_FORMAT2(::testing::internal::CmpHelperLT, val1, val2) #define EXPECT_GE(val1, val2) \ EXPECT_PRED_FORMAT2(::testing::internal::CmpHelperGE, val1, val2) #define EXPECT_GT(val1, val2) \ EXPECT_PRED_FORMAT2(::testing::internal::CmpHelperGT, val1, val2) #define GTEST_ASSERT_EQ(expected, actual) \ ASSERT_PRED_FORMAT2(::testing::internal:: \ EqHelper::Compare, \ expected, actual) #define GTEST_ASSERT_NE(val1, val2) \ ASSERT_PRED_FORMAT2(::testing::internal::CmpHelperNE, val1, val2) #define GTEST_ASSERT_LE(val1, val2) \ ASSERT_PRED_FORMAT2(::testing::internal::CmpHelperLE, val1, val2) #define GTEST_ASSERT_LT(val1, val2) \ ASSERT_PRED_FORMAT2(::testing::internal::CmpHelperLT, val1, val2) #define GTEST_ASSERT_GE(val1, val2) \ ASSERT_PRED_FORMAT2(::testing::internal::CmpHelperGE, val1, val2) #define GTEST_ASSERT_GT(val1, val2) \ ASSERT_PRED_FORMAT2(::testing::internal::CmpHelperGT, val1, val2) // Define macro GTEST_DONT_DEFINE_ASSERT_XY to 1 to omit the definition of // ASSERT_XY(), which clashes with some users' own code. #if !GTEST_DONT_DEFINE_ASSERT_EQ # define ASSERT_EQ(val1, val2) GTEST_ASSERT_EQ(val1, val2) #endif #if !GTEST_DONT_DEFINE_ASSERT_NE # define ASSERT_NE(val1, val2) GTEST_ASSERT_NE(val1, val2) #endif #if !GTEST_DONT_DEFINE_ASSERT_LE # define ASSERT_LE(val1, val2) GTEST_ASSERT_LE(val1, val2) #endif #if !GTEST_DONT_DEFINE_ASSERT_LT # define ASSERT_LT(val1, val2) GTEST_ASSERT_LT(val1, val2) #endif #if !GTEST_DONT_DEFINE_ASSERT_GE # define ASSERT_GE(val1, val2) GTEST_ASSERT_GE(val1, val2) #endif #if !GTEST_DONT_DEFINE_ASSERT_GT # define ASSERT_GT(val1, val2) GTEST_ASSERT_GT(val1, val2) #endif // C-string Comparisons. All tests treat NULL and any non-NULL string // as different. Two NULLs are equal. // // * {ASSERT|EXPECT}_STREQ(s1, s2): Tests that s1 == s2 // * {ASSERT|EXPECT}_STRNE(s1, s2): Tests that s1 != s2 // * {ASSERT|EXPECT}_STRCASEEQ(s1, s2): Tests that s1 == s2, ignoring case // * {ASSERT|EXPECT}_STRCASENE(s1, s2): Tests that s1 != s2, ignoring case // // For wide or narrow string objects, you can use the // {ASSERT|EXPECT}_??() macros. // // Don't depend on the order in which the arguments are evaluated, // which is undefined. // // These macros evaluate their arguments exactly once. #define EXPECT_STREQ(expected, actual) \ EXPECT_PRED_FORMAT2(::testing::internal::CmpHelperSTREQ, expected, actual) #define EXPECT_STRNE(s1, s2) \ EXPECT_PRED_FORMAT2(::testing::internal::CmpHelperSTRNE, s1, s2) #define EXPECT_STRCASEEQ(expected, actual) \ EXPECT_PRED_FORMAT2(::testing::internal::CmpHelperSTRCASEEQ, expected, actual) #define EXPECT_STRCASENE(s1, s2)\ EXPECT_PRED_FORMAT2(::testing::internal::CmpHelperSTRCASENE, s1, s2) #define ASSERT_STREQ(expected, actual) \ ASSERT_PRED_FORMAT2(::testing::internal::CmpHelperSTREQ, expected, actual) #define ASSERT_STRNE(s1, s2) \ ASSERT_PRED_FORMAT2(::testing::internal::CmpHelperSTRNE, s1, s2) #define ASSERT_STRCASEEQ(expected, actual) \ ASSERT_PRED_FORMAT2(::testing::internal::CmpHelperSTRCASEEQ, expected, actual) #define ASSERT_STRCASENE(s1, s2)\ ASSERT_PRED_FORMAT2(::testing::internal::CmpHelperSTRCASENE, s1, s2) // Macros for comparing floating-point numbers. // // * {ASSERT|EXPECT}_FLOAT_EQ(expected, actual): // Tests that two float values are almost equal. // * {ASSERT|EXPECT}_DOUBLE_EQ(expected, actual): // Tests that two double values are almost equal. // * {ASSERT|EXPECT}_NEAR(v1, v2, abs_error): // Tests that v1 and v2 are within the given distance to each other. // // Google Test uses ULP-based comparison to automatically pick a default // error bound that is appropriate for the operands. See the // FloatingPoint template class in gtest-internal.h if you are // interested in the implementation details. #define EXPECT_FLOAT_EQ(expected, actual)\ EXPECT_PRED_FORMAT2(::testing::internal::CmpHelperFloatingPointEQ, \ expected, actual) #define EXPECT_DOUBLE_EQ(expected, actual)\ EXPECT_PRED_FORMAT2(::testing::internal::CmpHelperFloatingPointEQ, \ expected, actual) #define ASSERT_FLOAT_EQ(expected, actual)\ ASSERT_PRED_FORMAT2(::testing::internal::CmpHelperFloatingPointEQ, \ expected, actual) #define ASSERT_DOUBLE_EQ(expected, actual)\ ASSERT_PRED_FORMAT2(::testing::internal::CmpHelperFloatingPointEQ, \ expected, actual) #define EXPECT_NEAR(val1, val2, abs_error)\ EXPECT_PRED_FORMAT3(::testing::internal::DoubleNearPredFormat, \ val1, val2, abs_error) #define ASSERT_NEAR(val1, val2, abs_error)\ ASSERT_PRED_FORMAT3(::testing::internal::DoubleNearPredFormat, \ val1, val2, abs_error) // These predicate format functions work on floating-point values, and // can be used in {ASSERT|EXPECT}_PRED_FORMAT2*(), e.g. // // EXPECT_PRED_FORMAT2(testing::DoubleLE, Foo(), 5.0); // Asserts that val1 is less than, or almost equal to, val2. Fails // otherwise. In particular, it fails if either val1 or val2 is NaN. GTEST_API_ AssertionResult FloatLE(const char* expr1, const char* expr2, float val1, float val2); GTEST_API_ AssertionResult DoubleLE(const char* expr1, const char* expr2, double val1, double val2); #if GTEST_OS_WINDOWS // Macros that test for HRESULT failure and success, these are only useful // on Windows, and rely on Windows SDK macros and APIs to compile. // // * {ASSERT|EXPECT}_HRESULT_{SUCCEEDED|FAILED}(expr) // // When expr unexpectedly fails or succeeds, Google Test prints the // expected result and the actual result with both a human-readable // string representation of the error, if available, as well as the // hex result code. # define EXPECT_HRESULT_SUCCEEDED(expr) \ EXPECT_PRED_FORMAT1(::testing::internal::IsHRESULTSuccess, (expr)) # define ASSERT_HRESULT_SUCCEEDED(expr) \ ASSERT_PRED_FORMAT1(::testing::internal::IsHRESULTSuccess, (expr)) # define EXPECT_HRESULT_FAILED(expr) \ EXPECT_PRED_FORMAT1(::testing::internal::IsHRESULTFailure, (expr)) # define ASSERT_HRESULT_FAILED(expr) \ ASSERT_PRED_FORMAT1(::testing::internal::IsHRESULTFailure, (expr)) #endif // GTEST_OS_WINDOWS // Macros that execute statement and check that it doesn't generate new fatal // failures in the current thread. // // * {ASSERT|EXPECT}_NO_FATAL_FAILURE(statement); // // Examples: // // EXPECT_NO_FATAL_FAILURE(Process()); // ASSERT_NO_FATAL_FAILURE(Process()) << "Process() failed"; // #define ASSERT_NO_FATAL_FAILURE(statement) \ GTEST_TEST_NO_FATAL_FAILURE_(statement, GTEST_FATAL_FAILURE_) #define EXPECT_NO_FATAL_FAILURE(statement) \ GTEST_TEST_NO_FATAL_FAILURE_(statement, GTEST_NONFATAL_FAILURE_) // Causes a trace (including the source file path, the current line // number, and the given message) to be included in every test failure // message generated by code in the current scope. The effect is // undone when the control leaves the current scope. // // The message argument can be anything streamable to std::ostream. // // In the implementation, we include the current line number as part // of the dummy variable name, thus allowing multiple SCOPED_TRACE()s // to appear in the same block - as long as they are on different // lines. #define SCOPED_TRACE(message) \ ::testing::internal::ScopedTrace GTEST_CONCAT_TOKEN_(gtest_trace_, __LINE__)(\ __FILE__, __LINE__, ::testing::Message() << (message)) // Compile-time assertion for type equality. // StaticAssertTypeEq() compiles iff type1 and type2 are // the same type. The value it returns is not interesting. // // Instead of making StaticAssertTypeEq a class template, we make it a // function template that invokes a helper class template. This // prevents a user from misusing StaticAssertTypeEq by // defining objects of that type. // // CAVEAT: // // When used inside a method of a class template, // StaticAssertTypeEq() is effective ONLY IF the method is // instantiated. For example, given: // // template class Foo { // public: // void Bar() { testing::StaticAssertTypeEq(); } // }; // // the code: // // void Test1() { Foo foo; } // // will NOT generate a compiler error, as Foo::Bar() is never // actually instantiated. Instead, you need: // // void Test2() { Foo foo; foo.Bar(); } // // to cause a compiler error. template bool StaticAssertTypeEq() { (void)internal::StaticAssertTypeEqHelper(); return true; } // Defines a test. // // The first parameter is the name of the test case, and the second // parameter is the name of the test within the test case. // // The convention is to end the test case name with "Test". For // example, a test case for the Foo class can be named FooTest. // // The user should put his test code between braces after using this // macro. Example: // // TEST(FooTest, InitializesCorrectly) { // Foo foo; // EXPECT_TRUE(foo.StatusIsOK()); // } // Note that we call GetTestTypeId() instead of GetTypeId< // ::testing::Test>() here to get the type ID of testing::Test. This // is to work around a suspected linker bug when using Google Test as // a framework on Mac OS X. The bug causes GetTypeId< // ::testing::Test>() to return different values depending on whether // the call is from the Google Test framework itself or from user test // code. GetTestTypeId() is guaranteed to always return the same // value, as it always calls GetTypeId<>() from the Google Test // framework. #define GTEST_TEST(test_case_name, test_name)\ GTEST_TEST_(test_case_name, test_name, \ ::testing::Test, ::testing::internal::GetTestTypeId()) // Define this macro to 1 to omit the definition of TEST(), which // is a generic name and clashes with some other libraries. #if !GTEST_DONT_DEFINE_TEST # define TEST(test_case_name, test_name) GTEST_TEST(test_case_name, test_name) #endif // Defines a test that uses a test fixture. // // The first parameter is the name of the test fixture class, which // also doubles as the test case name. The second parameter is the // name of the test within the test case. // // A test fixture class must be declared earlier. The user should put // his test code between braces after using this macro. Example: // // class FooTest : public testing::Test { // protected: // virtual void SetUp() { b_.AddElement(3); } // // Foo a_; // Foo b_; // }; // // TEST_F(FooTest, InitializesCorrectly) { // EXPECT_TRUE(a_.StatusIsOK()); // } // // TEST_F(FooTest, ReturnsElementCountCorrectly) { // EXPECT_EQ(0, a_.size()); // EXPECT_EQ(1, b_.size()); // } #define TEST_F(test_fixture, test_name)\ GTEST_TEST_(test_fixture, test_name, test_fixture, \ ::testing::internal::GetTypeId()) } // namespace testing // Use this function in main() to run all tests. 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Mersenne Twister Random Number Generator

The Mersenne Twister is an algorithm for generating random numbers. It was designed with consideration of the flaws in various other generators. It has an incredibly long period, 219937-1 (more than 106001), before its sequence of numbers will repeat. And it has 623 dimensions of equidistribution, meaning that all sequences up to 623 numbers long are equally probable. The generator is also fast; it avoids multiplication and division, and it benefits from caches and pipelines. See the inventors' page or Wikipedia article for more details.

I have implemented the Mersenne Twister in a C++ class that is fast, convenient, portable, and free. Take a look at the class and example program. Or download the complete package in zip or tarball format.

Features:

  • Simple creation of generator with MTRand r;
  • Convenient access with double a = r();
  • Generation of integers or floating-point numbers
  • Easy seeding options
    • Automatically from /dev/urandom or time() and clock()
    • Single integer
    • Arrays of any length (to access full 19937-bit range)
  • Ability to save and restore state
  • Thorough example program
  • Validation and performance tests
  • Open source code under BSD license

The included performance tests verify the speed and correctness of this generator compared to known sequences and alternative implementations. It has been tested in a variety of hardware and software environments including: Intel Core 2 Quad, AMD Opteron 848; Red Hat Linux, Mac OS X 10.5 Leopard, Windows XP; GNU Compiler Collection 4.2 (g++), Intel Compiler 10.1 (icpc), Portland Group International Compiler 9.0 (pgCC), Pathscale Compiler 3.1 (pathCC), and Microsoft Visual C++ 2008.

Version 1.0 incorporated several changes released by the Mersenne Twister inventors on 26 January 2002. The seeding algorithm was revised to correct a minor problem in which the highest bit of the seed was not well represented in the generator state. The ability to start with large seeds was extended to seed arrays of arbitrary length. Access was added for 53-bit real numbers in [0,1), matching the accuracy of IEEE doubles. Also, the software license was changed from the GNU Lesser General Public License to a BSD license, making commercial use of this software more convenient.

The v1.0 release included some other improvements as well. By popular demand, access was added for real numbers from normal (Gaussian) distributions. Safeguards were added to prevent out-of-range number generation on 64-bit machines. Finally, new optimizations yielded 25% faster generation overall and 100% faster generation for integers in [0,n].

Version 1.1 focuses on portability and reliability. Instances of deprecated C++ features were modernized. Operations were rewritten to work on ones'-complement machines and environments with unsigned enumerations. The test program was toughened and expanded. A slight correction was made in terminology; the parameter for setting the standard deviation of a Gaussian distribution is now properly labeled as "stddev" rather than "variance". A copy constructor and copy operator were also added. The seed correlations, generator functions, output sequences, and save formats are identical to Version 1.0.

Downloads:
Version 1.1Mersenne-1.1.zipMersenne-1.1.tar.gz
Version 1.0Mersenne-1.0.zipMersenne-1.0.tar.gz
Version 0.8Mersenne-0.8.zipMersenne-0.8.tar.gz
Version 0.7Mersenne-0.7.zipMersenne-0.7.tar.gz
Version 0.6Mersenne-0.6.zipMersenne-0.6.tar.gz
Version 0.5Mersenne-0.5.zipMersenne-0.5.tar.gz
Version 0.4Mersenne-0.4.zipMersenne-0.4.tar.gz
Version 0.3Mersenne-0.3.zipMersenne-0.3.tar.gz
Version 0.2Mersenne-0.2.zipMersenne-0.2.tar.gz
Version 0.1Mersenne-0.1.zipMersenne-0.1.tar.gz

Comments, questions, and improvements are always welcome.

If you like this software, you might also want to try my ConfigFile (C++) configuration file reader and Anneal.py (Python) module for optimization by simulated annealing.

Creations of Rick Wagner (wagnerr@umich.edu) 30 September 2009 april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/README000066400000000000000000000040561263004425400237260ustar00rootroot00000000000000README for MersenneTwister.h package Richard J. Wagner v1.1 29 September 2009 Instructions ------------ The only necessary file for using this Mersenne Twister random number generator is "MersenneTwister.h". The class name is MTRand. Usage examples are in "example.cpp". Linux, Unix, and Max OS X users can type "make" to compile and then type "./example" to run the example program. To test the output and compare to other random number generators type "make test". When you are done with testing, type "make clean" to get rid of temporary files. For Windows users with a compiler such as Microsoft Visual C++, simply add "example.cpp" and "MersenneTwister.h" to an empty C++ console application. Compile and run to see the generator in action. The "make" command will not work, so the test program "Test/Wagner/Wagner.cpp" must be run manually if desired. The output should contain no error messages and the lists of random numbers should exactly match those in "Test/Reference.out". If you encounter any problems, please e-mail a copy of the output and a description of the test system to me at "wagnerr@umich.edu". Any other feedback is welcome too. Installation ------------ Just copy the file "MersenneTwister.h" to your working directory or some other place where your compiler can find it. Put the following line at the top of your program to access the MTRand class: #include "MersenneTwister.h" Contents -------- README - this file MersenneTwister.h - declaration and implementation of MTRand class example.cpp - examples of using MTRand Makefile - instructions used by "make" command MersenneTwister.html - Web page about MersenneTwister.h Random.jpg - background for MersenneTwister.html Test/Makefile - instructions used by "make" command for test programs Test/Results.sh - script to examine the output from test programs Test/Reference.out - expected output from MT random number generators Test/Wagner/ - test program for MersenneTwister.h Test/*/ - test programs for other MT implementations april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Random.jpg000066400000000000000000000146051263004425400247710ustar00rootroot00000000000000JFIFKKLEAD Technologies Inc. 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Wagner 28 Sep 2009 // This is free, unrestricted software void of any warranty. #include #include #include "mtrand.h" int main ( int argc, char * const argv[] ) { printf( "Testing output and speed of Bedaux's Mersenne Twister class\n" ); printf( "\nTest of random integer generation:\n" ); unsigned long oneSeed = 4357UL; unsigned long bigSeed[4] = { 0x123UL, 0x234UL, 0x345UL, 0x456UL }; printf( "\nTest of random integer generation:\n" ); MTRand_int32 mtrand1( bigSeed, 4 ); unsigned long i; for( i = 0; i < 1000UL; ++i ) { printf( "%10lu ", mtrand1() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1) generation:\n" ); MTRand mtrand2( bigSeed, 4 ); for( i = 0; i < 1000UL; ++i ) mtrand2(); // advance to the proper position in the series for( i = 0; i < 1000UL; ++i ) { printf( "%10.8f ", mtrand2() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1] generation:\n" ); MTRand_closed mtrand3( oneSeed ); for( i = 0; i < 2000UL; ++i ) { printf( "%10.8f ", mtrand3() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of time to generate one billion random integers:\n" ); MTRand_int32 mtrand4( oneSeed ); unsigned long junk = 0; clock_t start = clock(); for( i = 0; i < 1000000000UL; ++i ) { junk ^= mtrand4(); } clock_t stop = clock(); if( junk == 0 ) printf( "jinx\n" ); printf( "Time elapsed = " ); printf( "%8.3f", double( stop - start ) / CLOCKS_PER_SEC ); printf( " s\n" ); return 0; } april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Bedaux/mtrand.cpp000066400000000000000000000040231263004425400271600ustar00rootroot00000000000000// mtrand.cpp, see include file mtrand.h for information #include "mtrand.h" // non-inline function definitions and static member definitions cannot // reside in header file because of the risk of multiple declarations // initialization of static private members unsigned long MTRand_int32::state[n] = {0x0UL}; int MTRand_int32::p = 0; bool MTRand_int32::init = false; void MTRand_int32::gen_state() { // generate new state vector for (int i = 0; i < (n - m); ++i) state[i] = state[i + m] ^ twiddle(state[i], state[i + 1]); for (int i = n - m; i < (n - 1); ++i) state[i] = state[i + m - n] ^ twiddle(state[i], state[i + 1]); state[n - 1] = state[m - 1] ^ twiddle(state[n - 1], state[0]); p = 0; // reset position } void MTRand_int32::seed(unsigned long s) { // init by 32 bit seed state[0] = s & 0xFFFFFFFFUL; // for > 32 bit machines for (int i = 1; i < n; ++i) { state[i] = 1812433253UL * (state[i - 1] ^ (state[i - 1] >> 30)) + i; // see Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier // in the previous versions, MSBs of the seed affect only MSBs of the array state // 2002/01/09 modified by Makoto Matsumoto state[i] &= 0xFFFFFFFFUL; // for > 32 bit machines } p = n; // force gen_state() to be called for next random number } void MTRand_int32::seed(const unsigned long* array, int size) { // init by array seed(19650218UL); int i = 1, j = 0; for (int k = ((n > size) ? n : size); k; --k) { state[i] = (state[i] ^ ((state[i - 1] ^ (state[i - 1] >> 30)) * 1664525UL)) + array[j] + j; // non linear state[i] &= 0xFFFFFFFFUL; // for > 32 bit machines ++j; j %= size; if ((++i) == n) { state[0] = state[n - 1]; i = 1; } } for (int k = n - 1; k; --k) { state[i] = (state[i] ^ ((state[i - 1] ^ (state[i - 1] >> 30)) * 1566083941UL)) - i; state[i] &= 0xFFFFFFFFUL; // for > 32 bit machines if ((++i) == n) { state[0] = state[n - 1]; i = 1; } } state[0] = 0x80000000UL; // MSB is 1; assuring non-zero initial array p = n; // force gen_state() to be called for next random number } april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Bedaux/mtrand.h000066400000000000000000000153741263004425400266400ustar00rootroot00000000000000// mtrand.h // C++ include file for MT19937, with initialization improved 2002/1/26. // Coded by Takuji Nishimura and Makoto Matsumoto. // Ported to C++ by Jasper Bedaux 2003/1/1 (see http://www.bedaux.net/mtrand/). // The generators returning floating point numbers are based on // a version by Isaku Wada, 2002/01/09 // // Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura, // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions // are met: // // 1. Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // // 2. Redistributions in binary form must reproduce the above copyright // notice, this list of conditions and the following disclaimer in the // documentation and/or other materials provided with the distribution. // // 3. The names of its contributors may not be used to endorse or promote // products derived from this software without specific prior written // permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS // "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT // LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR // A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR // CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, // EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, // PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. // // Any feedback is very welcome. // http://www.math.keio.ac.jp/matumoto/emt.html // email: matumoto@math.keio.ac.jp // // Feedback about the C++ port should be sent to Jasper Bedaux, // see http://www.bedaux.net/mtrand/ for e-mail address and info. #ifndef MTRAND_H #define MTRAND_H class MTRand_int32 { // Mersenne Twister random number generator public: // default constructor: uses default seed only if this is the first instance MTRand_int32() { if (!init) seed(5489UL); init = true; } // constructor with 32 bit int as seed MTRand_int32(unsigned long s) { seed(s); init = true; } // constructor with array of size 32 bit ints as seed MTRand_int32(const unsigned long* array, int size) { seed(array, size); init = true; } // the two seed functions void seed(unsigned long); // seed with 32 bit integer void seed(const unsigned long*, int size); // seed with array // overload operator() to make this a generator (functor) unsigned long operator()() { return rand_int32(); } // 2007-02-11: made the destructor virtual; thanks "double more" for pointing this out virtual ~MTRand_int32() {} // destructor protected: // used by derived classes, otherwise not accessible; use the ()-operator unsigned long rand_int32(); // generate 32 bit random integer private: static const int n = 624, m = 397; // compile time constants // the variables below are static (no duplicates can exist) static unsigned long state[n]; // state vector array static int p; // position in state array static bool init; // true if init function is called // private functions used to generate the pseudo random numbers unsigned long twiddle(unsigned long, unsigned long); // used by gen_state() void gen_state(); // generate new state // make copy constructor and assignment operator unavailable, they don't make sense MTRand_int32(const MTRand_int32&); // copy constructor not defined void operator=(const MTRand_int32&); // assignment operator not defined }; // inline for speed, must therefore reside in header file inline unsigned long MTRand_int32::twiddle(unsigned long u, unsigned long v) { return (((u & 0x80000000UL) | (v & 0x7FFFFFFFUL)) >> 1) ^ ((v & 1UL) ? 0x9908B0DFUL : 0x0UL); } inline unsigned long MTRand_int32::rand_int32() { // generate 32 bit random int if (p == n) gen_state(); // new state vector needed // gen_state() is split off to be non-inline, because it is only called once // in every 624 calls and otherwise irand() would become too big to get inlined unsigned long x = state[p++]; x ^= (x >> 11); x ^= (x << 7) & 0x9D2C5680UL; x ^= (x << 15) & 0xEFC60000UL; return x ^ (x >> 18); } // generates double floating point numbers in the half-open interval [0, 1) class MTRand : public MTRand_int32 { public: MTRand() : MTRand_int32() {} MTRand(unsigned long seed) : MTRand_int32(seed) {} MTRand(const unsigned long* seed, int size) : MTRand_int32(seed, size) {} ~MTRand() {} double operator()() { return static_cast(rand_int32()) * (1. / 4294967296.); } // divided by 2^32 private: MTRand(const MTRand&); // copy constructor not defined void operator=(const MTRand&); // assignment operator not defined }; // generates double floating point numbers in the closed interval [0, 1] class MTRand_closed : public MTRand_int32 { public: MTRand_closed() : MTRand_int32() {} MTRand_closed(unsigned long seed) : MTRand_int32(seed) {} MTRand_closed(const unsigned long* seed, int size) : MTRand_int32(seed, size) {} ~MTRand_closed() {} double operator()() { return static_cast(rand_int32()) * (1. / 4294967295.); } // divided by 2^32 - 1 private: MTRand_closed(const MTRand_closed&); // copy constructor not defined void operator=(const MTRand_closed&); // assignment operator not defined }; // generates double floating point numbers in the open interval (0, 1) class MTRand_open : public MTRand_int32 { public: MTRand_open() : MTRand_int32() {} MTRand_open(unsigned long seed) : MTRand_int32(seed) {} MTRand_open(const unsigned long* seed, int size) : MTRand_int32(seed, size) {} ~MTRand_open() {} double operator()() { return (static_cast(rand_int32()) + .5) * (1. / 4294967296.); } // divided by 2^32 private: MTRand_open(const MTRand_open&); // copy constructor not defined void operator=(const MTRand_open&); // assignment operator not defined }; // generates 53 bit resolution doubles in the half-open interval [0, 1) class MTRand53 : public MTRand_int32 { public: MTRand53() : MTRand_int32() {} MTRand53(unsigned long seed) : MTRand_int32(seed) {} MTRand53(const unsigned long* seed, int size) : MTRand_int32(seed, size) {} ~MTRand53() {} double operator()() { return (static_cast(rand_int32() >> 5) * 67108864. + static_cast(rand_int32() >> 6)) * (1. / 9007199254740992.); } private: MTRand53(const MTRand53&); // copy constructor not defined void operator=(const MTRand53&); // assignment operator not defined }; #endif // MTRAND_H april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Blevins/000077500000000000000000000000001263004425400253625ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Blevins/Blevins.cpp000066400000000000000000000032031263004425400274660ustar00rootroot00000000000000// Blevins.cpp // Test output and speed of Blevins's Mersenne Twister class // Richard J. Wagner 28 Sep 2009 // This is free, unrestricted software void of any warranty. #include #include #include "mt.h" int main ( int argc, char * const argv[] ) { printf( "Testing output and speed of Blevins's Mersenne Twister class\n" ); printf( "\nTest of random integer generation:\n" ); unsigned long oneSeed = 4357UL; unsigned long bigSeed[4] = { 0x123UL, 0x234UL, 0x345UL, 0x456UL }; printf( "\nTest of random integer generation:\n" ); MersenneTwister mtrand1; mtrand1.init_by_array( bigSeed, 4 ); unsigned long i; for( i = 0; i < 1000UL; ++i ) { printf( "%10lu ", mtrand1.genrand_int32() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1) generation:\n" ); for( i = 0; i < 1000UL; ++i ) { printf( "%10.8f ", mtrand1.genrand_real2() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1] generation:\n" ); mtrand1.init_genrand( oneSeed ); for( i = 0; i < 2000UL; ++i ) { printf( "%10.8f ", mtrand1.genrand_real1() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of time to generate one billion random integers:\n" ); MersenneTwister mtrand2; mtrand2.init_genrand( oneSeed ); unsigned long junk = 0; clock_t start = clock(); for( i = 0; i < 1000000000UL; ++i ) { junk ^= mtrand2.genrand_int32(); } clock_t stop = clock(); if( junk == 0 ) printf( "jinx\n" ); printf( "Time elapsed = " ); printf( "%8.3f", double( stop - start ) / CLOCKS_PER_SEC ); printf( " s\n" ); return 0; } april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Blevins/mt.cc000066400000000000000000000167621263004425400263250ustar00rootroot00000000000000/** * C++ Mersenne Twister wrapper class written by * Jason R. Blevins on July 24, 2006. * Based on the original MT19937 C code by * Takuji Nishimura and Makoto Matsumoto. */ /* A C-program for MT19937, with initialization improved 2002/1/26. Coded by Takuji Nishimura and Makoto Matsumoto. Before using, initialize the state by using init_genrand(seed) or init_by_array(init_key, key_length). Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura, All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. The names of its contributors may not be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Any feedback is very welcome. http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space) */ #include #include "april_assert.h" #include "mt.h" /** * Constructor */ MersenneTwister::MersenneTwister(void): mt_(new unsigned long[N]), mti_(N+1), init_key_(NULL), key_length_(0), s_(0), seeded_by_array_(false), seeded_by_int_(false) { unsigned long init[4] = { 0x123, 0x234, 0x345, 0x456 }; unsigned long length = 4; init_by_array(init, length); } /** * Destructor */ MersenneTwister::~MersenneTwister(void) { april_assert(mt_ != NULL); delete[] mt_; mt_ = NULL; april_assert(init_key_ != NULL); delete[] init_key_; init_key_ = NULL; } /** * Initializes the Mersenne Twister with a seed. * * \param s seed */ void MersenneTwister::init_genrand(unsigned long s) { mt_[0]= s & 0xffffffffUL; for (mti_=1; mti_> 30)) + mti_); /* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */ /* In the previous versions, MSBs of the seed affect */ /* only MSBs of the array mt_[]. */ /* 2002/01/09 modified by Makoto Matsumoto */ mt_[mti_] &= 0xffffffffUL; /* for >32 bit machines */ } // Store the seed s_ = s; seeded_by_array_ = false; seeded_by_int_ = true; } /** * Seed the Mersenne Twister using an array. * * \param init_key an array for initializing keys * \param key_length the length of \a init_key */ void MersenneTwister::init_by_array(unsigned long* init_key, int key_length) { // Store the key array int i, j, k; init_genrand(19650218UL); i=1; j=0; k = (N>key_length ? N : key_length); for (; k; k--) { mt_[i] = (mt_[i] ^ ((mt_[i-1] ^ (mt_[i-1] >> 30)) * 1664525UL)) + init_key[j] + j; /* non linear */ mt_[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */ i++; j++; if (i>=N) { mt_[0] = mt_[N-1]; i=1; } if (j>=key_length) j=0; } for (k=N-1; k; k--) { mt_[i] = (mt_[i] ^ ((mt_[i-1] ^ (mt_[i-1] >> 30)) * 1566083941UL)) - i; /* non linear */ mt_[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */ i++; if (i>=N) { mt_[0] = mt_[N-1]; i=1; } } mt_[0] = 0x80000000UL; /* MSB is 1; assuring non-zero initial array */ // Store the seed if (init_key_ != NULL) { delete[] init_key_; } init_key_ = new unsigned long[key_length]; for (int k = 0; k < key_length; k++) { init_key_[k] = init_key[k]; } key_length_ = key_length; seeded_by_int_ = false; seeded_by_array_ = true; } /** * Generates a random number on [0,0xffffffff]-interval * * \return random number on [0, 0xffffffff] */ unsigned long MersenneTwister::genrand_int32(void) { unsigned long y; static unsigned long mag01[2]={0x0UL, MATRIX_A}; /* mag01[x] = x * MATRIX_A for x=0,1 */ if (mti_ >= N) { /* generate N words at one time */ int kk; if (mti_ == N+1) /* if init_genrand() has not been called, */ init_genrand(5489UL); /* a default initial seed is used */ for (kk=0;kk> 1) ^ mag01[y & 0x1UL]; } for (;kk> 1) ^ mag01[y & 0x1UL]; } y = (mt_[N-1]&UPPER_MASK)|(mt_[0]&LOWER_MASK); mt_[N-1] = mt_[M-1] ^ (y >> 1) ^ mag01[y & 0x1UL]; mti_ = 0; } y = mt_[mti_++]; /* Tempering */ y ^= (y >> 11); y ^= (y << 7) & 0x9d2c5680UL; y ^= (y << 15) & 0xefc60000UL; y ^= (y >> 18); return y; } /** * Generates a random integer on [0,0x7fffffff]. * * \return a random integer on [0,0x7fffffff] */ long MersenneTwister::genrand_int31(void) { return (long)(genrand_int32()>>1); } /** * Generates a random real number on [0,1]. * * \return a random real number on [0,1] */ double MersenneTwister::genrand_real1(void) { return genrand_int32()*(1.0/4294967295.0); /* divided by 2^32-1 */ } /** * Generates a random real number on [0,1). * * \return a random real number on [0,1) */ double MersenneTwister::genrand_real2(void) { return genrand_int32()*(1.0/4294967296.0); /* divided by 2^32 */ } /** * Generates a random real number on (0,1). * * \return a random real number on (0,1) */ double MersenneTwister::genrand_real3(void) { return (((double)genrand_int32()) + 0.5)*(1.0/4294967296.0); /* divided by 2^32 */ } /** * Generates a random real number on [0,1) with 53-bit precision. * * \return a random 53-bit real number on [0,1) */ double MersenneTwister::genrand_res53(void) { unsigned long a=genrand_int32()>>5, b=genrand_int32()>>6; return(a*67108864.0+b)*(1.0/9007199254740992.0); } /* These real versions are due to Isaku Wada, 2002/01/09 added */ /** * Print interesting information about the Mersenne Twister. * */ void MersenneTwister::print(void) { std::cout << "MersenneTwister (M. Matsumoto and T. Nishimura), seed = "; if (seeded_by_int_) { std::cout << s_ << std::endl; } else { std::cout << "[ "; for (int k = 0; k < key_length_; k++) { std::cout << init_key_[k] << " "; } std::cout << "]" << std::endl; } } april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Blevins/mt.h000066400000000000000000000034271263004425400261610ustar00rootroot00000000000000/** * mt.h: Mersenne Twister header file * * Jason R. Blevins * Durham, March 7, 2007 */ #ifndef METRICS_MT_H #define METRICS_MT_H /** * Mersenne Twister. * * M. Matsumoto and T. Nishimura, "Mersenne Twister: A * 623-dimensionally equidistributed uniform pseudorandom number * generator", ACM Trans. on Modeling and Computer Simulation Vol. 8, * No. 1, January pp.3-30 (1998). * * http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html. */ class MersenneTwister { public: MersenneTwister(void); ~MersenneTwister(void); double random(void) { return genrand_real1(); } void print(void); void init_genrand(unsigned long s); void init_by_array(unsigned long* init_key, int key_length); unsigned long genrand_int32(void); long genrand_int31(void); double genrand_real1(void); double genrand_real2(void); double genrand_real3(void); double genrand_res53(void); private: static const int N = 624; static const int M = 397; // constant vector a static const unsigned long MATRIX_A = 0x9908b0dfUL; // most significant w-r bits static const unsigned long UPPER_MASK = 0x80000000UL; // least significant r bits static const unsigned long LOWER_MASK = 0x7fffffffUL; unsigned long* mt_; // the state vector int mti_; // mti == N+1 means mt not initialized unsigned long* init_key_; // Storage for the seed vector int key_length_; // Seed vector length unsigned long s_; // Seed integer bool seeded_by_array_; // Seeded by an array bool seeded_by_int_; // Seeded by an integer }; #endif // METRICS_MT_H april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Cokus/000077500000000000000000000000001263004425400250445ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Cokus/Cokus.cpp000066400000000000000000000030361263004425400266360ustar00rootroot00000000000000// Cokus.cpp // Test output and speed of Cokus's Mersenne Twister program // Richard J. Wagner 28 Sep 2009 // This is free, unrestricted software void of any warranty. #include #include #include "mt19937ar-cok.c" int main ( int argc, char * const argv[] ) { printf( "Testing output and speed of Cokus's Mersenne Twister program\n" ); printf( "\nTest of random integer generation:\n" ); unsigned long oneSeed = 4357UL; unsigned long bigSeed[4] = { 0x123UL, 0x234UL, 0x345UL, 0x456UL }; printf( "\nTest of random integer generation:\n" ); init_by_array( bigSeed, 4 ); unsigned long i; for( i = 0; i < 1000UL; ++i ) { printf( "%10lu ", genrand_int32() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1) generation:\n" ); for( i = 0; i < 1000UL; ++i ) { printf( "%10.8f ", genrand_real2() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1] generation:\n" ); init_genrand( oneSeed ); for( i = 0; i < 2000UL; ++i ) { printf( "%10.8f ", genrand_real1() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of time to generate one billion random integers:\n" ); init_genrand( oneSeed ); unsigned long junk = 0; clock_t start = clock(); for( i = 0; i < 1000000000UL; ++i ) { junk ^= genrand_int32(); } clock_t stop = clock(); if( junk == 0 ) printf( "jinx\n" ); printf( "Time elapsed = " ); printf( "%8.3f", double( stop - start ) / CLOCKS_PER_SEC ); printf( " s\n" ); return 0; } april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Cokus/mt19937ar-cok.c000066400000000000000000000163101263004425400273430ustar00rootroot00000000000000/* A C-program for MT19937, with initialization improved 2002/2/10. Coded by Takuji Nishimura and Makoto Matsumoto. This is a faster version by taking Shawn Cokus's optimization, Matthe Bellew's simplification, Isaku Wada's real version. Before using, initialize the state by using init_genrand(seed) or init_by_array(init_key, key_length). Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura, All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. The names of its contributors may not be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Any feedback is very welcome. http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space) */ #include /* Period parameters */ #define N 624 #define M 397 #define MATRIX_A 0x9908b0dfUL /* constant vector a */ #define UMASK 0x80000000UL /* most significant w-r bits */ #define LMASK 0x7fffffffUL /* least significant r bits */ #define MIXBITS(u,v) ( ((u) & UMASK) | ((v) & LMASK) ) #define TWIST(u,v) ((MIXBITS(u,v) >> 1) ^ ((v)&1UL ? MATRIX_A : 0UL)) static unsigned long state[N]; /* the array for the state vector */ static int left = 1; static int initf = 0; static unsigned long *next; /* initializes state[N] with a seed */ void init_genrand(unsigned long s) { int j; state[0]= s & 0xffffffffUL; for (j=1; j> 30)) + j); /* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */ /* In the previous versions, MSBs of the seed affect */ /* only MSBs of the array state[]. */ /* 2002/01/09 modified by Makoto Matsumoto */ state[j] &= 0xffffffffUL; /* for >32 bit machines */ } left = 1; initf = 1; } /* initialize by an array with array-length */ /* init_key is the array for initializing keys */ /* key_length is its length */ /* slight change for C++, 2004/2/26 */ void init_by_array(unsigned long init_key[], int key_length) { int i, j, k; init_genrand(19650218UL); i=1; j=0; k = (N>key_length ? N : key_length); for (; k; k--) { state[i] = (state[i] ^ ((state[i-1] ^ (state[i-1] >> 30)) * 1664525UL)) + init_key[j] + j; /* non linear */ state[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */ i++; j++; if (i>=N) { state[0] = state[N-1]; i=1; } if (j>=key_length) j=0; } for (k=N-1; k; k--) { state[i] = (state[i] ^ ((state[i-1] ^ (state[i-1] >> 30)) * 1566083941UL)) - i; /* non linear */ state[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */ i++; if (i>=N) { state[0] = state[N-1]; i=1; } } state[0] = 0x80000000UL; /* MSB is 1; assuring non-zero initial array */ left = 1; initf = 1; } static void next_state(void) { unsigned long *p=state; int j; /* if init_genrand() has not been called, */ /* a default initial seed is used */ if (initf==0) init_genrand(5489UL); left = N; next = state; for (j=N-M+1; --j; p++) *p = p[M] ^ TWIST(p[0], p[1]); for (j=M; --j; p++) *p = p[M-N] ^ TWIST(p[0], p[1]); *p = p[M-N] ^ TWIST(p[0], state[0]); } /* generates a random number on [0,0xffffffff]-interval */ unsigned long genrand_int32(void) { unsigned long y; if (--left == 0) next_state(); y = *next++; /* Tempering */ y ^= (y >> 11); y ^= (y << 7) & 0x9d2c5680UL; y ^= (y << 15) & 0xefc60000UL; y ^= (y >> 18); return y; } /* generates a random number on [0,0x7fffffff]-interval */ long genrand_int31(void) { unsigned long y; if (--left == 0) next_state(); y = *next++; /* Tempering */ y ^= (y >> 11); y ^= (y << 7) & 0x9d2c5680UL; y ^= (y << 15) & 0xefc60000UL; y ^= (y >> 18); return (long)(y>>1); } /* generates a random number on [0,1]-real-interval */ double genrand_real1(void) { unsigned long y; if (--left == 0) next_state(); y = *next++; /* Tempering */ y ^= (y >> 11); y ^= (y << 7) & 0x9d2c5680UL; y ^= (y << 15) & 0xefc60000UL; y ^= (y >> 18); return (double)y * (1.0/4294967295.0); /* divided by 2^32-1 */ } /* generates a random number on [0,1)-real-interval */ double genrand_real2(void) { unsigned long y; if (--left == 0) next_state(); y = *next++; /* Tempering */ y ^= (y >> 11); y ^= (y << 7) & 0x9d2c5680UL; y ^= (y << 15) & 0xefc60000UL; y ^= (y >> 18); return (double)y * (1.0/4294967296.0); /* divided by 2^32 */ } /* generates a random number on (0,1)-real-interval */ double genrand_real3(void) { unsigned long y; if (--left == 0) next_state(); y = *next++; /* Tempering */ y ^= (y >> 11); y ^= (y << 7) & 0x9d2c5680UL; y ^= (y << 15) & 0xefc60000UL; y ^= (y >> 18); return ((double)y + 0.5) * (1.0/4294967296.0); /* divided by 2^32 */ } /* generates a random number on [0,1) with 53-bit resolution*/ double genrand_res53(void) { unsigned long a=genrand_int32()>>5, b=genrand_int32()>>6; return(a*67108864.0+b)*(1.0/9007199254740992.0); } /* These real versions are due to Isaku Wada, 2002/01/09 added */ /* int main(void) { int i; unsigned long init[4]={0x123, 0x234, 0x345, 0x456}, length=4; init_by_array(init, length); */ /* This is an example of initializing by an array. */ /* You may use init_genrand(seed) with any 32bit integer */ /* as a seed for a simpler initialization */ /* printf("1000 outputs of genrand_int32()\n"); for (i=0; i<1000; i++) { printf("%10lu ", genrand_int32()); if (i%5==4) printf("\n"); } printf("\n1000 outputs of genrand_real2()\n"); for (i=0; i<1000; i++) { printf("%10.8f ", genrand_real2()); if (i%5==4) printf("\n"); } return 0; } */ april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Kuenning/000077500000000000000000000000001263004425400255365ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Kuenning/Kuenning.cpp000066400000000000000000000031631263004425400300230ustar00rootroot00000000000000// Kuenning.cpp // Test output and speed of Kuenning's Mersenne Twister class // Richard J. Wagner 28 Sep 2009 // This is free, unrestricted software void of any warranty. #include #include #include "mtwist.h" int main ( int argc, char * const argv[] ) { printf( "Testing output and speed of Kuenning's Mersenne Twister class\n" ); printf( "\nTest of random integer generation:\n" ); unsigned long oneSeed = 4357UL; mt_u32bit_t bigSeed[MT_STATE_SIZE] = { 0x123, 0x234, 0x345, 0x456 }; // NOTE: Kuenning's class lacks the usual seeding and generation functions printf( "\nTest of random integer generation:\n" ); mt_prng mtrand1( bigSeed ); unsigned long i; for( i = 0; i < 1000UL; ++i ) { printf( "%10lu ", mtrand1.lrand() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1) generation:\n" ); for( i = 0; i < 1000UL; ++i ) { printf( "%10.8f ", mtrand1.drand() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1] generation:\n" ); mt_prng mtrand2( oneSeed ); for( i = 0; i < 2000UL; ++i ) { printf( "%10.8f ", mtrand2.drand() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of time to generate one billion random integers:\n" ); mt_prng mtrand3( oneSeed ); unsigned long junk = 0; clock_t start = clock(); for( i = 0; i < 1000000000UL; ++i ) { junk ^= mtrand3.lrand(); } clock_t stop = clock(); if( junk == 0 ) printf( "jinx\n" ); printf( "Time elapsed = " ); printf( "%8.3f", double( stop - start ) / CLOCKS_PER_SEC ); printf( " s\n" ); return 0; } april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Kuenning/mtwist.c000066400000000000000000001011751263004425400272360ustar00rootroot00000000000000#ifndef lint static char Rcs_Id[] = "$Id: mtwist.c,v 1.20 2007/10/26 07:21:06 geoff Exp $"; #endif /* * C library functions for generating pseudorandom numbers using the * Mersenne Twist algorithm. See M. Matsumoto and T. Nishimura, * "Mersenne Twister: A 623-Dimensionally Equidistributed Uniform * Pseudo-Random Number Generator", ACM Transactions on Modeling and * Computer Simulation, Vol. 8, No. 1, January 1998, pp 3--30. * * The Web page on the Mersenne Twist algorithm is at: * * http://www.math.keio.ac.jp/~matumoto/emt.html * * These functions were written by Geoffrey H. Kuenning, Claremont, CA. * * IMPORTANT NOTE: the Makefile must define two machine-specific * variables to get optimum features and performance: * * MT_NO_INLINE should be defined if the compiler doesn't support * the "inline" keyword. * MT_NO_LONGLONG should be defined if the compiler doesn't support a * "long long" type for 64-bit integers * MT_MACHINE_BITS must be either 32 or 64, reflecting the natural * size of the processor registers. If undefined, it * will default to 32. * * The first two variables above are defined in an inverted sense * because I expect that most compilers will support inline and * long-long. By inverting the sense, this common case will require * no special compiler flags. * * IMPORTANT NOTE: this software assumes that the inherent width of a * "long" is 32 bits. If you are running on a machine that uses * 64-bit longs, some of the declarations and code will have to be * modified. * * This software is based on LGPL-ed code by Takuji Nishimura. It has * also been heavily influenced by code written by Shawn Cokus, and * somewhat influenced by code written by Richard J. Wagner. It is * therefore also distributed under the LGPL: * * This library is free software; you can redistribute it and/or * modify it under the terms of the GNU Library General Public License * as published by the Free Software Foundation; either version 2 of * the License, or (at your option) any later version. * * This library is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Library General Public License for more details. You should have * received a copy of the GNU Library General Public License along * with this library; if not, write to the Free Foundation, Inc., 59 * Temple Place, Suite 330, Boston, MA 02111-1307 USA * * $Log: mtwist.c,v $ * Revision 1.20 2007/10/26 07:21:06 geoff * Use the new mt_u32bit_t type. * * Revision 1.19 2003/09/11 05:55:19 geoff * Get rid of some minor compiler warnings. * * Revision 1.18 2003/09/11 05:50:53 geoff * Don't #define inline to nothing, since that breaks standard include * files. Instead, use MT_INLINE as a synonym. * * Revision 1.17 2002/10/31 22:07:10 geoff * Make WIN32 detection work with GCC as well as MS C * * Revision 1.16 2002/10/31 22:04:59 geoff * Fix a typo in the WIN32 option * * Revision 1.15 2002/10/31 06:01:43 geoff * Incorporate Joseph Brill's Windows-portability changes * * Revision 1.14 2002/10/30 07:39:53 geoff * Reintroduce the old seeding functions (so that old code will still * produce the same results), and give the new versions new names. * * Revision 1.13 2002/10/30 01:08:26 geoff * Switch to M&T's new initialization method * * Revision 1.12 2001/06/18 05:40:12 geoff * Prefix the compile options with MT_. * * Revision 1.11 2001/06/14 10:26:59 geoff * Invert the sense of the #define flags so that the default is the * normal case (if gcc is normal!). Also default MT_MACHINE_BITS to 32. * * Revision 1.10 2001/06/14 10:10:38 geoff * Move the RNG functions into the header file so they can be inlined. * Add saving/loading of state. Add a function that marks the PRNG as * initialized while also calculating critical constants. Run the * refresh routine whenever seed32 is called. Add functions to seed * based on /dev/random or the time. * * Revision 1.9 2001/06/11 10:00:04 geoff * Major changes to improve flexibility and performance, and to prepare * for inlining. This code is about as fast as it can get without * inlining the various PRNG functions. Add seed/goodseed/bestseed for * seeding from random start values. Add the refresh routine a la Cokus, * but optimize it by unrolling loops. Change getstate to return a * complete state pointer, since knowing the position in the state vector * is critical to restoring state. Add more macros to improve * readability. Rename certain macros in preparation for inlining. Get * rid of leftover optimizer-bug stuff. Stop using mtwist_guts.h; * instead use direct code (via macros) and the refresh function. * * Revision 1.8 2001/04/23 08:36:03 geoff * Move the #defined code into a header file to ease stepping with a debugger. * * Revision 1.7 2001/04/23 08:00:13 geoff * Add code to work around optimizer bug * * Revision 1.6 2001/04/14 01:33:32 geoff * Clarify the license * * Revision 1.5 2001/04/09 08:45:00 geoff * Rename default_state to mt_default_state, and make it global so that * the random-distribution code can use it. * * Revision 1.4 2001/04/07 23:24:11 geoff * My guess in the commentary for the last delta was right: it's faster * on a x86 to convert the two halves of the PRN to double, multiplying * them by the appropriate value to scale them, and then add them as * doubles. I suspect the reason is that there is no instruction to * convert a 64-bit value directly to a double, so the work of building * the long long (which isn't easy anyway, without assembly access) is * worse than wasted. So add support for MT_MACHINE_BITS, and only go * the via-long-long route on a true 64-bit machine. * * Revision 1.3 2001/04/07 23:09:38 geoff * Get rid of MT_INLINE. Convert all of the code to use preprocessor * macros for the guts of the PRNG code. Take advantage of the * conversion to get rid of unnecessary calls initialization tests. Also * clean up the generation of long-double pseudorandom numbers on * machines that have the long long type (by converting first to a long * long, then to a double, saving one floating-point operation). The * latter change might be a mistake on 32-bit machines. The code is now * much faster as a result of macro-izing. * * Revision 1.2 2001/04/07 22:21:41 geoff * Make the long-double code a hair faster by always having a 64-bit * conversion constant. Add commentary to the PRNG loop. * * Revision 1.1 2001/04/07 09:43:41 geoff * Initial revision * */ #ifdef _WIN32 #undef WIN32 #define WIN32 #endif /* _WIN32 */ #include #include #ifdef WIN32 #include #else /* WIN32 */ #include #endif /* WIN32 */ /* * Before we include the Mersenne Twist header file, we must do a bit * of magic setup. The code for actual random-number generation * resides in that file rather than here. We need to arrange for the * code to be compiled into this .o file, either because inlines * aren't supported or because somebody might want to take a pointer * to a function. We do so with a couple of careful #defines. */ #undef MT_NO_INLINE /* Ask for code to be compiled */ #define MT_INLINE /* Disable the inline keyword */ #define MT_EXTERN /* Generate real code for functions */ #include "mtwist.h" /* * Table of contents: */ void mts_mark_initialized(mt_state* state); /* Mark a PRNG state as initialized */ void mts_seed32(mt_state* state, unsigned long seed); /* Set random seed for any generator */ void mts_seed32new(mt_state* state, unsigned long seed); /* Set random seed for any generator */ void mts_seedfull(mt_state* state, mt_u32bit_t seeds[MT_STATE_SIZE]); /* Set complicated seed for any gen. */ void mts_seed(mt_state* state); /* Choose seed from random input */ void mts_goodseed(mt_state* state); /* Choose seed from more random */ /* ..input than mts_seed */ static void mts_devseed(mt_state* state, char* seed_dev); /* Choose seed from a device */ void mts_bestseed(mt_state* state); /* Choose seed from extremely random */ /* ..input (can be *very* slow) */ void mts_refresh(mt_state* state); /* Generate 624 more random values */ int mts_savestate(FILE* statefile, mt_state* state); /* Save state to a file (ASCII) */ int mts_loadstate(FILE* statefile, mt_state* state); /* Load state from a file (ASCII) */ void mt_seed32(unsigned long seed); /* Set random seed for default gen. */ void mt_seed32new(unsigned long seed); /* Set random seed for default gen. */ void mt_seedfull(mt_u32bit_t seeds[MT_STATE_SIZE]); /* Set complicated seed for default */ void mt_seed(void); /* Choose seed from random input */ void mt_goodseed(void); /* Choose seed from more random */ /* ..input than mts_seed */ void mt_bestseed(void); /* Choose seed from extremely random */ /* ..input (can be *very* slow) */ extern mt_state* mt_getstate(void); /* Get current state of default */ /* ..generator */ int mt_savestate(FILE* statefile); /* Save state to a file (ASCII) */ int mt_loadstate(FILE* statefile); /* Load state from a file (ASCII) */ /* * The following values are fundamental parameters of the algorithm. * With the exception of the two masks, all of them were found * experimentally using methods described in Matsumoto and Nishimura's * paper. They are exceedingly magic; don't change them. */ /* MT_STATE_SIZE is defined in the header file. */ #define RECURRENCE_OFFSET 397 /* Offset into state space for the */ /* ..recurrence relation. The */ /* ..recurrence mashes together two */ /* ..values that are separated by */ /* ..this offset in the state */ /* ..space. */ #define MATRIX_A 0x9908b0df /* Constant vector A for the */ /* ..recurrence relation. The */ /* ..mashed-together value is */ /* ..multiplied by this vector to */ /* ..get a new value that will be */ /* ..stored into the state space. */ /* * Width of a long. Don't change this even if your longs are 64 bits. */ #define BIT_WIDTH 32 /* Work with 32-bit words */ /* * Masks for extracting the bits to be mashed together. The widths of these * masks are also fundamental parameters of the algorithm, determined * experimentally -- but of course the masks themselves are simply bit * selectors. */ #define UPPER_MASK 0x80000000 /* Most significant w-r bits */ #define LOWER_MASK 0x7fffffff /* Least significant r bits */ /* * Macro to simplify code in the generation loop. This function * combines the top bit of x with the bottom 31 bits of y. */ #define COMBINE_BITS(x, y) \ (((x) & UPPER_MASK) | ((y) & LOWER_MASK)) /* * Another generation-simplification macro. This one does the magic * scrambling function. */ #define MATRIX_MULTIPLY(original, new) \ ((original) ^ ((new) >> 1) \ ^ matrix_decider[(new) & 0x1]) /* * Parameters of Knuth's PRNG (Line 25, Table 1, p. 102 of "The Art of * Computer Programming, Vol. 2, 2nd ed, 1981). */ #define KNUTH_MULTIPLIER_OLD \ 69069 /* * Parameters of Knuth's PRNG (p. 106 of "The Art of Computer * Programming, Vol. 2, 3rd ed). */ #define KNUTH_MULTIPLIER_NEW \ 1812433253ul #define KNUTH_SHIFT 30 // Even on a 64-bit machine! /* * Default 32-bit random seed if mts_seed32 wasn't called */ #define DEFAULT_SEED32_OLD \ 4357 #define DEFAULT_SEED32_NEW \ 5489ul /* * Where to get random numbers */ #define DEVRANDOM "/dev/random" #define DEVURANDOM "/dev/urandom" /* * Many applications need only a single PRNG, so it's a nuisance to have to * specify a state. For those applications, we will provide a default * state, and functions to use it. */ mt_state mt_default_state; /* * To generate double-precision random numbers, we need to divide the result * of mts_lrand or mts_llrand by 2^32 or 2^64, respectively. The quickest * way to do that on most machines is to multiply by the inverses of those * numbers. However, I don't trust the compiler to correctly convert the * corresponding decimal constant. So we will compute the correct number at * run time as part of initialization, which will produce a nice exact * result. */ double mt_32_to_double; /* Multiplier to convert long to dbl */ double mt_64_to_double; /* Mult'r to cvt long long to dbl */ /* * In the recurrence relation, the new value is XORed with MATRIX_A only if * the lower bit is nonzero. Since most modern machines don't like to * branch, it's vastly faster to handle this decision by indexing into an * array. The chosen bit is used as an index into the following vector, * which produces either zero or MATRIX_A and thus the desired effect. */ static mt_u32bit_t matrix_decider[2] = {0x0, MATRIX_A}; /* * Mark a PRNG's state as having been initialized. This is the only * way to set that field nonzero; that way we can be sure that the * constants are set properly before the PRNG is used. * * As a side effect, set up some constants that the PRNG assumes are * valid. These are calculated at initialization time rather than * being written as decimal constants because I frankly don't trust * the compiler's ASCII conversion routines. */ void mts_mark_initialized( mt_state* state) /* State vector to mark initialized */ { int i; /* Power of 2 being calculated */ /* * Figure out the proper multiplier for long-to-double conversion. We * don't worry too much about efficiency, since the assumption is that * initialization is vastly rarer than generation of random numbers. */ mt_32_to_double = 1.0; for (i = 0; i < BIT_WIDTH; i++) mt_32_to_double /= 2.0; mt_64_to_double = mt_32_to_double; for (i = 0; i < BIT_WIDTH; i++) mt_64_to_double /= 2.0; state->initialized = 1; } /* * Initialize a Mersenne Twist PRNG from a 32-bit seed. * * According to Matsumoto and Nishimura's paper, the seed array needs to be * filled with nonzero values. (My own interpretation is that there needs * to be at least one nonzero value). They suggest using Knuth's PRNG from * Line 25, Table 1, p.102, "The Art of Computer Programming," Vol. 2 (2nd * ed.), 1981. I find that rather odd, since that particular PRNG is * sensitive to having an initial seed of zero (there are many other PRNGs * out there that have an additive component, so that a seed of zero does * not generate a repeating-zero sequence). However, one thing I learned * from reading Knuth is that you shouldn't second-guess mathematicians * about PRNGs. Also, by following M & N's approach, we will be compatible * with other implementations. So I'm going to stick with their version, * with the single addition that a zero seed will be changed to their * default seed. */ void mts_seed32( mt_state* state, /* State vector to initialize */ unsigned long seed) /* 32-bit seed to start from */ { int i; /* Loop index */ if (seed == 0) seed = DEFAULT_SEED32_OLD; /* * Fill the state vector using Knuth's PRNG. Be sure to mask down * to 32 bits in case we're running on a machine with 64-bit * longs. */ state->statevec[MT_STATE_SIZE - 1] = seed & 0xffffffff; for (i = MT_STATE_SIZE - 2; i >= 0; i--) state->statevec[i] = (KNUTH_MULTIPLIER_OLD * state->statevec[i + 1]) & 0xffffffff; state->stateptr = MT_STATE_SIZE; mts_mark_initialized(state); /* * Matsumoto and Nishimura's implementation refreshes the PRNG * immediately after running the Knuth algorithm. This is * probably a good thing, since Knuth's PRNG doesn't generate very * good numbers. */ mts_refresh(state); } /* * Initialize a Mersenne Twist PRNG from a 32-bit seed, using * Matsumoto and Nishimura's newer reference implementation (Jan. 9, * 2002). */ void mts_seed32new( mt_state* state, /* State vector to initialize */ unsigned long seed) /* 32-bit seed to start from */ { int i; /* Loop index */ mt_u32bit_t nextval; /* Next value being calculated */ /* * Fill the state vector using Knuth's PRNG. Be sure to mask down * to 32 bits in case we're running on a machine with 64-bit * longs. */ state->statevec[MT_STATE_SIZE - 1] = seed & 0xffffffffUL; for (i = MT_STATE_SIZE - 2; i >= 0; i--) { nextval = state->statevec[i + 1] >> KNUTH_SHIFT; nextval ^= state->statevec[i + 1]; nextval *= KNUTH_MULTIPLIER_NEW; nextval += (MT_STATE_SIZE - 1) - i; state->statevec[i] = nextval & 0xffffffffUL; } state->stateptr = MT_STATE_SIZE; mts_mark_initialized(state); /* * Matsumoto and Nishimura's implementation refreshes the PRNG * immediately after running the Knuth algorithm. This is * probably a good thing, since Knuth's PRNG doesn't generate very * good numbers. */ mts_refresh(state); } /* * Initialize a Mersenne Twist RNG from a 624-long seed. * * The 32-bit seeding routine given by Matsumoto and Nishimura has the * drawback that there are only 2^32 different PRNG sequences that can be * generated by calling that function. This function solves that problem by * allowing a full 624*32-bit state to be given. (Note that 31 bits of the * given state are ignored; see the paper for details.) * * Since an all-zero state would cause the PRNG to cycle, we detect * that case and abort the program (silently, since there is no * portable way to produce a message in both C and C++ environments). * An alternative would be to artificially force the state to some * known nonzero value. However, I feel that if the user is providing * a full state, it's a bug to provide all zeros and we we shouldn't * conceal the bug by generating apparently correct output. */ void mts_seedfull( mt_state* state, /* State vector to initialize */ mt_u32bit_t seeds[MT_STATE_SIZE]) /* Seed array to start from */ { int had_nz = 0; /* NZ if at least one NZ seen */ int i; /* Loop index */ for (i = 0; i < MT_STATE_SIZE; i++) { if (seeds[i] != 0) had_nz = 1; state->statevec[MT_STATE_SIZE - i - 1] = seeds[i]; } if (!had_nz) { /* * It would be nice to abort with a message. Unfortunately, fprintf * isn't compatible with all implementations of C++. In the * interest of C++ compatibility, therefore, we will simply abort * silently. It will unfortunately be up to a programmer to run * under a debugger (or examine the core dump) to discover the cause * of the abort. */ abort(); } state->stateptr = MT_STATE_SIZE; mts_mark_initialized(state); } /* * Choose a seed based on some moderately random input. Prefers * /dev/urandom as a source of random numbers, but uses the lower bits * of the current time if /dev/urandom is not available. In any case, * only provides 32 bits of entropy. */ void mts_seed( mt_state* state) /* State vector to seed */ { mts_devseed(state, DEVURANDOM); } /* * Choose a seed based on some fairly random input. Prefers * /dev/random as a source of random numbers, but uses the lower bits * of the current time if /dev/random is not available. In any case, * only provides 32 bits of entropy. */ void mts_goodseed( mt_state* state) /* State vector to seed */ { mts_devseed(state, DEVRANDOM); } /* * Choose a seed based on a random-number device given by the caller. * If that device can't be opened, use the lower 32 bits from the * current time. */ static void mts_devseed( mt_state* state, /* State vector to seed */ char* seed_dev) /* Device to seed from */ { int bytesread; /* Byte count read from device */ int nextbyte; /* Index of next byte to read */ FILE* ranfile; /* Access to device */ union { char ranbuffer[sizeof (unsigned long)]; /* Space for reading random int */ unsigned long randomvalue; /* Random value for initialization */ } randomunion; /* Union for reading random int */ #ifdef WIN32 struct _timeb tb; /* Time of day (Windows mode) */ #else /* WIN32 */ struct timeval tv; /* Time of day */ struct timezone tz; /* Dummy for gettimeofday */ #endif /* WIN32 */ ranfile = fopen(seed_dev, "rb"); if (ranfile != NULL) { for (nextbyte = 0; nextbyte < (int)sizeof randomunion.ranbuffer; nextbyte += bytesread) { bytesread = fread(&randomunion.ranbuffer[nextbyte], 1, sizeof randomunion.ranbuffer - nextbyte, ranfile); if (bytesread == 0) break; } fclose(ranfile); if (nextbyte == sizeof randomunion.ranbuffer) { mts_seed32new(state, randomunion.randomvalue); return; } } /* * The device isn't available. Use the time. We will * assume that the time of day is accurate to microsecond * resolution, which is true on most modern machines. */ #ifdef WIN32 (void) _ftime (&tb); #else /* WIN32 */ (void) gettimeofday (&tv, &tz); #endif /* WIN32 */ /* * We just let the excess part of the seconds field overflow */ #ifdef WIN32 randomunion.randomvalue = tb.time * 1000 + tb.millitm; #else /* WIN32 */ randomunion.randomvalue = tv.tv_sec * 1000000 + tv.tv_usec; #endif /* WIN32 */ mts_seed32new(state, randomunion.randomvalue); } /* * Choose a seed based on the best random input available. Prefers * /dev/random as a source of random numbers, and reads the entire * 624-long state from that device. Because of this approach, the * function can take a long time (in real time) to complete, since * /dev/random may have to wait quite a while before it can provide * that much randomness. If /dev/random is unavailable, falls back to * calling mts_goodseed. */ void mts_bestseed( mt_state* state) /* State vector to seed */ { int bytesread; /* Byte count read from device */ int nextbyte; /* Index of next byte to read */ FILE* ranfile; /* Access to device */ ranfile = fopen("/dev/random", "rb"); if (ranfile == NULL) { mts_goodseed(state); return; } for (nextbyte = 0; nextbyte < (int)sizeof state->statevec; nextbyte += bytesread) { bytesread = fread((char *)&state->statevec + nextbyte, 1, sizeof state->statevec - nextbyte, ranfile); if (bytesread == 0) { /* * Something went wrong. Fall back to time-based seeding. */ fclose(ranfile); mts_goodseed(state); return; } } } /* * Generate 624 more random values. This function is called when the * state vector has been exhausted. It generates another batch of * pseudo-random values. The performance of this function is critical * to the performance of the Mersenne Twist PRNG, so it has been * highly optimized. */ void mts_refresh( register mt_state* state) /* State for the PRNG */ { register int i; /* Index into the state */ register mt_u32bit_t* state_ptr; /* Next place to get from state */ register mt_u32bit_t value1; /* Scratch val picked up from state */ register mt_u32bit_t value2; /* Scratch val picked up from state */ /* * Start by making sure a random seed has been set. If not, set * one. */ if (!state->initialized) { mts_seed32(state, DEFAULT_SEED32_OLD); return; /* Seed32 calls us recursively */ } /* * Now generate the new pseudorandom values by applying the * recurrence relation. We use two loops and a final * 2-statement sequence so that we can handle the wraparound * explicitly, rather than having to use the relatively slow * modulus operator. * * In essence, the recurrence relation concatenates bits * chosen from the current random value (last time around) * with the immediately preceding one. Then it * matrix-multiplies the concatenated bits with a value * RECURRENCE_OFFSET away and a constant matrix. The matrix * multiplication reduces to a shift and two XORs. * * Some comments on the optimizations are in order: * * Strictly speaking, none of the optimizations should be * necessary. All could conceivably be done by a really good * compiler. However, the compilers available to me aren't quite * smart enough, so hand optimization needs to be done. * * Shawn Cokus was the first to achieve a major speedup. In the * original code, the first value given to COMBINE_BITS (in my * characterization) was re-fetched from the state array, rather * than being carried in a scratch variable. Cokus noticed that * the first argument to COMBINE_BITS could be saved in a register * in the previous loop iteration, getting rid of the need for an * expensive memory reference. * * Cokus also switched to using pointers to access the state * array and broke the original loop into two so that he could * avoid using the expensive modulus operator. Cokus used three * pointers; Richard J. Wagner noticed that the offsets between * the three were constant, so that they could be collapsed into a * single pointer and constant-offset accesses. This is clearly * faster on x86 architectures, and is the same cost on RISC * machines. A secondary benefit is that Cokus' version was * register-starved on the x86, while Wagner's version was not. * * I made several smaller improvements to these observations. * First, I reversed the contents of the state vector. In the * current version of the code, this change doesn't directly * affect the performance of the refresh loop, but it has the nice * side benefit that an all-zero state structure represents an * uninitialized generator. It also slightly speeds up the * random-number routines, since they can compare the state * pointer against zero instead of against a constant (this makes * the biggest difference on RISC machines). * * Second, I returned to Matsumoto and Nishimura's original * technique of using a lookup table to decide whether to xor the * constant vector A (MATRIX_A in this code) with the newly * computed value. Cokus and Wagner had used the ?: operator, * which requires a test and branch. Modern machines don't like * branches, so the table lookup is faster. * * Third, in the Cokus and Wagner versions the loop ends with a * statement similar to "value1 = value2", which is necessary to * carry the fetched value into the next loop iteration. I * recognized that if the loop were unrolled so that it generates * two values per iteration, a bit of variable renaming would get * rid of that assignment. A nice side effect is that the * overhead of loop control becomes only half as large. * * It is possible to improve the code's performance somewhat * further. In particular, since the second loop's loop count * factors into 2*2*3*3*11, it could be unrolled yet further. * That's easy to do, too: just change the "/ 2" into a division * by whatever factor you choose, and then use cut-and-paste to * duplicate the code in the body. To remove a few more cycles, * fix the code to decrement state_ptr by the unrolling factor, and * adjust the various offsets appropriately. However, the payoff * will be small. At the moment, the x86 version of the loop is * 25 instructions, of which 3 are involved in loop control * (including the decrementing of state_ptr). Further unrolling by * a factor of 2 would thus produce only about a 6% speedup. * * The logical extension of the unrolling * approach would be to remove the loops and create 624 * appropriate copies of the body. However, I think that doing * the latter is a bit excessive! * * I suspect that a superior optimization would be to simplify the * mathematical operations involved in the recurrence relation. * However, I have no idea whether such a simplification is * feasible. */ state_ptr = &state->statevec[MT_STATE_SIZE - 1]; value1 = *state_ptr; for (i = (MT_STATE_SIZE - RECURRENCE_OFFSET) / 2; --i >= 0; ) { state_ptr -= 2; value2 = state_ptr[1]; value1 = COMBINE_BITS(value1, value2); state_ptr[2] = MATRIX_MULTIPLY(state_ptr[-RECURRENCE_OFFSET + 2], value1); value1 = state_ptr[0]; value2 = COMBINE_BITS(value2, value1); state_ptr[1] = MATRIX_MULTIPLY(state_ptr[-RECURRENCE_OFFSET + 1], value2); } value2 = *--state_ptr; value1 = COMBINE_BITS(value1, value2); state_ptr[1] = MATRIX_MULTIPLY(state_ptr[-RECURRENCE_OFFSET + 1], value1); for (i = (RECURRENCE_OFFSET - 1) / 2; --i >= 0; ) { state_ptr -= 2; value1 = state_ptr[1]; value2 = COMBINE_BITS(value2, value1); state_ptr[2] = MATRIX_MULTIPLY(state_ptr[MT_STATE_SIZE - RECURRENCE_OFFSET + 2], value2); value2 = state_ptr[0]; value1 = COMBINE_BITS(value1, value2); state_ptr[1] = MATRIX_MULTIPLY(state_ptr[MT_STATE_SIZE - RECURRENCE_OFFSET + 1], value1); } /* * The final entry in the table requires the "previous" value * to be gotten from the other end of the state vector, so it * must be handled specially. */ value1 = COMBINE_BITS(value2, state->statevec[MT_STATE_SIZE - 1]); *state_ptr = MATRIX_MULTIPLY(state_ptr[MT_STATE_SIZE - RECURRENCE_OFFSET], value1); /* * Now that refresh is complete, reset the state pointer to allow more * pseudorandom values to be fetched from the state array. */ state->stateptr = MT_STATE_SIZE; } /* * Save state to a file. The save format is compatible with Richard * J. Wagner's format, although the details are different. Returns NZ * if the save succeeded. Produces one very long line containing 625 * numbers. */ int mts_savestate( FILE* statefile, /* File to save to */ mt_state* state) /* State to be saved */ { int i; /* Next word to save */ if (!state->initialized) mts_seed32(state, DEFAULT_SEED32_OLD); for (i = MT_STATE_SIZE; --i >= 0; ) { if (fprintf(statefile, "%lu ", state->statevec[i]) < 0) return 0; } if (fprintf(statefile, "%d\n", state->stateptr) < 0) return 0; return 1; } /* * Load state from a file. Returns NZ if the load succeeded. */ int mts_loadstate( FILE* statefile, /* File to load from */ mt_state* state) /* State to be loaded */ { int i; /* Next word to load */ /* * Set the state to "uninitialized" in case the load fails. */ state->initialized = state->stateptr = 0; for (i = MT_STATE_SIZE; --i >= 0; ) { if (fscanf(statefile, "%lu", &state->statevec[i]) != 1) return 0; } if (fscanf(statefile, "%d", &state->stateptr) != 1) return 0; /* * The only validity checking we can do is to insist that the * state pointer be valid. */ if (state->stateptr < 0 || state->stateptr > MT_STATE_SIZE) { state->stateptr = 0; return 0; } mts_mark_initialized(state); return 1; } /* * Initialize the default Mersenne Twist PRNG from a 32-bit seed. * * See mts_seed32 for full commentary. */ void mt_seed32( unsigned long seed) /* 32-bit seed to start from */ { mts_seed32(&mt_default_state, seed); } /* * Initialize the default Mersenne Twist PRNG from a 32-bit seed. * * See mts_seed32new for full commentary. */ void mt_seed32new( unsigned long seed) /* 32-bit seed to start from */ { mts_seed32new(&mt_default_state, seed); } /* * Initialize a Mersenne Twist RNG from a 624-long seed. * * See mts_seedfull for full commentary. */ void mt_seedfull( mt_u32bit_t seeds[MT_STATE_SIZE]) { mts_seedfull(&mt_default_state, seeds); } /* * Initialize the PRNG from random input. See mts_seed. */ void mt_seed() { mts_seed(&mt_default_state); } /* * Initialize the PRNG from random input. See mts_goodseed. */ void mt_goodseed() { mts_goodseed(&mt_default_state); } /* * Initialize the PRNG from random input. See mts_bestseed. */ void mt_bestseed() { mts_bestseed(&mt_default_state); } /* * Return a pointer to the current state of the PRNG. The purpose of * this function is to allow the state to be saved for later * restoration. The state should not be modified; instead, it should * be reused later as a parameter to one of the mts_xxx functions. */ extern mt_state* mt_getstate() { return &mt_default_state; } /* * Save state to a file. The save format is compatible with Richard * J. Wagner's format, although the details are different. */ int mt_savestate( FILE* statefile) /* File to save to */ { return mts_savestate(statefile, &mt_default_state); } /* * Load state from a file. */ int mt_loadstate( FILE* statefile) /* File to load from */ { return mts_loadstate(statefile, &mt_default_state); } april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Kuenning/mtwist.h000066400000000000000000000655271263004425400272550ustar00rootroot00000000000000#ifndef MTWIST_H #define MTWIST_H /* * $Id: mtwist.h,v 1.17 2007/10/26 07:21:06 geoff Exp $ * * Header file for C/C++ use of the Mersenne-Twist pseudo-RNG. See * http://www.math.keio.ac.jp/~matumoto/emt.html for full information. * * Author of this header file: Geoffrey H. Kuenning, March 18, 2001. * http://www.cs.hmc.edu/~geoff/mtwist.html * IMPORTANT NOTE: the Makefile must define two machine-specific * variables to get optimum features and performance: * * MT_NO_INLINE should be defined if the compiler doesn't support * the "inline" keyword. * MT_NO_LONGLONG should be defined if the compiler doesn't support a * "long long" type for 64-bit integers * MT_MACHINE_BITS must be either 32 or 64, reflecting the natural * size of the processor registers. If undefined, it * will default to a value calculated from limits.h. * * The first two variables above are defined in an inverted sense * because I expect that most compilers will support inline and * long-long. By inverting the sense, this common case will require * no special compiler flags. * * IMPORTANT NOTE: this software requires access to a 32-bit type. Be * sure that "mt_u32bit_t" is set to an unsigned 32-bit integer type. * The Mersenne Twist algorithms are not guaranteed to produce correct * results with a 64-bit type. * * The executable part of this software is based on LGPL-ed code by * Takuji Nishimura. The header file is therefore also distributed * under the LGPL: * * This library is free software; you can redistribute it and/or * modify it under the terms of the GNU Library General Public License * as published by the Free Software Foundation; either version 2 of * the License, or (at your option) any later version. * * This library is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Library General Public License for more details. You should have * received a copy of the GNU Library General Public License along * with this library; if not, write to the Free Foundation, Inc., 59 * Temple Place, Suite 330, Boston, MA 02111-1307 USA * * $Log: mtwist.h,v $ * Revision 1.17 2007/10/26 07:21:06 geoff * Introduce, document, and use the new mt_u32bit_t type so that the code * will compile and run on 64-bit platforms (although it does not * currently use the 64-bit Mersenne Twist algorithm). * * Revision 1.16 2005/11/11 08:21:39 geoff * If possible, try to infer MT_MACHINE_BITS from limits.h. * * Revision 1.15 2003/09/11 23:56:20 geoff * Allow stdio references in C++ files; it turns out that ANSI has * blessed it. Declare the various functions as external even if they're * inlined or being compiled directly (in mtwist.c). Get rid of a #ifdef * that can't ever be true. * * Revision 1.14 2003/09/11 05:50:53 geoff * Don't allow stdio references from C++, since they're not guaranteed to * work on all compilers. Disable inlining using the MT_INLINE keyword * rather than #defining inline, since doing the latter can affect other * files and functions than our own. * * Revision 1.13 2003/07/01 23:29:29 geoff * Refer to streams from the standard library using the correct namespace. * * Revision 1.12 2002/10/30 07:39:54 geoff * Declare the new seeding functions. * * Revision 1.11 2001/06/19 00:41:16 geoff * For consistency with other C++ types, don't put out a newline after * the saved data. * * Revision 1.10 2001/06/18 10:09:24 geoff * Fix some places where I forgot to set one of the result values. Make * the C++ state vector protected so the random-distributions package can * pass it to the C functions. * * Revision 1.9 2001/06/18 05:40:12 geoff * Prefix the compile options with MT_. * * Revision 1.8 2001/06/14 10:26:59 geoff * Invert the sense of the #define flags so that the default is the * normal case (if gcc is normal!). Also default MT_MACHINE_BITS to 32. * * Revision 1.7 2001/06/14 10:10:38 geoff * Move the critical-path PRNG code into the header file so that it can * be inlined. Add saving/loading of state. Add functions to seed based * on /dev/random or the time. Add the function-call operator in the C++ * code. * * Revision 1.6 2001/06/11 10:00:04 geoff * Add declarations of the refresh and /dev/random seeding functions. * Change getstate to return a complete state pointer, since knowing the * position in the state vector is critical to restoring the state. * * Revision 1.5 2001/04/23 08:36:03 geoff * Remember to zero the state pointer when constructing, since otherwise * proper initialization won't happen. * * Revision 1.4 2001/04/14 01:33:32 geoff * Clarify the license * * Revision 1.3 2001/04/14 01:04:54 geoff * Add a C++ class, mt_prng, that makes usage more convenient for C++ * programmers. * * Revision 1.2 2001/04/09 08:45:00 geoff * Fix the name in the #ifndef wrapper, and clean up some outdated comments. * * Revision 1.1 2001/04/07 09:43:41 geoff * Initial revision * */ #include #ifdef __cplusplus #include #endif /* __cplusplus */ #ifndef MT_MACHINE_BITS #include #if INT_MAX == 2147483647 #define MT_MACHINE_BITS 32 #else /* INT_MAX */ #define MT_MACHINE_BITS 64 #endif /* INT_MAX */ #endif /* MT_MACHINE_BITS */ /* * Define an unsigned type that is guaranteed to be 32 bits wide. */ #if MT_MACHINE_BITS == 32 typedef unsigned long mt_u32bit_t; #else /* MT_MACHINE_BITS */ typedef unsigned int mt_u32bit_t; #endif /* MT_MACHINE_BITS */ /* * The following value is a fundamental parameter of the algorithm. * It was found experimentally using methods described in Matsumoto * and Nishimura's paper. It is exceedingly magic; don't change it. */ #define MT_STATE_SIZE 624 /* Size of the MT state vector */ /* * Internal state for an MT RNG. The user can keep multiple mt_state * structures around as a way of generating multiple streams of random * numbers. * * In Matsumoto and Nishimura's original paper, the state vector was * processed in a forward direction. I have reversed the state vector * in this implementation. The reason for the reversal is that it * allows the critical path to use a test against zero instead of a * test against 624 to detect the need to refresh the state. on most * machines, testing against zero is slightly faster. It also means * that a state that has been set to all zeros will be correctly * detected as needing initialization; this means that setting a state * vector to zero (either with memset or by statically allocating it) * will cause the RNG to operate properly. */ typedef struct { mt_u32bit_t statevec[MT_STATE_SIZE]; /* Vector holding current state */ int stateptr; /* Next state entry to be used */ int initialized; /* NZ if state was initialized */ } mt_state; #ifdef __cplusplus extern "C" { #endif /* * Functions for manipulating any generator (given a state pointer). */ extern void mts_mark_initialized(mt_state* state); /* Mark a PRNG state as initialized */ extern void mts_seed32(mt_state* state, unsigned long seed); /* Set random seed for any generator */ extern void mts_seed32new(mt_state* state, unsigned long seed); /* Set random seed for any generator */ extern void mts_seedfull(mt_state* state, mt_u32bit_t seeds[MT_STATE_SIZE]); /* Set complicated seed for any gen. */ extern void mts_seed(mt_state* state); /* Choose seed from random input. */ /* ..Prefers /dev/urandom; uses time */ /* ..if /dev/urandom unavailable. */ /* ..Only gives 32 bits of entropy. */ extern void mts_goodseed(mt_state* state); /* Choose seed from more random */ /* ..input than mts_seed. Prefers */ /* ../dev/random; uses time if that */ /* ..is unavailable. Only gives 32 */ /* ..bits of entropy. */ extern void mts_bestseed(mt_state* state); /* Choose seed from extremely random */ /* ..input (can be *very* slow). */ /* ..Prefers /dev/random and reads */ /* ..the entire state from there. */ /* ..If /dev/random is unavailable, */ /* ..falls back to mt_goodseed(). */ /* ..Not usually worth the cost. */ extern void mts_refresh(mt_state* state); /* Generate 624 more random values */ extern int mts_savestate(FILE* statefile, mt_state* state); /* Save state to a file (ASCII). */ /* ..Returns NZ if succeeded. */ extern int mts_loadstate(FILE* statefile, mt_state* state); /* Load state from a file (ASCII). */ /* ..Returns NZ if succeeded. */ /* * Functions for manipulating the default generator. */ extern void mt_seed32(unsigned long seed); /* Set random seed for default gen. */ extern void mt_seed32new(unsigned long seed); /* Set random seed for default gen. */ extern void mt_seedfull(mt_u32bit_t seeds[MT_STATE_SIZE]); /* Set complicated seed for default */ extern void mt_seed(void); /* Choose seed from random input. */ /* ..Prefers /dev/urandom; uses time */ /* ..if /dev/urandom unavailable. */ /* ..Only gives 32 bits of entropy. */ extern void mt_goodseed(void); /* Choose seed from more random */ /* ..input than mts_seed. Prefers */ /* ../dev/random; uses time if that */ /* ..is unavailable. Only gives 32 */ /* ..bits of entropy. */ extern void mt_bestseed(void); /* Choose seed from extremely random */ /* ..input (can be *very* slow). */ /* ..Prefers /dev/random and reads */ /* ..the entire state from there. */ /* ..If /dev/random is unavailable, */ /* ..falls back to mt_goodseed(). */ /* ..Not usually worth the cost. */ extern mt_state* mt_getstate(void); /* Get current state of default */ /* ..generator */ extern int mt_savestate(FILE* statefile); /* Save state to a file (ASCII) */ /* ..Returns NZ if succeeded. */ extern int mt_loadstate(FILE* statefile); /* Load state from a file (ASCII) */ /* ..Returns NZ if succeeded. */ #ifdef __cplusplus } #endif /* * Functions for generating random numbers. The actual code of the * functions is given in this file so that it can be declared inline. * For compilers that don't have the inline feature, mtwist.c will * incorporate this file with some clever #defining so that the code * actually gets compiled. In that case, however, "extern" * definitions will be needed here, so we give them. */ #ifdef __cplusplus #undef MT_NO_INLINE /* C++ definitely has inlining */ #endif /* __cplusplus */ extern unsigned long mts_lrand(mt_state* state); /* Generate 32-bit value, any gen. */ #ifndef MT_NO_LONGLONG extern unsigned long long mts_llrand(mt_state* state); /* Generate 64-bit value, any gen. */ #endif /* MT_NO_LONGLONG */ extern double mts_drand(mt_state* state); /* Generate floating value, any gen. */ /* Fast, with only 32-bit precision */ extern double mts_ldrand(mt_state* state); /* Generate floating value, any gen. */ /* Slower, with 64-bit precision */ extern unsigned long mt_lrand(void); /* Generate 32-bit random value */ #ifndef MT_NO_LONGLONG extern unsigned long long mt_llrand(void); /* Generate 64-bit random value */ #endif /* MT_NO_LONGLONG */ extern double mt_drand(void); /* Generate floating value */ /* Fast, with only 32-bit precision */ extern double mt_ldrand(void); /* Generate floating value */ /* Slower, with 64-bit precision */ #ifndef MT_NO_INLINE /* * Tempering parameters. These are perhaps the most magic of all the magic * values in the algorithm. The values are again experimentally determined. * The values generated by the recurrence relation (constants above) are not * equidistributed in 623-space. For some reason, the tempering process * produces that effect. Don't ask me why. Read the paper if you can * understand the math. Or just trust these magic numbers. */ #define MT_TEMPERING_MASK_B 0x9d2c5680 #define MT_TEMPERING_MASK_C 0xefc60000 #define MT_TEMPERING_SHIFT_U(y) \ (y >> 11) #define MT_TEMPERING_SHIFT_S(y) \ (y << 7) #define MT_TEMPERING_SHIFT_T(y) \ (y << 15) #define MT_TEMPERING_SHIFT_L(y) \ (y >> 18) /* * Macros to do the tempering. MT_PRE_TEMPER does all but the last step; * it's useful for situations where the final step can be incorporated * into a return statement. MT_FINAL_TEMPER does that final step (not as * an assignment). MT_TEMPER does the entire process. Note that * MT_PRE_TEMPER and MT_TEMPER both modify their arguments. */ #define MT_PRE_TEMPER(value) \ do \ { \ value ^= MT_TEMPERING_SHIFT_U(value); \ value ^= MT_TEMPERING_SHIFT_S(value) & MT_TEMPERING_MASK_B; \ value ^= MT_TEMPERING_SHIFT_T(value) & MT_TEMPERING_MASK_C; \ } \ while (0) #define MT_FINAL_TEMPER(value) \ ((value) ^ MT_TEMPERING_SHIFT_L(value)) #define MT_TEMPER(value) \ do \ { \ value ^= MT_TEMPERING_SHIFT_U(value); \ value ^= MT_TEMPERING_SHIFT_S(value) & MT_TEMPERING_MASK_B; \ value ^= MT_TEMPERING_SHIFT_T(value) & MT_TEMPERING_MASK_C; \ value ^= MT_TEMPERING_SHIFT_L(value); \ } \ while (0) extern mt_state mt_default_state; /* State of the default generator */ extern double mt_32_to_double; /* Multiplier to convert long to dbl */ extern double mt_64_to_double; /* Mult'r to cvt long long to dbl */ /* * In gcc, inline functions must be declared extern or they'll produce * assembly code (and thus linking errors). We have to work around * that difficulty with the MT_EXTERN define. */ #ifndef MT_EXTERN #ifdef __cplusplus #define MT_EXTERN /* C++ doesn't need static */ #else /* __cplusplus */ #define MT_EXTERN extern /* C (at least gcc) needs extern */ #endif /* __cplusplus */ #endif /* MT_EXTERN */ /* * Make it possible for mtwist.c to disable the inline keyword. We * use our own keyword so that we don't interfere with inlining in * C/C++ header files, above. */ #ifndef MT_INLINE #define MT_INLINE inline /* Compiler has inlining */ #endif /* MT_INLINE */ /* * Generate a random number in the range 0 to 2^32-1, inclusive, working * from a given state vector. * * The generator is optimized for speed. The primary optimization is that * the pseudorandom numbers are generated in batches of MT_STATE_SIZE. This * saves the cost of a modulus operation in the critical path. */ MT_EXTERN MT_INLINE unsigned long mts_lrand( register mt_state* state) /* State for the PRNG */ { register unsigned long random_value; /* Pseudorandom value generated */ if (state->stateptr <= 0) mts_refresh(state); random_value = state->statevec[--state->stateptr]; MT_PRE_TEMPER(random_value); return MT_FINAL_TEMPER(random_value); } #ifndef MT_NO_LONGLONG /* * Generate a random number in the range 0 to 2^64-1, inclusive, working * from a given state vector. * * According to Matsumoto and Nishimura, such a number can be generated by * simply concatenating two 32-bit pseudorandom numbers. Who am I to argue? * * Note that there is a slight inefficiency here: if the 624-entry state is * recycled on the second call to mts_lrand, there will be an unnecessary * check to see if the state has been initialized. The cost of that check * seems small (since it happens only once every 624 random numbers, and * never if only 64-bit numbers are being generated), so I didn't bother to * optimize it out. Doing so would be messy, since it would require two * nearly-identical internal implementations of mts_lrand. */ MT_EXTERN MT_INLINE unsigned long long mts_llrand( register mt_state* state) /* State for the PRNG */ { register unsigned long random_value_1; /* 1st pseudorandom value generated */ register unsigned long random_value_2; /* 2nd pseudorandom value generated */ /* * For maximum speed, we'll handle the two overflow cases * together. That will save us one test in the common case, at * the expense of an extra one in the overflow case. */ if (--state->stateptr <= 0) { if (state->stateptr < 0) { mts_refresh(state); random_value_1 = state->statevec[--state->stateptr]; } else { random_value_1 = state->statevec[state->stateptr]; mts_refresh(state); } } else random_value_1 = state->statevec[--state->stateptr]; MT_TEMPER(random_value_1); random_value_2 = state->statevec[--state->stateptr]; MT_PRE_TEMPER(random_value_2); return ((unsigned long long) random_value_1 << 32) | (unsigned long long) MT_FINAL_TEMPER(random_value_2); } #endif /* MT_NO_LONGLONG */ /* * Generate a double-precision random number between 0 (inclusive) and 1.0 * (exclusive). This function is optimized for speed, but it only generates * 32 bits of precision. Use mts_ldrand to get 64 bits of precision. */ MT_EXTERN MT_INLINE double mts_drand( register mt_state* state) /* State for the PRNG */ { register unsigned long random_value; /* Pseudorandom value generated */ if (state->stateptr <= 0) mts_refresh(state); random_value = state->statevec[--state->stateptr]; MT_TEMPER(random_value); return random_value * mt_32_to_double; } /* * Generate a double-precision random number between 0 (inclusive) and 1.0 * (exclusive). This function generates 64 bits of precision. Use * mts_drand for more speed but less precision. */ MT_EXTERN MT_INLINE double mts_ldrand( register mt_state* state) /* State for the PRNG */ { #if MT_MACHINE_BITS == 64 unsigned long long final_value; /* Final (integer) value */ #endif /* MT_MACHINE_BITS */ register unsigned long random_value_1; /* 1st pseudorandom value generated */ register unsigned long random_value_2; /* 2nd pseudorandom value generated */ /* * For maximum speed, we'll handle the two overflow cases * together. That will save us one test in the common case, at * the expense of an extra one in the overflow case. */ if (--state->stateptr <= 0) { if (state->stateptr < 0) { mts_refresh(state); random_value_1 = state->statevec[--state->stateptr]; } else { random_value_1 = state->statevec[state->stateptr]; mts_refresh(state); } } else random_value_1 = state->statevec[--state->stateptr]; MT_TEMPER(random_value_1); random_value_2 = state->statevec[--state->stateptr]; MT_TEMPER(random_value_2); #if MT_MACHINE_BITS == 64 final_value = ((unsigned long long) random_value_1 << 32) | (unsigned long long) random_value_2; return final_value * mt_64_to_double; #else /* MT_MACHINE_BITS */ return random_value_1 * mt_32_to_double + random_value_2 * mt_64_to_double; #endif /* MT_MACHINE_BITS */ } /* * Generate a random number in the range 0 to 2^32-1, inclusive, working * from the default state vector. * * See mts_lrand for full commentary. */ MT_EXTERN MT_INLINE unsigned long mt_lrand() { register unsigned long random_value; /* Pseudorandom value generated */ if (mt_default_state.stateptr <= 0) mts_refresh(&mt_default_state); random_value = mt_default_state.statevec[--mt_default_state.stateptr]; MT_PRE_TEMPER(random_value); return MT_FINAL_TEMPER(random_value); } #ifndef MT_NO_LONGLONG /* * Generate a random number in the range 0 to 2^64-1, inclusive, working * from the default state vector. * * See mts_llrand for full commentary. */ MT_EXTERN MT_INLINE unsigned long long mt_llrand() { register unsigned long random_value_1; /* 1st pseudorandom value generated */ register unsigned long random_value_2; /* 2nd pseudorandom value generated */ /* * For maximum speed, we'll handle the two overflow cases * together. That will save us one test in the common case, at * the expense of an extra one in the overflow case. */ if (--mt_default_state.stateptr <= 0) { if (mt_default_state.stateptr < 0) { mts_refresh(&mt_default_state); random_value_1 = mt_default_state.statevec[--mt_default_state.stateptr]; } else { random_value_1 = mt_default_state.statevec[mt_default_state.stateptr]; mts_refresh(&mt_default_state); } } else random_value_1 = mt_default_state.statevec[--mt_default_state.stateptr]; MT_TEMPER(random_value_1); random_value_2 = mt_default_state.statevec[--mt_default_state.stateptr]; MT_PRE_TEMPER(random_value_2); return ((unsigned long long) random_value_1 << 32) | (unsigned long long) MT_FINAL_TEMPER(random_value_2); } #endif /* MT_NO_LONGLONG */ /* * Generate a double-precision random number between 0 (inclusive) and 1.0 * (exclusive). This function is optimized for speed, but it only generates * 32 bits of precision. Use mt_ldrand to get 64 bits of precision. */ MT_EXTERN MT_INLINE double mt_drand() { register unsigned long random_value; /* Pseudorandom value generated */ if (mt_default_state.stateptr <= 0) mts_refresh(&mt_default_state); random_value = mt_default_state.statevec[--mt_default_state.stateptr]; MT_TEMPER(random_value); return random_value * mt_32_to_double; } /* * Generate a double-precision random number between 0 (inclusive) and 1.0 * (exclusive). This function generates 64 bits of precision. Use * mts_drand for more speed but less precision. */ MT_EXTERN MT_INLINE double mt_ldrand(void) { #if MT_MACHINE_BITS == 64 unsigned long long final_value; /* Final (integer) value */ #endif /* MT_MACHINE_BITS */ register unsigned long random_value_1; /* 1st pseudorandom value generated */ register unsigned long random_value_2; /* 2nd pseudorandom value generated */ /* * For maximum speed, we'll handle the two overflow cases * together. That will save us one test in the common case, at * the expense of an extra one in the overflow case. */ if (--mt_default_state.stateptr <= 0) { if (mt_default_state.stateptr < 0) { mts_refresh(&mt_default_state); random_value_1 = mt_default_state.statevec[--mt_default_state.stateptr]; } else { random_value_1 = mt_default_state.statevec[mt_default_state.stateptr]; mts_refresh(&mt_default_state); } } else random_value_1 = mt_default_state.statevec[--mt_default_state.stateptr]; MT_TEMPER(random_value_1); random_value_2 = mt_default_state.statevec[--mt_default_state.stateptr]; MT_TEMPER(random_value_2); #if MT_MACHINE_BITS == 64 final_value = ((unsigned long long) random_value_1 << 32) | (unsigned long long) random_value_2; return final_value * mt_64_to_double; #else /* MT_MACHINE_BITS */ return random_value_1 * mt_32_to_double + random_value_2 * mt_64_to_double; #endif /* MT_MACHINE_BITS */ } #endif /* MT_NO_INLINE */ #ifdef __cplusplus /* * C++ interface to the Mersenne Twist PRNG. This class simply * provides a more C++-ish way to access the PRNG. Only state-based * functions are provided. All functions are inlined, both for speed * and so that the same implementation code can be used in C and C++. */ class mt_prng { public: /* * Constructors and destructors. The default constructor * leaves initialization (seeding) for later unless pickSeed * is true, in which case the seed is chosen based on either * /dev/urandom (if available) or the system time. The other * constructors accept either a 32-bit seed, or a full * 624-long seed. */ mt_prng( // Default constructor bool pickSeed = false) // True to get seed from /dev/urandom // ..or time { state.stateptr = 0; state.initialized = 0; if (pickSeed) mts_seed(&state); } mt_prng(unsigned long seed) // Construct with 32-bit seeding { state.stateptr = 0; state.initialized = 0; mts_seed32(&state, seed); } mt_prng(mt_u32bit_t seeds[MT_STATE_SIZE]) // Construct with full seeding { state.stateptr = 0; state.initialized = 0; mts_seedfull(&state, seeds); } ~mt_prng() { } /* * Copy and assignment are best left defaulted. */ /* * PRNG seeding functions. */ void seed32(unsigned long seed) // Set 32-bit random seed { mts_seed32(&state, seed); } void seed32new(unsigned long seed) // Set 32-bit random seed { mts_seed32new(&state, seed); } void seedfull(mt_u32bit_t seeds[MT_STATE_SIZE]) // Set complicated random seed { mts_seedfull(&state, seeds); } void seed() // Choose seed from random input { mts_seed(&state); } void goodseed() // Choose better seed from random input { mts_goodseed(&state); } void bestseed() // Choose best seed from random input { mts_bestseed(&state); } friend std::ostream& operator<<(std::ostream& stream, const mt_prng& rng); friend std::istream& operator>>(std::istream& stream, mt_prng& rng); /* * PRNG generation functions */ unsigned long lrand() // Generate 32-bit pseudo-random value { return mts_lrand(&state); } #ifndef MT_NO_LONGLONG unsigned long long llrand() // Generate 64-bit pseudo-random value { return mts_llrand(&state); } #endif /* MT_NO_LONGLONG */ double drand() // Generate fast 32-bit floating value { return mts_drand(&state); } double ldrand() // Generate slow 64-bit floating value { return mts_ldrand(&state); } /* * Following Richard J. Wagner's example, we overload the * function-call operator to return a 64-bit floating value. * That allows the common use of the PRNG to be simplified as * in the following example: * * mt_prng ranno(true); * // ... * coinFlip = ranno() >= 0.5 ? heads : tails; */ double operator()() { return mts_drand(&state); } protected: /* * Protected data */ mt_state state; // Current state of the PRNG }; /* * Save state to a stream. See mts_savestate. */ MT_INLINE std::ostream& operator<<( std::ostream& stream, // Stream to save to const mt_prng& rng) // PRNG to save { for (int i = MT_STATE_SIZE; --i >= 0; ) { if (!(stream << rng.state.statevec[i] << ' ')) return stream; } return stream << rng.state.stateptr; } /* * Restore state from a stream. See mts_loadstate. */ MT_INLINE std::istream& operator>>( std::istream& stream, // Stream to laod from mt_prng& rng) // PRNG to load { rng.state.initialized = rng.state.stateptr = 0; for (int i = MT_STATE_SIZE; --i >= 0; ) { if (!(stream >> rng.state.statevec[i])) return stream; } if (!(stream >> rng.state.stateptr)) { rng.state.stateptr = 0; return stream; } /* * If the state is invalid, all we can do is to make it uninitialized. */ if (rng.state.stateptr < 0 || rng.state.stateptr > MT_STATE_SIZE) { rng.state.stateptr = 0; return stream; } mts_mark_initialized(&rng.state); return stream; } #endif #endif /* MTWIST_H */ april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Ladd/000077500000000000000000000000001263004425400246245ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Ladd/Ladd.cpp000066400000000000000000000033461263004425400262020ustar00rootroot00000000000000// Ladd.cpp // Test output and speed of Ladd's Mersenne Twister class // Richard J. Wagner 28 Sep 2009 // This is free, unrestricted software void of any warranty. #include #include #include #include "mtprng.h" using namespace libcoyote; using namespace std; int main ( int argc, char * const argv[] ) { printf( "Testing output and speed of Ladd's Mersenne Twister class\n" ); printf( "\nTest of random integer generation:\n" ); unsigned long oneSeed = 4357UL; vector bigSeed; bigSeed.push_back( 0x123UL ); bigSeed.push_back( 0x234UL ); bigSeed.push_back( 0x345UL ); bigSeed.push_back( 0x456UL ); printf( "\nTest of random integer generation:\n" ); mtprng mtrand1; mtrand1.init_by_array( bigSeed ); unsigned long i; for( i = 0; i < 1000UL; ++i ) { printf( "%10lu ", mtrand1.get_rand() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1) generation:\n" ); for( i = 0; i < 1000UL; ++i ) { printf( "%10.8f ", mtrand1.get_rand_real2() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1] generation:\n" ); mtprng mtrand2( oneSeed ); for( i = 0; i < 2000UL; ++i ) { printf( "%10.8f ", mtrand2.get_rand_real1() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of time to generate one billion random integers:\n" ); mtprng mtrand3( oneSeed ); unsigned long junk = 0; clock_t start = clock(); for( i = 0; i < 1000000000UL; ++i ) { junk ^= mtrand3.get_rand(); } clock_t stop = clock(); if( junk == 0 ) printf( "jinx\n" ); printf( "Time elapsed = " ); printf( "%8.3f", double( stop - start ) / CLOCKS_PER_SEC ); printf( " s\n" ); return 0; } april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Ladd/mtprng.cpp000066400000000000000000000144321263004425400266430ustar00rootroot00000000000000//--------------------------------------------------------------------- // Algorithmic Conjurings @ http://www.coyotegulch.com // // mtprng.cpp (libcoyote) // // Mersenne Twister -- A pseudorandom Number Generator // // ORIGINAL ALGORITHM COPYRIGHT // ============================ // Copyright (C) 1997, 2002 Makoto Matsumoto and Takuji Nishimura. // Any feedback is very welcome. For any question, comments, see // http://www.math.keio.ac.jp/matumoto/emt.html or email // matumoto@math.keio.ac.jp //--------------------------------------------------------------------- // // COPYRIGHT NOTICE, DISCLAIMER, and LICENSE: // // This notice applies *only* to this specific expression of this // algorithm, and does not imply ownership or invention of the // implemented algorithm. // // If you modify this file, you may insert additional notices // immediately following this sentence. // // Copyright 2001, 2002, 2003 Scott Robert Ladd. // All rights reserved, except as noted herein. // // This computer program source file is supplied "AS IS". Scott Robert // Ladd (hereinafter referred to as "Author") disclaims all warranties, // expressed or implied, including, without limitation, the warranties // of merchantability and of fitness for any purpose. The Author // assumes no liability for direct, indirect, incidental, special, // exemplary, or consequential damages, which may result from the use // of this software, even if advised of the possibility of such damage. // // The Author hereby grants anyone permission to use, copy, modify, and // distribute this source code, or portions hereof, for any purpose, // without fee, subject to the following restrictions: // // 1. The origin of this source code must not be misrepresented. // // 2. Altered versions must be plainly marked as such and must not // be misrepresented as being the original source. // // 3. This Copyright notice may not be removed or altered from any // source or altered source distribution. // // The Author specifically permits (without fee) and encourages the use // of this source code for entertainment, education, or decoration. If // you use this source code in a product, acknowledgment is not required // but would be appreciated. // // Acknowledgement: // This license is based on the wonderful simple license that // accompanies libpng. // //----------------------------------------------------------------------- // // For more information on this software package, please visit // Scott's web site, Coyote Gulch Productions, at: // // http://www.coyotegulch.com // //----------------------------------------------------------------------- #include "mtprng.h" using namespace libcoyote; #if _MSC_VER < 1300 const mtprng::int_type mtprng::MATRIX_A = 0x9908b0dfUL; const mtprng::int_type mtprng::UPPER_MASK = 0x80000000UL; const mtprng::int_type mtprng::LOWER_MASK = 0x7fffffffUL; #endif //-------------------------------------------------------------------------- // Constructor mtprng::mtprng(int_type seed) { init(seed); } //-------------------------------------------------------------------------- // Initializes the generator with "seed" void mtprng::init(int_type seed) { // Save seed for historical purpose m_seed = seed; m_mt[0] = seed & 0xffffffffUL; // Set the seed using values suggested by Matsumoto & Nishimura, using // a generator by Knuth. See original source for details. for (m_mti = 1; m_mti < N; ++m_mti) m_mt[m_mti] = 0xffffffffUL & (1812433253UL * (m_mt[m_mti - 1] ^ (m_mt[m_mti - 1] >> 30)) + m_mti); } //-------------------------------------------------------------------------- // Initialize the generator from an array of seeds void mtprng::init_by_array(const std::vector & init_key) { // Note: variable names match those in original example size_t i = 1; size_t j = 0; size_t k = static_cast((N > init_key.size()) ? N : init_key.size()); init(19650218UL); for (; k; --k) { m_mt[i] = (m_mt[i] ^ ((m_mt[i - 1] ^ (m_mt[i - 1] >> 30)) * 1664525UL)) + init_key[j] + j; m_mt[i] &= 0xffffffffUL; ++i; ++j; if (i >= N) { m_mt[0] = m_mt[N - 1]; i = 1; } if (j >= static_cast(init_key.size())) j = 0; } for (k = N - 1; k; --k) { m_mt[i] = (m_mt[i] ^ ((m_mt[i - 1] ^ (m_mt[i - 1] >> 30)) * 1566083941UL)) - i; m_mt[i] &= 0xffffffffUL; ++i; if (i >= N) { m_mt[0] = m_mt[N - 1]; i = 1; } } m_mt[0] = 0x80000000UL; } //-------------------------------------------------------------------------- // Obtain the next 32-bit integer in the psuedo-random sequence mtprng::int_type mtprng::get_rand() { // Note: variable names match those in original example const int_type mag01[2] = { 0, MATRIX_A }; int_type y; size_t kk; // Generate N words at a time if (m_mti >= N) { // Fill the m_mt array for (kk=0; kk < N-M; kk++) { y = (m_mt[kk] & UPPER_MASK) | (m_mt[kk+1] & LOWER_MASK); m_mt[kk] = m_mt[kk + M] ^ (y >> 1) ^ mag01[y & 0x1]; } for ( ; kk < N-1; kk++) { y = (m_mt[kk] & UPPER_MASK) | (m_mt[kk+1] & LOWER_MASK); m_mt[kk] = m_mt[kk+(M-N)] ^ (y >> 1) ^ mag01[y & 0x1]; } y = (m_mt[N-1] & UPPER_MASK) | (m_mt[0]&LOWER_MASK); m_mt[N-1] = m_mt[M-1] ^ (y >> 1) ^ mag01[y & 0x1]; m_mti = 0; } // Here is where we actually calculate the number with a series of transformations y = m_mt[m_mti++]; y ^= (y >> 11); y ^= (y << 7) & 0x9d2c5680UL; y ^= (y << 15) & 0xefc60000UL; y ^= (y >> 18); return y; } //-------------------------------------------------------------------------- // Obtain a psuedorandom real number in the range [0,1), i.e., a number // greater than or equal to 0 and less than 1, with 53-bit precision. mtprng::real_type mtprng::get_rand_real53() { // privides a granularity of approx. 1.1E-16 int_type a = get_rand() >> 5; int_type b = get_rand() >> 6; return real_type(a * 67108864.0 + b) * (1.0 / 9007199254740992.0); } april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Ladd/mtprng.h000066400000000000000000000267271263004425400263220ustar00rootroot00000000000000//--------------------------------------------------------------------- // Algorithmic Conjurings @ http://www.coyotegulch.com // // mtprng.h (libcoyote) // // Mersenne Twister -- A pseudorandom Number Generator // // ORIGINAL ALGORITHM COPYRIGHT // ============================ // Copyright (C) 1997, 2002 Makoto Matsumoto and Takuji Nishimura. // Any feedback is very welcome. For any question, comments, see // http://www.math.keio.ac.jp/matumoto/emt.html or email // matumoto@math.keio.ac.jp //--------------------------------------------------------------------- // // COPYRIGHT NOTICE, DISCLAIMER, and LICENSE: // // This notice applies *only* to this specific expression of this // algorithm, and does not imply ownership or invention of the // implemented algorithm. // // If you modify this file, you may insert additional notices // immediately following this sentence. // // Copyright 2001, 2002, 2003 Scott Robert Ladd. // All rights reserved, except as noted herein. // // This computer program source file is supplied "AS IS". Scott Robert // Ladd (hereinafter referred to as "Author") disclaims all warranties, // expressed or implied, including, without limitation, the warranties // of merchantability and of fitness for any purpose. The Author // assumes no liability for direct, indirect, incidental, special, // exemplary, or consequential damages, which may result from the use // of this software, even if advised of the possibility of such damage. // // The Author hereby grants anyone permission to use, copy, modify, and // distribute this source code, or portions hereof, for any purpose, // without fee, subject to the following restrictions: // // 1. The origin of this source code must not be misrepresented. // // 2. Altered versions must be plainly marked as such and must not // be misrepresented as being the original source. // // 3. This Copyright notice may not be removed or altered from any // source or altered source distribution. // // The Author specifically permits (without fee) and encourages the use // of this source code for entertainment, education, or decoration. If // you use this source code in a product, acknowledgment is not required // but would be appreciated. // // Acknowledgement: // This license is based on the wonderful simple license that // accompanies libpng. // //----------------------------------------------------------------------- // For more information on this software package, please visit // Scott's web site, Coyote Gulch Productions, at: // // http://www.coyotegulch.com //----------------------------------------------------------------------- #if !defined(LIBCOYOTE_MTPRNG_H) #define LIBCOYOTE_MTPRNG_H // Standard C++ Library #include #include #include namespace libcoyote { //! Implements the Mersenne Twister, a peudorandom number generator /*! The mtprng class encapsulates the Mersenne Twister algorithm invented by Makoto Matsumoto and Takuji Nishimura. One of the appealing aspects of the Mersenne Twister is its use of binary operations (as opposed to time-consuming multiplication) for generating numbers. The algorithm's period is 219937-1 (~106001), as compared to a period of ~108 for the best variants of the linear congruential methods. For practical purposes, the Mersenne Twister doesn't repeat itself. And the basic algorithm generates 32-bit integers, while the standard rand() function produces 16-bit values.

Version history - 1.0.0 (9 December 2001) - Original release . - 1.1.0 (26 Jan 2002) - Fixed problems with Microsoft C++ 6 (v12.00) and static constant initializations. - Added protection from multiple inclusions. - Added Doxygen comments. - Changed get_rand_range to use int_value parameters instead of int. - Added function to return an encoded version number. . 1.2.0 (5 February 2002) - Implemented enhancements announced on 26 Jan by Matsumoto and Nishimura - Added new functions to reflect M&N's latest work. . 1.2.1 7 February 2002 - Added function to return a random zero-based, size_t index - Inlined the simplest "get" functions . 1.3.0 19 April 2002 - Updated for improve Microsoft Visual C++ 13.0 in Visual Studio.NET. - Move these classes back into the libcoyote namespace. . 1.3.1 15 June 2002 - Updated and expanded doxygen comments . 1.3.2 15 June 2002 - Added ability to retrieve seed used in initialization . 1.3.2 15 January 2003 - Modified init_by_array to eliminate warnings. - improved consistency with my other code. . \version 1.3.2 \date 15 January 2003 */ class mtprng { public: //! Defines the 32-bit integer type. typedef unsigned long int_type; // needs to be a 32-bit type //! Defines the 64-bit IEEE-754 type. typedef double real_type; // needs to be a 64-bit or larger type private: #if _MSC_VER < 1300 // Period parameters #define N size_t(624) #define M size_t(397) static const int_type MATRIX_A; static const int_type UPPER_MASK; static const int_type LOWER_MASK; #else // Period parameters static const size_t N = 624; static const size_t M = 397; static const int_type MATRIX_A = 0x9908b0dfUL; static const int_type UPPER_MASK = 0x80000000UL; static const int_type LOWER_MASK = 0x7fffffffUL; #endif // Working storage int_type m_seed; int_type m_mt[N]; size_t m_mti; int_type m_multiplier; public: //! Default constructor, with optional seed. /*! The constructor uses a default value for the seed. In practice, you'll want to use a better seed, perhaps based on the time or some stochastic source such as /dev/random or /dev/urandom. \param seed - Seed value used to "start" or seed the generator */ mtprng(int_type seed = 19650218UL); //! Initializes the generator with "seed" /*! Resets the generator using the provided seed value. \param seed - Seed value used to "start" or seed the generator \sa int_type */ void init(int_type seed); //! Returns the original seed value /*! Returns the seed value used to initialize this generator. \return The seed value used to initialize this generator */ int_type get_seed() { return m_seed; } //! Initialize the generator from an array of seeds /*! Uses an array of integer seeds to initialize the generator. \param init_key - A vector of int_type seeds \sa int_type */ void init_by_array(const std::vector & init_key); //! Get the next integer /*! Returns the next int_type in sequence. \return A pseudorandom int_type value \sa int_type */ int_type get_rand(); //! Get the next integer in the range [lo,hi] /*! Returns the next int_value between lo and hi, inclusive. \param lo - Minimum value of result \param hi - Maximum value of result \return A pseudorandom int_type value \sa int_type */ int_type get_rand_range(int_type lo, int_type hi); //! Get the next random value as a size_t index /*! Returns the next value as a size_t "index" in the range [0,length). \param length - Maximum value of result \return A pseudorandom size_t value */ size_t get_rand_index(size_t length); //! Get the next number in the range [0,1] /*! Returns the next real number in the range [0,1], i.e., a number greater than or equal to 0 and less than or equal to 1. Provides 32-bit precision. \return A pseudorandom real_type value \sa real_type */ real_type get_rand_real1(); //! Get the next number in the range [0,1) /*! Returns the next real number in the range [0,1), i.e., a number greater than or equal to 0 and less than 1. Provides 32-bit precision. \return A pseudorandom real_type value \sa real_type */ real_type get_rand_real2(); //! Get the next number in the range (0,1) /*! Returns the next real number in the range (0,1), i.e., a number greater than 0 and less than 1. Provides 32-bit precision. \return A pseudorandom real_type value \sa real_type */ real_type get_rand_real3(); //! Get the next number in the range [0,1) /*! Returns the next real number in the range [0,1), i.e., a number greater than or equal to 0 and less than 1. Provides 53-bit precision. \return A pseudorandom real_type value \sa real_type */ real_type get_rand_real53(); }; //--------------------------------------------------------------------------- // Obtain a psuedorandom integer in the range [lo,hi] inline mtprng::int_type mtprng::get_rand_range(mtprng::int_type lo, mtprng::int_type hi) { // Local working storage real_type range = hi - lo + 1.0; // Use real value to caluclate range return lo + int_type(floor(range * get_rand_real2())); } //-------------------------------------------------------------------------- // Returns the next value as a size_t "index" in the range [0,length). inline size_t mtprng::get_rand_index(size_t length) { return size_t(real_type(length) * get_rand_real2()); } //-------------------------------------------------------------------------- // Obtain a psuedorandom real number in the range [0,1], i.e., a number // greater than or equal to 0 and less than or equal to 1. inline mtprng::real_type mtprng::get_rand_real1() { // privides a granularity of approx. 2.3E-10 return real_type(get_rand()) * (1.0 / 4294967295.0); } //-------------------------------------------------------------------------- // Obtain a psuedorandom real number in the range [0,1), i.e., a number // greater than or equal to 0 and less than 1. inline mtprng::real_type mtprng::get_rand_real2() { // privides a granularity of approx. 2.3E-10 return real_type(get_rand()) * (1.0 / 4294967296.0); } //-------------------------------------------------------------------------- // Obtain a psuedorandom real number in the range (0,1), i.e., a number // greater than 0 and less than 1. inline mtprng::real_type mtprng::get_rand_real3() { // privides a granularity of approx. 2.3E-10 return real_type((double(get_rand()) + 0.5) * (1.0 / 4294967296.0)); } } // end namespace CoyoteGulch #endif april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Makefile000066400000000000000000000037601263004425400254260ustar00rootroot00000000000000# Makefile for testing various Mersenne Twister implementations # Define compiler and compilation options CC = g++ CFLAGS = -ansi -Wall COPTIM = -O3 # Compile and run test programs .PHONY: all run test clean all: test run: test WagnerTest: Wagner/Wagner.cpp ../MersenneTwister.h $(CC) $(CFLAGS) $(COPTIM) -o WagnerTest -I../ Wagner/Wagner.cpp BedauxTest: Bedaux/Bedaux.cpp Bedaux/mtrand.h Bedaux/mtrand.cpp -$(CC) $(COPTIM) -o BedauxTest Bedaux/Bedaux.cpp Bedaux/mtrand.cpp BlevinsTest: Blevins/Blevins.cpp Blevins/mt.h Blevins/mt.cc -$(CC) $(COPTIM) -o BlevinsTest Blevins/Blevins.cpp Blevins/mt.cc CokusTest: Cokus/Cokus.cpp Cokus/mt19937ar-cok.c -$(CC) $(COPTIM) -o CokusTest Cokus/Cokus.cpp KuenningTest: Kuenning/Kuenning.cpp Kuenning/mtwist.h Kuenning/mtwist.c -$(CC) $(COPTIM) -o KuenningTest Kuenning/Kuenning.cpp Kuenning/mtwist.c LaddTest: Ladd/Ladd.cpp Ladd/mtprng.h Ladd/mtprng.cpp -$(CC) $(COPTIM) -o LaddTest Ladd/Ladd.cpp Ladd/mtprng.cpp OriginalTest: Original/Original.cpp Original/mt19937ar.c -$(CC) $(COPTIM) -o OriginalTest Original/Original.cpp StandardTest: Standard/Standard.cpp -$(CC) $(COPTIM) -o StandardTest Standard/Standard.cpp YangTest: Yang/Yang.cpp Yang/mtrnd.h -$(CC) $(COPTIM) -o YangTest Yang/Yang.cpp test: WagnerTest BedauxTest BlevinsTest CokusTest KuenningTest LaddTest OriginalTest StandardTest YangTest @ echo @ echo "Testing output and speed of random number generators, please be patient..." ./WagnerTest > Wagner.out -./BedauxTest > Bedaux.out -./BlevinsTest > Blevins.out -./CokusTest > Cokus.out -./KuenningTest > Kuenning.out -./LaddTest > Ladd.out -./OriginalTest > Original.out -./StandardTest > Standard.out -./YangTest > Yang.out ./Results.sh # Clean away executable and output files clean: @ rm -f Wagner.out Bedaux.out Blevins.out Cokus.out Kuenning.out Ladd.out Original.out Standard.out Yang.out @ rm -f WagnerTest BedauxTest BlevinsTest CokusTest KuenningTest LaddTest OriginalTest StandardTest YangTest @ rm -f state.dat *.tmp core april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Original/000077500000000000000000000000001263004425400255245ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Original/Original.cpp000066400000000000000000000030441263004425400277750ustar00rootroot00000000000000// Original.cpp // Test output and speed of inventors' Mersenne Twister program // Richard J. Wagner 29 Sep 2009 // This is free, unrestricted software void of any warranty. #include #include #include "mt19937ar.c" int main ( int argc, char * const argv[] ) { printf( "Testing output and speed of inventors' Mersenne Twister program\n" ); printf( "\nTest of random integer generation:\n" ); unsigned long oneSeed = 4357UL; unsigned long bigSeed[4] = { 0x123UL, 0x234UL, 0x345UL, 0x456UL }; printf( "\nTest of random integer generation:\n" ); init_by_array( bigSeed, 4 ); unsigned long i; for( i = 0; i < 1000UL; ++i ) { printf( "%10lu ", genrand_int32() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1) generation:\n" ); for( i = 0; i < 1000UL; ++i ) { printf( "%10.8f ", genrand_real2() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1] generation:\n" ); init_genrand( oneSeed ); for( i = 0; i < 2000UL; ++i ) { printf( "%10.8f ", genrand_real1() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of time to generate one billion random integers:\n" ); init_genrand( oneSeed ); unsigned long junk = 0; clock_t start = clock(); for( i = 0; i < 1000000000UL; ++i ) { junk ^= genrand_int32(); } clock_t stop = clock(); if( junk == 0 ) printf( "jinx\n" ); printf( "Time elapsed = " ); printf( "%8.3f", double( stop - start ) / CLOCKS_PER_SEC ); printf( " s\n" ); return 0; } april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Original/mt19937ar.c000066400000000000000000000143031263004425400272510ustar00rootroot00000000000000/* A C-program for MT19937, with initialization improved 2002/1/26. Coded by Takuji Nishimura and Makoto Matsumoto. Before using, initialize the state by using init_genrand(seed) or init_by_array(init_key, key_length). Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura, All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. The names of its contributors may not be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Any feedback is very welcome. http://www.math.keio.ac.jp/matumoto/emt.html email: matumoto@math.keio.ac.jp */ #include /* Period parameters */ #define N 624 #define M 397 #define MATRIX_A 0x9908b0dfUL /* constant vector a */ #define UPPER_MASK 0x80000000UL /* most significant w-r bits */ #define LOWER_MASK 0x7fffffffUL /* least significant r bits */ static unsigned long mt[N]; /* the array for the state vector */ static int mti=N+1; /* mti==N+1 means mt[N] is not initialized */ /* initializes mt[N] with a seed */ void init_genrand(unsigned long s) { mt[0]= s & 0xffffffffUL; for (mti=1; mti> 30)) + mti); /* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */ /* In the previous versions, MSBs of the seed affect */ /* only MSBs of the array mt[]. */ /* 2002/01/09 modified by Makoto Matsumoto */ mt[mti] &= 0xffffffffUL; /* for >32 bit machines */ } } /* initialize by an array with array-length */ /* init_key is the array for initializing keys */ /* key_length is its length */ void init_by_array(unsigned long init_key[], int key_length) { int i, j, k; init_genrand(19650218UL); i=1; j=0; k = (N>key_length ? N : key_length); for (; k; k--) { mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1664525UL)) + init_key[j] + j; /* non linear */ mt[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */ i++; j++; if (i>=N) { mt[0] = mt[N-1]; i=1; } if (j>=key_length) j=0; } for (k=N-1; k; k--) { mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1566083941UL)) - i; /* non linear */ mt[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */ i++; if (i>=N) { mt[0] = mt[N-1]; i=1; } } mt[0] = 0x80000000UL; /* MSB is 1; assuring non-zero initial array */ } /* generates a random number on [0,0xffffffff]-interval */ unsigned long genrand_int32(void) { unsigned long y; static unsigned long mag01[2]={0x0UL, MATRIX_A}; /* mag01[x] = x * MATRIX_A for x=0,1 */ if (mti >= N) { /* generate N words at one time */ int kk; if (mti == N+1) /* if init_genrand() has not been called, */ init_genrand(5489UL); /* a default initial seed is used */ for (kk=0;kk> 1) ^ mag01[y & 0x1UL]; } for (;kk> 1) ^ mag01[y & 0x1UL]; } y = (mt[N-1]&UPPER_MASK)|(mt[0]&LOWER_MASK); mt[N-1] = mt[M-1] ^ (y >> 1) ^ mag01[y & 0x1UL]; mti = 0; } y = mt[mti++]; /* Tempering */ y ^= (y >> 11); y ^= (y << 7) & 0x9d2c5680UL; y ^= (y << 15) & 0xefc60000UL; y ^= (y >> 18); return y; } /* generates a random number on [0,0x7fffffff]-interval */ long genrand_int31(void) { return (long)(genrand_int32()>>1); } /* generates a random number on [0,1]-real-interval */ double genrand_real1(void) { return genrand_int32()*(1.0/4294967295.0); /* divided by 2^32-1 */ } /* generates a random number on [0,1)-real-interval */ double genrand_real2(void) { return genrand_int32()*(1.0/4294967296.0); /* divided by 2^32 */ } /* generates a random number on (0,1)-real-interval */ double genrand_real3(void) { return (((double)genrand_int32()) + 0.5)*(1.0/4294967296.0); /* divided by 2^32 */ } /* generates a random number on [0,1) with 53-bit resolution*/ double genrand_res53(void) { unsigned long a=genrand_int32()>>5, b=genrand_int32()>>6; return(a*67108864.0+b)*(1.0/9007199254740992.0); } /* These real versions are due to Isaku Wada, 2002/01/09 added */ /* This main() outputs 2000 generated integers and reals. */ /* int main(void) { int i; unsigned long init[4]={0x123, 0x234, 0x345, 0x456}, length=4; init_by_array(init, length); printf("1000 outputs of genrand_int32()\n"); for (i=0; i<1000; i++) { printf("%10lu ", genrand_int32()); if (i%5==4) printf("\n"); } printf("\n1000 outputs of genrand_real2()\n"); for (i=0; i<1000; i++) { printf("%10.8f ", genrand_real2()); if (i%5==4) printf("\n"); } return 0; } */ april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Reference.out000066400000000000000000001300651263004425400264140ustar00rootroot00000000000000Testing output and speed of inventors' Mersenne Twister program Test of random integer generation: Test of random integer generation: 1067595299 955945823 477289528 4107218783 4228976476 3344332714 3355579695 227628506 810200273 2591290167 2560260675 3242736208 646746669 1479517882 4245472273 1143372638 3863670494 3221021970 1773610557 1138697238 1421897700 1269916527 2859934041 1764463362 3874892047 3965319921 72549643 2383988930 2600218693 3237492380 2792901476 725331109 605841842 271258942 715137098 3297999536 1322965544 4229579109 1395091102 3735697720 2101727825 3730287744 2950434330 1661921839 2895579582 2370511479 1004092106 2247096681 2111242379 3237345263 4082424759 219785033 2454039889 3709582971 835606218 2411949883 2735205030 756421180 2175209704 1873865952 2762534237 4161807854 3351099340 181129879 3269891896 776029799 2218161979 3001745796 1866825872 2133627728 34862734 1191934573 3102311354 2916517763 1012402762 2184831317 4257399449 2899497138 3818095062 3030756734 1282161629 420003642 2326421477 2741455717 1278020671 3744179621 271777016 2626330018 2560563991 3055977700 4233527566 1228397661 3595579322 1077915006 2395931898 1851927286 3013683506 1999971931 3006888962 1049781534 1488758959 3491776230 104418065 2448267297 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2077782664 1232942813 4023002732 1399011509 3140569849 2579909222 3794857471 900758066 2887199683 1720257997 3367494931 2668921229 955539029 3818726432 1105704962 3889207255 2277369307 2746484505 1761846513 2413916784 2685127085 4240257943 1166726899 4215215715 3082092067 3960461946 1663304043 2087473241 4162589986 2507310778 1579665506 767234210 970676017 492207530 1441679602 1314785090 3262202570 3417091742 1561989210 3011406780 1146609202 3262321040 1374872171 1634688712 1280458888 2230023982 419323804 3262899800 39783310 1641619040 1700368658 2207946628 2571300939 2424079766 780290914 2715195096 3390957695 163151474 2309534542 1860018424 555755123 280320104 1604831083 2713022383 1728987441 3639955502 623065489 3828630947 4275479050 3516347383 2343951195 2430677756 635534992 3868699749 808442435 3070644069 4282166003 2093181383 2023555632 1568662086 3422372620 4134522350 3016979543 3259320234 2888030729 3185253876 4258779643 1267304371 1022517473 815943045 929020012 2995251018 3371283296 3608029049 2018485115 122123397 2810669150 1411365618 1238391329 1186786476 3155969091 2242941310 1765554882 279121160 4279838515 1641578514 3796324015 13351065 103516986 1609694427 551411743 2493771609 1316337047 3932650856 4189700203 463397996 2937735066 1855616529 2626847990 55091862 3823351211 753448970 4045045500 1274127772 1124182256 92039808 2126345552 425973257 386287896 2589870191 1987762798 4084826973 2172456685 3366583455 3602966653 2378803535 2901764433 3716929006 3710159000 2653449155 3469742630 3096444476 3932564653 2595257433 318974657 3146202484 853571438 144400272 3768408841 782634401 2161109003 570039522 1886241521 14249488 2230804228 1604941699 3928713335 3921942509 2155806892 134366254 430507376 1924011722 276713377 196481886 3614810992 1610021185 1785757066 851346168 3761148643 2918835642 3364422385 3012284466 3735958851 2643153892 3778608231 1164289832 205853021 2876112231 3503398282 3078397001 3472037921 1748894853 2740861475 316056182 1660426908 168885906 956005527 3984354789 566521563 1001109523 1216710575 2952284757 3834433081 3842608301 2467352408 3974441264 3256601745 1409353924 1329904859 2307560293 3125217879 3622920184 3832785684 3882365951 2308537115 2659155028 1450441945 3532257603 3186324194 1225603425 1124246549 175808705 3009142319 2796710159 3651990107 160762750 1902254979 1698648476 1134980669 497144426 3302689335 4057485630 3603530763 4087252587 427812652 286876201 823134128 1627554964 3745564327 2589226092 4202024494 62878473 3275585894 3987124064 2791777159 1916869511 2585861905 1375038919 1403421920 60249114 3811870450 3021498009 2612993202 528933105 2757361321 3341402964 2621861700 273128190 4015252178 3094781002 1621621288 2337611177 1796718448 1258965619 4241913140 2138560392 3022190223 4174180924 450094611 3274724580 617150026 2704660665 1469700689 1341616587 356715071 1188789960 2278869135 1766569160 2795896635 57824704 2893496380 1235723989 1630694347 3927960522 428891364 1814070806 2287999787 4125941184 3968103889 3548724050 1025597707 1404281500 2002212197 92429143 2313943944 2403086080 3006180634 3561981764 1671860914 1768520622 1803542985 844848113 3006139921 1410888995 1157749833 2125704913 1789979528 1799263423 741157179 2405862309 767040434 2655241390 3663420179 2172009096 2511931187 1680542666 231857466 1154981000 157168255 1454112128 3505872099 1929775046 2309422350 2143329496 2960716902 407610648 2938108129 2581749599 538837155 2342628867 430543915 740188568 1937713272 3315215132 2085587024 4030765687 766054429 3517641839 689721775 1294158986 1753287754 4202601348 1974852792 33459103 3568087535 3144677435 1686130825 4134943013 3005738435 3599293386 426570142 754104406 3660892564 1964545167 829466833 821587464 1746693036 1006492428 1595312919 1256599985 1024482560 1897312280 2902903201 691790057 1037515867 3176831208 1968401055 2173506824 1089055278 1748401123 2941380082 968412354 1818753861 2973200866 3875951774 1119354008 3988604139 1647155589 2232450826 3486058011 3655784043 3759258462 847163678 1082052057 989516446 2871541755 3196311070 3929963078 658187585 3664944641 2175149170 2203709147 2756014689 2456473919 3890267390 1293787864 2830347984 3059280931 4158802520 1561677400 2586570938 783570352 1355506163 31495586 3789437343 3340549429 2092501630 896419368 671715824 3530450081 3603554138 1055991716 3442308219 1499434728 3130288473 3639507000 17769680 2259741420 487032199 4227143402 3693771256 1880482820 3924810796 381462353 4017855991 2452034943 2736680833 2209866385 2128986379 437874044 595759426 641721026 1636065708 3899136933 629879088 3591174506 351984326 2638783544 2348444281 2341604660 2123933692 143443325 1525942256 364660499 599149312 939093251 1523003209 106601097 376589484 1346282236 1297387043 764598052 3741218111 933457002 1886424424 3219631016 525405256 3014235619 323149677 2038881721 4100129043 2851715101 2984028078 1888574695 2014194741 3515193880 4180573530 3461824363 2641995497 3179230245 2902294983 2217320456 4040852155 1784656905 3311906931 87498458 2752971818 2635474297 2831215366 3682231106 2920043893 3772929704 2816374944 309949752 2383758854 154870719 385111597 1191604312 1840700563 872191186 2925548701 1310412747 2102066999 1504727249 3574298750 1191230036 3330575266 3180292097 3539347721 681369118 3305125752 3648233597 950049240 4173257693 1760124957 512151405 681175196 580563018 1169662867 4015033554 2687781101 699691603 2673494188 1137221356 123599888 472658308 1053598179 1012713758 3481064843 3759461013 3981457956 3830587662 1877191791 3650996736 988064871 3515461600 4089077232 2225147448 1249609188 2643151863 3896204135 2416995901 1397735321 3460025646 Test of random real number [0,1) generation: 0.76275443 0.99000644 0.98670464 0.10143112 0.27933125 0.69867227 0.94218740 0.03427201 0.78842173 0.28180608 0.92179002 0.20785655 0.54534773 0.69644020 0.38107718 0.23978165 0.65286910 0.07514568 0.22765211 0.94872929 0.74557914 0.62664415 0.54708246 0.90959343 0.42043116 0.86334511 0.19189126 0.14718544 0.70259889 0.63426346 0.77408121 0.04531601 0.04605807 0.88595519 0.69398270 0.05377184 0.61711170 0.05565708 0.10133577 0.41500776 0.91810699 0.22320679 0.23353705 0.92871862 0.98897234 0.19786706 0.80558809 0.06961067 0.55840445 0.90479405 0.63288060 0.95009721 0.54948447 0.20645042 0.45000959 0.87050869 0.70806991 0.19406895 0.79286390 0.49332866 0.78483914 0.75145146 0.12341941 0.42030252 0.16728160 0.59906494 0.37575460 0.97815160 0.39815952 0.43595080 0.04952478 0.33917805 0.76509902 0.61034321 0.90654701 0.92915732 0.85365931 0.18812377 0.65913428 0.28814566 0.59476081 0.27835931 0.60722542 0.68310435 0.69387186 0.03699800 0.65897714 0.17527003 0.02889304 0.86777366 0.12352068 0.91439461 0.32022990 0.44445731 0.34903686 0.74639273 0.65918367 0.92492794 0.31872642 0.77749724 0.85413832 0.76385624 0.32744211 0.91326300 0.27458185 0.22190155 0.19865383 0.31227402 0.85321225 0.84243342 0.78544200 0.71854080 0.92503892 0.82703064 0.88306297 0.47284073 0.70059042 0.48003761 0.38671694 0.60465770 0.41747204 0.47163243 0.72750808 0.65830223 0.10955369 0.64215401 0.23456345 0.95944940 0.72822249 0.40888451 0.69980355 0.26677428 0.57333635 0.39791582 0.85377858 0.76962816 0.72004885 0.90903087 0.51376506 0.37732665 0.12691640 0.71249738 0.81217908 0.37037313 0.32772374 0.14238259 0.05614811 0.74363008 0.39773267 0.94859135 0.31452454 0.11730313 0.62962618 0.33334237 0.45547255 0.10089665 0.56550662 0.60539371 0.16027624 0.13245301 0.60959939 0.04671662 0.99356286 0.57660859 0.40269560 0.45274629 0.06699735 0.85064246 0.87742744 0.54508392 0.87242982 0.29321385 0.67660627 0.68230715 0.79052073 0.48592054 0.25186266 0.93769755 0.28565487 0.47219067 0.99054882 0.13155240 0.47110470 0.98556600 0.84397623 0.12875246 0.90953202 0.49129015 0.23792727 0.79481194 0.44337770 0.96564297 0.67749118 0.55684872 0.27286897 0.79538393 0.61965356 0.22487929 0.02226018 0.49248200 0.42247006 0.91797788 0.99250134 0.23449967 0.52531508 0.10246337 0.78685622 0.34310922 0.89892996 0.40454552 0.68608407 0.30752487 0.83601319 0.54956031 0.63777550 0.82199797 0.24890696 0.48801123 0.48661910 0.51223987 0.32969635 0.31075073 0.21393155 0.73453207 0.15565705 0.58584522 0.28976728 0.97621478 0.61498701 0.23891470 0.28518540 0.46809591 0.18371914 0.37597910 0.13492176 0.66849449 0.82811466 0.56240330 0.37548956 0.27562998 0.27521910 0.74096121 0.77176757 0.13748143 0.99747138 0.92504502 0.09175241 0.21389176 0.21766512 0.31183245 0.23271221 0.21207367 0.57903312 0.77523344 0.13242613 0.31037988 0.01204835 0.71652949 0.84487594 0.14982178 0.57423142 0.45677888 0.48420169 0.53465428 0.52667473 0.46880526 0.49849733 0.05670710 0.79022476 0.03872047 0.21697212 0.20443086 0.28949326 0.81678186 0.87629474 0.92297064 0.27373097 0.84625273 0.51505586 0.00582792 0.33295971 0.91848412 0.92537226 0.91760033 0.07541125 0.71745848 0.61158698 0.00941650 0.03135554 0.71527471 0.24821915 0.63636652 0.86159918 0.26450229 0.60160194 0.35557725 0.24477500 0.07186456 0.51757096 0.62120362 0.97981062 0.69954667 0.21065616 0.13382753 0.27693186 0.59644095 0.71500764 0.04110751 0.95730081 0.91600724 0.47704678 0.26183479 0.34706971 0.07545431 0.29398385 0.93236070 0.60486023 0.48015011 0.08870451 0.45548581 0.91872718 0.38142712 0.10668643 0.01397541 0.04520355 0.93822273 0.18011940 0.57577277 0.91427606 0.30911399 0.95853475 0.23611214 0.69619891 0.69601980 0.76765372 0.58515930 0.49479057 0.11288752 0.97187699 0.32095365 0.57563608 0.40760618 0.78703383 0.43261152 0.90877651 0.84686346 0.10599030 0.72872803 0.19315490 0.66152912 0.10210518 0.06257876 0.47950688 0.47062066 0.72701157 0.48915116 0.66110261 0.60170685 0.24516994 0.12726050 0.03451185 0.90864994 0.83494878 0.94800035 0.91035206 0.14480751 0.88458997 0.53498312 0.15963215 0.55378627 0.35171349 0.28719791 0.09097957 0.00667896 0.32309622 0.87561479 0.42534520 0.91748977 0.73908457 0.41793223 0.99279792 0.87908370 0.28458072 0.59132853 0.98672190 0.28547393 0.09452165 0.89910674 0.53681109 0.37931425 0.62683489 0.56609740 0.24801549 0.52948179 0.98328855 0.66403523 0.55523786 0.75886666 0.84784685 0.86829981 0.71448906 0.84670080 0.43922919 0.20771016 0.64157936 0.25664246 0.73055695 0.86395782 0.65852932 0.99061803 0.40280575 0.39146298 0.07291005 0.97200603 0.20555729 0.59616495 0.08138254 0.45796388 0.33681125 0.33989127 0.18717090 0.53545811 0.60550838 0.86520709 0.34290701 0.72743276 0.73023855 0.34195926 0.65019733 0.02765254 0.72575740 0.32709576 0.03420866 0.26061893 0.56997511 0.28439072 0.84422744 0.77637570 0.55982168 0.06720327 0.58449067 0.71657369 0.15819609 0.58042821 0.07947911 0.40193792 0.11376012 0.88762938 0.67532159 0.71223735 0.27829114 0.04806073 0.21144026 0.58830274 0.04140071 0.43215628 0.12952729 0.94668759 0.87391019 0.98382450 0.27750768 0.90849647 0.90962737 0.59269720 0.96102026 0.49544979 0.32007095 0.62585546 0.03119821 0.85953001 0.22017528 0.05834068 0.80731217 0.53799961 0.74166948 0.77426600 0.43938444 0.54862081 0.58575513 0.15886492 0.73214332 0.11649057 0.77463977 0.85788827 0.17061997 0.66838056 0.96076133 0.07949296 0.68521946 0.89986254 0.05667410 0.12741385 0.83470977 0.63969104 0.46612929 0.10200126 0.01194925 0.10476340 0.90285217 0.31221221 0.32980614 0.46041971 0.52024973 0.05425470 0.28330912 0.60426543 0.00598243 0.97244013 0.21135841 0.78561597 0.78428734 0.63422849 0.32909934 0.44771136 0.27380750 0.14966697 0.18156268 0.65686758 0.28726350 0.97074787 0.63676171 0.96649494 0.24526295 0.08297372 0.54257548 0.03166785 0.33735355 0.15946671 0.02102971 0.46228045 0.11892296 0.33408336 0.29875681 0.29847692 0.73767569 0.02080745 0.62980060 0.08082293 0.22993106 0.25031439 0.87787525 0.45150053 0.13673441 0.63407612 0.97907688 0.52241942 0.50580158 0.06273902 0.05270283 0.77031811 0.05113352 0.24393329 0.75036441 0.37436336 0.22877652 0.59975358 0.85707591 0.88691457 0.85547165 0.36641027 0.58720133 0.45462835 0.09243817 0.32981586 0.07820411 0.25421519 0.36004706 0.60092307 0.46192412 0.36758683 0.98424170 0.08019934 0.68594024 0.45826386 0.29962317 0.79365413 0.89231296 0.49478547 0.87645944 0.23590734 0.28106737 0.75026285 0.08136314 0.79582424 0.76010628 0.82792971 0.27947652 0.72482861 0.82191216 0.46171689 0.79189752 0.96043686 0.51609668 0.88995725 0.28998963 0.55191845 0.03934737 0.83033700 0.49553013 0.98009549 0.19017594 0.98347750 0.33452066 0.87144372 0.72106301 0.71272114 0.71465963 0.88361677 0.85571283 0.73782329 0.20920458 0.34855153 0.46766817 0.02780062 0.74898344 0.03680650 0.44866557 0.77426312 0.91025891 0.25195236 0.87319953 0.63265037 0.25552148 0.27422476 0.95217406 0.39281839 0.66441573 0.09158900 0.94515992 0.07800798 0.02507888 0.39901462 0.17382573 0.12141278 0.85502334 0.19902911 0.02160210 0.44460522 0.14688742 0.68020336 0.71323733 0.60922473 0.95400380 0.99611159 0.90897777 0.41073520 0.66206647 0.32064685 0.62805003 0.50677209 0.52690101 0.87473387 0.73918362 0.39826974 0.43683919 0.80459118 0.32422684 0.01958019 0.95319576 0.98326137 0.83931735 0.69060863 0.33671416 0.68062550 0.65152380 0.33392969 0.03451730 0.95227244 0.68200635 0.85074171 0.64721009 0.51234433 0.73402047 0.00969637 0.93835057 0.80803854 0.31485260 0.20089527 0.01323282 0.59933780 0.31584602 0.20209563 0.33754800 0.68604181 0.24443049 0.19952227 0.78162632 0.10336988 0.11360736 0.23536740 0.23262256 0.67803776 0.48749791 0.74658435 0.92156640 0.56706407 0.36683221 0.99157136 0.23421374 0.45183767 0.91609720 0.85573315 0.37706276 0.77042618 0.30891908 0.40709595 0.06944866 0.61342849 0.88817388 0.58734506 0.98711323 0.14744128 0.63242656 0.87704136 0.68347125 0.84446569 0.43265239 0.25146321 0.04130111 0.34259839 0.92697368 0.40878778 0.56990338 0.76204273 0.19820348 0.66314909 0.02482844 0.06669207 0.50205581 0.26084093 0.65139159 0.41650223 0.09733904 0.56344203 0.62651696 0.67332139 0.58037374 0.47258086 0.21010758 0.05713135 0.89390629 0.10781246 0.32037450 0.07628388 0.34227964 0.42190597 0.58201860 0.77363549 0.49595133 0.86031236 0.83906769 0.81098161 0.26694195 0.14215941 0.88210306 0.53634237 0.12090720 0.82480459 0.75930318 0.31847147 0.92768077 0.01037616 0.56201727 0.88107122 0.35925856 0.85860762 0.61109408 0.70408301 0.58434977 0.92192494 0.62667915 0.75988365 0.06858761 0.36156496 0.58057195 0.13636150 0.57719713 0.59340255 0.63530602 0.22976282 0.71915530 0.41162531 0.63979565 0.09931342 0.79344045 0.10893790 0.84450224 0.23122236 0.99485593 0.73637397 0.17276368 0.13357764 0.74965804 0.64991737 0.61990341 0.41523170 0.05878239 0.05687301 0.05497131 0.42868366 0.42571090 0.25810502 0.89642955 0.30439758 0.39310223 0.11357431 0.04288255 0.23397550 0.11200634 0.85621396 0.89733974 0.37508865 0.42077265 0.68597384 0.72781399 0.19296476 0.61699087 0.31667128 0.67756410 0.00177323 0.05725176 0.79474693 0.18885238 0.06724856 0.68193156 0.42202167 0.22082041 0.28554673 0.64995708 0.87851940 0.29124547 0.61009521 0.87374537 0.05743712 0.69902994 0.81925115 0.45653873 0.37236821 0.31118709 0.52734307 0.39672836 0.38185294 0.30163915 0.17374510 0.04913278 0.90404879 0.25742801 0.58266467 0.97663209 0.79823377 0.36437958 0.15206043 0.26529938 0.22690047 0.05839021 0.84721160 0.18622435 0.37809403 0.55706977 0.49828704 0.47659049 0.24289680 0.88477595 0.07807463 0.56245739 0.73490635 0.21099431 0.13164942 0.75840044 0.66877037 0.28988183 0.44046090 0.24967434 0.80048356 0.26029740 0.30416821 0.64151867 0.52067892 0.12880774 0.85465381 0.02690525 0.19149288 0.49630295 0.79682619 0.43566145 0.00288078 0.81484193 0.03763639 0.68529083 0.01339574 0.38405386 0.30537067 0.22994703 0.44000045 0.27217985 0.53831243 0.02870435 0.86282045 0.61831306 0.09164956 0.25609707 0.07445781 0.72185784 0.90058883 0.30070608 0.94476583 0.56822213 0.21933909 0.96772793 0.80063440 0.26307906 0.31183306 0.16501252 0.55436179 0.68562285 0.23829083 0.86511559 0.57868991 0.81888344 0.20126869 0.93172350 0.66028129 0.21786948 0.78515828 0.10262106 0.35390326 0.79303876 0.63427924 0.90479631 0.31024934 0.60635447 0.56198079 0.63573813 0.91854197 0.99701497 0.83085849 0.31692291 0.01925964 0.97446405 0.98751283 0.60944293 0.13751018 0.69519957 0.68956636 0.56969015 0.46440193 0.88341765 0.36754434 0.89223647 0.39786427 0.85055280 0.12749961 0.79452122 0.89449784 0.14567830 0.45716830 0.74822309 0.28200437 0.42546044 0.17464886 0.68308746 0.65496587 0.52935411 0.12736159 0.61523955 0.81590528 0.63107864 0.39786553 0.20102294 0.53292914 0.75485590 0.59847044 0.32861691 0.12125866 0.58917183 0.07638293 0.86845380 0.29192617 0.03989733 0.52180460 0.32503407 0.64071852 0.69516575 0.74254998 0.54587026 0.48713246 0.32920155 0.08719954 0.63497059 0.54328459 0.64178757 0.45583809 0.70694291 0.85212760 0.86074305 0.33163422 0.85739792 0.59908488 0.74566046 0.72157152 Test of random real number [0,1] generation: 0.99974175 0.16290988 0.28261781 0.94720108 0.23165654 0.48497361 0.95747696 0.74430534 0.54004366 0.73995298 0.75994380 0.65863661 0.31563762 0.80440301 0.51967212 0.16857242 0.47552973 0.39231399 0.22166769 0.21319046 0.03033520 0.33353925 0.19414885 0.94371678 0.57993168 0.89830486 0.66556393 0.49861031 0.56062826 0.18228465 0.29652553 0.11740893 0.06291767 0.64812557 0.72541853 0.63713116 0.71388506 0.09957624 0.69926720 0.10781247 0.12924275 0.50240304 0.20777991 0.28891031 0.08317479 0.12812422 0.54737141 0.08231960 0.29214143 0.89162374 0.22711784 0.43184546 0.14073300 0.40039213 0.68694690 0.17067091 0.44082087 0.04533657 0.31129641 0.50618105 0.18241084 0.51103202 0.74078821 0.36598863 0.16080884 0.46010679 0.62783647 0.67760369 0.69819652 0.47853687 0.09010759 0.33872852 0.09521380 0.43654196 0.47467335 0.41924593 0.77753685 0.62461056 0.98043655 0.37043020 0.83081264 0.14080645 0.74408531 0.82973968 0.39110432 0.62195639 0.34669948 0.04616952 0.61306632 0.56737405 0.49889403 0.72380208 0.14455052 0.04230316 0.31078702 0.12164115 0.24206967 0.38105886 0.44012854 0.59979590 0.64457465 0.43262622 0.55596826 0.71684117 0.64236251 0.68577673 0.09615815 0.12293346 0.05699742 0.82007204 0.12553929 0.31574507 0.18056692 0.14222722 0.66442961 0.68518922 0.19100193 0.43634302 0.96445922 0.86816359 0.13087997 0.48444228 0.37465445 0.90047512 0.17865679 0.67963513 0.62287431 0.98365595 0.44071478 0.80473728 0.99484506 0.54155096 0.25590546 0.63894564 0.57591027 0.25872142 0.19159300 0.44566305 0.14926651 0.99672369 0.12176222 0.65153928 0.02779510 0.38997760 0.82791304 0.28381391 0.61020364 0.23641275 0.41082105 0.67771462 0.84712659 0.64925623 0.08138265 0.12083048 0.47919926 0.77787836 0.47197770 0.94333751 0.98080099 0.33455473 0.20266792 0.34284123 0.65354424 0.68275880 0.60993614 0.09992710 0.76625498 0.73558153 0.24113914 0.26317871 0.96086990 0.42339574 0.33605815 0.00024950 0.86884102 0.00375315 0.16584631 0.01182084 0.60645507 0.72997202 0.61382456 0.96576818 0.49709826 0.52988540 0.46160753 0.71303370 0.57995977 0.68280256 0.95392151 0.02365520 0.28011015 0.86952635 0.29933327 0.31955360 0.30095171 0.94111149 0.84812706 0.75334613 0.53824409 0.40848138 0.21237132 0.07614040 0.28993491 0.01978183 0.24124790 0.38461916 0.45490689 0.37398252 0.44018880 0.11789681 0.80542984 0.16489264 0.28252994 0.17268540 0.93584233 0.68095306 0.13369674 0.25476122 0.39944488 0.36923537 0.72636189 0.27783746 0.69356910 0.50035469 0.11840554 0.15130334 0.68144694 0.72066592 0.97964694 0.69677911 0.55721007 0.68082148 0.95535205 0.59820896 0.77045390 0.91359749 0.65895865 0.67097461 0.57818518 0.95303929 0.16292346 0.33505699 0.95182470 0.10966164 0.61930230 0.95681674 0.98524309 0.07073775 0.50233039 0.68072123 0.55332007 0.58700558 0.69162056 0.46264791 0.57425429 0.07289009 0.63826652 0.38775729 0.22096022 0.00223180 0.49565678 0.19131652 0.02226501 0.90358902 0.73862818 0.44453089 0.41770224 0.76086112 0.43775322 0.19098286 0.57711296 0.13268834 0.31782435 0.48691649 0.93909107 0.93394628 0.07366014 0.61243630 0.51474872 0.62466358 0.13064526 0.64521044 0.13414855 0.65292597 0.26521001 0.38180527 0.59021506 0.66970408 0.55433248 0.01950476 0.18434696 0.99118046 0.57367776 0.63776209 0.59485760 0.51524469 0.33069351 0.39674245 0.88396548 0.77148527 0.59907538 0.02472663 0.01225879 0.69845232 0.26599101 0.73670072 0.99997262 0.74979232 0.48495559 0.82370053 0.62277709 0.90251209 0.05650513 0.73907739 0.37617622 0.03680076 0.77619822 0.83735419 0.34508193 0.08184265 0.22262154 0.15247632 0.40117720 0.53161261 0.81170660 0.04077757 0.11788901 0.57518997 0.83236221 0.20464185 0.23872177 0.99692870 0.25859060 0.89205597 0.84685979 0.30658371 0.03336249 0.70642050 0.19361561 0.50897814 0.02154515 0.67273279 0.81356244 0.80728405 0.48152684 0.53751910 0.78084861 0.33584891 0.69925937 0.42585530 0.82524066 0.94561369 0.55484125 0.71049519 0.37836037 0.64833873 0.04567272 0.15547732 0.88535397 0.72156572 0.96166720 0.43030089 0.13203135 0.43933121 0.46718774 0.41008322 0.27719671 0.27850956 0.95462081 0.80435749 0.96851047 0.99972279 0.94716028 0.24855114 0.00670499 0.44472732 0.67404878 0.49648036 0.02100925 0.83176322 0.10854585 0.09315164 0.89020564 0.44594521 0.90690677 0.55403982 0.75943435 0.81555138 0.53296850 0.05513515 0.05398565 0.89918819 0.14690737 0.48264731 0.06730298 0.28116186 0.93284917 0.50731793 0.56450301 0.80071320 0.64588750 0.30921950 0.04780661 0.25196583 0.71388114 0.67099402 0.60528576 0.14827190 0.79525035 0.66527735 0.85430204 0.81053368 0.07114398 0.06879357 0.89046657 0.75804596 0.07031059 0.85209448 0.77535690 0.68489520 0.23455279 0.46157569 0.93643546 0.66494642 0.45967959 0.88782351 0.57462226 0.03016862 0.76735472 0.34547856 0.60912314 0.21754287 0.64376056 0.57139265 0.80231105 0.96233555 0.40176986 0.99655342 0.74594581 0.44841118 0.39578428 0.12338993 0.53261491 0.83337960 0.91767313 0.82560757 0.44591540 0.26713620 0.66439890 0.76686069 0.66596828 0.50395511 0.83515370 0.62240538 0.45753892 0.55498328 0.36581371 0.65630223 0.91703867 0.27605459 0.12121444 0.96617825 0.69743901 0.44354779 0.63019582 0.36834667 0.23819196 0.30027382 0.71033217 0.04747484 0.49252544 0.08125398 0.12201678 0.99310218 0.35509103 0.76486373 0.90409954 0.39610961 0.81713486 0.34897422 0.26619363 0.36750196 0.75231621 0.58780002 0.48942109 0.67347406 0.32829614 0.85394584 0.83238074 0.15958869 0.32241102 0.95017371 0.09537671 0.23101986 0.86060775 0.35962719 0.98484370 0.03197567 0.82864991 0.51680949 0.48940792 0.96397730 0.96013174 0.68181679 0.86078817 0.45582928 0.33239066 0.05914980 0.45224598 0.21735422 0.34560744 0.54997199 0.31762225 0.89297644 0.49004545 0.25647901 0.96899864 0.91063647 0.22671760 0.32782857 0.28670209 0.14251505 0.09928174 0.19233241 0.30837687 0.87141596 0.39114879 0.78866088 0.20081604 0.98647596 0.88286213 0.10986245 0.35428326 0.55574268 0.69069846 0.64381575 0.36310429 0.07886271 0.20082041 0.71697353 0.74435375 0.76763643 0.24544245 0.66800912 0.88698938 0.36684993 0.53155663 0.50284398 0.31454367 0.62254136 0.01990386 0.67635513 0.42981862 0.23283521 0.98761946 0.30657214 0.49463704 0.74861489 0.89184356 0.04528550 0.42756107 0.22697844 0.48407299 0.16464563 0.08980749 0.38426374 0.02383547 0.32973455 0.53123074 0.47668336 0.87748247 0.45550163 0.49730250 0.39618430 0.88612473 0.73607009 0.10891760 0.39792190 0.84257502 0.82620032 0.93665517 0.24558961 0.63968862 0.49333503 0.07344951 0.78013810 0.04211212 0.70111648 0.94052327 0.70054817 0.77676027 0.19274258 0.00692527 0.84298363 0.91932418 0.24208327 0.19010067 0.73508464 0.16452232 0.99030645 0.98284794 0.65716954 0.01877364 0.75959648 0.35756761 0.50901634 0.73889968 0.56792316 0.28905663 0.41501714 0.98105456 0.36588448 0.51787826 0.84420902 0.96812265 0.25889453 0.47831044 0.43734099 0.37939800 0.20308188 0.55082075 0.25554272 0.55009803 0.87047794 0.24123021 0.15710824 0.21826083 0.11627774 0.74901828 0.15829066 0.47635391 0.54532732 0.87897812 0.01714422 0.54298199 0.31801808 0.78880534 0.87172137 0.73849041 0.09233301 0.30139864 0.63710329 0.57156427 0.71281034 0.64428924 0.23047601 0.97169559 0.96615943 0.29188391 0.17528582 0.31288255 0.98465128 0.56839135 0.84446856 0.14443391 0.45994061 0.60789791 0.18412271 0.34280549 0.60643300 0.83819659 0.18618852 0.03027447 0.30739186 0.12528603 0.27039496 0.87416148 0.37050956 0.89423337 0.40799567 0.88187847 0.64795124 0.23698673 0.52880734 0.29373154 0.09432043 0.93453863 0.12167933 0.34968176 0.06702686 0.64219677 0.69244714 0.33492673 0.37424419 0.31388505 0.53873829 0.09859252 0.49051423 0.32873567 0.70972579 0.88169803 0.39300048 0.85424327 0.46377659 0.52705639 0.49330989 0.26778434 0.58307748 0.05735142 0.95933637 0.77141717 0.04271846 0.49843337 0.05229427 0.56155145 0.96036191 0.61981731 0.52862837 0.69823518 0.18616204 0.55399817 0.66612029 0.15273105 0.94875016 0.18682579 0.58051266 0.85102444 0.10686584 0.67586174 0.79604524 0.65764610 0.00934952 0.20626759 0.63642037 0.03825646 0.67771025 0.67791793 0.67168427 0.39631772 0.66159705 0.63336038 0.96212424 0.99271142 0.09934483 0.06789327 0.42601315 0.94704550 0.70832601 0.46681785 0.04483629 0.74858092 0.67837069 0.21092134 0.39849031 0.95367558 0.02890228 0.93576657 0.84693047 0.66276018 0.86791090 0.65235932 0.45280494 0.30522898 0.35203499 0.27964340 0.23604559 0.02700346 0.65206239 0.71200023 0.61993087 0.12543908 0.45278996 0.92233151 0.12084436 0.40380897 0.26029045 0.77884364 0.66784120 0.02678944 0.49133230 0.91506089 0.70402535 0.62820085 0.57833847 0.62915642 0.73041065 0.64131833 0.46370933 0.61429124 0.25447066 0.80868269 0.22898373 0.45047800 0.87423514 0.20277391 0.52371119 0.12651827 0.57940290 0.26188467 0.20776906 0.55283816 0.85139536 0.51359444 0.55825984 0.66614854 0.99897466 0.17827407 0.11673964 0.06842554 0.62271338 0.31448295 0.88982793 0.80647766 0.42991695 0.52469546 0.45267553 0.63074312 0.56659449 0.95886066 0.90805229 0.70089826 0.37702538 0.68379623 0.19808846 0.61740070 0.41372616 0.82358842 0.75557795 0.70309732 0.36429428 0.81978699 0.75158176 0.04876951 0.52856900 0.61674819 0.27094283 0.80084175 0.23517422 0.90378655 0.25880157 0.19133641 0.01241034 0.85341400 0.62100871 0.85586193 0.14010620 0.87268796 0.70883974 0.09264099 0.02075042 0.78263652 0.03008252 0.50461063 0.08162218 0.77349375 0.87257728 0.88003125 0.88352430 0.87242733 0.45872223 0.90229884 0.54790495 0.05598844 0.59117989 0.56394171 0.77613008 0.29556978 0.04085365 0.39856718 0.28227462 0.80671632 0.50715936 0.68815096 0.49466404 0.45454604 0.42148009 0.03925173 0.09119620 0.39381531 0.13537319 0.96865058 0.81167611 0.32596541 0.96199918 0.10028120 0.10292461 0.30725909 0.33368206 0.85796613 0.52292174 0.61550004 0.98155868 0.79748474 0.19880967 0.45670419 0.57097080 0.21490870 0.68643331 0.27860212 0.17973985 0.39749795 0.16285894 0.80262176 0.08364591 0.63827075 0.23085652 0.58009438 0.86429251 0.93273829 0.82139312 0.48059047 0.63637302 0.18150866 0.46920050 0.30927644 0.66881043 0.72234116 0.57485667 0.52785451 0.80923156 0.98688266 0.32386050 0.60639646 0.75955897 0.79096818 0.06992981 0.55046541 0.00929828 0.78462948 0.68904411 0.96358809 0.51644160 0.35717830 0.48233689 0.42995960 0.99630615 0.60117601 0.78500421 0.97054212 0.48785455 0.09492675 0.97933177 0.12087774 0.63026034 0.19424754 0.21308170 0.01459878 0.36667112 0.34010078 0.72178635 0.36753311 0.02103354 0.13168799 0.58675968 0.73360464 0.86363515 0.13699465 0.05242698 0.40622341 0.24165695 0.47245070 0.87221598 0.45471923 0.07157907 0.31406124 0.49282311 0.74172113 0.69478366 0.98286787 0.31974814 0.80420370 0.05346782 0.74615535 0.30347493 0.09308151 0.93453166 0.74686819 0.10004847 0.72029651 0.21075374 0.96309675 0.74918941 0.73962193 0.51007233 0.08729299 0.65002047 0.08236485 0.72692075 0.53261827 0.74930587 0.86126694 0.03469945 0.09312246 0.65525710 0.95951785 0.48705723 0.85989575 0.08479442 0.71854172 0.85091833 0.81888478 0.71627446 0.40822393 0.63658567 0.52383870 0.37203887 0.35342610 0.59804905 0.09748687 0.27635304 0.46249328 0.62679520 0.16735534 0.29105841 0.37902551 0.89725452 0.92018046 0.88948500 0.45488573 0.44267745 0.50958911 0.37432772 0.40695476 0.97650358 0.36800316 0.11249840 0.24206472 0.69537830 0.96438770 0.91734899 0.05689786 0.65183612 0.91849217 0.06429130 0.95630841 0.46250993 0.46027806 0.25840852 0.43050347 0.29243294 0.74456400 0.07128114 0.17557919 0.43304426 0.28971250 0.54252216 0.65136994 0.97384792 0.18674972 0.42044311 0.93804625 0.72129356 0.31747715 0.73144622 0.97734543 0.02304122 0.25751111 0.76485814 0.45246407 0.79161878 0.23062322 0.33255548 0.38463149 0.69782529 0.03913658 0.41040371 0.93600181 0.44097263 0.51610418 0.10958358 0.18347718 0.48742201 0.29238579 0.61061153 0.94559573 0.26314358 0.99061572 0.21250485 0.89721615 0.21404979 0.26948987 0.45919460 0.81484508 0.08600816 0.85263778 0.78815212 0.82828977 0.20557045 0.10719847 0.85181249 0.14065521 0.68507960 0.64962273 0.49912890 0.36593842 0.92036375 0.20749966 0.62605210 0.35093936 0.81442674 0.53821678 0.97315263 0.66935241 0.96723114 0.11358916 0.44158966 0.02479640 0.29690360 0.32150035 0.67347448 0.46204118 0.98979777 0.48736192 0.11302875 0.02292857 0.68325535 0.37852404 0.49162356 0.74022269 0.07569384 0.80243880 0.30799855 0.00405781 0.11625931 0.69371346 0.17928194 0.09165273 0.35186219 0.73856375 0.51278689 0.71948082 0.82445063 0.00109667 0.80895488 0.33990554 0.59961583 0.44190693 0.44728645 0.26262404 0.41768393 0.27527363 0.42366847 0.90357941 0.62924864 0.56271578 0.90503263 0.77559845 0.21444352 0.54363274 0.68626897 0.00297602 0.18779326 0.66573594 0.74778574 0.53463212 0.72994014 0.59488998 0.46206025 0.84830971 0.06257460 0.74039936 0.55547288 0.10915408 0.44299368 0.78044512 0.99762820 0.25970964 0.27190048 0.43330299 0.75000007 0.94874757 0.92423643 0.36408412 0.44658803 0.48395359 0.60164320 0.35104197 0.22196158 0.89093397 0.85213753 0.02613714 0.17920246 0.77656505 0.77477701 0.47888598 0.11236843 0.57539895 0.33626404 0.51855719 0.06150124 0.19945519 0.18901322 0.35091639 0.21266716 0.12097324 0.14082743 0.53498359 0.57009249 0.44825861 0.07625562 0.48338675 0.87812897 0.92779163 0.16484649 0.30837901 0.53583996 0.34568556 0.79072169 0.23275695 0.77972473 0.96327223 0.69156891 0.17933842 0.31236052 0.60554383 0.33782581 0.35007524 0.17010294 0.75913042 0.76634243 0.97659223 0.13196118 0.13700643 0.88539669 0.32858954 0.32332471 0.79776557 0.77683905 0.05156944 0.82369356 0.58479079 0.01822297 0.06769188 0.56494328 0.00699099 0.66331498 0.47989495 0.89726858 0.15747825 0.10008720 0.01672149 0.42361903 0.77922210 0.16464581 0.51752479 0.02739695 0.05908112 0.65092022 0.21838759 0.40098605 0.15340441 0.06701079 0.92152195 0.20483403 0.41581201 0.08128819 0.57687698 0.07482144 0.60695357 0.12932764 0.43747291 0.52845065 0.97415121 0.29679724 0.63546098 0.18610085 0.96907701 0.24360399 0.82216364 0.09844640 0.99817895 0.39582247 0.66397677 0.54607742 0.13846181 0.79793847 0.04494742 0.82023869 0.37206952 0.59607428 0.75033941 0.51943293 0.35440496 0.57089925 0.29601236 0.93332957 0.09497664 0.49184085 0.31728012 0.96906454 0.11994357 0.54646329 0.82201922 0.39506882 0.23921519 0.76761357 0.53438962 0.17372273 0.10845020 0.51441305 0.47582057 0.57394731 0.93893074 0.74507000 0.84557306 0.84601724 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0.78101832 0.51592103 0.18073078 0.26971111 0.17543616 0.93652782 0.86947788 0.77956203 0.98613123 0.51945309 0.76112297 0.67705868 0.47933131 0.99475630 0.34528709 0.38394699 0.07025305 0.00573427 0.86044753 0.11975500 0.92854724 0.83272646 0.71044605 0.60851951 0.82361458 0.68116306 0.24342647 0.69858178 0.26309842 0.43015149 0.58283530 0.70608120 0.14284203 0.46741283 0.62884886 0.19732262 0.80905760 0.17236722 0.84548908 0.12512492 0.45794801 0.43014769 0.52079268 0.42995478 0.98690099 0.92426876 0.48105819 0.70702091 0.12772345 0.44929222 0.26948541 0.70621619 0.68545705 0.15442103 0.65096869 0.16947351 0.93334458 0.74529585 0.11107633 0.24800350 0.12932850 0.58592100 0.01702782 0.16408463 0.61205788 0.72908582 0.62861950 0.21679924 0.37220002 0.00143082 0.36929477 0.26522050 0.49576252 0.71643839 0.86512150 0.42316449 0.64121531 0.02177983 0.64557469 0.36590948 0.29502106 0.55301687 0.82193643 0.51250061 0.56384409 0.13038157 0.27747515 0.79906040 0.44327644 0.03573633 0.26647402 0.46007386 0.57273575 0.05955294 0.02738484 0.27755662 0.38169572 0.83568626 0.57810167 0.35188065 0.75052650 0.93784373 0.06873385 0.15550009 0.75770542 0.39399266 0.76738973 0.82258832 0.54570517 0.26109914 0.41387064 0.98988503 0.73862661 0.89405087 0.46517263 0.76892131 0.63834069 0.22694307 0.17413545 0.45388516 0.13778819 0.87718817 0.19358900 0.39669745 0.69410826 0.38942591 0.74846699 0.60166847 0.10070349 0.79814943 0.38520069 0.06113565 0.63849960 0.87445695 0.28151821 0.66647061 0.69045021 0.27026380 0.38000198 0.54785494 0.21392325 0.03768333 0.97564645 0.62088589 0.43109009 0.35529123 0.65398020 0.40164284 0.68442648 0.60018319 0.82954864 0.20588517 0.26434500 0.40327609 0.67231594 0.00001071 0.12568464 0.94184068 0.84787368 0.28238956 0.75353663 0.64248200 0.40284897 0.38774205 0.09660828 0.69231332 0.43263685 0.21746137 0.63643088 0.17036714 0.41380928 0.62440287 0.01524991 0.71660294 0.35039726 0.12890050 0.93603942 0.37728988 0.53986125 0.19086737 0.79948718 0.21336918 0.86500133 0.01730441 0.52699327 0.93460360 0.78688085 0.48753694 0.47270218 0.16718951 0.62584322 0.07784314 0.25880550 0.31614274 0.82720485 0.03930877 0.48836467 0.75672626 0.51982789 0.52661187 0.58994948 0.26021491 0.85740866 0.00270608 0.84953742 0.54582054 0.49245070 0.81082741 0.03650983 0.70423463 0.28868105 0.36034209 0.62670183 0.55153555 0.70261313 0.52340994 0.94126331 0.92782611 0.83976392 0.68451381 0.45417252 0.42818433 0.90718905 0.92167762 0.83592956 0.77223501 0.21000816 0.36844489 0.42105175 0.93254882 0.55116609 0.71012751 0.64443141 0.95030443 0.54010041 0.47428573 0.21414311 0.40365527 0.97398575 0.80842660 0.33926944 0.45469210 0.80718342 0.43932528 0.33541083 0.17845952 0.81576049 0.53261815 0.88017310 0.26603507 0.77185675 0.99748308 0.62138555 0.45572542 0.98952409 0.29449151 0.13132836 0.99309783 0.93285650 0.75109686 0.64941883 0.76049034 0.56793616 0.82309452 0.98914869 0.34820035 0.94189845 0.44831773 0.13945743 0.10096745 0.11156922 0.27555091 0.34565316 0.70353568 0.32496337 0.13686084 0.77024512 0.34054553 0.01573949 0.83543082 0.88943741 0.44316549 0.70468817 0.39202185 0.75558344 0.72904960 0.00293116 0.14430837 0.17406997 0.61716542 0.97152630 0.53263715 0.53342867 0.62738670 0.70928541 0.17240765 0.87766521 0.34364405 0.91037934 0.64626307 0.47972638 0.19022095 0.92093843 0.94606042 0.09841273 0.05376057 0.37769904 0.99337472 0.17411575 0.14251156 0.77208802 0.57248955 0.24789910 0.42049708 0.05905334 0.27052679 0.88617116 0.05486600 0.17222135 0.34808022 0.82182394 0.70571761 0.29748556 0.61295951 0.68171897 0.87923813 0.41185968 0.76925120 0.11329592 0.97930007 0.39963163 0.98513040 0.16385038 0.98107033 0.78849187 0.53094677 0.21334692 0.18792823 0.35384094 0.63650769 Test of time to generate one billion random integers: Time elapsed = 6.736 s april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Results.sh000077500000000000000000000107101263004425400257570ustar00rootroot00000000000000#!/bin/sh # Results.sh # Examine the output from tests of Mersenne Twister random number generators # Explain the meaning in plain English rm -f Bug.txt echo echo "Examining performance of Wagner's MersenneTwister.h C++ class..." # Extract the various distribution series from each generator's output for NAME in *.out; do BASE=`basename $NAME .out` grep -A 200 "integer generation:" $NAME | tail -200 > $BASE.integer.tmp grep -A 200 -F "[0,1) generation:" $NAME | tail -200 > $BASE.exclusive.tmp grep -A 400 -F "[0,1] generation:" $NAME | tail -400 > $BASE.inclusive.tmp done # Compare the output to the inventors' reference output rm -f *.reference.tmp for NAME in *.out; do BASE=`basename $NAME .out` diff --brief $BASE.integer.tmp Reference.integer.tmp >> $BASE.reference.tmp diff --brief $BASE.exclusive.tmp Reference.exclusive.tmp >> $BASE.reference.tmp diff --brief $BASE.inclusive.tmp Reference.inclusive.tmp >> $BASE.reference.tmp done # Look for an available awk command if which awk &> /dev/null then AWK=awk elif which gawk &> /dev/null then AWK=gawk elif which nawk &> /dev/null then AWK=nawk fi # Report comparison test results if [ $AWK ]; then echo echo "Comparison of integer generation rate with other versions:" printf " This version " if [ -s Wagner.out ]; then $AWK '/Time elapsed/{ printf( "%6.1f million per second", 1000 / $4 ) }' Wagner.out if [ -s Wagner.reference.tmp ]; then printf " (non-conforming)\n" else printf "\n" fi else printf " Failed to run\n" fi printf " Inventors' version " if [ -s Original.out ]; then $AWK '/Time elapsed/{ printf( "%6.1f million per second", 1000 / $4 ) }' Original.out if [ -s Original.reference.tmp ]; then printf " (non-conforming)\n" else printf "\n" fi else printf " Failed to run\n" fi printf " Bedaux's version " if [ -s Bedaux.out ]; then $AWK '/Time elapsed/{ printf( "%6.1f million per second", 1000 / $4 ) }' Bedaux.out if [ -s Bedaux.reference.tmp ]; then printf " (non-conforming)\n" else printf "\n" fi else printf " Failed to run\n" fi printf " Blevins's version " if [ -s Blevins.out ]; then $AWK '/Time elapsed/{ printf( "%6.1f million per second", 1000 / $4 ) }' Blevins.out if [ -s Blevins.reference.tmp ]; then printf " (non-conforming)\n" else printf "\n" fi else printf " Failed to run\n" fi printf " Cokus's version " if [ -s Cokus.out ]; then $AWK '/Time elapsed/{ printf( "%6.1f million per second", 1000 / $4 ) }' Cokus.out if [ -s Cokus.reference.tmp ]; then printf " (non-conforming)\n" else printf "\n" fi else printf " Failed to run\n" fi printf " Kuenning's version " if [ -s Kuenning.out ]; then $AWK '/Time elapsed/{ printf( "%6.1f million per second", 1000 / $4 ) }' Kuenning.out if [ -s Kuenning.reference.tmp ]; then printf " (non-conforming)\n" else printf "\n" fi else printf " Failed to run\n" fi printf " Ladd's version " if [ -s Ladd.out ]; then $AWK '/Time elapsed/{ printf( "%6.1f million per second", 1000 / $4 ) }' Ladd.out if [ -s Ladd.reference.tmp ]; then printf " (non-conforming)\n" else printf "\n" fi else printf " Failed to run\n" fi printf " Yang's version " if [ -s Yang.out ]; then $AWK '/Time elapsed/{ printf( "%6.1f million per second", 1000 / $4 ) }' Yang.out if [ -s Yang.reference.tmp ]; then printf " (non-conforming)\n" else printf "\n" fi else printf " Failed to run\n" fi printf " Built-in rand() " if [ -s Standard.out ]; then $AWK '/Time elapsed/{ printf( "%6.1f million per second", 1000 / $4 ) }' Standard.out if [ -s Standard.reference.tmp ]; then printf " (non-conforming)\n" else printf "\n" fi else printf " Failed to run\n" fi fi # Report own performance test results echo grep -A 100 "Test of generation rates in various distributions:" Wagner.out # Summarize results echo grep "Error" Wagner.out >> Wagner.error.tmp if [ -s Wagner.reference.tmp ] && ![ -s Wagner.error.tmp ]; then cat Wagner.out Original.out Cokus.out > Bug.txt echo "Failed tests - MersenneTwister.h generated incorrect output" echo "Results have been written to a file called 'Bug.txt'" echo "Please send a copy of 'Bug.txt' and system info to wagnerr@umich.edu" else echo "MersenneTwister.h passed all tests" fi rm -f *.tmp exit 0 april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Standard/000077500000000000000000000000001263004425400255205ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Standard/Standard.cpp000066400000000000000000000034051263004425400277660ustar00rootroot00000000000000// Standard.cpp // Test output and speed of standard random number generator // Richard J. Wagner 29 Sep 2009 // This is free, unrestricted software void of any warranty. #include #include #include int main ( int argc, char * const argv[] ) { printf( "Testing output and speed of standard random number generator\n" ); printf( "\nTest of random integer generation:\n" ); unsigned long oneSeed = 4357UL; unsigned long bigSeed[4] = { 0x123UL, 0x234UL, 0x345UL, 0x456UL }; // NOTE: The standard random number generator provided with a C++ compiler // is unlikely to be the Mersenne Twister. Therefore it probably lacks the // ability to accept a big seed and will probably not match any of the // expected output. printf( "\nTest of random integer generation:\n" ); srand( bigSeed[0] ); unsigned long i; for( i = 0; i < 1000UL; ++i ) { printf( "%10i ", rand() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1) generation:\n" ); for( i = 0; i < 1000UL; ++i ) { printf( "%10.8f ", rand() / ( RAND_MAX + 1.0 ) ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1] generation:\n" ); srand( oneSeed ); for( i = 0; i < 2000UL; ++i ) { printf( "%10.8f ", rand() / ( RAND_MAX + 0.0 ) ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of time to generate one billion random integers:\n" ); srand( oneSeed ); unsigned long junk = 0; clock_t start = clock(); for( i = 0; i < 1000000000UL; ++i ) { junk ^= rand(); } clock_t stop = clock(); if( junk == 0 ) printf( "jinx\n" ); printf( "Time elapsed = " ); printf( "%8.3f", double( stop - start ) / CLOCKS_PER_SEC ); printf( " s\n" ); return 0; } april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Wagner/000077500000000000000000000000001263004425400252035ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Wagner/Wagner.cpp000066400000000000000000000226661263004425400271460ustar00rootroot00000000000000// Wagner.cpp // Test output and speed of MersenneTwister.h // Richard J. Wagner 30 Sep 2009 // This is free, unrestricted software void of any warranty. #include #include #include #include "MersenneTwister.h" void showrate( clock_t start, clock_t stop, int reps ); int main( int argc, char * const argv[] ) { printf( "Testing output and speed of MersenneTwister.h\n" ); MTRand::uint32 oneSeed = 4357UL; MTRand::uint32 bigSeed[4] = { 0x123UL, 0x234UL, 0x345UL, 0x456UL }; printf( "\nTest of random integer generation:\n" ); MTRand mtrand1( bigSeed, 4 ); unsigned long i; for( i = 0; i < 1000UL; ++i ) { printf( "%10lu ", mtrand1.randInt() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1) generation:\n" ); for( i = 0; i < 1000UL; ++i ) { printf( "%10.8f ", mtrand1.randExc() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1] generation:\n" ); MTRand mtrand2( oneSeed ); for( i = 0; i < 2000UL; ++i ) { printf( "%10.8f ", mtrand2.rand() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of time to generate one billion random integers:\n" ); MTRand mtrand3( oneSeed ); unsigned long junk = 0; clock_t start = clock(); for( i = 0; i < 1000000000UL; ++i ) { junk ^= mtrand3.randInt(); } clock_t stop = clock(); if( junk == 0 ) printf( "jinx\n" ); printf( "Time elapsed = " ); printf( "%8.3f", double( stop - start ) / CLOCKS_PER_SEC ); printf( " s\n" ); printf( "\nTest of generation rates in various distributions:\n" ); { unsigned long junki = 0; double junkf = 0; printf( " Integers in [0,2^32-1] " ); start = clock(); for( i = 0; i < 1000000000UL; ++i ) junki ^= mtrand3.randInt(); stop = clock(); showrate(start,stop,1000); printf( " Integers in [0,100] " ); start = clock(); for( i = 0; i < 500000000UL; ++i ) junki ^= mtrand3.randInt(100); stop = clock(); showrate(start,stop,500); printf( " Reals in [0,1] " ); start = clock(); for( i = 0; i < 500000000UL; ++i ) junkf += mtrand3.rand(); stop = clock(); showrate(start,stop,500); printf( " Reals in [0,7] " ); start = clock(); for( i = 0; i < 500000000UL; ++i ) junkf += mtrand3.rand(7.0); stop = clock(); showrate(start,stop,500); printf( " Reals in normal distribution" ); start = clock(); for( i = 0; i < 100000000UL; ++i ) junkf += mtrand3.randNorm(7.0,2.0); stop = clock(); showrate(start,stop,100); if( junki == 0 ) printf("jinx\n"); if( junkf == 0.0 ) printf("jinx\n"); } printf( "\nTests of functionality:\n" ); // Array save/load test bool saveArrayFailure = false; MTRand mtrand4a, mtrand4b; MTRand::uint32 saveArray[ MTRand::SAVE ]; mtrand4a.save( saveArray ); mtrand4b.load( saveArray ); for( i = 0; i < 2000UL; ++i ) if( mtrand4b.randInt() != mtrand4a.randInt() ) saveArrayFailure = true; if( saveArrayFailure ) printf( "Error - Failed array save/load test\n" ); else printf( "Passed array save/load test\n" ); // Stream save/load test bool saveStreamFailure = false; std::ofstream dataOut( "state.dat" ); if( dataOut ) { dataOut << mtrand4a; // comment out if compiler does not support dataOut.close(); } std::ifstream dataIn( "state.dat" ); if( dataIn ) { dataIn >> mtrand4b; // comment out if compiler does not support dataIn.close(); } for( i = 0; i < 2000UL; ++i ) if( mtrand4b.randInt() != mtrand4a.randInt() ) saveStreamFailure = true; if( saveStreamFailure ) printf( "Error - Failed stream save/load test\n" ); else printf( "Passed stream save/load test\n" ); // Copy constructor test bool copyConstructorFailure = false; MTRand mtrand4c( mtrand4a ); for( i = 0; i < 2000UL; ++i ) if( mtrand4c.randInt() != mtrand4a.randInt() ) copyConstructorFailure = true; if( copyConstructorFailure ) printf( "Error - Failed copy constuctor test\n" ); else printf( "Passed copy constructor test\n" ); // Copy operator test bool copyOperatorFailure = false; MTRand mtrand4d; mtrand4d = mtrand4a; for( i = 0; i < 2000UL; ++i ) if( mtrand4d.randInt() != mtrand4a.randInt() ) copyOperatorFailure = true; if( copyOperatorFailure ) printf( "Error - Failed copy operator test\n" ); else printf( "Passed copy operator test\n" ); // Integer range test MTRand mtrand5; bool integerRangeFailure = false; unsigned long integerRangeCount[18]; for( i = 0; i < 18UL; ++i ) integerRangeCount[i] = 0; for( i = 0; i < 180000UL; ++i ) { int r = mtrand5.randInt(17); if( r < 0 || r > 17 ) integerRangeFailure = true; else ++integerRangeCount[ mtrand5.randInt(17) ]; } for( i = 0; i < 18UL; ++i ) if( integerRangeCount[i] < 5000 || integerRangeCount[i] > 15000 ) integerRangeFailure = true; if( integerRangeFailure ) printf( "Error - Failed integer range test\n" ); else printf( "Passed integer range test\n" ); // Float range test MTRand mtrand6; bool floatRangeFailure = false; unsigned long floatRangeLo = 0; unsigned long floatRangeHi = 0; for( i = 0; i < 100000UL; ++i ) { double r = mtrand6(); if( r < 0.0 || r > 1.0 ) floatRangeFailure = true; if( r < 0.1 ) ++floatRangeLo; if( r > 0.9 ) ++floatRangeHi; } if( floatRangeLo < 5000 || floatRangeLo > 15000 ) floatRangeFailure = true; if( floatRangeHi < 5000 || floatRangeHi > 15000 ) floatRangeFailure = true; floatRangeLo = 0; floatRangeHi = 0; for( i = 0; i < 100000UL; ++i ) { double r = mtrand6.rand(); if( r < 0.0 || r > 1.0 ) floatRangeFailure = true; if( r < 0.1 ) ++floatRangeLo; if( r > 0.9 ) ++floatRangeHi; } if( floatRangeLo < 5000 || floatRangeLo > 15000 ) floatRangeFailure = true; if( floatRangeHi < 5000 || floatRangeHi > 15000 ) floatRangeFailure = true; floatRangeLo = 0; floatRangeHi = 0; for( i = 0; i < 100000UL; ++i ) { double r = mtrand6.rand(0.3183); if( r < 0.0 || r > 0.3183 ) floatRangeFailure = true; if( r < 0.03183 ) ++floatRangeLo; if( r > 0.28647 ) ++floatRangeHi; } floatRangeFailure |= !floatRangeLo; floatRangeFailure |= !floatRangeHi; floatRangeLo = false; floatRangeHi = false; for( i = 0; i < 100000UL; ++i ) { double r = mtrand6.randExc(); if( r < 0.0 || r >= 1.0 ) floatRangeFailure = true; if( r < 0.1 ) ++floatRangeLo; if( r > 0.9 ) ++floatRangeHi; } if( floatRangeLo < 5000 || floatRangeLo > 15000 ) floatRangeFailure = true; if( floatRangeHi < 5000 || floatRangeHi > 15000 ) floatRangeFailure = true; floatRangeLo = 0; floatRangeHi = 0; for( i = 0; i < 100000UL; ++i ) { double r = mtrand6.randExc(0.3183); if( r < 0.0 || r >= 0.3183 ) floatRangeFailure = true; if( r < 0.03183 ) ++floatRangeLo; if( r > 0.28647 ) ++floatRangeHi; } if( floatRangeLo < 5000 || floatRangeLo > 15000 ) floatRangeFailure = true; if( floatRangeHi < 5000 || floatRangeHi > 15000 ) floatRangeFailure = true; floatRangeLo = 0; floatRangeHi = 0; for( i = 0; i < 100000UL; ++i ) { double r = mtrand6.randDblExc(); if( r <= 0.0 || r >= 1.0 ) floatRangeFailure = true; if( r < 0.1 ) ++floatRangeLo; if( r > 0.9 ) ++floatRangeHi; } if( floatRangeLo < 5000 || floatRangeLo > 15000 ) floatRangeFailure = true; if( floatRangeHi < 5000 || floatRangeHi > 15000 ) floatRangeFailure = true; floatRangeLo = 0; floatRangeHi = 0; for( i = 0; i < 100000UL; ++i ) { double r = mtrand6.randDblExc(0.3183); if( r <= 0.0 || r >= 0.3183 ) floatRangeFailure = true; if( r < 0.03183 ) ++floatRangeLo; if( r > 0.28647 ) ++floatRangeHi; } if( floatRangeLo < 5000 || floatRangeLo > 15000 ) floatRangeFailure = true; if( floatRangeHi < 5000 || floatRangeHi > 15000 ) floatRangeFailure = true; if( floatRangeFailure ) printf( "Error - Failed float range test\n" ); else printf( "Passed float range test\n" ); // Gaussian distribution test MTRand mtrand7; bool gaussianFailure = false; const double mean = 100.0; const double stddev = 50.0; long gaussianExpect[] = { 0, 0, 0, 0, 0, 0, 0, 31, 1318, 21400, 135905, 341344, 341344, 135905, 21400, 1318, 31, 0, 0, 0, 0, 0, 0, 0 }; long gaussian[24]; for( i = 0; i < 24; ++i ) gaussian[i] = 0; for( i = 0; i < 1000000UL; ++i ) { double r = mtrand7.randNorm( mean, stddev ); long bin = 12 + long( floor( ( r - mean ) / stddev ) ); if( bin < 0 || bin > 23 ) gaussianFailure = true; else ++gaussian[bin]; } for( i = 0; i < 24UL; ++i ) { if( gaussian[i] - 2 * gaussianExpect[i] > 5 ) gaussianFailure = true; if( gaussianExpect[i] / 2 - gaussian[i] > 5 ) gaussianFailure = true; } if( gaussianFailure ) printf( "Error - Failed Gaussian distribution test\n" ); else printf( "Passed Gaussian distribution test\n" ); // Auto-seed uniqueness test MTRand mtrand8a, mtrand8b, mtrand8c; unsigned long r8a = mtrand8a.randInt(); unsigned long r8b = mtrand8b.randInt(); unsigned long r8c = mtrand8c.randInt(); if( r8a == r8b || r8a == r8c || r8b == r8c ) printf( "Error - Failed auto-seed uniqueness test\n" ); else printf( "Passed auto-seed uniqueness test\n" ); return 0; } void showrate( clock_t start, clock_t stop, int reps ) { double time = double( stop - start ) / CLOCKS_PER_SEC; double rate = reps / time; printf( " %6.1f million per second\n", rate ); } april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Yang/000077500000000000000000000000001263004425400246565ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Yang/Yang.cpp000066400000000000000000000032201263004425400262550ustar00rootroot00000000000000// Yang.cpp // Test output and speed of Yang's Mersenne Twister class // Richard J. Wagner 28 Sep 2009 // This is free, unrestricted software void of any warranty. #include #include #include "mtrnd.h" using namespace MT; int main ( int argc, char * const argv[] ) { printf( "Testing output and speed of Yang's Mersenne Twister class\n" ); printf( "\nTest of random integer generation:\n" ); unsigned long oneSeed = 4357UL; unsigned long bigSeed[4] = { 0x123UL, 0x234UL, 0x345UL, 0x456UL }; printf( "\nTest of random integer generation:\n" ); MersenneTwist mtrand1; mtrand1.init_by_array( bigSeed, 4 ); unsigned long i; for( i = 0; i < 1000UL; ++i ) { printf( "%10lu ", mtrand1.genrand_int32() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1) generation:\n" ); for( i = 0; i < 1000UL; ++i ) { printf( "%10.8f ", mtrand1.genrand_real2() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of random real number [0,1] generation:\n" ); mtrand1.init_genrand( oneSeed ); for( i = 0; i < 2000UL; ++i ) { printf( "%10.8f ", mtrand1.genrand_real1() ); if( i % 5 == 4 ) printf("\n"); } printf( "\nTest of time to generate one billion random integers:\n" ); MersenneTwist mtrand2; mtrand2.init_genrand( oneSeed ); unsigned long junk = 0; clock_t start = clock(); for( i = 0; i < 1000000000UL; ++i ) { junk ^= mtrand2.genrand_int32(); } clock_t stop = clock(); if( junk == 0 ) printf( "jinx\n" ); printf( "Time elapsed = " ); printf( "%8.3f", double( stop - start ) / CLOCKS_PER_SEC ); printf( " s\n" ); return 0; } april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Test/Yang/mtrnd.h000066400000000000000000000153541263004425400261630ustar00rootroot00000000000000/* A C-program for MT19937, with initialization improved 2002/1/26. Coded by Takuji Nishimura and Makoto Matsumoto. Before using, initialize the state by using init_genrand(seed) or init_by_array(init_key, key_length). Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura, All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. The names of its contributors may not be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Any feedback is very welcome. http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html email: m-mat @ math.sci.hiroshima-u.ac.jp (remove space) Reference: M. Matsumoto and T. Nishimura, "Mersenne Twister: A 623-Dimensionally Equidistributed Uniform Pseudo-Random Number Generator", ACM Transactions on Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3--30. */ // C++ wrapped up by Changjiang Yang, more important: make it thread-safe. #ifndef _MT_RND_H_ #define _MT_RND_H_ namespace MT { /* Period parameters */ const int N = 624; const int M = 397; const unsigned long MATRIX_A = 0x9908b0dfUL; /* constant vector a */ const unsigned long UPPER_MASK = 0x80000000UL; /* most significant w-r bits */ const unsigned long LOWER_MASK = 0x7fffffffUL; /* least significant r bits */ class MersenneTwist { unsigned long mt[N]; /* the array for the state vector */ int mti; /* mti==N+1 means mt[N] is not initialized */ public: MersenneTwist() : mti(N+1) {} /* initializes mt[N] with a seed */ // Note: Initializing TWISTER to the scalar integer state 0 actually // corresponds to the C call init_genrand(5489). void init_genrand(unsigned long s) { mt[0]= s & 0xffffffffUL; for (mti=1; mti> 30)) + mti); /* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */ /* In the previous versions, MSBs of the seed affect */ /* only MSBs of the array mt[]. */ /* 2002/01/09 modified by Makoto Matsumoto */ mt[mti] &= 0xffffffffUL; /* for >32 bit machines */ } } /* initialize by an array with array-length */ /* init_key is the array for initializing keys */ /* key_length is its length */ /* slight change for C++, 2004/2/26 */ void init_by_array(unsigned long init_key[], int key_length) { int i, j, k; init_genrand(19650218UL); i=1; j=0; k = (N>key_length ? N : key_length); for (; k; k--) { mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1664525UL)) + init_key[j] + j; /* non linear */ mt[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */ i++; j++; if (i>=N) { mt[0] = mt[N-1]; i=1; } if (j>=key_length) j=0; } for (k=N-1; k; k--) { mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1566083941UL)) - i; /* non linear */ mt[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */ i++; if (i>=N) { mt[0] = mt[N-1]; i=1; } } mt[0] = 0x80000000UL; /* MSB is 1; assuring non-zero initial array */ } /* generates a random number on [0,0xffffffff]-interval */ unsigned long genrand_int32(void) { unsigned long y; static unsigned long mag01[2]={0x0UL, MATRIX_A}; /* mag01[x] = x * MATRIX_A for x=0,1 */ if (mti >= N) { /* generate N words at one time */ int kk; if (mti == N+1) /* if init_genrand() has not been called, */ init_genrand(5489UL); /* a default initial seed is used */ for (kk=0;kk> 1) ^ mag01[y & 0x1UL]; } for (;kk> 1) ^ mag01[y & 0x1UL]; } y = (mt[N-1]&UPPER_MASK)|(mt[0]&LOWER_MASK); mt[N-1] = mt[M-1] ^ (y >> 1) ^ mag01[y & 0x1UL]; mti = 0; } y = mt[mti++]; /* Tempering */ y ^= (y >> 11); y ^= (y << 7) & 0x9d2c5680UL; y ^= (y << 15) & 0xefc60000UL; y ^= (y >> 18); return y; } /* generates a random number on [0,0x7fffffff]-interval */ long genrand_int31(void) { return (long)(genrand_int32()>>1); } /* generates a random number on [0,1]-real-interval */ double genrand_real1(void) { return genrand_int32()*(1.0/4294967295.0); /* divided by 2^32-1 */ } /* generates a random number on [0,1)-real-interval */ double genrand_real2(void) { return genrand_int32()*(1.0/4294967296.0); /* divided by 2^32 */ } /* generates a random number on (0,1)-real-interval */ double genrand_real3(void) { return (((double)genrand_int32()) + 0.5)*(1.0/4294967296.0); /* divided by 2^32 */ } /* generates a random number on [0,1) with 53-bit resolution*/ double genrand_res53(void) { unsigned long a=genrand_int32()>>5, b=genrand_int32()>>6; return(a*67108864.0+b)*(1.0/9007199254740992.0); } }; } #endif april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/example.cpp000066400000000000000000000153311263004425400252030ustar00rootroot00000000000000// example.cpp // Examples of random number generation with MersenneTwister.h // Richard J. Wagner 27 September 2009 #include #include #include "MersenneTwister.h" using namespace std; int main( int argc, char * const argv[] ) { // A Mersenne Twister random number generator // can be declared with a simple MTRand mtrand1; // and used with double a = mtrand1(); // or double b = mtrand1.rand(); cout << "Two real numbers in the range [0,1]: "; cout << a << ", " << b << endl; // Those calls produced the default of floating-point numbers // in the range 0 to 1, inclusive. We can also get integers // in the range 0 to 2^32 - 1 (4294967295) with unsigned long c = mtrand1.randInt(); cout << "An integer in the range [0," << 0xffffffffUL; cout << "]: " << c << endl; // Or get an integer in the range 0 to n (for n < 2^32) with int d = mtrand1.randInt( 42 ); cout << "An integer in the range [0,42]: " << d << endl; // We can get a real number in the range 0 to 1, excluding // 1, with double e = mtrand1.randExc(); cout << "A real number in the range [0,1): " << e << endl; // We can get a real number in the range 0 to 1, excluding // both 0 and 1, with double f = mtrand1.randDblExc(); cout << "A real number in the range (0,1): " << f << endl; // The functions rand(), randExc(), and randDblExc() can // also have ranges defined just like randInt() double g = mtrand1.rand( 2.5 ); double h = mtrand1.randExc( 10.0 ); double i = 12.0 + mtrand1.randDblExc( 8.0 ); cout << "A real number in the range [0,2.5]: " << g << endl; cout << "One in the range [0,10.0): " << h << endl; cout << "And one in the range (12.0,20.0): " << i << endl; // The distribution of numbers over each range is uniform, // but it can be transformed to other useful distributions. // One common transformation is included for drawing numbers // in a normal (Gaussian) distribution cout << "A few grades from a class with a 52 pt average "; cout << "and a 9 pt standard deviation:" << endl; for( int student = 0; student < 20; ++student ) { double j = mtrand1.randNorm( 52.0, 9.0 ); cout << ' ' << int(j); } cout << endl; // Random number generators need a seed value to start // producing a sequence of random numbers. We gave no seed // in our declaration of mtrand1, so one was automatically // generated from the system clock (or the operating system's // random number pool if available). Alternatively we could // provide our own seed. Each seed uniquely determines the // sequence of numbers that will be produced. We can // replicate a sequence by starting another generator with // the same seed. MTRand mtrand2a( 1973 ); // makes new MTRand with given seed double k1 = mtrand2a(); // gets the first number generated MTRand mtrand2b( 1973 ); // makes an identical MTRand double k2 = mtrand2b(); // and gets the same number cout << "These two numbers are the same: "; cout << k1 << ", " << k2 << endl; // We can also restart an existing MTRand with a new seed mtrand2a.seed( 1776 ); mtrand2b.seed( 1941 ); double l1 = mtrand2a(); double l2 = mtrand2b(); cout << "Re-seeding gives different numbers: "; cout << l1 << ", " << l2 << endl; // But there are only 2^32 possible seeds when we pass a // single 32-bit integer. Since the seed dictates the // sequence, only 2^32 different random number sequences will // result. For applications like Monte Carlo simulation we // might want many more. We can seed with an array of values // rather than a single integer to access the full 2^19937-1 // possible sequences. MTRand::uint32 seed[ MTRand::N ]; for( int n = 0; n < MTRand::N; ++n ) seed[n] = 23 * n; // fill with anything MTRand mtrand3( seed ); double m1 = mtrand3(); double m2 = mtrand3(); double m3 = mtrand3(); cout << "We seeded this sequence with 19968 bits: "; cout << m1 << ", " << m2 << ", " << m3 << endl; // Again we will have the same sequence every time we run the // program. Make the array with something that will change // to get unique sequences. On a Linux system, the default // auto-initialization routine takes a unique sequence from // /dev/urandom. // For cryptography, also remember to hash the generated // random numbers. Otherwise the internal state of the // generator can be learned after reading 624 values. // We might want to save the state of the generator at an // arbitrary point after seeding so a sequence could be // replicated. An MTRand object can be saved into an array // or to a stream. MTRand mtrand4; // The array must be of type uint32 and length SAVE. MTRand::uint32 randState[ MTRand::SAVE ]; mtrand4.save( randState ); // A stream is convenient for saving to a file. ofstream stateOut( "state.dat" ); if( stateOut ) { stateOut << mtrand4; stateOut.close(); } unsigned long n1 = mtrand4.randInt(); unsigned long n2 = mtrand4.randInt(); unsigned long n3 = mtrand4.randInt(); cout << "A random sequence: " << n1 << ", " << n2 << ", " << n3 << endl; // And loading the saved state is as simple as mtrand4.load( randState ); unsigned long o4 = mtrand4.randInt(); unsigned long o5 = mtrand4.randInt(); unsigned long o6 = mtrand4.randInt(); cout << "Restored from an array: " << o4 << ", " << o5 << ", " << o6 << endl; ifstream stateIn( "state.dat" ); if( stateIn ) { stateIn >> mtrand4; stateIn.close(); } unsigned long p7 = mtrand4.randInt(); unsigned long p8 = mtrand4.randInt(); unsigned long p9 = mtrand4.randInt(); cout << "Restored from a stream: " << p7 << ", " << p8 << ", " << p9 << endl; // We can also duplicate a generator by copying MTRand mtrand5( mtrand3 ); // copy upon construction double q1 = mtrand3(); double q2 = mtrand5(); cout << "These two numbers are the same: "; cout << q1 << ", " << q2 << endl; mtrand5 = mtrand4; // copy by assignment double r1 = mtrand4(); double r2 = mtrand5(); cout << "These two numbers are the same: "; cout << r1 << ", " << r2 << endl; // In summary, the recommended common usage is MTRand mtrand6; // automatically generate seed double s = mtrand6(); // real number in [0,1] double t = mtrand6.randExc(0.5); // real number in [0,0.5) unsigned long u = mtrand6.randInt(10); // integer in [0,10] // with the << and >> operators used for saving to and // loading from streams if needed. cout << "Your lucky number for today is " << s + t * u << endl; return 0; } april-ann-0.4.1/packages/basics/random/c_src/MersenneTwister.cc000066400000000000000000000167271263004425400244520ustar00rootroot00000000000000#include "buffer_list.h" #include "MersenneTwister.h" namespace Basics { const unsigned int MTRand::N; const unsigned int MTRand::SAVE; MTRand::MTRand(const uint32_t& oneSeed) { seed(oneSeed); } MTRand::MTRand(uint32_t *const bigSeed, const uint32_t seedLength) { seed(bigSeed,seedLength); } MTRand::MTRand() { seed(); } MTRand::MTRand(const MTRand& r) : Serializable() { register uint32_t *s = state; const register uint32_t *t = r.state; register int i = N; for( ; i--; *s++ = *t++ ) {} left = r.left; pNext = &state[N-left]; } MTRand& MTRand::operator=(const MTRand& r) { if (this != &r) { register uint32_t *s = state; const register uint32_t *t = r.state; register int i = N; for( ; i--; *s++ = *t++ ) {} left = r.left; pNext = &state[N-left]; } return (*this); } double MTRand::rand() { return double(randInt()) * (1.0/4294967295.0); } double MTRand::rand( const double& n) { return rand() * n; } double MTRand::randExc() { return double(randInt()) * (1.0/4294967296.0); } double MTRand::randExc(const double& n) { return randExc() * n; } double MTRand::randDblExc() { return ( double(randInt()) + 0.5 ) * (1.0/4294967296.0); } double MTRand::randDblExc(const double& n) { return randDblExc() * n; } double MTRand::rand53() { uint32_t a = randInt() >> 5, b = randInt() >> 6; return ( a * 67108864.0 + b ) * (1.0/9007199254740992.0); // by Isaku Wada } double MTRand::randNorm(const double& mean, const double& variance) { // Return a real number from a normal (Gaussian) distribution with given // mean and variance by Box-Muller method double r = sqrt( -2.0 * log( 1.0-randDblExc()) ) * variance; double phi = 2.0 * 3.14159265358979323846264338328 * randExc(); return mean + r * cos(phi); } uint32_t MTRand::randInt() { // Pull a 32-bit integer from the generator state // Every other access function simply transforms the numbers extracted here if( left == 0 ) reload(); --left; register uint32_t s1; s1 = *pNext++; s1 ^= (s1 >> 11); s1 ^= (s1 << 7) & 0x9d2c5680UL; s1 ^= (s1 << 15) & 0xefc60000UL; return ( s1 ^ (s1 >> 18) ); } uint32_t MTRand::randInt(const uint32_t& n) { // Find which bits are used in n uint32_t used = n; used |= used >> 1; used |= used >> 2; used |= used >> 4; used |= used >> 8; used |= used >> 16; // Draw numbers until one is found in [0,n] uint32_t i; do i = randInt() & used; // toss unused bits to shorten search while( i > n ); return i; } void MTRand::seed( const uint32_t oneSeed ) { // Seed the generator with a simple uint32 initialize(oneSeed); reload(); } void MTRand::seed( uint32_t *const bigSeed, const uint32_t seedLength ) { // Seed the generator with an array of uint32's // There are 2^19937-1 possible initial states. This function allows // all of those to be accessed by providing at least 19937 bits (with a // default seed length of N = 624 uint32's). Any bits above the lower 32 // in each element are discarded. // Just call seed() if you want to get array from /dev/urandom initialize(19650218UL); register unsigned int i = 1; register uint32_t j = 0; register int k = ( N > seedLength ? N : seedLength ); for( ; k; --k ) { state[i] = state[i] ^ ( (state[i-1] ^ (state[i-1] >> 30)) * 1664525UL ); state[i] += ( bigSeed[j] & 0xffffffffUL ) + j; state[i] &= 0xffffffffUL; ++i; ++j; if( i >= N ) { state[0] = state[N-1]; i = 1; } if( j >= seedLength ) j = 0; } for( k = N - 1; k; --k ) { state[i] = state[i] ^ ( (state[i-1] ^ (state[i-1] >> 30)) * 1566083941UL ); state[i] -= i; state[i] &= 0xffffffffUL; ++i; if( i >= N ) { state[0] = state[N-1]; i = 1; } } state[0] = 0x80000000UL; // MSB is 1, assuring non-zero initial array reload(); } void MTRand::seed() { // Seed the generator with an array from /dev/urandom if available // Otherwise use a hash of time() and clock() values // First try getting an array from /dev/urandom FILE* urandom = fopen( "/dev/urandom", "rb" ); if( urandom ) { uint32_t bigSeed[N]; register uint32_t *s = bigSeed; register int i = N; register bool success = true; while( success && i-- ) success = fread( s++, sizeof(uint32_t), 1, urandom ); fclose(urandom); if( success ) { seed( bigSeed, N ); return; } } // Was not successful, so use time() and clock() instead seed( hash( time(NULL), clock() ) ); } void MTRand::initialize( const uint32_t seed ) { // Initialize generator state with seed // See Knuth TAOCP Vol 2, 3rd Ed, p.106 for multiplier. // In previous versions, most significant bits (MSBs) of the seed affect // only MSBs of the state array. Modified 9 Jan 2002 by Makoto Matsumoto. register uint32_t *s = state; register uint32_t *r = state; register unsigned int i = 1; *s++ = seed & 0xffffffffUL; for( ; i < N; ++i ) { *s++ = ( 1812433253UL * ( *r ^ (*r >> 30) ) + i ) & 0xffffffffUL; r++; } } void MTRand::reload() { // Generate N new values in state // Made clearer and faster by Matthew Bellew (matthew.bellew@home.com) static const int MmN = int(M) - int(N); // in case enums are unsigned register uint32_t *p = state; register int i; for( i = N - M; i--; ++p ) *p = twist( p[M], p[0], p[1] ); for( i = M; --i; ++p ) *p = twist( p[MmN], p[0], p[1] ); *p = twist( p[MmN], p[0], state[0] ); left = N, pNext = state; } uint32_t MTRand::hash( time_t t, clock_t c ) { // Get a uint32 from t and c // Better than uint32(x) in case x is floating point in [0,1] // Based on code by Lawrence Kirby (fred@genesis.demon.co.uk) static uint32_t differ = 0; // guarantee time-based seeds will change uint32_t h1 = 0; unsigned char *p = (unsigned char *) &t; for( size_t i = 0; i < sizeof(t); ++i ) { h1 *= UCHAR_MAX + 2U; h1 += p[i]; } uint32_t h2 = 0; p = (unsigned char *) &c; for( size_t j = 0; j < sizeof(c); ++j ) { h2 *= UCHAR_MAX + 2U; h2 += p[j]; } return ( h1 + differ++ ) ^ h2; } void MTRand::shuffle(int size, int *vector) { for (int i=0; i < size; i++) vector[i] = i; for (int i = size-1; i > 0; i--) { int j = randInt(i); int swap = vector[i]; vector[i] = vector[j]; vector[j] = swap; } } void MTRand::save( uint32_t* saveArray ) const { register uint32_t *sa = saveArray; register const uint32_t *s = state; register int i = N; for( ; i--; *sa++ = *s++ ) {} *sa = left; } void MTRand::load( uint32_t *const loadArray ) { register uint32_t *s = state; register uint32_t *la = loadArray; register int i = N; for( ; i--; *s++ = *la++ ) {} left = *la; pNext = &state[N-left]; } const char *MTRand::luaCtorName() const { return "random():fromTable"; } int MTRand::exportParamsToLua(lua_State *L) { uint32_t randState[ SAVE ]; save( randState ); AprilUtils::LuaTable table(L); for (unsigned int i=0; i #include #include #include #include #include "lua_table.h" #include "serializable.h" namespace Basics { class MTRand : public AprilIO::Serializable { // Data public: static const unsigned int N = 624; // length of state vector static const unsigned int SAVE = N+1; // length of array for save() protected: enum { M = 397 }; // period parameter uint32_t state[N]; // internal state uint32_t *pNext; // next value to get from state int left; // number of values left before reload needed //Methods public: MTRand( const uint32_t& oneSeed ); // initialize with a simple uint32 MTRand( uint32_t *const bigSeed, uint32_t const seedLength = N ); // or an array MTRand(); // auto-initialize with /dev/urandom or time() and clock() // two new methods MTRand& operator=(const MTRand&); MTRand(const MTRand& r); // Do NOT use for CRYPTOGRAPHY without securely hashing several returned // values together, otherwise the generator state can be learned after // reading 624 consecutive values. // Access to 32-bit random numbers double rand(); // real number in [0,1] double rand( const double& n ); // real number in [0,n] double randExc(); // real number in [0,1) double randExc( const double& n ); // real number in [0,n) double randDblExc(); // real number in (0,1) double randDblExc( const double& n ); // real number in (0,n) uint32_t randInt(); // integer in [0,2^32-1] uint32_t randInt( const uint32_t& n ); // integer in [0,n] for n < 2^32 double operator()() { return rand(); } // same as rand() // Access to 53-bit random numbers (capacity of IEEE double precision) double rand53(); // real number in [0,1) // Access to nonuniform random number distributions double randNorm( const double& mean = 0.0, const double& variance = 0.0 ); // Re-seeding functions with same behavior as initializers void seed( const uint32_t oneSeed ); void seed( uint32_t *const bigSeed, const uint32_t seedLength = N ); void seed(); // Saving and loading generator state void save( uint32_t* saveArray ) const; // to array of size SAVE void load( uint32_t *const loadArray ); // from such array // friend std::ostream& operator<<( std::ostream& os, const MTRand& mtrand ); // friend std::istream& operator>>( std::istream& is, MTRand& mtrand ); // void shuffle(int size, int *vector); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); protected: void initialize( const uint32_t oneSeed ); void reload(); uint32_t hiBit( const uint32_t& u ) const { return u & 0x80000000UL; } uint32_t loBit( const uint32_t& u ) const { return u & 0x00000001UL; } uint32_t loBits( const uint32_t& u ) const { return u & 0x7fffffffUL; } uint32_t mixBits( const uint32_t& u, const uint32_t& v ) const { return hiBit(u) | loBits(v); } uint32_t twist( const uint32_t& m, const uint32_t& s0, const uint32_t& s1 ) const { return m ^ (mixBits(s0,s1)>>1) ^ (-loBit(s1) & 0x9908b0dfUL); } static uint32_t hash( time_t t, clock_t c ); }; } // namespace Basics DECLARE_LUA_TABLE_BIND_SPECIALIZATION(Basics::MTRand); #endif // MERSENNETWISTER_H // Change log: // // v0.1 - First release on 15 May 2000 // - Based on code by Makoto Matsumoto, Takuji Nishimura, and Shawn Cokus // - Translated from C to C++ // - Made completely ANSI compliant // - Designed convenient interface for initialization, seeding, and // obtaining numbers in default or user-defined ranges // - Added automatic seeding from /dev/urandom or time() and clock() // - Provided functions for saving and loading generator state // // v0.2 - Fixed bug which reloaded generator one step too late // // v0.3 - Switched to clearer, faster reload() code from Matthew Bellew // // v0.4 - Removed trailing newline in saved generator format to be consistent // with output format of built-in types // // v0.5 - Improved portability by replacing static const int's with enum's and // clarifying return values in seed(); suggested by Eric Heimburg // - Removed MAXINT constant; use 0xffffffffUL instead // // v0.6 - Eliminated seed overflow when uint32 is larger than 32 bits // - Changed integer [0,n] generator to give better uniformity // // v0.7 - Fixed operator precedence ambiguity in reload() // - Added access for real numbers in (0,1) and (0,n) // // v0.8 - Included time.h header to properly support time_t and clock_t // // v1.0 - Revised seeding to match 26 Jan 2002 update of Nishimura and Matsumoto // - Allowed for seeding with arrays of any length // - Added access for real numbers in [0,1) with 53-bit resolution // - Added access for real numbers from normal (Gaussian) distributions // - Increased overall speed by optimizing twist() // - Doubled speed of integer [0,n] generation // - Fixed out-of-range number generation on 64-bit machines // - Improved portability by substituting literal constants for long enum's // - Changed license from GNU LGPL to BSD april-ann-0.4.1/packages/basics/random/c_src/dice.cc000066400000000000000000000030141263004425400222010ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "dice.h" namespace Basics { Dice::Dice(int outcom, double *prob) { outcomes = outcom; threshold = new double[outcomes]; double sum=0.0; for (int i=0; irand(); //real number in [0,1] int left=0,right=outcomes-1; while (left < right) { int middle = (left+right)/2; if (threshold[middle] <= key) left = middle+1; else right = middle; } return left; }; } // namespace Basics april-ann-0.4.1/packages/basics/random/c_src/dice.h000066400000000000000000000022471263004425400220520ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef DICE_H #define DICE_H #include "referenced.h" #include "MersenneTwister.h" namespace Basics { class Dice : public Referenced { int outcomes; double *threshold; public: Dice(int outcom, double *prob); ~Dice(); int getOutcomes() const { return outcomes; } int thrown(MTRand *generator); }; } // namespace Basics #endif // DICE_H april-ann-0.4.1/packages/basics/random/lua_src/000077500000000000000000000000001263004425400213275ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/random/lua_src/random.lua000066400000000000000000000113771263004425400233230ustar00rootroot00000000000000--------------------------- -- BINDING DOCUMENTATION -- --------------------------- april_set_doc(random, { class = "class", summary = "Pseudo-random numbers generator", }) april_set_doc(random, { class = "method", summary = "Constructor", description ={ "Constructor of random objects", }, params = { "A number with the initial seed", }, outputs = { "A random instantiated object" }, }) april_set_doc(random, { class = "method", summary = "Constructor", description ={ "Constructor of random objects", }, params = { "A table with numbers for initial seeds", }, outputs = { "A random instantiated object" }, }) april_set_doc(random, { class = "method", summary = "Constructor", description ={ "Constructor of random objects, the initial seed", "is taken from current time.", }, outputs = { "A random instantiated object" }, }) april_set_doc(random.."rand", { class = "method", summary = "Returns a double precision random number, interval [0,n]", params = { "The n number for the interval [optional]. By default is n=1.", }, outputs = { "A double precision random number" }, }) april_set_doc(random.."randExc", { class = "method", summary = "Returns a double precision random number, interval [0,n)", params = { "The n number for the interval [optional]. By default is n=1.", }, outputs = { "A double precision random number" }, }) april_set_doc(random.."randDblExc", { class = "method", summary = "Returns a double precision random number, interval (0,n)", params = { "The n number for the interval [optional]. By default is n=1.", }, outputs = { "A double precision random number" }, }) april_set_doc(random.."randInt", { class = "method", summary = "Returns an integer random number, interval [0,2^32-1]", outputs = { "An integer random number" }, }) april_set_doc(random.."randInt", { class = "method", summary = "Returns an integer random number, interval [0,x]", params = { "The x number for the interval.", }, outputs = { "An integer random number" }, }) april_set_doc(random.."randInt", { class = "method", summary = "Returns an integer random number, interval [x,y]", params = { "The x number for the interval.", "The y number for the interval.", }, outputs = { "An integer random number" }, }) april_set_doc(random.."shuffle", { class = "method", summary = "Returns a permutation of an array", params = { "A number with the size of the sequence", }, outputs = { "A table with the permutation" }, }) april_set_doc(random.."shuffle", { class = "method", summary = "Returns a random sort of an array", params = { "A table with the array for reordering", }, outputs = { "A table with the given array randomly reordered" }, }) april_set_doc(random.."choose", { class = "method", summary = "Returns a random position of a given array", params = { "A table with the array", }, outputs = { "A number which is a random position in the given array" }, }) april_set_doc(random.."randNorm", { class = "method", summary = "Returns a Gaussian random number", params = { "Mean of the Gaussian", "Variance of the Gaussian", }, outputs = { "A Gaussian random number" }, }) april_set_doc(random.."seed", { class = "method", summary = "Sets the current seed.", params = { "A number [optional]. By default is taken from current time.", }, }) april_set_doc(random.."seed", { class = "method", summary = "Sets the current seed.", params = { "A table with an array of seeds.", }, }) april_set_doc(random.."clone", { class = "method", summary = "Returns a deep-copy of the caller object", outputs = { "An instance of random." }, }) april_set_doc(random.."toTable", { class = "method", summary = "Serializes the random state to a table.", outputs = { "A table with the random state." }, }) april_set_doc(random.."fromTable", { class = "method", summary = "Loads the random state from a table.", params = { "A table with the random state" }, }) ------------------------------------------------------------------------------- april_set_doc(random.dice, { class = "class", summary = "A class for random dice parametrization", }) april_set_doc(random.dice, { class = "method", summary = "Constructor", params = { "A table with the positive score of each side of the dice", }, }) april_set_doc(random.dice.."outcomes", { class = "method", summary = "Returns the number of sides of the dice", outputs = { "The number of sides" }, }) april_set_doc(random.dice.."thrown", { class = "method", summary = "Throws the dice and returns the outcome", params = { "A random instance", }, outputs = { "The side of the dice (the outcome)" }, }) april-ann-0.4.1/packages/basics/random/package.lua000066400000000000000000000020551263004425400217770ustar00rootroot00000000000000 package{ name = "random", version = "1.0", depends = { "util", "aprilio" }, keywords = { "random" }, description = "Mersenne Twister random number generator", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_mtrand.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", --debug = "yes", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_mtrand.lua.cc", dest_dir = "build", }, }, target{ name = "document", document_src{}, document_bind{}, }, } april-ann-0.4.1/packages/basics/random/test/000077500000000000000000000000001263004425400206565ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/random/test/test_dice.lua000066400000000000000000000007051263004425400233260ustar00rootroot00000000000000tabladice = {0.4,0.2,0.1,0.1,0.1,0.1} dado = random.dice(tabladice) aleat = random() histogram = {} for i=1,dado:outcomes() do table.insert(histogram,0) end veces = 10000 for i=1,veces do resul = dado:thrown(aleat) --printf("%d,",resul) histogram[resul] = histogram[resul]+1 end print"---------------------------------------" for i=1,dado:outcomes() do printf("Histograma[%d] = %.3f should be %.3f\n", i,histogram[i]/veces,tabladice[i]) end april-ann-0.4.1/packages/basics/random/test/test_random.lua000066400000000000000000000014711263004425400237030ustar00rootroot00000000000000print("Empieza el programa") a = random() b = a:clone() for i=1,10 do print("randInt 1 a 10",a:randInt(1,10)) end print("-----------------------------") print("Debe salir la misma secuencia:") for i=1,10 do print("randInt 1 a 10",b:randInt(1,10)) end numpermutaciones = 10 tallapermutacion = 10 printf("Vamos a ver %d permutaciones de %d elementos\n", numpermutaciones, tallapermutacion) for i=1,numpermutaciones do print(string.join(a:shuffle(tallapermutacion),",")) end print("-----------------------------") print("VAMOS A PERMUTAR UNA TABLA") tabla = {"uno", "dos", "tres", "cuatro", "cinco", "seis", "siete", "ocho" } print("Tabla original : "..table.concat(tabla,",")) for i=1,numpermutaciones do print("Tabla permutada: "..table.concat(a:shuffle(tabla),",")) end print("Termina el programa") april-ann-0.4.1/packages/basics/stats/000077500000000000000000000000001263004425400175555ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/stats/binding/000077500000000000000000000000001263004425400211675ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/stats/binding/bind_stats.lua.cc000066400000000000000000000357131263004425400244210ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "bind_matrix.h" #include "bind_sparse_matrix.h" #include "bind_mtrand.h" //BIND_END //BIND_HEADER_H #include "beta_distribution.h" #include "binomial_distribution.h" #include "combinations.h" #include "exponential_distribution.h" #include "gamma_distribution.h" #include "statistical_distribution.h" #include "uniform_distribution.h" #include "normal_distribution.h" using namespace Stats; //BIND_END //BIND_FUNCTION stats.comb { unsigned int n, k; LUABIND_GET_PARAMETER(1, uint, n); LUABIND_GET_PARAMETER(2, uint, k); LUABIND_RETURN(uint, Combinations::get(static_cast(n), static_cast(k))); } //BIND_END //BIND_FUNCTION stats.log_comb { unsigned int n, k; LUABIND_GET_PARAMETER(1, uint, n); LUABIND_GET_PARAMETER(2, uint, k); LUABIND_RETURN(double, static_cast (Combinations::lget(static_cast(n), static_cast(k)))); } //BIND_END //BIND_FUNCTION stats.lgamma { double x; LUABIND_GET_PARAMETER(1, double, x); LUABIND_RETURN(double, lgamma(x)); } //BIND_END ////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME StatisticalDistributionBase stats.dist //BIND_CPP_CLASS StatisticalDistributionBase //BIND_LUACLASSNAME Serializable aprilio.serializable //BIND_SUBCLASS_OF StatisticalDistributionBase Serializable //BIND_CONSTRUCTOR StatisticalDistributionBase { LUABIND_ERROR("Abstract class"); } //BIND_END //BIND_METHOD StatisticalDistributionBase sample { MTRand *rng; MatrixFloat *dest; LUABIND_GET_PARAMETER(1, MTRand, rng); int result_pos = 2, N=-1; if (lua_isnumber(L,2)) { LUABIND_GET_PARAMETER(2, int, N); if (N < 1) LUABIND_ERROR("Expected > 0 number as 2nd argument\n"); result_pos++; } LUABIND_GET_OPTIONAL_PARAMETER(result_pos, MatrixFloat, dest, 0); if (N > 0) { if (dest == 0) { int dims[2] = { N, static_cast(obj->getSize()) }; dest = new MatrixFloat(2, dims); } else { if (N != dest->getDimSize(0)) LUABIND_FERROR2("Expected a matrix with %d rows, found %d rows\n", N, dest->getDimSize(0)); } } LUABIND_RETURN(MatrixFloat, obj->sample(rng, dest)); } //BIND_END //BIND_METHOD StatisticalDistributionBase logpdf { MatrixFloat *x, *dest; if (lua_isMatrixFloat(L,1)) { LUABIND_GET_PARAMETER(1, MatrixFloat, x); LUABIND_GET_OPTIONAL_PARAMETER(2, MatrixFloat, dest, 0); } else { float xf; LUABIND_CHECK_ARGN(==,1); LUABIND_GET_PARAMETER(1, float, xf); dest = 0; int dims[2] = {1,1}; x = new MatrixFloat(2, dims); (*x)(0,0) = xf; } IncRef(x); LUABIND_RETURN(MatrixFloat, obj->logpdf(x, dest)); DecRef(x); } //BIND_END //BIND_METHOD StatisticalDistributionBase logcdf { MatrixFloat *x, *dest; if (lua_isMatrixFloat(L,1)) { LUABIND_GET_PARAMETER(1, MatrixFloat, x); LUABIND_GET_OPTIONAL_PARAMETER(2, MatrixFloat, dest, 0); } else { float xf; LUABIND_CHECK_ARGN(==,1); LUABIND_GET_PARAMETER(1, float, xf); dest = 0; int dims[2] = {1,1}; x = new MatrixFloat(2, dims); (*x)(0,0) = xf; } IncRef(x); LUABIND_RETURN(MatrixFloat, obj->logcdf(x, dest)); DecRef(x); } //BIND_END //BIND_METHOD StatisticalDistributionBase logpdf_derivative { MatrixFloat *x, *grads; if (lua_isMatrixFloat(L,1)) { LUABIND_GET_PARAMETER(1, MatrixFloat, x); LUABIND_GET_OPTIONAL_PARAMETER(2, MatrixFloat, grads, 0); } else { float xf; LUABIND_CHECK_ARGN(==,1); LUABIND_GET_PARAMETER(1, float, xf); grads = 0; int dims[2] = {1,1}; x = new MatrixFloat(2, dims); (*x)(0,0) = xf; } IncRef(x); LUABIND_RETURN(MatrixFloat, obj->logpdfDerivative(x, grads)); DecRef(x); } //BIND_END //BIND_METHOD StatisticalDistributionBase clone { LUABIND_RETURN(StatisticalDistributionBase, obj->clone()); } //BIND_END //BIND_METHOD StatisticalDistributionBase size { LUABIND_RETURN(uint, obj->getSize()); } //BIND_END ////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME UniformDistribution stats.dist.uniform //BIND_CPP_CLASS UniformDistribution //BIND_SUBCLASS_OF UniformDistribution StatisticalDistributionBase //BIND_CONSTRUCTOR UniformDistribution { MatrixFloat *low, *high; if (lua_isMatrixFloat(L,1)) { LUABIND_GET_PARAMETER(1, MatrixFloat, low); LUABIND_GET_PARAMETER(2, MatrixFloat, high); } else { float lowf, highf; LUABIND_GET_PARAMETER(1, float, lowf); LUABIND_GET_PARAMETER(2, float, highf); int dims[1] = { 1 }; low = new MatrixFloat(1, dims); high = new MatrixFloat(1, dims); (*low)(0) = lowf; (*high)(0) = highf; } obj = new UniformDistribution(low, high); LUABIND_RETURN(UniformDistribution, obj); } //BIND_END //BIND_METHOD UniformDistribution clone { LUABIND_RETURN(UniformDistribution, static_cast(obj->clone())); } //BIND_END ////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME GeneralNormalDistribution stats.dist.normal.general //BIND_CPP_CLASS GeneralNormalDistribution //BIND_SUBCLASS_OF GeneralNormalDistribution StatisticalDistributionBase //BIND_LUACLASSNAME DiagonalNormalDistribution stats.dist.normal.diagonal //BIND_CPP_CLASS DiagonalNormalDistribution //BIND_SUBCLASS_OF DiagonalNormalDistribution StatisticalDistributionBase //BIND_LUACLASSNAME StandardNormalDistribution stats.dist.normal.standard //BIND_CPP_CLASS StandardNormalDistribution //BIND_SUBCLASS_OF StandardNormalDistribution StatisticalDistributionBase //BIND_CONSTRUCTOR GeneralNormalDistribution { LUABIND_ERROR("Use stats.dist.normal constructor"); } //BIND_END //BIND_CONSTRUCTOR DiagonalNormalDistribution { LUABIND_ERROR("Use stats.dist.normal constructor"); } //BIND_END //BIND_CONSTRUCTOR StandardNormalDistribution { LUABIND_ERROR("Use stats.dist.normal constructor"); } //BIND_END //BIND_FUNCTION stats.dist.normal { int argn; argn = lua_gettop(L); // number of arguments if (argn == 0) { StandardNormalDistribution *obj = new StandardNormalDistribution(); LUABIND_RETURN(StandardNormalDistribution, obj); } else { MatrixFloat *mean; if (lua_isMatrixFloat(L,1)) { LUABIND_GET_PARAMETER(1, MatrixFloat, mean); if (lua_isMatrixFloat(L,2)) { MatrixFloat *cov; LUABIND_GET_PARAMETER(2, MatrixFloat, cov); GeneralNormalDistribution *obj = new GeneralNormalDistribution(mean, cov); LUABIND_RETURN(GeneralNormalDistribution, obj); } else { SparseMatrixFloat *cov; LUABIND_GET_PARAMETER(2, SparseMatrixFloat, cov); DiagonalNormalDistribution *obj = new DiagonalNormalDistribution(mean, cov); LUABIND_RETURN(DiagonalNormalDistribution, obj); } } else { SparseMatrixFloat *cov; float mu, sigma; LUABIND_GET_PARAMETER(1, float, mu); LUABIND_GET_PARAMETER(2, float, sigma); int dims[1] = { 1 }; mean = new MatrixFloat(1, dims); (*mean)(0) = mu; cov = SparseMatrixFloat::diag(1, sigma); DiagonalNormalDistribution *obj = new DiagonalNormalDistribution(mean, cov); LUABIND_RETURN(DiagonalNormalDistribution, obj); } } } //BIND_END //BIND_METHOD GeneralNormalDistribution clone { LUABIND_RETURN(GeneralNormalDistribution, static_cast(obj->clone())); } //BIND_END //BIND_METHOD DiagonalNormalDistribution clone { LUABIND_RETURN(DiagonalNormalDistribution, static_cast(obj->clone())); } //BIND_END //BIND_METHOD StandardNormalDistribution clone { LUABIND_RETURN(StandardNormalDistribution, static_cast(obj->clone())); } //BIND_END ////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME GeneralLogNormalDistribution stats.dist.lognormal.general //BIND_CPP_CLASS GeneralLogNormalDistribution //BIND_SUBCLASS_OF GeneralLogNormalDistribution StatisticalDistributionBase //BIND_LUACLASSNAME DiagonalLogNormalDistribution stats.dist.lognormal.diagonal //BIND_CPP_CLASS DiagonalLogNormalDistribution //BIND_SUBCLASS_OF DiagonalLogNormalDistribution StatisticalDistributionBase //BIND_CONSTRUCTOR GeneralNormalDistribution { LUABIND_ERROR("Use stats.dist.lognormal constructor"); } //BIND_END //BIND_CONSTRUCTOR DiagonalNormalDistribution { LUABIND_ERROR("Use stats.dist.lognormal constructor"); } //BIND_END //BIND_FUNCTION stats.dist.lognormal { MatrixFloat *mean, *location; if (lua_isMatrixFloat(L,1)) { LUABIND_GET_PARAMETER(1, MatrixFloat, mean); LUABIND_GET_OPTIONAL_PARAMETER(3, MatrixFloat, location, 0); if (lua_isMatrixFloat(L,2)) { MatrixFloat *cov; LUABIND_GET_PARAMETER(2, MatrixFloat, cov); GeneralLogNormalDistribution *obj = new GeneralLogNormalDistribution(mean, cov, location); LUABIND_RETURN(GeneralLogNormalDistribution, obj); } else { SparseMatrixFloat *cov; LUABIND_GET_PARAMETER(2, SparseMatrixFloat, cov); DiagonalLogNormalDistribution *obj = new DiagonalLogNormalDistribution(mean, cov, location); LUABIND_RETURN(DiagonalLogNormalDistribution, obj); } } else { SparseMatrixFloat *cov; float mu, sigma, loc; LUABIND_GET_PARAMETER(1, float, mu); LUABIND_GET_PARAMETER(2, float, sigma); LUABIND_GET_OPTIONAL_PARAMETER(3, float, loc, 0.0f); int dims[1] = { 1 }; mean = new MatrixFloat(1, dims); (*mean)(0) = mu; cov = SparseMatrixFloat::diag(1, sigma); if (loc != 0.0f) { location = new MatrixFloat(1, dims); (*location)(0) = loc; } else location = 0; DiagonalLogNormalDistribution *obj = new DiagonalLogNormalDistribution(mean, cov, location); LUABIND_RETURN(DiagonalLogNormalDistribution, obj); } } //BIND_END //BIND_METHOD GeneralLogNormalDistribution clone { LUABIND_RETURN(GeneralLogNormalDistribution, static_cast(obj->clone())); } //BIND_END //BIND_METHOD DiagonalLogNormalDistribution clone { LUABIND_RETURN(DiagonalLogNormalDistribution, static_cast(obj->clone())); } //BIND_END ////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME ExponentialDistribution stats.dist.exponential //BIND_CPP_CLASS ExponentialDistribution //BIND_SUBCLASS_OF ExponentialDistribution StatisticalDistributionBase //BIND_CONSTRUCTOR ExponentialDistribution { MatrixFloat *lambda; if (lua_isMatrixFloat(L,1)) { LUABIND_GET_PARAMETER(1, MatrixFloat, lambda); } else { float lambdaf; LUABIND_GET_PARAMETER(1, float, lambdaf); int dims[1] = {1}; lambda = new MatrixFloat(1, dims); AprilMath::MatrixExt::Initializers::matFill(lambda, lambdaf); } obj = new ExponentialDistribution(lambda); LUABIND_RETURN(ExponentialDistribution, obj); } //BIND_END //BIND_METHOD ExponentialDistribution clone { LUABIND_RETURN(ExponentialDistribution, static_cast(obj->clone())); } //BIND_END ////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME BetaDistribution stats.dist.beta //BIND_CPP_CLASS BetaDistribution //BIND_SUBCLASS_OF BetaDistribution StatisticalDistributionBase //BIND_CONSTRUCTOR BetaDistribution { MatrixFloat *alpha, *beta; if (lua_isMatrixFloat(L, 1)) { LUABIND_GET_PARAMETER(1, MatrixFloat, alpha); LUABIND_GET_PARAMETER(2, MatrixFloat, beta); } else { float alphaf, betaf; LUABIND_GET_PARAMETER(1, float, alphaf); LUABIND_GET_PARAMETER(2, float, betaf); int dims[1] = {1}; alpha = new MatrixFloat(1, dims); (*alpha)(0) = alphaf; beta = new MatrixFloat(1, dims); (*beta)(0) = betaf; } obj = new BetaDistribution(alpha, beta); LUABIND_RETURN(BetaDistribution, obj); } //BIND_END //BIND_METHOD BetaDistribution clone { LUABIND_RETURN(BetaDistribution, static_cast(obj->clone())); } //BIND_END ////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME GammaDistribution stats.dist.gamma //BIND_CPP_CLASS GammaDistribution //BIND_SUBCLASS_OF GammaDistribution StatisticalDistributionBase //BIND_CONSTRUCTOR GammaDistribution { MatrixFloat *alpha, *beta; if (lua_isMatrixFloat(L, 1)) { LUABIND_GET_PARAMETER(1, MatrixFloat, alpha); LUABIND_GET_PARAMETER(2, MatrixFloat, beta); } else { float alphaf, betaf; LUABIND_GET_PARAMETER(1, float, alphaf); LUABIND_GET_PARAMETER(2, float, betaf); int dims[1] = {1}; alpha = new MatrixFloat(1, dims); (*alpha)(0) = alphaf; beta = new MatrixFloat(1, dims); (*beta)(0) = betaf; } obj = new GammaDistribution(alpha, beta); LUABIND_RETURN(GammaDistribution, obj); } //BIND_END //BIND_METHOD GammaDistribution clone { LUABIND_RETURN(GammaDistribution, static_cast(obj->clone())); } //BIND_END ////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME BinomialDistribution stats.dist.binomial //BIND_CPP_CLASS BinomialDistribution //BIND_SUBCLASS_OF BinomialDistribution StatisticalDistributionBase //BIND_CONSTRUCTOR BinomialDistribution { MatrixFloat *n, *p; if (lua_isMatrixFloat(L, 1)) { LUABIND_GET_PARAMETER(1, MatrixFloat, n); LUABIND_GET_PARAMETER(2, MatrixFloat, p); } else { unsigned int ni; float pf; LUABIND_GET_PARAMETER(1, uint, ni); LUABIND_GET_PARAMETER(2, float, pf); int dims[1] = {1}; n = new MatrixFloat(1, dims); (*n)(0) = static_cast(ni); p = new MatrixFloat(1, dims); (*p)(0) = pf; } obj = new BinomialDistribution(n, p); LUABIND_RETURN(BinomialDistribution, obj); } //BIND_END //BIND_METHOD BinomialDistribution clone { LUABIND_RETURN(BinomialDistribution, static_cast(obj->clone())); } //BIND_END april-ann-0.4.1/packages/basics/stats/c_src/000077500000000000000000000000001263004425400206465ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/stats/c_src/beta_distribution.cc000066400000000000000000000073511263004425400246750ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include // #include // FIXME: this library needs c++11 extensions #include "buffer_list.h" #include "error_print.h" #include "beta_distribution.h" #include "gamma_variate.h" #include "utilMatrixFloat.h" using AprilUtils::buffer_list; using AprilUtils::log_float; using Basics::MatrixFloat; using Basics::MTRand; namespace Stats { BetaDistribution::BetaDistribution(MatrixFloat *alpha, MatrixFloat *beta) : StatisticalDistributionBase(1), alpha(alpha), beta(beta) { if (alpha->getNumDim() != 1 || beta->getNumDim() != 1 || alpha->getDimSize(0) != 1 || beta->getDimSize(0) != 1) ERROR_EXIT(128, "Expected alpha,beta one-dimensional matrices with size 1\n"); updateParams(); } BetaDistribution::~BetaDistribution() { } void BetaDistribution::updateParams() { alphaf = (*alpha)(0); betaf = (*beta)(0); if (!(alphaf > 0.0f) || !(betaf > 0.0f)) ERROR_EXIT(128, "Beta distribution needs > 0 alpha and beta params\n"); log_float gamma_a(lgamma(alphaf)); log_float gamma_b(lgamma(betaf)); log_float gamma_ab(lgamma(alphaf + betaf)); Bab = ( gamma_a * gamma_b / gamma_ab ); } void BetaDistribution::privateSample(MTRand *rng, MatrixFloat *result) { // generation via gamma variate for (MatrixFloat::iterator result_it(result->begin()); result_it != result->end(); ++result_it) { double y1 = gammaVariate(rng, 0.0f, 1.0f, alphaf); double y2 = gammaVariate(rng, 0.0f, 1.0f, betaf); *result_it = static_cast( y1 / (y1 + y2) ); } } void BetaDistribution::privateLogpdf(const MatrixFloat *x, MatrixFloat *result) { MatrixFloat::const_iterator x_it(x->begin()); MatrixFloat::iterator result_it(result->begin()); while(x_it != x->end()) { if (*x_it < 0.0f || *x_it > 1.0f) *result_it = log_float::zero().log(); else { log_float vx = log_float::from_float(*x_it).raise_to(alphaf - 1.0f); log_float v1x = log_float::from_float(1.0f - *x_it).raise_to(betaf - 1.0f); log_float r; if (vx <= log_float::zero() || v1x <= log_float::zero()) r = log_float::zero(); else r = vx * v1x / Bab; *result_it = r.log(); } ++x_it; ++result_it; } } void BetaDistribution::privateLogcdf(const MatrixFloat *x, MatrixFloat *result) { UNUSED_VARIABLE(x); UNUSED_VARIABLE(result); ERROR_EXIT(128, "NOT IMPLEMENTED\n"); } StatisticalDistributionBase *BetaDistribution::clone() { return new BetaDistribution(alpha->clone(), beta->clone()); } const char *BetaDistribution::luaCtorName() const { return "stats.dist.beta"; } int BetaDistribution::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable::pushInto(L, alphaf); AprilUtils::LuaTable::pushInto(L, betaf); return 2; } } april-ann-0.4.1/packages/basics/stats/c_src/beta_distribution.h000066400000000000000000000034621263004425400245360ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef BETA_DISTRIBUTION_H #define BETA_DISTRIBUTION_H #include "logbase.h" #include "smart_ptr.h" #include "statistical_distribution.h" namespace Stats { class BetaDistribution : public StatisticalDistributionBase { AprilUtils::SharedPtr alpha, beta; float alphaf, betaf; AprilUtils::log_float Bab; void updateParams(); protected: virtual void privateSample(Basics::MTRand *rng, Basics::MatrixFloat *result); virtual void privateLogpdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogcdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); public: BetaDistribution(Basics::MatrixFloat *alpha, Basics::MatrixFloat *beta); virtual ~BetaDistribution(); virtual StatisticalDistributionBase *clone(); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // BETA_DISTRIBUTION_H april-ann-0.4.1/packages/basics/stats/c_src/binomial_distribution.cc000066400000000000000000000114751263004425400255560ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include // #include // FIXME: this library needs c++11 extensions #include "buffer_list.h" #include "error_print.h" #include "binomial_distribution.h" #include "combinations.h" #include "utilMatrixFloat.h" using AprilUtils::buffer_list; using AprilUtils::log_float; using Basics::MatrixFloat; using Basics::MTRand; namespace Stats { BinomialDistribution::BinomialDistribution(MatrixFloat *n, MatrixFloat *p) : StatisticalDistributionBase(1), n(n), p(p) { if (n->getNumDim() != 1 || p->getNumDim() != 1 || n->getDimSize(0) != 1 || p->getDimSize(0) != 1) ERROR_EXIT(128, "Expected n,p one-dimensional matrices with size 1\n"); updateParams(); } BinomialDistribution::~BinomialDistribution() { } void BinomialDistribution::updateParams() { float nf = (*n)(0); pf = (*p)(0); // if (!(nf > 0.0f) || !(pf > 0.0f)) ERROR_EXIT(128, "Binomial distribution needs > 0 n and p params\n"); if (!(pf < 1.0f)) ERROR_EXIT(128, "Binomial distribution needs < 1 p param\n"); if (floorf(nf) != nf) ERROR_EXIT(128, "Binomial distribution needs an integer n param\n"); // pfm1 = 1.0f - pf; if (pf == 1.0f) { lpf = log_float::one(); lpfm1 = log_float::zero(); } else if (pf == 0.0f) { lpf = log_float::zero(); lpfm1 = log_float::one(); } else { lpf = log_float::from_float(pf); lpfm1 = log_float::from_float(pfm1); } ni = static_cast(nf); } void BinomialDistribution::privateSample(MTRand *rng, MatrixFloat *result) { // generation via gamma variate for (MatrixFloat::iterator result_it(result->begin()); result_it != result->end(); ++result_it) { // simulate n Bernoulli trials, and sum all values int counts = 0; for (int i=0; irand() < pf) ++counts; } *result_it = static_cast(counts); } } log_float BinomialDistribution::computeDensity(int k) { unsigned int Ci = Combinations::get(ni, k); log_float C = log_float::from_float(static_cast(Ci)); return ( C * lpf.raise_to(static_cast(k)) * lpfm1.raise_to(static_cast(ni - k)) ); } void BinomialDistribution::privateLogpdf(const MatrixFloat *x, MatrixFloat *result) { MatrixFloat::const_iterator x_it(x->begin()); MatrixFloat::iterator result_it(result->begin()); while(x_it != x->end()) { if (floorf(*x_it) != *x_it) ERROR_EXIT(128, "All values must be integers\n"); if (*x_it < 0.0f || *x_it > static_cast(ni)) *result_it = log_float::zero().log(); else { unsigned int k = static_cast(*x_it); *result_it = computeDensity(k).log(); } ++x_it; ++result_it; } } void BinomialDistribution::privateLogcdf(const MatrixFloat *x, MatrixFloat *result) { MatrixFloat::const_iterator x_it(x->begin()); MatrixFloat::iterator result_it(result->begin()); while(x_it != x->end()) { if (floorf(*x_it) != *x_it) ERROR_EXIT(128, "All values must be integers\n"); if (*x_it < 0.0f) *result_it = log_float::zero().log(); else if (*x_it > static_cast(ni)) *result_it = log_float::one().log(); else { log_float r = computeDensity(0); int k = static_cast(*x_it); for (int i=1; i<=k; ++i) { r += computeDensity(i); } *result_it = r.log(); } ++x_it; ++result_it; } } StatisticalDistributionBase *BinomialDistribution::clone() { return new BinomialDistribution(n->clone(), p->clone()); } const char *BinomialDistribution::luaCtorName() const { return "stats.dist.binomial"; } int BinomialDistribution::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable::pushInto(L, ni); AprilUtils::LuaTable::pushInto(L, pf); return 2; } } april-ann-0.4.1/packages/basics/stats/c_src/binomial_distribution.h000066400000000000000000000037021263004425400254120ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef BINOMIAL_DISTRIBUTION_H #define BINOMIAL_DISTRIBUTION_H #include "logbase.h" #include "smart_ptr.h" #include "statistical_distribution.h" namespace Stats { class BinomialDistribution : public StatisticalDistributionBase { AprilUtils::SharedPtr n, p; int ni; float pf, pfm1; AprilUtils::log_float lpf, lpfm1; void updateParams(); AprilUtils::log_float computeDensity(int k); protected: virtual void privateSample(Basics::MTRand *rng, Basics::MatrixFloat *result); virtual void privateLogpdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogcdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); public: BinomialDistribution(Basics::MatrixFloat *alpha, Basics::MatrixFloat *binomial); virtual ~BinomialDistribution(); virtual StatisticalDistributionBase *clone(); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // BINOMIAL_DISTRIBUTION_H april-ann-0.4.1/packages/basics/stats/c_src/combinations.h000066400000000000000000000051711263004425400235100ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef COMBINATIONS_H #define COMBINATIONS_H #include extern "C" { #include } #include "cmath_overloads.h" #include "error_print.h" #include "maxmin.h" namespace Stats { class Combinations { // it is forbidden to instantiate this class, it is a static class Combinations() {} public: /// Returns the logarithm of binomial coefficient of n items in groups of k static long double lget(uint32_t n, uint32_t k) { if (k>n) ERROR_EXIT(256, "k must be less or equal than n\n"); // base case if (k == 0 || k == n) return 0.0; // general case for large numbers, use lgammal function long double a = lgammal(n + 1u); long double b = lgammal(k + 1u); long double c = lgammal(n - k + 1u); long double result = a - b - c; return result; } /// Returns the binomial coefficient of n items in groups of k static uint32_t get(uint32_t n, uint32_t k) { // general case for large numbers, use lgammal function if (n > 20u) { long double result = roundl(expl(lget(n, k))); if (result > static_cast(AprilMath::Limits::max())) { ERROR_EXIT(256, "Overflow in 32 bits unsigned integer, use logarithmic method\n"); } return static_cast(result); } else { if (k>n) ERROR_EXIT(256, "k must be less or equal than n\n"); // base case if (k == 0 || k == n) return 1u; // general case for short numbers, use iteration else { // take into account triangle symmetry k = AprilUtils::min(k, n - k); uint32_t result = 1u; for (uint32_t i=0u; i #include "c_string.h" #include "error_print.h" #include "exponential_distribution.h" #include "matrix_ext.h" #include "smart_ptr.h" #include "utilMatrixFloat.h" using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilMath::MatrixExt::Operations; using namespace AprilMath::MatrixExt::Reductions; using AprilUtils::log_float; using AprilUtils::SharedPtr; using AprilIO::CStringStream; using Basics::MatrixFloat; using Basics::MTRand; namespace Stats { ExponentialDistribution::ExponentialDistribution(MatrixFloat *lambda) : StatisticalDistributionBase(lambda->size()), lambda(lambda), inv_lambda(0) { if (lambda->getNumDim() != 1) ERROR_EXIT(128, "Expected one-dimensional lambda matrix\n"); IncRef(lambda); updateParams(); } ExponentialDistribution::~ExponentialDistribution() { } void ExponentialDistribution::updateParams() { for (MatrixFloat::iterator it(lambda->begin()); it != lambda->end(); ++it) { if (*it < 0.0f) { ERROR_EXIT1(128, "Found negative lambda parameter at position %d\n", it.getIdx()); } } AprilUtils::UniquePtr log_lambda( lambda->clone() ); matLog(log_lambda.get()); lambda_prod = log_float(matSum(log_lambda.get())); if (inv_lambda) inv_lambda.reset(); } void ExponentialDistribution::privateSample(MTRand *rng, MatrixFloat *result) { if (inv_lambda.empty()) inv_lambda = matDiv(lambda.get(), 1.0f, lambda->cloneOnlyDims()); for (MatrixFloat::iterator it(result->begin()); it != result->end(); ++it) { float v = static_cast(rng->randDblExc()); april_assert(v > 0.0f && v < 1.0f); *it = v; } matLog(result); matScal(result,-1.0f); MatrixFloat *result_row = 0; for (int i=0; igetDimSize(0); ++i) { result_row = result->select(0, i, result_row); matCmul(result_row, inv_lambda.get()); } delete result_row; } void ExponentialDistribution::privateLogpdf(const MatrixFloat *x, MatrixFloat *result) { int a,b; if (matMin(x,a,b) < 0.0f) { ERROR_EXIT(128, "Exponential dist. is not defined for neg. numbers\n"); } UNUSED_VARIABLE(a); UNUSED_VARIABLE(b); matFill(result, lambda_prod.log()); matGemv(result, CblasNoTrans, -1.0f, x, lambda.get(), 1.0f); } void ExponentialDistribution::privateLogcdf(const MatrixFloat *x, MatrixFloat *result) { int a,b; if (matMin(x,a,b) < 0.0f) ERROR_EXIT(128, "Exponential dist. is not defined for neg. numbers\n"); UNUSED_VARIABLE(a); UNUSED_VARIABLE(b); int dims[2] = { result->getDimSize(0), 1 }; // FIXME: needs a contiguous result matrix SharedPtr rewrapped_result( result->rewrap(dims, 2) ); SharedPtr x_clone( x->clone() ), x_row; // for (int i=0; igetDimSize(0); ++i) { x_row = x_clone->select(0, i, x_row.get()); matCmul(x_row.get(), lambda.get()); } matScal(x_clone.get(), -1.0f); matExp(x_clone.get()); matScal(x_clone.get(), -1.0f); matLog1p(x_clone.get()); matSum(x_clone.get(), 1, rewrapped_result.get()); } StatisticalDistributionBase *ExponentialDistribution::clone() { return new ExponentialDistribution(lambda->clone()); } const char *ExponentialDistribution::luaCtorName() const { return "stats.dist.exponential"; } int ExponentialDistribution::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable::pushInto(L, lambda); return 1; } } april-ann-0.4.1/packages/basics/stats/c_src/exponential_distribution.h000066400000000000000000000035271263004425400261530ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef EXPONENTIAL_DISTRIBUTION_H #define EXPONENTIAL_DISTRIBUTION_H #include "logbase.h" #include "smart_ptr.h" #include "statistical_distribution.h" namespace Stats { class ExponentialDistribution : public StatisticalDistributionBase { AprilUtils::SharedPtr lambda, inv_lambda; AprilUtils::log_float lambda_prod; void updateParams(); protected: virtual void privateSample(Basics::MTRand *rng, Basics::MatrixFloat *result); virtual void privateLogpdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogcdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); public: ExponentialDistribution(Basics::MatrixFloat *lambda); virtual ~ExponentialDistribution(); virtual StatisticalDistributionBase *clone(); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // EXPONENTIAL_DISTRIBUTION_H april-ann-0.4.1/packages/basics/stats/c_src/gamma_distribution.cc000066400000000000000000000072761263004425400250520ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2015, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include // #include // FIXME: this library needs c++11 extensions #include "buffer_list.h" #include "error_print.h" #include "gamma_distribution.h" #include "gamma_variate.h" #include "matrix_ext_blas.h" #include "matrix_ext_initializers.h" #include "matrix_ext_operations.h" #include "utilMatrixFloat.h" using AprilUtils::buffer_list; using AprilUtils::log_float; using AprilUtils::SharedPtr; using AprilUtils::UniquePtr; using Basics::MatrixFloat; using Basics::MTRand; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilMath::MatrixExt::Operations; namespace Stats { GammaDistribution::GammaDistribution(MatrixFloat *alpha, MatrixFloat *beta) : StatisticalDistributionBase(1), alpha(alpha), beta(beta) { if (alpha->getNumDim() != 1 || beta->getNumDim() != 1 || alpha->getDimSize(0) != 1 || beta->getDimSize(0) != 1) ERROR_EXIT(128, "Expected alpha,beta one-dimensional matrices with size 1\n"); updateParams(); } GammaDistribution::~GammaDistribution() { } void GammaDistribution::updateParams() { alphaf = (*alpha)(0); betaf = (*beta)(0); if (!(alphaf > 0.0f) || !(betaf > 0.0f)) { ERROR_EXIT(128, "Gamma distribution needs > 0 alpha and beta params\n"); } // log( beta^alpha / gamma(alpha) ) = alpha * log beta - lgamma(alpha) log_float beta_pow_alpha(logf(betaf)*alphaf); log_float gamma_a(lgamma(alphaf)); CTE = beta_pow_alpha / gamma_a; } void GammaDistribution::privateSample(MTRand *rng, MatrixFloat *result) { double scale = 1.0/static_cast(betaf); for (MatrixFloat::iterator result_it(result->begin()); result_it != result->end(); ++result_it) { *result_it = gammaVariate(rng, 0.0, scale, static_cast(alphaf)); } } void GammaDistribution::privateLogpdf(const MatrixFloat *x, MatrixFloat *result) { // pdf = CTE x^(alpha - 1) exp(-beta * x) // logpdf = logCTE + (alpha-1)*log(x) - beta*x UniquePtr aux_r(result->rightInflate(1)); matLog(x, aux_r.get()); matScal(aux_r.get(), alphaf - 1.0f); matAxpy(aux_r.get(), -betaf, x); matScalarAdd(aux_r.get(), CTE.log()); } void GammaDistribution::privateLogcdf(const MatrixFloat *x, MatrixFloat *result) { UNUSED_VARIABLE(x); UNUSED_VARIABLE(result); ERROR_EXIT(128, "NOT IMPLEMENTED\n"); } StatisticalDistributionBase *GammaDistribution::clone() { return new GammaDistribution(alpha->clone(), beta->clone()); } const char *GammaDistribution::luaCtorName() const { return "stats.dist.gamma"; } int GammaDistribution::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable::pushInto(L, alphaf); AprilUtils::LuaTable::pushInto(L, betaf); return 2; } } april-ann-0.4.1/packages/basics/stats/c_src/gamma_distribution.h000066400000000000000000000040261263004425400247020ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2015, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef GAMMA_DISTRIBUTION_H #define GAMMA_DISTRIBUTION_H #include "logbase.h" #include "smart_ptr.h" #include "statistical_distribution.h" namespace Stats { class GammaDistribution : public StatisticalDistributionBase { /// A positive real number. The scale parameter. AprilUtils::SharedPtr alpha; /// A positive real number. The rate paremater. AprilUtils::SharedPtr beta; float alphaf; ///< The scale parameter. float betaf; /// The rate parameter. AprilUtils::log_float CTE; void updateParams(); protected: virtual void privateSample(Basics::MTRand *rng, Basics::MatrixFloat *result); virtual void privateLogpdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogcdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); public: GammaDistribution(Basics::MatrixFloat *alpha, Basics::MatrixFloat *beta); virtual ~GammaDistribution(); virtual StatisticalDistributionBase *clone(); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // GAMMA_DISTRIBUTION_H april-ann-0.4.1/packages/basics/stats/c_src/gamma_variate.cc000066400000000000000000000044551263004425400237620ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include "april_assert.h" #include "gamma_variate.h" using Basics::MTRand; namespace Stats { // a=location, b=scale, c=shape // Modification of: http://ftp.arl.mil/random/random.pdf double gammaVariate(MTRand *rng, const double a, const double b, const double c) { double y; april_assert( b > 0.0 && c > 0.0 ); const double A = 1. / sqrt( 2.0 * c - 1.0 ); const double B = c - log( 4.0 ); const double Q = c + 1.0 / A; const double T = 4.5; const double D = 1.0 + log( T ); const double C = 1.0 + c / M_E; if ( c < 1.0 ) { while ( true ) { const double p = C * rng->rand(); if ( p > 1.0 ) { y = -log( ( C - p ) / c ); if ( rng->rand() <= pow( y, c - 1.0 ) ) break; } else { y = pow( p, 1.0 / c ); if ( rng->rand() <= exp( -y ) ) break; } } } else if ( c == 1.0 ) { // exponential variate y = -log(rng->randDblExc()); } else { while ( true ) { const double p1 = rng->rand(); const double p2 = rng->rand(); const double v = A * log( p1 / ( 1.0 - p1 ) ); y = c * exp( v ); const double z = p1 * p1 * p2; const double w = B + Q * v - y; if ( w + D - T * z >= 0.0 || w >= log( z ) ) break; } } if (a == 0.0) { if (b == 1.0) return y; else return b*y; } else { if (b == 1.0) return a + y; else return a + b*y; } } } april-ann-0.4.1/packages/basics/stats/c_src/gamma_variate.h000066400000000000000000000026531263004425400236220ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef GAMMA_VARIATE_H #define GAMMA_VARIATE_H #include "MersenneTwister.h" namespace Stats { /** * @brief Computes a Gamma variate random number. * * @params rng A random numbers generator. * @params a A location parameter. * @params b A scale parameter. * @params c A shape parameter. * * @note The shape can be transformed into a rate computing \f$ * \frac{1}{shape} \f$. * * @note Modification of: http://ftp.arl.mil/random/random.pdf */ double gammaVariate(Basics::MTRand *rng, const double a, const double b, const double c); } #endif // GAMMA_VARIATE_H april-ann-0.4.1/packages/basics/stats/c_src/normal_distribution.cc000066400000000000000000000431231263004425400252470ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #define _USE_MATH_DEFINES #include #include "buffer_list.h" #include "check_floats.h" #include "error_print.h" #include "matrixFloat.h" #include "normal_distribution.h" #include "smart_ptr.h" #include "sparse_matrixFloat.h" #include "unused_variable.h" using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilMath::MatrixExt::LAPACK; using namespace AprilMath::MatrixExt::Operations; using namespace AprilMath::MatrixExt::Reductions; using AprilUtils::log_float; using AprilUtils::SharedPtr; using AprilIO::CStringStream; using Basics::MatrixFloat; using Basics::SparseMatrixFloat; using Basics::MTRand; namespace Stats { const float M_2PI = M_PI*2.0f; GeneralNormalDistribution::GeneralNormalDistribution(MatrixFloat *mean, MatrixFloat *cov) : StatisticalDistributionBase(mean->size()), mean(mean), cov(cov), inv_cov(0), L(0) { if (mean->getNumDim() != 1) ERROR_EXIT(128, "Expected one-dimensional mean matrix\n"); if (cov->getNumDim() != 2 || cov->getDimSize(0) != cov->getDimSize(1)) ERROR_EXIT(128, "Expected squared bi-dimensional cov matrix\n"); if (mean->getDimSize(0) != cov->getDimSize(0)) ERROR_EXIT(128, "Expected mean and cov matrix with same size\n"); updateParams(); } GeneralNormalDistribution::~GeneralNormalDistribution() { } void GeneralNormalDistribution::updateParams() { // K = 1 / sqrtf( 2*pi^k * |cov| ) inv_cov = matInv(cov.get()); // TODO: check covariance matrix to be definite positive cov_det = matLogDeterminant(cov.get(), cov_det_sign); log_float KM_2PI = log_float::from_float(M_2PI). raise_to(static_cast(mean->getDimSize(0))); log_float denom = (KM_2PI * cov_det).raise_to(0.5f); K = log_float::one() / denom; L.reset(); } void GeneralNormalDistribution::privateSample(MTRand *rng, MatrixFloat *result) { if (L.empty()) L = matCholesky(cov.get(), 'L'); AprilUtils::SharedPtr z = result->cloneOnlyDims(); for (MatrixFloat::iterator z_it = z->begin(); z_it != z->end(); ++z_it) { *z_it = static_cast(rng->randNorm(0.0, 1.0)); } matGemm(result, CblasNoTrans, CblasNoTrans, 1.0f, z.get(), L.get(), 0.0f); AprilUtils::SharedPtr result_row; for (int i=0; igetDimSize(0); ++i) { result_row = result->select(0, i, result_row.get()); matAxpy(result_row.get(), 1.0f, mean.get()); } } void GeneralNormalDistribution::privateLogpdf(const MatrixFloat *x, MatrixFloat *result) { SharedPtr diff( x->clone() ); int dims[1] = { x->getDimSize(1) }; SharedPtr mult( new MatrixFloat(1, dims) ); // over all samples (bunch_size) MatrixFloat::iterator result_it(result->begin()); SharedPtr diff_row; for (int i=0; igetDimSize(0); ++i, ++result_it) { diff_row = diff->select(0, i, diff_row.get()); matAxpy(diff_row.get(), -1.0f, mean.get()); matGemv(mult.get(), CblasNoTrans, 1.0f, inv_cov.get(), diff_row.get(), 0.0f); *result_it = -0.5 * matDot(mult.get(), diff_row.get()); } matScalarAdd(result, K.log() ); } void GeneralNormalDistribution::privateLogcdf(const MatrixFloat *x, MatrixFloat *result) { UNUSED_VARIABLE(x); UNUSED_VARIABLE(result); ERROR_EXIT(128, "Not implemented"); } void GeneralNormalDistribution::privateLogpdfDerivative(const MatrixFloat *x, MatrixFloat *result) { SharedPtr diff( x->clone() ); // over all samples (bunch_size) SharedPtr diff_row; SharedPtr result_row; for (int i=0; igetDimSize(0); ++i) { diff_row = diff->select(0, i, diff_row.get()); result_row = result->select(0, i, result_row.get()); matAxpy(diff_row.get(), -1.0f, mean.get()); matGemv(result_row.get(), CblasNoTrans, -1.0f, inv_cov.get(), diff_row.get(), 1.0f); } } StatisticalDistributionBase *GeneralNormalDistribution::clone() { return new GeneralNormalDistribution(mean->clone(), cov->clone()); } const char *GeneralNormalDistribution::luaCtorName() const { return "stats.dist.normal"; } int GeneralNormalDistribution::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable::pushInto(L, mean); AprilUtils::LuaTable::pushInto(L, cov); return 2; } //////////////////////////////////////////////////////////////////////////// DiagonalNormalDistribution::DiagonalNormalDistribution(MatrixFloat *mean, SparseMatrixFloat *cov) : StatisticalDistributionBase(mean->size()), mean(mean), cov(cov), inv_cov(0), L(0) { if (mean->getNumDim() != 1) ERROR_EXIT(128, "Expected one-dimensional mean matrix\n"); if (cov->getNumDim() != 2 || cov->getDimSize(0) != cov->getDimSize(1)) ERROR_EXIT(128, "Expected squared bi-dimensional cov matrix\n"); if (mean->getDimSize(0) != cov->getDimSize(0)) ERROR_EXIT(128, "Expected mean and cov matrix with same size\n"); updateParams(); } DiagonalNormalDistribution::~DiagonalNormalDistribution() { } void DiagonalNormalDistribution::updateParams() { if (!cov->isDiagonal()) ERROR_EXIT(256, "Expected diagonal cov sparse matrix\n"); // K = 1 / sqrtf( 2*pi^k * |cov| ) inv_cov = cov->clone(); matDiv(inv_cov.get(), 1.0f); // inv_cov->pruneSubnormalAndCheckNormal(); cov_det = log_float::one(); for (SparseMatrixFloat::iterator it(cov->begin()); it != cov->end(); ++it) { if (!std::isfinite(*it)) { int x0,x1; it.getCoords(x0,x1); ERROR_EXIT3(256, "No finite number at position %d,%d with value %g\n", x0, x1, *it); } if (*it < 0.0f) ERROR_EXIT(256, "Expected a definite positive covariance matrix\n"); cov_det *= log_float::from_float(*it); } log_float KM_2PI = log_float::from_float(M_2PI). raise_to(static_cast(mean->getDimSize(0))); log_float denom = (KM_2PI * cov_det).raise_to(0.5f); K = log_float::one() / denom; L.reset(); } void DiagonalNormalDistribution::privateSample(MTRand *rng, MatrixFloat *result) { if (L.empty()) { L = matSqrt( cov->clone() ); } SharedPtr z( result->cloneOnlyDims() ); for (MatrixFloat::iterator z_it = z->begin(); z_it != z->end(); ++z_it) { *z_it = static_cast(rng->randNorm(0.0, 1.0)); } SharedPtr rT(result->transpose()); matSparseMM(rT.get(), CblasTrans, CblasTrans, 1.0f, L.get(), z.get(), 0.0f); SharedPtr result_row; for (int i=0; igetDimSize(0); ++i) { result_row = result->select(0, i, result_row.get()); matAxpy(result_row.get(), 1.0f, mean.get()); } } void DiagonalNormalDistribution::privateLogpdf(const MatrixFloat *x, MatrixFloat *result) { SharedPtr diff( x->clone() ); int dims[1] = { x->getDimSize(1) }; SharedPtr mult( new MatrixFloat(1, dims) ); // over all samples (bunch_size) MatrixFloat::iterator result_it(result->begin()); SharedPtr diff_row; for (int i=0; igetDimSize(0); ++i, ++result_it) { diff_row = diff->select(0, i, diff_row.get()); matAxpy(diff_row.get(), -1.0f, mean.get()); matGemv(mult.get(), CblasNoTrans, 1.0f, inv_cov.get(), diff_row.get(), 0.0f); *result_it = -0.5 * matDot(mult.get(), diff_row.get()); } matScalarAdd(result, K.log() ); } void DiagonalNormalDistribution::privateLogcdf(const MatrixFloat *x, MatrixFloat *result) { if (getSize() != 1) { ERROR_EXIT(128, "Only implemented for univariate distributions\n"); } float mu = *(mean->begin()); float sd = ::sqrtf(*(cov->begin())); static float inv_sd_sqrt2 = 1.0f/(sd*sqrtf(2.0f)); MatrixFloat::const_iterator x_it = x->begin(); for (MatrixFloat::iterator it=result->begin(); it!=result->end(); ++it) { *it = AprilMath::m_log( 0.5f * (1.0f + ::erff( (*x_it - mu) * inv_sd_sqrt2 )) ); } } void DiagonalNormalDistribution::privateLogpdfDerivative(const MatrixFloat *x, MatrixFloat *result) { SharedPtr diff( x->clone() ); // over all samples (bunch_size) SharedPtr diff_row; SharedPtr result_row; for (int i=0; igetDimSize(0); ++i) { diff_row = diff->select(0, i, diff_row.get()); result_row = result->select(0, i, result_row.get()); matAxpy(diff_row.get(), -1.0f, mean.get()); matGemv(result_row.get(), CblasNoTrans, -1.0f, inv_cov.get(), diff_row.get(), 1.0f); } } StatisticalDistributionBase *DiagonalNormalDistribution::clone() { return new DiagonalNormalDistribution(mean->clone(), cov->clone()); } const char *DiagonalNormalDistribution::luaCtorName() const { return "stats.dist.normal"; } int DiagonalNormalDistribution::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable::pushInto(L, mean); AprilUtils::LuaTable::pushInto(L, cov); return 2; } //////////////////////////////////////////////////////////////////////////// StandardNormalDistribution::StandardNormalDistribution() : StatisticalDistributionBase(1) { K = log_float::from_float(1.0f/sqrtf(M_2PI)); } StandardNormalDistribution::~StandardNormalDistribution() { } void StandardNormalDistribution::privateSample(MTRand *rng, MatrixFloat *result) { for (MatrixFloat::iterator result_it = result->begin(); result_it != result->end(); ++result_it) { *result_it = static_cast(rng->randNorm(0.0, 1.0)); } } void StandardNormalDistribution::privateLogpdf(const MatrixFloat *x, MatrixFloat *result) { SharedPtr x2( x->clone() ); matPow(x2.get(), 2.0f); matFill(result, K.log()); matAxpy(result, -0.5f, x2.get()); } void StandardNormalDistribution::privateLogcdf(const MatrixFloat *x, MatrixFloat *result) { static float inv_sqrt2 = 1.0f/sqrtf(2.0f); MatrixFloat::const_iterator x_it = x->begin(); for (MatrixFloat::iterator it=result->begin(); it!=result->end(); ++it) { *it = AprilMath::m_log( 0.5f * (1.0f + ::erff( *x_it * inv_sqrt2 )) ); } } void StandardNormalDistribution::privateLogpdfDerivative(const MatrixFloat *x, MatrixFloat *result) { matAxpy(result, -1.0f, x); } StatisticalDistributionBase *StandardNormalDistribution::clone() { return new StandardNormalDistribution(); } const char *StandardNormalDistribution::luaCtorName() const { return "stats.dist.normal"; } int StandardNormalDistribution::exportParamsToLua(lua_State *L) { UNUSED_VARIABLE(L); return 0; } //////////////////////////////////////////////////////////////////////////// GeneralLogNormalDistribution::GeneralLogNormalDistribution(MatrixFloat *mean, MatrixFloat *cov, MatrixFloat *location) : GeneralNormalDistribution(mean,cov), location(location) { if (location == 0) { location = mean->cloneOnlyDims(); matZeros(location); this->location = location; } if (!location->sameDim(mean)) { ERROR_EXIT(256, "Expected location param with same shape as mean param\n"); } updateParams(); } GeneralLogNormalDistribution::~GeneralLogNormalDistribution() { } void GeneralLogNormalDistribution::privateSample(MTRand *rng, MatrixFloat *result) { GeneralNormalDistribution::privateSample(rng, result); matExp(result); SharedPtr result_row; for (int i=0; igetDimSize(0); ++i) { result_row = result->select(0, i, result_row.get()); matAxpy(result_row.get(), 1.0f, location.get()); } } void GeneralLogNormalDistribution::privateLogpdf(const MatrixFloat *x, MatrixFloat *result) { SharedPtr xlog( x->clone() ); SharedPtr xlog_row; for (int i=0; igetDimSize(0); ++i) { xlog_row = xlog->select(0, i, xlog_row.get()); matAxpy(xlog_row.get(), -1.0f, location.get()); } matLog(xlog.get()); GeneralNormalDistribution::privateLogpdf(matLog(xlog.get()), result); SharedPtr xlog_sum( matSum(xlog.get(), 1) ); matAxpy(result, -1.0f, xlog_sum.get()); } void GeneralLogNormalDistribution::privateLogcdf(const MatrixFloat *x, MatrixFloat *result) { UNUSED_VARIABLE(x); UNUSED_VARIABLE(result); ERROR_EXIT(128, "Not implemented"); } void GeneralLogNormalDistribution::privateLogpdfDerivative(const MatrixFloat *x, MatrixFloat *result) { UNUSED_VARIABLE(x); UNUSED_VARIABLE(result); ERROR_EXIT(128, "Not implemented"); } StatisticalDistributionBase *GeneralLogNormalDistribution::clone() { return new GeneralLogNormalDistribution(mean->clone(), cov->clone(), location->clone()); } const char *GeneralLogNormalDistribution::luaCtorName() const { return "stats.dist.lognormal"; } int GeneralLogNormalDistribution::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable::pushInto(L, mean); AprilUtils::LuaTable::pushInto(L, cov); AprilUtils::LuaTable::pushInto(L, location); return 3; } //////////////////////////////////////////////////////////////////////////// DiagonalLogNormalDistribution::DiagonalLogNormalDistribution(MatrixFloat *mean, SparseMatrixFloat *cov, MatrixFloat *location) : DiagonalNormalDistribution(mean, cov), location(location) { if (location == 0) { location = mean->cloneOnlyDims(); matZeros(location); this->location = location; } if (!location->sameDim(mean)) ERROR_EXIT(256, "Expected location param with same shape as mean param\n"); updateParams(); } DiagonalLogNormalDistribution::~DiagonalLogNormalDistribution() { } void DiagonalLogNormalDistribution::privateSample(MTRand *rng, MatrixFloat *result) { DiagonalNormalDistribution::privateSample(rng, result); matExp(result); SharedPtr result_row; for (int i=0; igetDimSize(0); ++i) { result_row = result->select(0, i, result_row.get()); matAxpy(result_row.get(), 1.0f, location.get()); } } void DiagonalLogNormalDistribution::privateLogpdf(const MatrixFloat *x, MatrixFloat *result) { SharedPtr xlog( x->clone() ); SharedPtr xlog_row; for (int i=0; igetDimSize(0); ++i) { xlog_row = xlog->select(0, i, xlog_row.get()); matAxpy(xlog_row.get(), -1.0f, location.get()); } matLog(xlog.get()); DiagonalNormalDistribution::privateLogpdf(xlog.get(), result); SharedPtr xlog_sum( matSum(xlog.get(), 1) ); matAxpy(result, -1.0f, xlog_sum.get()); } void DiagonalLogNormalDistribution::privateLogcdf(const MatrixFloat *x, MatrixFloat *result) { UNUSED_VARIABLE(x); UNUSED_VARIABLE(result); ERROR_EXIT(128, "Not implemented"); } void DiagonalLogNormalDistribution::privateLogpdfDerivative(const MatrixFloat *x, MatrixFloat *result) { UNUSED_VARIABLE(x); UNUSED_VARIABLE(result); ERROR_EXIT(128, "Not implemented"); } StatisticalDistributionBase *DiagonalLogNormalDistribution::clone() { return new DiagonalLogNormalDistribution(mean->clone(), cov->clone(), location->clone()); } const char *DiagonalLogNormalDistribution::luaCtorName() const { return "stats.dist.lognormal"; } int DiagonalLogNormalDistribution::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable::pushInto(L, mean); AprilUtils::LuaTable::pushInto(L, cov); AprilUtils::LuaTable::pushInto(L, location); return 3; } } april-ann-0.4.1/packages/basics/stats/c_src/normal_distribution.h000066400000000000000000000146101263004425400251100ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef NORMAL_DISTRIBUTION_H #define NORMAL_DISTRIBUTION_H #include "matrixFloat.h" #include "smart_ptr.h" #include "sparse_matrixFloat.h" #include "statistical_distribution.h" namespace Stats { /// Normal distribution with general covariance matrix class GeneralNormalDistribution : public StatisticalDistributionBase { protected: AprilUtils::SharedPtr mean, cov, inv_cov, L; AprilUtils::log_float cov_det, K; float cov_det_sign; void updateParams(); virtual void privateSample(Basics::MTRand *rng, Basics::MatrixFloat *result); virtual void privateLogpdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogcdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogpdfDerivative(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); public: GeneralNormalDistribution(Basics::MatrixFloat *mean, Basics::MatrixFloat *cov); virtual ~GeneralNormalDistribution(); virtual StatisticalDistributionBase *clone(); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; /// Normal distribution with diagonal covariance sparse matrix class DiagonalNormalDistribution : public StatisticalDistributionBase { protected: AprilUtils::SharedPtr mean; AprilUtils::log_float cov_det, K; float cov_det_sign; AprilUtils::SharedPtr cov, inv_cov, L; void updateParams(); virtual void privateSample(Basics::MTRand *rng, Basics::MatrixFloat *result); virtual void privateLogpdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogcdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogpdfDerivative(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); public: DiagonalNormalDistribution(Basics::MatrixFloat *mean, Basics::SparseMatrixFloat *cov); virtual ~DiagonalNormalDistribution(); virtual StatisticalDistributionBase *clone(); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; /// Normal distribution with mean=0 and var=1 class StandardNormalDistribution : public StatisticalDistributionBase { protected: AprilUtils::log_float K; virtual void privateSample(Basics::MTRand *rng, Basics::MatrixFloat *result); virtual void privateLogpdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogcdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogpdfDerivative(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); public: StandardNormalDistribution(); virtual ~StandardNormalDistribution(); virtual StatisticalDistributionBase *clone(); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; /// Log-Normal distribution with general covariance matrix class GeneralLogNormalDistribution : public GeneralNormalDistribution { AprilUtils::SharedPtr location; protected: virtual void privateSample(Basics::MTRand *rng, Basics::MatrixFloat *result); virtual void privateLogpdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogcdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogpdfDerivative(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); public: GeneralLogNormalDistribution(Basics::MatrixFloat *mean, Basics::MatrixFloat *cov, Basics::MatrixFloat *location=0); virtual ~GeneralLogNormalDistribution(); virtual StatisticalDistributionBase *clone(); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; /// Log-LogNormal distribution with diagonal covariance sparse matrix class DiagonalLogNormalDistribution : public DiagonalNormalDistribution { AprilUtils::SharedPtr location; protected: virtual void privateSample(Basics::MTRand *rng, Basics::MatrixFloat *result); virtual void privateLogpdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogcdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogpdfDerivative(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); public: DiagonalLogNormalDistribution(Basics::MatrixFloat *mean, Basics::SparseMatrixFloat *cov, Basics::MatrixFloat *location=0); virtual ~DiagonalLogNormalDistribution(); virtual StatisticalDistributionBase *clone(); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // NORMAL_DISTRIBUTION_H april-ann-0.4.1/packages/basics/stats/c_src/statistical_distribution.h000066400000000000000000000222261263004425400261460ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef STATISTICAL_DISTRIBUTION_H #define STATISTICAL_DISTRIBUTION_H #include "error_print.h" #include "logbase.h" #include "matrixFloat.h" #include "MersenneTwister.h" #include "serializable.h" /// Classes related with statistical functions and distributions. namespace Stats { /** * @brief Class StatisticalDistributionBase implements basic interface for * statistical distributions and defines a private API for new classes * derivation. * All the methods work with two-dimensional matrices where first dimension is * the bunch_size (like ANN components). */ class StatisticalDistributionBase : public AprilIO::Serializable { unsigned int size; protected: /** * @brief Receives a random generator and a MatrixFloat where sampled values * will be stored. The number of samples values will be equal to * result->getDimSize(0) * * @param rng - A MTRand instance. * @param result - A MatrixFloat where the sampled data will be stored. */ virtual void privateSample(Basics::MTRand *rng, Basics::MatrixFloat *result) = 0; /** * @brief Receives a x MatrixFloat with NxM size (N = bunch_size), and a N * sized result MatrixFloat. * * @param x - A NxM MatrixFloat with N data points of size M. * @param result - A one-dimensional MatrixFloat where logpdf will be stored. */ virtual void privateLogpdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result) = 0; /** * @brief Receives a x MatrixFloat with NxM size (N = bunch_size), and a N * sized result MatrixFloat. * * @param x - A NxM MatrixFloat with N data points of size M. * @param result - A one-dimensional MatrixFloat where logcdf will be stored. */ virtual void privateLogcdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result) = 0; /** * @brief Receives a x MatrixFloat with NxM size (N = bunch_size), and a N * sized grads MatrixFloat. * * @param x - A NxM MatrixFloat with N data points of size M. * @param result - A MatrixFloat where derivative of logpdf will be stored. */ virtual void privateLogpdfDerivative(const Basics::MatrixFloat *x, Basics::MatrixFloat *result) { UNUSED_VARIABLE(x); UNUSED_VARIABLE(result); ERROR_EXIT(128, "Derivative not implemented\n"); } public: /** * @param size - The size of the distribution data points. */ StatisticalDistributionBase(unsigned int size) : Serializable(), size(size) {} virtual ~StatisticalDistributionBase() {} /** * @brief Public part of sample method, where arguments will be checked. * * @param rng - A MTRand instance. * * @param result - An auxiliary MatrixFloat where to store the result, if * not given a MatrixFloat with 1xM size will be allocated. * * @return A MatrixFloat with the sample result. */ Basics::MatrixFloat *sample(Basics::MTRand *rng, Basics::MatrixFloat *result=0) { int dims[2] = { 1, static_cast(size) }; if (result == 0) { result = new Basics::MatrixFloat(2, dims); } else if (result->getNumDim() != 2 || result->getDimSize(1) != static_cast(size)) ERROR_EXIT1(128, "Incorrect result matrix size, expected " "bi-dimensional matrix with Nx%u shape\n", size); // virtual call privateSample(rng, result); return result; } /** * @brief Public part of logpdf method, arguments will be checked here. * * @param x - A MatrixFloat with size NxM where N is the number of data * points. * * @param result - An auxiliary MatrixFloat where to store the result. * * @return A MatrixFloat with the sample result. */ Basics::MatrixFloat *logpdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result=0) { if (x->getNumDim() != 2 || x->getDimSize(1) != static_cast(size)) ERROR_EXIT1(128, "Incorrect x matrix size, expected bi-dimensional " "matrix with Nx%u shape\n", size); int dims[1] = { x->getDimSize(0) }; if (result == 0) { result = new Basics::MatrixFloat(1, dims); } else if (result->getNumDim() != 1 || result->getDimSize(0) != dims[0]) ERROR_EXIT1(128, "Incorrect result matrix size, expected " "one-dimensional matrix with %d size\n", dims[0]); // virtual call privateLogpdf(x, result); return result; } /** * @brief Public part of logcdf method, arguments will be checked here. * * @param x - A MatrixFloat with size NxM where N is the number of data * points. * * @param result - An auxiliary MatrixFloat where to store the result. * * @return A MatrixFloat with the sample result. */ Basics::MatrixFloat *logcdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result=0) { if (x->getNumDim() != 2 || x->getDimSize(1) != static_cast(size)) ERROR_EXIT1(128, "Incorrect x matrix size, expected bi-dimensional " "matrix with Nx%u shape\n", size); int dims[1] = { x->getDimSize(0) }; if (result == 0) { result = new Basics::MatrixFloat(1, dims); } else if (result->getNumDim() != 1 || result->getDimSize(0) != dims[0]) ERROR_EXIT1(128, "Incorrect result matrix size, expected " "one-dimensional matrix with %d size\n", dims[0]); // virtual call privateLogcdf(x, result); return result; } /** * @brief Public part of logpdfDerivative method, arguments will be checked * here. * * @param x - A MatrixFloat with size NxM where N is the number of data * points. * * @param result - An auxiliary MatrixFloat where to store the result. * * @return A MatrixFloat with the sample result. */ Basics::MatrixFloat *logpdfDerivative(const Basics::MatrixFloat *x, Basics::MatrixFloat *grads=0) { if (x->getNumDim() != 2 || x->getDimSize(1) != static_cast(size)) ERROR_EXIT1(128, "Incorrect x matrix size, expected bi-dimensional " "matrix with Nx%u shape\n", size); const int *dims = x->getDimPtr(); if (grads == 0) { grads = new Basics::MatrixFloat(2, dims); AprilMath::MatrixExt::Initializers::matZeros(grads); } else if (grads->getNumDim() != 2 || grads->getDimSize(0) != dims[0] || grads->getDimSize(1) != dims[1]) ERROR_EXIT2(128, "Incorrect grads matrix size, expected " "bidimensional matrix with %dx%d size\n", dims[0], dims[1]); // virtual call IncRef(grads); privateLogpdfDerivative(x, grads); // WARNING: don't use DecRef macro because it will destroy grads matrix grads->decRef(); return grads; } /** * @return The size of data points. */ unsigned int getSize() { return size; } // abstract interface /** * @return A deep copy (clone) of the caller object. */ virtual StatisticalDistributionBase *clone() = 0; // virtual const char *luaCtorName() const; // virtual int exportParamsToLua(lua_State *L); }; //////////////////////////////////////////////////////////////////////////// /* class ExponentialDistribution : public StatisticalDistributionBase { MatrixFloat *lambda; }; class DiagonalNormalDistribution : public StatisticalDistributionBase { MatrixFloat *mean; SparseMatrixFloat *cov; }; class GeneralNormalDistribution : public StatisticalDistributionBase { MatrixFloat *mean, *cov; }; class StudentDistribution : public StatisticalDistributionBase { MatrixFloat *v; }; class GammaDistribution : public StatisticalDistributionBase { MatrixFloat *alpha, *beta; }; class BetaDistribution : public StatisticalDistributionBase { MatrixFloat *alpha, *beta; }; class BinomialDistribution : public StatisticalDistributionBase { MatrixFloat *p; }; class MultinomialDistribution : public StatisticalDistributionBase { MatrixFloat *p; }; */ } #endif // STATISTICAL_DISTRIBUTION_H april-ann-0.4.1/packages/basics/stats/c_src/uniform_distribution.cc000066400000000000000000000115111263004425400254320ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "matrixFloat.h" #include "smart_ptr.h" #include "uniform_distribution.h" using AprilUtils::log_float; using AprilUtils::SharedPtr; using AprilIO::CStringStream; using Basics::MatrixFloat; using Basics::MTRand; namespace Stats { UniformDistribution::UniformDistribution(MatrixFloat *low, MatrixFloat *high) : StatisticalDistributionBase(low->size()), low(low), high(high), diff(0) { if (!low->sameDim(high)) ERROR_EXIT(128, "Expected same sizes in low and high matrices\n"); MatrixFloat::const_iterator low_it(low->begin()); MatrixFloat::const_iterator high_it(high->begin()); while(low_it != low->end()) { if ( ! (*low_it < *high_it) ) ERROR_EXIT(128, "All low values must be less than high matrix\n"); ++low_it; ++high_it; } updateParams(); } UniformDistribution::~UniformDistribution() { } void UniformDistribution::privateSample(MTRand *rng, MatrixFloat *result) { // traverse in row_major result matrix MatrixFloat::iterator it(result->begin()); while(it != result->end()) { // traverse in row_major low and diff matrices MatrixFloat::const_iterator low_it(low->begin()), diff_it(diff->begin()); while(low_it != low->end()) { *it = rng->rand(*diff_it) + *low_it; ++it; ++low_it; ++diff_it; } } } void UniformDistribution::privateLogpdf(const MatrixFloat *x, MatrixFloat *result) { MatrixFloat::iterator result_it(result->begin()); MatrixFloat::const_iterator x_it(x->begin()); while(x_it != x->end()) { log_float one = log_float::one(); log_float current_result = log_float::one(); MatrixFloat::const_iterator low_it(low->begin()), high_it(high->begin()); MatrixFloat::const_iterator diff_it(diff->begin()); while(low_it != low->end() && current_result > log_float::zero()) { if (*low_it <= *x_it && *x_it <= *high_it) current_result *= one / log_float::from_float(*diff_it); else current_result *= log_float::zero(); ++low_it; ++high_it; ++x_it; ++diff_it; } while(low_it != low->end()) { ++low_it; ++high_it; ++x_it; ++diff_it; } *result_it = current_result.log(); ++result_it; } } void UniformDistribution::privateLogcdf(const MatrixFloat *x, MatrixFloat *result) { MatrixFloat::iterator result_it(result->begin()); MatrixFloat::const_iterator x_it(x->begin()); while(x_it != x->end()) { log_float one = log_float::one(); log_float current_result = log_float::one(); MatrixFloat::const_iterator low_it(low->begin()), high_it(high->begin()); MatrixFloat::const_iterator diff_it(diff->begin()); while(low_it != low->end() && current_result > log_float::zero()) { if (*x_it < *low_it) { current_result *= log_float::zero(); } else if (*low_it <= *x_it && *x_it < *high_it) { current_result *= log_float::from_float(*x_it - *low_it) / log_float::from_float(*diff_it); } else { current_result *= log_float::one(); } ++low_it; ++high_it; ++x_it; ++diff_it; } while(low_it != low->end()) { ++low_it; ++high_it; ++x_it; ++diff_it; } *result_it = current_result.log(); ++result_it; } } StatisticalDistributionBase *UniformDistribution::clone() { return new UniformDistribution(low->clone(), high->clone()); } const char *UniformDistribution::luaCtorName() const { return "stats.dist.uniform"; } int UniformDistribution::exportParamsToLua(lua_State *L) { AprilUtils::LuaTable::pushInto(L, low); AprilUtils::LuaTable::pushInto(L, high); return 2; } void UniformDistribution::updateParams() { diff = high->clone(); AprilMath::MatrixExt::BLAS::matAxpy(diff.get(), -1.0f, low.get()); } } april-ann-0.4.1/packages/basics/stats/c_src/uniform_distribution.h000066400000000000000000000040721263004425400253000ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef UNIFORM_DISTRIBUTION_H #define UNIFORM_DISTRIBUTION_H #include "smart_ptr.h" #include "statistical_distribution.h" #include "unused_variable.h" namespace Stats { class UniformDistribution : public StatisticalDistributionBase { AprilUtils::SharedPtr low, high, diff; void updateParams(); protected: virtual void privateSample(Basics::MTRand *rng, Basics::MatrixFloat *result); virtual void privateLogpdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogcdf(const Basics::MatrixFloat *x, Basics::MatrixFloat *result); virtual void privateLogpdfDerivative(const Basics::MatrixFloat *x, Basics::MatrixFloat *result) { UNUSED_VARIABLE(x); AprilMath::MatrixExt::Initializers::matZeros(result); } public: UniformDistribution(Basics::MatrixFloat *low, Basics::MatrixFloat *high); virtual ~UniformDistribution(); virtual StatisticalDistributionBase *clone(); virtual const char *luaCtorName() const; virtual int exportParamsToLua(lua_State *L); }; } #endif // UNIFORM_DISTRIBUTION_H april-ann-0.4.1/packages/basics/stats/lua_src/000077500000000000000000000000001263004425400212055ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/stats/lua_src/pca.lua000066400000000000000000000175501263004425400224630ustar00rootroot00000000000000stats = get_table_from_dotted_string("stats", true) stats.pca = stats.pca or {} stats.zca = stats.zca or {} april_set_doc(stats.pca,{ class = "namespace", summary = "Table with PCA related stuff", }) april_set_doc(stats.zca,{ class = "namespace", summary = "Table with ZCA related stuff", }) local function normalize(m,norm) local norm = norm or m:norm2() m:scal(1/norm) end local function re_orhtonormalize(submatrix,colmatrix,aux) aux:gemv{ alpha=1.0, A=submatrix, X=colmatrix, beta=0.0, trans_A=true } colmatrix:gemv{ alpha=-1.0, A=submatrix, X=aux, beta=1.0, trans_A=false } end ------------------------------------------------------------------------------- -- WARNING IN PLACE OPERATION function stats.pca.center_by_pattern(X) local X=X:clone() local dim = X:dim() assert(#dim == 2, "Expected a bi-dimensional matrix") local M,N = table.unpack(dim) -- U is the mean over all columns local U,auxX = X:sum(2):rewrap(M):scal(1/N) -- X is centered subtracting by -U for i=1,X:dim(2) do auxX=X:select(2,i,auxX):axpy(-1, U) end return X,U end ------------------------------------------------------------------------------- -- NOT IN-PLACE function stats.pca.whitening(X,U,S,epsilon) local epsilon = epsilon or 0.0 local result = matrix(X:dim(1), S:dim(1)) result:gemm{ A=X, B=U, trans_B=false, beta=0, alpha=1} for v,i in S:iterate() do result:select(2,i):scal( 1/math.sqrt(v + epsilon) ) end return result end -- WARNING IN PLACE OPERATION function stats.zca.whitening(X,U,S,epsilon) local aux = stats.pca.whitening(X,U,S,epsilon) X:gemm{ A=aux, B=U, trans_B=true, beta=0, alpha=1 } return X end -- compute PCA mass stats.pca.mass = april_doc{ class = "function", summary = "Computes PCA mass probability given S diagonal sparse matrix", params = { "S diagonal sparse matrix" }, outputs = { "A matrix with probability mass" }, } .. function(S) local acc = 0 local acc_mat = S:clone() for v,i in S:iterate() do acc=acc + v end acc_mat:scal(1.0/acc) return acc_mat end -- show PCA threshold stats.pca.threshold = april_doc{ class = "function", summary = "Computes the PCA threshold for a given mass probability", params = { "The S diagonal sparse matrix with singular values", "A number in [0,1] range indicating the mass probability [optional]. 0.99 by default", }, outputs = { "The number of components", "The threshold singular value", "The accumulated probability", }, } .. function(S,mass) local mass = mass or 0.99 local acc = 0 local sum = S:sum() local acc_th,th,vth = 0,1 for v,i in S:iterate() do acc=acc + v vth,acc_th,th=v,acc,i if acc/sum > mass then break end end assert(acc_th > 0, "The probability mass needs to be larger") return th,vth,acc_th/sum end ------------------------------------------------------------------------------- -- PCA algorithm based on covariance matrix and SVD decomposition the matrix Xc -- must be zero mean centerd for each pattern. Patterns are ordered by rows. stats.pca = april_doc{ class = "function", summary = "Computes PCA using SVD decomposition of covariance matrix", description = { "Data is ordered by rows, features by columns.", "If not centered, the data is centered by columns instead", "that by rows (using stats.pca.center_by_pattern function", "instead of stats.center function)." }, params = { "A 2D matrix", "An [optional] table with 'centered' boolean, by default centered=false", }, outputs = { "U matrix with left singular vectors", "S diagonal sparse matrix with singular values", "VT transpose of right singular vectors", "In case centered=false, fourth result is the center vector [optional]", }, }.. setmetatable(stats.pca, { __call = function(self, Xc, params) local params = get_table_fields( { centered = { type_match = "boolean", default = nil }, }, params) assert(#Xc:dim() == 2, "Expected a bi-dimensional matrix") local center if not params.centered then Xc,center = stats.pca.center_by_pattern(Xc) end local sigma = stats.cov(Xc,{ centered=true }) local U,S,VT = sigma:svd() return U,S,VT,center end }) ------------------------------------------------------------------------------- stats.pca.gs_pca = april_doc{ class = "function", summary = "Computes PCA using GS-PCA (iterative PCA algorithm)", params = { X = "A matrix of MxN, M are numPatterns and N patternSize", K = "The number of components that you want, K <= N", max_iter = "Maximum number of iterations [optional], 10000 by default", epsilon = "A number with the convergence criterion [optional], by default 1e-07", }, outputs = { "The T=V*S=X*U scores matrix, size MxK", "The P loads matrix, or U right eigenvectors matrix, size NxK", "The R residuals matrix, size MxN", "The V left eigenvectors matrix, size MxN", "The S singular values vector, size K", }, } .. -- EXTRACTED FROM: -- Parallel GPU Implementation of Iterative PCA Algorithms, M. Andrecut -- -- http://arxiv.org/pdf/0811.1081.pdf -- -- GS-PCA algorithm -- -- input: X is a MxN matrix, M number of patterns, N pattern size -- input: K is the number of components, K <= N -- input: max_iter is the maximum number of iterations -- input: epsilon is the convergence criterion -- output: T is a MxK scores matrix -- output: P is a NxK loads matrix -- output: R is a MxN residuals matrix -- -- PCA model: X = TLP’ + R function(params) local params = get_table_fields( { X = { isa_match=matrix, mandatory=true }, K = { type_match="number", mandatory=true }, max_iter = { type_match="number", mandatory=true, default=10000 }, epsilon = { type_match="number", mandatory=true, default=1e-07 }, }, params) local X,K,max_iter,epsilon = params.X,params.K,params.max_iter,params.epsilon local M,N = table.unpack(X:dim()) assert(K<=N, "K <= N failed") assert(#X:dim() == 2, "Needs a bi-dimensional matrix") if M < N then print("# Warning, M < N, probably matrix need to be transposed") end local T = matrix(M,K):zeros() -- left eigenvectors local P = matrix(N,K):zeros() -- right eigenvectors local L = matrix(K):zeros() -- eigenvalues local R = X:clone() local U = R:sum(2):scal(1/R:dim(2)):rewrap(R:dim(1)) assert( math.abs(U:sum() / U:size()) < 1e-03, "A zero mean (at each pattern) data matrix is needed") -- GS-PCA local Tcol, Rcol, Pcol, Uslice, Pslice, Tslice, Lk for k=1,K do Tcol = T:select(2,k,Tcol) Rcol = R:select(2,k,Rcol) Pcol = P:select(2,k,Pcol) -- if k > 1 then Uslice = U:slice({1},{k-1}) Pslice = P:slice({1,1},{N,k-1}) Tslice = T:slice({1,1},{M,k-1}) end -- Tcol:copy(Rcol) local a = 0.0 for it=1,max_iter do Pcol:gemv{ alpha=1.0, A=R, X=Tcol, beta=0.0, trans_A=true } if k>1 then re_orhtonormalize(Pslice, Pcol, Uslice) end normalize(Pcol) Tcol:gemv{ alpha=1.0, A=R, X=Pcol, beta=0.0, trans_A=false } if k>1 then re_orhtonormalize(Tslice, Tcol, Uslice) end Lk = Tcol:norm2() normalize(Tcol, Lk) if math.abs(a - Lk) < epsilon*Lk then break end a = Lk end L:set(k, Lk) R:ger{ alpha=-Lk, X=Tcol, Y=Pcol } end local V = T:clone() for k=1,K do T:select(2,k):scal( L:get(k) ) end return T,P,R,V,L end april-ann-0.4.1/packages/basics/stats/lua_src/statistics.lua000066400000000000000000001566711263004425400241220ustar00rootroot00000000000000local alternatives = { right=true, left=true, ["two-sided"] = true } stats = stats or {} -- global environment stats.running = stats.running or {} april_set_doc(stats.running,{ class = "namespace", summary = "Table with running statistics classes", }) stats.dist = stats.dist or {} ------------------------------------------------------------------------------- stats.levels = function(m) local symbols = {} local inv_symbols = {} for i=1,#m do local x = m[i] if not inv_symbols[x] then symbols[#symbols+1],inv_symbols[x] = x,true end end table.sort(symbols) return symbols end stats.hist = function(m, params) local params = get_table_fields({ breaks = { default=13 }, normalize = { type_match="boolean", default=false }, }, params or {}) local breaks = params.breaks local result = matrix(breaks+1, 5) local min = m:min() local max = m:max() local diff = max - min assert(diff > 0, "Unable to compute histogram for given matrix") local x = result:select(2,1):linspace(min, max) local result = result[{ {1,breaks}, ':' }] local x = result:select(2,1) local dx = math.abs( x[2] - x[1] ) local x2 = result:select(2,2):copy(x):scalar_add(0.5*dx) local y = result:select(2,3) local z = result:select(2,4) local z2 = result:select(2,5) local aux = m:clone(): scalar_add(-min): scal(1.0/diff * breaks): floor(): scalar_add(1.0): clamp(-math.huge,breaks): flatten() local y_aux = iterator.zeros():take(breaks):table() for i=1,#aux do local b=aux[i] y_aux[b] = y_aux[b] + 1 end y:copy_from_table(y_aux) local ratio = 1 / (y:sum() * dx) z:copy(y):scal( ratio ) z2:copy(y):scal(1/m:size()) local df = data_frame{ data=result, columns={"bin","key","count","density","ratio"} } return df end stats.ihist = function(m, params) local params = get_table_fields({ symbols = { type_match="table", default={} }, normalize = { type_match="boolean", default=false }, }, params or {}) local symbols = params.symbols if #symbols == 0 then symbols = stats.levels(m) end local inv_symbols = table.invert(symbols) assert(#symbols > 0, "Unable to compute histogram for given matrix") local x = matrix(#symbols):linspace() local y = matrix(#symbols) local z = matrix(#symbols) local y_aux = iterator.zeros():take(#symbols):table() for i=1,#m do local v=m[i] local b = inv_symbols[v] y_aux[b] = y_aux[b] + 1 end y:copy_from_table(y_aux) z:copy(y):scal(1/m:size()) return data_frame{ data={ bin=x, key=symbols, count=y, ratio=z }, columns={ "bin","key","count","ratio" } } end ------------------------------------------------------------------------------- do local function bisect(dist, x, y, log_p, EPSILON, MAX) local i,m = 0,nil repeat m = 0.5 * (x + y) local aux = dist:logcdf(matrix(1,1,{m}))[1] if (y-x < EPSILON) or math.abs(aux - log_p) < EPSILON then return m elseif aux > log_p then y = m else x = m end i=i+1 until i == MAX fprintf(io.stderr, "Warning!!! bisect maximum number of iterations\n") return m end stats.dist.quantile = function(dist, p, EPSILON, MAX) assert(dist:size() == 1, "Only implemented for univariate distributions") assert(0 < p and p < 1.0, "The probabilbity should be in range (0,1)") local log_p = math.log(p) local a = -1.0 local b = 1.0 while true do local cdfa = dist:logcdf(matrix(1,1,{a}))[1] local cdfb = dist:logcdf(matrix(1,1,{b}))[1] if cdfa < log_p and cdfb > log_p then break end if cdfa > log_p then a = a*10 end if cdfb < log_p then b = b*10 end end return bisect(dist, a, b, log_p, EPSILON or 1e-08, MAX or 10000) end end local tbl,methods = class("stats.hypothesis_test") april_set_doc(tbl, { class = "class", summary = "Result of hypotheses test", }) stats.hypothesis_test = tbl tbl.constructor = april_doc{ class = "method", summary = "Constructor given a pivot and the H0 stats.dist instance", } .. function(self, pivot, h0_dist, true_dist) assert(pivot and h0_dist and true_dist, "Needs a pivot, H0 distribution and true distribution") self.P = matrix(1,1,{pivot}) self.h0_dist = h0_dist self.true_dist = true_dist end methods.pvalue = april_doc{ class = "method", summary = "Returns the p-value of the pivot for the H0 distribution", } .. function(self, alternative) local alternative = alternative or "two-sided" april_assert(alternatives[alternative], "Unknown alternative value %s", alternative) local P = self.P local h0_dist = self.h0_dist local a,b = 0.0,0.0 local two_sided = (alternative=="two-sided") if two_sided or alternative == "left" then a = math.exp( h0_dist:logcdf(-P)[1] ) if two_sided and a > 0.5 then a = 1.0 - a end end if two_sided or alternative == "right" then b = 1.0 - math.exp( h0_dist:logcdf(P)[1] ) if two_sided and b > 0.5 then b = 1.0 - b end end return a + b end methods.pivot = april_doc{ class = "method", summary = "Returns the test pivot", } .. function(self) return self.P:get(1,1) end methods.ci = april_doc { class = "method", summary = "Returns the confidence interval of the true distribution", } .. function(self, confidence, alternative) local alternative = alternative or "two-sided" april_assert(alternatives[alternative], "Unknown alternative value %s", alternative) local true_dist = self.true_dist local alpha = 1.0 - (confidence or 0.95) local two_sided = (alternative=="two-sided") if two_sided then alpha = alpha * 0.5 end local a = -math.huge local b = math.huge if two_sided or alternative == "right" then a = stats.dist.quantile(true_dist, alpha) end if two_sided or alternative == "left" then b = stats.dist.quantile(true_dist, 1.0 - alpha) end return a,b end class.extend_metamethod(tbl, "__tostring", function(self) local a,b = self:ci(0.95) local tbl = { "pivot= ", tostring(self:pivot()), "\np-value= ", tostring(self:pvalue()), "\nCI(95%)= [", tostring(a), ", ", tostring(b), "]" } return table.concat(tbl) end) ----------------------------------------------------------------------------- local mop = matrix.op local sdiag = matrix.sparse.diag -- x must be a 2D matrix local function center(x,mu) local x_dim = x:dim() local N = x_dim[1] if #x_dim == 1 then mu = mu or x:sum()/N return x - mu, mu else mu = mu or x:sum(1):scal(1/N) if mu:size() == 1 then return x - mu, mu else return matrix.ext.broadcast(bind(x.axpy, nil, -1.0), x, mu), mu end end end stats.standardize = april_doc{ class = "function", summary = "Standardize data to have zero-mean one-variance", description = "Data is ordered by rows, features by columns.", params = { "A 2D matrix", "A table with center and/or scale matrices [optional]"}, outputs = { "Another new allocated matrix", "Center matrix", "Scale matrix" }, } .. function(x, params) local params = params or {} assert(#x:dim() == 2, "Needs a 2D matrix") local N = x:dim(1) local mu,sigma = params.center,params.scale if not sigma then local sigma2,mup = stats.var(x,1) mu = mu or mup sigma = sigma2:sqrt() elseif not mu then mu = stats.amean(x,1) end if mu:size() == 1 then x = x - mu:get(table.unpack(mu:dim())) else x = matrix.ext.broadcast(bind(x.axpy, nil, -1.0), x, mu) end if sigma:size() == 1 then x = x / sigma:get(table.unpack(sigma:dim())) else x = matrix.ext.broadcast(x.cmul, x, 1/sigma) end return x,mu,sigma end stats.center = april_doc{ class = "function", summary = "Centers data by rows, computing mean of every column", description = "Data is ordered by rows, features by columns.", params = { "A 2D matrix", "Center matrix" }, outputs = { "Another new allocated matrix", "The center matrix" }, } .. function(x,mu) assert(#x:dim() == 2, "Needs a 2D matrix") return center(x,mu) end stats.var = april_doc{ class = "function", summary = "Computes variance over a dimension", params = { "A matrix", "A dimension number [optional].", }, outputs = { "A new allocated matrix or a number if not dim given", "The mean used to center the data" }, } .. function(x,dim) local mean = stats.amean(x,dim) local x,x_row,sz = x:clone() if dim then sz = x:dim(dim) for i=1,sz do x_row=x:select(dim,i,x_row):axpy(-1.0, mean) end else x:scalar_add(-mean) sz = x:size() end return x:pow(2):sum(dim)/(sz-1),mean end stats.std = april_doc{ class = "function", summary = "Computes standard deviation over a dimension", params = { "A matrix", "A dimension number [optional].", }, outputs = { "A new allocated matrix or a number if not dim given", "The mean used to center the data", }, } .. function(x,dim) local result,center = stats.var(x,dim) if dim then result:sqrt() else result = math.sqrt(result) end return result,center end stats.cov = april_doc{ class = "function", summary = "Compute covariance matrix of two matrices.", description = "Data is ordered by rows, features by columns.", params = { "A 2D matrix or a vector (x)", "Another 2D matrix or a vector (y)", "An [optional] table with 'centered' boolean, 'true_mean' boolean", }, outputs = { "Covariance matrix" } } .. april_doc{ class = "function", summary = "Compute covariance matrix.", description = "Data is ordered by rows, features by columns.", params = { "A 2D matrix or a vector (x)", "An [optional] table with 'centered' boolean, 'true_mean' boolean", }, outputs = { "Covariance matrix", "The x center vector if not centered flag [optional]", "The y center vector if not centered flag [optional]" } } .. function(x,...) local y,params = ... if type(y) == "table" or not y then y,params = x,y end collectgarbage("collect") assert(class.is_a(x,matrix) and class.is_a(y,matrix), "Needs at least two matrix arguments") local params = get_table_fields( { centered = { type_match = "boolean", default = nil }, true_mean = { type_match = "boolean", default =nil }, }, params) assert(not params.true_mean or params.centered, "true_mean=true is mandatory of centered=true") local x_dim,y_dim = x:dim(),y:dim() assert((#x_dim <= 2) and (#y_dim <= 2), "Needs 2D matrices or vectors") assert(x_dim[1] == y_dim[1] and x_dim[2] == y_dim[2], "Require same shape matrices") local mu_x,mu_y local N,M = table.unpack(x_dim) if not params.centered then local oldx = x x,mu_x = center(x) if rawequal(xold,y) then y,mu_y = x,mu_x else y,mu_y = center(y) end end local sz = N-1 if params.true_mean then sz = N end return (x:transpose() * y):scal(1/sz):rewrap(M or 1,M or 1),mu_x,mu_y end stats.cor = april_doc{ class = "function", summary = "Compute correlation matrix of two matrices.", description = "Data is ordered by rows, features by columns.", params = { "A 2D matrix or a vector (x)", "Another 2D matrix or a vector (y)", "An [optional] table with 'centered' boolean", }, outputs = { "Correlation matrix" } } .. april_doc{ class = "function", summary = "Compute correlation matrix.", description = "Data is ordered by rows, features by columns.", params = { "A 2D matrix or a vector (x)", "An [optional] table with 'centered' boolean", }, outputs = { "Correlation matrix", "The x center vector if not centered flag [optional]", "The y center vector if not centered flag [optional]" } } .. function(x,...) local y,params = ... if type(y) == "table" or not y then y,params = x,y end local params = params or {} local mu_x,mu_y if not params.centered then local xold = x x,mu_x = center(x) if rawequal(xold,y) then y,mu_y = x,mu_x else y,mu_y = center(y) end end local function cstd(m) return sdiag((m^2):sum(1):scal(1/(m:dim(1)-1)):sqrt():div(1):squeeze()) end local sigma = stats.cov(x,y,{ centered=true }) local sx = cstd(x) local sy = rawequal(x,y) and sx or cstd(y) return sx * sigma * sy,mu_x,mu_y end stats.acf = april_doc{ class = "function", summary = "Compute auto-correlation of one or more series.", description = "Data is ordered by rows, series by columns.", params = { "A 2D matrix or a vector (x)", { "An [optional] table with 'lag_max' number,", "'lag_step' number, 'lag_start' number,", "'cor' function (one of stats.cor [default], stats.cov)." }, }, outputs = { "A matrix with auto-correlation of the series", "A matrixInt32 with lag values" }, } .. function(x,params) assert(class.is_a(x, matrix), "Needs a matrix argument") local x_dim = x:dim() assert(x_dim[1] > 1, "Needs two or more rows") assert(#x_dim <= 2, "Requires 2D matrix or a vector") local params = get_table_fields( { lag_max = { type_match = "number", default = x_dim[1]-2 }, lag_step = { type_match = "number", default = 1 }, lag_start = { type_match = "number", default = 1 }, cor = { type_match = "function", default = stats.cor }, }, params) local lag_start,lag_max,lag_step = params.lag_start,params.lag_max,params.lag_step if #x_dim == 1 then x = x:rewrap(x:size(),1) end local N,M = x_dim[1],x:dim(2) local result = matrix(math.floor((lag_max + 1 - lag_start) / lag_step), M) local acf_func = params.cor for j=1,M do local i=1 for lag = lag_start, lag_max, lag_step do local a,b = x({1,N-lag},j), x({lag+1,N},j) local y = acf_func(a,b) result[{i,j}] = y i=i+1 end end local lags = matrixInt32(iterator(range(lag_start,lag_max,lag_step)):table()) return result,lags end -- arithmetic mean of a matrix stats.amean = april_doc{ class = "function", summary = "Computes the arithmetic mean over a given dimension", params = { "A matrix", "A dimension number [optional]", }, outputs = { "A matrix if given a dimension, a number otherwise", }, } .. function(m, D) local r = m:sum(D) if D then return r:scal(1/m:dim(D)) else return r/m:size() end end -- geometric mean of a matrix with positive elements stats.gmean = april_doc{ class = "function", summary = "Computes the geometric mean over a given dimension", params = { "A matrix with positive elements", "A dimension number [optional]", }, outputs = { "A matrix if given a dimension, a number otherwise", }, } .. function(m, D) local r = mop.log(m):sum(D) if D then return r:scal(1.0/m:dim(D)):exp() else return math.exp(r / m:size()) end end -- harmonic mean of a matrix with non-zero elements stats.hmean = april_doc{ class = "function", summary = "Computes the harmonic mean over a given dimension", params = { "A matrix with non-zero elements", "A dimension number [optional]", }, outputs = { "A matrix if given a dimension, a number otherwise", }, } .. function(m, D) local r = (1 / m):sum(D) if D then return r:div( m:dim(D) ) else return m:size() / r end end ----------------------------------------------------------------------------- local mean_var,mean_var_methods = class("stats.running.mean_var") stats.running.mean_var = mean_var -- global environment april_set_doc(stats.running.mean_var, { class = "class", summary = "Class to compute mean and variance", description ={ "This class is designed to compute mean and variance", "by adding a sequence of data values (or tables)", }, }) ----------------------------------------------------------------------------- april_set_doc(stats.running.mean_var, { class = "method", summary = "Constructor", description ={ "Constructor of a mean_var object", }, params = { "A number [optional]. If given, the assumed_mean approach", "will be followed.", }, outputs = { "A mean_var object" }, }) function mean_var:constructor() self:clear() end ----------------------------------------------------------------------------- mean_var_methods.clear = april_doc{ class = "method", summary = "Re-initializes the object" } .. function(self) self.old_m = 0 self.old_s = 0 self.new_m = 0 self.new_s = 0 self.N = 0 return self end ----------------------------------------------------------------------------- mean_var_methods.add = april_doc{ class = "method", summary = "Adds one value", params = { "A number", }, outputs = { "The caller mean_var object (itself)" }, } .. april_doc{ class = "method", summary = "Adds a sequence of values", params = { "A Lua table (as array of numbers)", }, outputs = { "The caller mean_var object (itself)" }, } .. april_doc{ class = "method", summary = "Adds a sequence of values from an iterator function", params = { "An iterator function", }, outputs = { "The caller mean_var object (itself)" }, } .. function (self, ...) local arg = { ... } local v = arg[1] if type(v) == "table" then return self:add(ipairs(v)) elseif type(v) == "function" then local f,s,v = table.unpack(arg) local tmp = table.pack(f(s,v)) while tmp[1] ~= nil do v = tmp[1] if #tmp > 1 then table.remove(tmp,1) end for _,aux in ipairs(tmp) do self:add(aux) end tmp = table.pack(f(s,v)) end elseif type(v) == "number" then self.N = self.N + 1 -- see Knuth TAOCP vol 2, 3rd edition, page 232 if self.N == 1 then self.old_m,self.new_m = v,v self.old_s = 0.0 else local old_diff = (v - self.old_m) self.new_m = self.old_m + old_diff/self.N self.new_s = self.old_s + old_diff*(v - self.new_m) -- setup for next iteration self.old_m = self.new_m self.old_s = self.new_s end else error("Incorrect type="..type(v)..". Expected number, table or function") end return self end ----------------------------------------------------------------------------- mean_var_methods.size = april_doc{ class = "method", summary = "Return the number of elements added", outputs = { "The number of elements added" }, } .. function(self) return self.N end ----------------------------------------------------------------------------- mean_var_methods.compute = april_doc{ class = "method", summary = "Computes mean and variance of given values", outputs = { "A number, the mean of the data", "A number, the variance of the data", }, } .. function(self) return self.new_m,self.new_s/(self.N-1) end -------------------- -- Confusion Matrix -- ----------------- local confus_matrix,confus_matrix_methods = class("stats.confusion_matrix") stats.confusion_matrix = confus_matrix -- global environment april_set_doc(stats.confusion_matrix, { class = "class", summary = "class for computing confusion matrix and classification metrics", description ={ "This class is designed to store a confusion matrix and compute main metrics for classification stats", }, }) april_set_doc(stats.confusion_matrix, { class ="method", summary = "Constructor of confusion matrix.", description ={ "This class is designed to store a confusion matrix and compute main metrics for classification stats", }, params = { "A number of classes [mandatory].", "A table of size num_classes, with the elements on the set.", outputs = {"A confusion_matrix object"} } }) function confus_matrix:constructor(num_classes, class_dict) local confusion = {} for i = 1, num_classes do local t = {} for j = 1, num_classes do table.insert(t, 0) end table.insert(confusion, t) end if (class_dict) then --assert(#class_dict == num_classes, "The map table doesn't have the exact size") map_dict = class_dict --for i, v in ipairs(map_table) do -- map_dict[v] = i --end end self.num_classes = num_classes self.confusion = confusion self.hits = 0 self.misses = 0 self.samples = 0 -- FIXME: IS NOT POSSIBLE USE MAP DICT AS NIL self.map_dict = map_dict or false end confus_matrix_methods.clone = april_doc{ class ="method", summary = "Clone onstructor of confusion matrix.", description ={ "This class is designed to store a confusion matrix and compute main metrics for classification stats", }, params = { } } .. function(self) local obj = table.deep_copy(self) return class_instance(obj, stats.confusion_matrix) end confus_matrix_methods.reset = april_doc{ class = "method", summary = "Reset to 0 all the counters", } .. function(self) for i = 1, self.num_classes do local t = {} for j = 1, self.num_classes do self.confusion[i][j] = 0 end end self.hits = 0 self.misses = 0 self.samples = 0 end function confus_matrix_methods:checkType(clase) return type(clase) == "number" and clase >= 1 and clase <= self.num_classes or false end --------------------------------------------- function confus_matrix_methods:addSample(pred, gt) if self.map_dict then pred = map_dict[pred] gt = map_dict[gt] end if not self:checkType(pred) or not self:checkType(gt) then printf("Error %f %f, %d\n", pred, gt, self.samples) return --error("The class is not correct") end if gt == pred then self.hits = self.hits + 1 else self.misses = self.misses + 1 end self.samples = self.samples + 1 self.confusion[gt][pred] = self.confusion[gt][pred] + 1 end ------------------------------------------------ confus_matrix_methods.printConfusionRaw = april_doc{ class = "method", summary = "Print the counters for each class", } .. function(self) for i,v in ipairs(self.confusion) do print(table.concat(v, "\t")) end end confus_matrix_methods.printConfusion = april_doc{ class = "method", summary = "Print the counters for each class and PR and RC", params = { "A num_classes string table [optional] with the tags of each class",} } .. function(self, tags) local total_pred = {} printf("\t|\t Predicted ") for i = 1, self.num_classes do printf("\t\t") end printf("|\n") printf("______\t|") for i = 1, self.num_classes do printf("\t___\t") end printf("\t___\t\t|\n") for i,v in ipairs(self.confusion) do local tag = i if tags then tag = tags[i] end printf("%s\t|\t", tag) local recall, hits, total = self:getRecall(i) printf("%s\t|\t %d/%d %0.4f\t|\n", table.concat(v, "\t|\t"), hits, total, recall) end printf("______\t|") for i = 1, self.num_classes do printf("\t___\t") end printf("\t___\t|\n") printf("\t\t|") for i = 1, self.num_classes do printf("\t%0.4f\t|", self:getPrecision(i)) end local acc, hits, total = self:getAccuracy() printf("\t%d/%d %0.4f\t|\n", hits, total, acc) end confus_matrix_methods.tostring = function(self) local total_pred = {} local t = {} table.insert(t, "\t|\t Predicted ") for i = 1, self.num_classes do table.insert(t, ("\t\t")) end table.insert(t,"|\n") table.insert(t, "______\t|") for i = 1, self.num_classes do table.insert(t, "\t___\t") end table.insert(t, "\t___\t\t|\n") for i,v in ipairs(self.confusion) do local tag = i table.insert(t, string.format("%s\t|\t", tag)) local recall, hits, total = self:getRecall(i) table.insert(t, string.format("%s\t|\t %d/%d %0.4f\t|\n", table.concat(v, "\t|\t"), hits, total, recall)) end table.insert(t, "______\t|") for i = 1, self.num_classes do table.insert(t, "\t___\t") end table.insert(t, "\t___\t|\n") table.insert(t, "\t\t|") for i = 1, self.num_classes do table.insert(t, string.format("\t%0.4f\t|", self:getPrecision(i))) end local acc, hits, total = self:getAccuracy() table.insert(t, string.format("\t%d/%d %0.4f\t|\n", hits, total, acc)) return table.concat(t,"") end function confus_matrix_methods:printInf() printf("Samples %d, hits = %d, misses = %d (%0.4f)\n", self.samples, self.hits, self.misses, self.misses/self.total) for i = 1, self.num_classes do print("Predicted %d", i) local total = 0 for j = 1, self.num_classes do total = total + self.confusion[i][j] end for j = 1, self.num_classes do printf(" - class %d %d/%d (%0.4f)", j, self.confusion[i][j], total, self.confusion[i][j]/total) end print() end end -------------------------------------------- -- Datasets and Tables Iterators -------------------------------------------- function stats.confusion_matrix.twoTablesIterator(table_pred, table_gt) local i = 0 local n = #table_pred return function() i = i+1 if i <= n then return table_pred[i],table_gt[i] end end end ---------------------------------------------------------------- function stats.confusion_matrix.oneTableIterator(typeTable) local i = 0 local n = #typeTable return function() i = i+1 if i <= n then return typeTable[i][1], typeTable[i][2] end end end -------------------------------------------------------------- function stats.confusion_matrix.oneDatasetIterator(typeDataset) local i = 0 local n = typeDataset:numPatterns() return function() i = i+1 if i <= n then return typeDataset:getPattern(i)[1], typeDataset:getPattern(i)[2] end end end function stats.confusion_matrix.twoDatasetsIterator(predDs, gtDs) local i = 0 assert(predDs:numPatterns() == gtDs:numPatterns(), "Datasets doesn't have the same size") local n = predDs:numPatterns() return function() i = i+1 if i <= n then return predDs:getPattern(i)[1], gtDs:getPattern(i)[1] end end end --------------------------------------------------------------------------------------------------------- confus_matrix_methods.addData = april_doc{ class = "method", summary = "Add the info of Predicted and Ground Truth set", description = { "This class recieves two tables with the predicted class and the", "ground truth of that class.", "Also it can recieve a iterator function that returns two elements:", "predicted sample and groundtruth sample" }, params = { "This parameter can be a table of the predicted tags or an iterator function", "This parameter is used if the first parameter is the Predicted table, otherwise it should be nil"}, } .. function(self, param1, param2) local iterator if type(param1) == 'matrix' then return self:addDataMatrix(param1, param2) end if( type(param1) == 'function') then iterator = param1 assert(param2 == nil) elseif (type(param1) == 'dataset') then iterator = stats.confusion_matrix.twoDatasetsIterator(param1, param2) else iterator = stats.confusion_matrix.twoTablesIterator(param1, param2) assert(type(param1) == "table" and type(param2) == "table", "The type of the params is not correct") assert(#param1, #param2, "The tables does not have the same dimension") end for pred, gt in iterator do self:addSample(pred, gt) end end --[[ function confus_matrix_methods.addDataMatrix(self, m1, m2) assert(#m1:dim() == 1, "M1 does not have one dimension") assert(#m2:dim() == 1, "M2 does not have dimension") assert(m1:dim(1) == m2:dim(1), "Dimensions did not match") -- Compute hits -- self.samples = m1:dim(1) self.hits = m1:eq(m2):count_ones() for gt = 1,self.num_classes do for pred = 1, self.num_classes do b_m1 = m1:eq(gt) b_m2 = m2:eq(pred) self.confusion[gt][pred] = b_m1:land(b_m2):count_ones() end end end ]] function confus_matrix_methods.addDataMatrix(self, target, pred) for i=1,#target do local t_c = target[i] local p_c = pred[i] local row = self.confusion[t_c] row[p_c] = row[p_c] + 1 end end function confus_matrix_methods.combine(self, conf1) assert(conf1.num_classes == self.num_classes) self.samples = self.samples + conf1.samples self.hits = self.hits + conf1.hits for gt = 1,self.num_classes do for pred = 1, self.num_classes do self.confusion[gt][pred] = self.confusion[gt][pred] + conf1.confusion[gt][pred] end end end --------------------------------------------------------------- confus_matrix_methods.getError = april_doc{ class = "method", summary = "Return the global classification error (misses/total)", outputs = { "The global classification error." }, } .. function(self) return self.misses/self.samples, self.misses, self.samples end confus_matrix_methods.getWeightedError = april_doc{ class = "method", summary = "Return the classification error weighted by given values", params = {"A table of size weight"}, outputs = { "The global classification error." }, } .. function(self, weights) local totalError = 0.0 for i,w in ipairs(weights) do totalError = totalError+(1-w*self:getRecall(i)) end return totalError end confus_matrix_methods.getAvgError = april_doc{ class = "method", summary = "Return the average error.", outputs = { "The average classification error." }, } .. function(self, weights) local totalError = 0.0 local w = 1.0/self.num_classes local i for i = 1, self.num_classes do totalError = totalError+(1-self:getRecall(i)) end return totalError*w end confus_matrix_methods.getAccuracy = april_doc{ class = "method", summary = "Return the accuracy (hits/total)", outputs = { "The global accuracy." }, } .. function(self) return self.hits/self.samples, self.hits, self.samples end -------------------------------------------------------------- function confus_matrix_methods:getConfusionTables() return self.confusion end ------------------------------------------------------------ -- confus_matrix_methods.getPrecision = april_doc{ class = "method", summary = "Return the accuracy (hits/total)", params = {"The index of the class for computing the Precision"}, outputs = { "The selected class Precision." }, } .. function(self, tipo) local tp = 0 local den = 0 -- Moving by columns for i=1, self.num_classes do v = self.confusion[i][tipo] if i == tipo then tp = v end den = den + v end if den == 0 then return 1, tp, den end return tp/den, tp, den end confus_matrix_methods.getMultiPrecision = april_doc{ class = "method", summary = "Return the precision of joined classes", params = {"The indexes of the joined classes"}, outputs = { "The selected classes Precision." }, } .. function(self, cls) local tp = 0 local den = 0 -- Moving by columns for i=1, self.num_classes do local iscorrect = false local values = 0 for t, tipo in pairs(cls) do v = self.confusion[i][tipo] values = values + v if i == tipo then iscorrect = true end end if iscorrect then tp = tp + values end den = den + values end if den == 0 then return 1, tp, den end return tp/den, tp, den end confus_matrix_methods.getRecall = april_doc{ class = "method", summary = "Return the accuracy (hits/total)", params = {"The index of the class for computing the Recall"}, outputs = { "The selected class Recall." }, } .. function(self, tipo) local tp = 0 local den = 0 -- Moving by columns for j=1, self.num_classes do v = self.confusion[tipo][j] if j == tipo then tp = v end den = den + v end if den == 0 then return 1, tp, den end return tp/den, tp, den end confus_matrix_methods.getMultiRecall = april_doc{ class = "method", summary = "Return the accuracy (hits/total)", params = {"Index of the joined class for the Recall"}, outputs = { "The selected class Recall." }, } .. function(self, cls) local tp = 0 local den = 0 print ("joining") -- Moving by columns for j=1, self.num_classes do local iscorrect = false local values = 0 for t, tipo in ipairs(cls) do local v = self.confusion[tipo][j] values = values + v if tipo == j then iscorrect = true end end if iscorrect then tp = tp + values end den = den + values end if den == 0 then return 1, tp, den end return tp/den, tp, den end confus_matrix_methods.getFMeasure = april_doc{ class = "method", summary = "Return the accuracy (hits/total)", params = {"The index of the class for computing the Precision"}, outputs = { "The selected class Precision." }, } .. function(self, tipo, beta) local nBeta = beta or 1 nBeta = nBeta*nBeta local PR = self:getRecall(tipo) local RC = self:getPrecision(tipo) return (1+nBeta)*(PR*RC)/(nBeta*PR+RC) end ------------------------------------------------------- confus_matrix_methods.clearGTClass = april_doc{ class = "method", summary = "Clear the counters of one class", description= "This function is useful when you don't want to count determinated class.", params = {"The index of the class to be clear"}, } .. function(self, tipo) local n_samples = 0 local hits = 0 local misses = 0 -- Moving by columns for i=1, self.num_classes do n_samples = n_samples + self.confusion[tipo][i] if i == tipo then hits = self.confusion[tipo][i] else misses = misses + self.confusion[tipo][i] end self.confusion[tipo][i] = 0 end self.samples = self.samples - n_samples self.hits = self.hits - hits self.misses = self.misses - misses end confus_matrix_methods.clearClass = april_doc{ class = "method", summary = "Clear the counters of one pair classes", description= "This function is useful when you don't want to count determinated pair class.", params = {"The index of the Ground Truth class.","The index of the predicted class"}, } .. function(self, gt, pred) local samples = self.confusion[gt][pred] local n_samples = 0 if gt == pred then self.hits = self.hits - samples else self.misses = self.misses - samples end self.confusion[gt][pred] = 0 self.samples = self.samples - samples end confus_matrix_methods.clearPredClass = april_doc{ class = "method", summary = "Clear the counters of one class", description= "This function is useful when you don't want to count determinated class.", params = {"The index of the class to be clear"}, } .. function(self, tipo) local n_samples = 0 -- Moving by Rows for i=1, self.num_classes do n_samples = n_samples + self.confusion[i][tipo] self.confusion[i][tipo] = 0 end self.samples = self.samples - n_samples end ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- stats.perm = {} local perm = function(self,params,...) local params = get_table_fields( { samples = { mandatory = true, type_match="table" }, R = { type_match = "number", mandatory = true }, statistic = { type_match = "function", mandatory = true }, k = { type_match = "number", mandatory = false, default = 1 }, verbose = { mandatory = false }, ncores = { mandatory = false, type_match = "number", default = 1 }, seed = { mandatory = false, type_match = "number" }, random = { mandatory = false, isa_match = random }, paired = { mandatory = false, type_match = "boolean" }, }, params) assert(not params.seed or not params.random, "Fields 'seed' and 'random' are forbidden together") local extra = table.pack(...) local paired = params.paired local samples = params.samples local repetitions = params.R local statistic = params.statistic local ncores = params.ncores local seed = params.seed local rnd = params.random or random(seed) local k = params.k local result = matrix.MMapped(repetitions, k):zeros() local joined = matrix.join(1, samples) local joined_size = joined:size() local sizes = iterator(samples):call("size"):table() local get_row,N -- resample function executed in parallel using parallel_foreach local last_i = 0 local rnd_matrix assert(not paired, "Paired option is not fully implemented") if paired then for i=2,#sizes do assert(sizes[i-1] == sizes[i], "Found different sizes in paired test") end local M = sizes[1] local sub_indices = matrix.ext.repmat(matrixInt32(M):linspace(), #sizes) local indices = {} for i=1,#sizes do for j=1,M do indices[#indices+1] = i-1 end end rnd_matrix = function() local shuf = rnd:shuffle(indices) local m = matrixInt32(shuf):scal(M):axpy(1.0, sub_indices) return m end else local indices = iterator.range(joined_size):table() rnd_matrix = function() return matrixInt32(joined:size(), rnd:shuffle(indices)) end end local permute = function(i, id) collectgarbage("collect") -- this loop allows to synchronize the random number generator, allowing to -- produce the same exact result independently of ncores value for j=last_i+1,i-1 do rnd_matrix() end last_i = i -- local new_samples_idx = rnd_matrix() local new_samples_joined = joined:index(1,new_samples_idx) local new_samples = {} local acc = 1 for i=1,#sizes do new_samples[i] = new_samples_joined[{ {acc, acc+sizes[i]-1} }] acc = acc + sizes[i] end local r = table.pack( statistic(multiple_unpack(new_samples, extra)) ) april_assert(#r == k, "Unexpected number of returned values in statistic, expected %d, found %d", k, #r) result[i]:copy_from_table(r) if (not id or id == 1) and params.verbose and i % 20 == 0 then fprintf(io.stderr, "\r%3.0f%%", i/repetitions*100) io.stderr:flush() end end local ok,msg = xpcall(parallel_foreach, debug.traceback, ncores, repetitions, permute) result = result:clone() if not ok then error(msg) end if params.verbose then fprintf(io.stderr, " done\n") end return result end setmetatable(stats.perm, { __call = perm }) stats.perm.pvalue = function(perm_result, observed, idx, alternative) assert(not alternative or alternative == "two-sided") local ge_observed = perm_result:select(2, idx or 1):lt(observed):count_zeros() local pvalue = ge_observed / perm_result:dim(1) return (pvalue<0.5) and pvalue or (1.0 - pvalue) end ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- stats.boot = {} april_set_doc(stats.boot, { class = "function", summary = "Produces a bootstrap resampling table", description= { "This function is useful to compute confidence intervals", "by using bootstrapping technique. The function receives", "the population size and a function which returns statistics", "of a sample.", "A table with the computation of the post-process function", "for every repetition will be returned.", }, params = { size = "Population size, it can be a table with several sizes", resample = "Resample value [optional] by default it is 1", R = "Number of repetitions, recommended minimum of 1000", statistic = { "A function witch receives as many matrixInt32 (with", "sample indices) as given number of population sizes", "and computes statistics (k>=1 statistics) over", "the sample.", }, k = "Expected number of returned values in statistic function [optional], by default it is 1", verbose = "True or false", ncores = "Number of cores [optional], by default it is 1", seed = "A random seed [optional]", random = "A random numbers generator [optional]", ["..."] = "Second and beyond parameters are extra arguments for statistic function.", }, outputs = { "A matrix with Rxk, being R repetitions." }, }) -- self is needed because of __call metamethod, but it will be ignored local function boot(self,params,...) local params = get_table_fields( { size = { mandatory = true, }, resample = { mandatory = false, type_match = "number", default = 1 }, R = { type_match = "number", mandatory = true }, statistic = { type_match = "function", mandatory = true }, k = { type_match = "number", mandatory = false, default = 1 }, verbose = { mandatory = false }, ncores = { mandatory = false, type_match = "number", default = 1 }, seed = { mandatory = false, type_match = "number" }, random = { mandatory = false, isa_match = random }, }, params) assert(not params.seed or not params.random, "Fields 'seed' and 'random' are forbidden together") local extra = table.pack(...) local size = params.size local resample = params.resample local repetitions = params.R local statistic = params.statistic local ncores = params.ncores local seed = params.seed local rnd = params.random or random(seed) local tsize = type(size) local k = params.k local result = matrix.MMapped(repetitions, k):zeros() assert(resample > 0.0 and resample <= 1.0, "Incorrect resample value") assert(tsize == "number" or tsize == "table", "Needs a 'size' field with a number or a table of numbers") if tsize == "number" then size = { size } end local resamples = {} for i=1,#size do resamples[i] = math.round(size[i]*resample) assert(resamples[i] > 0, "Resample underflow, increase resample value") end local get_row,N -- resample function executed in parallel using parallel_foreach local last_i = 0 local rnd_matrix = function(sz,rsmpls) return matrixInt32(rsmpls):uniform(1,sz,rnd) end local resample = function(i, id) collectgarbage("collect") -- this loop allows to synchronize the random number generator, allowing to -- produce the same exact result independently of ncores value for j=last_i+1,i-1 do for r=1,#size do for k=1,resamples[r] do rnd:randInt(size[r]-1) end end end last_i = i -- local sample = iterator.zip(iterator(size), iterator(resamples)):map(rnd_matrix):table() local r = table.pack( statistic(multiple_unpack(sample, extra)) ) april_assert(#r == k, "Unexpected number of returned values in statistic, expected %d, found %d", k, #r) result[i]:copy_from_table(r) if (not id or id == 1) and params.verbose and i % 20 == 0 then fprintf(io.stderr, "\r%3.0f%%", i/repetitions*100) io.stderr:flush() end end local ok,msg = xpcall(parallel_foreach, debug.traceback, ncores, repetitions, resample) result = result:clone() if not ok then error(msg) end if params.verbose then fprintf(io.stderr, " done\n") end return result end setmetatable(stats.boot, { __call = boot }) ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- stats.boot.ci = april_doc{ class = "function", summary = "Returns the extremes of a confidence interval", description= { "This function returns the extremes of a confidence interval", "given the result of stats.boot function and the confidence value.", "It could compute the interval over a slice of the table.", "This functions uses stats.boot.percentile() to compute the interval.", }, params = { "The result of stats.boot function.", "The confidence [optional], by default it is 0.95.", "The statistic index for which you want compute the CI [optional], by default it is 1", }, outputs = { "The left limit of the interval", "The right limit of the interval", }, } .. -- returns the extremes of the interval function(data, confidence, index, alternative) local alternative = alternative or "two-sided" april_assert(alternatives[alternative], "Unknown alternative value %s", alternative) local confidence,index = confidence or 0.95, index or 1 assert(confidence > 0 and confidence < 1, "Incorrect confidence value, it must be in range (0,1)") local Pa = 0.0 local Pb = 1.0 if alternative == "two-sided" then Pa = (1.0 - confidence)*0.5 Pb = 1.0 - Pa elseif alternative == "left" then Pb = confidence else Pa = 1.0 - confidence end return stats.boot.percentile(data, { Pa, Pb }, index) end stats.boot.percentile = april_doc{ class = "function", summary = "Returns a percentile value from bootstrap output following NIST method", description= { "This function returns a percentile value", "given the result of stats.boot function and the percentile number.", "It could compute the percentile over a slice of the table.", }, params = { "The result of stats.boot function.", "The percentile [optional], by default it is 0.5. It can be a table of several percentiles", "The statistic index for which you want compute the percentile [optional], by default it is 1", }, outputs = { "The percentile value", "Another pecentil value", "..." }, } .. -- returns the percentile function(data, percentile, index) if type(percentile) ~= "table" then percentile= { percentile } end return stats.percentile(data:select(2, index or 1), table.unpack(percentile)) end -- An Empirical Investigation of Statistical Significance in NLP. -- Taylor Berg-Kirkpatrick David Burkett Dan Klein. -- http://www.cs.berkeley.edu/~tberg/papers/emnlp2012.pdf stats.boot.pvalue = function(data, pivot, index, params) local params = get_table_fields( { h0 = { mandatory = false, default = 0.0, type_match = "number" }, alternative = { mandatory = false, default = "two-sided", type_match = "string" }, }, params or {}) local h0 = params.h0 local p50 = stats.boot.percentile(data, 0.50, index) local alternative = params.alternative april_assert(alternatives[alternative], "Unknown alternative value %s", alternative) local data = data:select(2, index or 1) local a,b = 0.0,0.0 local two_sided = (alternative=="two-sided") if two_sided or alternative == "left" then if two_sided and pivot > 0.0 then a = data:lt(-pivot + p50 + h0):count_ones() else a = data:lt(pivot + p50 + h0):count_ones() end end if two_sided or alternative == "right" then if two_sided and pivot < 0.0 then b = data:gt(-pivot + p50 + h0):count_ones() else b = data:gt(pivot + p50 + h0):count_ones() end end local pvalue = (a + b + 1) / (data:size() + 1) return pvalue end ---------------------------------------------------------------------------- stats.percentile = april_doc{ class = "function", summary = "Returns a percentile value from a matrix (should be a vector)", params = { "A one-dimensional matrix (a vector).", "A percentile", "Another percentile", "...", }, outputs = { "The percentile value", "Another percentile value", "..." }, } .. -- returns the percentile function(data, ...) local data = data:squeeze() assert(data:num_dim() == 1, "Needs a data vector") local order = data:order() local result_tbl = {} for _,v in ipairs(table.pack(...)) do assert(v >= 0.0 and v <= 1.0, "Incorrect percentile value, it must be in range [0,1]") local N = data:size() local pos = (N+1)*v local pos_floor,pos_ceil,result = math.floor(pos),math.ceil(pos) local result if pos_floor == 0 then result = data[order[1]] elseif pos_floor >= N then result = data[order[data:size()]] else local dec = pos - pos_floor local a,b = data[order[pos_floor]],data[order[pos_ceil]] result = a + dec * (b - a) end result_tbl[#result_tbl + 1] = result end return table.unpack(result_tbl) end stats.summary = function(data) local data = data:squeeze() assert(data:num_dim() == 1, "Needs a data vector") local var,mean = stats.var(data) local order = data:order() local p0,p25,p50,p75,p100 = stats.percentile(data, 0.00, 0.25, 0.50, 0.75, 1.00) return setmetatable({ sd = math.sqrt(var), mean = mean, p0 = p0, p25 = p25, p50 = p50, p75 = p75, p100 = p100, }, { __tostring = function(self) local header = iterator{"Mean","SD","Min","Q1","Median","Q3","Max"}: map(bind(string.format, "%8s")):concat(" ") local data = iterator{self.mean, self.sd, self.p0, self.p25, self.p50, self.p75, self.p100 }: map(bind(string.format, "%8.4g")):concat(" ") return table.concat({header, data}, "\n") end }) end ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- local pearson,pearson_methods = class("stats.running.pearson") stats.running.pearson = pearson function pearson:constructor(x,y) self.mean_var_x = stats.running.mean_var() self.mean_var_y = stats.running.mean_var() self.xy_sum = 0 if x then self:add(x,y) end end function pearson_methods:clear() self.mean_var_x:clear() self.mean_var_y:clear() self.xy_sum = 0 return self end function pearson_methods:add(x,y) local x,y = x,y if not y then if type(x) == "table" then x,y = table.unpack(x) end end assert(x and y, "Needs two values or an array table with two components") self.mean_var_x:add(x) self.mean_var_y:add(y) self.xy_sum = self.xy_sum + x*y return self end function pearson_methods:compute() local N = self.mean_var_x:size() local mu_x,s_x = self.mean_var_x:compute() local mu_y,s_y = self.mean_var_y:compute() local rxy = ( self.xy_sum - N*mu_x*mu_y ) / ( (N-1)*math.sqrt(s_x*s_y) ) return rxy end ------------------------------------------------------------------------------- stats.dist.bernoulli = function(p) if class.is_a(p, matrix) then return stats.dist.binomial(matrix(1,{1}),p) else return stats.dist.binomial(1,p) end end ------------------------------------------------------------------------------- do local std_norm = stats.dist.normal() local check = function(x) local tt = type(x) if tt == "number" then x = matrix{x} elseif tt == "table" then x = matrix(x) end x = x:contiguous():rewrap(x:size(), 1) return x,tt end -- stats.dnorm = function(x, mean, sd) local x,tt = check(x) if mean then x:axpy(-1.0, mean) end if sd then x:scal(1/sd) end return std_norm:logpdf(x):exp() end -- stats.pnorm = function(x, mean, sd) local x,tt = check(x) if mean then x:axpy(-1.0, mean) end if sd then x:scal(1/sd) end return std_norm:logcdf(x):exp() end -- stats.qnorm = function(x, mean, sd) return stats.dist.quantile(std_norm, x)*(sd or 1) + (mean or 0) end end ------------------------------------------------------------------------------- class.extend(stats.dist, "quantile", stats.dist.quantile) ------------------------------------------------------------------------------- april_set_doc(stats.comb,{ class = "function", summary = "Computes k-combination", params = { "Total number of elements (n)", "How many selected elements (k)", }, outputs = { "A number with (n over k)" }, }) stats.mean_var = make_deprecated_function("stats.mean_var", "stats.running.mean_var", stats.running.mean_var) stats.correlation = {} -- deprecated table stats.correlation.pearson = make_deprecated_function("stats.correlation.pearson", "stats.running.pearson", stats.running.pearson) april-ann-0.4.1/packages/basics/stats/misc/000077500000000000000000000000001263004425400205105ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/stats/misc/gs-pca.cc000066400000000000000000000144321263004425400221750ustar00rootroot00000000000000// g++ -g -o gs-pca gs-pca.cc `pkg-config --libs gsl` -fpermissive `pkg-config --cflags gsl` // // C/C++ example for the CBLAS (GNU Scientific Library) // implementation of PCA-GS algorithm // // M. Andrecut (c) 2008 // includes, system #include #include // includes, GSL & CBLAS #include #include #include #include // declarations int gs_pca_gsl(int, int, int, gsl_matrix *, gsl_matrix *, gsl_matrix *); int print_results(int, int, int, gsl_matrix *, gsl_matrix *, gsl_matrix *, gsl_matrix *); // main int main(int argc, char** argv) { // PCA model: X = TP’ + R // input: X, MxN matrix (data) // input: M = number of rows in X // input: N = number of columns in X // input: K = number of components (K<=N) // output: T, MxK scores matrix // output: P, NxK loads matrix // output: R, MxN residual matrix int M = 1000, m; int N = M/2, n; int K = 10; printf("\nProblem dimensions: MxN=%dx%d, K=%d", M, N, K); // initialize srand and clock srand(time(NULL)); clock_t start=clock(); double htime; // initiallize some random test data X gsl_matrix *X = gsl_matrix_alloc (M, N); for(m=0; m0) { gsl_blas_dgemv(CblasTrans, 1.0, &gsl_matrix_submatrix (P, 0, 0, N, k).matrix, &gsl_matrix_column(P, k).vector, 0.0, &gsl_vector_subvector (U, 0, k).vector); gsl_vector *aux = &gsl_vector_subvector(U,0,k).vector; gsl_blas_dgemv(CblasNoTrans, -1.0, &gsl_matrix_submatrix (P, 0, 0, N, k).matrix, &gsl_vector_subvector (U, 0, k).vector, 1.0, &gsl_matrix_column(P, k).vector); } gsl_blas_dscal(1.0/gsl_blas_dnrm2(&gsl_matrix_column(P, k).vector), &gsl_matrix_column(P, k).vector); gsl_blas_dgemv(CblasNoTrans, 1.0, R, &gsl_matrix_column(P, k).vector, 0.0, &gsl_matrix_column(T, k).vector); if(k>0) { gsl_blas_dgemv(CblasTrans, 1.0, &gsl_matrix_submatrix (T, 0, 0, M, k).matrix, &gsl_matrix_column(T, k).vector, 0.0, &gsl_vector_subvector (U, 0, k).vector); gsl_blas_dgemv(CblasNoTrans, -1.0, &gsl_matrix_submatrix (T, 0, 0, M, k).matrix, &gsl_vector_subvector (U, 0, k).vector, 1.0, &gsl_matrix_column(T, k).vector); } gsl_vector_set(L, k, gsl_blas_dnrm2(&gsl_matrix_column(T, k).vector)); gsl_blas_dscal(1.0/gsl_vector_get(L, k), &gsl_matrix_column(T, k).vector); if(fabs(a - gsl_vector_get(L, k)) < er*gsl_vector_get(L, k)) break; a = gsl_vector_get(L, k); } gsl_blas_dger (-gsl_vector_get(L, k), &gsl_matrix_column(T, k).vector, &gsl_matrix_column(P, k).vector, R); } for(k=0; k 12) return EXIT_SUCCESS; printf("\nX\n"); for(m=0; mp3X-уjh1KJ,'_~PgO T+ja4k˅5z:EhRD NdA8wW l6n,yc1N7+\ujmm`_A_V|wySJ|}`gZYz$ Iso-6f)UuqJ)b34I hSOPOfZ5pL֯vEQe)c,1f) Q*C3dsHދ177\Wr 9pLԚ֤1{.FT!2QT? 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impossible to connect with cafre.dsic.upv.es") os.exit(0) end m = matrix.fromTabFilename("/tmp/sample.txt.gz"):transpose() else m = m:transpose() end -------------------------------------------------------------------------- local aR = stats.pca.center_by_pattern(m:clone()) T("PCATest", function() local aU,aS,aVT = stats.pca(aR) -- check regeneration of original covariance matrix local cov = stats.cov(aR, aR, { centered=true }) check(function() return cov:equals(aU * aS:to_dense() * aVT) end, "Regeneration of covariance matrix") -- ROTATION local amRot = aR * aU -- check covariance of rotated data local cov = stats.cov(amRot, amRot, { centered=true }) -- adjusting the data to be between 0 and 1 for sw in cov:sliding_window():iterate() do sw:adjust_range(0,1) end -- the adjusted covariance must be an identity matrix -- assert(cov:equals( cov:clone():zeros():diag(1), 0.1 )) -- U matrix orthogonality check local aUmul = aU:clone():gemm{ A=aU, B=aU, trans_B=true, alpha=1.0, beta=0.0, } check(function() return aUmul:equals( aUmul:clone():zeros():diag(1) ) end, "U orthogonality test") -- V matrix orthogonality check local aVTmul = aVT:clone():gemm{ A=aVT, B=aVT, trans_B=true, alpha=1.0, beta=0.0, } check(function() return aVTmul:equals( aVTmul:clone():zeros():diag(1) ) end, "V orthogonality test") -- check U matrix with octave computation local refU = matrix.fromTabFilename(base_dir.."data/U.gz"): abs() check(function() return refU:equals(aU:clone():abs(), 0.06) end, "U matrix comparison with octave") -- check V matrix with octave computation local refV = matrix.fromTabFilename(base_dir.."data/V.gz"): transpose():abs() check(function() return refV:equals(aVT:clone():abs(), 0.06) end, "V matrix comparison with octave") -- check S matrix with octave computation local refS = matrix.fromFilename(base_dir.."data/S.gz") check(function() -- FIXME: the last value is weird... we need to remove it for pass the -- test (both matrices are of (1:144,1:144) return refS:diagonalize()('1:143','1:143'): equals(aS:to_dense()('1:143','1:143') ) end, "S matrix comparison with octave") end) -------------------------------------------------------------------------- -------------------------------------------------------------------------- -------------------------------------------------------------------------- T("GS-PCATest", function() local aR = stats.pca.center_by_pattern(m:clone()) local bT,bP,bR,bV,bS = stats.pca.gs_pca{ X = aR, K = 144, } -- check regeneration of original matrix check(function() return aR:equals( bT * bP:transpose() + bR ) end) -- check covariance of rotated data local cov = stats.cov(bT, bT, { centered=true }) -- adjusting the data to be between 0 and 1 for sw in cov:sliding_window():iterate() do sw:adjust_range(0,1) end -- the adjusted covariance must be an identity matrix -- assert(cov:equals( cov:clone():zeros():diag(1), 1e-02 )) -- U matrix orthogonality check local bPmul = bP:clone():gemm{ A=bP, B=bP, trans_B=true, alpha=1.0, beta=0.0, } check(function() return bPmul:equals( bPmul:clone():zeros():diag(1) ) end) end) april-ann-0.4.1/packages/basics/stats/test/test-zca-whitening.lua000066400000000000000000000030601263004425400247620ustar00rootroot00000000000000local check = utest.check local T = utest.test -- local path = string.get_path(arg[0]).."../../../../TEST" local m = ImageIO.read(path.."/digitos/digits.png"):invert_colors():to_grayscale():matrix() local ds = dataset.matrix(m, { patternSize = {16,16}, offset = {0,0}, numSteps = {100,10}, stepSize = {16,16}, orderStep = {1,0} }) local m = ds:toMatrix() local aux = stats.pca.center_by_pattern(m:clone()) local aU,aS,aVT = stats.pca(aux) -- PCA THRESHOLD STATISTICS T("PCAThresholdTest", function() local takeN,eigen_value,prob_mass=stats.pca.threshold(aS, 0.99) check.eq(takeN, 193) check.number_eq(eigen_value,0.017318) check.number_eq(prob_mass,0.990025) end) local zca_whitening,new if ann.components.zca_whitening then zca_whitening = ann.components.zca_whitening{ U=aU, S=aS, epsilon=0.017, takeN=193, } new = zca_whitening:forward(aux) end local new2 = stats.zca.whitening(aux:clone(), aU(':','1:193'), aS('1:193','1:193'), 0.017) if new then T("ZCAWhiteningTest", function() for i=1,new:dim(1) do local d = new(i,':'):clone():rewrap(16,16):adjust_range(0,1) local d2 = new2(i,':'):clone():rewrap(16,16):adjust_range(0,1) check.eq(d, d2) -- ImageIO.write(Image(d), "wop-" .. string.format("%03d",i) .. ".png") end end) end -- PCA FILTERS -- for i=1,aU:dim(1) do -- local d = aU:select(2,i):clone():rewrap(16,16):adjust_range(0,1) -- ImageIO.write(Image(d), "filter-" .. string.format("%03d",i) .. 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0.026538084030151 1.0301678631757 0.026553579330444 1.058410094665 0.026654905319214 1.0978682539962 0.026682909011841 1.07733184845 0.026683570861816 1.0809664645114 0.02674967956543 0.95812071837462 0.026784418106079 1.0765653348661 0.026905778884888 0.97691753032329 0.027137321472168 1.0946453044842 0.027151512145996 1.0556515988645 0.02715747833252 0.98449493194366 0.027308446884155 0.99078992322401 0.027402572631836 1.0292468982655 0.027815879821777 0.9820030601891 0.028136375427246 1.021507835961 0.028176364898682 1.0079200294044 0.028453170776367 1.1027041445743 0.028708322525024 1.0980313809904 0.028857799530029 1.0767214968875 0.028963069915771 1.0010038114286 0.029835041046143 1.0691976155843 0.029883909225464 1.0520360448339 0.030238887786865 0.92851964513341 0.030539659500122 1.0412190755208 0.030684015274048 1.0611773883258 0.030809280395508 1.0884618749609 0.030962867736816 1.0351371879692 0.031026882171631 0.99381980857811 0.031295557022095 0.9952306432409 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1.0759740453344 0.038406158447266 0.9960645459913 0.038451072692871 0.96671164572776 0.038606220245361 0.93770253407705 0.038615161895752 1.0521253675551 0.03969499206543 0.95792362186405 0.039697967529297 1.0206764381569 0.039989917755127 1.0874651506976 0.040078868865967 0.9914281957739 0.040383377075195 1.0680948282267 0.040595588684082 0.9284337438024 0.040873783111572 0.97370545594423 0.04094966506958 0.97705933472535 0.041040943145752 1.0093283591208 0.041302917480469 1.1201742513998 0.041637935638428 1.0246659623491 0.041894115447998 1.0029055544803 0.041896259307861 1.0224143821556 0.042120624542236 0.9908983690722 0.042345867156982 1.0719625875876 0.042744487762451 0.94125534225632 0.042826866149902 1.0153833032251 0.042979148864746 0.99312001210195 0.043081836700439 0.96495567833458 0.043155529022217 1.0914709875892 0.043218952178955 0.99560766821509 0.043281295776367 0.98356138120542 0.043843460083008 0.98319272641782 0.045273983001709 1.0888350508712 0.045520481109619 1.0273177229964 0.046036468505859 1.0626924531954 0.046259845733643 0.97621620644082 0.046645740509033 1.0561855801114 0.047194896697998 1.0959219717765 0.047271553039551 1.0163558333724 0.048469245910645 0.98894939861737 0.04894083404541 1.0727051514405 0.049178276062012 1.0423162420233 0.049610012054443 1.0083210041096 0.049942150115967 1.1647489774931 0.050112808227539 1.025536034081 0.050169910430908 1.0023273395466 0.050283821105957 1.0889175308121 0.050968967437744 0.9893054064807 0.051204177856445 1.0843582840653 0.051449329376221 1.0138896831402 0.052074756622314 0.97411327342968 0.052944717407227 1.0334457993149 0.053335613250732 0.97738345034488 0.053926624298096 1.0182070498233 0.054101776123047 1.0296316824637 0.05553157043457 0.97650598596644 0.057814231872559 1.0539977233092 0.057859004974365 1.0451113955753 0.058161582946777 1.042089697119 0.05969079208374 1.027648375915 0.061543079376221 1.0324322124859 0.061552082061768 1.0881930514499 0.06779817199707 1.0591816181416 0.067896919250488 1.143285375219 0.068321327209473 1.0145425576944 0.070601638793945 1.0241486603791 0.070763732910156 1.0339359134525 0.071525016784668 1.0725572985094 0.0813525390625 1.0816148179429 0.087429878234863 0.99826547739145 0.090349304199219 0.96682345186984 0.091708694458008 1.1308075653779 0.092193511962891 1.0155173484031 0.092709159851074 1.0323883453766 april-ann-0.4.1/packages/basics/stats/test/test_bootstrap.lua000066400000000000000000000033731263004425400243210ustar00rootroot00000000000000local check = utest.check local T = utest.test local base_dir = string.get_path(arg[0]) local rnd = random(567) local errors = matrix(iterator(range(1,1000)):map(function()return rnd:randNorm(0.0,1.0)end):table()) T("BootstrapTest", function() local boot_result = stats.boot{ size=errors:size(), R=1000, seed=1234, verbose=true, k=2, statistic = function(sample) local s = errors:index(1, sample) local var,mean = stats.var(s) return mean,var end } local boot_result = boot_result:index(1, boot_result:select(2,1):order()) iterator(io.lines(base_dir.."test_bootstrap-output.log")): map(string.tokenize): enumerate(): apply(function(i,t) check.number_eq(tonumber(t[1]), boot_result[i][1]) check.number_eq(tonumber(t[2]), boot_result[i][2]) end) -- local boot_result = stats.boot{ size=errors:size(), R=1000, random=random(1234), ncores=2, verbose=true, k=2, statistic = function(sample) local s = errors:index(1, sample) local var,mean = stats.var(s) return mean,var end } local boot_result = boot_result:index(1, boot_result:select(2,1):order()) iterator(io.lines(base_dir.."test_bootstrap-output.log")): map(string.tokenize): enumerate(): apply(function(i,t) check.number_eq(tonumber(t[1]), boot_result[i][1]) check.number_eq(tonumber(t[2]), boot_result[i][2]) end) local a,b = stats.boot.ci(boot_result, 0.95) local m,p0,pn = stats.boot.percentile(boot_result, { 0.5, 0.0, 1.0 }) check.number_eq(a, -0.073266) check.number_eq(b, 0.051443) check.number_eq(m, -0.012237) check.number_eq(p0, -0.117945) check.number_eq(pn, 0.092709) end) april-ann-0.4.1/packages/basics/stats/test/test_comb.lua000066400000000000000000000013251263004425400232170ustar00rootroot00000000000000local T = utest.test local check = utest.check function log_comb(n, k) return stats.lgamma(n+1) - stats.lgamma(k+1) - stats.lgamma(n-k+1) end function comb(n, k) return math.round(math.exp(log_comb(n, k))) end T("CombinatorialsTest", function() for i=0,30 do for j=0,i do check.eq( stats.comb(i,j), comb(i,j), string.format("C(%d,%d)", i, j) ) end end end) T("LogCombinatorialsTest", function() for i=0,100 do for j=0,i do check.number_eq( stats.log_comb(i,j), log_comb(i,j), 0.01, -- 1% relative error string.format("C(%d,%d)", i, j) ) end end end) april-ann-0.4.1/packages/basics/stats/test/test_covariance.lua000066400000000000000000000005011263004425400244040ustar00rootroot00000000000000local check = utest.check local T = utest.test T("CovarianceCorrelationTest", function() local m = matrix(3,3,{1,6,9, 4,5,5, 7,4,1}) check.eq(stats.cov(m), matrix(3,3,{9,-3,-12, -3,1,4, -12,4,16})) check.eq(stats.cor(m), matrix(3,3,{1,-1,-1, -1,1,1, -1,1,1})) end) april-ann-0.4.1/packages/basics/stats/test/test_distributions.lua000066400000000000000000000233601263004425400252040ustar00rootroot00000000000000local check = utest.check local T = utest.test local M = matrix local EPSILON = 0.001 local N = 1000 local function check_grads(d, point) local point = point:clone() local g = d:logpdf_derivative(point) for i = 1,point:dim(2) do local v = point:get(1,i) point:set(1, i, v + EPSILON) local logpdf1 = d:logpdf(point):get(1) point:set(1, i, v - EPSILON) local logpdf2 = d:logpdf(point):get(1) point:set(1, i, v) local g_hat = (logpdf1 - logpdf2) / (2 * EPSILON) check.number_eq(g:get(1,i), g_hat) end end local function check_pdf_and_sample(d) if d:size() == 1 then local m = d:sample(random(1234), 10000) local h = stats.hist(m, {breaks=100}) local key = h[{"key"}] local density = h[{"density"}][{'2:-2'}] local aux = d:logpdf(key:right_inflate():contiguous())[{'2:-2'}]:exp() check.TRUE(aux:eq(density)) end end ----------------------------------------------------------------------------- -- UNIFORM DISTRIBUTION T("UniformDistTest", function() local d = stats.dist.uniform( M(3,{1,2,3}), M(3,{2,3,4}) ) check_pdf_and_sample(d) local cdf_result = M(10,{ 0.0592946, 0.21913, 0.472505, 0.0353412, 0.0440094, 0.124041, 0.0364003, 0.00314816, 0.161239, 0.0291983 }) check.eq( d:logcdf( d:sample( random(1234), M(10,3) ) ):exp(), cdf_result ) end) ----------------------------------------------------------------------------- -- NORMAL DISTRIBUTION T("NormalDistTest", function() local d = stats.dist.normal( M(3):uniformf(0,1,random(1234)), M(3,3):zeros():diag(2):set(1,2,1):set(2,1,1) ) check_pdf_and_sample(d) check.eq(type(d), "stats.dist.normal.general") local pdf_result = M(2, { 0.0151933, 0.00832571 }) check.eq( d:logpdf( M(2,3):uniformf(-1,2,random(9427)) ):exp(), pdf_result ) for _,a in ipairs{-4, -0.1, 0.1, 4} do for _,b in ipairs{0.1, 1.0, 4.0} do local d = stats.dist.normal( M(3):fill(a), M(3,3):zeros():diag(b) ) check_pdf_and_sample(d) local data = d:sample( random(4295), M(N,3) ) -- FIXME: check this test, it fails eventually -- check(function() -- return data:sum(1):scal(1/N):equals( M(1,3):fill(a) ) -- end, "Multivariate population mean test") local mv = stats.running.mean_var() data:map(function(x) mv:add(x) end) local mu,sigma = mv:compute() check.number_eq(mu, a, ( math.abs(a) < 1.0 ) and 0.4 or nil, "Population mean test") check.number_eq(sigma, b, nil, "Population variance test") for i=1,10 do check_grads(d, data(i,':')) end end end end) ----------------------------------------------------------------------------- T("QuantileTest", function() local d = stats.dist.normal() check.number_eq(stats.dist.quantile(d, 0.975), 1.9599) check.number_eq(stats.dist.quantile(d, 0.95), 1.6448) check.number_eq(stats.dist.quantile(d, 0.05), -1.6448) check.number_eq(stats.dist.quantile(d, 0.20), -0.8416212) check.number_eq(stats.dist.quantile(d, 0.50), 0.0) end) ----------------------------------------------------------------------------- -- DIAGONAL NORMAL DISTRIBUTION T("DiagNormalDistTest", function() for _,a in ipairs{-4, -0.1, 0.1, 4} do for _,b in ipairs{0.1, 1.0, 4.0} do local d = stats.dist.normal( M(3):fill(a), matrix.sparse.diag{b, b, b} ) check_pdf_and_sample(d) check.eq(type(d), "stats.dist.normal.diagonal") local data = d:sample( random(4295), M(N,3) ) -- FIXME: check this test, it fails eventually -- check(function() -- return data:sum(1):scal(1/N):equals( M(1,3):fill(a) ) -- end, "Multivariate population mean test") local mv = stats.running.mean_var() data:map(function(x) mv:add(x) end) local mu,sigma = mv:compute() check.number_eq(mu, a, ( math.abs(a) < 1.0 ) and 0.4 or nil, "Population mean test") check.number_eq(sigma, b, nil, "Population variance test") for i=1,10 do check_grads(d, data(i,':')) end end end end) ----------------------------------------------------------------------------- -- STANDARD NORMAL DISTRIBUTION T("StdNormalDist", function() local d = stats.dist.normal() check_pdf_and_sample(d) check.eq(type(d), "stats.dist.normal.standard") local data = d:sample( random(4295), M(N,1) ) check(function() return math.abs(data:sum()/N) < 0.1 end) local mv = stats.running.mean_var() data:map(function(x) mv:add(x) end) local mu,sigma = mv:compute() check(function() return math.abs(mu) < 0.04 end) check.number_eq(sigma, 1.0, 0.1) for i=1,10 do check_grads(d, data(i,':')) end end) ----------------------------------------------------------------------------- -- EXPONENTIAL DISTRIBUTION T("ExpDistTest", function() local d = stats.dist.exponential(4) check_pdf_and_sample(d) local samples = M(10,1,{ 0.41319, 0.17446, 0.11866, 0.050273, 0.20654, 0.12271, 0.060404, 0.0649, 0.062123, 0.037511, }) check.eq( d:sample(random(1234),10), samples ) local pdf_result = M(10,{ 1.01885, -45.38, -1.25495, -15.5582, -11.3048, -26.279, -1.00439, -15.7705, -5.93778, -63.1531, }) local x = M(10,1,{ 0.091862, 11.691586, 0.660310, 4.236131, 3.172766, 6.916327, 0.597670, 4.289197, 1.831019, 16.134842, }) check.eq( d:logpdf(x), pdf_result ) local cdf_result = M(10,{ -1.17928, -4.89368e-21, -0.0739403, -4.37609e-08, -3.07852e-06, -9.66294e-13, -0.0960346, -3.53917e-08, -0.000659686, -9.35209e-29, }) check.eq( d:logcdf(x), cdf_result ) local x = x:rewrap(1,10) local d = stats.dist.exponential(M(10):fill(4)) check_pdf_and_sample(d) check.number_eq( d:logpdf(x):get(1), pdf_result:sum() ) check.number_eq( d:logcdf(x):get(1), cdf_result:sum() ) end) ----------------------------------------------------------------------------- -- BINOMIAL DISTRIBUTION T("BinomDistTest", function() local d = stats.dist.binomial(10,0.5) check.eq( d:sample(random(1234),10), M(10,1,{3,6,6,6,5,5,4,5,3,5}) ) local pdf_result = M(3,{-1.58436,-3.12481,-4.62889}) check.eq( d:logpdf(M(3,1,{4,8,1})), pdf_result ) local cdf_result = M(3,{-0.975635,-0.0108004,-4.53358}) check.eq( d:logcdf(M(3,1,{4,8,1})), cdf_result ) end) ----------------------------------------------------------------------------- -- BERNOULLI DISTRIBUTION T("BernoulliDistTest", function() local d = stats.dist.bernoulli(0.5) check.TRUE(class.is_a(d, stats.dist.binomial)) end) ----------------------------------------------------------------------------- -- LOG-NORMAL DISTRIBUTION T("LogNormalDistTest", function() for _,a in ipairs{-4, -0.1, 0.1, 4} do for _,b in ipairs{0.1, 1.0, 4.0} do local d = stats.dist.lognormal( M(3):fill(a), M(3,3):zeros():diag(b) ) check_pdf_and_sample(d) local data = d:sample( random(4295), M(N,3) ) check(function() return (data:sum(1):scal(1/N):log() - M(1,3):fill(a + b/2)):abs():sum()/3 < 0.1 end) local mv = stats.running.mean_var() data:map(function(x) mv:add(x) end) local mu,sigma = mv:compute() check.number_eq(math.log(mu), a + b/2, 0.1) -- FIXME: PRECISSION PROBLEMS ????? -- check.number_eq(math.log(sigma), (b - 1 + (2*a + b))) end end end) ----------------------------------------------------------------------------- -- DIAGONAL NORMAL DISTRIBUTION T("DiagLogNormalDistTest", function() for _,a in ipairs{-4, -0.1, 0.1, 4} do for _,b in ipairs{0.1, 1.0, 4.0} do local d = stats.dist.lognormal( M(3):fill(a), matrix.sparse.diag{b, b, b} ) check_pdf_and_sample(d) check.eq(type(d), "stats.dist.lognormal.diagonal") local data = d:sample( random(4295), M(N,3) ) check(function() return (data:sum(1):scal(1/N):log() - M(1,3):fill(a + b/2)):abs():sum()/3 < 0.1 end) local mv = stats.running.mean_var() data:map(function(x) mv:add(x) end) local mu,sigma = mv:compute() check.number_eq(mu, math.exp(a + b/2), 0.1) -- FIXME: PRECISSION PROBLEMS ????? -- check.number_eq(math.log(sigma), (b - 1 + (2*a + b)), 0.08) end end end) ----------------------------------------------------------------------------- -- GAMMA DISTRIBUTION T("GammaDistribution", function() for _,pair in ipairs{ {1.0,1.0}, {2.0,1.0}, {0.5,1.0}, {1.0,2.0}, {1.0,0.5} } do local a,b = table.unpack(pair) local d = stats.dist.gamma(a, b) check_pdf_and_sample(d) end end) april-ann-0.4.1/packages/basics/stats/test/test_means.lua000066400000000000000000000016421263004425400234040ustar00rootroot00000000000000local check = utest.check local T = utest.test T("MeansTest", function() local m = matrix(3,4):linear() check.number_eq(stats.amean(m), m:sum()/m:size()) check.TRUE(stats.gmean(m) == 0) check.TRUE(stats.hmean(m) == 0) check.eq(stats.amean(m,1), matrix(1,4,{(0+4+8)/3, (1+5+9)/3, (2+6+10)/3, (3+7+11)/3})) check.eq(stats.gmean(m,1), matrix(1,4,{(0*4*8)^(1/3), (1*5*9)^(1/3), (2*6*10)^(1/3), (3*7*11)^(1/3)})) check.eq(stats.hmean(m,1), matrix(1,4,{0, 3/(1/1+1/5+1/9), 3/(1/2+1/6+1/10), 3/(1/3+1/7+1/11)})) local m = matrix(3,4):linear(1) check.number_eq(stats.amean(m), m:sum()/m:size()) check.number_eq(stats.gmean(m), iterator(range(1,12)):reduce(math.mul,1)^(1/m:size())) check.number_eq(stats.hmean(m), m:size() / iterator(range(1,12)):map(function(x) return 1/x end):reduce(math.add,0)) end) april-ann-0.4.1/packages/basics/stats/test/test_permutation_test.lua000066400000000000000000000015701263004425400257070ustar00rootroot00000000000000local check = utest.check local T = utest.test local base_dir = string.get_path(arg[0]) local rnd = random(567) local errors1 = matrix(iterator(range(1,1000)):map(function()return rnd:randNorm(0.0,1.0)end):table()) local errors2 = matrix(iterator(range(1,1000)):map(function()return rnd:randNorm(0.01,1.0)end):table()) T("PermutationTest", function() local perm_result = stats.perm{ samples={ errors1, errors2 }, R=1000, seed=1234, verbose=true, k=1, statistic = function(e1, e2) local m1 = stats.amean(e1) local m2 = stats.amean(e2) return m1 - m2 end } local perm_result = perm_result:index(1, perm_result:select(2,1):order()) local mean_diff = stats.amean(errors1) - stats.amean(errors2) check.number_eq(mean_diff, -0.041067314147949) check.number_eq(stats.perm.pvalue(perm_result, mean_diff), 0.368*0.5) end) april-ann-0.4.1/packages/basics/thread_utils/000077500000000000000000000000001263004425400211065ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/thread_utils/binding/000077500000000000000000000000001263004425400225205ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/thread_utils/binding/bind_threadable.lua.cc000066400000000000000000000033041263004425400266760ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_H #include "threadable.h" #include "sig_int_handler.h" using namespace AprilThreadUtils; //BIND_END //BIND_HEADER_C //BIND_END //BIND_FUNCTION util.threads.install_sig_int_handler { SigIntHandler::install_handler(); } //BIND_END //BIND_LUACLASSNAME Threadable __threadable__ //BIND_CPP_CLASS Threadable //BIND_CONSTRUCTOR Threadable { LUABIND_ERROR("Abstract class!!"); } //BIND_END //BIND_METHOD Threadable is_running { LUABIND_RETURN(bool, obj->isRunning()); } //BIND_END //BIND_METHOD Threadable is_joined { LUABIND_RETURN(bool, obj->isJoined()); } //BIND_END //BIND_METHOD Threadable start_thread { obj->startThread(); } //BIND_END //BIND_METHOD Threadable stop_thread { obj->stopThread(); } //BIND_END //BIND_METHOD Threadable wait_thread { obj->waitThread(); } //BIND_END //BIND_METHOD Threadable get_name { LUABIND_RETURN(string, obj->getName()); } //BIND_END april-ann-0.4.1/packages/basics/thread_utils/c_src/000077500000000000000000000000001263004425400221775ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/thread_utils/c_src/mutexed_fifo.h000066400000000000000000000062001263004425400250240ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MUTEX_FIFO_H #define MUTEX_FIFO_h #include #include #include "fifo.h" using AprilUtils::fifo; namespace AprilThreadUtils { template class MutexedFIFO { // cola fifo queue; // semaforo pthread_mutex_t fifo_mutex; // variable condicional para que se esperen los procesos lectores a // que haya datos en el canal. pthread_cond_t fifo_readers_cond; bool locked; public: MutexedFIFO() { locked = true; pthread_mutex_init(&fifo_mutex, NULL); pthread_cond_init (&fifo_readers_cond, NULL); } ~MutexedFIFO() { pthread_mutex_destroy(&fifo_mutex); pthread_cond_destroy(&fifo_readers_cond); } // indica si esta vacia la cola bool empty() { bool ret; pthread_mutex_lock(&fifo_mutex); ret = queue.empty(); pthread_mutex_unlock(&fifo_mutex); return ret; } // ESTE METODO SI ES BLOQUEANTE EN FUNCION DEL VALOR DE // "locked". Si es true, entonces es bloqueante, en otro caso no T get() { pthread_mutex_lock(&fifo_mutex); // metemos la espera en un bucle para comprobar cada vez que se // despierte si realmente esta vacia la cola while(queue.empty()) { if (!locked) { // salimos sin bloquear pthread_mutex_unlock(&fifo_mutex); return T(); } // bloqueamos pthread_cond_wait(&fifo_readers_cond, &fifo_mutex); } T data = T(); queue.get(data); pthread_mutex_unlock(&fifo_mutex); return data; } // hace un put en el fifo, usando el mutex y despertando a quien // toque si hubiera alguien esperando. Este nunca es bloqueante. void put(T data) { pthread_mutex_lock(&fifo_mutex); queue.put(data); if (queue.size() == 1) { // SUPERFIXME se puede poner el pthread_cond_signal a pelo // enviamos la senyal de que se puede leer del canal pthread_cond_signal(&fifo_readers_cond); } pthread_mutex_unlock(&fifo_mutex); } // desbloquea el fifo despertando los procesos dormidos, // impidiendo que vuelva a ser bloqueante void unlock() { locked = false; pthread_cond_signal(&fifo_readers_cond); } // bloquea el fifo. vuelve a ser bloqueante void lock() { locked = true; } }; }; #endif // MUTEX_FIFO_H april-ann-0.4.1/packages/basics/thread_utils/c_src/sig_int_handler.cc000066400000000000000000000031411263004425400256360ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "threadable.h" #include "sig_int_handler.h" namespace AprilThreadUtils { bool SigIntHandler::installed = false; list SigIntHandler::objects; void SigIntHandler::sig_int_handler(int sgn) { fprintf (stderr, "\tReceived ctrl+c, stopping %u threads\n", (unsigned int)objects.size()); for (list::iterator it = objects.begin(); it != objects.end(); ++it) { fprintf (stderr, "\t\t%s\n", (*it)->getName()); (*it)->stopThread(); } } void SigIntHandler::add_thread(Threadable *obj) { objects.push_back(obj); } void SigIntHandler::remove_thread(Threadable *obj) { objects.remove(obj); } void SigIntHandler::install_handler() { if (!installed) { installed = true; signal(SIGINT, sig_int_handler); } } } april-ann-0.4.1/packages/basics/thread_utils/c_src/sig_int_handler.h000066400000000000000000000024701263004425400255040ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SIG_INT_HANDLER_H #define SIG_INT_HANDLER_H #include #include #include "list.h" using AprilUtils::list; // forward declaration class Threadable; namespace AprilThreadUtils { class SigIntHandler { static bool installed; static list objects; public: static void sig_int_handler(int sgn); static void add_thread(Threadable *obj); static void remove_thread(Threadable *obj); static void install_handler(); }; } #endif // SIG_INT_HANDLER april-ann-0.4.1/packages/basics/thread_utils/c_src/threadable.h000066400000000000000000000056221263004425400244500ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef THREADBLE_H #define THREADBLE_H #include #include #include "sig_int_handler.h" #include "referenced.h" using AprilThreadUtils::SigIntHandler; class Threadable : public Referenced { // controla la ejecucion del bucle bool running; // controla si se ha ejecutado el join bool joined; // el ID del thread pthread_t thread_id; // nombre char *name; static void *execute(void *ptr) { Threadable *obj = reinterpret_cast(ptr); while (obj->running && obj->threadProcedure()); obj->running = false; pthread_exit(0); } protected: // permite ejecutar cosas ANTES de hacer el running virtual void executeBeforeStart() { } // permite ejecutar cosas ANTES de hacer el stop virtual void executeBeforeStop() { } // permite ejecutar cosas DESPUES de hacer el wait virtual void executeAfterWait() { } // el codigo principal del thread, que va dentro del bucle. Si // devuelve false, seria equivalente a hacer un stop del thread virtual bool threadProcedure() = 0; public: Threadable(const char *name=0) : running(false), joined(true) { if (name) { this->name = new char[strlen(name)+1]; strcpy(this->name, name); } else this->name = 0; } virtual ~Threadable() { stopThread(); waitThread(); delete[] name; } const char *getName() { return name; } bool isRunning() { return running; } bool isJoined() { return joined; } void startThread() { if (!running) { if (!joined) waitThread(); joined = false; running = true; executeBeforeStart(); pthread_create(&thread_id, 0, execute, this); SigIntHandler::add_thread(this); } } void stopThread() { if (running) { running = false; executeBeforeStop(); SigIntHandler::remove_thread(this); fprintf(stderr, "\t\t\t%s stopped\n", getName()); } } void waitThread() { if (!running && !joined) { pthread_join(thread_id, 0); joined = true; executeAfterWait(); fprintf(stderr, "\t\t\t%s joined\n", getName()); } } }; #endif // THREADBLE_H april-ann-0.4.1/packages/basics/thread_utils/package.lua000066400000000000000000000020051263004425400232010ustar00rootroot00000000000000package{ name = "thread_utils", version = "1.0", depends = { "util" }, keywords = { }, link_libraries = { "pthread" }, description = "", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_threadable.lua.cc" , dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", dest_dir = "build", -- flags = "-std=c99", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_threadable.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/tokens/000077500000000000000000000000001263004425400177225ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/tokens/binding/000077500000000000000000000000001263004425400213345ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/tokens/binding/bind_tokens.lua.cc000066400000000000000000000245661263004425400247370ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_H #include "token_base.h" #include "token_memory_block.h" #include "token_matrix.h" #include "token_null.h" #include "token_sparse_matrix.h" #include "token_vector.h" #include "smart_ptr.h" using namespace Basics; bool lua_isAuxToken(lua_State *L, int n); AprilUtils::SharedPtr lua_toAuxToken(lua_State *L, int n); void lua_pushAuxToken(lua_State *L, AprilUtils::SharedPtr &value); //BIND_END //BIND_HEADER_C #include "bind_matrix.h" #include "bind_sparse_matrix.h" #include "matrixFloat.h" #include "sparse_matrixFloat.h" namespace AprilUtils { template<> AprilUtils::SharedPtr LuaTable:: convertTo< AprilUtils::SharedPtr >(lua_State *L, int idx) { return lua_toAuxToken(L, idx); } template<> void LuaTable:: pushInto< Basics::Token * >(lua_State *L, Basics::Token * ptr) { AprilUtils::SharedPtr shared_ptr(ptr); lua_pushAuxToken(L, shared_ptr); shared_ptr.weakRelease(); } template<> void LuaTable:: pushInto< Basics::Token >(lua_State *L, AprilUtils::SharedPtr ptr) { lua_pushAuxToken(L, ptr); } template<> bool LuaTable:: checkType< AprilUtils::SharedPtr >(lua_State *L, int idx) { return lua_isAuxToken(L, idx); } } namespace Basics { int token_bunch_vector_iterator_function(lua_State *L) { // se llama con: local var_1, ... , var_n = _f(_s, _var) donde _s es // el estado invariante (en este caso el token vector) y _var es var_1 de // iteracion anterior (en este caso el indice) TokenBunchVector *obj = lua_toTokenBunchVector(L, 1); unsigned int index = static_cast(lua_tonumber(L, 2)) + 1; // le sumamos uno if (index > obj->size()) return 0; lua_pushnumber(L, index); AprilUtils::SharedPtr token( (*obj)[index-1] ); lua_pushAuxToken(L, token); return 2; } } // namespace Basics bool lua_isAuxToken(lua_State *L, int n) { return lua_isSparseMatrixFloat(L,n) || lua_isMatrixFloat(L,n) || lua_isToken(L,n); } AprilUtils::SharedPtr lua_toAuxToken(lua_State *L, int n) { if (lua_isMatrixFloat(L, n)) { MatrixFloat *mat = lua_toMatrixFloat(L,n); return new TokenMatrixFloat(mat); } else if (lua_isSparseMatrixFloat(L, n)) { SparseMatrixFloat *mat = lua_toSparseMatrixFloat(L,n); return new TokenSparseMatrixFloat(mat); } else if (lua_isnil(L, n)) { return TokenNull::getInstance(); } return lua_toToken(L,n); } void lua_pushAuxToken(lua_State *L, AprilUtils::SharedPtr &value) { DEBUG("lua_pushAuxToken (begin)"); if (value.empty()) { DEBUG("lua_pushAuxToken: pushing a nil value"); lua_pushTokenNull(L, TokenNull::getInstance()); } else { DEBUG_OBJ("lua_pushAuxToken", value.get()); switch(value->getTokenCode()) { case Basics::table_of_token_codes::token_matrix: lua_pushMatrixFloat(L, ((TokenMatrixFloat*)value.get())->getMatrix()); break; case Basics::table_of_token_codes::token_sparse_matrix: lua_pushSparseMatrixFloat(L, ((TokenSparseMatrixFloat*)value.get())->getMatrix()); break; case Basics::table_of_token_codes::vector_Tokens: lua_pushTokenBunchVector(L, (TokenBunchVector*)value.get()); break; case Basics::table_of_token_codes::token_null: lua_pushTokenNull(L, TokenNull::getInstance()); break; default: lua_pushToken(L, value.get()); } } DEBUG("lua_pushAuxToken (end)"); } //BIND_END //BIND_LUACLASSNAME Token tokens.base //BIND_CPP_CLASS Token //BIND_CONSTRUCTOR Token { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD Token clone { LUABIND_RETURN(Token, obj->clone()); } //BIND_END //BIND_METHOD Token get_matrix { switch(obj->getTokenCode()) { case table_of_token_codes::token_matrix: { TokenMatrixFloat *token_matrix = obj->convertTo(); LUABIND_RETURN(MatrixFloat, token_matrix->getMatrix()); break; } case table_of_token_codes::token_sparse_matrix: { TokenSparseMatrixFloat *token_sparse_matrix; token_sparse_matrix = obj->convertTo(); LUABIND_RETURN(SparseMatrixFloat, token_sparse_matrix->getMatrix()); break; } default: ; } } //BIND_END //BIND_METHOD Token convert_to_memblock { if (obj->getTokenCode() == table_of_token_codes::token_mem_block) { TokenMemoryBlock *token_memblock = obj->convertTo(); LUABIND_RETURN(TokenMemoryBlock, token_memblock); } } //BIND_END //BIND_METHOD Token convert_to_bunch_vector { if (obj->getTokenCode() == table_of_token_codes::vector_Tokens) { TokenBunchVector *token_bunch_vector = obj->convertTo(); LUABIND_RETURN(TokenBunchVector, token_bunch_vector); } } //BIND_END //////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME TokenNull tokens.null //BIND_CPP_CLASS TokenNull //BIND_SUBCLASS_OF TokenNull Token //BIND_CONSTRUCTOR TokenNull { LUABIND_RETURN(TokenNull, TokenNull::getInstance()); } //BIND_END //////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME TokenMemoryBlock tokens.memblock //BIND_CPP_CLASS TokenMemoryBlock //BIND_SUBCLASS_OF TokenMemoryBlock Token //BIND_CONSTRUCTOR TokenMemoryBlock { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, table); unsigned int sz; LUABIND_TABLE_GETN(1, sz); float *vector = new float[sz]; LUABIND_TABLE_TO_VECTOR(1, float, vector, sz); obj = new TokenMemoryBlock(sz); obj->setData(vector, sz); delete[] vector; LUABIND_RETURN(TokenMemoryBlock, obj); } //BIND_END //BIND_METHOD TokenMemoryBlock to_table { int sz = static_cast(obj->getUsedSize()); const float *vector = obj->getMemBlock()->getPPALForRead(); LUABIND_VECTOR_TO_NEW_TABLE(float, vector, sz); LUABIND_RETURN_FROM_STACK(-1); } //BIND_END //////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME TokenMatrixFloat tokens.matrix //BIND_CPP_CLASS TokenMatrixFloat //BIND_SUBCLASS_OF TokenMatrixFloat Token //BIND_CONSTRUCTOR TokenMatrixFloat { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, MatrixFloat); MatrixFloat *mat; LUABIND_GET_PARAMETER(1, MatrixFloat, mat); obj = new TokenMatrixFloat(mat); LUABIND_RETURN(TokenMatrixFloat, obj); } //BIND_END //BIND_METHOD TokenMatrixFloat get_matrix { LUABIND_RETURN(MatrixFloat, obj->getMatrix()); } //BIND_END //////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME TokenSparseMatrixFloat tokens.sparse_matrix //BIND_CPP_CLASS TokenSparseMatrixFloat //BIND_SUBCLASS_OF TokenSparseMatrixFloat Token //BIND_CONSTRUCTOR TokenSparseMatrixFloat { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, SparseMatrixFloat); SparseMatrixFloat *mat; LUABIND_GET_PARAMETER(1, SparseMatrixFloat, mat); obj = new TokenSparseMatrixFloat(mat); LUABIND_RETURN(TokenSparseMatrixFloat, obj); } //BIND_END //BIND_METHOD TokenSparseMatrixFloat get_matrix { LUABIND_RETURN(SparseMatrixFloat, obj->getMatrix()); } //BIND_END //////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME TokenVectorGeneric tokens.vector //BIND_CPP_CLASS TokenVectorGeneric //BIND_SUBCLASS_OF TokenVectorGeneric Token //BIND_CONSTRUCTOR TokenVectorGeneric { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD TokenVectorGeneric size { LUABIND_RETURN(uint, obj->size()); } //BIND_END //BIND_METHOD TokenVectorGeneric clear { obj->clear(); } //BIND_END //////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME TokenBunchVector tokens.vector.bunch //BIND_CPP_CLASS TokenBunchVector //BIND_SUBCLASS_OF TokenBunchVector TokenVectorGeneric //BIND_CONSTRUCTOR TokenBunchVector { LUABIND_CHECK_ARGN(<=, 1); int argn = lua_gettop(L); if (argn == 1) { if (lua_isnumber(L, 1)) { unsigned int size; LUABIND_CHECK_PARAMETER(1, uint); LUABIND_GET_PARAMETER(1, uint, size); obj = new TokenBunchVector(size); } else { int sz; LUABIND_TABLE_GETN(1, sz); obj = new TokenBunchVector(sz); for (unsigned int i=0; i(sz); ++i) { lua_pushnumber(L, i+1); // OJO: +1 lua_gettable(L, 1); AprilUtils::SharedPtr aux(lua_toAuxToken(L,-1)); lua_pop(L,1); (*obj)[i] = aux; } } } else { obj = new TokenBunchVector(); } LUABIND_RETURN(TokenBunchVector, obj); } //BIND_END //BIND_METHOD TokenBunchVector at { LUABIND_CHECK_ARGN(==, 1); unsigned int pos; LUABIND_CHECK_PARAMETER(1, uint); LUABIND_GET_PARAMETER(1, uint, pos); AprilUtils::SharedPtr token( (*obj)[pos-1] ); LUABIND_RETURN(AuxToken, token); } //BIND_END //BIND_METHOD TokenBunchVector set { LUABIND_CHECK_ARGN(==, 2); unsigned int pos; AprilUtils::SharedPtr token; LUABIND_CHECK_PARAMETER(1, uint); LUABIND_CHECK_PARAMETER(2, AuxToken); LUABIND_GET_PARAMETER(1, uint, pos); LUABIND_GET_PARAMETER(2, AuxToken, token); (*obj)[pos-1] = token; LUABIND_RETURN(TokenBunchVector, obj); } //BIND_END //BIND_METHOD TokenBunchVector push_back { LUABIND_CHECK_ARGN(==, 1); AprilUtils::SharedPtr token; LUABIND_CHECK_PARAMETER(1, AuxToken); LUABIND_GET_PARAMETER(1, AuxToken, token); obj->TokenBunchVector::push_back(token); LUABIND_RETURN(TokenBunchVector, obj); } //BIND_END //BIND_METHOD TokenBunchVector iterate // para iterar con un for index,value in obj:iterate() do ... end { LUABIND_CHECK_ARGN(==, 0); LUABIND_RETURN(cfunction,token_bunch_vector_iterator_function); LUABIND_RETURN(TokenBunchVector,obj); LUABIND_RETURN(int,0); } //BIND_END april-ann-0.4.1/packages/basics/tokens/c_src/000077500000000000000000000000001263004425400210135ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/tokens/c_src/table_of_token_codes.h000066400000000000000000000053051263004425400253170ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef TABLE_OF_TOKEN_CODES_H #define TABLE_OF_TOKEN_CODES_H #include /* TOKEN TYPE GROUPS PREPARED FOR FUTURE AMPLIATIONS Basic group with 4096 elements (0x1000) Block Number Class 0 0x0000 error types 1 0x1000 signals 2 0x2000 basic types 3 0x3000 vectors 4 0x4000 graphs */ namespace Basics { /// Definition of TokenCode type typedef uint32_t TokenCode; /// Static class which contains TokenCodes for each corresponding Token type class table_of_token_codes { public: // especial codes 1024 (0x400) static const TokenCode error = 0x0000; // notifications 1024 // 1024-20 static const TokenCode signal_end = 0x1000; // basic types 1024 static const TokenCode boolean = 0x2000; static const TokenCode token_char = 0x2001; static const TokenCode token_int32 = 0x2002; static const TokenCode token_uint32 = 0x2003; static const TokenCode token_mem_block = 0x2004; static const TokenCode token_matrix = 0x2005; static const TokenCode token_sparse_matrix = 0x2006; static const TokenCode token_null = 0x2999; // vectors: static const TokenCode vector_float = 0x3000; static const TokenCode vector_double = 0x3001; static const TokenCode vector_log_float = 0x3002; static const TokenCode vector_log_double = 0x3003; static const TokenCode vector_char = 0x3004; static const TokenCode vector_int32 = 0x3005; static const TokenCode vector_uint32 = 0x3006; static const TokenCode vector_SymbolScores = 0x3007; static const TokenCode vector_Tokens = 0x3008; // graph protocol: static const TokenCode token_idag = 0x4000; }; } // namespace Basics #endif // TABLE_OF_TOKEN_CODES_H april-ann-0.4.1/packages/basics/tokens/c_src/token_base.cc000066400000000000000000000020031263004425400234270ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include "token_base.h" #include "token_null.h" namespace Basics { Token::Token() : Referenced() { } Token::~Token() { } } // namespace Basics april-ann-0.4.1/packages/basics/tokens/c_src/token_base.h000066400000000000000000000133311263004425400232770ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef TOKEN_BASE_H #define TOKEN_BASE_H #include #include #include "april_assert.h" #include "buffer_list.h" #include "constString.h" #include "disallow_class_methods.h" #include "lua_table.h" #include "referenced.h" #include "smart_ptr.h" #include "table_of_token_codes.h" namespace Basics { /// A pure abstract class with interface of Token. A Token represents the /// concept of a datatype throught Dataflow architectures (even Artificial /// Neural Network components). class Token : public Referenced { APRIL_DISALLOW_COPY_AND_ASSIGN(Token); public: Token(); virtual ~Token(); /// This method implements a deep copy virtual Token *clone() const = 0; /// FOR DEBUG PURPOSES virtual AprilUtils::buffer_list* debugString(const char *prefix, int debugLevel)=0; /// Abstract method which indicates the TokenCode of child Token classes virtual TokenCode getTokenCode() const = 0; /// Abstract method for serialization purposes virtual AprilUtils::buffer_list* toString()=0; // ALL TOKENS MUST IMPLEMENT THIS STATIC METHOD FOR SERIALIZATION PURPOSES // Token *fromString(AprilUtils::constString &cs); /// Templatized method which returns true if a Token pointer could be /// transformed to a given Token child class template bool isA() const { return typeid(T) == typeid(*this); } /// Templatized method which converts the given Token pointer to a Token child /// class template T convertTo(); /// Templatized method which converts the given Token pointer to a Token child /// class and throws an error in case of failure template T convertToAndCheck(); /// Templatized method which converts the given const Token pointer to a const /// Token child class template const T convertTo() const; /// Templatized method which converts the given const Token pointer to a const /// Token child class and throws an error in case of failure template const T convertToAndCheck() const; }; /// TokenNull is a singleton class which represents a void Token. class TokenNull : public Token { APRIL_DISALLOW_COPY_AND_ASSIGN(TokenNull); TokenNull() { } public: static TokenNull *getInstance() { static AprilUtils::SharedPtr singleton( new TokenNull() ); return singleton.get(); } virtual ~TokenNull() { } virtual Token *clone() const { return getInstance(); } // FOR DEBUG PURPOSES // TODO: virtual AprilUtils::buffer_list* debugString(const char *prefix, int debugLevel) { UNUSED_VARIABLE(prefix); UNUSED_VARIABLE(debugLevel); return 0; } virtual TokenCode getTokenCode() const { return table_of_token_codes::token_null; } // TODO: virtual AprilUtils::buffer_list* toString() { return 0; } // ALL TOKENS MUST IMPLEMENT THIS STATIC METHOD FOR SERIALIZATION PURPOSES // TODO: // Token *fromString(AprilUtils::constString &cs); }; template T Token::convertTo() { if (static_cast(this) == static_cast(TokenNull::getInstance())) { return static_cast(0); } T result = dynamic_cast(this); april_assert(result != 0); return result; } template const T Token::convertTo() const { if (static_cast(this) == static_cast(TokenNull::getInstance())) { return static_cast(0); } const T result = dynamic_cast(this); april_assert(result != 0); return result; } template T Token::convertToAndCheck() { T result = this->convertTo(); if (result == 0) { ERROR_EXIT1(256, "Unable to convert the given token into %s", typeid(T).name()); } return result; } template const T Token::convertToAndCheck() const { const T result = this->convertTo(); if (result == 0) { ERROR_EXIT1(256, "Unable to convert the given token into %s", typeid(T).name()); } return result; } } // namespace Basics //////////////////////////////////////////////////////////////////////////// namespace AprilUtils { template<> AprilUtils::SharedPtr LuaTable:: convertTo< AprilUtils::SharedPtr >(lua_State *L, int idx); template<> void LuaTable::pushInto< Basics::Token* >(lua_State *L, Basics::Token *value); template<> void LuaTable:: pushInto< Basics::Token >(lua_State *L, AprilUtils::SharedPtr value); template<> bool LuaTable:: checkType< AprilUtils::SharedPtr >(lua_State *L, int idx); } #endif // TOKEN_BASE_H april-ann-0.4.1/packages/basics/tokens/c_src/token_matrix.cc000066400000000000000000000016131263004425400240270ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "token_matrix.h" namespace Basics { template class TokenMatrix; } april-ann-0.4.1/packages/basics/tokens/c_src/token_matrix.h000066400000000000000000000056341263004425400237000ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef TOKEN_MATRIX_H #define TOKEN_MATRIX_H #include "disallow_class_methods.h" #include "matrix.h" #include "token_base.h" #include "unused_variable.h" namespace Basics { template class TokenMatrix : public Token { APRIL_DISALLOW_COPY_AND_ASSIGN(TokenMatrix); Matrix *mat; public: TokenMatrix(Matrix *mat); ~TokenMatrix(); Matrix *getMatrix() { return mat; } const Matrix *getMatrix() const { return mat; } unsigned int size() const { return mat->size(); } Token *clone() const; AprilUtils::buffer_list* toString(); AprilUtils::buffer_list* debugString(const char *prefix, int debugLevel); TokenCode getTokenCode() const; static Token *fromString(AprilUtils::constString &cs) { // NOT IMPLEMENTED UNUSED_VARIABLE(cs); return 0; } bool getCudaFlag() { return mat->getCudaFlag(); } void printDebug() { /* const float *data = mem_block->getPPALForRead(); for (unsigned int i=0; i TokenMatrix::TokenMatrix(Matrix *mat) : Token(), mat(mat) { IncRef(mat); } template TokenMatrix::~TokenMatrix() { DecRef(mat); } template Token *TokenMatrix::clone() const { TokenMatrix *token = new TokenMatrix( mat->clone() ); return token; } template AprilUtils::buffer_list* TokenMatrix::toString() { // NOT IMPLEMENTED return 0; } template AprilUtils::buffer_list* TokenMatrix::debugString(const char *prefix, int debugLevel) { // NOT IMPLEMENTED UNUSED_VARIABLE(prefix); UNUSED_VARIABLE(debugLevel); return 0; } template TokenCode TokenMatrix::getTokenCode() const { return table_of_token_codes::token_matrix; } /////////////////////////////////////////////////////////////////////////// typedef TokenMatrix TokenMatrixFloat; } // namespace Basics #endif // TOKEN_MATRIX_H april-ann-0.4.1/packages/basics/tokens/c_src/token_memory_block.cc000066400000000000000000000046701263004425400252130ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "gpu_mirrored_memory_block.h" #include "mathcore.h" #include "token_memory_block.h" using AprilUtils::buffer_list; namespace Basics { TokenMemoryBlock::TokenMemoryBlock() : Token(), mem_block(0), used_size(0) { } TokenMemoryBlock::TokenMemoryBlock(unsigned int size) : Token(), mem_block(0), used_size(0) { resize(size); } TokenMemoryBlock::~TokenMemoryBlock() { delete mem_block; } void TokenMemoryBlock::setData(float *data, unsigned int size) { resize(size); float *mem_ptr = mem_block->getPPALForWrite(); for (unsigned int i=0; i mem_block->getSize()) { delete mem_block; mem_block = new AprilMath::FloatGPUMirroredMemoryBlock(size); } used_size = size; } Token *TokenMemoryBlock::clone() const { TokenMemoryBlock *token = new TokenMemoryBlock(mem_block->getSize()); token->used_size = used_size; doCopy(mem_block->getSize(), mem_block, 0, 1, token->mem_block, 0, 1, false); return token; } buffer_list* TokenMemoryBlock::toString() { // NOT IMPLEMENTED return 0; } buffer_list* TokenMemoryBlock::debugString(const char *prefix, int debugLevel) { // NOT IMPLEMENTED UNUSED_VARIABLE(prefix); UNUSED_VARIABLE(debugLevel); return 0; } TokenCode TokenMemoryBlock::getTokenCode() const { return table_of_token_codes::token_mem_block; } } // namespace Basics april-ann-0.4.1/packages/basics/tokens/c_src/token_memory_block.h000066400000000000000000000044311263004425400250500ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef TOKEN_MEMORY_BLOCK_H #define TOKEN_MEMORY_BLOCK_H #include "disallow_class_methods.h" #include "gpu_mirrored_memory_block.h" #include "token_base.h" #include "unused_variable.h" namespace Basics { class TokenMemoryBlock : public Token { APRIL_DISALLOW_COPY_AND_ASSIGN(TokenMemoryBlock); AprilMath::FloatGPUMirroredMemoryBlock *mem_block; unsigned int used_size; public: TokenMemoryBlock(); TokenMemoryBlock(unsigned int size); ~TokenMemoryBlock(); void setData(float *data, unsigned int size); AprilMath::FloatGPUMirroredMemoryBlock *getMemBlock() { return mem_block; } unsigned int getUsedSize() const { return used_size; } unsigned int getMaxSize() const { return mem_block?mem_block->getSize():0; } void resize(unsigned int size); Token *clone() const; AprilUtils::buffer_list* toString(); AprilUtils::buffer_list* debugString(const char *prefix, int debugLevel); TokenCode getTokenCode() const; static Token *fromString(AprilUtils::constString &cs) { // NOT IMPLEMENTED UNUSED_VARIABLE(cs); return 0; } void clear() { used_size = 0; } bool getInCudag() { return mem_block->getInCuda(); } void printDebug() { const float *data = mem_block->getPPALForRead(); for (unsigned int i=0; igetSize(), mem_block, 1u, 0u, mem_block, 1u, 0u, use_cuda, AprilMath::m_curried_fill(0.0f)); } } // namespace Basics april-ann-0.4.1/packages/basics/tokens/c_src/token_null.h000066400000000000000000000016531263004425400233430ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef TOKEN_NULL_H #define TOKEN_NULL_H #include "token_base.h" #endif // TOKEN_NULL_H april-ann-0.4.1/packages/basics/tokens/c_src/token_sparse_matrix.cc000066400000000000000000000016301263004425400254030ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "token_sparse_matrix.h" namespace Basics { template class TokenSparseMatrix; } april-ann-0.4.1/packages/basics/tokens/c_src/token_sparse_matrix.h000066400000000000000000000060731263004425400252530ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef TOKEN_SPARSE_MATRIX_H #define TOKEN_SPARSE_MATRIX_H #include "disallow_class_methods.h" #include "matrix.h" #include "token_base.h" #include "unused_variable.h" namespace Basics { template class TokenSparseMatrix : public Token { APRIL_DISALLOW_COPY_AND_ASSIGN(TokenSparseMatrix); SparseMatrix *mat; public: TokenSparseMatrix(SparseMatrix *mat); ~TokenSparseMatrix(); SparseMatrix *getMatrix() { return mat; } const SparseMatrix *getMatrix() const { return mat; } unsigned int size() const { return mat->size(); } Token *clone() const; AprilUtils::buffer_list* toString(); AprilUtils::buffer_list* debugString(const char *prefix, int debugLevel); TokenCode getTokenCode() const; static Token *fromString(AprilUtils::constString &cs) { // NOT IMPLEMENTED UNUSED_VARIABLE(cs); return 0; } bool getCudaFlag() { return mat->getCudaFlag(); } void printDebug() { /* const float *data = mem_block->getPPALForRead(); for (unsigned int i=0; i TokenSparseMatrix::TokenSparseMatrix(SparseMatrix *mat) : Token(), mat(mat) { IncRef(mat); } template TokenSparseMatrix::~TokenSparseMatrix() { DecRef(mat); } template Token *TokenSparseMatrix::clone() const { TokenSparseMatrix *token = new TokenSparseMatrix( mat->clone() ); return token; } template AprilUtils::buffer_list* TokenSparseMatrix::toString() { // NOT IMPLEMENTED return 0; } template AprilUtils::buffer_list* TokenSparseMatrix::debugString(const char *prefix, int debugLevel) { // NOT IMPLEMENTED UNUSED_VARIABLE(prefix); UNUSED_VARIABLE(debugLevel); return 0; } template TokenCode TokenSparseMatrix::getTokenCode() const { return table_of_token_codes::token_sparse_matrix; } /////////////////////////////////////////////////////////////////////////// typedef TokenSparseMatrix TokenSparseMatrixFloat; } // namespace Basics #endif // TOKEN_SPARSE_MATRIX_H april-ann-0.4.1/packages/basics/tokens/c_src/token_vector.cc000066400000000000000000000245001263004425400240250ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include "unused_variable.h" #include "token_vector.h" #include "binarizer.h" #include "table_of_token_codes.h" using AprilUtils::buffer_list; using AprilUtils::constString; using AprilUtils::vector; using AprilUtils::pair; namespace Basics { template TokenVector::TokenVector() : TokenVectorGeneric() { } template TokenVector::TokenVector(unsigned int vlength) : TokenVectorGeneric(), vec(vlength) { } template TokenVector::TokenVector(const T *vec, unsigned int vlength) : TokenVectorGeneric(), vec(vec, vec+vlength) { } template TokenVector::TokenVector(const vector &vec) : TokenVectorGeneric(), vec(vec) { } template TokenVector::~TokenVector() { } template Token *TokenVector::clone() const { return new TokenVector(vec); } template buffer_list* TokenVector::toString() { // ERROR, no se puede serializar de forma general return 0; // para indicar error } template buffer_list* TokenVector::debugString(const char *prefix, int debugLevel) { UNUSED_VARIABLE(debugLevel); buffer_list *resul = new buffer_list; resul->add_formatted_string_right("%s TokenVector of generic type\n",prefix); return resul; } template TokenCode TokenVector::getTokenCode() const { return table_of_token_codes::error; } template Token *TokenVector::fromString(constString &cs) { UNUSED_VARIABLE(cs); return 0; // no hay un fromString generico } // ------------------------- vector float ------------------------- template<> buffer_list* TokenVector::toString() { buffer_list *resul = new buffer_list; resul->add_binarized_float_left(vec.begin(),vec.size()); return resul; } template<> buffer_list* TokenVector::debugString(const char *prefix, int debugLevel) { // TODO: de momento ignoramos debugLevel UNUSED_VARIABLE(debugLevel); buffer_list *resul = new buffer_list; resul->add_formatted_string_right("%s TokenVector_float with %d values\n", prefix,vec.size()); return resul; } template <> TokenCode TokenVector::getTokenCode() const { return table_of_token_codes::vector_float; } template <> Token *TokenVector::fromString(constString &cs) { if (cs.len() % 5 != 0) return 0; // talla incorrecta int vec_len = cs.len() / 5; TokenVector *resul = new TokenVector(vec_len); bool all_is_ok = true; for (int i=0; all_is_ok && ivec[i])); } if (!all_is_ok) { delete resul; resul = 0; } return resul; } // ------------------------- vector double ------------------------- template <> buffer_list* TokenVector::toString() { buffer_list *resul = new buffer_list; resul->add_binarized_double_left(vec.begin(),vec.size()); return resul; } template <> buffer_list* TokenVector::debugString(const char *prefix, int debugLevel) { // TODO: de momento ignoramos debugLevel UNUSED_VARIABLE(debugLevel); buffer_list *resul = new buffer_list; resul->add_formatted_string_right("%s TokenVector_double with %u values\n", prefix,vec.size()); return resul; } template <> TokenCode TokenVector::getTokenCode() const { return table_of_token_codes::vector_double; } template <> Token *TokenVector::fromString(constString &cs) { if (cs.len() % 10 != 0) return 0; // talla incorrecta int vec_len = cs.len() / 10; TokenVector *resul = new TokenVector(vec_len); bool all_is_ok = true; for (int i=0; all_is_ok && ivec[i])); } if (!all_is_ok) { delete resul; resul = 0; } return resul; } // ------------------------- vector int32 ------------------------- template <> buffer_list* TokenVector::toString() { buffer_list *resul = new buffer_list; resul->add_binarized_int32_left(vec.begin(),vec.size()); return resul; } template <> buffer_list* TokenVector::debugString(const char *prefix, int debugLevel) { // TODO: de momento ignoramos debugLevel UNUSED_VARIABLE(debugLevel); buffer_list *resul = new buffer_list; resul->add_formatted_string_right("%s TokenVector_int32 with %d values\n", prefix,vec.size()); return resul; } template <> TokenCode TokenVector::getTokenCode() const { return table_of_token_codes::vector_int32; } template <> Token *TokenVector::fromString(constString &cs) { if (cs.len() % 5 != 0) return 0; // talla incorrecta int vec_len = cs.len() / 5; TokenVector *resul = new TokenVector(vec_len); bool all_is_ok = true; for (int i=0; all_is_ok && ivec[i])); } if (!all_is_ok) { delete resul; resul = 0; } return resul; } // ------------------------- vector uint32_t ------------------------- template <> buffer_list* TokenVector::toString() { buffer_list *resul = new buffer_list; resul->add_binarized_uint32_left(vec.begin(),vec.size()); return resul; } template <> buffer_list* TokenVector::debugString(const char *prefix, int debugLevel) { // TODO: de momento ignoramos debugLevel UNUSED_VARIABLE(debugLevel); buffer_list *resul = new buffer_list; resul->add_formatted_string_right("%s TokenVector_uint32 with %d values\n", prefix,vec.size()); return resul; } template <> TokenCode TokenVector::getTokenCode() const { return table_of_token_codes::vector_uint32; } template <> Token *TokenVector::fromString(constString &cs) { if (cs.len() % 5 != 0) return 0; // talla incorrecta int vec_len = cs.len() / 5; TokenVector *resul = new TokenVector(vec_len); bool all_is_ok = true; for (int i=0; all_is_ok && ivec[i])); } if (!all_is_ok) { delete resul; resul = 0; } return resul; } // ------------------------- vector char ------------------------- template <> buffer_list* TokenVector::toString() { buffer_list *resul = new buffer_list; resul->add_constString_left(constString(vec.begin(),vec.size())); return resul; } template <> buffer_list* TokenVector::debugString(const char *prefix, int debugLevel) { // TODO: de momento ignoramos debugLevel UNUSED_VARIABLE(debugLevel); buffer_list *resul = new buffer_list; resul->add_formatted_string_right("%s TokenVector_char with %d values\n", prefix,vec.size()); return resul; } template <> TokenCode TokenVector::getTokenCode() const { return table_of_token_codes::vector_char; } template <> Token *TokenVector::fromString(constString &cs) { TokenVector *resul = new TokenVector((const char*)cs,cs.len()); return resul; } // ------------------------- vector token ------------------------- template <> buffer_list* TokenVector >::toString() { /* buffer_list *resul = new buffer_list; char b[5]; constString cs(binarizer::code_uint32(vec.size())); resul->add_constString_left(cs); for (unsigned int i=0; iadd_buffer_right(vec[i].toString()); return resul; */ // NOT IMPLEMENTED return 0; } template <> buffer_list* TokenVector >::debugString(const char *prefix, int debugLevel) { // TODO: de momento ignoramos debugLevel UNUSED_VARIABLE(debugLevel); buffer_list *resul = new buffer_list; resul->add_formatted_string_right("%s TokenVector_Token with %d values\n", prefix,vec.size()); return resul; } template <> TokenCode TokenVector >::getTokenCode() const { return table_of_token_codes::vector_Tokens; } template <> Token *TokenVector >::fromString(constString &cs) { UNUSED_VARIABLE(cs); /* uint32_t size; cs.extract_uint32_binary(&size); TokenVector *resul = new TokenVector(); resul->vec.resize(size); for (unsigned int i=0; i resul->vec.push_back( } return resul; */ // NOT IMPLEMENTED return 0; } // ---------------------------------------------------------------- template class TokenVector; template class TokenVector; template class TokenVector; template class TokenVector; template class TokenVector; template class TokenVector >; } // namespace Basics april-ann-0.4.1/packages/basics/tokens/c_src/token_vector.h000066400000000000000000000130221263004425400236640ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef TOKEN_VECTOR_H #define TOKEN_VECTOR_H #include "pair.h" #include "smart_ptr.h" #include "token_base.h" #include "vector.h" namespace Basics { class TokenVectorGeneric : public Token { APRIL_DISALLOW_COPY_AND_ASSIGN(TokenVectorGeneric); public: TokenVectorGeneric() : Token() { } virtual unsigned int size() const = 0; virtual void clear() = 0; }; template class TokenVector : public TokenVectorGeneric { APRIL_DISALLOW_COPY_AND_ASSIGN(TokenVector); AprilUtils::vector vec; public: TokenVector(); TokenVector(unsigned int vlength); // always copy the vector TokenVector(const T *vec, unsigned int vlength); TokenVector(const AprilUtils::vector &vec); ~TokenVector(); T& operator[] (unsigned int i) { return vec[i]; } const T& operator[] (unsigned int i) const { return vec[i]; } AprilUtils::vector &getContainer() { return vec; } const AprilUtils::vector &getContainer() const { return vec; } void push_back(T const &data) { vec.push_back(data); } T *data() { return vec.begin(); } const T *data() const { return vec.begin(); } Token *clone() const; AprilUtils::buffer_list* toString(); AprilUtils::buffer_list* debugString(const char *prefix, int debugLevel); TokenCode getTokenCode() const; static Token *fromString(AprilUtils::constString &cs); virtual unsigned int size() const { return vec.size(); } virtual void clear() { vec.clear(); } }; typedef TokenVector TokenVectorFloat; typedef TokenVector TokenVectorDouble; typedef TokenVector TokenVectorInt32; typedef TokenVector TokenVectorUint32; typedef TokenVector TokenVectorChar; typedef TokenVector > TokenBunchVector; /* forward declarations */ template<> AprilUtils::buffer_list* TokenVector::toString(); template<> AprilUtils::buffer_list* TokenVector::debugString(const char *prefix, int debugLevel); template <> TokenCode TokenVector::getTokenCode() const; template <> Token *TokenVector::fromString(AprilUtils::constString &cs); // ------------------------- vector double ------------------------- template <> AprilUtils::buffer_list* TokenVector::toString(); template <> AprilUtils::buffer_list* TokenVector::debugString(const char *prefix, int debugLevel); template <> TokenCode TokenVector::getTokenCode() const; template <> Token *TokenVector::fromString(AprilUtils::constString &cs); // ------------------------- vector int32 ------------------------- template <> AprilUtils::buffer_list* TokenVector::toString(); template <> AprilUtils::buffer_list* TokenVector::debugString(const char *prefix, int debugLevel); template <> TokenCode TokenVector::getTokenCode() const; template <> Token *TokenVector::fromString(AprilUtils::constString &cs); // ------------------------- vector uint32_t ------------------------- template <> AprilUtils::buffer_list* TokenVector::toString(); template <> AprilUtils::buffer_list* TokenVector::debugString(const char *prefix, int debugLevel); template <> TokenCode TokenVector::getTokenCode() const; template <> Token *TokenVector::fromString(AprilUtils::constString &cs); // ------------------------- vector char ------------------------- template <> AprilUtils::buffer_list* TokenVector::toString(); template <> AprilUtils::buffer_list* TokenVector::debugString(const char *prefix, int debugLevel); template <> TokenCode TokenVector::getTokenCode() const; template <> Token *TokenVector::fromString(AprilUtils::constString &cs); // ------------------------- vector token ------------------------- template <> AprilUtils::buffer_list* TokenVector >::toString(); template <> AprilUtils::buffer_list* TokenVector >::debugString(const char *prefix, int debugLevel); template <> TokenCode TokenVector >::getTokenCode() const; template <> Token *TokenVector >::fromString(AprilUtils::constString &cs); } // namespace Basics #endif // TOKEN_VECTOR_H april-ann-0.4.1/packages/basics/tokens/lua_src/000077500000000000000000000000001263004425400213525ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/tokens/lua_src/tokens.lua000066400000000000000000000021051263004425400233560ustar00rootroot00000000000000tokens = tokens or {} --------------------------------------------------------------------------- class.extend(tokens.null, "to_lua_string", function(self) return "tokens.null()" end) class.extend(tokens.vector.bunch, "to_lua_string", function(self, format) local str = { "tokens.vector.bunch{" } for i,v in self:iterate() do str[#str+1] = util.to_lua_string(v, format) str[#str+1] = "," end str[#str+1] = "}" return table.concat(str) end) class.declare_functional_index(tokens.vector.bunch, function(self,key) local k = tonumber(key) return (k and self:at(k)) or nil end) class.extend_metamethod(tokens.vector.bunch, "__newindex", function(self,key,value) local k = assert(tonumber(key), "Needs a number key") return self:set(k,value) end) april-ann-0.4.1/packages/basics/tokens/package.lua000066400000000000000000000021421263004425400220170ustar00rootroot00000000000000package{ name = "tokens", version = "1.0", depends = { "util", "mathcore", "matrix" }, keywords = { }, description = "", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_tokens.lua.cc" , dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", dest_dir = "build", -- flags = "-std=c99", }, object{ file = "c_src/*.cu", dest_dir = "build", -- flags = "-std=c99", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_tokens.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/utest/000077500000000000000000000000001263004425400175635ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/utest/lua_src/000077500000000000000000000000001263004425400212135ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/utest/lua_src/utest.lua000066400000000000000000000147331263004425400230720ustar00rootroot00000000000000-- This module allows unit testing in APRIL-ANN. This module uses internal -- variables to account for 'passed' and 'failed' tests. At the end of the -- program a summary will be printed to stderr. In case of a non-terminal -- output, only the 'failed' tests will produce a print out. This module exports -- the following functions: -- -- utest.check(function, error_message): executes the given function, in case of -- fail, it shows the error_message -- -- utest.check.success(function, error_message): an alias of previous one -- -- utest.check.fail(function, error_message): the opposite of previous one -- -- utest.check.number_eq(a, b, epsilon, error_message): tests of a == b with epsilon tolerance -- -- utest.check.eq(a, b, error_message): tests of a == b -- -- utest.check.neq(a, b, error_message): tests of a ~= b -- -- utest.check.lt(a, b, error_message): tests of a < b -- -- utest.check.le(a, b, error_message): tests of a <= b -- -- utest.check.gt(a, b, error_message): tests of a > b -- -- utest.check.ge(a, b, error_message): tests of a >= b -- -- utest.check.TRUE(a, error_message): tests of a == true -- -- utest.check.FALSE(a, error_message): tests of a == false ------------------------------------------------------------------------------- utest = utest or {} -- local function write(level,format,...) if level>0 or util.stdout_is_a_terminal() then fprintf(io.stderr, format,...) end end -- utest.warning = function(format,...) return fprintf(io.stderr, table.concat({ "\t", ansi.fg.bright_yellow, "Warning: ", ansi.fg.default, format }), ...) end -- local NONAMED = "UNKNOWN" local test_name = NONAMED local testn = 0 local passed = 0 local failed = 0 local failed_list = {} local names_order = {} utest.finish = function() write((failed > 0 and 1) or 0, "%d total tests: %s%d passed%s, %s%d failed%s\n", testn, ansi.fg.bright_green, passed, ansi.fg.default, ansi.fg.bright_red, failed, ansi.fg.default) if failed > 0 then for _,name in ipairs(names_order) do write(1, "%sTest failed%s %s\tList: [ %s ]\n"% {ansi.fg.bright_red, ansi.fg.default, name, #failed_list[name] < 20 and table.concat( failed_list[name], ", ") or "too large to be displayed"}) end os.exit(1) end write(0, "%sOk%s\n", ansi.fg.bright_green, ansi.fg.default) end local selected_tests local function register() -- global utest.__initialized__ = {} setmetatable(utest.__initialized__, { __gc = utest.finish }) if not selected_tests then utest.select_tests(arg) end end -- local check = function (func,error_msg) if not utest.__initialized__ then register() end testn = testn + 1 local ret = table.pack(xpcall(func,debug.traceback)) local ok = table.remove(ret,1) local success = ret[1] if ok and success then write(0, "Test %s %d: %sok%s\n", test_name, testn, ansi.fg.bright_green, ansi.fg.default) passed = passed + 1 return true else if not ok then -- protected call to write, in case tostring fails with returned values pcall(function() write(1, "%s\n", iterator(ipairs(ret)):select(2):map(tostring):concat(" ")) end) end write(1, "Test %s %d: %sfail%s", test_name, testn, ansi.fg.bright_red, ansi.fg.default) if error_msg then if type(error_msg) == "function" then error_msg = error_msg() or "" else error_msg = tostring(error_msg) end error_msg = ", msg: %s"%{error_msg} end write(1, "%s, it follows the traceback\n", error_msg or "") write(1, "%s\n", debug.traceback()) failed = failed + 1 if not failed_list[test_name] then table.insert(names_order, test_name) failed_list[test_name] = {} end table.insert(failed_list[test_name], testn) return false end end utest.check = { } -- utest.check.number_eq = function(a, b, epsilon, ...) local epsilon = epsilon or 0.02 return check(function() if a == 0 and b == 0 then return true end return math.abs(a-b)/math.abs(a+b) < epsilon end, ...) end utest.check.eq = function(a, b, ...) return check(function() return a == b end, ...) end utest.check.neq = function(a, b, ...) return check(function() return a ~= b end, ...) end utest.check.lt = function(a, b, ...) return check(function() return a < b end, ...) end utest.check.le = function(a, b, ...) return check(function() return a <= b end, ...) end utest.check.gt = function(a, b, ...) return check(function() return a > b end, ...) end utest.check.ge = function(a, b, ...) return check(function() return a > b end, ...) end utest.check.success = check utest.check.fail = function(f, ...) return check(function() return not f() end, ...) end utest.check.errored = function(f, ...) util.silent_errors(true) local ok = check(function() local ok=pcall(f) return not ok end, ...) util.silent_errors(false) return ok end utest.check.TRUE = function(a, ...) return check(function() return a end, ...) end utest.check.FALSE = function(a, ...) return check(function() return not a end, ...) end utest.check.NIL = function(a, ...) return check(function() return a==nil end, ...) end utest.check.NAN = function(a, ...) return check(function() return tonumber(a) and tostring(a)=="nan" end, ...) end -- utest.test = function(name, test_func) assert( test_name == NONAMED ) assert( type(name) == "string", "Needs a string as first argument" ) assert( type(test_func) == "function", "Needs a function as second argument") if not utest.__initialized__ then register() end if selected_tests and not selected_tests[name] then return end test_name = name local ok,msg = xpcall(test_func,debug.traceback) if not ok then write(1, "Test %s: %sexecutionfailure%s\n", test_name, ansi.fg.bright_red, ansi.fg.default) write(1, "%s\n", msg) failed = failed + 1 if not failed_list[test_name] then table.insert(names_order, test_name) failed_list[test_name] = {} end table.insert(failed_list[test_name], "executionfailure") end test_name = NONAMED end -- utest.select_tests = function(arg) if #arg > 0 then selected_tests = table.invert(arg) end end -- setmetatable(utest.check,{ __call = function(self,...) return check(...) end }) -- global call to select test from command line arguments april-ann-0.4.1/packages/basics/utest/package.lua000066400000000000000000000012421263004425400216600ustar00rootroot00000000000000package{ name = "utest", version = "1.0", depends = { "util" }, keywords = { }, description = "Unit testing", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", }, target{ name = "build", depends = "provide", use_timestamp = true, luac{ orig_dir = "lua_src", dest_dir = "build", }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/util/000077500000000000000000000000001263004425400173745ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/util/binding/000077500000000000000000000000001263004425400210065ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/util/binding/bind_util.lua.cc000066400000000000000000000563261263004425400240620ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_H #include #include #include #ifdef USE_MKL extern "C" { #include #include #include #include } #endif #include "mfset.h" #include "mmapped_data.h" #include "linear_least_squares.h" #include "lua_table.h" #include "popen2.h" #include "signal_handler.h" #include "trie_vector.h" #include "trie_hash_4_lua.h" #include "stopwatch.h" #include "words_table.h" using namespace AprilUtils; extern const char *__COMMIT_NUMBER__; extern const char *__COMMIT_HASH__; extern const char *__APRILANN_VERSION_MAJOR__; extern const char *__APRILANN_VERSION_MINOR__; int lua_isLuaTable(lua_State *L, int index); AprilUtils::LuaTable lua_toLuaTable(lua_State *L, int index); AprilUtils::LuaTable luaL_optLuaTable(lua_State *L, int index); void lua_pushLuaTable(lua_State *L, AprilUtils::LuaTable &table); //BIND_END //BIND_HEADER_C #include #include #include #include #include extern "C" { #include #include #include #include } #ifndef NO_OMP #include #endif #include "binarizer.h" #include "error_print.h" #include "omp_utils.h" #include "smart_ptr.h" int lua_isLuaTable(lua_State *L, int index) { return lua_istable(L, index); } AprilUtils::LuaTable lua_toLuaTable(lua_State *L, int index) { return AprilUtils::LuaTable(L, index); } AprilUtils::LuaTable luaL_optLuaTable(lua_State *L, int index) { if (lua_gettop(L) >= index) return AprilUtils::LuaTable(L, index); else return AprilUtils::LuaTable(L); } void lua_pushLuaTable(lua_State *L, AprilUtils::LuaTable &table) { table.pushTable(L); } namespace AprilUtils { template<> LuaTable LuaTable::convertTo(lua_State *L, int idx) { return lua_toLuaTable(L, idx); } template<> void LuaTable::pushInto(lua_State *L, LuaTable value) { value.pushTable(L); } template<> bool LuaTable::checkType(lua_State *L, int idx) { return lua_isLuaTable(L, idx); } template<> stopwatch *LuaTable:: convertTo(lua_State *L, int idx) { return lua_tostopwatch(L, idx); } template<> void LuaTable:: pushInto(lua_State *L, stopwatch *value) { lua_pushstopwatch(L, value); } template<> bool LuaTable:: checkType(lua_State *L, int idx) { return lua_isstopwatch(L, idx); } } // COPIED FROM liolib.c:168 static int io_fclose (lua_State *L) { luaL_Stream *p = ((luaL_Stream *)luaL_checkudata(L, 1, LUA_FILEHANDLE)); int res = fclose(p->f); return luaL_fileresult(L, (res == 0), NULL); } // COPIED FROM liolib.c, newprefile and newfile functions FILE **newfile (lua_State *L) { luaL_Stream *p = (luaL_Stream *)lua_newuserdata(L, sizeof(luaL_Stream)); p->closef = &io_fclose; p->f = NULL; luaL_setmetatable(L, LUA_FILEHANDLE); return &p->f; } //BIND_END //BIND_STATIC_CONSTRUCTOR utils_static_constructor { binarizer::init(); SignalHandler::initialize(L); } //BIND_END //BIND_FUNCTION util.version { LUABIND_RETURN(int, atoi(__APRILANN_VERSION_MAJOR__)); LUABIND_RETURN(int, atoi(__APRILANN_VERSION_MINOR__)); LUABIND_RETURN(string, __COMMIT_NUMBER__); LUABIND_RETURN(string, __COMMIT_HASH__); } //BIND_END //BIND_FUNCTION util.is_cuda_available { #ifdef USE_CUDA LUABIND_RETURN(bool, true); #else LUABIND_RETURN(bool, false); #endif } //BIND_END //BIND_FUNCTION util.omp_set_num_threads { #ifndef NO_OMP int n; LUABIND_CHECK_ARGN(==, 1); LUABIND_GET_PARAMETER(1, int, n); omp_set_num_threads(n); #ifdef USE_MKL mkl_set_num_threads(n); #endif #endif } //BIND_END //BIND_FUNCTION util.omp_get_num_threads { LUABIND_RETURN(int, OMPUtils::get_num_threads()); } //BIND_END //BIND_FUNCTION util.gettimeofday { LUABIND_CHECK_ARGN(==, 0); struct timeval tv; struct timezone tz; tz.tz_minuteswest=0; tz.tz_dsttime=0; if (gettimeofday(&tv, &tz) == -1) { LUABIND_FERROR1("Error in gettimeofday: %s", strerror(errno)); } LUABIND_RETURN(number,tv.tv_sec); LUABIND_RETURN(number,tv.tv_usec); } //BIND_END //BIND_FUNCTION util.execp //DOC_BEGIN // execp(file, arg1, arg2, ...) //DOC_END { int n = lua_gettop(L); AprilUtils::UniquePtr args = new char*[n+1]; const char *file = luaL_checkstring(L, 1); for (int i=1; i<=n; ++i) args[i-1] = const_cast(luaL_checkstring(L, i)); args[n] = NULL; int err = execvp(file, args.get()); if (err < 0) { LUABIND_FERROR1("Error in execvp system call: %s", strerror(errno)); } } //BIND_END //BIND_FUNCTION util.getpid { LUABIND_RETURN(int, getpid()); } //BIND_END //BIND_FUNCTION util.getppid { LUABIND_RETURN(int, getppid()); } //BIND_END //BIND_FUNCTION util.split_process //DOC_BEGIN // split_process(...) /// como fork pero multiple, recibe numero de procesos y devuelve un /// numero entre 1 y numero de procesos //DOC_END { const int TOPE = 100; int num_processes, which_I_am = 1; LUABIND_CHECK_ARGN(==, 1); LUABIND_GET_PARAMETER(1, int, num_processes); if (num_processes < 1 || num_processes > TOPE) LUABIND_FERROR1("Error in split_process, number out of range: %d", num_processes); while (1) { if (which_I_am == num_processes) { // el ultimo hijo no devuelve PID, por que no tiene hijo // asociado LUABIND_RETURN(number,num_processes); break; } pid_t ch_pid=fork(); if (ch_pid != 0) { // el padre LUABIND_RETURN(number,which_I_am); LUABIND_RETURN(number,ch_pid); break; } else { // el hijo which_I_am++; } } } //BIND_END //BIND_FUNCTION util.wait //DOC_BEGIN // pid,status wait(...) /// espera a que terminen UNO de los hijos del proceso /// despues usar split_process //DOC_END { int status; pid_t pid = wait(&status); LUABIND_RETURN(int,pid); LUABIND_RETURN(int,status); } //BIND_END //BIND_FUNCTION util.stdout_is_a_terminal //DOC_BEGIN // bool stdout_is_a_terminal() /// returns true if stdout fd refers to a terminal //DOC_END { LUABIND_RETURN(bool, isatty(1)); } //BIND_END //BIND_FUNCTION util.pipe { int fd[2]; bool iserror = false; int en; // = errno FILE **fpin, **fpout; if (pipe(fd) < 0) { iserror = true; en = errno; } else { fpin = newfile(L); fpout = newfile(L); *fpin = fdopen(fd[0], "r"); if (*fpin==NULL) { iserror=true; en=errno; } else { *fpout = fdopen(fd[1], "w"); if (*fpout==NULL) { iserror=true; en=errno; } else LUABIND_INCREASE_NUM_RETURNS(2); } } if (iserror) LUABIND_FERROR1("Error opening the pipe: %s", strerror(en)); } //BIND_END //BIND_FUNCTION io.popen2 //DOC_BEGIN // popen2(...) /// recibe una cadena con el comando, devuelve nil+msg_error o dos /// descriptores de fichero //DOC_END { constString cs; LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, string); LUABIND_GET_PARAMETER(1,constString,cs); const char *command = (const char *)cs; bool iserror = false; int en; // = errno; int infp, outfp; FILE **fpin, **fpout; if (popen2(command, &infp, &outfp) < 0) { iserror=true; en=errno; } else { fpin = newfile(L); fpout = newfile(L); *fpin = fdopen(infp , "w"); if (*fpin==NULL) { iserror=true; en=errno; } else { *fpout = fdopen(outfp, "r"); if (*fpout==NULL) { iserror=true; en=errno; } } } if (iserror) { lua_pushnil(L); lua_pushfstring(L, "%s: %s", command, strerror(en)); } return 2; } //BIND_END ///////////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME TrieVector util.trie_vector //BIND_CPP_CLASS TrieVector //BIND_CONSTRUCTOR TrieVector { int log_size; LUABIND_GET_PARAMETER(1, int, log_size); TrieVector *obj = new TrieVector(log_size); LUABIND_RETURN(TrieVector, obj); } //BIND_END //BIND_METHOD TrieVector get_size { LUABIND_RETURN(uint, obj->getSize()); } //BIND_END //BIND_METHOD TrieVector get_parent { unsigned int node; LUABIND_GET_PARAMETER(1, uint, node); LUABIND_RETURN(uint, obj->getParent(node)); } //BIND_END //BIND_METHOD TrieVector get_word { unsigned int node; LUABIND_GET_PARAMETER(1, uint, node); LUABIND_RETURN(uint, obj->getWord(node)); } //BIND_END //BIND_METHOD TrieVector has_child { unsigned int node, word, destnode; LUABIND_GET_PARAMETER(1, uint, node); LUABIND_GET_PARAMETER(2, uint, word); bool ret = obj->hasChild(node, word, destnode); LUABIND_RETURN(bool, ret); LUABIND_RETURN(uint, destnode); } //BIND_END //BIND_METHOD TrieVector get_child { unsigned int node, word; LUABIND_GET_PARAMETER(1, uint, node); LUABIND_GET_PARAMETER(2, uint, word); LUABIND_RETURN(uint, obj->getChild(node, word)); } //BIND_END //BIND_METHOD TrieVector has_sequence { unsigned int *sequence, destnode; int length; bool ret; LUABIND_TABLE_GETN(1, length); sequence = new unsigned int[length]; LUABIND_TABLE_TO_VECTOR(1, uint, sequence, length); ret = obj->hasSequence(sequence, length, destnode); LUABIND_RETURN(bool, ret); LUABIND_RETURN(uint, destnode); delete[] sequence; } //BIND_END //BIND_METHOD TrieVector search_sequence { unsigned int *sequence; int length; LUABIND_TABLE_GETN(1, length); sequence = new unsigned int[length]; LUABIND_TABLE_TO_VECTOR(1, uint, sequence, length); unsigned int id = obj->searchSequence(sequence, length); LUABIND_RETURN(uint, id); delete[] sequence; } //BIND_END //BIND_METHOD TrieVector get_sequence { unsigned int node; int maxlength; LUABIND_GET_PARAMETER(1, uint, node); LUABIND_GET_PARAMETER(2, int, maxlength); unsigned int *sequence = new unsigned int[maxlength]; int ret = obj->getSequence(node, sequence, maxlength); if (ret >= 0) { LUABIND_VECTOR_TO_NEW_TABLE(uint, sequence, ret); LUABIND_RETURN_FROM_STACK(-1); } delete[] sequence; } //BIND_END //BIND_METHOD TrieVector root_node { LUABIND_RETURN(uint, obj->rootNode()); } //BIND_END //BIND_METHOD TrieVector clear { obj->clear(); } //BIND_END ///////////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME TrieHash4Lua util.trie_hash //BIND_CPP_CLASS TrieHash4Lua //BIND_CONSTRUCTOR TrieHash4Lua { LUABIND_RETURN(TrieHash4Lua, new TrieHash4Lua()); } //BIND_END //BIND_METHOD TrieHash4Lua reserveId { LUABIND_RETURN(int, obj->reserveId()); } //BIND_END //BIND_METHOD TrieHash4Lua find { int *sequence, length; LUABIND_TABLE_GETN(1, length); sequence = new int[length]; LUABIND_TABLE_TO_VECTOR(1, int, sequence, length); LUABIND_RETURN(int, obj->find(sequence, length)); delete[] sequence; } //BIND_END ///////////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME MFSet util.mfset //BIND_CPP_CLASS MFSet //BIND_CONSTRUCTOR MFSet { obj = new MFSet(); LUABIND_RETURN(MFSet, obj); } //BIND_END //BIND_METHOD MFSet set_size { int sz; LUABIND_GET_PARAMETER(1, int, sz); obj->setSize(sz); } //BIND_END //BIND_DESTRUCTOR MFSet { } //BIND_END //BIND_METHOD MFSet clear { obj->clear(); } //BIND_END //BIND_METHOD MFSet find { LUABIND_CHECK_ARGN(==,1); int v; LUABIND_GET_PARAMETER(1, int, v); LUABIND_RETURN(int, obj->find(v-1)+1); } //BIND_END //BIND_METHOD MFSet merge { LUABIND_CHECK_ARGN(==,2); int v1, v2; LUABIND_GET_PARAMETER(1, int, v1); LUABIND_GET_PARAMETER(2, int, v2); obj->merge(v1-1, v2-1); } //BIND_END //BIND_METHOD MFSet size { LUABIND_RETURN(int, obj->size()); } //BIND_END //BIND_METHOD MFSet clone { LUABIND_RETURN(MFSet, obj->clone()); } //BIND_END //BIND_METHOD MFSet print { obj->print(); } //BIND_END //BIND_METHOD MFSet toString { char *buffer; int size = obj->toString(&buffer); lua_pushlstring(L,buffer,size); delete[] buffer; LUABIND_RETURN_FROM_STACK(-1); } //BIND_END //BIND_METHOD MFSet fromString { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, string); constString cs; LUABIND_GET_PARAMETER(1,constString,cs); obj->fromString(cs); } //BIND_END //BIND_CLASS_METHOD MFSet fromString { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, string); constString cs; LUABIND_GET_PARAMETER(1,constString,cs); MFSet *obj = new MFSet(); obj->fromString(cs); LUABIND_RETURN(MFSet, obj); } //BIND_END ///////////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME stopwatch util.stopwatch //BIND_CPP_CLASS stopwatch //BIND_CONSTRUCTOR stopwatch //DOC_BEGIN // stopwatch() //DOC_END { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(stopwatch, new AprilUtils::stopwatch()); } //BIND_END //BIND_DESTRUCTOR stopwatch { } //BIND_END //BIND_METHOD stopwatch reset //DOC_BEGIN // void resest() /// inicializa el cronometro //DOC_END { LUABIND_CHECK_ARGN(==,0); obj->reset(); } //BIND_END //BIND_METHOD stopwatch stop //DOC_BEGIN // void stop() /// para el cronometro //DOC_END { LUABIND_CHECK_ARGN(==,0); obj->stop(); } //BIND_END //BIND_METHOD stopwatch go //DOC_BEGIN // void go() /// reinicia el cronometro //DOC_END { LUABIND_CHECK_ARGN(==,0); obj->go(); } //BIND_END //BIND_METHOD stopwatch read //DOC_BEGIN // double read() /// lee cronometro //DOC_END { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(double, obj->read_cpu_time()); LUABIND_RETURN(double, obj->read_wall_time()); } //BIND_END //BIND_METHOD stopwatch is_on //DOC_BEGIN // bool is_on() /// devuelve true si esta en marcha, false si esta parado //DOC_END { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(bool, obj->is_on()); } //BIND_END //BIND_METHOD stopwatch clone { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(stopwatch, new AprilUtils::stopwatch(*obj)); } //BIND_END //BIND_METHOD stopwatch to_lua_string { LUABIND_RETURN(string, "util.stopwatch()"); } //BIND_END //BIND_METHOD stopwatch ctor_name { LUABIND_RETURN(string, "util.stopwatch"); } //BIND_END //BIND_METHOD stopwatch ctor_params { } //BIND_END //BIND_FUNCTION util.alarm { double sec; LUABIND_GET_PARAMETER(1, double, sec); struct itimerval new_timer, old_timer; new_timer.it_interval.tv_usec = 0; new_timer.it_interval.tv_sec = 0; new_timer.it_value.tv_usec = static_cast((sec - floor(sec)) * 1.0e6); new_timer.it_value.tv_sec = static_cast(sec); if (setitimer(ITIMER_REAL, &new_timer, &old_timer) != 0) { LUABIND_RETURN_NIL(); LUABIND_RETURN(string, strerror(errno)); } double old_sec = old_timer.it_value.tv_sec + old_timer.it_value.tv_usec*1.0e-6; LUABIND_RETURN(double, old_sec); } //BIND_END // FIXME: nanosleep puede volver antes, en tal caso para avisar a lua // se podría devolver el booleano que devuelve (y que estamos // ignorando) y el tiempo restante :P //BIND_FUNCTION util.sleep { LUABIND_CHECK_ARGN(==,1); double sleeptime; LUABIND_GET_PARAMETER(1, double, sleeptime); double seconds = floor(sleeptime); struct timespec req, rem; req.tv_sec = static_cast(seconds); req.tv_nsec = static_cast((sleeptime-seconds)*1.0e9); double rem_seconds = 0.0; if (nanosleep(&req, &rem) == 1) { LUABIND_RETURN_NIL(); LUABIND_RETURN(string, strerror(errno)); rem_seconds = rem.tv_sec + rem.tv_nsec*1.0e-9; } LUABIND_RETURN(double, rem_seconds); } //BIND_END //BIND_FUNCTION util.linear_least_squares { LUABIND_CHECK_ARGN(==,1); int numPoints; LUABIND_TABLE_GETN(1, numPoints); double *x = new double[numPoints]; double *y = new double[numPoints]; for (int i=1; i <= numPoints; ++i) { lua_rawgeti(L,1,i); // punto i-esimo, es una tabla lua_rawgeti(L,-1,1); // x LUABIND_GET_PARAMETER(-1, double, x[i-1]); lua_pop(L,1); // la quitamos de la pila lua_rawgeti(L,-1,2); // y LUABIND_GET_PARAMETER(-1, double, y[i-1]); lua_pop(L,2); // la quitamos de la pila, tb la tabla } double a,b; // f(x) = a + b*x least_squares(x,y,numPoints,a,b); delete[] x; delete[] y; LUABIND_RETURN(double, a); LUABIND_RETURN(double, b); } //BIND_END //////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME WordsTable util.words_table //BIND_CPP_CLASS WordsTable //BIND_CONSTRUCTOR WordsTable { WordsTable *obj = new WordsTable(); LUABIND_RETURN(WordsTable, obj); } //BIND_END //BIND_METHOD WordsTable filter_words { int size; unsigned int *t; LUABIND_TABLE_GETN(1, size); t = new unsigned int[size+1]; t[0] = 0; LUABIND_TABLE_TO_VECTOR(1, uint, (t+1), size); WordsTable *newobj = new WordsTable(obj, t); delete[] t; LUABIND_RETURN(WordsTable, newobj); } //BIND_END //BIND_METHOD WordsTable insert_words { unsigned int *vec, size; LUABIND_TABLE_GETN(1, size); vec = new unsigned int[size]; LUABIND_TABLE_TO_VECTOR(1, uint, vec, size); obj->insertWords(vec, size); delete[] vec; } //BIND_END //BIND_METHOD WordsTable get_words { unsigned int *vec; unsigned int size, index; LUABIND_GET_PARAMETER(1, uint, index); size = obj->getWords(index, &vec); LUABIND_VECTOR_TO_NEW_TABLE(uint, vec, size); LUABIND_RETURN_FROM_STACK(-1); } //BIND_END //BIND_METHOD WordsTable size { LUABIND_RETURN(uint, obj->size()); } //BIND_END ////////////////////////////////////////////////////////////////////// //BIND_ENUM_CONSTANT signal.SIGHUP SIGHUP //BIND_ENUM_CONSTANT signal.SIGINT SIGINT //BIND_ENUM_CONSTANT signal.SIGQUIT SIGQUIT //BIND_ENUM_CONSTANT signal.SIGILL SIGILL //BIND_ENUM_CONSTANT signal.SIGTRAP SIGTRAP //BIND_ENUM_CONSTANT signal.SIGABRT SIGABRT //BIND_ENUM_CONSTANT signal.SIGFPE SIGFPE //BIND_ENUM_CONSTANT signal.SIGKILL SIGKILL //BIND_ENUM_CONSTANT signal.SIGBUS SIGBUS //BIND_ENUM_CONSTANT signal.SIGSEGV SIGSEGV //BIND_ENUM_CONSTANT signal.SIGSYS SIGSYS //BIND_ENUM_CONSTANT signal.SIGPIPE SIGPIPE //BIND_ENUM_CONSTANT signal.SIGALRM SIGALRM //BIND_ENUM_CONSTANT signal.SIGTERM SIGTERM //BIND_ENUM_CONSTANT signal.SIGURG SIGURG //BIND_ENUM_CONSTANT signal.SIGSTOP SIGSTOP //BIND_ENUM_CONSTANT signal.SIGTSTP SIGTSTP //BIND_ENUM_CONSTANT signal.SIGCONT SIGCONT //BIND_ENUM_CONSTANT signal.SIGCHLD SIGCHLD //BIND_ENUM_CONSTANT signal.SIGTTIN SIGTTIN //BIND_ENUM_CONSTANT signal.SIGTTOU SIGTTOU //BIND_ENUM_CONSTANT signal.SIGIO SIGIO //BIND_ENUM_CONSTANT signal.SIGXCPU SIGXCPU //BIND_ENUM_CONSTANT signal.SIGXFSZ SIGXFSZ //BIND_ENUM_CONSTANT signal.SIGVTALRM SIGVTALRM //BIND_ENUM_CONSTANT signal.SIGPROF SIGPROF //BIND_ENUM_CONSTANT signal.SIGWINCH SIGWINCH //BIND_ENUM_CONSTANT signal.SIGUSR1 SIGUSR1 //BIND_ENUM_CONSTANT signal.SIGUSR2 SIGUSR2 //BIND_FUNCTION signal.register { int sgn; LUABIND_CHECK_ARGN(==,2); LUABIND_CHECK_PARAMETER(1, int); LUABIND_CHECK_PARAMETER(2, function); LUABIND_GET_PARAMETER(1, int, sgn); SignalHandler::register_signal(sgn); } //BIND_END //BIND_FUNCTION signal.release { int sgn; LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, int); LUABIND_GET_PARAMETER(1, int, sgn); SignalHandler::release_signal(sgn); } //BIND_END ////////////////////////////////////////////////////////////////////// //BIND_FUNCTION binarizer.code.int32 { int n; char b[6]; LUABIND_GET_PARAMETER(1, int, n); binarizer::code_int32(n, b); b[5]='\0'; LUABIND_RETURN(string,b); } //BIND_END //BIND_FUNCTION binarizer.code.uint32 { unsigned int n; char b[6]; LUABIND_GET_PARAMETER(1, uint, n); binarizer::code_uint32(n, b); b[5]='\0'; LUABIND_RETURN(string,b); } //BIND_END //BIND_FUNCTION binarizer.decode.int32 { const char *b; LUABIND_GET_PARAMETER(1, string, b); if (strlen(b) != 5) LUABIND_ERROR("A string of len=5 is expected"); int n = binarizer:: decode_int32( reinterpret_cast(b) ); LUABIND_RETURN(int,n); } //BIND_END //BIND_FUNCTION binarizer.decode.uint32 { const char *b; LUABIND_GET_PARAMETER(1, string, b); if (strlen(b) != 5) LUABIND_ERROR("A string of len=5 is expected"); unsigned int n = binarizer:: decode_uint32( reinterpret_cast(b) ); LUABIND_RETURN(uint,n); } //BIND_END ////////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME MMappedDataReader util.mmap.reader //BIND_CPP_CLASS MMappedDataReader //BIND_CONSTRUCTOR MMappedDataReader { const char *path; bool write, shared; LUABIND_CHECK_ARGN(>=,1); LUABIND_CHECK_ARGN(<=,3); LUABIND_GET_PARAMETER(1, string, path); LUABIND_GET_OPTIONAL_PARAMETER(2, bool, write, true); LUABIND_GET_OPTIONAL_PARAMETER(3, bool, shared, true); obj = new MMappedDataReader(path,write,shared); LUABIND_RETURN(MMappedDataReader, obj); } //BIND_END //BIND_LUACLASSNAME MMappedDataWriter util.mmap.writer //BIND_CPP_CLASS MMappedDataWriter //BIND_CONSTRUCTOR MMappedDataWriter { const char *path; LUABIND_CHECK_ARGN(==,1); LUABIND_GET_PARAMETER(1, string, path); obj = new MMappedDataWriter(path); LUABIND_RETURN(MMappedDataWriter, obj); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_FUNCTION math.log1p { double a; LUABIND_GET_PARAMETER(1,double,a); LUABIND_RETURN(double,log1p(a)); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_FUNCTION util.silent_errors { int argn = lua_gettop(L); if (argn > 0) { bool v; LUABIND_GET_PARAMETER(1, bool, v); setSilentErrorsValue(v); } LUABIND_RETURN(bool, getSilentErrorsValue()); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_FUNCTION util.options.test { AprilUtils::SharedPtr clock = new stopwatch(); // stack: nil lua_newtable(L); // stack: table lua_pushstopwatch(L, clock.get()); // stack: table stopwatch lua_setfield(L,-2,"clock1"); // stack: table AprilUtils::LuaTable opt(L,-1); opt.put("clock2", clock.get()); // stopwatch *opt_clock1 = opt.get("clock1"); stopwatch *opt_clock2 = opt.get("clock2"); // stack: table lua_getfield(L,-1,"clock1"); // stack: table stopwatch stopwatch *tbl_clock1 = lua_tostopwatch(L,-1); // stack: table stopwatch lua_pop(L,1); // stack: table lua_getfield(L,-1,"clock2"); if (!lua_isstopwatch(L,-1)) LUABIND_ERROR("TEST 1 FAILED\n"); // stack: table stopwatch stopwatch *tbl_clock2 = lua_tostopwatch(L,-1); if (tbl_clock2 == 0) LUABIND_ERROR("TEST 2 FAILED\n"); // stack: table stopwatch lua_pop(L,1); // stack: table if (opt_clock1 != tbl_clock1) LUABIND_ERROR("TEST 1 FAILED\n"); if (opt_clock2 != tbl_clock2) LUABIND_ERROR("TEST 2 FAILED\n"); // opt.put("str", "Hello world!"); string str(opt.toLuaString()); lua_pushstring(L, str.c_str()); return 2; // returns the table } //BIND_END april-ann-0.4.1/packages/basics/util/c_src/000077500000000000000000000000001263004425400204655ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/util/c_src/aligned_memory.h000066400000000000000000000030611263004425400236310ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef ALIGNED_MEMORY_H #define ALIGNED_MEMORY_H #ifndef NO_MM_MALLOC extern "C" { #include } #define VECTOR_ALIGNMENT 16 namespace AprilUtils { template inline T* aligned_malloc(size_t nmemb) { return (T*)_mm_malloc(sizeof(T)*nmemb,VECTOR_ALIGNMENT); } template inline void aligned_free(T *ptr) { _mm_free(ptr); } } // namespace AprilUtils #else #include namespace AprilUtils { template inline T* aligned_malloc(size_t nmemb) { return (T*)malloc(sizeof(T)*nmemb); } template inline void aligned_free(T *ptr) { free(ptr); } } // namespace AprilUtils #endif #endif // ALIGNED_MEMORY_H april-ann-0.4.1/packages/basics/util/c_src/april_assert.h000066400000000000000000000022611263004425400233270ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include "error_print.h" #ifdef NDEBUG #define april_assert(cond) #else #define april_assert(cond) do { \ if (!(cond)) { \ ERROR_EXIT1(128, "Assertion failed: (%s)\n", #cond); \ } \ } while(0) #endif april-ann-0.4.1/packages/basics/util/c_src/april_endian.h000066400000000000000000000031221263004425400232610ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef APRIL_ENDIAN_H #define APRIL_ENDIAN_H // Endianness checks // TODO: these ones are possibly unsafe, we should execute // a test before compiling and define endianness accordingly. // (like configure does in a typical build-system) #define APRIL_BIG_ENDIAN 0xdeadbeef #define APRIL_LITTLE_ENDIAN 0xefbeadde #ifndef APRIL_ENDIANNESS #if defined(__POWERPC__)|| defined(__ppc__) || defined(_M_PPC) || \ defined(_M_M68K) || defined(__m68k__) || defined(mc68000) || \ (defined(__MIPS__) && defined(__MISPEB__)) || \ defined(__hppa__) || \ defined(__sparc__) #define APRIL_ENDIANNESS APRIL_BIG_ENDIAN #else #define APRIL_ENDIANNESS APRIL_LITTLE_ENDIAN #endif #endif // !defined(APRIL_ENDIANNESS) #endif // !defined(APRIL_ENDIAN_H) april-ann-0.4.1/packages/basics/util/c_src/april_print.cc000066400000000000000000000024061263004425400233210ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include "april_print.h" namespace AprilUtils { void aprilPrint(const float &v) { printf("%f", v); } void aprilPrint(const double &v) { printf("%f", v); } void aprilPrint(const char &v) { printf("%c", v); } void aprilPrint(const int &v) { printf("%d", v); } void aprilPrint(const unsigned int &v) { printf("%u", v); } void aprilPrint(const bool &v) { printf("%s", (v) ? ("true") : ("false")); } } april-ann-0.4.1/packages/basics/util/c_src/april_print.h000066400000000000000000000024721263004425400231660ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef APRIL_PRINT_H #define APRIL_PRINT_H #include namespace AprilUtils { void aprilPrint(const float &v); void aprilPrint(const double &v); void aprilPrint(const char &v); void aprilPrint(const int &v); void aprilPrint(const unsigned int &v); void aprilPrint(const bool &v); template void aprilPrint(const char *str1, const T &v, const char *str2) { if (str1 != 0) printf("%s",str1); aprilPrint(v); if (str2 != 0) printf("%s",str2); } } #endif // APRIL_PRINT_H april-ann-0.4.1/packages/basics/util/c_src/aux_hash_table.h000066400000000000000000000174361263004425400236200ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef AUX_HASH_TABLE_H #define AUX_HASH_TABLE_H extern "C" { #include } #include // strcmp #include "april_assert.h" #include "error_print.h" #include "constString.h" #include "mystring.h" #include "pair.h" namespace AprilUtils { //---------------------------------------------------------------------- template struct default_hash_function { static const uint32_t cte_hash = 2654435769U; // hash Fibonacci uint64_t operator()(const T& key) const { uint32_t resul = 1; unsigned int length = sizeof(T); const unsigned char *r = reinterpret_cast(&key); for (unsigned int i=0; i struct default_equality_comparison_function { bool operator()(const T& i1, const T& i2) const { return i1 == i2; } }; //---------------------------------------------------------------------- // Hash function for ints (operator == is OK) // template<> struct default_hash_function { static const uint32_t cte_hash = 2654435769U; // hash Fibonacci uint64_t operator()(const int &i) const { return cte_hash*i; } }; //---------------------------------------------------------------------- // Hash function for unsigned ints (operator == is OK) // template<> struct default_hash_function { static const uint32_t cte_hash = 2654435769U; // hash Fibonacci uint64_t operator()(const unsigned int &i) const { return cte_hash*i; } }; //---------------------------------------------------------------------- // Hash function for pair (operator == is OK) // typedef AprilUtils::pair int_pair; template<> struct default_hash_function { static const uint32_t cte_hash = 2654435769U; // hash Fibonacci uint64_t operator()(const int_pair &i) const { return ((cte_hash*i.first) + i.second) * cte_hash; } }; //---------------------------------------------------------------------- // Hash function for pair (operator == is OK) // typedef AprilUtils::pair uint_pair; template<> struct default_hash_function { static const uint32_t cte_hash = 2654435769U; // hash Fibonacci uint64_t operator()(const uint_pair &i) const { return ((cte_hash*i.first) + i.second) * cte_hash; } }; //---------------------------------------------------------------------- // Hash function for pair (operator == is OK) // typedef AprilUtils::pair int16_pair; template<> struct default_hash_function { static const uint32_t cte_hash = 2654435769U; // hash Fibonacci uint64_t operator()(const int16_pair &i) const { return ((cte_hash*i.first) + i.second) * cte_hash; } }; //---------------------------------------------------------------------- // Hash function for constString (operator == is OK) // template <> struct default_hash_function { static const uint32_t cte_hash = 2654435769U; // hash Fibonacci uint64_t operator()(const constString &cs) const { uint32_t resul = 1; const char *r = (const char*)cs; // we are using operator const char *() for (int l=cs.len(); l>0; l--,r++) resul = (resul+(unsigned int)(*r))*cte_hash; return resul; } }; //---------------------------------------------------------------------- // Hash function for string (operator == is OK) // // For hash tables template <> struct default_hash_function { static const uint32_t cte_hash = 2654435769U; // hash Fibonacci uint64_t operator()(const string &s1) const { uint32_t resul = 1; for (const char *r = s1.begin(); r != s1.end(); r++) resul = (resul+(unsigned int)(*r))*cte_hash; return resul; } }; //---------------------------------------------------------------------- // Hash function for generic pointers (operator == is OK) // template struct default_hash_function { static const uint32_t cte_hash = 2654435769U; // hash Fibonacci uint64_t operator()(T* p) const { // arquitectura 32 bits if (sizeof(void*) == 4) { union { uint32_t i; void *p; } avoid_strict_aliasing; avoid_strict_aliasing.p = p; return avoid_strict_aliasing.i * cte_hash; } // arquitectura 64 bits else if (sizeof(void*) == 8) { union { uint32_t i[2]; /* usamos 2 punteros de 32 para poder hacer hashing del puntero de 64 */ void *p; } avoid_strict_aliasing; avoid_strict_aliasing.p = p; return ((avoid_strict_aliasing.i[0] * cte_hash + avoid_strict_aliasing.i[1]) * cte_hash); } else { ERROR_PRINT("parsers_pool_hash_function(): sizeof(void*) tiene un tamaño desconocido.\n"); } return 0; } }; //---------------------------------------------------------------------- // c-style strings (const char *) need also a comparison function // template <> struct default_equality_comparison_function { bool operator()(const char* s1, const char* s2) const { return strcmp(s1, s2) == 0; } }; template <> struct default_hash_function { static const uint32_t cte_hash = 2654435769U; // hash Fibonacci uint64_t operator()(const char* s1) const { uint32_t resul = 1; for (const char *r = s1; *r != '\0'; r++) resul = (resul+(unsigned int)(*r))*cte_hash; return resul; } }; //---------------------------------------------------------------------- // c-style strings (const char *) need also a comparison function // template <> struct default_equality_comparison_function { bool operator()(const char* s1, const char* s2) const { return strcmp(s1, s2) == 0; } }; template <> struct default_hash_function { static const uint32_t cte_hash = 2654435769U; // hash Fibonacci uint64_t operator()(const char* s1) const { uint32_t resul = 1; for (const char *r = s1; *r != '\0'; r++) resul = (resul+(unsigned int)(*r))*cte_hash; return resul; } }; //---------------------------------------------------------------------- // template para hash de "cosas" que tengan el metodo size, // elementos que son tipos básicos y acceso a ellos via operator[] template struct hash_restricted_vector { static const uint32_t cte_hash = 2654435769U; // hash Fibonacci uint64_t operator()(const T& key) const { uint32_t resul = 1; unsigned int objsize = key.size(); for (unsigned int i=0; i #include #include #include #include "binarizer.h" // glibc defines these ones in string.h // they're gone in C99, but stay in C++ :_( #undef BIG_ENDIAN #undef LITTLE_ENDIAN namespace AprilUtils { // from BASE5 on we need to use long constants to avoid overflow static const uint32_t BASE = 85; static const uint32_t BASE1 = 85; static const uint32_t BASE2 = 85*85; static const uint32_t BASE3 = 85*85*85; static const uint32_t BASE4 = 85*85*85*85; static const uint64_t BASE5 = uint64_t(85)*85*85*85*85; static const uint64_t BASE6 = uint64_t(85)*85*85*85*85*85; static const uint64_t BASE7 = uint64_t(85)*85*85*85*85*85*85; static const uint64_t BASE8 = uint64_t(85)*85*85*85*85*85*85*85; static const uint64_t BASE9 = uint64_t(85)*85*85*85*85*85*85*85*85; binarizer::endian_enum binarizer::endianness; // vector de talla BASE=85, da el codigo ascii no extendido asociado a // cada uno de los 85 valores diferentes: char binarizer::cod[] = {'\041','\044','\045','\046','\047','\050','\051','\052','\053','\054', '\056','\057','\060','\061','\062','\063','\064','\065','\066','\067', '\070','\071','\072','\073','\074','\075','\076','\077','\100','\101', '\102','\103','\104','\105','\106','\107','\110','\111','\112','\113', '\114','\115','\116','\117','\120','\121','\122','\123','\124','\125', '\126','\127','\130','\131','\132','\136','\137','\140','\141','\142', '\143','\144','\145','\146','\147','\150','\151','\152','\153','\154', '\155','\156','\157','\160','\161','\162','\163','\164','\165','\166', '\167','\170','\171','\172','\173',}; // vector de talla 256, dado un valor ascii devuelve el digito en base 85 asociado: char binarizer::uncod[] = {'\000','\000','\000','\000','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000','\001','\002','\003','\004', '\005','\006','\007','\010','\011','\000','\012','\013','\014','\015', '\016','\017','\020','\021','\022','\023','\024','\025','\026','\027', '\030','\031','\032','\033','\034','\035','\036','\037','\040','\041', '\042','\043','\044','\045','\046','\047','\050','\051','\052','\053', '\054','\055','\056','\057','\060','\061','\062','\063','\064','\065', '\066','\000','\000','\000','\067','\070','\071','\072','\073','\074', '\075','\076','\077','\100','\101','\102','\103','\104','\105','\106', '\107','\110','\111','\112','\113','\114','\115','\116','\117','\120', '\121','\122','\123','\124','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000','\000','\000','\000','\000', '\000','\000','\000','\000','\000','\000',}; // initialization, sanity checks, etc void binarizer::init() { double d = 1234.5678; // 40 93 4a 45 6d 5c fa ad unsigned char c[8]; unsigned char big[8] = {0x40,0x93,0x4a,0x45,0x6d,0x5c,0xfa,0xad}; unsigned char little[8] = {0xad,0xfa,0x5c,0x6d,0x45,0x4a,0x93,0x40}; memcpy(c, &d, sizeof(double)); // Check for big endian endianness = BIG_ENDIAN; for (int i=0; i<8; i++) { if (c[i] != big[i]) { endianness = UNKNOWN_ENDIAN; break; } } if (endianness == UNKNOWN_ENDIAN) { // Check for little endian endianness = LITTLE_ENDIAN; for (int i=0; i<8; i++) { if (c[i] != little[i]) { endianness = UNKNOWN_ENDIAN; break; } } } if (endianness == UNKNOWN_ENDIAN) { fprintf(stderr, "FATAL ERROR: Unknown endianness or unknown (no IEEE 754) floating-point format\n"); exit(EXIT_FAILURE); } } // ------------------- 16 bits ------------------- #ifdef HAVE_UINT16 uint16_t binarizer::decode_uint16(const char b[3]) { return uncod[(int)b[0]] * BASE2 + uncod[(int)b[1]] * BASE1 + uncod[(int)b[2]]; } void binarizer::code_uint16(uint16_t a0, char b[3]) { uint16_t a1,a2; a1 = a0/BASE; a2 = a0/BASE2; b[0] = cod[a2]; b[1] = cod[a1-a2*BASE]; b[2] = cod[a0-a1*BASE]; } // signed case is reduced to unsigned case. Two complement // representation is assumed int16_t binarizer::decode_int16(const char b[3]) { uint16_t ui; int16_t i; ui = decode_uint16(b); memcpy(&i, &ui, sizeof(uint16_t)); return i; } void binarizer::code_int16(int16_t a0, char b[3]) { uint16_t ui; memcpy(&ui, &a0, sizeof(uint16_t)); code_uint16(ui,b); } #endif // ------------------- 32 bits ------------------- uint32_t binarizer::decode_uint32(const char c[5]) { return uncod[(int)c[0]] * BASE4 + uncod[(int)c[1]] * BASE3 + uncod[(int)c[2]] * BASE2 + uncod[(int)c[3]] * BASE1 + uncod[(int)c[4]]; } void binarizer::code_uint32(uint32_t a0, char b[5]) { uint32_t a1,a2,a3,a4; a1 = a0/BASE1; a2 = a0/BASE2; a3 = a0/BASE3; a4 = a0/BASE4; b[0] = cod[a4]; b[1] = cod[a3-a4*BASE]; b[2] = cod[a2-a3*BASE]; b[3] = cod[a1-a2*BASE]; b[4] = cod[a0-a1*BASE]; } // signed case is reduced to unsigned case. Two complement // representation is assumed int32_t binarizer::decode_int32(const char b[5]) { uint32_t ui; int32_t i; ui = decode_uint32(b); memcpy(&i, &ui, sizeof(uint32_t)); return i; } void binarizer::code_int32(int32_t a0, char b[5]) { uint32_t ui; memcpy(&ui, &a0, sizeof(uint32_t)); code_uint32(ui,b); } // ------------------- 64 bits ------------------- #ifdef HAVE_UINT64 uint64_t binarizer::decode_uint64(const char c[10]) { return uncod[(int)c[0]] * BASE9 + uncod[(int)c[1]] * BASE8 + uncod[(int)c[2]] * BASE7 + uncod[(int)c[3]] * BASE6 + uncod[(int)c[4]] * BASE5 + uncod[(int)c[5]] * BASE4 + uncod[(int)c[6]] * BASE3 + uncod[(int)c[7]] * BASE2 + uncod[(int)c[8]] * BASE1 + uncod[(int)c[9]]; } void binarizer::code_uint64(uint64_t a0, char b[10]) { uint64_t a1,a2,a3,a4,a5,a6,a7,a8,a9; a1 = a0/BASE1; a2 = a0/BASE2; a3 = a0/BASE3; a4 = a0/BASE4; a5 = a0/BASE5; a6 = a0/BASE6; a7 = a0/BASE7; a8 = a0/BASE8; a9 = a0/BASE9; b[0] = cod[a9]; b[1] = cod[a8-a9*BASE]; b[2] = cod[a7-a8*BASE]; b[3] = cod[a6-a7*BASE]; b[4] = cod[a5-a6*BASE]; b[5] = cod[a4-a5*BASE]; b[6] = cod[a3-a4*BASE]; b[7] = cod[a2-a3*BASE]; b[8] = cod[a1-a2*BASE]; b[9] = cod[a0-a1*BASE]; } // signed case is reduced to unsigned case. Two complement // representation is assumed int64_t binarizer::decode_int64(const char b[10]) { int64_t i; uint64_t ui; ui = decode_uint64(b); memcpy(&i, &ui, sizeof(uint64_t)); return i; } void binarizer::code_int64(int64_t a0, char b[10]) { uint64_t ui; memcpy(&ui, &a0, sizeof(uint64_t)); code_uint64(ui,b); } #endif // ------------------- FLOATING POING ------------------- void binarizer::code_float (float i, char b[5]) { // asumimos float en representación IEEE 754, lo pasamos bit a bit a // uint32 uint32_t ui; memcpy(&ui, &i, sizeof(float)); code_uint32(ui,b); } void binarizer::code_double(double i, char b[10]) { // asumimos double en representación IEEE 754, lo pasamos bit a bit // a uint64 uint32_t words[2]; uint32_t msw, lsw; memcpy(words, &i, sizeof(double)); if (endianness == BIG_ENDIAN) { msw = words[0]; lsw = words[1]; } else { msw = words[1]; lsw = words[0]; } code_uint32(msw, b); code_uint32(lsw, b+5); } float binarizer::decode_float(const char b[5]) { // asumimos float en representación IEEE 754, lo pasamos bit a bit a // uint32 float f; uint32_t ui; ui = decode_uint32(b); memcpy(&f, &ui, sizeof(uint32_t)); return f; } double binarizer::decode_double(const char b[10]) { // asumimos double en representación IEEE 754, lo pasamos bit a bit // a uint64 uint32_t msw, lsw; uint32_t words[2]; double result; msw = decode_uint32(b); lsw = decode_uint32(b+5); if (endianness == BIG_ENDIAN) { words[0] = msw; words[1] = lsw; } else { words[0] = lsw; words[1] = msw; } memcpy(&result, words, sizeof(double)); return result; } // ------------------- AUXILIAR ------------------- int binarizer::buffer_size_16(int num, bool with_newlines) { int estimation = num*3+1; // +1 due to final '\0' if (with_newlines) // \n every 26 numbers to get 78char linewith estimation += num/26+1; return estimation; } int binarizer::buffer_size_32(int num, bool with_newlines) { int estimation = num*5+1; // +1 due to final '\0' if (with_newlines) // \n every 26 numbers to get 80char linewith estimation += num/16+1; return estimation; } int binarizer::buffer_size_64(int num, bool with_newlines) { int estimation = num*10+1; // +1 due to final '\0' if (with_newlines) // \n every 26 numbers to get 80char linewith estimation += num/8+1; return estimation; } // ------------------- AUXILIAR ------------------- int binarizer::code_vector_float(const float *vect, int vect_size, char *dest_buffer, int dest_buffer_size, bool with_newlines) { return code_iterator_float(vect, vect+vect_size, vect_size, dest_buffer, dest_buffer_size, with_newlines); } int binarizer::code_vector_int32(const int32_t *vect, int vect_size, char *dest_buffer, int dest_buffer_size, bool with_newlines) { int i; char *rb = dest_buffer; if (buffer_size_32(vect_size,with_newlines) <= dest_buffer_size) { i = 0; while (i unsigned int binarizer::binary_size() { return 5u; } template<> unsigned int binarizer::binary_size() { return 10u; } template<> unsigned int binarizer::binary_size() { return 5u; } template<> unsigned int binarizer::binary_size() { return 1u; } template<> unsigned int binarizer::binary_size() { return 1u; } template<> void binarizer::code(const float &value, char *b) { binarizer::code_float(value, b); } template<> void binarizer::code(const double &value, char *b) { binarizer::code_double(value, b); } template<> void binarizer::code(const int32_t &value, char *b) { binarizer::code_int32(value, b); } template<> void binarizer::code(const char &value, char *b) { *b = value; } template<> void binarizer::code(const bool &value, char *b) { *b = value ? '1' : '0'; } template<> float binarizer::decode(const char *b) { return binarizer::decode_float(b); } template<> double binarizer::decode(const char *b) { return binarizer::decode_double(b); } template<> int32_t binarizer::decode(const char *b) { return binarizer::decode_int32(b); } template<> char binarizer::decode(const char *b) { return *b; } template<> bool binarizer::decode(const char *b) { return ( (*b) == '1' ) ? true : false; } } // namespace AprilUtils april-ann-0.4.1/packages/basics/util/c_src/binarizer.h000066400000000000000000000126061263004425400226300ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef BINARIZER_H #define BINARIZER_H extern "C" { #include } #include "error_print.h" #include "unused_variable.h" namespace AprilUtils { // glibc defines these ones in string.h // they're gone in C99, but stay in C++ :_( #undef BIG_ENDIAN #undef LITTLE_ENDIAN // clase con métodos estáticos: class binarizer { static char cod[]; // tablas static char uncod[]; static enum endian_enum {BIG_ENDIAN, LITTLE_ENDIAN, UNKNOWN_ENDIAN} endianness; public: static void init(); template static unsigned int binary_size() { ERROR_EXIT(128, "Not implemented\n"); return 0; } template static void code(const T &value, char *b) { UNUSED_VARIABLE(value); UNUSED_VARIABLE(b); ERROR_EXIT(128, "Not implemented\n"); } template static T decode(const char *b) { UNUSED_VARIABLE(b); ERROR_EXIT(128, "Not implemented\n"); return T(0.0f); } static void code_uint32(uint32_t i, char b[5]); static void code_int32 ( int32_t i, char b[5]); static uint32_t decode_uint32(const char b[5]); static int32_t decode_int32 (const char b[5]); static void code_float ( float i, char b[5]); static void code_double(double i, char b[10]); static float decode_float (const char b[5]); static double decode_double(const char b[10]); #ifdef HAVE_UINT16 static void code_uint16(uint16_t i, char b[3]); static void code_int16 ( int16_t i, char b[3]); static uint16_t decode_uint16(const char b[3]); static int16_t decode_int16 (const char b[3]); #endif #ifdef HAVE_UINT64 static void code_uint64(uint64_t i, char b[10]); static void code_int64 ( int64_t i, char b[10]); static uint64_t decode_uint64(const char b[10]); static int64_t decode_int64 (const char b[10]); #endif // estima (por exceso) la longitud en bytes al escribir n numeros de // XXX bits con la opción de poner '\n' cada 80 caracteres aprox: static int buffer_size_16(int num, bool with_newlines=true); static int buffer_size_32(int num, bool with_newlines=true); static int buffer_size_64(int num, bool with_newlines=true); // El objetivo es codificar el vector y dejar el resultado en el // buffer. Devuelve el numero de caracteres utilizados en el // buffer. Si el buffer no es lo bastante grande para guardar todo // el contenido, no hace nada y devuelve 0 caracteres utilizados. static int code_vector_float(const float *vect, int vect_size, char *dest_buffer, int dest_buffer_size, bool with_newlines=true); template static int code_iterator_float(ITERATOR it, ITERATOR end, int vect_size, char *dest_buffer, int dest_buffer_size, bool with_newlines=true) { int i; char *rb = dest_buffer; if (buffer_size_32(vect_size,with_newlines) <= dest_buffer_size) { i = 0; while (it != end) { code_float(*it,rb); rb+=5; i++; ++it; if (with_newlines && !(i%16)) { *rb = '\n'; rb++; } } if (with_newlines && (i % 16)) { *rb = '\n'; rb++; } *rb = '\0'; rb++; } return rb-dest_buffer; } static int code_vector_int32(const int32_t *vect, int vect_size, char *dest_buffer, int dest_buffer_size, bool with_newlines=true); }; template<> unsigned int binarizer::binary_size(); template<> unsigned int binarizer::binary_size(); template<> unsigned int binarizer::binary_size(); template<> unsigned int binarizer::binary_size(); template<> unsigned int binarizer::binary_size(); template<> void binarizer::code(const float &value, char *b); template<> void binarizer::code(const double &value, char *b); template<> void binarizer::code(const int32_t &value, char *b); template<> void binarizer::code(const char &value, char *b); template<> void binarizer::code(const bool &value, char *b); template<> float binarizer::decode(const char *b); template<> double binarizer::decode(const char *b); template<> int32_t binarizer::decode(const char *b); template<> char binarizer::decode(const char *b); template<> bool binarizer::decode(const char *b); } // namespace AprilUtils #endif // BINARIZER_H april-ann-0.4.1/packages/basics/util/c_src/binary_search.h000066400000000000000000000036001263004425400234460ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef BINARY_SEARCH_H #define BINARY_SEARCH_H /* Template del algoritmo de busqueda dicotomica REQUIERE QUE EL TIPO T TENGA DEFINIDA LAS OPERACIONES "<" y "==" con el tipo K */ namespace AprilUtils { template inline int binary_search(const T *vec, int sz, const K&value) { int izq = 0, der = sz-1; while (izq <= der) { int m = (izq+der)>>1; if (vec[m]==value) return m; if (vec[m] < value) izq = m+1; else der = m-1; } return -1; } // REQUIERE QUE EL TIPO T TENGA DEFINIDA LAS OPERACIONES "<" con el tipo K template inline const T * binary_search_first(const T *vec, int sz, const K&value) { int izq = 0, der = sz-2; // OJO: -2, necesita que el vector tenga // un centinela en la posicion sz-1 while (izq <= der) { int m = (izq+der)>>1; if (!(vec[m] #include "april_assert.h" #include #include #include "binarizer.h" namespace AprilUtils { buffer_list_node::buffer_list_node(int sz, buffer_list_node *nxt) { size = sz; buffer = new char[size+1]; next = nxt; } buffer_list_node::~buffer_list_node() { if (buffer) delete[] buffer; } buffer_list::~buffer_list() { while (first) { buffer_list_node *aux = first; first = first->next; delete aux; } } void buffer_list::append(buffer_list *other) { size += other->size; if (last) { last->next = other->first; } else { // lista izquierda está vacía first = other->first; } last = other->last; // Los nodos de other pasan a ser de this. // Por tanto, other esta vacio other->first = 0; other->last = 0; other->size = 0; } void buffer_list::add_buffer_left(buffer_list_node *nd) { size += nd->size; nd->next = first; first = nd; if (!last) last=first; } void buffer_list::add_buffer_right(buffer_list_node *nd) { size += nd->size; nd->next = 0; if (last) { last->next = nd; } else { first = nd; } last = nd; } #define FORMAT_BUFFER_SIZE 200 void buffer_list::add_formatted_string_left(const char *fmt, ...) { int n; char buf[FORMAT_BUFFER_SIZE]; buffer_list_node *node; va_list ap; va_start(ap, fmt); n = vsnprintf (buf, FORMAT_BUFFER_SIZE, fmt, ap); va_end(ap); april_assert(n>=0); // n doesn't include the terminating '\0' node = new buffer_list_node(n+1,0); if (n < FORMAT_BUFFER_SIZE) { strcpy(node->buffer, buf); } else { va_start(ap, fmt); n = vsnprintf (node->buffer, n+1, fmt, ap); va_end(ap); } add_buffer_left(node); } void buffer_list::add_formatted_string_right(const char *fmt, ...) { int n; char buf[FORMAT_BUFFER_SIZE]; buffer_list_node *node; va_list ap; va_start(ap, fmt); n = vsnprintf (buf, FORMAT_BUFFER_SIZE, fmt, ap); va_end(ap); april_assert(n>=0); // n doesn't include the terminating '\0' // but we don't want a null-terminated string anyway node = new buffer_list_node(n,0); if (n < FORMAT_BUFFER_SIZE) { memcpy(node->buffer, buf, n); } else { va_start(ap, fmt); n = vsnprintf (node->buffer, n+1, fmt, ap); va_end(ap); } add_buffer_right(node); } void buffer_list::printf(const char *fmt, ...) { int n; char buf[FORMAT_BUFFER_SIZE]; buffer_list_node *node; va_list ap; va_start(ap, fmt); n = vsnprintf (buf, FORMAT_BUFFER_SIZE, fmt, ap); va_end(ap); april_assert(n>=0); // n doesn't include the terminating '\0' // but we don't want a null-terminated string anyway node = new buffer_list_node(n,0); if (n < FORMAT_BUFFER_SIZE) { memcpy(node->buffer, buf, n); } else { va_start(ap, fmt); n = vsnprintf (node->buffer, n+1, fmt, ap); va_end(ap); } add_buffer_right(node); } void buffer_list::add_constString_left (const constString &cs) { buffer_list_node *node = new buffer_list_node(cs.len()); memcpy(node->buffer, (const char *)cs, cs.len()); add_buffer_left(node); } void buffer_list::add_constString_right (const constString &cs) { buffer_list_node *node = new buffer_list_node(cs.len()); memcpy(node->buffer, (const char *)cs, cs.len()); add_buffer_right(node); } char *buffer_list::to_string(string_termination t) { int s = size; if (t == NULL_TERMINATED) { s++; } char *res = new char[s]; char *pos = res; buffer_list_node *cur; for (cur = first; cur != NULL; cur = cur->next) { memcpy(pos, cur->buffer, cur->size); pos += cur->size; } if (t==NULL_TERMINATED) { *pos = '\0'; } return res; } #ifdef HAVE_UINT16 void buffer_list::add_binarized_int16_left (const int16_t *v, int v_sz) { buffer_list_node *node = new buffer_list_node(v_sz*3); char *r = node->buffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; ibuffer; for (int i=0; i } #include "logbase.h" #include "constString.h" namespace AprilUtils { struct buffer_list_node { char *buffer; int size; buffer_list_node *next; buffer_list_node() : buffer(0), size(0), next(0) {} buffer_list_node(int sz, buffer_list_node *nxt=0); ~buffer_list_node(); }; struct buffer_list { enum string_termination { NON_NULL_TERMINATED, NULL_TERMINATED }; buffer_list_node *first; buffer_list_node *last; int size; // buffer_list() : first(0), last(0), size(0) {}; ~buffer_list(); void append(buffer_list *other); int get_size() const { return size; } void add_buffer_left(buffer_list_node *nd); void add_buffer_right(buffer_list_node *nd); void add_constString_left (const constString &cs); void add_constString_right(const constString &cs); void add_formatted_string_left (const char *fmt, ...); void add_formatted_string_right(const char *fmt, ...); /// es una copia de add_formatted_string_right TODO: se puede hacer /// que sea un alias en lugar de una copia? void printf(const char *fmt, ...); #ifdef HAVE_UINT16 void add_binarized_int16_left (const int16_t *v, int v_sz); void add_binarized_int16_right(const int16_t *v, int v_sz); void add_binarized_uint16_left (const uint16_t *v, int v_sz); void add_binarized_uint16_right(const uint16_t *v, int v_sz); #endif void add_binarized_int32_left (const int32_t *v, int v_sz); void add_binarized_int32_right(const int32_t *v, int v_sz); void add_binarized_uint32_left (const uint32_t *v, int v_sz); void add_binarized_uint32_right(const uint32_t *v, int v_sz); #ifdef HAVE_UINT64 void add_binarized_int64_left (const int64_t *v, int v_sz); void add_binarized_int64_right(const int64_t *v, int v_sz); void add_binarized_uint64_left (const uint64_t *v, int v_sz); void add_binarized_uint64_right(const uint64_t *v, int v_sz); #endif void add_binarized_float_left (const float *v, int v_sz); void add_binarized_float_right(const float *v, int v_sz); void add_binarized_log_float_left (const log_float *v, int v_sz); void add_binarized_log_float_right(const log_float *v, int v_sz); void add_binarized_double_left (const double *v, int v_sz); void add_binarized_double_right(const double *v, int v_sz); void add_binarized_log_double_left (const log_double *v, int v_sz); void add_binarized_log_double_right(const log_double *v, int v_sz); char* to_string(string_termination t = NON_NULL_TERMINATED); }; } // namespace AprilUtils #endif // BUFFER_LIST_H april-ann-0.4.1/packages/basics/util/c_src/cache_open_addressing_hash.h000066400000000000000000000277401263004425400261420ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef CACHE_OPEN_ADDR_HASH_H #define CACHE_OPEN_ADDR_HASH_H /* Cache con tabla hash de direccionamiento abierto (CON TIMESTAMP) Se utiliza un vector para guardar directamente los valores. Cuando se busca un valor, se utiliza la función de dispersión para obtener el indice en el vector. Cuando una posicion es ocupada, la clave y el valor viejos se sobreescriben con los nuevos. Los tipos de datos para los campos clave y valor asumen que el operador de copia funciona suficientemente bien como para que al "machacar" una posición del vector con un valor nuevo, el valor anterior se libere convenientemente. También se asume que ambos tipos de datos tienen constructores por defecto. Un valor estará siempre en la misma posición ya que no hay rehashing. */ #include "aux_hash_table.h" #include // ceilf #include // ptrdiff_t, size_t... #include "pair.h" namespace AprilUtils { // HashFcn es del tipo: // struct hash_fcn { // unsigned int operator()(const char* s1) const { // return blah...; // } // }; // EqualKey es del tipo: // struct eqstr { // bool operator()(const char* s1, const char* s2) const { // return strcmp(s1, s2) == 0; // } // }; template , typename EqualKey = default_equality_comparison_function > class cache_open_addr_hash { public: struct node { pair value; unsigned int stamp; node() {} node(KeyType& k, DataType& d): value(k,d) {} }; typedef KeyType key_type; typedef DataType data_type; typedef pair value_type; typedef value_type& reference; typedef const reference const_reference; typedef value_type* pointer; typedef ptrdiff_t difference_type; typedef size_t size_type; private: static const unsigned int maxstamp = 1<<30; unsigned int timestamp; node *buckets; // vector of nodes int used_size; int num_buckets;// a power of 2 int hash_mask; // useful to do "& hash_mask" instead of "% // num_buckets" int first_power_of_2(int value);// auxiliary function HashFcn hash_function; EqualKey equal_key; public: cache_open_addr_hash(int nbckts=18); // constructor cache_open_addr_hash(const cache_open_addr_hash&); // copy constructor ~cache_open_addr_hash(); // destructor // assignment operator cache_open_addr_hash& operator=(const cache_open_addr_hash&); void clear(); // Erases all of the elements. data_type* find(const key_type& k); const value_type* find_pair(const key_type& k) const; bool search(const key_type& k) const { return find_pair(k) != 0; } data_type& operator[] (const key_type& k); void insert(const key_type& k, data_type& d) { (*this)[k] = d; } int bucket_count() const { // Returns the number of buckets used by the hash return used_size; } bool get(const key_type& k, data_type** d); class const_iterator; class iterator { friend class const_iterator; friend class cache_open_addr_hash; cache_open_addr_hash *h; int index; iterator(cache_open_addr_hash *h, int index): h(h), index(index) {} public: typedef KeyType key_type; typedef DataType data_type; typedef pair value_type; typedef value_type& reference; typedef const reference const_reference; typedef value_type* pointer; typedef ptrdiff_t difference_type; typedef size_t size_type; iterator(): h(0), index(0) {} iterator(const iterator &other): h(other.h), index(other.index) {} iterator& operator=(const iterator &other) { if (&other != this) { h = other.h; index = other.index; } return (*this); } iterator& operator++() { // preincrement // asumimos que no se incrementa un iterador con // index>=num_buckets do { index++; } while (indexnum_buckets && h->buckets[index].stamp != h->timestamp); return *this; } iterator operator++(int) { // postincrement iterator tmp(*this); ++(*this); return tmp; } value_type& operator *() { //dereference return h->buckets[index].value; } value_type* operator ->() { return &(h->buckets[index].value); } bool operator == (const iterator &other) { return ((index == other.index) && (h == other.h)); } bool operator != (const iterator &other) { return ((index != other.index) || (h != other.h)); } }; class const_iterator { friend class cache_open_addr_hash; const cache_open_addr_hash *h; int index; const_iterator(cache_open_addr_hash *h, int index): h(h), index(index) {} public: typedef KeyType key_type; typedef DataType data_type; typedef pair value_type; typedef value_type& reference; typedef const reference const_reference; typedef value_type* pointer; typedef ptrdiff_t difference_type; typedef size_t size_type; const_iterator(): h(0), index(0) {} // Copy constructor (from iterator and const_iterator) const_iterator(const iterator &other): h(other.h), index(other.index) {} const_iterator(const const_iterator &other): h(other.h), index(other.index) {} // Assignment operators const_iterator& operator=(const iterator &other) { h = other.h; index = other.index; } const_iterator& operator=(const const_iterator &other) { h = other.h; index = other.index; } const_iterator& operator++() { // preincrement // asumimos que no se incrementa un iterador con // index>=num_buckets do { index++; } while (indexnum_buckets && h->buckets[index].stamp != h->timestamp); return *this; } const_iterator operator++(int) { // postincrement const_iterator tmp(*this); ++(*this); return tmp; } const value_type& operator *() { //dereference return h->buckets[index].value; } const value_type* operator ->() { return &(h->buckets[index].value); } // Eq comparisons bool operator == (const iterator &other) { return ((index == other.index) && (h == other.h)); } bool operator == (const const_iterator &other) { return ((index == other.index) && (h == other.h)); } bool operator != (const iterator &other) { return ((index != other.index) || (h != other.h)); } bool operator != (const const_iterator &other) { return ((index != other.index) || (h != other.h)); } }; iterator begin() { int i=0; while (i int cache_open_addr_hash::first_power_of_2(int value) { int result = 4; // ojito, minimo 4. TODO: se queda este valor? while (result < value) result += result; return result; } template cache_open_addr_hash::cache_open_addr_hash(int nbckts) { num_buckets = first_power_of_2(nbckts); hash_mask = num_buckets-1; // num_buckets is a power of 2 end_iterator = iterator(this, num_buckets); buckets = new node[num_buckets]; timestamp = maxstamp - 1; // se encarga de inicializar el stamp clear(); } template cache_open_addr_hash::cache_open_addr_hash(const cache_open_addr_hash& other) { // copy constructor used_size = other.used_size; num_buckets = other.num_buckets; hash_mask = other.hash_mask; buckets = new node[num_buckets]; for (int i=0; i void cache_open_addr_hash::clear() { used_size = 0; ++timestamp; if (timestamp == maxstamp) { for (int i=0; i cache_open_addr_hash& cache_open_addr_hash::operator=(const cache_open_addr_hash& other) { // The assignment operator if (this != &other) { used_size = other.used_size; if (num_buckets != other.num_buckets) { delete[] buckets; num_buckets = other.num_buckets; buckets = new node[num_buckets]; } hash_mask = other.hash_mask; for (int i=0; i cache_open_addr_hash::~cache_open_addr_hash() { // destructor delete[] buckets; } template dt* cache_open_addr_hash::find(const ky& k) { value_type* p = const_cast(find_pair(k)); return p ? &(p->second) : 0; } template const pair * cache_open_addr_hash::find_pair(const ky& k) const { unsigned int index = hash_function(k) & hash_mask; if (equal_key(buckets[index].value.first,k) && buckets[index].stamp == timestamp) return &(buckets[index].value); return 0; } template dt& cache_open_addr_hash::operator[] (const ky& k) { unsigned int index = hash_function(k) & hash_mask; if (equal_key(buckets[index].value.first,k) && buckets[index].stamp == timestamp) return buckets[index].value.second; else { if (buckets[index].stamp != timestamp) ++used_size; buckets[index].value.second = dt(); } buckets[index].stamp = timestamp; buckets[index].value.first = k; return buckets[index].value.second; } template bool cache_open_addr_hash::get(const ky& k, dt** d) { unsigned int index = hash_function(k) & hash_mask; // devolvemos el puntero al valor que hay en index *d = &buckets[index].value.second; if (equal_key(buckets[index].value.first,k) && buckets[index].stamp == timestamp) return true; // copiamos la nueva key buckets[index].value.first = k; buckets[index].stamp = timestamp; ++used_size; return false; } } // namespace AprilUtils #endif // CACHE_OPEN_ADDR_HASH_H april-ann-0.4.1/packages/basics/util/c_src/ceiling_power_of_two.cc000066400000000000000000000022571263004425400252050ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "ceiling_power_of_two.h" namespace AprilUtils { // Returns the highest and closest power of two of a value unsigned int ceilingPowerOfTwo(unsigned int value) { unsigned int power_of_two = 1; while (power_of_two < value) { power_of_two = power_of_two << 1; } return power_of_two; } } april-ann-0.4.1/packages/basics/util/c_src/ceiling_power_of_two.h000066400000000000000000000021331263004425400250400ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef CEILING_POWER_OF_TWO_H #define CEILING_POWER_OF_TWO_H namespace AprilUtils { // Returns the highest and closest power of two of a value unsigned int ceilingPowerOfTwo(unsigned int value); } #endif // CEILING_POWER_OF_TWO_H april-ann-0.4.1/packages/basics/util/c_src/check_floats.cc000066400000000000000000000023251263004425400234230ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "error_print.h" #include "check_floats.h" namespace AprilUtils { bool check_floats(float *v, unsigned int sz) { for (unsigned int i=0; i // convierte todos los numeros denormales en 0, // aunque para en cuanto detecta un NaN o inf, en cuyo caso // devolveria false. Si todo esta bien devuelve true. namespace AprilUtils { bool check_floats(float *v, unsigned int sz); } #endif // CHECK_FLOATS_H april-ann-0.4.1/packages/basics/util/c_src/clamp.h000066400000000000000000000021211263004425400217260ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef CLAMP_H #define CLAMP_H namespace AprilUtils { template T clamp(T val, T lower, T upper) { if (val > upper) return upper; if (val < lower) return lower; return val; } } #endif // defined(CLAMP_H) april-ann-0.4.1/packages/basics/util/c_src/comparable_ptr.h000066400000000000000000000030771263004425400236370ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef COMPARABLE_PTR_H #define COMPARABLE_PTR_H namespace AprilUtils { template class ComparablePtr { T *ptr; public: ComparablePtr(T *p=0) : ptr(p) {} ~ComparablePtr() {} bool operator<(const ComparablePtr &b) const { return *(ptr) < *(b.ptr); } bool operator>(const ComparablePtr &b) const { return *(ptr) > *(b.ptr); } bool operator==(const ComparablePtr &b) const { return *(ptr) == *(b.ptr); } bool operator!=(const ComparablePtr &b) const { return *(ptr) != *(b.ptr); } T& operator *() const { // dereference return *ptr; } T* operator ->() const { return ptr; } }; } #endif // COMPARABLE_PTR_H april-ann-0.4.1/packages/basics/util/c_src/constString.cc000066400000000000000000000264261263004425400233230ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include #include "april_assert.h" #include "binarizer.h" #include "constString.h" #include "mystring.h" namespace AprilUtils { constString::constString(const char *s, size_t n) { buffer = s; length = n; } constString::constString(const char *s) { buffer = s; length = strlen(s); } char* constString::newString() const { int addzero = (length == 0 || buffer[length-1] != '\0') ? 1 : 0; char *resul = new char[length + addzero]; strncpy(resul, buffer, length); if (addzero) resul[length] = '\0'; return resul; } bool constString::operator == (const constString &otro) const { if (length != otro.length) return false; return strncmp(buffer,otro.buffer,length) == 0; } bool constString::operator != (const constString &otro) const { if (length != otro.length) return true; return strncmp(buffer,otro.buffer,length) != 0; } bool constString::operator < (const constString &otro) const { size_t min = (length < otro.length) ? length : otro.length; int cmp = strncmp(buffer,otro.buffer,min); // Si difieren en los primeros min caracteres, ya esta if (cmp==-1) return true; else if (cmp==1) return false; // si no, miramos la longitud else return (length < otro.length); } bool constString::operator <= (const constString &otro) const { size_t min = (length < otro.length) ? length : otro.length; int cmp = strncmp(buffer,otro.buffer,min); // Si difieren en los primeros min caracteres, ya esta if (cmp==-1) return true; else if (cmp==1) return false; // si no, miramos la longitud else return(length <= otro.length); } bool constString::operator > (const constString &otro) const { size_t min = (length < otro.length) ? length : otro.length; int cmp = strncmp(buffer,otro.buffer,min); // Si difieren en los primeros min caracteres, ya esta if (cmp==-1) return false; else if (cmp==1) return true; // si no, miramos la longitud else return (length > otro.length); } bool constString::operator >= (const constString &otro) const { size_t min = (length < otro.length) ? length : otro.length; int cmp = strncmp(buffer,otro.buffer,min); // Si difieren en los primeros min caracteres, ya esta if (cmp==-1) return false; else if (cmp==1) return true; // si no, miramos la longitud else return (length >= otro.length); } void constString::skip(size_t n) { if (buffer) { if (n>length) n = length; length -= n; buffer += n; } } void constString::ltrim(const char *acepta) { // todo: puede fallar si la cadena no es terminada en '\0' if (buffer) { size_t n = AprilUtils::strnspn(buffer,length,acepta,strlen(acepta)); april_assert(n<=length); length -= n; buffer += n; } } bool constString::is_prefix(const constString &theprefix) { if (length < theprefix.length) return false; return strncmp(buffer,theprefix.buffer,theprefix.length) == 0; } bool constString::is_prefix(const char *theprefix) { return is_prefix(constString(theprefix)); } bool constString::skip(const constString &theprefix) { if (!is_prefix(theprefix)) return false; skip(theprefix.length); return true; } bool constString::skip(const char *theprefix) { return skip(constString(theprefix)); } constString constString::extract_prefix(size_t prefix_len) { if (empty()) return constString(); // prefix_len no puede ser mayor que length: if (prefix_len > length) prefix_len = length; constString resul = constString(buffer,prefix_len); length -= prefix_len; buffer += prefix_len; return resul; } constString constString::extract_token(const char *delim, bool keep_delim) { if (!keep_delim) ltrim(delim); if (empty()) return constString(); const char *newbuffer = buffer; size_t newlength = AprilUtils::strncspn(newbuffer,length,delim,strlen(delim)); if (newlength < length && keep_delim) ++newlength; april_assert(newlength<=length); skip(newlength); return constString(newbuffer,newlength); } constString constString::extract_line() { return extract_token("\r\n"); } constString constString::extract_u_line() { constString aux; do { aux = extract_token("\r\n"); } while ((aux.length > 0) && (aux.buffer[0] == '#')); return aux; } bool constString::extract_char(char *resul) { if (empty()) return false; *resul = buffer[0]; skip(1); return true; } bool constString::extract_float(float *resul,const char *delim) { ltrim(delim); if (empty()) return false; char *aux; // FIXME: strtof no controla si nos salimos del constString, luego // lo comprobamos viendo si length < 0 pero podría dar violación de // segmento float value = strtof(buffer,&aux); if (aux == buffer) return false; if (aux > buffer+length+1) return false; length -= aux - buffer; buffer = aux; *resul = value; return true; } bool constString::extract_float_binary(float *resul) { if (empty()) return false; if (buffer[0] == '\n') skip(1); if (length<5 || buffer[0] == 0 || buffer[1] == 0 || buffer[2] == 0 || buffer[3] == 0 || buffer[4] == 0) return false; *resul = binarizer::decode_float(buffer); skip(5); return true; } bool constString::extract_double(double *resul,const char *delim) { ltrim(delim); char *aux; // FIXME: strtod no controla si nos salimos del constString, luego // lo comprobamos viendo si length < 0 pero podría dar violación de // segmento double value = strtod(buffer,&aux); if (aux == buffer) return false; if (aux > buffer+length+1) return false; length -= aux - buffer; buffer = aux; *resul = value; return true; } bool constString::extract_log_float_binary(log_float *resul) { float aux; if (extract_float_binary(&aux)) { *resul = log_float(aux); return true; } return false; } bool constString::extract_log_double_binary(log_double *resul) { double aux; if (extract_double_binary(&aux)) { *resul = log_double::from_double(aux); return true; } return false; } bool constString::extract_double_binary(double *resul) { if (empty()) return false; if (buffer[0] == '\n') skip(1); if (length<5 || buffer[0] == 0 || buffer[1] == 0 || buffer[2] == 0 || buffer[3] == 0 || buffer[4] == 0 || buffer[5] == 0 || buffer[6] == 0 || buffer[7] == 0 || buffer[8] == 0 || buffer[9] == 0) return false; *resul = binarizer::decode_double(buffer); skip(10); return true; } bool constString::extract_int(int *resul, int base,const char *delim) { long int x; if (extract_long(&x,base,delim)) { *resul = (int)x; return true; } return false; } bool constString::extract_unsigned_int(unsigned int *resul, int base,const char *delim) { long int x; if (extract_long(&x,base,delim)) { *resul = (unsigned int)x; return true; } return false; } bool constString::extract_long(long int *resul, int base, const char *delim) { ltrim(delim); if (empty()) return false; char *aux; // fixme: strtol no controla si nos salimos del constString, luego // lo comprobamos viendo si length < 0 pero podría dar violación de // segmento long int value = strtol(buffer,&aux, base); if (aux == buffer) return false; if (aux > buffer+length+1) return false; length -= aux - buffer; buffer = aux; *resul = value; return true; } bool constString::extract_long_long(long long int *resul, int base, const char *delim) { ltrim(delim); if (empty()) return false; char *aux; long long int value = strtoll(buffer,&aux, base); if (aux == buffer) return false; if (aux > buffer+length+1) return false; length -= aux - buffer; buffer = aux; *resul = value; return true; } #ifdef HAVE_UINT16 bool constString::extract_uint16_binary(uint16_t *resul) { if (empty()) return false; if (buffer[0] == '\n') skip(1); if (length<3 || buffer[0] == 0 || buffer[1] == 0 || buffer[2] == 0) return false; *resul = binarizer::decode_uint16(buffer); skip(3); return true; } bool constString::extract_int16_binary(int16_t *resul) { if (empty()) return false; if (buffer[0] == '\n') skip(1); if (length<3 || buffer[0] == 0 || buffer[1] == 0 || buffer[2] == 0) return false; *resul = binarizer::decode_int16(buffer); skip(3); return true; } #endif bool constString::extract_uint32_binary(uint32_t *resul) { if (empty()) return false; if (buffer[0] == '\n') skip(1); if (length<5 || buffer[0] == 0 || buffer[1] == 0 || buffer[2] == 0 || buffer[3] == 0 || buffer[4] == 0) return false; *resul = binarizer::decode_uint32(buffer); skip(5); return true; } bool constString::extract_int32_binary(int32_t *resul) { if (empty()) return false; if (buffer[0] == '\n') skip(1); if (length<5 || buffer[0] == 0 || buffer[1] == 0 || buffer[2] == 0 || buffer[3] == 0 || buffer[4] == 0) return false; *resul = binarizer::decode_int32(buffer); skip(5); return true; } #ifdef HAVE_UINT64 bool constString::extract_uint64_binary(uint64_t *resul) { if (empty()) return false; if (buffer[0] == '\n') skip(1); if (length<10 || buffer[0] == 0 || buffer[1] == 0 || buffer[2] == 0 || buffer[3] == 0 || buffer[4] == 0 || buffer[5] == 0 || buffer[6] == 0 || buffer[7] == 0 || buffer[8] == 0 || buffer[9] == 0) return false; *resul = binarizer::decode_uint64(buffer); skip(10); return true; } bool constString::extract_int64_binary(int64_t *resul) { if (empty()) return false; if (buffer[0] == '\n') skip(1); if (length<10 || buffer[0] == 0 || buffer[1] == 0 || buffer[2] == 0 || buffer[3] == 0 || buffer[4] == 0 || buffer[5] == 0 || buffer[6] == 0 || buffer[7] == 0 || buffer[8] == 0 || buffer[9] == 0) return false; *resul = binarizer::decode_int64(buffer); skip(10); return true; } #endif void constString::print(FILE *F) { for (size_t i=0;i extern "C" { #include } #include "logbase.h" namespace AprilUtils { class constString { const char *buffer; size_t length; public: constString() { buffer = 0; length = 0; } constString(const char *s); constString(const char *s, size_t n); operator bool() { return length>0 && buffer; } bool empty() const{ return length<=0 || !buffer; } bool operator !() { return length<=0 || !buffer; } size_t len() const { return length; } // ojito, este método NO añade el \0 al final operator const char *() const { return buffer; } char operator [] (int i) const { return buffer[i]; } char operator [] (unsigned int i) const { return buffer[i]; } char operator [] (size_t i) const { return buffer[i]; } // char operator [] (size_t i) const { return buffer[i]; } char *newString() const; // el método siguiente crea una cadena nueva que se debe // liberar posteriormente con delete[] // por implementar: // char* operator char*() { return buffer; } // conversor bool operator == (const constString &otro) const; bool operator != (const constString &otro) const; bool operator < (const constString &otro) const; bool operator <= (const constString &otro) const; bool operator > (const constString &otro) const; bool operator >= (const constString &otro) const; bool operator == (const char *otro) const { return operator==(constString(otro)); } bool operator != (const char *otro) const { return operator!=(constString(otro)); } bool operator < (const char *otro) const { return operator<(constString(otro)); } bool operator <= (const char *otro) const { return operator<=(constString(otro)); } bool operator > (const char *otro) const { return operator>(constString(otro)); } bool operator >= (const char *otro) const { return operator>=(constString(otro)); } void skip(size_t n); void ltrim(const char *acepta = " \t"); // void rtrim(); // void trim(); bool is_prefix(const constString &theprefix); bool is_prefix(const char *theprefix); bool skip(const char *theprefix); bool skip(const constString &theprefix); constString extract_prefix(size_t prefix_len); constString extract_token(const char *delim=" \t,;\r\n", bool keep_delim=false); constString extract_line(); constString extract_u_line(); bool extract_char(char *resul); bool extract_int(int *resul, int base = 10, const char *delim=" \t,;\r\n"); bool extract_unsigned_int(unsigned int *resul, int base = 10, const char *delim=" \t,;\r\n"); bool extract_long(long int *resul, int base = 10, const char *delim=" \t,;\r\n"); bool extract_long_long(long long int *resul, int base = 10, const char *delim=" \t,;\r\n"); bool extract_float(float *resul, const char *delim=" \t,;\r\n"); bool extract_double(double *resul, const char *delim=" \t,;\r\n"); bool extract_float_binary(float *resul); bool extract_double_binary(double *resul); bool extract_log_float_binary(log_float *resul); bool extract_log_double_binary(log_double *resul); #ifdef HAVE_UINT16 bool extract_uint16_binary(uint16_t *resul); bool extract_int16_binary(int16_t *resul); #endif bool extract_uint32_binary(uint32_t *resul); bool extract_int32_binary(int32_t *resul); #ifdef HAVE_UINT64 bool extract_uint64_binary(uint64_t *resul); bool extract_int64_binary(int64_t *resul); #endif void print(FILE *F=stdout); bool good() const { return !empty(); } }; char *copystr(const char *c); } // namespace AprilUtils #endif // CONSTSTRING_H april-ann-0.4.1/packages/basics/util/c_src/context.h000066400000000000000000000233351263004425400223300ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef CONTEXT_H #define CONTEXT_H #include "april_assert.h" #include /* AprilUtils::context * * Una cola con acceso aleatorio a los elementos. Sirve para guardar el * contexto de los objetos de una secuencia que vamos recorriendo. * * Metodos publicos: * * - context(int before, int after): Constructor, crea un objeto de tipo * context reservando espacio para (before) objetos de tipo T anteriores al * elemento actual y (after) objetos de tipo T posteriores al actual. * * +-----+-----+-----+-----+-----+-----+-----+-----+-----+ * | -4 | -3 | -2 | -1 | 0 | +1 | +2 | +3 | +4 | * +-----+-----+-----+-----+-----+-----+-----+-----+-----+ * * <--------before-------->| cur |<---------after--------> * * - bool insert(T *elem): Toma un puntero a un objeto de tipo T y lo inserta * en la posicion (after) del vector, dado que es el mas reciente, * desplazando el resto y destruyendo, si procede, el mas antiguo. * Devuelve true si el elemento se ha insertado, false si se intenta * insertar despues de llamar a end_input() * * - bool insert(const T& elem): Igual que el anterior pero realizando una * copia del objeto pasado como parámetro. * * - bool ready(): devuelve true cuando todos los elementos del contexto son * validos. Al crear el context es necesario insertar (after+1) elementos * para que ready() devuelva true. Al final del proceso ready() devolvera * false cuando el elemento actual se encuentre despues del ultimo * introducido. * * Ejemplo: entrada=ABCDE, before=1, after=2 * * /--- Elemento actual * | * v * t=1 insert(A) A|A|-- ready=false * t=2 insert(B) A|A|B- ready=false * t=3 insert(C) A|A|BC ready=true * t=4 insert(D) A|B|CD ready=true * t=5 insert(E) B|C|DE ready=true * --- end_input() * t=6 shift() C|D|EE ready=true * t=7 shift() D|E|EE ready=true * t=8 shift() E|E|EE ready=false * * - void end_input(): Se utiliza para marcar el final de los datos de entrada * * - bool shift(): Una vez marcado el final de la entrada con end_input(), cada * llamada a shift() desplaza el vector. Conceptualmente es equivalente a * insertar una copia del ultimo elemento de la entrada utilizando insert() * * - void reset(): Reinicializa el objeto. Borra todos los objetos del contexto * y lo deja como si estuviera recien creado por el constructor. * * - const T& operator[]: Permite el acceso al contexto utilizando los indices indicados * en el diagrama anterior. 0 representa el elemento actual. -1,-2... los * elementos anteriores y 1,2,... los posteriores. */ namespace AprilUtils { template class context { int before; int after; int num_inserts; int num_shifts; // Numero de desplazamientos tras el fin de la entrada bool end; bool fill_after; int vec_size; T** vec; void init(){ num_inserts=0; num_shifts=0; end=false; fill_after=false; } void delete_contents() { // comprobamos que haya habido alguna insercion if (num_inserts != 0) { int before=0; int after=vec_size-1; while ((before < vec_size-1) && (vec[before] == vec[before+1])) before++; // Si hay elementos nulos al final, no hay repetidos // posteriores y el bucle parara en el ultimo 0 empezando // desde el final del vector. No obstante, hacer un delete de un // puntero nulo es correcto (no hace nada) :) while ((after > before) && (vec[after] == vec[after-1])) after--; for(int i=before; i<=after; i++) delete vec[i]; } // ponemos los punteros del vector a 0 for (int i = 0; i < vec_size; i++) vec[i] = 0; } public: context(int before, int after): before(before), after(after), vec_size(before+after+1) { // cuando comparamos un elemento y el siguiente del array // necesitamos al menos un array de tam = 2 april_assert(before+after > 0); vec = new T* [vec_size]; init(); for (int i = 0; i < vec_size; i++) vec[i] = 0; } ~context() { delete_contents(); delete[] vec; } int get_before() const { return before; } int get_after() const { return after; } // Toma un puntero y se adueña de el, liberandolo // cuando ya no sea necesario. bool insert(T* elem) { if (end) return false; if (before+num_inserts < vec_size) { // Aun no hemos llenado el vector por primera vez vec[before+num_inserts] = elem; } else { // El vector ya esta lleno, desplazamos e insertamos al final if (vec[0] != vec[1]) delete vec[0]; for (int i=0; i after); else return (num_shifts <= after) && (num_shifts <= num_inserts); } void end_input() { end = true; fill_after = (num_inserts > 0 && num_inserts < vec_size); } bool shift() { if (!end) return false; // Si no se ha llenado el vector, se replica el // ultimo elemento tantas veces como sea necesario // para llenar los elementos posteriores del contexto // y no se desplaza la primera vez (el elemento central // nunca ha estado ready y no ha sido accedido aun) if (fill_after) { for (int i=before+num_inserts; i after || t <= num_inserts); // Comprobaciones de rango april_assert(t<=after); april_assert(t>=-before); return *vec[before+t]; } }; // wrapper para un caso tipico de uso de context template struct vec_wrapper { T *vec; int input_vec_size; vec_wrapper(T *v, int sz) : input_vec_size(sz) { vec = new T[sz]; for (int i=0; i class context_of_vectors { context > ctxt; int input_vec_size; public: context_of_vectors(int before, int after, int input_vec_size): ctxt(before,after), input_vec_size(input_vec_size) { } ~context_of_vectors() { } bool insert(T* vec) { return ctxt.insert(new vec_wrapper(vec,input_vec_size)); } bool ready() const { return ctxt.ready(); } void end_input() { ctxt.end_input(); } bool is_ended() const { return ctxt.is_ended(); } bool shift() { return ctxt.shift(); } void reset() { ctxt.reset(); } T* getOutputVector() const { T *output = 0; if (ctxt.ready()) { int before = ctxt.get_before(); int after = ctxt.get_after(); output = new T[(before+1+after)*input_vec_size]; int o_idx = 0; for (int i=-before; i<=after; i++) for(int j = 0; j < input_vec_size; j++, o_idx++) output[o_idx] = ctxt[i][j]; } return output; } }; } #endif april-ann-0.4.1/packages/basics/util/c_src/derivative.cc000066400000000000000000000033011263004425400231330ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "derivative.h" #include "clamp.h" namespace AprilUtils { // Explicacion de las formulas en: // http://legacy.ncsu.edu/classes-a/mat310_info/DiffInt/NumDeriv.html void derivative1(float *v, float *v_dest, int n) { int izq1, izq2, der1, der2; for (int i=0; i void swap_bytes_in_place(T &data) { size_t sz = sizeof(T); char *ptr = reinterpret_cast(&data); size_t last = sz-1; const size_t half = sz/2; for (size_t i=0; i T swap_bytes(T data) { T copy_data = data; size_t sz = sizeof(T); char *ptr = reinterpret_cast(©_data); size_t last = sz-1; const size_t half = sz/2; for (size_t i=0; i #include #include #include #include "unused_variable.h" /** Print a demangled stack backtrace of the caller function to FILE* out. */ void print_CPP_stacktrace(FILE *out) { if (getSilentErrorsValue()) return; #ifdef NDEBUG UNUSED_VARIABLE(out); #else fprintf(out, "C/C++ stack trace:\n"); // storage array for stack trace address data void* addrlist[MAX_FRAMES+1]; // retrieve current stack addresses int addrlen = backtrace(addrlist, sizeof(addrlist) / sizeof(void*)); if (addrlen == 0) { fprintf(out, " \n"); return; } // resolve addresses into strings containing "filename(function+address)", // this array must be free()-ed char** symbollist = backtrace_symbols(addrlist, addrlen); // allocate string which will be filled with the demangled function name size_t funcnamesize = FUNC_NAME_SIZE; char* funcname = (char*)malloc(funcnamesize); // iterate over the returned symbol lines. skip the first, it is the // address of this function. for (int i = 1; i < addrlen; i++) { char *begin_name = 0, *begin_offset = 0, *end_offset = 0; // find parentheses and +address offset surrounding the mangled name: // ./module(function+0x15c) [0x8048a6d] for (char *p = symbollist[i]; *p; ++p) { if (*p == '(') begin_name = p; else if (*p == '+') begin_offset = p; else if (*p == ')' && begin_offset) { end_offset = p; break; } } if (begin_name && begin_offset && end_offset && begin_name < begin_offset) { *begin_name++ = '\0'; *begin_offset++ = '\0'; *end_offset = '\0'; // mangled name is now in [begin_name, begin_offset) and caller // offset in [begin_offset, end_offset). now apply // __cxa_demangle(): int status; char* ret = abi::__cxa_demangle(begin_name, funcname, &funcnamesize, &status); if (status == 0) { funcname = ret; // use possibly realloc()-ed string fprintf(out, " %s : %s+%s\n", symbollist[i], funcname, begin_offset); } else { // demangling failed. Output function name as a C function with // no arguments. fprintf(out, " %s : %s()+%s\n", symbollist[i], begin_name, begin_offset); } } else { // couldn't parse the line? print the whole line. fprintf(out, " %s\n", symbollist[i]); } } free(funcname); free(symbollist); #endif } ////////////////////////////////////////////////////////////////////////////// #define SIZE 2048u void print_CPP_LUA_stacktrace_and_exit(int errorcode, const char *format, ...) { UNUSED_VARIABLE(errorcode); va_list list; va_start( list, format ); print_CPP_stacktrace(); char *error_message = new char[SIZE+1]; int len = vsnprintf(error_message, SIZE, format, list); va_end(list); throw(error_message); } #undef SIZE april-ann-0.4.1/packages/basics/util/c_src/error_print.h000066400000000000000000000106501263004425400232050ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef ERROR_PRINT_H #define ERROR_PRINT_H #include bool getSilentErrorsValue(); void setSilentErrorsValue(bool value); void print_CPP_LUA_stacktrace_and_exit(int errorcode, const char *format, ...); void print_CPP_stacktrace(FILE *out = stderr); #define ERROR_PRINT(strformat) \ if (!getSilentErrorsValue()) fprintf(stderr, "Error in file %s in line %d, function %s: " strformat, __FILE__, __LINE__, __FUNCTION__) #define ERROR_PRINT1(strformat, v1) \ if (!getSilentErrorsValue()) fprintf(stderr, "Error in file %s in line %d, function %s: " strformat, __FILE__, __LINE__, __FUNCTION__,(v1)) #define ERROR_PRINT2(strformat, v1, v2) \ if (!getSilentErrorsValue()) fprintf(stderr, "Error in file %s in line %d, function %s: " strformat, __FILE__, __LINE__, __FUNCTION__, (v1), (v2)) #define ERROR_PRINT3(strformat, v1, v2, v3) \ if (!getSilentErrorsValue()) fprintf(stderr, "Error in file %s in line %d, function %s: " strformat, __FILE__, __LINE__, __FUNCTION__, (v1), (v2), (v3)) #define ERROR_PRINT4(strformat, v1, v2, v3, v4) \ if (!getSilentErrorsValue()) fprintf(stderr, "Error in file %s in line %d, function %s: " strformat, __FILE__, __LINE__, __FUNCTION__, (v1), (v2), (v3), (v4)) #define ERROR_PRINT5(strformat, v1, v2, v3, v4, v5) \ if (!getSilentErrorsValue()) fprintf(stderr, "Error in file %s in line %d, function %s: " strformat, __FILE__, __LINE__, __FUNCTION__, (v1), (v2), (v3), (v4), (v5)) #define ERROR_PRINT6(strformat, v1, v2, v3, v4, v5, v6) \ if (!getSilentErrorsValue()) fprintf(stderr, "Error in file %s in line %d, function %s: " strformat, __FILE__, __LINE__, __FUNCTION__, (v1), (v2), (v3), (v4), (v5), (v6)) #define ERROR_PRINT7(strformat, v1, v2, v3, v4, v5, v6, v7) \ if (!getSilentErrorsValue()) fprintf(stderr, "Error in file %s in line %d, function %s: " strformat, __FILE__, __LINE__, __FUNCTION__, (v1), (v2), (v3), (v4), (v5), (v6), (v7)) #define ERROR_EXIT(errorcode, strformat) \ print_CPP_LUA_stacktrace_and_exit(errorcode,"Error in file %s in line %d, function %s: " strformat,__FILE__,__LINE__,__FUNCTION__) #define ERROR_EXIT1(errorcode, strformat, v1) \ print_CPP_LUA_stacktrace_and_exit(errorcode,"Error in file %s in line %d, function %s: " strformat,__FILE__,__LINE__,__FUNCTION__,(v1)) #define ERROR_EXIT2(errorcode, strformat, v1, v2) \ print_CPP_LUA_stacktrace_and_exit(errorcode,"Error in file %s in line %d, function %s: " strformat,__FILE__,__LINE__,__FUNCTION__,(v1),(v2)) #define ERROR_EXIT3(errorcode, strformat, v1, v2, v3) \ print_CPP_LUA_stacktrace_and_exit(errorcode,"Error in file %s in line %d, function %s: " strformat,__FILE__,__LINE__,__FUNCTION__,(v1),(v2),(v3)) #define ERROR_EXIT4(errorcode, strformat, v1, v2, v3, v4) \ print_CPP_LUA_stacktrace_and_exit(errorcode,"Error in file %s in line %d, function %s: " strformat,__FILE__,__LINE__,__FUNCTION__,(v1),(v2),(v3),(v4)) #define ERROR_EXIT5(errorcode, strformat, v1, v2, v3, v4, v5) \ print_CPP_LUA_stacktrace_and_exit(errorcode,"Error in file %s in line %d, function %s: " strformat,__FILE__,__LINE__,__FUNCTION__,(v1),(v2),(v3),(v4),(v5)) #define ERROR_EXIT6(errorcode, strformat, v1, v2, v3, v4, v5, v6) \ print_CPP_LUA_stacktrace_and_exit(errorcode,"Error in file %s in line %d, function %s: " strformat,__FILE__,__LINE__,__FUNCTION__,(v1),(v2),(v3),(v4),(v5),(v6)) #define ERROR_EXIT7(errorcode, strformat, v1, v2, v3, v4, v5, v6, v7) \ print_CPP_LUA_stacktrace_and_exit(errorcode,"Error in file %s in line %d, function %s: " strformat,__FILE__,__LINE__,__FUNCTION__,(v1),(v2),(v3),(v4),(v5),(v6),(v7)) #endif // ERROR_EXIT_H april-ann-0.4.1/packages/basics/util/c_src/fifo.h000066400000000000000000000057671263004425400216000ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef FIFO_H #define FIFO_H namespace AprilUtils { template struct fifo_node { S value; fifo_node *next; fifo_node(S val) : value(val), next(0) { } }; template class fifo { fifo_node *first, *last; int the_size; public: fifo(); ~fifo(); const fifo_node *begin() const { return first; } //const fifo_node *end() const { return last; } int size() const; bool empty() const; void put(T value); bool get(T &value); bool consult(T &value); bool drop_by_value(T value); }; template fifo::fifo() : first(0), last(0), the_size(0) { } template fifo::~fifo() { while (first) { fifo_node *aux = first; first = first->next; // TODO ¿delete value? si: // delete aux->value; delete aux; } } template int fifo::size() const { return the_size; } template bool fifo::empty() const { return the_size == 0; } template void fifo::put(T value) { fifo_node *aux = new fifo_node(value); if (first) last->next = aux; else first = aux; last = aux; the_size++; } template bool fifo::get(T &value) { if (!first) return false; the_size--; value = first->value; if (first == last) last = 0; fifo_node *aux = first; first = first->next; delete aux; return true; } template bool fifo::consult(T &value) { if (!first) return false; value = first->value; return true; } template bool fifo::drop_by_value(T value) { fifo_node *prev = 0; fifo_node *reco = first; while (reco && reco->value != value) { prev = reco; reco = reco->next; } if (reco == 0) return false; // eliminar valor apuntado por reco the_size--; if (last == reco) last = prev; if (prev == 0) { first = reco->next; } else { prev->next = reco->next; } delete reco; // return true; } } #endif // FIFO_H april-ann-0.4.1/packages/basics/util/c_src/fifo_block.h000066400000000000000000000214611263004425400227370ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef FIFO_BLOCK_H #define FIFO_BLOCK_H #include "swap.h" namespace AprilUtils { /** * representa una cola fifo pero es una implementación hibrida entre * vector y listas enlazadas. Se trata de una lista de vectores de * talla fija (talla fifo_block_size) y requiere dos índices de * vector para indicar en qué posiciones del primer vector de la * lista, y en qué posición del último vector de la lista, se * encuentran los elementos a extraer y a insertar, respectivamente. */ template class fifo_block { struct fifo_block_node { T value[fifo_block_size]; fifo_block_node *next; fifo_block_node() : next(0) { } }; // atributos fifo_block_node *first, *last; int index_read; // pos siguiente lectura int index_write; // pos siguiente escritura // metodo auxiliar void internal_copy(const fifo_block& other) { // asumimos que nuestro objeto está ya vacio int other_read = other.index_read; // ahora recorremos los elementos de other const fifo_block_node *other_pointer = other.first; while (other_pointer != other.last || other_read < other.index_write) { put(other_pointer->value[other_read]); other_read++; if (other_read >= fifo_block_size) { other_read = 0; other_pointer = other_pointer->next; } } } public: typedef T value_type; typedef T* pointer; typedef T& reference; typedef const T& const_reference; typedef size_t size_type; typedef ptrdiff_t difference_type; struct block_iterator { friend class fifo_block; private: fifo_block_node *ptr; public: typedef T value_type; typedef T* pointer; typedef T& reference; typedef const T& const_reference; typedef ptrdiff_t difference_type; block_iterator(fifo_block_node *p=0): ptr(p) {} block_iterator& operator++() { // preincrement ptr = ptr->next; return *this; } T* operator *() { // dereference return ptr->value; } bool operator == (const block_iterator &i) { return ptr == i.ptr; } bool operator != (const block_iterator &i) { return ptr != i.ptr; } }; struct const_iterator; struct iterator { friend struct const_iterator; friend class fifo_block; private: int index; fifo_block_node *ptr; public: typedef T value_type; typedef T* pointer; typedef T& reference; typedef const T& const_reference; typedef ptrdiff_t difference_type; iterator(): index(0),ptr(0) {} iterator(int i, fifo_block_node *p): index(i),ptr(p) {} iterator& operator++() { // preincrement index++; if (index >= fifo_block_size) { index = 0; ptr = ptr->next; } return *this; } iterator operator++(int) { // postincrement int itmp = index; fifo_block_node *ptmp = ptr; index++; if (index >= fifo_block_size) { index = 0; ptr = ptr->next; } return iterator(itmp,ptmp); } T& operator *() { // dereference return ptr->value[index]; } T* operator ->() { return &(ptr->value[index]); } bool operator == (const iterator &i) { return index == i.index && ptr == i.ptr; } bool operator != (const iterator &i) { return index != i.index || ptr != i.ptr; } }; // closes struct iterator struct const_iterator { private: int index; const fifo_block_node *ptr; public: typedef T value_type; typedef T* pointer; typedef T& reference; typedef const T& const_reference; typedef ptrdiff_t difference_type; const_iterator(): index(0), ptr(0) {} const_iterator(int i, const fifo_block_node *p): index(i), ptr(p) {} const_iterator(const iterator &i): index(i.index), ptr(i.ptr) {} const_iterator& operator++() { // preincrement index++; if (index >= fifo_block_size) { index = 0; ptr = ptr->next; } } const_iterator operator++(int) { // postincrement int itmp = index; fifo_block_node *ptmp = ptr; index++; if (index >= fifo_block_size) { index = 0; ptr = ptr->next; } return const_iterator(itmp,ptmp); } const T& operator *() { // dereference return ptr->value[index]; } const T* operator ->() { return &(ptr->value[index]); } bool operator == (const const_iterator &i) { return index == i.index && ptr == i.ptr; } bool operator != (const const_iterator &i) { return index != i.index || ptr != i.ptr; } }; // closes struct const_iterator iterator begin() { return iterator(index_read,first); } iterator end() { return iterator(index_write,last); } const_iterator begin() const { return const_iterator(index_read,first); } const_iterator end() const { return const_iterator(index_write,last); } block_iterator block_begin() { return block_iterator(first); } block_iterator block_end() { return block_iterator(0); } size_type size() const { return count(); } size_type block_size() const { return fifo_block_size; } size_type max_size() const { return size_type(-1); } bool empty() const { return (first == last && index_read >= index_write); } void clear() { while (first) { fifo_block_node *aux = first; first = first->next; delete aux; } index_read = index_write = 0; last = 0; } bool is_end(const iterator &iter) const { return (iter.ptr == 0) || ((iter.ptr == last) && (iter.index == index_write)); } fifo_block(): first(0), last(0), index_read(0), index_write(0) {} fifo_block(const fifo_block& other) : first(0), last(0), index_read(0), index_write(0) { internal_copy(other); } ~fifo_block() { clear(); } fifo_block& operator=(const fifo_block& other) { // asignment operator if (&other != this) { clear(); internal_copy(other); } return *this; } T* put(const T& value) { if (last == 0 || index_write >= fifo_block_size) { fifo_block_node *aux = new fifo_block_node; ((last) ? last->next : first) = aux; last = aux; index_write = 0; } T *address = &(last->value[index_write]); last->value[index_write] = value; index_write++; return address; } void drop() { // CUIDADO! REQUIERE QUE NO ESTE VACIA index_read++; if (index_read >= fifo_block_size) { fifo_block_node *aux = first; if (last == first) last = 0; first = first->next; index_read = 0; delete aux; } } bool get(T &value) { if (empty()) return false; value = first->value[index_read]; drop(); return true; } bool consult(T &value) { if (empty()) return false; value = first->value[index_read]; return true; } int count() const { int i = index_read, c = 0; const fifo_block_node *p = first; while (p != last || i < index_write) { c++; i++; if (i >= fifo_block_size) { i = 0; p = p->next; } } return c; } void take_content_from(fifo_block& other) { if (&other != this) { clear(); first = other.first; last = other.last; index_read = other.index_read; index_write = other.index_write; other.first = other.last = 0; other.index_read = other.index_write= 0; } } void swap(fifo_block &other) { AprilUtils::swap(index_read, other.index_read); AprilUtils::swap(index_write, other.index_write); AprilUtils::swap(first, other.first); AprilUtils::swap(last, other.last); } bool contains_node(T *ptr) const { for (fifo_block_node *r = first; r!=0; r=r->next) if (r->value <= ptr && ptr < r->value+fifo_block_size) return true; return false; } }; // closes class fifo_block } // closes namespace AprilUtils #endif // FIFO_BLOCK_H april-ann-0.4.1/packages/basics/util/c_src/geometry.cc000066400000000000000000000036321263004425400226330ustar00rootroot00000000000000#include #include #include #include #include "geometry.h" namespace AprilUtils { const float infinity = std::numeric_limits::infinity(); template line::line(const Point &x, const Point &y) { float x1 = (float) x.x; float y1 = (float) x.y; float x2 = (float) y.x; float y2 = (float) y.y; if (x2 == x1) { fprintf(stderr, "Warning the slope is infinite"); m = infinity; } else { m = (y2 - y1)/(x2-x1); } b = y1 -m*x1; } template line::line(const Point &, const Point &); // static line fromPolar(float phi, float r); /* void line::getPolars(float &phi, float &r) { //TODO return; }; */ Point2D line::intersection(const line &out, bool &intersect) { // Parallel form if (m == out.m){ intersect = false; return (Point2D(infinity, infinity)); } // FIXME: Infinite slope float m1 = m; float m2 = out.m; float b1 = b; float b2 = out.b; float x = (b2 - b1)/(m1-m2); float y = m1*x+b1; return Point2D(x,y); } template <> float line::distance(const Point &p) { float x = p.x; float y = p.y; return fabs(m*x+b-y)/sqrt(m*m+1);; } template <> float line::distance(const Point &p) { Point pf = Point(p); return this->distance(pf); } template Point2D line::closestPoint(const Point &p, float &dist) { int x1 = p.x; int y1 = p.y; // Extracted from: http://math.ucsd.edu/~wgarner/math4c/derivations/distance/distptline.htm float x = (m*y1+x1-m*b)/(m*m+1); float y = (m*m*y1+m*x1+b)/(m*m+1); dist = distance(p); return Point2D(x, y); } template <> Point2D line::closestPoint(const Point &p, float &dist) { Point pf = Point(p); return this->closestPoint(pf,dist); } } april-ann-0.4.1/packages/basics/util/c_src/geometry.h000066400000000000000000000042351263004425400224750ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez, Salvador España-Boquera, Joan Pastor-Pellicer * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef GEOMETRY_H #define GEOMETRY_H #include "pair.h" namespace AprilUtils { template struct Point { T x; T y; Point(T x, T y):x(x),y(y){}; Point(){}; Point(const Point &p){ x = static_cast(p.x); y = static_cast(p.y); }; }; typedef Point Point2D; // TODO: Define Point2D class line { protected: // Slope, y-intercept float m, b; public: line(float m, float b): m(m),b(b){}; template line(const Point &, const Point &); // static line fromPolar(float phi, float r); float getSlope() { return m; }; float getYintercept() { return b; }; //void getPolars(float &phi, float &r); Point2D intersection(const line &, bool &intersect); template Point2D closestPoint(const Point &, float &); template float distance(const Point &); //static void polarToRect(float , float , float &, float &); //static void rectToPolar(float, float , float &, float &); }; // TODO: Point/Angle Functions // Derivate interest_point Point2D } #endif april-ann-0.4.1/packages/basics/util/c_src/hash_table.h000066400000000000000000000401711263004425400227330ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef HASH_TABLE_H #define HASH_TABLE_H #include "aux_hash_table.h" #include // ceilf #include // ptrdiff_t, size_t... #include "pair.h" //#include #include "vector.h" /** \namespace AprilUtils esto es una prueba */ namespace AprilUtils { // HashFcn es del tipo: // struct hash_fcn { // unsigned int operator()(const char* s1) const { // return blah...; // } // }; // EqualKey es del tipo: // struct eqstr { // bool operator()(const char* s1, const char* s2) const { // return strcmp(s1, s2) == 0; // } // }; template , typename EqualKey = default_equality_comparison_function > class hash { public: // Para ser un "Pair associative container" el value_type deberia ser // un std::pair. typedef KeyType key_type; typedef DataType data_type; typedef pair value_type; typedef value_type& reference; typedef const value_type const_value; typedef const_value& const_reference; typedef value_type* pointer; typedef ptrdiff_t difference_type; typedef size_t size_type; struct node { value_type value; node *next; node(const KeyType& k, const DataType& d, node *n): value(k,d), next(n) {} node(const node& other): value(other.value.first, other.value.second), next(other.next){} }; private: node **buckets; // vector of pointers to node int num_buckets;// a power of 2 int hash_mask; // useful to do "& hash_mask" instead of "% num_buckets" int the_size; int rehash_threshold; float max_load_factor; // for rehashing purposes int first_power_of_2(int value);// auxiliary function void copy_buckets(const hash&); // auxiliary function HashFcn hash_function; EqualKey equal_key; public: hash(int nbckts=8, float mxloadf=4.0); // constructor hash(const hash&); // copy constructor ~hash(); // destructor hash& operator=(const hash&); // assignment operator void clear(); // Erases all of the elements. data_type* find(const key_type& k) const; value_type* find_pair(const key_type& k) const; bool search(const key_type& k) const { return find_pair(k) != 0; } void erase(const key_type& k); template void delete_if(predicate &p); // bool operator==(const hash&) const; // tests two hash for equality. value_type* find_and_add_pair(const key_type& k, bool &isNew); data_type& operator[] (const key_type& k) { bool dummy; return find_and_add_pair(k,dummy)->second; } // devuelve true si se acaba de crear bool insert(const key_type& k, const data_type& d) { bool resul; find_and_add_pair(k,resul)->second = d; return resul; } void resize(int n); // rehash, num_buckets at least n after resize int bucket_count() const { // Returns the number of buckets used by the hash return num_buckets; } int size() const { // Returns the size of the hash return the_size; } bool empty() const { return the_size == 0; } float get_max_load_factor() const { return max_load_factor; } int get_num_buckets() const { return num_buckets; } void get_hash_nodes(vector &output_vector) const; class const_iterator; class iterator { friend class const_iterator; friend class hash; hash *h; int index; node *ptr; iterator(hash *h, int index, node *ptr): h(h), index(index), ptr(ptr) {} public: // Para ser un "Pair associative container" el value_type deberia ser // un std::pair. Bueno, que le vamos a hacer :_( typedef KeyType key_type; typedef DataType data_type; typedef pair value_type; typedef value_type& reference; typedef const value_type const_value; typedef const_value& const_reference; typedef value_type* pointer; typedef ptrdiff_t difference_type; typedef size_t size_type; //typedef std::forward_iterator_tag iterator_category; iterator(): h(0), index(0), ptr(0) {} iterator(const iterator &other): h(other.h), index(other.index), ptr(other.ptr) {} iterator& operator=(const iterator &other) { if (&other != this) { h = other.h; index = other.index; ptr = other.ptr; } return *this; } iterator& operator++(){ // preincrement ptr = ptr->next; while (ptr == 0) { index++; if (index < h->num_buckets) ptr = h->buckets[index]; else break; } return *this; } iterator operator++(int){ // postincrement iterator tmp(*this); ++(*this); return tmp; } value_type& operator *() { //dereference return ptr->value; } value_type* operator ->() { return &(ptr->value); } bool operator == (const iterator &other) { return ((ptr == other.ptr) && (h == other.h) && (index == other.index)); } bool operator != (const iterator &other) { return ((ptr != other.ptr) || (h != other.h) || (index != other.index)); } }; class const_iterator { friend class hash; const hash *h; int index; const node *ptr; const_iterator(const hash *h, int index, const node *ptr): h(h), index(index), ptr(ptr) {} public: // Para ser un "Pair associative container" el value_type deberia ser // un std::pair. Bueno, que le vamos a hacer :_( typedef KeyType key_type; typedef DataType data_type; typedef pair value_type; typedef value_type& reference; typedef const value_type const_value; typedef const_value& const_reference; typedef value_type* pointer; typedef ptrdiff_t difference_type; typedef size_t size_type; //typedef std::forward_iterator_tag iterator_category; const_iterator(): h(0), index(0), ptr(0) {} // Copy constructor (from iterator and const_iterator) const_iterator(const iterator &other): h(other.h), index(other.index), ptr(other.ptr) {} const_iterator(const const_iterator &other): h(other.h), index(other.index), ptr(other.ptr) {} // Assignment operators const_iterator& operator=(const iterator &other) { h = other.h; index = other.index; ptr = other.ptr; return *this; } const_iterator& operator=(const const_iterator &other) { h = other.h; index = other.index; ptr = other.ptr; return *this; } const_iterator& operator++(){ // preincrement ptr = ptr->next; while (ptr == 0) { index++; if (index < h->num_buckets) ptr = h->buckets[index]; else break; } return *this; } const_iterator operator++(int){ // postincrement const_iterator tmp(*this); ++(*this); return tmp; } const value_type& operator *() { //dereference return ptr->value; } const value_type* operator ->() { return &(ptr->value); } // Eq comparisons bool operator == (const iterator &other) const { return ((ptr == other.ptr) && (h == other.h) && (index == other.index)); } bool operator == (const const_iterator &other) const { return ((ptr == other.ptr) && (h == other.h) && (index == other.index)); } bool operator != (const iterator &other) const { return ((ptr != other.ptr) || (h != other.h) || (index != other.index)); } bool operator != (const const_iterator &other) const { return ((ptr != other.ptr) || (h != other.h) || (index != other.index)); } }; iterator begin() { int i=0; node *ptr = buckets[0]; while (ptr == 0) { i++; if (i < num_buckets) ptr = buckets[i]; else break; } return iterator(this, i, ptr); } const_iterator begin() const { int i=0; const node *ptr = buckets[0]; while (ptr == 0) { i++; if (i < num_buckets) ptr = buckets[i]; else break; } return const_iterator(this, i, ptr); } private: iterator end_iterator; public: iterator end() const { return end_iterator; } }; template int hash::first_power_of_2(int value) { int result = 1; while (result < value) result += result; return result; } template hash::hash(int nbckts, float mxloadf) { num_buckets = first_power_of_2(nbckts); hash_mask = num_buckets-1; // num_buckets is a power of 2 the_size = 0; max_load_factor = mxloadf; rehash_threshold= (int)ceilf(max_load_factor*num_buckets); buckets = new node*[num_buckets]; end_iterator = iterator(this, num_buckets, 0); for (int i=0; i inline void hash::copy_buckets(const hash& other) { // auxiliary function // num_buckets == other.num_buckets is assumed for (int i=0; inext) { *totail = new node(*reco); // **totail = *reco; // shallow copy totail = &((*totail)->next); } *totail = 0; } } template hash::hash(const hash& other) { // copy constructor num_buckets = other.num_buckets; hash_mask = other.hash_mask; the_size = other.the_size; max_load_factor = other.max_load_factor; rehash_threshold= other.rehash_threshold; buckets = new node* [num_buckets]; end_iterator = iterator(this, num_buckets, 0); copy_buckets(other); } template void hash::clear() { // Erases all of the elements. if (!empty()) { for (int i=0; inext; delete aux; } the_size = 0; } } // recibe un vector y deposita en el las direcciones de todos los // nodos de la tabla, alternativa a usar un iterador para recorrer // toda la tabla, que quizas seria lo mas elegante y adecuado template void hash::get_hash_nodes(vector &output_vector) const { output_vector.clear(); if (!empty()) { for (int i=0; inext) output_vector.push_back(&r->value); } } template hash& hash::operator=(const hash& other) { // The assignment operator if (this != &other) { clear(); if (num_buckets != other.num_buckets) { delete[] buckets; num_buckets = other.num_buckets; buckets = new node* [num_buckets]; } end_iterator = iterator(this, num_buckets, 0); hash_mask = other.hash_mask; the_size = other.the_size; max_load_factor = other.max_load_factor; rehash_threshold= other.rehash_threshold; copy_buckets(other); } return *this; } template hash::~hash() { // destructor clear(); delete[] buckets; } // template // bool hash::operator==(const hash&) const { // Tests two hash for equality. // if (size() != other.size()) return false; // // equal size, look for inclusion // for (int i=0; inext) { // const node *p = other.find(reco->value.first); // if (!p || reco->value.first != p->value.first) // falta comparar campo data!!!! // return false; // } // return true; // } template dt* hash::find(const ky& k) const { value_type* p = find_pair(k); return p ? &(p->second) : 0; } template pair* hash::find_pair(const ky& k) const { unsigned int index = hash_function(k) & hash_mask; for (node* reco = buckets[index]; reco != 0; reco = reco->next) if (equal_key(k,reco->value.first)) return &(reco->value); return 0; } template void hash::erase(const ky& k) { unsigned int index = hash_function(k) & hash_mask; for (node** reco = &buckets[index]; *reco != 0; reco = &((*reco)->next)) if (equal_key(k,(*reco)->value.first)) { node* aux = *reco; *reco = (*reco)->next; delete aux; the_size--; return; } return; } template pair* hash::find_and_add_pair(const ky& k, bool &isNew) { unsigned int index = hash_function(k) & hash_mask; for (node* reco = buckets[index]; reco != 0; reco = reco->next) if (equal_key(k,reco->value.first)) { isNew = false; return &(reco->value); } node* newnode = new node(k, dt(), buckets[index]); buckets[index]= newnode; the_size++; if (the_size >= rehash_threshold) // rehashing? resize(2*num_buckets); isNew = true; return &(newnode->value); } template void hash::resize(int n) { n = first_power_of_2(n); if (n != num_buckets) { node **old_buckets = buckets; int old_num_buckets= num_buckets; num_buckets = n; end_iterator= iterator(this, num_buckets, 0); hash_mask = n-1; rehash_threshold= (int)ceilf(max_load_factor*num_buckets); buckets = new node* [num_buckets]; for (int i=0; inext; unsigned int index = hash_function(aux->value.first) & hash_mask; aux->next = buckets[index]; buckets[index] = aux; } delete[] old_buckets; } } template template void hash::delete_if(predicate &p) { for (int i=0; ivalue)) { if (prev == 0) buckets[i] = cur->next; else prev->next = cur->next; node *tmp = cur; cur = cur->next; // prev sigue siendo el mismo al borrar cur delete tmp; --the_size; } else { prev = cur; cur = cur->next; } } } } } // namespace AprilUtils #endif // HASH_TABLE_H april-ann-0.4.1/packages/basics/util/c_src/ignore_result.h000066400000000000000000000020621263004425400235170ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef IGNORE_RESULT_H #define IGNORE_RESULT_H inline void ignore_result_helper(int __attribute__((unused)) dummy, ...) { } #define IGNORE_RESULT(X) ignore_result_helper(0, (X)) #endif // IGNORE_RESULT_H april-ann-0.4.1/packages/basics/util/c_src/is_same.h000066400000000000000000000020341263004425400222550ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2015, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef IS_SAME_H #define IS_SAME_H template struct is_same { static const bool value = false; }; template struct is_same { static const bool value = true; }; #endif // IS_SAME_H april-ann-0.4.1/packages/basics/util/c_src/linear_least_squares.cc000066400000000000000000000030251263004425400252010ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ // f(x) = a + b*x // // n*sum(xi*yi) - (sum(xi)*sum(yi)) // b = -------------------------------- // n*sum(xi^2) - (sum(xi))^2 // // a = sum(yi)/n - b*(sum(xi)/n) #include "linear_least_squares.h" namespace AprilUtils { void least_squares(double x[], double y[], int numPoints, double &a, double &b) { double sum_xi=0, sum_yi=0, sum_xi_2=0, sum_xi_yi=0; for (int i=0; i #include "swap.h" #ifdef USE_ITERATOR_TAGS #include #endif namespace AprilUtils { namespace list_aux_templates{ class _true_type {}; class _false_type {}; template struct is_integer{ typedef _false_type type; }; template<> struct is_integer { typedef _true_type type; }; template<> struct is_integer { typedef _true_type type; }; template<> struct is_integer { typedef _true_type type; }; template<> struct is_integer { typedef _true_type type; }; template<> struct is_integer { typedef _true_type type; }; template<> struct is_integer { typedef _true_type type; }; template<> struct is_integer { typedef _true_type type; }; template<> struct is_integer { typedef _true_type type; }; template<> struct is_integer { typedef _true_type type; }; template<> struct is_integer{ typedef _true_type type; }; } // Be careful! It's not std::list :) // Implements Reversible Container, Front Insertion Sequence and Back Insertion Sequence template class list { // Linked-list nodes struct node { T data; node *prev; node *next; // Constructor node(): data(T()), prev(this), next(this) {} node(T t, node* p, node *n):data(t), prev(p), next(n) {} }; // Circular list implementation node sentinel; size_t list_size; void init_list() { sentinel.prev = &sentinel; sentinel.next = &sentinel; list_size = 0; } // Some template magic in order to distinguish list(iterator, iterator) from list(int, int) // in template list(InputIterator, InputIterator) public: typedef T value_type; //< The type of object, T, stored in the list. typedef T* pointer; //< Pointer to T. typedef T& reference; //< Reference to T. typedef const T& const_reference; //< Const reference to T typedef size_t size_type; //< An unsigned integral type. typedef ptrdiff_t difference_type; //< A signed integral type. // Bidirectional containers must define iterator, const_iterator AND // reverse_iterator, const_reverse_iterator. // FIXME: Equality comparison between iterator and const_iterator is broken /// Iterator used to iterate through a list. struct iterator { friend class list; //private: node *ptr; public: typedef T value_type; typedef T* pointer; typedef T& reference; typedef const T& const_reference; typedef ptrdiff_t difference_type; #ifdef USE_ITERATOR_TAGS typedef std::bidirectional_iterator_tag iterator_category; #endif iterator(): ptr(0) {} iterator(void *p): ptr(static_cast(p)) {} iterator& operator++() { // preincrement ptr = ptr->next; return *this; } iterator operator++(int) { // postincrement node *tmp = ptr; ptr = ptr->next; return iterator(tmp); } iterator& operator--() { // predecrement ptr = ptr->prev; return *this; } iterator operator--(int) { // postdecrement node *tmp = ptr; ptr = ptr->prev; return iterator(tmp); } T& operator *() const { // dereference return ptr->data; } T* operator ->() const { return &(ptr->data); } bool operator == (const iterator &i) const { return ptr == i.ptr; } bool operator != (const iterator &i) const { return ptr != i.ptr; } }; /// Const iterator used to iterate through a list. struct const_iterator { friend class list; //private: const node *ptr; const_iterator(const node *p): ptr(p) {} public: typedef T value_type; typedef const T* pointer; typedef const T& reference; typedef const T& const_reference; typedef ptrdiff_t difference_type; #ifdef USE_ITERATOR_TAGS typedef std::bidirectional_iterator_tag iterator_category; #endif const_iterator(const iterator &i): ptr(i.ptr) {} const_iterator(iterator &i): ptr(i.ptr) {} const_iterator& operator++() { // preincrement ptr = ptr->next; return *this; } const_iterator operator++(int) { // postincrement const node *tmp = ptr; ptr = ptr->next; return const_iterator(tmp); } const_iterator& operator--() { // predecrement ptr = ptr->prev; return *this; } const_iterator operator--(int) { // postdecrement node *tmp = ptr; ptr = ptr->prev; return const_iterator(tmp); } reference operator *() const { // dereference return ptr->data; } pointer operator ->() const { return &(ptr->data); } bool operator == (const const_iterator &i) const { return ptr == i.ptr; } bool operator != (const const_iterator &i) const { return ptr != i.ptr; } }; /// Iterator used to iterate backwards through a list. struct reverse_iterator { // deberia heredar de std::bidirectional_iterator friend class list; //private: iterator current; /// private constructor. we don't want reverse iterators created from iterators :) reverse_iterator(const iterator &i): current(i) {} public: typedef T value_type; typedef T* pointer; typedef T& reference; typedef const T& const_reference; typedef ptrdiff_t difference_type; #ifdef USE_ITERATOR_TAGS typedef std::bidirectional_iterator_tag iterator_category; #endif reverse_iterator(const reverse_iterator &other): current(other.current) {} reverse_iterator& operator++() { // preincrement --current; return *this; } reverse_iterator operator++(int) { // postincrement iterator tmp(current); --current; return reverse_iterator(tmp); } reverse_iterator& operator--() { // predecrement ++current; return *this; } reverse_iterator operator--(int) { // postdecrement iterator tmp(current); ++current; return reverse_iterator(tmp); } reference operator *() const { // dereference iterator tmp(current); return *(--tmp); } pointer operator ->() const { return &(operator*()); } iterator base() { return current; } bool operator == (const reverse_iterator &other) const { return current == other.current; } bool operator != (const reverse_iterator &other) const { return current != other.current; } }; /// Iterator used to iterate backwards through a list. struct const_reverse_iterator { // deberia heredar de std::bidirectional_iterator friend class list; //private: const_iterator current; /// private constructor. we don't want reverse iterators created from iterators :) const_reverse_iterator(const const_iterator &ci): current(ci) {} public: typedef T value_type; typedef const T* pointer; typedef const T& reference; typedef const T& const_reference; typedef ptrdiff_t difference_type; #ifdef USE_ITERATOR_TAGS typedef std::bidirectional_iterator_tag iterator_category; #endif const_reverse_iterator(const const_reverse_iterator &other): current(other.current) {} const_reverse_iterator& operator++() { // preincrement --current; return *this; } const_reverse_iterator operator++(int) { // postincrement const_iterator tmp(current); --current; return const_reverse_iterator(tmp); } const_reverse_iterator& operator--() { // predecrement ++current; return *this; } const_reverse_iterator operator--(int) { // postdecrement const_iterator tmp(current); ++current; return const_reverse_iterator(tmp); } reference operator *() const { // dereference iterator tmp(current); return *(--tmp); } pointer operator ->() const { return &(operator*()); } iterator base() { return current; } bool operator == (const reverse_iterator &other) const { return current == other.current; } bool operator != (const reverse_iterator &other) const { return current != other.current; } }; /// Returns an iterator pointing to the beginning of the list. iterator begin() { return iterator(sentinel.next); } /// Returns an iterator pointing to the end of the list. iterator end() { return iterator(&sentinel); } /// Returns a const iterator pointing to the beginning of the list. const_iterator begin() const { return const_iterator(sentinel.next); } /// Returns a const iterator pointing to the end of the list. const_iterator end() const { return const_iterator(&sentinel); } /// Returns a reverse iterator pointing to the beginning of the reversed list. reverse_iterator rbegin() { return reverse_iterator(end()); } /// Returns a reverse iterator pointing to the end of the reversed list. reverse_iterator rend() { return reverse_iterator(begin()); } /// Returns a const reverse iterator pointing to the beginning of the reversed list. const_reverse_iterator rbegin() const { return const_reverse_iterator(end()); } /// Returns a const reverse iterator pointing to the end of the reversed list. const_reverse_iterator rend() const { return const_reverse_iterator(begin()); } /// Returns the size of the list. This is not required to be constant time /// by the standard. However, this is NOT std::list, and we have decided to /// keep size() constant time at the expense of having linear time splices. size_type size() const { return list_size; } /// Returns the largest possible size of the list. size_type max_size() const { return size_type(-1); } /// true if the list's size is 0. bool empty() const { return (list_size==0); } /// Creates an empty list. list() { init_list(); } /// Creates a list with n elements, each of which is a copy of T(). list(size_type n) { init_list(); for (size_type i=0; i void init_dispatch(I n, I x, list_aux_templates::_true_type) { init_fill(static_cast(n), static_cast(x)); } template void init_dispatch(InputIterator f, InputIterator l, list_aux_templates::_false_type) { init_range(f,l); } void init_fill(size_type n, const_reference t) { init_list(); for (size_type i=0; i void init_range(InputIterator f, InputIterator l) { init_list(); for (; f != l; f++) { push_back(*f); } } public: template list(InputIterator f, InputIterator l) { // Check if it's an integer type. If it's integer, it's not an iterator typedef typename list_aux_templates::is_integer::type IsInteger; init_dispatch(f,l, IsInteger()); } /// The destructor. ~list() { clear(); } /// The assignment operator list &operator=(const list &l){ if (l != *this) { clear(); for (iterator i = l.begin(); i != l.end(); i++) push_back(*i); } return *this; } /// Returns the first element. /// Precondition: !empty() reference front() { return sentinel.next->data; } /// Returns the first element. /// Precondition: !empty() const_reference front() const { return sentinel.next->data; } /// Returns the last element. /// Precondition: !empty() reference back() { return sentinel.prev->data; } /// Returns the last element. /// Precondition: !empty() const_reference back() const { return sentinel.prev->data; } /// Inserts a new element at the beginning. void push_front(const_reference t) { insert(begin(), t); } /// Inserts a new element at the end. void push_back(const_reference t) { insert(end(), t); } /// Removes the first element. /// Precondition: !empty() void pop_front() { erase(begin()); } /// Removes the last element. /// Precondition: !empty() void pop_back() { erase(iterator(sentinel.prev)); } /// Swaps the contents of two lists. void swap(list &l){ node *first, *first_l; node *last, *last_l; first = sentinel.next; first_l = l.sentinel.next; last = sentinel.prev; last_l = l.sentinel.prev; AprilUtils::swap(first->prev, first_l->prev); AprilUtils::swap(last->next, last_l->next); AprilUtils::swap(sentinel.prev, l.sentinel.prev); AprilUtils::swap(sentinel.next, l.sentinel.next); AprilUtils::swap(list_size, l.list_size); } /// Inserts x before pos. /// Returns an iterator pointing to the inserted element iterator insert(iterator pos, const T& x) { node *ptr = pos.ptr; node *tmp = new node(x, ptr->prev, ptr); ptr->prev->next = tmp; ptr->prev = tmp; list_size++; return iterator(tmp); } private: template void insert_dispatch(iterator pos, I n, I x, list_aux_templates::_true_type) { insert_copies(pos, static_cast(n), static_cast(x)); } template void insert_dispatch(iterator pos, InputIterator f, InputIterator l, list_aux_templates::_false_type) { insert_range(pos, f,l); } /// Inserts n copies of x before pos void insert_copies(iterator pos, size_type n, const_reference x) { for (size_type i = 0; i < n; i++) insert(pos, x); } /// Inserts the range [f, l) before pos template void insert_range(iterator pos, InputIterator f, InputIterator l) { for (InputIterator i = f; i != l; i++) insert(pos, *i); } public: /// Inserts the range [f, l) before pos. template void insert(iterator pos, InputIterator f, InputIterator l) { typedef typename list_aux_templates::is_integer::type IsInteger; insert_dispatch(pos, f, l, IsInteger()); } /// Inserts n copies of x before pos. void insert(iterator pos, size_type n, const T& x) { insert_copies(pos, n, x); } /// Erases the element at position pos. /// Returns an iterator to the element immediately following the one that /// was erased. /// Precondition: pos must be a dereferenceable iterator iterator erase(iterator pos) { node *ptr = pos.ptr; node *next = ptr->next; ptr->prev->next = ptr->next; ptr->next->prev = ptr->prev; delete ptr; list_size--; return iterator(next); } /// Erases the elements in range [first, last) /// Returns last iterator erase(iterator first, iterator last) { while(first != last) first = erase(first); return last; } /// Erases all of the elements. void clear() { erase(begin(), end()); } /// Inserts or erases elements at the end such that the size becomes n. void resize(size_t n, T x=T()) { if (list_size < n) { while (list_size < n) { push_back(x); } } else if (list_size > n) { while (list_size > n) { pop_back(); } } list_size = n; } /// position must be a valid iterator in *this, and x must be a list that /// is distinct from *this. (That is, it is required that &x != this.) All of /// the elements of x are inserted before position and removed from x. All /// iterators remain valid, including iterators that point to elements of x. /// NOTE: This function is linear time in order to keep size() constant time void splice(iterator position, list& x) { splice(position, x, x.begin(), x.end()); } /// position must be a valid iterator in *this, and i must be a /// dereferenceable iterator in x. Splice moves the element pointed to by i /// from x to *this, inserting it before position. All iterators remain /// valid, including iterators that point to elements of x. If position /// == i or position == ++i, this function is a null operation. This function /// is linear time in order to keep size() constant time. void splice(iterator position, list& x, iterator i) { iterator first,last; first = i; last = ++i; splice(position, x, first, last); } /// position must be a valid iterator in *this, and [first, last) must be /// a valid range in x. position may not be an iterator in the range [first, /// last). Splice moves the elements in [first, last) from x to *this, /// inserting them before position. All iterators remain valid, including /// iterators that point to elements of x. [3] This function is linear /// time in order to keep size() constant time. void splice(iterator position, list& x, iterator f, iterator l) { node *pos = position.ptr; node *first = f.ptr; node *last = l.ptr->prev; // we're supposed to check if *this and x use the same allocators, // but this is not the STL and we don't have allocators, so x is not used // (iterators are sufficient) int count=0; for (iterator i = f; i != l; i++) ++count; x.list_size -= count; this->list_size += count; first->prev->next = last->next; last->next->prev = first->prev; first->prev = pos->prev; last->next = pos; pos->prev->next = first; pos->prev = last; } /// Removes all elements that compare equal to val. The relative order of /// elements that are not removed is unchanged, and iterators to elements /// that are not removed remain valid. This function is linear time: it /// performs exactly size() comparisons for equality. void remove(const T& val) { iterator i = begin(); while(i != end()) { if (*i == val) i = erase(i); else i++; } } /// Removes all elements *i such that p(*i) is true. The relative order of /// elements that are not removed is unchanged, and iterators to elements /// that are not removed remain valid. This function is linear time: it /// performs exactly size() applications of p. template void remove_if(Predicate p) { iterator i = begin(); while(i != end()) { if (p(*i)) i = erase(i); else i++; } } /// Removes all but the first element in every consecutive group of equal /// elements. The relative order of elements that are not removed is /// unchanged, and iterators to elements that are not removed remain valid. /// This function is linear time: it performs exactly size() - 1 comparisons /// for equality. void unique(); /// Removes all but the first element in every consecutive group of /// equivalent elements, where two elements *i and *j are considered /// equivalent if p(*i, *j) is true. The relative order of elements that are /// not removed is unchanged, and iterators to elements that are not removed /// remain valid. This function is linear time: it performs exactly size() - /// 1 comparisons for equality. template void unique(BinaryPredicate p); /// Both *this and x must be sorted according to operator<, and they must /// be distinct. (That is, it is required that &x != this.) This function /// removes all of x's elements and inserts them in order into *this. The /// merge is stable; that is, if an element from *this is equivalent to one /// from x, then the element from *this will precede the one from x. All /// iterators to elements in *this and x remain valid. This function is /// linear time: it performs at most size() + x.size() - 1 comparisons. void merge(list& x); /// Comp must be a comparison function that induces a strict weak ordering /// (as defined in the LessThan Comparable requirements) on objects of type /// T, and both *this and x must be sorted according to that ordering. The /// lists x and *this must be distinct. (That is, it is required that &x != /// this.) This function removes all of x's elements and inserts them in /// order into *this. The merge is stable; that is, if an element from *this /// is equivalent to one from x, then the element from *this will precede the /// one from x. All iterators to elements in *this and x remain valid. This /// function is linear time: it performs at most size() + x.size() - 1 /// applications of Comp. template void merge(list& x, BinaryPredicate Comp); /// Reverses the order of elements in the list. All iterators remain valid /// and continue to point to the same elements. This function is linear /// time. void reverse(); /// Sorts *this according to operator<. The sort is stable, that is, the /// relative order of equivalent elements is preserved. All iterators remain /// valid and continue to point to the same elements. [6] The number of /// comparisons is approximately N log N, where N is the list's size. void sort(); /// Comp must be a comparison function that induces a strict weak ordering /// (as defined in the LessThan Comparable requirements on objects of type T. /// This function sorts the list *this according to Comp. The sort is stable, /// that is, the relative order of equivalent elements is preserved. All /// iterators remain valid and continue to point to the same elements. [6] /// The number of comparisons is approximately N log N, where N is the list's /// size. template void sort(BinaryPredicate comp); }; } // namespace AprilUtils #endif april-ann-0.4.1/packages/basics/util/c_src/logbase.h000066400000000000000000000021061263004425400222510ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LOGBASE_H #define LOGBASE_H #ifdef ASSERT_LOGBASE_ZERO #include "logbase_assert.h" #else #ifdef ABSOLUTE_ZERO_LOGBASE #include "logbase_zero.h" #else #include "logbase_standard.h" #endif #endif #endif // LOGBASE_H april-ann-0.4.1/packages/basics/util/c_src/logbase_assert.h000066400000000000000000000344471263004425400236470ustar00rootroot00000000000000#ifdef ASSERT_LOGBASE_ZERO /* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LOGBASE_ASSERT_H #define LOGBASE_ASSERT_H #include "april_assert.h" #include #include namespace AprilUtils { // Esta clase representa valores numéricos en base logarítmica. // Por tanto, sólo tiene sentido para representar números >0 // aunque el 0 se aproxima por un valor muy cercano. class log_double; // forward declaration class log_float { float raw_value; // nota: el minimo numero float no denormal es 1.2e-38 static const float floatnearzero = 1e-37; static const float rawscorenearzero = -99; static const float rawscorezero = -1e12; static const float rawscoreone = 0; public: log_float(float x) : raw_value(x) {} log_float() : raw_value(rawscorezero) {} static log_float zero() { return log_float(rawscorezero); } static log_float one() { return log_float(rawscoreone); } static log_float from_float(float value) { return log_float((value < floatnearzero) ? rawscorezero : ::log(value)); } float to_float() const { return expf(raw_value); } double to_double() const { return exp((double)raw_value); } float log() const { return raw_value; } log_float raise_to(float exponent) { float aux = raw_value*exponent; april_assert(aux >= rawscorezero); return log_float(aux); } // arithmetic operations friend log_float operator + (const log_float &x, const log_float &y); friend log_float operator * (const log_float &x, const log_float &y); friend log_float operator / (const log_float &x, const log_float &y); friend log_float operator - (const log_float &x, const log_float &y); log_float operator += (const log_float &y) { *this = *this + y; april_assert(raw_value >= rawscorezero); return *this; } log_float operator += (const log_double &y); log_float operator *= (const log_float &y) { *this = *this * y; april_assert(raw_value >= rawscorezero); return *this; } log_float operator *= (const log_double &y); log_float operator /= (const log_float &y) { *this = *this / y; april_assert(raw_value >= rawscorezero); return *this; } log_float operator /= (const log_double &y); log_float operator -= (const log_float &y) { *this = *this - y; april_assert(raw_value >= rawscorezero); return *this; } log_float operator -= (const log_double &y); // comparison operations friend bool operator == (const log_float &x, const log_float &y); friend bool operator != (const log_float &x, const log_float &y); friend bool operator >= (const log_float &x, const log_float &y); friend bool operator <= (const log_float &x, const log_float &y); friend bool operator > (const log_float &x, const log_float &y); friend bool operator < (const log_float &x, const log_float &y); // conversion operator float() const { return raw_value; } operator double() const { return (double)raw_value; } operator unsigned int() const { return (unsigned int)(raw_value); } // assignment log_float &operator = (float &value) { raw_value = value; april_assert(raw_value >= rawscorezero); return *this; } log_float &operator = (double &value) { raw_value = value; april_assert(raw_value >= rawscorezero); return *this; } log_float &operator = (const log_double &value); }; class log_double { friend class log_float; double raw_value; // nota: el minimo numero float no denormal es 1.2e-38 static const double doublenearzero = 1e-37; static const double rawscorenearzero = -85; static const double rawscorezero = -1e8; static const double rawscoreone = 0; public: log_double(double x) : raw_value(x) {} log_double(const log_float& f): raw_value(double(f)) {} log_double() : raw_value(rawscorezero) {} static log_double from_double(double value) { return log_double((value < doublenearzero) ? rawscorezero : ::log(value)); } static log_double zero() { return log_double(rawscorezero); } static log_double one() { return log_double(rawscoreone); } double to_double() const { return exp(raw_value); } float to_float() const { return expf((float)raw_value); } double log() const { return raw_value; } // arithmetic operations log_double raise_to(double exponent) { double aux = raw_value*exponent; april_assert(aux >= rawscorezero); return log_double(aux); } friend log_double operator + (const log_double &x, const log_double &y); friend log_double operator * (const log_double &x, const log_double &y); friend log_double operator / (const log_double &x, const log_double &y); friend log_double operator - (const log_double &x, const log_double &y); log_double operator += (const log_double &y) { *this = *this * y; april_assert(raw_value >= rawscorezero); return *this; } log_double operator *= (const log_double &y) { *this = *this * y; april_assert(raw_value >= rawscorezero); return *this; } log_double operator /= (const log_double &y) { *this = *this / y; april_assert(raw_value >= rawscorezero); return *this; } log_double operator -= (const log_double &y) { *this = *this - y; april_assert(raw_value >= rawscorezero); return *this; } // comparison operations friend bool operator == (const log_double &x, const log_double &y); friend bool operator != (const log_double &x, const log_double &y); friend bool operator >= (const log_double &x, const log_double &y); friend bool operator <= (const log_double &x, const log_double &y); friend bool operator > (const log_double &x, const log_double &y); friend bool operator < (const log_double &x, const log_double &y); /* // conversion operator double() const { return raw_value; } operator float() const { return (float)raw_value; } operator log_float() const { return log_float((float)raw_value); } */ // assignment log_double &operator = (double &value) { raw_value = value; april_assert(raw_value >= rawscorezero); return *this; } log_double &operator = (float &value) { raw_value = (double)value; april_assert(raw_value >= rawscorezero); return *this; } log_double &operator = (log_float &value) { raw_value = (float)value; april_assert(raw_value >= rawscorezero); return *this; } }; //--------- // arithmetic operations log_float operator + (const log_float &x, const log_float &y); log_float operator - (const log_float &x, const log_float &y); log_float operator * (const log_float &x, const log_float &y); log_float operator / (const log_float &x, const log_float &y); // comparison operations bool operator == (const log_float &x, const log_float &y); bool operator != (const log_float &x, const log_float &y); bool operator >= (const log_float &x, const log_float &y); bool operator <= (const log_float &x, const log_float &y); bool operator > (const log_float &x, const log_float &y); bool operator < (const log_float &x, const log_float &y); // arithmetic operations log_double operator + (const log_double &x, const log_double &y); log_double operator - (const log_double &x, const log_double &y); log_double operator * (const log_double &x, const log_double &y); log_double operator / (const log_double &x, const log_double &y); // comparison operations bool operator == (const log_double &x, const log_double &y); bool operator != (const log_double &x, const log_double &y); bool operator >= (const log_double &x, const log_double &y); bool operator <= (const log_double &x, const log_double &y); bool operator > (const log_double &x, const log_double &y); bool operator < (const log_double &x, const log_double &y); //--------------------------------------------------------------- inline log_float& log_float::operator = (const log_double &value) { raw_value = (float)value.raw_value; april_assert(raw_value >= rawscorezero); return *this; } // arithmetic operations inline float logadd1(float x) { // invocamos esta función siempre para x<=0 return log1p(exp(x)); } inline float log1sub(float x) { return log1p(-exp(x)); } inline log_float operator + (const log_float &x, const log_float &y) { log_float result = (x.raw_value > y.raw_value) ? log_float(x.raw_value + logadd1(y.raw_value - x.raw_value)) : log_float(y.raw_value + logadd1(x.raw_value - y.raw_value)); assert (result >= log_float::zero()); return result; } inline log_float operator - (const log_float &x, const log_float &y) { assert (x.raw_value >= y.raw_value); log_float result = log_float(x.raw_value + log1sub(y.raw_value - x.raw_value)); assert (result >= log_float::zero()); return result; } inline log_float operator * (const log_float &x, const log_float &y) { log_float result = log_float(x.raw_value + y.raw_value); assert (result >= log_float::zero()); return result; } inline log_float operator / (const log_float &x, const log_float &y) { log_float result = log_float(x.raw_value - y.raw_value); assert (result >= log_float::zero()); return result; } // comparison operations inline bool operator == (const log_float &x, const log_float &y) { return (x.raw_value == y.raw_value); } inline bool operator != (const log_float &x, const log_float &y) { return (x.raw_value != y.raw_value); } inline bool operator <= (const log_float &x, const log_float &y) { return (x.raw_value <= y.raw_value); } inline bool operator >= (const log_float &x, const log_float &y) { return (x.raw_value >= y.raw_value); } inline bool operator < (const log_float &x, const log_float &y) { return (x.raw_value < y.raw_value); } inline bool operator > (const log_float &x, const log_float &y) { return (x.raw_value > y.raw_value); } inline double logadd1(double x) { return log1p(exp(x)); } inline double log1sub(double x) { return log1p(-exp(x)); } inline log_double operator + (const log_double &x, const log_double &y) { log_double result = (x.raw_value > y.raw_value) ? log_double(x.raw_value + logadd1(y.raw_value - x.raw_value)) : log_double(y.raw_value + logadd1(x.raw_value - y.raw_value)); april_assert(result >= log_float::zero()); return result; } inline log_double operator - (const log_double &x, const log_double &y) { if (x.raw_value < y.raw_value) { // TODO: report error } log_double result = log_double(x.raw_value + log1sub(y.raw_value - x.raw_value)); april_assert(result >= log_float::zero()); return result; } inline log_double operator * (const log_double &x, const log_double &y) { log_double result = log_double(x.raw_value + y.raw_value); april_assert(result >= log_float::zero()); return result; } inline log_double operator / (const log_double &x, const log_double &y) { log_double result = log_double(x.raw_value - y.raw_value); april_assert(result >= log_float::zero()); return result; } // comparison operations inline bool operator == (const log_double &x, const log_double &y) { return (x.raw_value == y.raw_value); } inline bool operator != (const log_double &x, const log_double &y) { return (x.raw_value != y.raw_value); } inline bool operator <= (const log_double &x, const log_double &y) { return (x.raw_value <= y.raw_value); } inline bool operator >= (const log_double &x, const log_double &y) { return (x.raw_value >= y.raw_value); } inline bool operator < (const log_double &x, const log_double &y) { return (x.raw_value < y.raw_value); } inline bool operator > (const log_double &x, const log_double &y) { return (x.raw_value > y.raw_value); } // special cases: inline log_float log_float::operator += (const log_double &y) { *this = log_double(*this) + y; april_assert(raw_value >= rawscorezero); return *this; } inline log_float log_float::operator *= (const log_double &y) { *this = log_double(*this) * y; april_assert(raw_value >= rawscorezero); return *this; } inline log_float log_float::operator /= (const log_double &y) { *this = log_double(*this) / y; april_assert(raw_value >= rawscorezero); return *this; } inline log_float log_float::operator -= (const log_double &y) { *this = log_double(*this) - y; april_assert(raw_value >= rawscorezero); return *this; } } // namespace AprilUtils #endif // LOGBASE_ASSERT_H #endif april-ann-0.4.1/packages/basics/util/c_src/logbase_standard.cc000066400000000000000000000024601263004425400242720ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "logbase_standard.h" namespace AprilUtils { const float log_float::floatnearzero = 1e-37; const float log_float::rawscorenearzero = -99; const float log_float::rawscorezero = -1e12; const float log_float::rawscoreone = 0; const double log_double::doublenearzero = 1e-37; const double log_double::rawscorenearzero = -85; const double log_double::rawscorezero = -1e8; const double log_double::rawscoreone = 0; } april-ann-0.4.1/packages/basics/util/c_src/logbase_standard.h000066400000000000000000000313561263004425400241420ustar00rootroot00000000000000#if !defined(ASSERT_LOGBASE_ZERO) && !defined(ABSOLUTE_ZERO_LOGBASE) /* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LOGBASE_STANDARD_H #define LOGBASE_STANDARD_H #include #include namespace AprilUtils { // Esta clase representa valores numéricos en base logarítmica. // Por tanto, sólo tiene sentido para representar números >0 // aunque el 0 se aproxima por un valor muy cercano. class log_double; // forward declaration class log_float { float raw_value; // nota: el minimo numero float no denormal es 1.2e-38 static const float floatnearzero; static const float rawscorenearzero; static const float rawscorezero; static const float rawscoreone; public: log_float(float x) : raw_value(x) {} log_float() : raw_value(rawscorezero) {} static log_float zero() { return log_float(rawscorezero); } static log_float one() { return log_float(rawscoreone); } static log_float from_float(float value) { return log_float((value < floatnearzero) ? rawscorezero : ::log(value)); } static log_float from_double(double value) { return log_float((value < floatnearzero) ? rawscorezero : ::log(value)); } float to_float() const { return expf(raw_value); } double to_double() const { return exp((double)raw_value); } float log() const { return raw_value; } log_float raise_to(float exponent) const { return log_float(raw_value*exponent); } // arithmetic operations friend log_float operator + (const log_float &x, const log_float &y); friend log_float operator * (const log_float &x, const log_float &y); friend log_float operator / (const log_float &x, const log_float &y); friend log_float operator - (const log_float &x, const log_float &y); log_float operator += (const log_float &y) { return *this = *this + y; } log_float operator += (const log_double &y); log_float operator *= (const log_float &y) { return *this = *this * y; } log_float operator *= (const log_double &y); log_float operator /= (const log_float &y) { return *this = *this / y; } log_float operator /= (const log_double &y); log_float operator -= (const log_float &y) { return *this = *this - y; } log_float operator -= (const log_double &y); // comparison operations friend bool operator == (const log_float &x, const log_float &y); friend bool operator != (const log_float &x, const log_float &y); friend bool operator >= (const log_float &x, const log_float &y); friend bool operator <= (const log_float &x, const log_float &y); friend bool operator > (const log_float &x, const log_float &y); friend bool operator < (const log_float &x, const log_float &y); // conversion operator float() const { return raw_value; } operator double() const { return (double)raw_value; } operator unsigned int() const { return (unsigned int)(raw_value); } // assignment log_float &operator = (float &value) { raw_value = value; return *this; } log_float &operator = (double &value) { raw_value = value; return *this; } log_float &operator = (const log_double &value); }; class log_double { friend class log_float; double raw_value; // nota: el minimo numero float no denormal es 1.2e-38 static const double doublenearzero; static const double rawscorenearzero; static const double rawscorezero; static const double rawscoreone; public: log_double(double x) : raw_value(x) {} log_double(const log_float& f): raw_value(double(f)) {} log_double() : raw_value(rawscorezero) {} static log_double from_double(double value) { return log_double((value < doublenearzero) ? rawscorezero : ::log(value)); } static log_double zero() { return log_double(rawscorezero); } static log_double one() { return log_double(rawscoreone); } double to_double() const { return exp(raw_value); } float to_float() const { return expf((float)raw_value); } double log() const { return raw_value; } log_double raise_to(double exponent) { return log_double(raw_value*exponent); } // arithmetic operations friend log_double operator + (const log_double &x, const log_double &y); friend log_double operator * (const log_double &x, const log_double &y); friend log_double operator / (const log_double &x, const log_double &y); friend log_double operator - (const log_double &x, const log_double &y); log_double operator += (const log_double &y) { return *this = *this + y; } log_double operator *= (const log_double &y) { return *this = *this * y; } log_double operator /= (const log_double &y) { return *this = *this / y; } log_double operator -= (const log_double &y) { return *this = *this - y; } // comparison operations friend bool operator == (const log_double &x, const log_double &y); friend bool operator != (const log_double &x, const log_double &y); friend bool operator >= (const log_double &x, const log_double &y); friend bool operator <= (const log_double &x, const log_double &y); friend bool operator > (const log_double &x, const log_double &y); friend bool operator < (const log_double &x, const log_double &y); /* // conversion operator double() const { return raw_value; } operator float() const { return (float)raw_value; } operator log_float() const { return log_float((float)raw_value); } */ // assignment log_double &operator = (double &value) { raw_value = value; return *this; } log_double &operator = (float &value) { raw_value = (double)value; return *this; } log_double &operator = (log_float &value) { raw_value = (float)value; return *this; } }; //--------- // arithmetic operations log_float operator + (const log_float &x, const log_float &y); log_float operator - (const log_float &x, const log_float &y); log_float operator * (const log_float &x, const log_float &y); log_float operator / (const log_float &x, const log_float &y); // comparison operations bool operator == (const log_float &x, const log_float &y); bool operator != (const log_float &x, const log_float &y); bool operator >= (const log_float &x, const log_float &y); bool operator <= (const log_float &x, const log_float &y); bool operator > (const log_float &x, const log_float &y); bool operator < (const log_float &x, const log_float &y); // arithmetic operations log_double operator + (const log_double &x, const log_double &y); log_double operator - (const log_double &x, const log_double &y); log_double operator * (const log_double &x, const log_double &y); log_double operator / (const log_double &x, const log_double &y); // comparison operations bool operator == (const log_double &x, const log_double &y); bool operator != (const log_double &x, const log_double &y); bool operator >= (const log_double &x, const log_double &y); bool operator <= (const log_double &x, const log_double &y); bool operator > (const log_double &x, const log_double &y); bool operator < (const log_double &x, const log_double &y); //--------------------------------------------------------------- inline log_float& log_float::operator = (const log_double &value) { raw_value = (float)value.raw_value; return *this; } // arithmetic operations inline float logadd1(float x) { // invocamos esta función siempre para x<=0 return log1p(exp(x)); } inline float log1sub(float x) { return log1p(-exp(x)); } inline log_float operator + (const log_float &x, const log_float &y) { return (x.raw_value > y.raw_value) ? log_float(x.raw_value + logadd1(y.raw_value - x.raw_value)) : log_float(y.raw_value + logadd1(x.raw_value - y.raw_value)); } inline log_float operator - (const log_float &x, const log_float &y) { if (x.raw_value < y.raw_value) { // TODO: report error } return log_float(x.raw_value + log1sub(y.raw_value - x.raw_value)); } inline log_float operator * (const log_float &x, const log_float &y) { return log_float(x.raw_value + y.raw_value); } inline log_float operator / (const log_float &x, const log_float &y) { return log_float(x.raw_value - y.raw_value); } // comparison operations inline bool operator == (const log_float &x, const log_float &y) { return (x.raw_value == y.raw_value); } inline bool operator != (const log_float &x, const log_float &y) { return (x.raw_value != y.raw_value); } inline bool operator <= (const log_float &x, const log_float &y) { return (x.raw_value <= y.raw_value); } inline bool operator >= (const log_float &x, const log_float &y) { return (x.raw_value >= y.raw_value); } inline bool operator < (const log_float &x, const log_float &y) { return (x.raw_value < y.raw_value); } inline bool operator > (const log_float &x, const log_float &y) { return (x.raw_value > y.raw_value); } inline double logadd1(double x) { return log1p(exp(x)); } inline double log1sub(double x) { return log1p(-exp(x)); } inline log_double operator + (const log_double &x, const log_double &y) { return (x.raw_value > y.raw_value) ? log_double(x.raw_value + logadd1(y.raw_value - x.raw_value)) : log_double(y.raw_value + logadd1(x.raw_value - y.raw_value)); } inline log_double operator - (const log_double &x, const log_double &y) { if (x.raw_value < y.raw_value) { // TODO: report error } return log_double(x.raw_value + log1sub(y.raw_value - x.raw_value)); } inline log_double operator * (const log_double &x, const log_double &y) { return log_double(x.raw_value + y.raw_value); } inline log_double operator / (const log_double &x, const log_double &y) { return log_double(x.raw_value - y.raw_value); } // comparison operations inline bool operator == (const log_double &x, const log_double &y) { return (x.raw_value == y.raw_value); } inline bool operator != (const log_double &x, const log_double &y) { return (x.raw_value != y.raw_value); } inline bool operator <= (const log_double &x, const log_double &y) { return (x.raw_value <= y.raw_value); } inline bool operator >= (const log_double &x, const log_double &y) { return (x.raw_value >= y.raw_value); } inline bool operator < (const log_double &x, const log_double &y) { return (x.raw_value < y.raw_value); } inline bool operator > (const log_double &x, const log_double &y) { return (x.raw_value > y.raw_value); } // special cases: inline log_float log_float::operator += (const log_double &y) { return *this = log_double(*this) + y; } inline log_float log_float::operator *= (const log_double &y) { return *this = log_double(*this) * y; } inline log_float log_float::operator /= (const log_double &y) { return *this = log_double(*this) / y; } inline log_float log_float::operator -= (const log_double &y) { return *this = log_double(*this) - y; } } // namespace AprilUtils #endif // LOGBASE_STANDARD_H #endif april-ann-0.4.1/packages/basics/util/c_src/logbase_zero.h000066400000000000000000000354421263004425400233210ustar00rootroot00000000000000#ifdef ABSOLUTE_ZERO_LOGBASE /* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LOGBASE_ZERO_H #define LOGBASE_ZERO_H #include #include namespace AprilUtils { // Esta clase representa valores numéricos en base logarítmica. // Por tanto, sólo tiene sentido para representar números >0 // aunque el 0 se aproxima por un valor muy cercano. class log_double; // forward declaration class log_float { float raw_value; // nota: el minimo numero float no denormal es 1.2e-38 static const float floatnearzero = 1e-37; static const float rawscorenearzero = -99; static const float rawscorezero = -1e12; static const float rawscoreone = 0; public: log_float(float x) : raw_value(x) {} log_float() : raw_value(rawscorezero) {} static log_float zero() { return log_float(rawscorezero); } static log_float one() { return log_float(rawscoreone); } static log_float from_float(float value) { return log_float((value < floatnearzero) ? rawscorezero : ::log(value)); } float to_float() const { return expf(raw_value); } double to_double() const { return exp((double)raw_value); } float log() const { return raw_value; } log_float raise_to(float exponent) { float aux = raw_value*exponent; if (aux <= rawscorezero) aux = rawscorezero; return log_float(aux); } // arithmetic operations friend log_float operator + (const log_float &x, const log_float &y); friend log_float operator * (const log_float &x, const log_float &y); friend log_float operator / (const log_float &x, const log_float &y); friend log_float operator - (const log_float &x, const log_float &y); log_float operator += (const log_float &y) { *this = *this + y; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } log_float operator += (const log_double &y); log_float operator *= (const log_float &y) { *this = *this * y; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } log_float operator *= (const log_double &y); log_float operator /= (const log_float &y) { *this = *this / y; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } log_float operator /= (const log_double &y); log_float operator -= (const log_float &y) { *this = *this - y; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } log_float operator -= (const log_double &y); // comparison operations friend bool operator == (const log_float &x, const log_float &y); friend bool operator != (const log_float &x, const log_float &y); friend bool operator >= (const log_float &x, const log_float &y); friend bool operator <= (const log_float &x, const log_float &y); friend bool operator > (const log_float &x, const log_float &y); friend bool operator < (const log_float &x, const log_float &y); // conversion operator float() const { return raw_value; } operator double() const { return (double)raw_value; } operator unsigned int() const { return (unsigned int)(raw_value); } // assignment log_float &operator = (float &value) { raw_value = value; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } log_float &operator = (double &value) { raw_value = value; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } log_float &operator = (const log_double &value); }; class log_double { friend class log_float; double raw_value; // nota: el minimo numero float no denormal es 1.2e-38 static const double doublenearzero = 1e-37; static const double rawscorenearzero = -85; static const double rawscorezero = -1e8; static const double rawscoreone = 0; public: log_double(double x) : raw_value(x) {} log_double(const log_float& f): raw_value(double(f)) {} log_double() : raw_value(rawscorezero) {} static log_double from_double(double value) { return log_double((value < doublenearzero) ? rawscorezero : ::log(value)); } static log_double zero() { return log_double(rawscorezero); } static log_double one() { return log_double(rawscoreone); } double to_double() const { return exp(raw_value); } float to_float() const { return expf((float)raw_value); } double log() const { return raw_value; } log_double raise_to(double exponent) { double aux = raw_value*exponent; if (aux <= rawscorezero) aux = rawscorezero; return log_double(aux); } // arithmetic operations friend log_double operator + (const log_double &x, const log_double &y); friend log_double operator * (const log_double &x, const log_double &y); friend log_double operator / (const log_double &x, const log_double &y); friend log_double operator - (const log_double &x, const log_double &y); log_double operator += (const log_double &y) { *this = *this * y; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } log_double operator *= (const log_double &y) { *this = *this * y; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } log_double operator /= (const log_double &y) { *this = *this / y; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } log_double operator -= (const log_double &y) { *this = *this - y; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } // comparison operations friend bool operator == (const log_double &x, const log_double &y); friend bool operator != (const log_double &x, const log_double &y); friend bool operator >= (const log_double &x, const log_double &y); friend bool operator <= (const log_double &x, const log_double &y); friend bool operator > (const log_double &x, const log_double &y); friend bool operator < (const log_double &x, const log_double &y); /* // conversion operator double() const { return raw_value; } operator float() const { return (float)raw_value; } operator log_float() const { return log_float((float)raw_value); } */ // assignment log_double &operator = (double &value) { raw_value = value; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } log_double &operator = (float &value) { raw_value = (double)value; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } log_double &operator = (log_float &value) { raw_value = (float)value; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } }; //--------- // arithmetic operations log_float operator + (const log_float &x, const log_float &y); log_float operator - (const log_float &x, const log_float &y); log_float operator * (const log_float &x, const log_float &y); log_float operator / (const log_float &x, const log_float &y); // comparison operations bool operator == (const log_float &x, const log_float &y); bool operator != (const log_float &x, const log_float &y); bool operator >= (const log_float &x, const log_float &y); bool operator <= (const log_float &x, const log_float &y); bool operator > (const log_float &x, const log_float &y); bool operator < (const log_float &x, const log_float &y); // arithmetic operations log_double operator + (const log_double &x, const log_double &y); log_double operator - (const log_double &x, const log_double &y); log_double operator * (const log_double &x, const log_double &y); log_double operator / (const log_double &x, const log_double &y); // comparison operations bool operator == (const log_double &x, const log_double &y); bool operator != (const log_double &x, const log_double &y); bool operator >= (const log_double &x, const log_double &y); bool operator <= (const log_double &x, const log_double &y); bool operator > (const log_double &x, const log_double &y); bool operator < (const log_double &x, const log_double &y); //--------------------------------------------------------------- inline log_float& log_float::operator = (const log_double &value) { raw_value = (float)value.raw_value; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } // arithmetic operations inline float logadd1(float x) { // invocamos esta función siempre para x<=0 return log1p(exp(x)); } inline float log1sub(float x) { return log1p(-exp(x)); } inline log_float operator + (const log_float &x, const log_float &y) { log_float result = (x.raw_value > y.raw_value) ? log_float(x.raw_value + logadd1(y.raw_value - x.raw_value)) : log_float(y.raw_value + logadd1(x.raw_value - y.raw_value)); return (result <= log_float::zero()) ? log_float::zero() : result; } inline log_float operator - (const log_float &x, const log_float &y) { if (x.raw_value < y.raw_value) { // TODO: report error } log_float result = log_float(x.raw_value + log1sub(y.raw_value - x.raw_value)); return (result <= log_float::zero()) ? log_float::zero() : result; } inline log_float operator * (const log_float &x, const log_float &y) { log_float result = log_float(x.raw_value + y.raw_value); return (result <= log_float::zero()) ? log_float::zero() : result; } inline log_float operator / (const log_float &x, const log_float &y) { log_float result = log_float(x.raw_value - y.raw_value); return (result <= log_float::zero()) ? log_float::zero() : result; } // comparison operations inline bool operator == (const log_float &x, const log_float &y) { return (x.raw_value == y.raw_value); } inline bool operator != (const log_float &x, const log_float &y) { return (x.raw_value != y.raw_value); } inline bool operator <= (const log_float &x, const log_float &y) { return (x.raw_value <= y.raw_value); } inline bool operator >= (const log_float &x, const log_float &y) { return (x.raw_value >= y.raw_value); } inline bool operator < (const log_float &x, const log_float &y) { return (x.raw_value < y.raw_value); } inline bool operator > (const log_float &x, const log_float &y) { return (x.raw_value > y.raw_value); } inline double logadd1(double x) { return log1p(exp(x)); } inline double log1sub(double x) { return log1p(-exp(x)); } inline log_double operator + (const log_double &x, const log_double &y) { log_double result = (x.raw_value > y.raw_value) ? log_double(x.raw_value + logadd1(y.raw_value - x.raw_value)) : log_double(y.raw_value + logadd1(x.raw_value - y.raw_value)); return (result <= log_float::zero()) ? log_float::zero() : result; } inline log_double operator - (const log_double &x, const log_double &y) { if (x.raw_value < y.raw_value) { // TODO: report error } log_double result = log_double(x.raw_value + log1sub(y.raw_value - x.raw_value)); return (result <= log_float::zero()) ? log_float::zero() : result; } inline log_double operator * (const log_double &x, const log_double &y) { log_double result = log_double(x.raw_value + y.raw_value); return (result <= log_float::zero()) ? log_float::zero() : result; } inline log_double operator / (const log_double &x, const log_double &y) { log_double result = log_double(x.raw_value - y.raw_value); return (result <= log_float::zero()) ? log_float::zero() : result; } // comparison operations inline bool operator == (const log_double &x, const log_double &y) { return (x.raw_value == y.raw_value); } inline bool operator != (const log_double &x, const log_double &y) { return (x.raw_value != y.raw_value); } inline bool operator <= (const log_double &x, const log_double &y) { return (x.raw_value <= y.raw_value); } inline bool operator >= (const log_double &x, const log_double &y) { return (x.raw_value >= y.raw_value); } inline bool operator < (const log_double &x, const log_double &y) { return (x.raw_value < y.raw_value); } inline bool operator > (const log_double &x, const log_double &y) { return (x.raw_value > y.raw_value); } // special cases: inline log_float log_float::operator += (const log_double &y) { *this = log_double(*this) + y; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } inline log_float log_float::operator *= (const log_double &y) { *this = log_double(*this) * y; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } inline log_float log_float::operator /= (const log_double &y) { *this = log_double(*this) / y; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } inline log_float log_float::operator -= (const log_double &y) { *this = log_double(*this) - y; if (raw_value <= rawscorezero) raw_value = rawscorezero; return *this; } } // namespace AprilUtils #endif // LOGBASE_ZERO_H #endif april-ann-0.4.1/packages/basics/util/c_src/lua_table.cc000066400000000000000000000213641263004425400227320ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ extern "C" { #include "lauxlib.h" #include "lualib.h" #include "lua.h" } #include "lua_table.h" namespace AprilUtils { LuaTable::LuaTable(lua_State *L) { lua_newtable(L); init(L, -1); lua_pop(L, 1); } LuaTable::LuaTable(lua_State *L, int i) { init(L, i); } LuaTable::LuaTable(const LuaTable &other) { int abspos; int pos = other.checkAndGetRef(abspos); if (pos != 0) { init(other.L, pos); other.popRef(pos); } } LuaTable::~LuaTable() { luaL_unref(L, LUA_REGISTRYINDEX, ref); if (absindex != 0) { ERROR_EXIT(128, "You need to call LuaTable::unlock() method\n"); } } bool LuaTable::empty() const { int pos, abspos; bool result; if ((pos=checkAndGetRef(abspos)) == 0) { result = true; } else { lua_pushnil(L); if (lua_next(L, abspos)) { lua_pop(L, 2); result = false; } else { result = true; } } popRef(pos); return result; } size_t LuaTable::length() const { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) ERROR_EXIT(128, "Invalid reference\n"); int len = luaL_len(L, pos); popRef(pos); return static_cast(len); } LuaTable &LuaTable::operator=(const LuaTable &other) { luaL_unref(L, LUA_REGISTRYINDEX, ref); int abspos; int pos = other.checkAndGetRef(abspos); init(other.L, pos); other.popRef(pos); return *this; } void LuaTable::init(lua_State *L, int i) { this->L = L; this->absindex = 0; if (lua_isnil(L,i) || lua_type(L,i) == LUA_TNONE) ref = LUA_NOREF; else { lua_pushvalue(L,i); if (!lua_istable(L,-1)) { ERROR_EXIT1(128,"Expected a table parameter at pos %d\n", i); } this->ref = luaL_ref(L, LUA_REGISTRYINDEX); } } string LuaTable::toLuaString(bool binary) { /* the function name */ lua_getglobal(L, "util"); lua_getfield(L, -1, "to_lua_string"); pushTable(L); if (binary) lua_pushstring(L, "binary"); else lua_pushstring(L, "ascii"); if (lua_pcall(L, 2, 1, 0) != LUA_OK) { string str(lua_tostring(L,-1)); lua_pop(L,1); ERROR_EXIT1(128, "%s", str.c_str()); } string str(lua_tostring(L,-1)); lua_pop(L,2); return str; } void LuaTable::pushTable(lua_State *L) { if (this->L != L) ERROR_EXIT(128, "Given incorrect lua_State\n"); int abspos; int pos = checkAndGetRef(abspos); if (pos != -1) lua_pushvalue(L, pos); } int LuaTable::checkAndGetRef(int &abspos) const { if (absindex != 0) { abspos = absindex; return absindex; } else if (ref == LUA_NOREF) { return 0; } lua_rawgeti(L, LUA_REGISTRYINDEX, ref); abspos = lua_absindex(L, -1); return -1; } void LuaTable::popRef(int pos, int extra) const { if (pos == -1) lua_pop(L, 1 + extra); else lua_pop(L, extra); } /////////////////////////////////////////////////////////////////////////// template<> char LuaTable::convertTo(lua_State *L, int idx) { const char *str = lua_tostring(L, idx); return *str; } template<> uint32_t LuaTable::convertTo(lua_State *L, int idx) { return static_cast(lua_tonumber(L, idx)); } template<> int LuaTable::convertTo(lua_State *L, int idx) { return static_cast(lua_tonumber(L, idx)); } template<> float LuaTable::convertTo(lua_State *L, int idx) { return static_cast(lua_tonumber(L, idx)); } template<> double LuaTable::convertTo(lua_State *L, int idx) { return lua_tonumber(L, idx); } template<> bool LuaTable::convertTo(lua_State *L, int idx) { if (lua_isboolean(L, idx)) return lua_toboolean(L, idx); else if (lua_isnil(L, idx)) return false; else if (lua_isnumber(L, idx)) { double n = lua_tonumber(L, idx); return n != 0.0; } else return false; } template<> const char *LuaTable::convertTo(lua_State *L, int idx) { UNUSED_VARIABLE(L); UNUSED_VARIABLE(idx); ERROR_EXIT(128, "Not implemented for 'const char *', use 'string'\n"); return 0; } template<> string LuaTable::convertTo(lua_State *L, int idx) { string aux(lua_tostring(L, idx), luaL_len(L, idx)); return aux; } template<> void LuaTable::pushInto(lua_State *L, char value) { lua_pushlstring(L, &value, 1); } template<> void LuaTable::pushInto(lua_State *L, uint32_t value) { lua_pushnumber(L, static_cast(value)); } template<> void LuaTable::pushInto(lua_State *L, int32_t value) { lua_pushnumber(L, static_cast(value)); } template<> void LuaTable::pushInto(lua_State *L, float value) { lua_pushnumber(L, static_cast(value)); } template<> void LuaTable::pushInto(lua_State *L, double value) { lua_pushnumber(L, value); } template<> void LuaTable::pushInto(lua_State *L, bool value) { lua_pushboolean(L, value); } template<> void LuaTable::pushInto(lua_State *L, string value) { size_t len = value.size(); if (len>0 && value.back() == '\0') { april_assert(len-1 == strlen(value.c_str())); lua_pushstring(L, value.c_str()); } else { lua_pushlstring(L, value.c_str(), len); } } template<> void LuaTable::pushInto(lua_State *L, const string &value) { size_t len = value.size(); if (len>0 && value.back() == '\0') { april_assert(len-1 == strlen(value.c_str())); lua_pushstring(L, value.c_str()); } else { lua_pushlstring(L, value.c_str(), len); } } template<> void LuaTable::pushInto(lua_State *L, const char *value) { lua_pushstring(L, value); } template<> bool LuaTable::checkType(lua_State *L, int idx) { return lua_type(L, idx)==LUA_TSTRING && luaL_len(L, idx)==1; } template<> bool LuaTable::checkType(lua_State *L, int idx) { return lua_isnumber(L, idx); } template<> bool LuaTable::checkType(lua_State *L, int idx) { return lua_isnumber(L, idx); } template<> bool LuaTable::checkType(lua_State *L, int idx) { return lua_isnumber(L, idx); } template<> bool LuaTable::checkType(lua_State *L, int idx) { return lua_isnumber(L, idx); } template<> bool LuaTable::checkType(lua_State *L, int idx) { return lua_isboolean(L,idx) || lua_isnumber(L,idx); } template<> bool LuaTable::checkType(lua_State *L, int idx) { return lua_isstring(L, idx); } template<> bool LuaTable::checkType(lua_State *L, int idx) { return lua_isstring(L, idx); } // overload of get for const char * template<> const char *LuaTable::get(const char *name) const { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) ERROR_EXIT(128, "Invalid reference\n"); lua_getfield(L, pos, name); if (lua_isnil(L,-1)) ERROR_EXIT1(128, "Unable to find field %s\n", name); const char *str = lua_tostring(L, -1); // NOTE: it is safe to pop because the string is referenced in a table, so, // as far as the table exists, the string will also exists. popRef(pos, 1); return str; } // overload of opt for const char * template<> const char *LuaTable::opt(const char *name, const char *def) const { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) { popRef(pos); return def; } else { lua_getfield(L, pos, name); if (lua_isnil(L,-1)) { popRef(pos, 1); return def; } const char *str = lua_tostring(L,-1); // NOTE: it is safe to pop because the string is referenced in a table, // so, as far as the table exists, the string will also exists. popRef(pos, 1); return str; } // return T(); } } april-ann-0.4.1/packages/basics/util/c_src/lua_table.h000066400000000000000000000626561263004425400226050ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LUA_TABLE_H #define LUA_TABLE_H extern "C" { #include #include "lauxlib.h" #include "lualib.h" #include "lua.h" } #include #include "base.h" #include "error_print.h" #include "is_same.h" #include "mystring.h" #include "referenced.h" #include "remove_pointer.h" #include "smart_ptr.h" #include "unused_variable.h" /** * @brief Macro for declaration of template specializations for * AprilUtils::LuaTable class. * * Example of use: * @code * DECLARE_LUA_TABLE_BIND_SPECIALIZATION(Basics::MatrixFloat); * @endcode * * @note This macro accepts any argument, even with namespaces. */ #define DECLARE_LUA_TABLE_BIND_SPECIALIZATION(type) \ namespace AprilUtils { \ template<> type *LuaTable::convertTo(lua_State *L, int idx); \ template<> void LuaTable::pushInto(lua_State *L, type *value); \ template<> void LuaTable::pushInto(lua_State *L, SharedPtr value); \ template<> bool LuaTable::checkType(lua_State *L, int idx); \ } /** * @brief Macro for implementation of template specializations for * AprilUtils::LuaTable class. * * @note This macro doesn't accepts arguments with namespaces. * * This macro is normally called in C++ bindings. Example of use: * @code * using Basics::MatrixFloat; // requires namespace using * ... * IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(MatrixFloat); * @endcode */ #define IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(type) \ namespace AprilUtils { \ template<> type *LuaTable::convertTo(lua_State *L, int idx) { \ return lua_to##type(L, idx); \ } \ template<> void LuaTable::pushInto(lua_State *L, type *value) { \ lua_push##type(L, value); \ } \ template<> void LuaTable::pushInto(lua_State *L, SharedPtr value) { \ lua_push##type(L, value.get()); \ } \ template<> bool LuaTable::checkType(lua_State *L, int idx) { \ return lua_is##type(L, idx); \ } \ } namespace AprilUtils { /** * @brief A class which allow to put and get data into a Lua table. * * This class allow to access from C++ to Lua values stored into a Lua table. * The Lua table is stored at the C registry, and will be remove in the * destructor. Template methods for put(), get(), and opt() operations are * defined. It is possible to specialize this methods in new C++ types by * specializing the static template methods: convertTo(), pushInto() and * checkType(). Operator[] has been overloaded to allow array and * dictionary access, as the following code. * @code * table["foo"] = bar1; * table[1] = bar2; * table[rng] = bar3; * bar1 = table["foo"].get(); * bar1 = table["foo"].opt(DefaultFooValue); * bar2 = table[1].opt(DefaultFooValue); * bar3 = table[rng].opt(DefaultFooValue); * @endcode * * @note Keys can be strings, integers or referenced pointers. * * @note Static template methods convertTo(), pushInto() and checkType() can * be used in C++ code to operate with Lua end. * * @see IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION and * DECLARE_LUA_TABLE_BIND_SPECIALIZATION macros. */ class LuaTable { /** * @brief Implements a helper for left hand side operator[] of LuaTable * class. * * This helper allow to use LuaTable in the following way: * * @code * table[1] = bar; * bar = table[1].get(); * bar = table[1].opt(DefaultValue); * @endcode */ class LHSAccessorByInteger { public: LHSAccessorByInteger(LuaTable *table, int n) : table(table),n(n) {} LHSAccessorByInteger(const LHSAccessorByInteger &other) : table(other.table),n(other.n) {} template LuaTable &operator=(T value) { return table->put(n, value); } template T get() const { return table->get(n); } template T opt(const T def_value) const { return table->opt(n, def_value); } template bool is() const { return table->checkNilOrType(n); } private: LuaTable *table; const int n; }; /** * @brief Implements a helper for left hand side operator[] of LuaTable * class. * * This helper allow to use LuaTable in the following way: * * @code * table[foo] = bar; * bar = table[foo].get(); * bar = table[foo].opt(DefaultFooValue); * table["foo"] = bar; * bar = table["foo"].get(); * bar = table["foo"].opt(DefaultFooValue); * @endcode */ template class LHSAccessorByPointer { public: LHSAccessorByPointer(LuaTable *table, K *key) : table(table),key(key) {} LHSAccessorByPointer(const LHSAccessorByPointer &other) : table(other.table),key(other.key) {} template LuaTable &operator=(T value) { return table->put(key, value); } template T get() const { return table->get(key); } template T opt(const T def_value) const { return table->opt(key, def_value); } template T opt(AprilUtils::SharedPtr::type> def_value) const { return table->opt(key, def_value.get()); } template bool is() const { return table->checkNilOrType(key); } private: LuaTable *table; K * key; }; /** * @brief Implements a helper for right hand side operator[] of LuaTable * class. * * This helper allow to use LuaTable in the following way: * * @code * bar = table[1].get(); * bar = table[1].opt(DefaultFooValue); * @endcode */ class RHSAccessorByInteger { public: RHSAccessorByInteger(const LuaTable *table, int n) : table(table),n(n) {} RHSAccessorByInteger(const RHSAccessorByInteger &other) : table(other.table),n(other.n) {} template T get() const { return table->get(n); } template T opt(const T def_value) const { return table->opt(n, def_value); } template bool is() const { return table->checkNilOrType(n); } private: const LuaTable *table; const int n; }; /** * @brief Implements a helper for right hand side operator[] of LuaTable * class. * * This helper allow to use LuaTable in the following way: * * @code * bar = table[foo].get(); * bar = table[foo].opt(DefaultFooValue); * bar = table["foo"].get(); * bar = table["foo"].opt(DefaultFooValue); * @endcode */ template class RHSAccessorByPointer { public: RHSAccessorByPointer(const LuaTable *table, K *key) : table(table),key(key) {} RHSAccessorByPointer(const RHSAccessorByPointer &other) : table(other.table),key(other.key) {} template T get() const { return table->get(key); } template T opt(const T def_value) const { return table->opt(key, def_value); } template T opt(AprilUtils::SharedPtr::type> def_value) const { return table->opt(key, def_value.get()); } template bool is() const { return table->checkNilOrType(key); } private: const LuaTable *table; K * key; }; //////////////////////////////////////////////////////////////////////// public: /// Constructor for a new LuaTable in the registry. LuaTable(lua_State *L = Base::getAndCheckGlobalLuaState()); /// Constructor for a new LuaTable in the registry containing C array data. template LuaTable(const T *vec, size_t len, lua_State *L = Base::getAndCheckGlobalLuaState()) { lua_newtable(L); init(L, -1); for (unsigned int i=0; i(L, vec[i]); lua_rawseti(L, -2, i+1); } lua_pop(L, 1); } /// Constructor for a LuaTable in a given Lua stack position. LuaTable(lua_State *L, int n); /// Copy constructor. LuaTable(const LuaTable &other); /// Destructor. ~LuaTable(); /** * @brief Pushes into stack the table and takes it as an absolute index. * * Be careful, the stack will be modified because a reference to the table * will be pushed on top of it. This method allows to perform a large number * of table read/write operations in an efficient way. See the example: * * @code * LuaTable t(L,-1); * t.lock(); * double sum; * for (int i=1; i<=1000000; ++i) sum += t[i].get(); * t.unlock(); * @endcode * * @note If LuaTable has been locked before, this method does nothing and * returns false. Otherwise it returns true. * * @note It is necessary to call unlock() method every time you do a lock(). */ bool lock() { if (absindex == 0) { int abspos; int pos = checkAndGetRef(abspos); if (pos == 0) ERROR_EXIT(128, "Found empty table\n"); assert(pos == -1); absindex = abspos; return true; } return false; } /** * @brief Removes from stack the absolute index taken by lock() method. Be * careful, the stack will be modified. * * @see lock() method. */ bool unlock() { if (absindex > 0) { lua_remove(L, absindex); absindex = 0; return true; } return false; } /// Indicates if the LuaTable is empty. bool empty() const; /// Executes length operator in Lua size_t length() const; /// Copy operator. LuaTable &operator=(const LuaTable &other); /// See RHSAccessorByPointer RHSAccessorByPointer operator[](const string &name) const { return RHSAccessorByPointer(this, name.c_str()); } /// See RHSAccessorByInteger RHSAccessorByInteger operator[](int n) const { return RHSAccessorByInteger(this, n); } /// See RHSAccessorByPointer template RHSAccessorByPointer operator[](K *key) const { return RHSAccessorByPointer(this, key); } /// See LHSAccessorByPointer LHSAccessorByPointer operator[](const string &name) { return LHSAccessorByPointer(this, name.c_str()); } /// See LHSAccessorByInteger LHSAccessorByInteger operator[](int n) { return LHSAccessorByInteger(this, n); } /// See LHSAccessorByPointer template LHSAccessorByPointer operator[](K *key) { return LHSAccessorByPointer(this, key); } /// Returns a C++ string with the Lua representation of the table. string toLuaString(bool binary=true); /// Puts a new value into the table, using the given key name. template LuaTable &put(const string &name, T value) { return put(name.c_str(), value); } /// Checks if the field at the given key name is nil. bool checkNil(const string &name) const { return checkNil(name.c_str()); } /// Checks if the field at the given key name is of the given type (a nil /// value will be taken as true). template bool checkNilOrType(const string &name) const { return checkNilOrType(name.c_str()); } /// Returns the value stored at the given key name field. template T get(const string &name) const { return get(name.c_str()); } /// Returns the value stored at the given key name field. In case the field /// is empty, it returns the given def_value argument. template T opt(const string &name, const T def_value) const { return opt(name.c_str(), def_value); } /// Puts a new value into the table, using the given key number. template LuaTable &put(int n, T value) { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) ERROR_EXIT(128, "Invalid reference\n"); lua_pushnumber(L, n); pushInto(L, value); lua_settable(L, abspos); popRef(pos); return *this; } /// Puts a new value into the table, using the given key pointer or string. template LuaTable &put(K *key, T value) { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) ERROR_EXIT(128, "Invalid reference\n"); pushInto(L, key); pushInto(L, value); lua_settable(L, abspos); popRef(pos); return *this; } /// Puts a new value into the table, using the given key name. template LuaTable &put(const char *name, size_t len, T value) { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) ERROR_EXIT(128, "Invalid reference\n"); lua_pushlstring(L, name, len); pushInto(L, value); lua_settable(L, abspos); popRef(pos); return *this; } /// Checks if the field at the given key number is nil. bool checkNil(int n) const { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) ERROR_EXIT(128, "Invalid reference\n"); lua_pushnumber(L, n); lua_gettable(L, abspos); bool ret = lua_isnil(L, -1); popRef(pos, 1); return ret; } /// Checks if the field at the given key pointer or string is nil. template bool checkNil(K *key) const { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) ERROR_EXIT(128, "Invalid reference\n"); pushInto(L, key); lua_gettable(L, abspos); bool ret = lua_isnil(L, -1); popRef(pos, 1); return ret; } /// Checks if the field at the given key name is nil. bool checkNil(const char *name, size_t len) const { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) ERROR_EXIT(128, "Invalid reference\n"); lua_pushlstring(L, name, len); lua_gettable(L, abspos); bool ret = lua_isnil(L, -1); popRef(pos, 1); return ret; } /// Checks if the field at the given key number is of the given type (a nil /// value will be taken as true). template bool checkNilOrType(int n) const { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) ERROR_EXIT(128, "Invalid reference\n"); lua_pushnumber(L, n); lua_gettable(L, abspos); bool ret = lua_isnil(L, -1) || checkType(L, -1); popRef(pos, 1); return ret; } /// Checks if the field at the given key pointer or string is of the given /// type (a nil value will be taken as true). template bool checkNilOrType(K *key) const { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) ERROR_EXIT(128, "Invalid reference\n"); pushInto(L, key); lua_gettable(L, abspos); bool ret = lua_isnil(L, -1) || checkType(L, -1); popRef(pos, 1); return ret; } /// Checks if the field at the given key name is of the given type (a nil /// value will be taken as true). template bool checkNilOrType(const char *name, size_t len) const { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) ERROR_EXIT(128, "Invalid reference\n"); lua_pushlstring(L, name, len); lua_gettable(L, abspos); bool ret = lua_isnil(L, -1) || checkType(L, -1); popRef(pos, 1); return ret; } /// Returns the value stored at the given key number field. template T get(int n) const { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) ERROR_EXIT(128, "Invalid reference\n"); lua_pushnumber(L, n); lua_gettable(L, abspos); if (lua_isnil(L,-1)) ERROR_EXIT1(128, "Unable to find field %d\n", n); if (!checkType(L, -1)) ERROR_EXIT(128, "Incorrect type\n"); T v = convertTo(L, -1); popRef(pos, 1); return v; } /// Returns the value stored at the given key pointer or string field. template T get(K *key) const { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) ERROR_EXIT(128, "Invalid reference\n"); pushInto(L, key); lua_gettable(L, abspos); if (lua_isnil(L,-1)) { if (is_same::value || is_same::value) { // string case, resolved at compilation ERROR_EXIT1(128, "Unable to find field %s\n", key); } else { // referenced pointer case ERROR_EXIT1(128, "Unable to find field %p\n", key); } } if (!checkType(L, -1)) ERROR_EXIT(128, "Incorrect type\n"); T v = convertTo(L, -1); popRef(pos, 1); return v; } /// Returns the value stored at the given key name field. template T get(const char *name, size_t len) const { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) ERROR_EXIT(128, "Invalid reference\n"); lua_pushlstring(L, name, len); lua_gettable(L, abspos); if (lua_isnil(L,-1)) ERROR_EXIT1(128, "Unable to find field %s\n", name); if (!checkType(L, -1)) ERROR_EXIT(128, "Incorrect type\n"); T v = convertTo(L, -1); popRef(pos, 1); return v; } /// Returns the value stored at the given key number field. In case the field /// is empty, it returns the given def_value argument. template T opt(int n, const T def_value) const { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) { popRef(pos); return def_value; } else { lua_pushnumber(L, n); lua_gettable(L, abspos); T v(def_value); if (!lua_isnil(L,-1)) { if (!checkType(L, -1)) ERROR_EXIT(128, "Incorrect type\n"); v = convertTo(L, -1); } popRef(pos, 1); return v; } // return T(); } /// Returns the value stored at the given key pointer or string field. In /// case the field is empty, it returns the given def_value argument. template T opt(K *key, const T def_value) const { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) { popRef(pos); return def_value; } else { pushInto(L, key); lua_gettable(L, abspos); T v(def_value); if (!lua_isnil(L,-1)) { if (!checkType(L, -1)) ERROR_EXIT(128, "Incorrect type\n"); v = convertTo(L, -1); } popRef(pos, 1); return v; } // return T(); } /// Returns the value stored at the given key name field. In case the field /// is empty, it returns the given def_value argument. template T opt(const char *name, size_t len, const T def_value) const { int pos, abspos; if ((pos=checkAndGetRef(abspos)) == 0) { popRef(pos); return def_value; } else { lua_pushlstring(L, name, len); lua_gettable(L, abspos); T v(def_value); if (!lua_isnil(L,-1)) { if (!checkType(L, -1)) ERROR_EXIT(128, "Incorrect type\n"); v = convertTo(L, -1); } popRef(pos, 1); return v; } // return T(); } /// Returns a userdata interpreted as the given type T avoiding type check template static T lua_rawgetudata(lua_State *L, int n) { T *pre_obj = static_cast(lua_touserdata(L,n)); T obj = 0; if (pre_obj) obj = (*pre_obj); return obj; } /// Pushes into Lua stack the Lua table associated with the object. void pushTable(lua_State *L); /// Converts the value at the given Lua stack index, without removing it. template static T convertTo(lua_State *L, int idx) { UNUSED_VARIABLE(L); UNUSED_VARIABLE(idx); ERROR_EXIT1(128, "NOT IMPLEMENTED FOR TYPE %s\n", typeid(T).name()); return T(); } /// Pushes a value into the Lua stack. template static void pushInto(lua_State *L, T value) { UNUSED_VARIABLE(L); UNUSED_VARIABLE(value); ERROR_EXIT1(128, "NOT IMPLEMENTED FOR TYPE %s\n", typeid(value).name()); } /// Pushes a SharedPtr instance into the Lua stack. template static void pushInto(lua_State *L, SharedPtr value) { UNUSED_VARIABLE(L); UNUSED_VARIABLE(value); ERROR_EXIT1(128, "NOT IMPLEMENTED FOR TYPE %s\n", typeid(value).name()); } /// Checks the expected type of the value at the given Lua stack index. template static bool checkType(lua_State *L, int idx) { UNUSED_VARIABLE(L); UNUSED_VARIABLE(idx); ERROR_EXIT1(128, "NOT IMPLEMENTED FOR TYPE %s\n", typeid(T).name()); return false; } private: /// The lua_State where the table is allocated. mutable lua_State *L; /// The reference in the registry where the table can be retrieved. int ref; /// Absolute index, only valid when LuaTable is in locked state (absindex>0). int absindex; /// Auxiliary method to simplify constructors. void init(lua_State *L, int i); /// Checks the value of ref and absindex and returns a valid position to the stack. int checkAndGetRef(int &abspos) const; /// Receives the position returned by checkAndGetRef() and performs operations needed to end using it. void popRef(int pos, int extra=0) const; }; // Basic data types specializations. template<> char LuaTable::convertTo(lua_State *L, int idx); template<> uint32_t LuaTable::convertTo(lua_State *L, int idx); template<> int32_t LuaTable::convertTo(lua_State *L, int idx); template<> float LuaTable::convertTo(lua_State *L, int idx); template<> double LuaTable::convertTo(lua_State *L, int idx); template<> bool LuaTable::convertTo(lua_State *L, int idx); template<> const char *LuaTable::convertTo(lua_State *L, int idx); template<> string LuaTable::convertTo(lua_State *L, int idx); template<> LuaTable LuaTable::convertTo(lua_State *L, int idx); template<> void LuaTable::pushInto(lua_State *L, char value); template<> void LuaTable::pushInto(lua_State *L, uint32_t value); template<> void LuaTable::pushInto(lua_State *L, int32_t value); template<> void LuaTable::pushInto(lua_State *L, float value); template<> void LuaTable::pushInto(lua_State *L, double value); template<> void LuaTable::pushInto(lua_State *L, bool value); template<> void LuaTable::pushInto(lua_State *L, string value); template<> void LuaTable::pushInto(lua_State *L, const string &value); template<> void LuaTable::pushInto(lua_State *L, const char *value); template<> void LuaTable::pushInto(lua_State *L, LuaTable value); template<> bool LuaTable::checkType(lua_State *L, int idx); template<> bool LuaTable::checkType(lua_State *L, int idx); template<> bool LuaTable::checkType(lua_State *L, int idx); template<> bool LuaTable::checkType(lua_State *L, int idx); template<> bool LuaTable::checkType(lua_State *L, int idx); template<> bool LuaTable::checkType(lua_State *L, int idx); template<> bool LuaTable::checkType(lua_State *L, int idx); template<> bool LuaTable::checkType(lua_State *L, int idx); template<> bool LuaTable::checkType(lua_State *L, int idx); // overload of get for const char * template<> const char *LuaTable::get(const char *name) const; // overload of opt for const char * template<> const char *LuaTable::opt(const char *name, const char *def) const; } // namespace AprilUtils #endif // LUA_TABLE_H april-ann-0.4.1/packages/basics/util/c_src/max_min_finder.h000066400000000000000000000204521263004425400236200ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MAX_MIN_FINDER_H #define MAX_MIN_FINDER_H #include "vector.h" namespace AprilUtils { // encuentra los maximos/minimos locales de una secuencia, usa contexto // izquierdo y derecho, asume que T soporta == y < template class max_min_finder { int ci,cd,maxsz,sz,first; T *vec, maxval,minval; bool findmax; vector *max_output; // puntero a un vector que "nos pasan" bool findmin; vector *min_output; // puntero a un vector que "nos pasan" void process_max_value(T value) { if (max_output) max_output->push_back(value); } void process_min_value(T value) { if (min_output) min_output->push_back(value); } T& value_at(int pos) { return vec[(first+pos)%maxsz]; } public: max_min_finder(int ci=0, int cd=0, bool findmax=true,vector*outvec=0, bool findmin=false,vector*invec=0) : ci(ci), cd(cd), findmax(findmax), max_output(outvec), findmin(findmin), min_output(invec) { maxsz = ci+1+cd; vec = new T[maxsz]; sz = first = 0; } ~max_min_finder() { delete[] vec; } void put(T entra) { if (sz= cd && vec[sz-cd] == maxval) process_max_value(vec[sz-cd]); } if (findmin) { if (sz == 0 || entra= cd && vec[sz-cd] == minval) process_min_value(vec[sz-cd]); } sz++; } else { // vamos a meter uno nuevo T sale = vec[first]; vec[first] = entra; first = (first+1)%maxsz; if (findmax) { if (maxval < entra) // el nuevo mantiene o mejora el maximo maxval = entra; else if (sale == maxval) { // buscar el nuevo maximo maxval = vec[first]; // value_at(0) for (int i=1;i= 0) ? sz-cd+1 : 0; if (findmax) for (int i=desde;i0) { T aux = value_at(maxsz-1) ; for (int i=0; i*out_maxvec=0, bool findmin=false,vector*out_minvec=0) { if (maxsz != ci + 1 + cd) { delete[] vec; maxsz = ci + 1 + cd; vec = new T[maxsz]; } this->ci=ci; this->cd=cd; this->findmax =findmax; this->max_output=out_maxvec; this->findmin =findmin; this->min_output=out_minvec; sz = first = 0; } }; // encuentra los maximos locales de una secuencia, usa contexto // izquierdo y derecho, asume que T soporta == y < template class max_finder { int ci,cd,maxsz,sz,first; T *vec, maxval; vector *max_output; // puntero a un vector que "nos pasan" void process_max_value(T value) { if (max_output) max_output->push_back(value); } T& value_at(int pos) { return vec[(first+pos)%maxsz]; } public: max_finder(int ci=0, int cd=0, vector*out_max_vec=0) : ci(ci), cd(cd), max_output(out_max_vec) { maxsz = ci+1+cd; vec = new T[maxsz]; sz = first = 0; } ~max_finder() { delete[] vec; } void put(T entra) { if (sz= cd && vec[sz-cd] == maxval) process_max_value(vec[sz-cd]); sz++; } else { // vamos a meter uno nuevo T sale = vec[first]; vec[first] = entra; first = (first+1)%maxsz; if (maxval < entra) // el nuevo mantiene o mejora el maximo maxval = entra; else if (sale == maxval) { // buscar el nuevo maximo maxval = vec[first]; // value_at(0) for (int i=1;i= 0) ? sz-cd+1 : 0; for (int i=desde;i0) { T aux = value_at(maxsz-1) ; for (int i=0; i*out_max_vec=0) { if (maxsz != ci + 1 + cd) { delete[] vec; maxsz = ci + 1 + cd; vec = new T[maxsz]; } this->ci=ci; this->cd=cd; this->max_output=out_max_vec; sz = first = 0; } }; // encuentra los minimos locales de una secuencia, usa contexto // izquierdo y derecho, asume que T soporta == y < template class min_finder { int ci,cd,maxsz,sz,first; T *vec, minval; vector *min_output; // puntero a un vector que "nos pasan" void process_min_value(T value) { if (min_output) min_output->push_back(value); } T& value_at(int pos) { return vec[(first+pos)%maxsz]; } public: min_finder(int ci=0, int cd=0, vector*out_min_vec=0) : ci(ci), cd(cd), min_output(out_min_vec) { maxsz = ci+1+cd; vec = new T[maxsz]; sz = first = 0; } ~min_finder() { delete[] vec; } void put(T entra) { if (sz= cd && vec[sz-cd] == minval) process_min_value(vec[sz-cd]); sz++; } else { // vamos a meter uno nuevo T sale = vec[first]; vec[first] = entra; first = (first+1)%maxsz; if (entra < minval) // el nuevo mantiene o mejora el minimo minval = entra; else if (sale == minval) { // buscar el nuevo minimo minval = vec[first]; // value_at(0) for (int i=1;i= 0) ? sz-cd+1 : 0; for (int i=desde;i0) { T aux = value_at(maxsz-1) ; for (int i=0; i*out_min_vec=0) { if (maxsz != ci + 1 + cd) { delete[] vec; maxsz = ci + 1 + cd; vec = new T[maxsz]; } this->ci=ci; this->cd=cd; this->min_output=out_min_vec; sz = first = 0; } }; } // closes namespace AprilUtils #endif // MAX_MIN_FINDER_H april-ann-0.4.1/packages/basics/util/c_src/maxiphobic_minheap.h000066400000000000000000000140251263004425400244640ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MAXIPHOBIC_MINHEAP_H #define MAXIPHOBIC_MINHEAP_H // #include reemplazado por "swap.h" #include "swap.h" #include "vector.h" #include using std::size_t; namespace AprilUtils{ template class maxiphobic_minheap { struct node { int size; node *left; node *right; T data; node(const T& d): size(1), left(0), right(0), data(d) { } node(const T& d, node * const l, node * const r): size(1), left(l), right(r), data(d) { if (l) size += l->size; if (r) size += r->size; } #ifndef NO_POOL inline static void * operator new(size_t size){ if (size != sizeof(node)) return ::operator new(size); node *n = freelist; if (n != 0) { freelist = n->left; poolsize--; return n; } else { return ::operator new(size); } } inline static void operator delete(void *object, size_t size) { if (object == 0) return; if (size != sizeof(node)) { ::operator delete(object); return; } if (poolsize < MAXPOOLSIZE) { node *deleted_node = static_cast(object); deleted_node->left = freelist; freelist = deleted_node; poolsize++; } else { ::operator delete(object); } } private: static node *freelist; static int poolsize; static const int MAXPOOLSIZE=2000000; #endif // NO_POOL }; node *root; static node* merge(node *node1, node *node2) { if (node1 == 0) return node2; if (node2 == 0) return node1; node *cur=0; node *A, *B, *C; if (node1->data < node2->data){ // merge(node1, node2) sobre node1 cur = node1; node1->size += node2->size; C = node2; } else { // merge(node1, node2) sobre node2 cur = node2; node2->size += node1->size; C = node1; } node *min = cur; A = cur->left; B = cur->right; while ((A != 0) && (B != 0) && (C != 0)){ // Tenemos 3 arboles: A, B y C a partir de los cuales // hay que crear 2 hijos para cur. // Hacemos que A sea el de mayor tamaño if (B->size > A->size) swap(A, B); if (C->size > A->size) swap(A, C); cur->left = A; if (B->data < C->data) { // merge(B, C) sobre B cur->right = B; cur = B; B->size += C->size; A = B->left; B = B->right; } else { // merge(B, C) sobre C cur->right = C; cur = C; C->size += B->size; A = C->left; C = C->right; } } // Al salir del bucle al menos uno de A, B, C esta vacio. if (A==0) { cur->left = B; cur->right = C; } else if (B==0) { cur->left = A; cur->right = C; } else { // C==0 cur->left = A; cur->right = B; } return min; } void delete_tree(node *n) { if (n->left != 0) delete_tree(n->left); if (n->right != 0) delete_tree(n->right); delete n; } // Copia recursiva del arbol node *copy(node *other) { return (other == 0 ? 0 : new node(other->data, copy(other->left), copy(other->right))); } public: maxiphobic_minheap(): root(0) { } // Constructor de copia y operador de asignacion // para evitar que los generados por defecto nos produzcan un universo de dolor. // Si hacen falta se implementan :) maxiphobic_minheap(const maxiphobic_minheap &other) { root = copy(other.root); } maxiphobic_minheap& operator= (const maxiphobic_minheap& other) { // Primero borramos los elementos que ya tuvieramos if (root != 0) delete_tree(root); root = copy(other.root); } ~maxiphobic_minheap() { if (root != 0) delete_tree(root); } void clear() { delete_tree(root); } void insert(const T &data) { node *p = new node(data); root = merge(root, p); } void delete_min() { node *old_root = root; root = merge(root->left, root->right); delete old_root; } T read_min() { return root->data; } T extract_min() { T res = read_min(); delete_min(); return res; } void foreach(void (*func)(T)) { if (root) { // Usamos 2*ln(size) como estimacion de profundidad del arbol vector stack; node *cur; stack.reserve(2*int(log(root->size))); stack.push_back(root); while (!stack.empty()) { cur = stack.back(); stack.pop_back(); func(cur->data); if (cur->right) stack.push_back(cur->right); if (cur->left) stack.push_back(cur->left); } } } bool empty() const { return root == 0; } int size() const { return (empty()? 0 : root->size); } }; #ifndef NO_POOL template int maxiphobic_minheap::node::poolsize=0; template typename maxiphobic_minheap::node *maxiphobic_minheap::node::freelist=0; #endif // NO_POOL } #endif april-ann-0.4.1/packages/basics/util/c_src/maxmin.h000066400000000000000000000054371263004425400221400ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MAX_MIN_H #define MAX_MIN_H #include "april_assert.h" namespace AprilUtils { template T max(T a, T b) { return (a T min(T a, T b) { return (a int argmax(const T *v, int size) { april_assert(size > 0); int p = 0; for (int i=1; i int argmin(const T *v, int size) { april_assert(size > 0); int p = 0; for (int i=1; i T max(const T *v, int size) { return v[argmax(v, size)]; } template T min(const T *v, int size) { return v[argmin(v, size)]; } // argmax, argmin, max, min for containers template Iterator argmax(Iterator begin, Iterator end) { Iterator max_iter = begin; for (Iterator i=begin; i!=end; ++i) { if (*max_iter < *i) { max_iter = i; } } return max_iter; } template Iterator argmin(Iterator begin, Iterator end) { Iterator min_iter = begin; for (Iterator i=begin; i!=end; ++i) { if (*i < *min_iter) { min_iter = i; } } return min_iter; } template typename T::iterator argmax(T& container) { return argmax(container.begin(), container.end()); } template typename T::iterator argmin(T& container) { return argmin(container.begin(), container.end()); } template typename T::value_type max(T& container) { return *AprilUtils::argmax(container.begin(), container.end()); } template typename T::value_type min(T& container) { return *AprilUtils::argmin(container.begin(), container.end()); } } #endif //MAX_MIN_H april-ann-0.4.1/packages/basics/util/c_src/mean_deviation.h000066400000000000000000000051411263004425400236210ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MEAN_DEVIATION_H #define MEAN_DEVIATION_H #include namespace AprilUtils { template void mean_deviation(T v[], int sz, double *mean, double *dev) { double sum = 0, sum2 = 0; for (int i=0;i 0) ? m_newM : 0.0; } double variance() const { return ( (m_n > 1) ? m_newS/(m_n - 1) : 0.0 ); } double standardDeviation() const { return sqrt( variance() ); } }; } #endif //MEAN_DEVIATION_H april-ann-0.4.1/packages/basics/util/c_src/mfset.h000066400000000000000000000106631263004425400217620ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MFSET_H #define MFSET_H /* Implementacion de un mfset, permite find(), merge(), toString() y fromString() */ extern "C" { #include } #include "april_assert.h" #include "constString.h" #include "binarizer.h" #include "referenced.h" #include "maxmin.h" #include "vector.h" #define DEFAULT_MFSET_SIZE 524288 // 512*1024 namespace AprilUtils { class MFSet : public Referenced { private: // vector que contiene el mfset vector data; int32_t max_vector_size, vector_size; public: // constructor de copia MFSet(MFSet *obj) { this->max_vector_size = obj->max_vector_size; this->vector_size = obj->vector_size; this->data.reserve(max_vector_size); for (int32_t i=0; idata[i] = obj->data[i]; } // construye un mefset por defecto donde cada componente de data // es un conjunto MFSet(int size = DEFAULT_MFSET_SIZE) : data(size) { max_vector_size = size; data.reserve(max_vector_size); vector_size = 0; for (int32_t i=0; i= max_vector_size) { int32_t old_max_vector_size = max_vector_size; max_vector_size = sz << 1; data.resize(max_vector_size); for (int32_t i=old_max_vector_size; i= max_vector_size || value2 >= max_vector_size) { int32_t old_max_vector_size = max_vector_size; max_vector_size = AprilUtils::max(value1,value2) << 1; data.resize(max_vector_size); for (int32_t i=old_max_vector_size; i struct CmpLessDefault { bool operator()(const T &a, const T &b) { return a < b; } }; template > class min_heap { // minheap binario de valores de tipo T comparables CmpLess cmpless; T *vec; // vector que empieza con indice 1 int vector_size; int the_size; int parent(int pos) { return pos>>1; } int left_child(int pos) { return pos<<1; } void heapify(int pos); void incr_size(); public: min_heap(int initial_max_size, CmpLess cmpless = CmpLess()) : cmpless(cmpless) { vector_size = (initial_max_size > 0) ? initial_max_size : 2; the_size = 0; T *rv = new T[vector_size]; vec = rv - 1; // vec[1] is rv[0],... } ~min_heap() { delete[] (vec+1); } void clear() { the_size = 0; } bool empty() const { return the_size == 0; } int size() const { return the_size; } const T& top() const { return vec[1]; } void pop() { if (the_size > 0) { vec[1] = vec[the_size]; the_size--; heapify(1); } } void push(const T &elemento) { incr_size(); int position = the_size; while ((position > 1) && (cmpless(elemento, vec[parent(position)]))) { vec[position] = vec[parent(position)]; position = parent(position); } vec[position] = elemento; } void push_back(const T &elemento) { incr_size(); vec[the_size] = elemento; } void buildheap() { // se usa para imponer propiedad de orden for (int i = the_size/2; i >= 1; i--) { heapify(i); } } // ITERADOR class iterator { friend class min_heap; // puntero al Heap min_heap *h; // indice del vector del heap (para iterar) int idx; public: // constructor... iterator(min_heap *p, int i) : h(p), idx(i) { } // desreferencia del iterador, devuelve el tipo T const T& operator *() const { return h->vec[idx]; } // operador flecha para acceder directamente al objeto T const T* operator ->() const { return &(h->vec[idx]); } // incremento void operator++() { ++idx; } // suma void operator+(int s) { idx += s; } // suma void operator+=(int s) { idx += s; } // operador de igualdad bool operator==(const iterator &b) const { return (h == b.h && idx == b.idx); } // operador de diferente bool operator!=(const iterator &b) const { return (h != b.h || idx != b.idx); } }; // primer iterador iterator begin() { return iterator(this, 1); } // ultimo iterador iterator end() { return iterator(this, the_size+1); } // borra una posicion del heap a partir de un iterador situado en la // misma void del(const min_heap::iterator &idx) { // cambiamos el elemento por el ultimo del heap vec[idx.idx] = vec[the_size]; the_size--; // hundimos idx heapify(idx.idx); } }; template void min_heap::incr_size() { if (the_size >= vector_size) { T *old_vec = vec; vec = new T[2*vector_size] - 1; for (int i=1; i<=vector_size; i++) vec[i] = old_vec[i]; vector_size *= 2; delete[] (old_vec+1); } the_size++; } template void min_heap::heapify(int pos) { // version iterativa int child; T tmp = vec[pos]; while (left_child(pos) <= the_size) { child = left_child(pos); if(child < the_size && cmpless(vec[child+1], vec[child])) child++; // el child derecho if(cmpless(vec[child], tmp)) vec[pos] = vec[child]; else break; pos = child; } vec[ pos ] = tmp; } }; #endif // MIN_HEAP_H april-ann-0.4.1/packages/basics/util/c_src/mmapped_data.cc000066400000000000000000000053641263004425400234200ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include #include #include #include // mmap() is defined in this header #include #include #include "mmapped_data.h" #include "error_print.h" extern const char *__COMMIT_NUMBER__; namespace AprilUtils { const int MAGIC_NUMBER = 0x4321; MMappedDataReader::MMappedDataReader(const char *path, bool write, bool shared) { if ((fd = open(path, O_RDWR)) < 0) ERROR_EXIT1(128,"Unable to open file %s\n", path); // find size of input file struct stat statbuf; if (fstat(fd, &statbuf) < 0) { ERROR_EXIT(128, "Error guessing filesize\n"); } // mmap the input file mmapped_data_size = statbuf.st_size; int prot = PROT_READ; if (write) prot = prot | PROT_WRITE; int flags; if (shared) flags = MAP_SHARED; else flags = MAP_PRIVATE; if ((mmapped_data = static_cast(mmap(0, mmapped_data_size, prot, flags, fd, 0))) == (caddr_t)-1) ERROR_EXIT(128, "mmap error\n"); int magic = *(reinterpret_cast(mmapped_data)); if (magic != MAGIC_NUMBER) ERROR_EXIT(128, "Incorrect endianism\n"); pos = sizeof(int); commit_number = *(this->get()); } MMappedDataReader::~MMappedDataReader() { if (fd != -1) close(fd); munmap(mmapped_data, mmapped_data_size); } size_t MMappedDataReader::size() const { return mmapped_data_size - pos; } //////////////////////////////////////////////////////////////// MMappedDataWriter::MMappedDataWriter(const char *path) { if ((fd = open(path, O_CREAT | O_WRONLY | O_TRUNC, S_IRUSR | S_IWUSR | S_IRGRP | S_IWGRP | S_IROTH)) < 0) ERROR_EXIT1(128,"Unable to open file %s\n", path); int magic = MAGIC_NUMBER; this->put(&magic); int commit_number = atoi(__COMMIT_NUMBER__); this->put(&commit_number); } MMappedDataWriter::~MMappedDataWriter() { close(fd); } } april-ann-0.4.1/packages/basics/util/c_src/mmapped_data.h000066400000000000000000000041541263004425400232560ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MMAPPED_DATA_H #define MMAPPED_DATA_H extern "C" { #include #include #include #include #include // mmap() is defined in this header } #include "referenced.h" #include "april_assert.h" #include "error_print.h" #include "ignore_result.h" namespace AprilUtils { class MMappedDataReader : public Referenced { int commit_number; char *mmapped_data; size_t mmapped_data_size; size_t pos; int fd; public: MMappedDataReader(const char *path, bool write=true, bool shared=true); ~MMappedDataReader(); size_t size() const; template T *get(size_t n=1) { size_t sz = sizeof(T)*n; if (sz + pos > mmapped_data_size) ERROR_EXIT(128, "Overflow reading from mmap\n"); T *ptr = reinterpret_cast(mmapped_data+pos); pos += sizeof(T)*n; if (pos == mmapped_data_size) { close(fd); fd=-1; } return ptr; } int getCommitNumber() const { return commit_number; } }; class MMappedDataWriter : public Referenced { int fd; public: MMappedDataWriter(const char *path); ~MMappedDataWriter(); template void put(const T *data, size_t n=1) { IGNORE_RESULT(write(fd, data, sizeof(T)*n)); } }; } #endif // MMAPPED_DATA_H april-ann-0.4.1/packages/basics/util/c_src/mod.h000066400000000000000000000017771263004425400214310ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MOD_H #define MOD_H namespace AprilUtils { inline int mod(int x, int y) { int z = x % y; return (z>=0) ? z : y+z; } } #endif // MOD_H april-ann-0.4.1/packages/basics/util/c_src/ms_sleep.cc000066400000000000000000000022241263004425400226030ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "ms_sleep.h" namespace AprilUtils { void msleep(unsigned long milisec) { struct timespec req={0,0}; time_t sec=(int)(milisec/1000); milisec=milisec-(sec*1000); req.tv_sec=sec; req.tv_nsec=milisec*1000000L; while(nanosleep(&req,&req)==-1) { continue; } } } april-ann-0.4.1/packages/basics/util/c_src/ms_sleep.h000066400000000000000000000020311263004425400224410ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MILISECOND_SLEEP_H #define MILISECOND_SLEEP_H #include #include namespace AprilUtils { void msleep(unsigned long milisec); } #endif // MILISECOND_SLEEP_H april-ann-0.4.1/packages/basics/util/c_src/mystring.cc000066400000000000000000000127621263004425400226600ustar00rootroot00000000000000#include #include #include "mystring.h" namespace AprilUtils { #define BUFFER_LENGTH_THRESHOLD 128 size_t strnspn(const char *buffer, size_t buffer_length, const char *accept, size_t accept_length) { if (buffer_length > BUFFER_LENGTH_THRESHOLD && accept_length > 1) { char lookup_table[256]; memset(lookup_table, 0, 256*sizeof(char)); for (size_t i=0; i < accept_length && accept[i] != '\0'; ++i) { lookup_table[static_cast(accept[i])] = 1; } size_t pos=0; while(pos < buffer_length && buffer[pos] != '\0' && lookup_table[static_cast(buffer[pos])]) { ++pos; } return pos; } else { size_t pos=0; while(pos < buffer_length && buffer[pos] != '\0' && strchr(accept, buffer[pos])) { ++pos; } return pos; } } size_t strncspn(const char *buffer, size_t buffer_length, const char *reject, size_t reject_length) { if (buffer_length > BUFFER_LENGTH_THRESHOLD && reject_length > 1) { char lookup_table[256]; memset(lookup_table, 0, 256*sizeof(char)); for (size_t i=0; i < reject_length && reject[i] != '\0'; ++i) { lookup_table[static_cast(reject[i])] = 1; } size_t pos=0; while(pos < buffer_length && buffer[pos] != '\0' && !lookup_table[static_cast(buffer[pos])]) { ++pos; } return pos; } else { size_t pos=0; while(pos < buffer_length && buffer[pos] != '\0' && !strchr(reject, buffer[pos])) { ++pos; } return pos; } } #undef BUFFER_LENGTH_THRESHOLD const char *strnchr(const char *buffer, int c, size_t length) { for (size_t i=0; i lower_b) return 1; ++a; ++b; } return 0; } const char *string::NULL_STRING = "\0"; string::string() { } string::string(const char *ptr) : vec(ptr, ptr+strlen(ptr)+1) { } string::string(const char *ptr, size_t len) : vec(ptr, ptr+len) { } string::string(const string& other) : vec(other.vec) { } string::~string() { } string &string::operator=(const string &other) { vec = other.vec; return *this; } string &string::operator+=(const string &other) { append(other); return *this; } void string::append(const string &other) { for (size_type i=0; i other.size()) return false; for (size_type i=0; i other.vec[i]) return false; if (vec[i] < other.vec[i]) return true; } return false; } bool string::operator<=(const string &other) const { if (size() < other.size()) return true; if (size() > other.size()) return false; for (size_type i=0; i other.vec[i]) return false; if (vec[i] < other.vec[i]) return true; } return true; } char &string::operator[](unsigned int i) { return vec[i]; } char string::operator[](unsigned int i) const { return vec[i]; } void string::push_back(char c) { vec.push_back(c); } void string::pop_back() { vec.pop_back(); } const char *string::c_str() const { if (vec.empty()) return NULL_STRING; else return vec.begin(); } const char *string::data() const { return vec.begin(); } char *string::begin() { return vec.begin(); } char *string::end() { return vec.end(); } const char *string::begin() const { return vec.begin(); } const char *string::end() const { return vec.end(); } string::size_type string::len() const { return size(); } string::size_type string::size() const { return vec.size(); } string::size_type string::max_size() const { return vec.max_size(); } void string::resize(string::size_type size) { vec.resize(size); } string::size_type string::capacity() const { return vec.capacity(); } void string::reserve(string::size_type size) { vec.reserve(size); } void string::clear() { vec.clear(); } bool string::empty() const { return vec.size() == 0; } void string::swap(string &other) { vec.swap(other.vec); } char string::at(unsigned int i) const { return vec[i]; } char &string::at(unsigned int i) { return vec[i]; } char string::front() const { return vec[0]; } char &string::front() { return vec[0]; } char string::back() const { return vec.back(); } char &string::back() { return vec.back(); } char *string::release() { return vec.release(); } } april-ann-0.4.1/packages/basics/util/c_src/mystring.h000066400000000000000000000042041263004425400225120ustar00rootroot00000000000000#ifndef STRING_H #define STRING_H #include #include "vector.h" namespace AprilUtils { size_t strnspn(const char *buffer, size_t buffer_length, const char *accept, size_t accept_length); size_t strncspn(const char *buffer, size_t buffer_length, const char *reject, size_t reject_length); const char *strnchr(const char *buffer, int c, size_t length); const char *strncchr(const char *buffer, int c, size_t length); int strcmpi(const char *a, const char *b); class string { static const char *NULL_STRING; public: typedef char value_type; typedef vector container; typedef char& reference; typedef const char& const_reference; typedef container::iterator iterator; typedef container::const_iterator const_iterator; typedef container::difference_type difference_type; typedef container::size_type size_type; private: vector vec; public: string(); string(const char *ptr); string(const char *ptr, size_t len); string(const string& other); ~string(); string &operator=(const string &other); string &operator+=(const string &other); void append(const string &other); operator const char *() const { return c_str(); } bool operator==(const string &other) const; bool operator<(const string &other) const; bool operator<=(const string &other) const; char &operator[](unsigned int i); char operator[](unsigned int i) const; void push_back(char c); void pop_back(); const char *c_str() const; const char *data() const; char *begin(); char *end(); const char *begin() const; const char *end() const; size_type len() const; size_type size() const; size_type max_size() const; void resize(size_type size); size_type capacity() const; void reserve(size_type size); void clear(); bool empty() const; void swap(string &other); char at(unsigned int i) const; char &at(unsigned int i); char front() const; char &front(); char back() const; char &back(); char *release(); }; } #endif // STRING_H april-ann-0.4.1/packages/basics/util/c_src/null_types.h000066400000000000000000000017671263004425400230470ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef NULL_TYPE_H #define NULL_TYPE_H namespace AprilUtils { class NullType {}; template class NullContainer {}; } #endif april-ann-0.4.1/packages/basics/util/c_src/omp_utils.cc000066400000000000000000000020231263004425400230040ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "omp_utils.h" namespace OMPUtils { int get_num_threads() { int n; #ifndef NO_OMP n = omp_get_max_threads(); // WARNING!!! max_threads instead of num_threads #else n = 1; #endif return n; } } april-ann-0.4.1/packages/basics/util/c_src/omp_utils.h000066400000000000000000000020211263004425400226440ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef OMP_UTILS_H #define OMP_UTILS_H #ifndef NO_OMP extern "C" { #include } #endif /// Utilities related with Open-MP parallelization. namespace OMPUtils { int get_num_threads(); } #endif // OMP_UTILS_H april-ann-0.4.1/packages/basics/util/c_src/open_addressing_hash.h000066400000000000000000000336111263004425400250110ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef OPEN_ADDR_HASH_H #define OPEN_ADDR_HASH_H /* Tabla hash con direccionamiento abierto SIN timestamps ni otras flotituras. Se utiliza un vector para guardar directamente los valores. Cuando se busca un valor, se utiliza la función de dispersión para obtener 2 valores: el indice en el vector y un offset para ir avanzando (modulo talla del vector) mientras las posiciones consultadas esten ocupadas por valores distintos del elemento buscado. La busqueda finaliza cuando se encuentra una posición libre o bien el elemento buscado. Es una plantilla y se especializa pasandole el tipo de clave y valor, asi como mecanismos para dispersar una clave, compararla con otra y ver si esta vacia. Los tipos de datos para los campos clave y valor asumen que el operador de copia funciona suficientemente bien como para que al "machacar" una posición del vector con un valor nuevo, el valor anterior se libere convenientemente. Tambien se asume que ambos tipos de datos tienen constructores por defecto. No se puede asumir que un valor estara siempre en la misma posicion, al menos tras realizar inserciones, puesto que vamos a implementar rehashing. No existe la operacion "erase" para borrar individualmente una entrada. */ #include // ceilf #include // ptrdiff_t, size_t... #include "aux_hash_table.h" #include "pair.h" namespace AprilUtils { // HashFcn es del tipo: // struct hash_fcn { // unsigned int operator()(const KeyType &value) const { // ... // } // }; // EqualKey es del tipo: // struct eqstr { // bool operator()(const KeyType &valueA, const KeyType &valueB) const { // ... // } // }; template , typename EqualKey = default_equality_comparison_function > class open_addr_hash { public: typedef pair node; typedef KeyType key_type; typedef DataType data_type; typedef pair value_type; typedef value_type& reference; typedef const reference const_reference; typedef value_type* pointer; typedef ptrdiff_t difference_type; typedef size_t size_type; private: int first_power_of_2(int value); // auxiliary function node *buckets; // vector of nodes int num_buckets;// a power of 2 int hash_mask; // useful to do "& hash_mask" instead of "% num_buckets" int the_size; // number of inserted elements int rehash_threshold; float max_load_factor; // for rehashing purposes, MUST BE <1.0 HashFcn hash_function; EqualKey equal_key; KeyType empty_key; public: open_addr_hash(KeyType empty_key, int nbckts=8, float mxloadf=0.75); // constructor open_addr_hash(const open_addr_hash&); // copy constructor ~open_addr_hash(); // destructor open_addr_hash& operator=(const open_addr_hash&); // assignment operator void clear(); // Erases all of the elements. data_type* find(const key_type& k); const value_type* find_pair(const key_type& k) const; bool search(const key_type& k) const { return const_cast(find_pair(k)) != 0; } data_type& operator[] (const key_type& k); void insert(const key_type& k, const data_type& d) { (*this)[k] = d; } void resize(int n); // rehash, num_buckets at least n after resize int bucket_count() const { // Returns the number of buckets used by the hash return num_buckets; } int size() const { // Returns the size of the hash return the_size; } bool empty() const { return the_size == 0; } class const_iterator; class iterator { friend class const_iterator; friend class open_addr_hash; open_addr_hash *h; int index; iterator(open_addr_hash *h, int index): h(h), index(index) {} public: typedef KeyType key_type; typedef DataType data_type; typedef pair value_type; typedef value_type& reference; typedef const reference const_reference; typedef value_type* pointer; typedef ptrdiff_t difference_type; typedef size_t size_type; iterator(): h(0), index(0) {} iterator(const iterator &other): h(other.h), index(other.index) {} iterator& operator=(const iterator &other) { if (&other != this) { h = other.h; index = other.index; } return *this; } iterator& operator++() { // preincrement // asumimos que no se incrementa un iterador con // index>=num_buckets do { index++; } while (indexnum_buckets && h->equal_key(h->buckets[index].first,h->empty_key)); return *this; } iterator operator++(int) { // postincrement iterator tmp(*this); ++(*this); return tmp; } value_type& operator *() { //dereference return h->buckets[index]; } value_type* operator ->() { return &(h->buckets[index]); } bool operator == (const iterator &other) { return ((index == other.index) && (h == other.h)); } bool operator != (const iterator &other) { return ((index != other.index) || (h != other.h)); } }; class const_iterator { friend class open_addr_hash; const open_addr_hash *h; int index; const_iterator(open_addr_hash *h, int index): h(h), index(index) {} public: typedef KeyType key_type; typedef DataType data_type; typedef pair value_type; typedef value_type& reference; typedef const reference const_reference; typedef value_type* pointer; typedef ptrdiff_t difference_type; typedef size_t size_type; const_iterator(): h(0), index(0) {} // Copy constructor (from iterator and const_iterator) const_iterator(const iterator &other): h(other.h), index(other.index) {} const_iterator(const const_iterator &other): h(other.h), index(other.index) {} // Assignment operators const_iterator& operator=(const iterator &other) { h = other.h; index = other.index; } const_iterator& operator=(const const_iterator &other) { h = other.h; index = other.index; } const_iterator& operator++() { // preincrement // asumimos que no se incrementa un iterador con // index>=num_buckets do { index++; } while (indexnum_buckets && h->equal_key(h->buckets[index].first,h->empty_key)); return *this; } const_iterator operator++(int) { // postincrement const_iterator tmp(*this); ++(*this); return tmp; } const value_type& operator *() { //dereference return h->buckets[index]; } const value_type* operator ->() { return &(h->buckets[index]); } // Eq comparisons bool operator == (const iterator &other) { return ((index == other.index) && (h == other.h)); } bool operator == (const const_iterator &other) { return ((index == other.index) && (h == other.h)); } bool operator != (const iterator &other) { return ((index != other.index) || (h != other.h)); } bool operator != (const const_iterator &other) { return ((index != other.index) || (h != other.h)); } }; iterator begin() { int i=0; while (i int open_addr_hash::first_power_of_2(int value) { int result = 4; // ojito, minimo 4. TODO: se queda este valor? while (result < value) result += result; return result; } template open_addr_hash::open_addr_hash(ky empty_key, int nbckts, float mxloadf) { this->empty_key = empty_key; num_buckets = first_power_of_2(nbckts); hash_mask = num_buckets-1; // num_buckets is a power of 2 the_size = 0; max_load_factor = (mxloadf <= 0.9) ? mxloadf : 0.9; // must be <1 rehash_threshold= (int)ceilf(max_load_factor*num_buckets); end_iterator = iterator(this, num_buckets); buckets = reinterpret_cast(new pair[num_buckets]); for (int i=0; i(&buckets[i].first) = empty_key; } template open_addr_hash::open_addr_hash(const open_addr_hash& other) { // copy constructor num_buckets = other.num_buckets; hash_mask = other.hash_mask; the_size = other.the_size; max_load_factor = other.max_load_factor; rehash_threshold= other.rehash_threshold; buckets = new node[num_buckets]; for (int i=0; i void open_addr_hash::clear() { for (int i=0; i(&buckets[i].first) = empty_key; the_size = 0; } template open_addr_hash& open_addr_hash::operator=(const open_addr_hash& other) { // The assignment operator if (this != &other) { if (num_buckets != other.num_buckets) { delete[] buckets; num_buckets = other.num_buckets; buckets = new node[num_buckets]; } hash_mask = other.hash_mask; the_size = other.the_size; max_load_factor = other.max_load_factor; rehash_threshold= other.rehash_threshold; for (int i=0; i open_addr_hash::~open_addr_hash() { // destructor delete[] buckets; } template dt* open_addr_hash::find(const ky& k) { value_type* p = const_cast(find_pair(k)); return p ? &(p->second) : 0; } template const pair* open_addr_hash::find_pair(const ky& k) const { unsigned int hfval = hash_function(k); unsigned int index = hfval & hash_mask; unsigned int step = (hfval >> 15) | 1; // debe ser impar while (!equal_key(buckets[index].first,empty_key)) { if (equal_key(buckets[index].first,k)) return &(buckets[index]); index = (index + step) & hash_mask; } return 0; } template dt& open_addr_hash::operator[] (const ky& k) { unsigned int hfval = hash_function(k); unsigned int index = hfval & hash_mask; unsigned int step = (hfval >> 15) | 1; // debe ser impar while (!equal_key(buckets[index].first,empty_key)) { if (equal_key(buckets[index].first,k)) return buckets[index].second; index = (index + step) & hash_mask; } the_size++; if (the_size >= rehash_threshold) { resize(2*num_buckets); // recalcular index sabiendo que no esta, hfval ya lo tenemos index = hfval & hash_mask; step = (hfval >> 15) | 1; while (!equal_key(buckets[index].first,empty_key)) index = (index + step) & hash_mask; } *const_cast(&buckets[index].first) = k; return buckets[index].second; } template void open_addr_hash::resize(int n) { n = first_power_of_2(n); if (n != num_buckets) { node *old_buckets = buckets; int old_num_buckets = num_buckets; num_buckets = n; end_iterator= iterator(this, num_buckets); hash_mask = n-1; rehash_threshold= (int)ceilf(max_load_factor*num_buckets); buckets = reinterpret_cast(new pair[num_buckets]); for (int i=0; i(&buckets[i].first) = empty_key; for (int i=0; i> 15) | 1; // debe ser impar while (!equal_key(buckets[index].first,empty_key)) { index = (index + step) & hash_mask; } *const_cast(&buckets[index].first) = old_buckets[i].first; buckets[index].second = old_buckets[i].second; } delete[] old_buckets; } } } // namespace AprilUtils #endif // OPEN_ADDR_HASH_H april-ann-0.4.1/packages/basics/util/c_src/open_addressing_hash_timestamp.h000066400000000000000000000354041263004425400270760ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef OPEN_ADDR_HASH_TIMESTAMP_H #define OPEN_ADDR_HASH_TIMESTAMP_H /* Tabla hash con direccionamiento abierto y timestamps Se utiliza un vector para guardar directamente los valores. Cuando se busca un valor, se utiliza la función de dispersión para obtener 2 valores: el indice en el vector y un offset para ir avanzando (modulo talla del vector) mientras las posiciones consultadas esten ocupadas por valores distintos del elemento buscado. La busqueda finaliza cuando se encuentra una posición libre o bien el elemento buscado. La forma de saber si una posición esta ocupada es comprobar el campo stamp. De esta forma se pueden borrar TODOS los elementos del vector en O(1). Nótese que NO se borran efectivamente esos elementos, no se llama a su destructor. Los tipos de datos para los campos clave y valor asumen que el operador de copia funciona suficientemente bien como para que al "machacar" una posición del vector con un valor nuevo, el valor anterior se libere convenientemente. También se asume que ambos tipos de datos tienen constructores por defecto. No se puede asumir que un valor estará siempre en la misma posición, al menos tras realizar inserciones, puesto que vamos a implementar rehashing. No existe la operacion erase para borrar individualmente una entrada. */ #include // ceilf #include // ptrdiff_t, size_t... #include "pair.h" #include "aux_hash_table.h" namespace AprilUtils { // HashFcn es del tipo: // struct hash_fcn { // unsigned int operator()(const char* s1) const { // return blah...; // } // }; // EqualKey es del tipo: // struct eqstr { // bool operator()(const char* s1, const char* s2) const { // return strcmp(s1, s2) == 0; // } // }; template , typename EqualKey = default_equality_comparison_function > class open_addr_hash_timestamp { public: struct node { pair value; int stamp; node(): value(KeyType(), DataType()) {} node(KeyType& k, DataType& d, int stmp): value(k,d), stamp(stmp) {} }; typedef KeyType key_type; typedef DataType data_type; typedef pair value_type; typedef value_type& reference; typedef const reference const_reference; typedef value_type* pointer; typedef ptrdiff_t difference_type; typedef size_t size_type; private: node *buckets; // vector of nodes int num_buckets;// a power of 2 int hash_mask; // useful to do "& hash_mask" instead of "% num_buckets" int the_size; int rehash_threshold; float max_load_factor; // for rehashing purposes, MUST BE <1.0 int current_stamp; static const int max_stamp = 1<<30; int first_power_of_2(int value);// auxiliary function HashFcn hash_function; EqualKey equal_key; public: open_addr_hash_timestamp(int nbckts=8, float mxloadf=0.75); // constructor open_addr_hash_timestamp(const open_addr_hash_timestamp&); // copy constructor ~open_addr_hash_timestamp(); // destructor open_addr_hash_timestamp& operator=(const open_addr_hash_timestamp&); // assignment operator void clear(); // Erases all of the elements. data_type* find(const key_type& k); const value_type* find_pair(const key_type& k) const; bool search(const key_type& k) const { return find_pair(k) != 0; } data_type& operator[] (const key_type& k); void insert(const key_type& k, const data_type& d) { (*this)[k] = d; } void resize(int n); // rehash, num_buckets at least n after resize int bucket_count() const { // Returns the number of buckets used by the hash return num_buckets; } int size() const { // Returns the size of the hash return the_size; } bool empty() const { return the_size == 0; } class const_iterator; class iterator { friend class const_iterator; friend class open_addr_hash_timestamp; open_addr_hash_timestamp *h; int index; iterator(open_addr_hash_timestamp *h, int index): h(h), index(index) {} public: typedef KeyType key_type; typedef DataType data_type; typedef pair value_type; typedef value_type& reference; typedef const reference const_reference; typedef value_type* pointer; typedef ptrdiff_t difference_type; typedef size_t size_type; iterator(): h(0), index(0) {} iterator(const iterator &other): h(other.h), index(other.index) {} iterator& operator=(const iterator &other) { if (&other != this) { h = other.h; index = other.index; } return *this; } iterator& operator++() { // preincrement // asumimos que no se incrementa un iterador con // index>=num_buckets do { index++; } while (indexnum_buckets && h->buckets[index].stamp != h->current_stamp); return *this; } iterator operator++(int) { // postincrement iterator tmp(*this); ++(*this); return tmp; } value_type& operator *() { //dereference return h->buckets[index].value; } value_type* operator ->() { return &(h->buckets[index].value); } bool operator == (const iterator &other) { return ((index == other.index) && (h == other.h)); } bool operator != (const iterator &other) { return ((index != other.index) || (h != other.h)); } }; class const_iterator { friend class open_addr_hash_timestamp; const open_addr_hash_timestamp *h; int index; const_iterator(open_addr_hash_timestamp *h, int index): h(h), index(index) {} public: typedef KeyType key_type; typedef DataType data_type; typedef pair value_type; typedef value_type& reference; typedef const reference const_reference; typedef value_type* pointer; typedef ptrdiff_t difference_type; typedef size_t size_type; const_iterator(): h(0), index(0) {} // Copy constructor (from iterator and const_iterator) const_iterator(const iterator &other): h(other.h), index(other.index) {} const_iterator(const const_iterator &other): h(other.h), index(other.index) {} // Assignment operators const_iterator& operator=(const iterator &other) { h = other.h; index = other.index; } const_iterator& operator=(const const_iterator &other) { h = other.h; index = other.index; } const_iterator& operator++() { // preincrement // asumimos que no se incrementa un iterador con // index>=num_buckets do { index++; } while (indexnum_buckets && h->buckets[index].stamp != h->current_stamp); return *this; } const_iterator operator++(int) { // postincrement const_iterator tmp(*this); ++(*this); return tmp; } const value_type& operator *() { //dereference return h->buckets[index].value; } const value_type* operator ->() { return &(h->buckets[index].value); } // Eq comparisons bool operator == (const iterator &other) { return ((index == other.index) && (h == other.h)); } bool operator == (const const_iterator &other) { return ((index == other.index) && (h == other.h)); } bool operator != (const iterator &other) { return ((index != other.index) || (h != other.h)); } bool operator != (const const_iterator &other) { return ((index != other.index) || (h != other.h)); } }; iterator begin() { int i=0; while (i int open_addr_hash_timestamp::first_power_of_2(int value) { int result = 4; // ojito, minimo 4. TODO: se queda este valor? while (result < value) result += result; return result; } template open_addr_hash_timestamp::open_addr_hash_timestamp(int nbckts, float mxloadf) { num_buckets = first_power_of_2(nbckts); hash_mask = num_buckets-1; // num_buckets is a power of 2 the_size = 0; max_load_factor = (mxloadf <= 0.9) ? mxloadf : 0.9; // must be <1 rehash_threshold= (int)ceilf(max_load_factor*num_buckets); end_iterator = iterator(this, num_buckets); current_stamp = 1; // buckets = reinterpret_cast(new pair[num_buckets]); buckets = reinterpret_cast(new node[num_buckets]); for (int i=0; i open_addr_hash_timestamp::open_addr_hash_timestamp(const open_addr_hash_timestamp& other) { // copy constructor num_buckets = other.num_buckets; hash_mask = other.hash_mask; the_size = other.the_size; max_load_factor = other.max_load_factor; rehash_threshold= other.rehash_threshold; current_stamp = other.current_stamp; buckets = new node[num_buckets]; for (int i=0; i void open_addr_hash_timestamp::clear() { // Erases all of the elements. if (current_stamp >= max_stamp) { for (int i=0; i open_addr_hash_timestamp& open_addr_hash_timestamp::operator=(const open_addr_hash_timestamp& other) { // The assignment operator if (this != &other) { if (num_buckets != other.num_buckets) { delete[] buckets; num_buckets = other.num_buckets; buckets = new node[num_buckets]; } hash_mask = other.hash_mask; the_size = other.the_size; max_load_factor = other.max_load_factor; rehash_threshold= other.rehash_threshold; current_stamp = other.current_stamp; for (int i=0; i open_addr_hash_timestamp::~open_addr_hash_timestamp() { // destructor delete[] buckets; } template dt* open_addr_hash_timestamp::find(const ky& k) { value_type* p = const_cast(find_pair(k)); return p ? &(p->second) : 0; } template const pair* open_addr_hash_timestamp::find_pair(const ky& k) const { unsigned int hfval = hash_function(k); unsigned int index = hfval & hash_mask; unsigned int step = (hfval >> 15) | 1; // debe ser impar while (buckets[index].stamp == current_stamp) { if (equal_key(buckets[index].value.first,k)) return &(buckets[index].value); index = (index + step) & hash_mask; } return 0; } template dt& open_addr_hash_timestamp::operator[] (const ky& k) { unsigned int hfval = hash_function(k); unsigned int index = hfval & hash_mask; unsigned int step = (hfval >> 15) | 1; // debe ser impar while (buckets[index].stamp == current_stamp) { if (equal_key(buckets[index].value.first,k)) return buckets[index].value.second; index = (index + step) & hash_mask; } the_size++; if (the_size >= rehash_threshold) { resize(2*num_buckets); // recalcular index sabiendo que no esta, hfval ya lo tenemos index = hfval & hash_mask; step = (hfval >> 15) | 1; while (buckets[index].stamp == current_stamp) index = (index + step) & hash_mask; } buckets[index].stamp = current_stamp; *((ky *)(&buckets[index].value.first)) = k; buckets[index].value.second = dt(); return buckets[index].value.second; } template void open_addr_hash_timestamp::resize(int n) { n = first_power_of_2(n); if (n != num_buckets) { node *old_buckets = buckets; int old_num_buckets= num_buckets; int old_stamp = current_stamp; num_buckets = n; end_iterator= iterator(this, num_buckets); hash_mask = n-1; rehash_threshold= (int)ceilf(max_load_factor*num_buckets); buckets = new node[num_buckets]; for (int i=0; i> 15) | 1; // debe ser impar while (buckets[index].stamp == current_stamp) { index = (index + step) & hash_mask; } buckets[index].stamp = current_stamp; *const_cast(&buckets[index].value.first) = old_buckets[i].value.first; buckets[index].value.second = old_buckets[i].value.second; //buckets[index].value = old_buckets[i].value; } delete[] old_buckets; } } } // namespace AprilUtils #endif // OPEN_ADDR_HASH_TIMESTAMP_H april-ann-0.4.1/packages/basics/util/c_src/open_addressing_hash_with_fast_iterator.h000066400000000000000000000364721263004425400310020ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef OPEN_ADDR_HASH_FAST_IT_H #define OPEN_ADDR_HASH_FAST_IT_H /* Tabla hash con direccionamiento abierto y timestamps Se utiliza un vector para guardar directamente los valores. Cuando se busca un valor, se utiliza la función de dispersión para obtener 2 valores: el indice en el vector y un offset para ir avanzando (modulo talla del vector) mientras las posiciones consultadas esten ocupadas por valores distintos del elemento buscado. La busqueda finaliza cuando se encuentra una posición libre o bien el elemento buscado. La forma de saber si una posición esta ocupada es comprobar el campo stamp. De esta forma se pueden borrar TODOS los elementos del vector en O(1). Nótese que NO se borran efectivamente esos elementos, no se llama a su destructor. Los tipos de datos para los campos clave y valor asumen que el operador de copia funciona suficientemente bien como para que al "machacar" una posición del vector con un valor nuevo, el valor anterior se libere convenientemente. También se asume que ambos tipos de datos tienen constructores por defecto. No se puede asumir que un valor estará siempre en la misma posición, al menos tras realizar inserciones, puesto que vamos a implementar rehashing. No existe la operacion erase para borrar individualmente una entrada. */ #include "aux_hash_table.h" #include // ceilf #include // ptrdiff_t, size_t... #include "pair.h" namespace AprilUtils { // HashFcn es del tipo: // struct hash_fcn { // unsigned int operator()(const char* s1) const { // return blah...; // } // }; // EqualKey es del tipo: // struct eqstr { // bool operator()(const char* s1, const char* s2) const { // return strcmp(s1, s2) == 0; // } // }; template , typename EqualKey = default_equality_comparison_function > class open_addr_hash_fast_it { public: struct node { pair value; int stamp; node() : value(KeyType(), DataType()) {} node(KeyType& k, DataType& d, int stmp): value(k,d), stamp(stmp) {} }; typedef KeyType key_type; typedef DataType data_type; typedef pair value_type; typedef value_type& reference; typedef const value_type const_value; typedef const_value& const_reference; typedef value_type* pointer; typedef ptrdiff_t difference_type; typedef size_t size_type; private: node *buckets; // vector of nodes // // FIXME: ESTO DEBE SER PRIVADO!!! public: int *iterator_vector; // vector para poder iterar de forma // eficiente sobre los elementos de la tabla private: // int num_buckets;// a power of 2 int hash_mask; // useful to do "& hash_mask" instead of "% num_buckets" int rehash_threshold; float max_load_factor; // for rehashing purposes, MUST BE <1.0 int current_stamp; static const int max_stamp = 1<<30; int first_power_of_2(int value);// auxiliary function HashFcn hash_function; EqualKey equal_key; public: open_addr_hash_fast_it(int nbckts=8, float mxloadf=0.75); // constructor open_addr_hash_fast_it(const open_addr_hash_fast_it&); // copy constructor ~open_addr_hash_fast_it(); // destructor open_addr_hash_fast_it& operator=(const open_addr_hash_fast_it&); // assignment operator void clear(); // Erases all of the elements. data_type* find(const key_type& k); const value_type* find_pair(const key_type& k) const; bool search(const key_type& k) const { return find_pair(k) != 0; } data_type& operator[] (const key_type& k); void insert(const key_type& k, const data_type& d) { (*this)[k] = d; } void resize(int n); // rehash, num_buckets at least n after resize int bucket_count() const { // Returns the number of buckets used by the hash return num_buckets; } int size() const { // Returns the size of the hash return the_size; } bool empty() const { return the_size == 0; } class const_iterator; class iterator { friend class const_iterator; friend class open_addr_hash_fast_it; open_addr_hash_fast_it *h; int index; iterator(open_addr_hash_fast_it *h, int index): h(h), index(index) {} public: typedef KeyType key_type; typedef DataType data_type; typedef pair value_type; typedef value_type& reference; typedef const value_type const_value; typedef const_value& const_reference; typedef value_type* pointer; typedef ptrdiff_t difference_type; typedef size_t size_type; iterator(): h(0), index(0) {} iterator(const iterator &other): h(other.h), index(other.index) {} iterator& operator=(const iterator &other) { if (&other != this) { h = other.h; index = other.index; } return *this; } iterator& operator++() { // preincrement index++; return *this; } iterator operator++(int) { // postincrement iterator tmp(*this); ++(*this); return tmp; } value_type& operator *() { //dereference // return h->buckets[h->iterator_vector[index]].value; // } value_type* operator ->() { // return &(h->buckets[h->iterator_vector[index]].value); // } bool operator == (const iterator &other) { return ((index == other.index) && (h == other.h)); } bool operator != (const iterator &other) { return ((index != other.index) || (h != other.h)); } }; class const_iterator { friend class open_addr_hash_fast_it; const open_addr_hash_fast_it *h; int index; const_iterator(open_addr_hash_fast_it *h, int index): h(h), index(index) {} public: typedef KeyType key_type; typedef DataType data_type; typedef pair value_type; typedef value_type& reference; typedef const value_type const_value; typedef const_value& const_reference; typedef value_type* pointer; typedef ptrdiff_t difference_type; typedef size_t size_type; const_iterator(): h(0), index(0) {} // Copy constructor (from iterator and const_iterator) const_iterator(const iterator &other): h(other.h), index(other.index) {} const_iterator(const const_iterator &other): h(other.h), index(other.index) {} // Assignment operators const_iterator& operator=(const iterator &other) { h = other.h; index = other.index; } const_iterator& operator=(const const_iterator &other) { h = other.h; index = other.index; } const_iterator& operator++() { // preincrement index++; return *this; } const_iterator operator++(int) { // postincrement const_iterator tmp(*this); ++(*this); return tmp; } const value_type& operator *() { //dereference // return h->buckets[h->iterator_vector[index]].value; // } const value_type* operator ->() { // return &(h->buckets[h->iterator_vector[index]].value); // } // Eq comparisons bool operator == (const iterator &other) { return ((index == other.index) && (h == other.h)); } bool operator == (const const_iterator &other) { return ((index == other.index) && (h == other.h)); } bool operator != (const iterator &other) { return ((index != other.index) || (h != other.h)); } bool operator != (const const_iterator &other) { return ((index != other.index) || (h != other.h)); } }; iterator begin() { return iterator(this, 0); } private: iterator end_iterator; int &the_size; public: iterator& end() { //end_iterator = iterator(this, the_size); return end_iterator; } }; template int open_addr_hash_fast_it::first_power_of_2(int value) { int result = 4; // ojito, minimo 4. TODO: se queda este valor? while (result < value) result += result; return result; } template open_addr_hash_fast_it::open_addr_hash_fast_it(int nbckts, float mxloadf) : end_iterator(this, 0), the_size(end_iterator.index) { num_buckets = first_power_of_2(nbckts); hash_mask = num_buckets-1; // num_buckets is a power of 2 the_size = 0; max_load_factor = (mxloadf <= 0.9) ? mxloadf : 0.9; // must be <1 rehash_threshold= (int)ceilf(max_load_factor*num_buckets); // end_iterator = iterator(this, 0); current_stamp = 1; buckets = new node[num_buckets]; for (int i=0; i open_addr_hash_fast_it::open_addr_hash_fast_it(const open_addr_hash_fast_it& other) : end_iterator(this, other.the_size), the_size(end_iterator.index) { // copy constructor num_buckets = other.num_buckets; hash_mask = other.hash_mask; the_size = other.the_size; max_load_factor = other.max_load_factor; rehash_threshold= other.rehash_threshold; current_stamp = other.current_stamp; buckets = new node[num_buckets]; for (int i=0; i void open_addr_hash_fast_it::clear() { // Erases all of the elements. if (current_stamp >= max_stamp) { for (int i=0; i open_addr_hash_fast_it& open_addr_hash_fast_it::operator=(const open_addr_hash_fast_it& other) { // The assignment operator if (this != &other) { hash_mask = other.hash_mask; // the_size = other.the_size; max_load_factor = other.max_load_factor; rehash_threshold= other.rehash_threshold; current_stamp = other.current_stamp; if (num_buckets != other.num_buckets) { delete[] buckets; num_buckets = other.num_buckets; buckets = new node[num_buckets]; // delete[] iterator_vector; iterator_vector = new int[rehash_threshold+1]; // } for (int i=0; i open_addr_hash_fast_it::~open_addr_hash_fast_it() { // destructor delete[] buckets; // delete[] iterator_vector; // } template dt* open_addr_hash_fast_it::find(const ky& k) { value_type* p = const_cast(find_pair(k)); return p ? &(p->second) : 0; } template const pair * open_addr_hash_fast_it::find_pair(const ky& k) const { unsigned int hfval = hash_function(k); unsigned int index = hfval & hash_mask; unsigned int step = (hfval >> 15) | 1; // debe ser impar while (buckets[index].stamp == current_stamp) { if (equal_key(buckets[index].value.first,k)) return &(buckets[index].value); index = (index + step) & hash_mask; } return 0; } template dt& open_addr_hash_fast_it::operator[] (const ky& k) { unsigned int hfval = hash_function(k); unsigned int index = hfval & hash_mask; unsigned int step = (hfval >> 15) | 1; // debe ser impar while (buckets[index].stamp == current_stamp) { if (equal_key(buckets[index].value.first,k)) return buckets[index].value.second; index = (index + step) & hash_mask; } ++the_size; if (the_size >= rehash_threshold) { resize(num_buckets<<1); // recalcular index sabiendo que no esta, hfval ya lo tenemos index = hfval & hash_mask; step = (hfval >> 15) | 1; while (buckets[index].stamp == current_stamp) index = (index + step) & hash_mask; } // iterator_vector[the_size-1] = index; // buckets[index].stamp = current_stamp; *const_cast(&buckets[index].value.first) = k; return buckets[index].value.second; } template void open_addr_hash_fast_it::resize(int n) { n = first_power_of_2(n); if (n != num_buckets) { node *old_buckets = buckets; int old_num_buckets= num_buckets; int old_stamp = current_stamp; num_buckets = n; hash_mask = n-1; rehash_threshold= (int)ceilf(max_load_factor*num_buckets); // delete[] iterator_vector; iterator_vector = new int[rehash_threshold+1]; // buckets = new node[num_buckets]; for (int i=0; i> 15) | 1; // debe ser impar while (buckets[index].stamp == current_stamp) { index = (index + step) & hash_mask; } buckets[index].stamp = current_stamp; *const_cast(&buckets[index].value.first) = old_buckets[i].value.first; buckets[index].value.second = old_buckets[i].value.second; // iterator_vector[it_vector_pos] = index; it_vector_pos++; // } delete[] old_buckets; } } } // namespace AprilUtils #endif // OPEN_ADDR_HASH_FAST_IT_H april-ann-0.4.1/packages/basics/util/c_src/pair.h000066400000000000000000000057061263004425400216010ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef PAIR_H #define PAIR_H #include "null_types.h" namespace AprilUtils { template struct pair { T1 first; T2 second; typedef T1 first_type; typedef T2 second_type; // Constructors pair() : first(T1()), second(T2()) {} pair(const T1& first, const T2& second): first(first), second(second) {} pair(const pair &other): first(other.first), second(other.second) {} pair& operator=(const pair& other) { if (&other != this) { first = other.first; second = other.second; } return (*this); } }; template bool operator== (const pair& x, const pair& y) { return ((x.first == y.first) && (x.second == y.second)); } template bool operator< (const pair& x, const pair& y) { return (( x.first < y.first) || ((x.first == y.first) && (x.second < y.second))); } //---------------------------------------------------------------------- // especializacion para NullType //---------------------------------------------------------------------- template struct pair { T1 first; static NullType second; typedef T1 first_type; typedef NullType second_type; // Constructors pair() {} pair(const T1& first, const NullType&): first(first) {} pair(const pair &other): first(other.first) {} pair& operator=(const pair& other) { if (&other != this) { first = other.first; } return (*this); } }; template bool operator== (const pair& x, const pair& y) { return (x.first == y.first); } template bool operator< (const pair& x, const pair& y) { return (x.first < y.first); } template NullType pair::second; template inline pair make_pair(const first& _X, const second& _Y) { return pair(_X,_Y); } } #endif // PAIR_H april-ann-0.4.1/packages/basics/util/c_src/popen2.cc000066400000000000000000000030601263004425400221760ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "popen2.h" #define READ 0 #define WRITE 1 namespace AprilUtils { pid_t popen2(const char *command, int *infp, int *outfp) { int p_stdin[2], p_stdout[2]; pid_t pid; if (pipe(p_stdin) != 0 || pipe(p_stdout) != 0) return -1; pid = fork(); if (pid < 0) { return pid; } else if (pid == 0) { // el hijo close(p_stdin[WRITE]); dup2(p_stdin[READ], READ); close(p_stdout[READ]); dup2(p_stdout[WRITE], WRITE); execl("/bin/sh", "sh", "-c", command, NULL); perror("execl"); exit(1); } close(p_stdin[READ]); close(p_stdout[WRITE]); *infp = p_stdin[WRITE]; *outfp = p_stdout[READ]; return pid; } } april-ann-0.4.1/packages/basics/util/c_src/popen2.h000066400000000000000000000021251263004425400220410ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef POPEN2_H #define POPEN2_H #include #include #include #include #include namespace AprilUtils { pid_t popen2(const char *command, int *infp, int *outfp); } #endif // POPEN2_H april-ann-0.4.1/packages/basics/util/c_src/ptr_ref.h000066400000000000000000000055251263004425400223060ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef PTR_REF_H #define PTR_REF_H #include "error_print.h" #include "referenced.h" #include "unused_variable.h" namespace AprilUtils { /** * Default reference template, uses IncRef. */ template struct DefaultReferencer { DefaultReferencer() { } DefaultReferencer(const DefaultReferencer &) { } void operator()(T *ptr) const { if (ptr != 0) IncRef(ptr); } void checkUnique(T *ptr) const { if (ptr != 0 && ptr->getRef() != 1) { ERROR_EXIT(128, "checkUnique test failure\n"); } } }; /** * Default deleter template, uses DecRef. */ template struct DefaultDeleter { DefaultDeleter() { } DefaultDeleter(const DefaultDeleter &) { } void operator()(T *ptr) const { if (ptr != 0) DecRef(ptr); } }; /** * Standard referencer template, does nothing. */ template struct StandardReferencer { StandardReferencer() { } StandardReferencer(const StandardReferencer &) { } void operator()(T *ptr) const { UNUSED_VARIABLE(ptr); } void checkUnique(T *ptr) const { UNUSED_VARIABLE(ptr); } }; /** * Standard referencer template specialization for new[]. */ template struct StandardReferencer { StandardReferencer() { } StandardReferencer(const StandardReferencer &) { } void operator()(T *ptr) const { UNUSED_VARIABLE(ptr); } void checkUnique(T *ptr) const { UNUSED_VARIABLE(ptr); } }; /** * Standard deleter template, uses delete. */ template struct StandardDeleter { StandardDeleter() { } StandardDeleter(const StandardDeleter &) { } void operator()(T *ptr) const { delete ptr; } }; /** * Standard deleter template specialization for delete[]. */ template struct StandardDeleter { StandardDeleter() { } StandardDeleter(const StandardDeleter &) { } void operator()(T *ptr) const { delete[] ptr; } }; } #endif // PTR_REF_H april-ann-0.4.1/packages/basics/util/c_src/qsort.h000066400000000000000000000167371263004425400220240ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef QSORT_H #define QSORT_H #include "swap.h" namespace AprilUtils { // use T::operator<() template inline void InsertionSort(T v[], int low, int high) { int i,j; T aux; for (i = low+1; i <= high; i++) { aux=v[i]; for (j = i-1; j>=low && aux inline void InsertionSort(T v[], int low, int high, const Compare &compare) { int i,j; T aux; for (i = low+1; i <= high; i++) { aux=v[i]; for (j = i-1; j>=low && compare(aux,v[j]); j--) v[j+1]=v[j]; v[j+1]=aux; } } // use T::operator<() template inline T med3(T v[], int low, int high) { int cnt = (low+high)/2; if (v[cnt] inline T med3(T v[], int low, int high, const Compare &compare) { int cnt = (low+high)/2; if (compare(v[cnt] ,v[low])) swap(v[low],v[cnt]); if (compare(v[high],v[low])) swap(v[low],v[high]); if (compare(v[high],v[cnt])) swap(v[cnt],v[high]); swap(v[cnt],v[high-1]); return(v[high-1]); } // use T::operator<() template inline int partition(T v[], int low, int high) { // precondition: low+1 < high int izq,der; T piv = med3(v,low,high); izq=low;der=high-1; do { do { izq++; } while(v[izq] inline int partition(T v[], int low, int high, const Compare &compare) { // precondition: low+1 < high int izq,der; T piv = med3(v,low,high, compare); izq=low;der=high-1; do { do { izq++; } while(compare(v[izq],piv)); do { der--; } while(compare(piv,v[der])); swap(v[izq],v[der]); } while (izq void Sort(T v[], int low, int high) { const int MIN_SIZE = 8; // Stack space optimization: the smaller partition is dealt with recursively, // and then the bigger one is sorted by tail recursion/iteration, this way // the space complexity is theta(log n), even for the worst case // Also, halt recursion and iteration when the section of the // array to be sorted is less than MIN_SIZE long, and use InsertionSort instead while (high - low >= MIN_SIZE) { int p = partition(v, low, high); if (p - low < high - p) { Sort(v, low, p); low = p + 1; } else { Sort(v, p + 1, high); high = p; } } InsertionSort(v, low, high); } // use specified comparison function template void Sort(T v[], int low, int high, const Compare &compare) { const int MIN_SIZE = 8; // Stack space optimization: the smaller partition is dealt with recursively, // and then the bigger one is sorted by tail recursion/iteration, this way // the space complexity is theta(log n), even for the worst case // Also, halt recursion and iteration when the section of the // array to be sorted is less than MIN_SIZE long, and use InsertionSort instead while (high - low >= MIN_SIZE) { int p = partition(v, low, high, compare); if (p - low < high - p) { Sort(v, low, p, compare); low = p + 1; } else { Sort(v, p + 1, high, compare); high = p; } } InsertionSort(v, low, high, compare); } /** Template del algoritmo quicksort en la version que realiza una sola llamada recursiva (para evitar que en el caso peor la pila crezca de forma lineal con la talla del vector. En un caso base inferior a MINSIZE (ahora es constante, TODO: se puede meter como un valor en el template y dar valor por defecto) se utiliza InsertionSort. REQUIERE QUE EL TIPO T TENGA DEFINIDA LA OPERACION DE COPIA Y LA COMPARACION MENOR ESTRICTO "<". Se utiliza basicamente asi: \code T v[n]; Sort(v,n); // ordenamos el vector \endcode */ template void Sort(T v[], int sze) { Sort(v,0,sze-1); } template void Sort(T v[], int sze, const Compare &compare) { Sort(v,0,sze-1, compare); } template T Selection(T v[], int sze, int k) { const int MIN_SIZE = 8; int low=0,high=sze-1,q; while (high - low >= MIN_SIZE) { q = partition(v, low, high); if (k <= q) high = q; else low = q+1; } InsertionSort(v, low, high); return v[k]; } template T Selection(T v[], int sze, int k, const Compare &cmp) { const int MIN_SIZE = 8; int low=0,high=sze-1,q; while (high - low >= MIN_SIZE) { q = partition(v, low, high, cmp); if (k <= q) high = q; else low = q+1; } InsertionSort(v, low, high, cmp); return v[k]; } template class PartQ { // QuickSortQueue static const int threshold = 15; static const int sizestack = 200; T* v; int size; int first; int stack[sizestack]; int topStack; int lastSorted; void push(int x) { topStack++; stack[topStack] = x; } int top() { return stack[topStack]; } void pop() { topStack--; } void increase_lastSorted() { while (top() < lastSorted) pop(); int ini = lastSorted+1; while (top()-ini >= threshold) { push(partition(v, ini, top()-1)); } InsertionSort(v,ini,top()-1); lastSorted = top(); pop(); } public: PartQ() {} ~PartQ() {} void configure(T* vector, int size) { v = vector; this->size = size; first = 0; lastSorted = -1; topStack = -1; push(size); } bool extractMin(T& value) { if (first >= size) return false; if (first > lastSorted) { increase_lastSorted(); } value = v[first]; first++; return true; } void sort_up_to(int index) { if (index >= size) index = size-1; while (lastSorted < index) increase_lastSorted(); } int getSize() { return size - first; } }; } // namespace #endif //QSORT_H april-ann-0.4.1/packages/basics/util/c_src/referenced.cc000066400000000000000000000040671263004425400231050ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ // #define __PRINT_STACK__ // #define __DEBUG__ // #define _debugrefsno0_ extern "C" { #include "lauxlib.h" #include "lualib.h" #include "lua.h" } #include "base.h" #include "referenced.h" #ifdef __DEBUG__ #include #include "error_print.h" #endif #ifdef _debugrefsno0_ #include #endif Referenced::Referenced() { #ifdef __DEBUG__ fprintf(stderr," DEBUG Creating %p\n",this); #ifdef __PRINT_STACK__ print_CPP_stacktrace(); #endif #endif refs = 0; } Referenced::~Referenced() { #ifdef __DEBUG__ fprintf(stderr," DEBUG Destroying %p with reference %d\n",this,refs); #ifdef __PRINT_STACK__ print_CPP_stacktrace(); #endif #endif #ifdef _debugrefsno0_ if (refs != 0) { fprintf(stderr,"Warning: destroying %p with reference %d!=0\n",this,refs); } #endif } void Referenced::incRef() { refs++; #ifdef __DEBUG__ fprintf(stderr," DEBUG IncRef %p to reference %d\n",this,refs); #ifdef __PRINT_STACK__ print_CPP_stacktrace(); #endif #endif } bool Referenced::decRef() { refs--; #ifdef __DEBUG__ fprintf(stderr," DEBUG DecRef %p to reference %d\n",this,refs); #ifdef __PRINT_STACK__ print_CPP_stacktrace(); #endif #endif return (refs <= 0); } int Referenced::getRef() const { return refs; } april-ann-0.4.1/packages/basics/util/c_src/referenced.h000066400000000000000000000044411263004425400227430ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef REFERENCED_H #define REFERENCED_H #define IncRef(x) (x)->incRef() #define DecRef(x) if ((x)->decRef()) delete (x) // to avoid deletion of objects before pointer return, releases the references // but not deletes the object #define ReleaseRef(x) (x)->decRef() /** * @brief The class Referenced is used as base class for binded to Lua * classes. It implements reference counting interface. * * @note In general, all derived classes from Reference need to be @c IncRef * when they are allocated using @c new operator, and therefore @c DecRef * when the pointer is not longer needed. * * @see AprilUtils::SharedPtr class for an utility which allows to execute * @c IncRef and @c DecRef in an automatic way. */ class Referenced { private: int refs; ///< Number of living references of this object. public: Referenced(); virtual ~Referenced(); virtual void incRef(); virtual bool decRef(); virtual int getRef() const; }; /** * The functions template AssignRef allows to change the reference of a pointer * taking into account the corresponding IncRef and DecRef. * * @param[out] dest It is the variable where to assign the value, its content * will be DecRef'ed. * * @param ref It is the variable with the value which you want to assign. */ template void AssignRef(T *&dest, T *ref) { if (dest != ref) { if (dest != 0) DecRef(dest); dest = ref; if (dest != 0) IncRef(dest); } } #endif // REFERENCED_H april-ann-0.4.1/packages/basics/util/c_src/remove_const.h000066400000000000000000000020461263004425400233430ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2015, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef REMOVE_CONST_H #define REMOVE_CONST_H template struct remove_const { typedef T type; }; template struct remove_const { typedef typename remove_const::type type; }; #endif // REMOVE_CONST_H april-ann-0.4.1/packages/basics/util/c_src/remove_pointer.h000066400000000000000000000020551263004425400236750ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2015, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef REMOVE_POINTER_H #define REMOVE_POINTER_H template struct remove_pointer { typedef T type; }; template struct remove_pointer { typedef typename remove_pointer::type type; }; #endif // REMOVE_POINTER_H april-ann-0.4.1/packages/basics/util/c_src/reservoir.h000066400000000000000000000100361263004425400226560ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef RESERVOIR_H #define RESERVOIR_H #include "slist.h" #ifdef _OPENMP #include #endif /* esta clase sirve para crear un pool de objetos de modo que los objetos se sacan del pool con el constructor de copia y se devuelven al pool con el destructor entre otras cosas, sirve para tener variables caras de construir y destruir que se utilicen en un paralel for de openmp usando el cualificador firstprivate que llama al constructor de copia y crea una instancia por thread en lugar de crear una instancia por iteracion */ namespace AprilUtils { template struct ReservoirPool { #ifdef _OPENMP omp_lock_t lock; #endif slist pool; ReservoirPool() { #ifdef _OPENMP omp_init_lock(&lock); #endif } ~ReservoirPool() { #ifdef _OPENMP omp_destroy_lock(&lock); #endif while (!pool.empty()) { T *aux = pool.front(); pool.pop_front(); delete aux; } } T* get() { T *resul; #ifdef _OPENMP omp_set_lock(&lock); #endif if (pool.empty()) { resul = new T; } else { resul = pool.front(); pool.pop_front(); } #ifdef _OPENMP omp_unset_lock(&lock); #endif return resul; } void release(T *released) { #ifdef _OPENMP omp_set_lock(&lock); #endif pool.push_back(released); #ifdef _OPENMP omp_unset_lock(&lock); #endif } }; template class ReservoirContainer { ReservoirPool *pool; T *val; public: T* value() const { return val; } ReservoirContainer(ReservoirPool *pool) { this->pool = pool; val = pool->get(); } ReservoirContainer(const ReservoirContainer &other) { pool = other.pool; val = pool->get(); } ~ReservoirContainer() { pool->release(val); } }; template struct VectorReservoirPool { #ifdef _OPENMP omp_lock_t lock; #endif slist pool; int vector_size; VectorReservoirPool(int vector_size) : vector_size(vector_size) { #ifdef _OPENMP omp_init_lock(&lock); #endif } ~VectorReservoirPool() { #ifdef _OPENMP omp_destroy_lock(&lock); #endif while (!pool.empty()) { T *aux = pool.front(); pool.pop_front(); delete [] aux; } } T* get() { T *resul; #ifdef _OPENMP omp_set_lock(&lock); #endif if (pool.empty()) { resul = new T[vector_size]; } else { resul = pool.front(); pool.pop_front(); } #ifdef _OPENMP omp_unset_lock(&lock); #endif return resul; } void release(T *released) { #ifdef _OPENMP omp_set_lock(&lock); #endif pool.push_back(released); #ifdef _OPENMP omp_unset_lock(&lock); #endif } }; template class VectorReservoirContainer { VectorReservoirPool *pool; T *val; public: T* value() const { return val; } VectorReservoirContainer(VectorReservoirPool *pool) { this->pool = pool; val = pool->get(); } VectorReservoirContainer(const VectorReservoirContainer &other) { pool = other.pool; val = pool->get(); } ~VectorReservoirContainer() { pool->release(val); } }; } // namespace AprilUtils #endif // RESERVOIR_H april-ann-0.4.1/packages/basics/util/c_src/shared_ptr.h000066400000000000000000000153341263004425400227770ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SHARED_PTR_H #define SHARED_PTR_H #include "april_assert.h" #include "error_print.h" #include "ptr_ref.h" #include "referenced.h" #include "unique_ptr.h" #include "unused_variable.h" namespace AprilUtils { // forward declaration template class WeakPtr; /** * @brief A smart pointer for shared references. * * @note T must be derivated from Referenced. */ template< typename T, typename Referencer=DefaultReferencer, typename Deleter=DefaultDeleter > class SharedPtr { friend class WeakPtr; public: /** * @brief Builds a SharedPtr from a given pointer, by default NULL. */ SharedPtr(T *ptr=0) : referencer(Referencer()), deleter(Deleter()), ptr(ptr) { referencer(ptr); } /** * @brief Builds a SharedPtr from other SharedPtr object, increasing the * reference counter. */ SharedPtr(SharedPtr &other) : referencer(Referencer()), deleter(Deleter()), ptr(other.get()) { referencer(ptr); } /** * @brief Builds a SharedPtr from other SharedPtr object, increasing the * reference counter. */ SharedPtr(const SharedPtr &other) : referencer(Referencer()), deleter(Deleter()), ptr(other.ptr) { referencer(ptr); } /** * @brief Builds a SharedPtr from other SharedPtr object, increasing the * reference counter. */ template SharedPtr(SharedPtr &other) : referencer(Referencer()), deleter(Deleter()), ptr(other.get()) { referencer(ptr); } /** * @brief Builds a SharedPtr from other SharedPtr object, increasing the * reference counter. */ template SharedPtr(const SharedPtr &other) : referencer(Referencer()), deleter(Deleter()), ptr(other.ptr) { referencer(ptr); } /** * @brief Resets the object to a NULL pointer, what will execute a DecRef. */ ~SharedPtr() { reset(); } /// True if the pointer is not empty. operator bool() const { return !empty(); } /// True if the pointer is empty. bool operator !() const { return empty(); } /** * @brief Dereferencing, returns the pointer itself. */ T *operator->() { return get(); } /** * @brief Dereferencing, returns the pointer itself. */ const T *operator->() const { return get(); } /** * @brief Dereferencing, returns a reference to the data. */ T &operator*() { return *get(); } /** * @brief Dereferencing, returns a reference to the data. */ const T &operator*() const { return *get(); } /** * @brief Assignment operator, takes the ownership of the pointer and * increases the reference. */ SharedPtr &operator=(UniquePtr &other) { reset(other.release()); return *this; } /** * @brief Assignment operator, copies the pointer and increases the * reference. */ SharedPtr &operator=(SharedPtr &other) { reset(other.get()); return *this; } /** * @brief Assignment operator, copies the pointer and increases the * reference. */ SharedPtr &operator=(const SharedPtr &other) { reset(other.ptr); return *this; } /** * @brief Assignment operator, copies the pointer and increases the * reference. */ template SharedPtr &operator=(SharedPtr &other) { reset(other.get()); return *this; } /** * @brief Assignment operator, copies the pointer and increases the * reference. */ template SharedPtr &operator=(const SharedPtr &other) { reset(other.ptr); return *this; } /** * @brief Assignment operator, copies the pointer and increases the * reference. */ SharedPtr &operator=(T *other) { reset(other); return *this; } bool operator==(const SharedPtr &other) const { return ptr == other.ptr; } bool operator==(const T *&other) const { return ptr == other; } bool operator!=(const SharedPtr &other) const { return ptr != other.ptr; } bool operator!=(const T *&other) const { return ptr != other; } /** * @brief Bypasses the pointer, but stills having a reference. */ T *get() { return ptr; } /** * @brief Bypasses the pointer, but stills having a reference. */ const T *get() const { return ptr; } /** * @brief Releases the pointer, but NOT decreases its reference counter. */ T *release() { T *tmp = ptr; ptr = 0; return tmp; } /** * @brief Releases the pointer, decreases its reference counter, but NOT * deletes the content. */ T *weakRelease() { T *tmp = release(); if (tmp != 0) ReleaseRef(tmp); return tmp; } /** * @brief Takes the ownership without IncRef the pointer. */ void take(T *other) { reset(); ptr = other; } /** * @brief DecRef its pointer, and IncRef the given pointer. * * @note By default receives a NULL pointer. */ void reset(T *other = 0) { if (ptr != other) { referencer(other); deleter(ptr); ptr = other; } } bool empty() const { return get() == 0; } private: Referencer referencer; Deleter deleter; T *ptr; }; template SharedPtr makeSharedPtr(T *ptr) { return SharedPtr(ptr); } } // namespace AprilUtils #endif // SHARED_PTR_H april-ann-0.4.1/packages/basics/util/c_src/signal_handler.cc000066400000000000000000000122101263004425400237420ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ extern "C" { #include "lauxlib.h" #include "lualib.h" #include "lua.h" } #include #include #include #include #include "error_print.h" #include "mystring.h" #include "signal_handler.h" #include "unused_variable.h" /// Table which contains the Lua function references #define TABLE_NAME "april_signal" namespace AprilUtils { /// The mapping between signals and Lua function references int SignalHandler::signal_handlers[MAX_SIGNALS]; lua_State *SignalHandler::globalL = 0; /// The handler in C++, a static function which calls the Lua function related /// with the given signal number void SignalHandler::sig_handler(int sgn) { if (globalL == 0) ERROR_EXIT(1024, "Lua state not defined\n"); if (signal_handlers[sgn] == LUA_REFNIL) { ERROR_EXIT(128, "It couldn't be happening... :S\n"); } lua_getfield(globalL, LUA_REGISTRYINDEX, TABLE_NAME); lua_rawgeti(globalL, -1, signal_handlers[sgn]); if (lua_pcall(globalL, 0, 0, 0) != LUA_OK) { AprilUtils::string str(lua_tostring(globalL,-1)); lua_pop(globalL,1); ERROR_EXIT1(128, "%s", str.c_str()); } lua_pop(globalL, 1); } /// Initialization of all the mappings to LUA_REFNIL, captures the lua_State, /// and register of TABLE_NAME in the registry of Lua void SignalHandler::initialize(lua_State *L) { if (globalL != 0) { ERROR_EXIT(256, "Trying to initialize twice\n"); } globalL = L; for (int i=0; i= MAX_SIGNALS) { ERROR_EXIT2(256,"Unknown signal number, found %d, expected to be in " "range [0,%d]\n", sgn, MAX_SIGNALS-1); } if (signal_handlers[sgn] != LUA_REFNIL) { ERROR_PRINT("Trying to register previously registered signal (it will be overwritten)\n"); release_signal(sgn); } sig_t handler_func; int ref; if (lua_isnil(globalL,-1)) { ref = LUA_REFNIL; handler_func = SIG_IGN; } else { lua_getfield(globalL, LUA_REGISTRYINDEX, TABLE_NAME); lua_pushvalue(globalL, -2); ref = luaL_ref(globalL, -2); lua_pop(globalL, -1); handler_func = SignalHandler::sig_handler; } signal_handlers[sgn] = ref; struct sigaction current, old; sigset_t mask; sigemptyset(&mask); current.sa_handler = handler_func; current.sa_mask = mask; current.sa_flags = 0; int ret = sigaction(sgn, ¤t, &old); UNUSED_VARIABLE(old); if (ret < 0) { ERROR_EXIT1(128, "%s\n", strerror(errno)); } /* TODO: if ( ((old.sa_flags & SA_SIGINFO) && old.sa_sigaction != 0) || (!(old.sa_flags & SA_SIGINFO) && old.sa_handler != SIG_IGN && old.sa_handler != SIG_DFL) ) { ERROR_PRINT("Registering a signal which was previously " "registered by a third (it will be overwritten)\n"); } */ } /// Releases the function associated with the given signal void SignalHandler::release_signal(int sgn) { if (globalL == 0) ERROR_EXIT(1024, "Lua state not defined\n"); if (sgn < 0 || sgn >= MAX_SIGNALS) { ERROR_EXIT2(256,"Unknown signal number, found %d, expected to be in " "range [0,%d]\n", sgn, MAX_SIGNALS-1); } struct sigaction current, old; sigset_t mask; sigemptyset(&mask); current.sa_handler = SIG_DFL; current.sa_mask = mask; current.sa_flags = 0; int ret = sigaction(sgn, ¤t, &old); UNUSED_VARIABLE(old); if (ret < 0) { ERROR_EXIT1(128, "%s\n", strerror(errno)); } else if (signal_handlers[sgn] == LUA_REFNIL) { ERROR_EXIT(256, "Releasing a not registered signal or registered by a third\n"); } lua_getfield(globalL, LUA_REGISTRYINDEX, TABLE_NAME); lua_pushvalue(globalL, -2); luaL_unref(globalL, -2, signal_handlers[sgn]); lua_pop(globalL, -1); signal_handlers[sgn] = LUA_REFNIL; } /// Masks the given set of signals void SignalHandler::mask_signals(int how, sigset_t *set) { if (sigprocmask(how, set, 0) != 0) { ERROR_EXIT1(128, "%s\n", strerror(errno)); } } } april-ann-0.4.1/packages/basics/util/c_src/signal_handler.h000066400000000000000000000026711263004425400236160ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SIGNAL_HANDLER_H #define SIGNAL_HANDLER_H #include extern "C" { #include "lauxlib.h" #include "lualib.h" #include "lua.h" } #define MAX_SIGNALS 32 namespace AprilUtils { /// This class is not thread-safe, so don't use it with threads. class SignalHandler { static lua_State *globalL; // hash ( signal -> lua reference ) static int signal_handlers[MAX_SIGNALS]; static void sig_handler(int sgn); public: static void initialize(lua_State *L); static void register_signal(int sgn); static void release_signal(int sgn); static void mask_signals(int how, sigset_t *set); }; } #endif april-ann-0.4.1/packages/basics/util/c_src/slist.h000066400000000000000000000161431263004425400220010ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SLIST_H #define SLIST_H #include #include "swap.h" //#include namespace AprilUtils { // Be careful! It's not std::slist :) // Implements Container and Front Insertion Sequence template class slist { // Linked-list nodes struct node { T data; node *next; // Constructor node(T t, node* n):data(t), next(n) {} }; node *first; node *last; size_t list_size; void init_list() { first = 0; last = 0; list_size = 0; } void delete_list() { while (!empty()) pop_front(); list_size = 0; first = 0; last = 0; } public: typedef T value_type; typedef T* pointer; typedef T& reference; typedef const T& const_reference; typedef size_t size_type; typedef ptrdiff_t difference_type; struct const_iterator; struct iterator { friend struct const_iterator; private: node *ptr; public: typedef T value_type; typedef T* pointer; typedef T& reference; typedef const T& const_reference; typedef ptrdiff_t difference_type; //typedef std::forward_iterator_tag iterator_category; iterator(): ptr(0) {} iterator(node *p): ptr(p) {} iterator& operator++() { // preincrement ptr = ptr->next; return *this; } iterator operator++(int) { // postincrement node *tmp = ptr; ptr = ptr->next; return iterator(tmp); } T& operator *() { // dereference return ptr->data; } T* operator ->() { return &(ptr->data); } bool operator == (const iterator &i) { return ptr == i.ptr; } bool operator != (const iterator &i) { return ptr != i.ptr; } }; struct const_iterator { private: const node *ptr; public: typedef T value_type; typedef T* pointer; typedef T& reference; typedef const T& const_reference; typedef ptrdiff_t difference_type; //typedef std::forward_iterator_tag iterator_category; const_iterator(): ptr(0) {} const_iterator(const node *p): ptr(p) {} const_iterator(const iterator &i): ptr(i.ptr) {} const_iterator& operator++() { // preincrement ptr = ptr->next; return *this; } const_iterator operator++(int) { // postincrement const node *tmp = ptr; ptr = ptr->next; return const_iterator(tmp); } const T& operator *() { // dereference return ptr->data; } const T* operator ->() { return &(ptr->data); } bool operator == (const const_iterator &i) { return ptr == i.ptr; } bool operator != (const const_iterator &i) { return ptr != i.ptr; } }; iterator begin() { return iterator(first); } iterator end() { return iterator(0); } const_iterator begin() const { return const_iterator(first); } const_iterator end() const { return const_iterator(0); } size_type size() const { return list_size; } size_type max_size() const { return size_type(-1); } bool empty() const { return (list_size==0); } slist() { init_list(); } slist(size_type n) { init_list(); for (size_type i=0; i slist(InputIterator f, InputIterator l) { init_list(); for (InputIterator i = f; i != l; i++) { push_back(*i); } } ~slist() { delete_list(); } slist &operator=(slist &l){ if (&l != this) { delete_list(); for (iterator i = l.begin(); i != l.end(); i++) push_back(*i); } return *this; } void swap(slist &l){ AprilUtils::swap(first, l.first); AprilUtils::swap(last, l.last); AprilUtils::swap(list_size, l.list_size); } // These 2 functions have precondition = !empty() reference front() { return first->data; } const_reference front() const { return first->data; } void push_front(const_reference t) { first = new node(t, first); if (list_size == 0) last = first; list_size++; } // Precondition: !empty() void pop_front() { node *tmp = first; first = first->next; delete tmp; list_size--; } void push_back(const_reference t) { if (list_size == 0) { first = new node(t,0); last = first; } else { last->next = new node(t, 0); last = last->next; } list_size++; } // TODO: Reflexionar sobre la conveniencia de meter un metodo // que no se parece en nada a lo que hay en la slist de la STL. // // transfer_front_to_front toma el primer elemento de la lista l y lo inserta // en la cabeza de this, sin hacer un push_front y un pop_front que // supondrian un new y un delete adicionales. void transfer_front_to_front(slist &l) { if (l.first) { node *aux = l.first; // No usamos pop_front porque no queremos hacer un delete del nodo l.first = l.first->next; l.list_size--; aux->next = first; first = aux; if (list_size == 0) { last = aux; } list_size++; } } // transfer_front_to_back toma el primer elemento de la lista l y lo inserta // en la cola de this, sin hacer un push_back y un pop_front que // supondrian un new y un delete adicionales. void transfer_front_to_back(slist &l) { if (l.first) { node *aux = l.first; // No usamos pop_front porque no queremos hacer un delete del nodo l.first = l.first->next; l.list_size--; aux->next = 0; if (list_size == 0) { last = first = aux; } else { last->next = aux; last = last->next; } list_size++; } } }; } #endif april-ann-0.4.1/packages/basics/util/c_src/smart_ptr.h000066400000000000000000000016741263004425400226610ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SMART_PTR_H #define SMART_PTR_H #include "shared_ptr.h" #include "unique_ptr.h" #include "weak_ptr.h" #endif // SMART_PTR_H april-ann-0.4.1/packages/basics/util/c_src/stopwatch.cc000066400000000000000000000045301263004425400230120ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "stopwatch.h" #include #include namespace AprilUtils { double stopwatch::get_cpu_clock() const { struct rusage wop; getrusage(RUSAGE_SELF, &wop); return static_cast(wop.ru_utime.tv_sec) + static_cast(wop.ru_utime.tv_usec)*1e-6; } double stopwatch::get_wall_clock() const { struct timeval wop; gettimeofday(&wop, 0); return static_cast(wop.tv_sec) + static_cast(wop.tv_usec)*1e-6; } stopwatch::stopwatch() { reset(); _is_on = false; } void stopwatch::reset() { cpu_elapsed = 0.0; wall_elapsed = 0.0; cpu_t_ini = get_cpu_clock(); wall_t_ini = get_wall_clock(); } void stopwatch::stop() { double cpu_increment = get_cpu_clock() - cpu_t_ini; if (cpu_increment>0) cpu_elapsed += cpu_increment; double wall_increment = get_wall_clock() - wall_t_ini; if (wall_increment>0) wall_elapsed += wall_increment; _is_on = false; } void stopwatch::go() { _is_on = true; cpu_t_ini = get_cpu_clock(); wall_t_ini = get_wall_clock(); } double stopwatch::read_cpu_time() const { double increment = (_is_on) ? get_cpu_clock() - cpu_t_ini : 0; if (increment<0) increment = 0; return cpu_elapsed+increment; } double stopwatch::read_wall_time() const { double increment = (_is_on) ? get_wall_clock() - wall_t_ini : 0; if (increment<0) increment = 0; return wall_elapsed+increment; } } april-ann-0.4.1/packages/basics/util/c_src/stopwatch.h000066400000000000000000000031331263004425400226520ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef STOPWATCH_H #define STOPWATCH_H #include "referenced.h" namespace AprilUtils { class stopwatch : public Referenced { double cpu_elapsed; ///< tiempo acumulado de cpu double wall_elapsed; ///< tiempo acumulado double cpu_t_ini; ///< auxiliar double wall_t_ini; ///< auxiliar bool _is_on; ///< significado obvio /// devuelve tiempo en segundos inline double get_cpu_clock() const; inline double get_wall_clock() const; public: stopwatch(); void reset(); void stop(); void go(); double read_cpu_time() const; double read_wall_time() const; double read() const { return read_cpu_time(); } // compatible hacia abajo bool is_on() const { return _is_on; } }; } #endif // STOPWATCH_H april-ann-0.4.1/packages/basics/util/c_src/stringQueue.cc000066400000000000000000000140761263004425400233170ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "stringQueue.h" #include // vsnprintf #include // memcpy(dest,src,sz) #include #include #include "maxmin.h" namespace AprilUtils { StringQueue::StringQueue() { firstNode = lastNode = 0; theSize = 0; } void StringQueue::clear() { while (firstNode) { Node *aux = firstNode; firstNode = firstNode->next; delete aux; } lastNode = 0; theSize = 0; } inline void StringQueue::checkNonEmpty() { if (!lastNode) { firstNode = lastNode = new Node; } } inline void StringQueue::checkLast() { if (lastNode->last == Node::bufferSize) { lastNode->next = new Node; lastNode = lastNode->next; } } void StringQueue::putchar(char c) { checkNonEmpty(); checkLast(); lastNode->putCharNoCheck(c); theSize++; } void StringQueue::putchars(char c, int times) { checkNonEmpty(); for (int i=0;iputCharNoCheck(c); } theSize += times; } void StringQueue::print(const char *str) { checkNonEmpty(); for (char c = *str++; c != '\0'; c = *str++) { checkLast(); lastNode->putCharNoCheck(c); theSize++; } } void StringQueue::printEsc(const char *str) { checkNonEmpty(); for (char c = *str++; c != '\0'; c = *str++) { bool esc=true; switch (c) { case '\\': if (*str=='u') esc=false; break; // copy \uHHHH verbatim case '"': break; case '\b': c = 'b'; break; case '\f': c = 'f'; break; case '\n': c = 'n'; break; case '\r': c = 'r'; break; case '\t': c = 't'; break; default: esc = false; break; } if (esc) { checkLast(); lastNode->putCharNoCheck('\\'); theSize++; } checkLast(); lastNode->putCharNoCheck(c); theSize++; } } void StringQueue::putBuffer(const char* buffer,int buffersz) { if (buffersz <= 0) return; checkNonEmpty(); theSize += buffersz; while (buffersz > 0) { checkLast(); int toCopy = min(buffersz,lastNode->freeSpace()); memcpy(lastNode->buffer+lastNode->last, buffer, toCopy); lastNode->last += toCopy; buffer += toCopy; buffersz -= toCopy; } } void StringQueue::putStringQueue(const StringQueue &other) { for (const Node *r = other.firstNode; r!=0; r=r->next) putBuffer(r->buffer,r->occuped()); // theSize is incremented there } void StringQueue::printf(const char *fmt, ...) { const int FIRSTSIZE = 256; int bufsize = FIRSTSIZE; char *buf = 0; for (;;) { delete[] buf; buf = new char[bufsize]; va_list args; va_start(args, fmt); int outsize = vsnprintf(buf, bufsize, fmt, args); va_end(args); if (outsize == -1) { // Clear indication that output was truncated, but no clear // indication of how big buffer needs to be, so simply double // existing buffer size for next time. bufsize *= 2; } else if (outsize == bufsize) { // Output was truncated (since at least the \0 could not fit), // but no indication of how big the buffer needs to be, so just // double existing buffer size for next time. bufsize *= 2; } else if (outsize > bufsize) { // Output was truncated, but we were told exactly how big the // buffer needs to be next time. Add two chars to the returned // size. One for the \0, and one to prevent ambiguity in the // next case below. bufsize += 2; } else if (outsize == bufsize - 1) { // This is ambiguous. May mean that the output string exactly // fits, but on some systems the output string may have been // trucated. We can't tell. Just double the buffer size for // next time. bufsize *= 2; } else { // Output was not truncated putBuffer(buf,outsize); // theSize is incremented there delete[] buf; return; } } } // returns a buffer pointer and a buffer size int StringQueue::getBufferChunk(char **buffer) { if (!firstNode) { *buffer=0; return 0; } *buffer = firstNode->buffer + firstNode->first; return (firstNode->last - firstNode->first); } char* StringQueue::exportBuffer(int &sz) const { sz = size(); char *resul, *dest; resul = dest = new char[sz+1]; for (const Node *r = firstNode; r!=0; r=r->next) { int t = r->occuped(); memcpy(dest, r->buffer, t); dest += t; } *dest = '\0'; return resul; } // drops first bufferAdvance bytes from StringQueue // a bufferAdvance value <= previous getBufferChunk result is assumed void StringQueue::advanceBuffer(int bufferAdvance) { firstNode->first += bufferAdvance; theSize -= bufferAdvance; if (firstNode->first >= firstNode->last) { if (firstNode == lastNode) { // only one node firstNode->first = firstNode->last = 0; // reset node } else { // firstNode->first == Node::bufferSize and >1 Node Node *aux = firstNode; firstNode = firstNode->next; delete aux; } } } } // namespace AprilUtils april-ann-0.4.1/packages/basics/util/c_src/stringQueue.h000066400000000000000000000047371263004425400231640ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef STRINGQUEUE_H #define STRINGQUEUE_H namespace AprilUtils { class StringQueue { struct Node { static const int bufferSize = 2048 - 2*sizeof(int) - sizeof(Node*); int first,last; Node *next; char buffer[bufferSize]; Node() : first(0), last(0), next(0) {} int occuped() const { return last-first; } int freeSpace() const { return bufferSize-last; } void putCharNoCheck(char c) { buffer[last] = c; last++; } }; Node *firstNode, *lastNode; int theSize; void checkNonEmpty(); void checkLast(); public: StringQueue(); ~StringQueue() { clear(); } void clear(); int size() const { return theSize; } bool empty() const { return size() == 0; } void putchar(char); void putchars(char c,int times); void putBuffer(const char* buffer,int buffersz); void putStringQueue(const StringQueue &other); void print(const char *str); void printEsc(const char *str); void printf(const char *fmt, ...); // returns a buffer pointer and a buffer size int getBufferChunk(char **buffer); // drops first bufferAdvance bytes from StringQueue void advanceBuffer(int bufferAdvance); // returns a new buffer char *exportBuffer(int &sz) const; // syntactic sugar :) StringQueue& operator<< (const char *str) { print(str); return *this; } StringQueue& operator<< (int i) { printf("%d",i); return *this; } StringQueue& operator<< (float f) { printf("%g",f); return *this; } StringQueue& operator<< (double f) { printf("%g",f); return *this; } }; } // namespace AprilUtils #endif // STRINGQUEUE_H april-ann-0.4.1/packages/basics/util/c_src/swap.h000066400000000000000000000020171263004425400216100ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SWAP_H #define SWAP_H namespace AprilUtils { template inline void swap(T & a, T & b) { T tmp(a); a = b; b = tmp; } } #endif //SWAP_H april-ann-0.4.1/packages/basics/util/c_src/trie_hash.h000066400000000000000000000204211263004425400226030ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef TRIE_HASH_H #define TRIE_HASH_H #include #include #include "aux_hash_table.h" #include "error_print.h" #include "hash_table.h" namespace AprilUtils { /// Plantilla para implementar un Trie generico, que guarda /// transiciones entre estados con el tipo int, y da como salida el tipo /// O. template class TrieHash { public: // una transicion va de (estado, int) => (dest) typedef AprilUtils::hash transitions_t; private: // tabla de finales AprilUtils::hash outputs_tbl; // nodos y transiciones transitions_t transitions_tbl; int *levels_tbl; int num_nodes; int next_node; public: ///////////////////////////////////////////////////////////////////////////// typedef typename AprilUtils::hash::iterator outputs_iterator; // iterador sencillo class iterator { friend class TrieHash; TrieHash *trie; typename transitions_t::iterator hash_it; iterator(TrieHash *trie, typename transitions_t::iterator it) { this->trie = trie; this->hash_it = it; } public: iterator(): trie(0) {} iterator& operator++(){ // preincrement hash_it++; return *this; } iterator operator++(int){ // postincrement iterator tmp(*this); ++(*this); return tmp; } int get_node() { // typedef AprilUtils::hash<(estado,word), int, return hash_it->first.first; } int get_tr_value() { // typedef AprilUtils::hash<(estado,word), int, return hash_it->first.second; } int get_dest() { // typedef AprilUtils::hash<(estado,word), int, return hash_it->second; } int get_level() { // typedef AprilUtils::hash<(estado,word), int, return trie->levels_tbl[hash_it->first.first]; } pair & get_transition() { return *hash_it; } const O *get_outputs() { // typedef AprilUtils::hash<(estado,word), int, return trie->outputs_tbl.find(hash_it->first.first); } bool operator == (const iterator &other) { return ((hash_it == other.hash_it) && (trie == other.trie)); } bool operator != (const iterator &other) { return ((hash_it != other.hash_it) || (trie != other.trie)); } }; ///////////////////////////////////////////////////////////////////////////// /// Reserva memoria, el tamanyo del Trie debe ser conocido a priori. TrieHash(int num_nodes = 8) : outputs_tbl(8, 2.0), transitions_tbl(8, 2.0) { if (num_nodes <= 0) num_nodes = 8; this->num_nodes = num_nodes; next_node = 1; levels_tbl = new int[num_nodes]; levels_tbl[0] = 0; } /// Libera los recursos ~TrieHash() { delete[] levels_tbl; } void clear() { next_node = 1; transitions_tbl.clear(); outputs_tbl.clear(); } int get_state_level(int st) { return levels_tbl[st]; } int get_size() { return next_node; } /// Crea una transicion entre estados void insert(int orig, int dest, int key, int level) { if (orig > next_node) next_node = orig+1; if (dest > next_node) next_node = dest+1; if (orig > num_nodes) resize(orig<<1); if (dest > num_nodes) resize(dest<<1); transitions_tbl[int_pair(orig, key)] = dest; levels_tbl[orig] = level; levels_tbl[dest] = level+1; } /// Guarda los outputs void set_state_output(int st, O value) { outputs_tbl[st] = value; } /// Devuelve los outputs const O *get_state_output(int st) { return outputs_tbl.find(st); } /// Inserta una secuencia en trie, y le asocia value como salida void insert(const int *key, O value, int key_size) { int current_node = 0; int next_level = 1; for (int i=0; i= num_nodes) resize(num_nodes<<1); } next_level++; } // guarda el valor de salida en la tabla de outputs outputs_tbl[current_node] = value; } void resize(int n) { // para hacer un resize del Trie... int *old_levels = levels_tbl; int old_num_nodes = num_nodes; num_nodes = n; levels_tbl = new int[n]; for (int i=0; i= num_nodes) resize(num_nodes<<1); } next_level++; } // buscamos el nodo en la lista de outputs del Trie return outputs_tbl[current_node]; } iterator begin() { return iterator(this, transitions_tbl.begin()); } iterator end() { return iterator(this, transitions_tbl.end()); } outputs_iterator begin_outputs() { return outputs_tbl.begin(); } outputs_iterator end_outputs() { return outputs_tbl.end(); } }; }; #endif // TRIE_HASH_H april-ann-0.4.1/packages/basics/util/c_src/trie_hash_4_lua.cc000066400000000000000000000026041263004425400240300ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "trie_hash_4_lua.h" namespace AprilUtils { TrieHash4Lua::TrieHash4Lua() { lastId = rootNode; } int TrieHash4Lua::reserveId() { lastId++; return lastId; } int TrieHash4Lua::find(int *ids, int lenght) { int index = rootNode; for (int i=0; isecond = reserveId(); } index = r->second; } return index; } } // namespace april-ann-0.4.1/packages/basics/util/c_src/trie_hash_4_lua.h000066400000000000000000000027551263004425400237010ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef TRIE_HASH_4_LUA_H #define TRIE_HASH_4_LUA_H #include "referenced.h" #include "aux_hash_table.h" #include "hash_table.h" namespace AprilUtils { // This c++ class replaces a previous one implemented in lua, I have // decided not to reuse a previous trie class since this one is even // simpler class TrieHash4Lua : public Referenced { static const int rootNode = 0; int lastId; // state x id -> state typedef hash hash_type; hash_type transition_t; public: TrieHash4Lua(); int reserveId(); int find(int *ids, int lenght); }; } // namespace AprilUtils #endif // TRIE_HASH_4_LUA_H april-ann-0.4.1/packages/basics/util/c_src/trie_open_addressing.h000066400000000000000000000246051263004425400250340ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef TRIE_OPEN_ADDR_H #define TRIE_OPEN_ADDR_H #include "aux_hash_table.h" #include "error_print.h" #include #include #include "open_addressing_hash_timestamp.h" namespace AprilUtils { /// Plantilla para implementar un Trie generico, que guarda /// transiciones entre estados con el tipo int, y da como salida el tipo /// O. template class TrieOpenAddr { public: // una transicion va de (estado, int) => (dest) typedef AprilUtils::open_addr_hash_timestamp transitions_t; private: // tabla de finales AprilUtils::open_addr_hash_timestamp outputs_tbl; // nodos y transiciones transitions_t transitions_tbl; int *levels_tbl; int num_nodes; int next_node; public: //////////////////////////////////////////////////////////////////////////// typedef typename AprilUtils::hash::iterator outputs_iterator; // iterador sencillo class iterator { friend class TrieOpenAddr; TrieOpenAddr *trie; typename transitions_t::iterator hash_it; iterator(TrieOpenAddr *trie, typename transitions_t::iterator it) { this->trie = trie; this->hash_it = it; } public: iterator(): trie(0) {} iterator& operator++(){ // preincrement hash_it++; return *this; } iterator operator++(int){ // postincrement iterator tmp(*this); ++(*this); return tmp; } int get_node() { // typedef AprilUtils::hash<(estado,word), int, return hash_it->first.first; } int get_tr_value() { // typedef AprilUtils::hash<(estado,word), int, return hash_it->first.second; } int get_dest() { // typedef AprilUtils::hash<(estado,word), int, return hash_it->second; } int get_level() { // typedef AprilUtils::hash<(estado,word), int, return trie->levels_tbl[hash_it->first.first]; } pair & get_transition() { return *hash_it; } const O *get_outputs() { // typedef AprilUtils::hash<(estado,word), int, return trie->outputs_tbl.find(hash_it->first.first); } bool operator == (const iterator &other) { return ((hash_it == other.hash_it) && (trie == other.trie)); } bool operator != (const iterator &other) { return ((hash_it != other.hash_it) || (trie != other.trie)); } }; /////////////////////////////////////////////////////////////////////////// /// Reserva memoria, el tamanyo del Trie debe ser conocido a priori. TrieOpenAddr(int num_nodes = 8) : outputs_tbl(8, 0.6), transitions_tbl(8, 0.6) { if (num_nodes <= 0) num_nodes = 8; this->num_nodes = num_nodes; next_node = 1; levels_tbl = new int[num_nodes]; levels_tbl[0] = 0; } /// Libera los recursos ~TrieOpenAddr() { delete[] levels_tbl; } void clear() { next_node = 1; transitions_tbl.clear(); outputs_tbl.clear(); } int get_state_level(int st) { return levels_tbl[st]; } int get_size() { return next_node; } /// Crea una transicion entre estados void insert(int orig, int dest, int key, int level) { if (orig > next_node) next_node = orig+1; if (dest > next_node) next_node = dest+1; if (orig > num_nodes) resize(orig<<1); if (dest > num_nodes) resize(dest<<1); transitions_tbl[int_pair(orig, key)] = dest; levels_tbl[orig] = level; levels_tbl[dest] = level+1; } /// Guarda los outputs void set_state_output(int st, O value) { outputs_tbl[st] = value; } /// Devuelve los outputs const O *get_state_output(int st) { return outputs_tbl.find(st); } /// Inserta una secuencia en trie, y le asocia value como salida void insert(const int *key, O value, int key_size) { int current_node = 0; int next_level = 1; for (int i=0; i= num_nodes) resize(num_nodes<<1); } next_level++; } // guarda el valor de salida en la tabla de outputs outputs_tbl[current_node] = value; } /// Inserta una secuencia en trie, y le asocia value como salida void insert(const int *key, int last_key, O value, int key_size) { int current_node = 0; int next_level = 1; for (int i=0; i= num_nodes) resize(num_nodes<<1); } next_level++; } { int_pair tr_key(current_node, last_key); // busca la componente actual de la secuencia en el estado current_node const int *aux = transitions_tbl.find(tr_key); if (aux != 0) current_node = *aux; else { // si no lo encuentra, crea un nuevo acceso en la tabla y un // nuevo nodo destino transitions_tbl[tr_key] = next_node; levels_tbl[next_node] = next_level; current_node = next_node++; if (next_node >= num_nodes) resize(num_nodes<<1); } next_level++; } // guarda el valor de salida en la tabla de outputs outputs_tbl[current_node] = value; } void resize(int n) { // para hacer un resize del Trie... int *old_levels = levels_tbl; int old_num_nodes = num_nodes; num_nodes = n; levels_tbl = new int[n]; for (int i=0; i= num_nodes) resize(num_nodes<<1); } next_level++; } // buscamos el nodo en la lista de outputs del Trie return outputs_tbl[current_node]; } iterator begin() { return iterator(this, transitions_tbl.begin()); } iterator end() { return iterator(this, transitions_tbl.end()); } outputs_iterator begin_outputs() { return outputs_tbl.begin(); } outputs_iterator end_outputs() { return outputs_tbl.end(); } }; }; #endif // TRIE_OPEN_ADDR_H april-ann-0.4.1/packages/basics/util/c_src/trie_vector.cc000066400000000000000000000126521263004425400233270ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include // memset #include "trie_vector.h" #include "error_print.h" #include "swap.h" namespace AprilUtils { TrieVector::TrieVector(int logSize) { vectorSize = 1< max_allowed_size) ERROR_EXIT1(-1,"trie vector grew too much (maxAllowedSize = %d)\n", max_allowed_size); return index; } index = (index+increment) & mask; } return 0; // esto no deberia ocurrir, para que no se queje el compilador } uint32_t TrieVector::getPersistentChild (uint32_t node, uint32_t word) { static const unsigned int cte_hash = 2654435769U; // hash Fibonacci TrieNode searched(node,word<<8); unsigned int index = (node*cte_hash ^ word) & mask; unsigned int increment = word | 1; // considera que los nodos efimeros estan todos libres while ((data[index].wordStamp & 255) == 0 && data[index] != searched) index = (index+increment) & mask; if (data[index] != searched) { data[index] = searched; // size++; --max_allowed_size; if (size > max_allowed_size) { ERROR_EXIT1(-1,"trie vector grew too much (maxAllowedSize = %d)\n", max_allowed_size); } } return index; } bool TrieVector::hasChild (uint32_t node, uint32_t word, uint32_t &destnode) { static const unsigned int cte_hash = 2654435769U; // hash Fibonacci TrieNode searchedP(node,word<<8); TrieNode searchedE(node,(word<<8)|stamp); unsigned int index = (node*cte_hash ^ word) & mask; unsigned int increment = word | 1; for (;;) { unsigned int stmp = data[index].wordStamp & 255; if (stmp == 0) { // es un nodo persistente if (data[index] == searchedP) { destnode=index; return true; } } else if (stmp == stamp) { if (data[index] == searchedE) { destnode=index; return true; } } else { return false; } index = (index+increment) & mask; } return false; // esto no deberia ocurrir, para que no se queje el compilador } bool TrieVector::hasSequence(const uint32_t *sequence, int length, uint32_t &destnode) { uint32_t index = rootNode(); for (int i=0; i> 8; node = data[node].parent; len++; } if (node != 0) return -1; // reverse sequence: int first=0,last=len-1; while (first } #include "referenced.h" /* Estructura de datos para representar tries de palabras. Las palabras son uint32 con valores entre 0 y 2**24-2 (la 2**24-1 se reserva) NO SOPORTA REHASHING, pues cada nodo se identifica con su indice en el vector de open addressing. Cada nodo contiene el indice de su padre y la ultima palabra introducida. Para acceder a un nodo hijo se hace hashing con el propio nodo padre y la palabra introducida. Utiliza timestamp de talla 1 byte, lo que supone recorrer la tabla cada 255 llamadas a "clear()" El valor de timestamp 0 se reserva para nodos "persistentes" que no se borran con la operacion "clear". Se presupone que todas las inserciones persistentes se realizan al principio, con lo que no hace falta comprobar que todos los antecesores de un nodo persistente tambien lo son. */ namespace AprilUtils { class TrieVector : public Referenced { unsigned int max_allowed_size; static const uint32_t NoWord = (1<<24)-1; struct TrieNode { union { struct { uint32_t parent; // indice en vector uint32_t wordStamp; // word<<8|stamp }; uint64_t rawValue; }; TrieNode(uint32_t parent=0, uint32_t wordStamp=0) : parent(parent), wordStamp(wordStamp) {} bool operator!= (const TrieNode &other) const { return rawValue != other.rawValue; } bool operator== (const TrieNode &other) const { return rawValue == other.rawValue; } }; unsigned int vectorSize; // talla del vector, potencia de 2 unsigned int mask; // vectorSize-1 unsigned int size; // elementos insertados unsigned int stamp; // actual TrieNode *data; // el vector public: TrieVector(int logSize=20); ~TrieVector(); unsigned int getSize() const { return size; } uint32_t getParent(uint32_t node) const { return data[node].parent; } uint32_t getWord(uint32_t node) const { return data[node].wordStamp>>8; } // busqueda sin insertar bool hasChild (uint32_t node, uint32_t word, uint32_t &destnode); // busqueda insertando uint32_t getChild (uint32_t node, uint32_t word); uint32_t getPersistentChild (uint32_t node, uint32_t word); // busqueda sin insertar bool hasSequence(const uint32_t *sequence, int length, uint32_t &destnode); // busqueda insertando uint32_t searchSequence(const uint32_t *sequence, int length); uint32_t searchPersistentSequence(const uint32_t *sequence, int length); /// devuelve la longitud, -2 si no existe, -1 si no cabe int getSequence(uint32_t node, uint32_t *sequence, int maxLength); uint32_t rootNode() const { return 0; } void clear(); }; // class TrieVector } // namespace #endif // TRIE_VECTOR_H april-ann-0.4.1/packages/basics/util/c_src/tuple.h000066400000000000000000000047631263004425400220010ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef TUPLE_H #define TUPLE_H #include "april_assert.h" #include namespace AprilUtils { template class tuple { T *vec; size_t tuple_size; public: typedef T value_type; typedef T* pointer; typedef T& reference; typedef const T& const_reference; typedef size_t size_type; typedef ptrdiff_t difference_type; size_type size() const { return tuple_size; } tuple() { tuple_size = 0; vec = 0; } tuple(int tuple_size) { april_assert(tuple_size >= 0); this->tuple_size = tuple_size; vec = new T[tuple_size]; } tuple(const tuple &l) { tuple_size = l.tuple_size; vec = new T[tuple_size]; for (unsigned int i=0; i namespace AprilUtils { // responde al perfil de fgets inline char* get_uncommented_line(char *s, int size, FILE *stream) { char *aux; do { aux = fgets(s,size,stream); } while(aux && aux[0] == '#'); return aux; } inline char* get_line(char *s, int size, FILE *stream) { char *aux = fgets(s,size,stream); return aux; } } // namespace AprilUtils #endif // UNCOMMENTED_LINE_H april-ann-0.4.1/packages/basics/util/c_src/unique_ptr.h000066400000000000000000000242001263004425400230270ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef UNIQUE_PTR_H #define UNIQUE_PTR_H #include "april_assert.h" #include "disallow_class_methods.h" #include "error_print.h" #include "ptr_ref.h" #include "referenced.h" #include "unused_variable.h" namespace AprilUtils { /** * @brief Smart pointer similar to auto_ptr in old C++ (before C++11). * * This class uses StandardReferencer and StandardDeleter to reference and * delete the owned resource. In other words, by default it does nothing when * referneces a pointer, but executes delete or delete[] when its time * expires. * * @note Avoid using this class as return value in functions, it is * safer to return a plain pointer which can be captured in tha assignment, * as the following example does: * @code * float *foo(int sz) { return new float[sz]; } * int main() { * AprilUtils::UniquePtr ptr = foo(10); * } * @endcode */ template< typename T, typename Referencer=StandardReferencer, typename Deleter=StandardDeleter > class UniquePtr { APRIL_DISALLOW_COPY_AND_ASSIGN(UniquePtr); public: /** * @brief Builds a UniquePtr from a given pointer, by default NULL. */ UniquePtr(T *ptr=0) : referencer(Referencer()), deleter(Deleter()), ptr(ptr) { referencer(ptr); referencer.checkUnique(ptr); } /** * @brief Builds a UniquePtr from other UniquePtr object, taking the * ownership of the referenced pointer. */ UniquePtr(UniquePtr &other) : referencer(Referencer()), deleter(Deleter()), ptr(other.release()) { } /** * @brief Builds a UniquePtr from other UniquePtr object, taking the * ownership of the referenced pointer. */ template UniquePtr(UniquePtr &other) : referencer(Referencer()), deleter(Deleter()), ptr(other.release()) { } /** * @brief Resets the object to a NULL pointer, what will execute delete. */ ~UniquePtr() { reset(); } /// True if the pointer is not empty. operator bool() const { return !empty(); } /// True if the pointer is empty. bool operator !() const { return empty(); } /** * @brief Dereferencing, returns the pointer itself. */ T *operator->() { april_assert(get() != 0); return get(); } /** * @brief Dereferencing, returns a const reference to the pointer itself. */ const T *operator->() const { april_assert(get() != 0); return get(); } /** * @brief Dereferencing, returns a reference to the data. */ T &operator*() { april_assert(get() != 0); return *get(); } /** * @brief Dereferencing, returns a const reference to the data. */ const T &operator*() const { april_assert(get() != 0); return *get(); } /** * @brief Assignment operator, transfers the ownership of the pointer * referenced by the given other object. */ UniquePtr &operator=(UniquePtr &other) { take(other.release()); return *this; } /** * @brief Assignment operator, transfers the ownership of the pointer * referenced by the given other object. */ template UniquePtr &operator=(UniquePtr &other) { take(other.release()); return *this; } /** * @brief Assignment operator, takes the ownership of the given pointer. */ UniquePtr &operator=(T *other) { reset(other); return *this; } private: /** * @brief Operator[], returns a reference to the data. */ T &operator[](int i) { return ptr[i]; } /** * @brief Operator[], returns a reference to the data. */ const T &operator[](int i) const { return ptr[i]; } public: bool operator==(const T *&other) const { return ptr == other; } bool operator!=(const T *&other) const { return ptr != other; } /** * @brief Bypasses the pointer, but stills having the ownership. */ T *get() { return ptr; } /** * @brief Bypasses the pointer, but stills having the ownership. */ const T *get() const { return ptr; } /** * @brief Releases the pointer and the ownership, but NOT executes delete, * so it transfers the ownership to the caller. */ T *release() { T *tmp = ptr; ptr = 0; return tmp; } /** * @brief Takes the ownership without executing the referencer. */ void take(T *other) { reset(); ptr = other; referencer.checkUnique(ptr); } /** * @brief Deletes its pointer, and takes ownership and executes the * referencer the given pointer. * * @note By default receives a NULL pointer. */ void reset(T *other = 0) { if (ptr != other) { referencer(other); deleter(ptr); ptr = other; referencer.checkUnique(ptr); } } bool empty() const { return get() == 0; }; private: Referencer referencer; Deleter deleter; T *ptr; }; // Specialization for array declarations template< typename T, typename Referencer, typename Deleter > class UniquePtr { public: /** * @brief Builds a UniquePtr from a given pointer, by default NULL. */ UniquePtr(T *ptr=0) : referencer(Referencer()), deleter(Deleter()), ptr(ptr) { referencer(ptr); referencer.checkUnique(ptr); } /** * @brief Builds a UniquePtr from other UniquePtr object, taking the * ownership of the referenced pointer. */ UniquePtr(UniquePtr &other) : referencer(Referencer()), deleter(Deleter()), ptr(other.release()) { } /** * @brief Builds a UniquePtr from other UniquePtr object, taking the * ownership of the referenced pointer. */ template UniquePtr(UniquePtr &other) : referencer(Referencer()), deleter(Deleter()), ptr(other.release()) { } public: /** * @brief Resets the object to a NULL pointer, what will execute delete. */ ~UniquePtr() { reset(); } /** * @brief Dereferencing, returns the pointer itself. */ T *operator->() { april_assert(get() != 0); return get(); } /** * @brief Dereferencing, returns a const reference to the pointer itself. */ const T *operator->() const { april_assert(get() != 0); return get(); } /** * @brief Dereferencing, returns a reference to the data. */ T &operator*() { april_assert(get() != 0); return *get(); } /** * @brief Dereferencing, returns a const reference to the data. */ const T &operator*() const { april_assert(get() != 0); return *get(); } /** * @brief Assignment operator, transfers the ownership of the pointer * referenced by the given other object. */ UniquePtr &operator=(UniquePtr &other) { take(other.release()); return *this; } /** * @brief Assignment operator, transfers the ownership of the pointer * referenced by the given other object. */ template UniquePtr &operator=(UniquePtr &other) { take(other.release()); return *this; } /** * @brief Assignment operator, takes the ownership of the given pointer. */ UniquePtr &operator=(T *other) { reset(other); return *this; } /** * @brief Operator[], returns a reference to the data. */ T &operator[](int i) { april_assert(ptr != 0); return ptr[i]; } /** * @brief Operator[], returns a reference to the data. */ const T &operator[](int i) const { april_assert(ptr != 0); return ptr[i]; } bool operator==(const T *&other) const { return ptr == other; } bool operator!=(const T *&other) const { return ptr != other; } /** * @brief Bypasses the pointer, but stills having the ownership. */ T *get() { return ptr; } /** * @brief Bypasses the pointer, but stills having the ownership. */ const T *get() const { return ptr; } /** * @brief Releases the pointer and the ownership, but NOT executes delete, * so it transfers the ownership to the caller. */ T *release() { T *tmp = ptr; ptr = 0; return tmp; } /** * @brief Takes the ownership without executing the referencer. */ void take(T *other) { reset(); ptr = other; referencer.checkUnique(ptr); } /** * @brief Deletes its pointer, and takes ownership and executes the * referencer the given pointer. * * @note By default receives a NULL pointer. */ void reset(T *other = 0) { if (ptr != other) { referencer(other); deleter(ptr); ptr = other; referencer.checkUnique(ptr); } } bool empty() const { return get() == 0; }; private: Referencer referencer; Deleter deleter; T *ptr; }; template UniquePtr makeUniquePtr(T *ptr) { return UniquePtr(ptr); } } // namespace AprilUtils #endif // UNIQUE_PTR_H april-ann-0.4.1/packages/basics/util/c_src/unused_variable.h000066400000000000000000000016531263004425400240130ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef UNUSED_VARIABLE_H #define UNUSED_VARIABLE_H #define UNUSED_VARIABLE(x) (void)(x) #endif // IGNORE_RESULT_H april-ann-0.4.1/packages/basics/util/c_src/vector.h000066400000000000000000000115451263004425400221460ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef VECTOR_H #define VECTOR_H #include #include "swap.h" namespace AprilUtils { // Be careful! It's not std::vector :) template class vector { protected: T *vec; size_t used_size,vector_size; public: typedef T value_type; typedef T* pointer; typedef T& reference; typedef const T& const_reference; typedef size_t size_type; typedef ptrdiff_t difference_type; typedef T* iterator; typedef const T* const_iterator; size_type size() const { return used_size; } size_type capacity() const { return vector_size; } size_type max_size() const { return size_type(-1); } bool empty() const { return (used_size==0); } pointer release() { pointer tmp = vec; used_size = vector_size = 0; vec = 0; return tmp; } vector(size_type n=0) { // Creates a vector with n elements. used_size = n; vector_size = n; vec = 0; if (used_size > 0) { vec = new T[vector_size]; } } vector(size_type n, const_reference t) { // Creates a vector with n copies of t. used_size = n; vector_size = n; vec = 0; if (used_size > 0) { vec = new T[vector_size]; for (unsigned int i=0; i vector_size -> reservar vector mas grande. // used_size no cambia. if (n > vector_size) { vector_size = n; T *old_vec = vec; vec = new T[vector_size]; for (unsigned int i=0; i= vector_size) { size_type old_vector_size = vector_size; vector_size = (vector_size == 0) ? 1 : 2*vector_size; T *old_vec = vec; vec = new T[vector_size]; for (unsigned int i=0; i 0) used_size--; } reference back() { return vec[used_size-1]; } const_reference back() const { return vec[used_size-1]; } void resize(size_type n) { reserve(n); used_size = n; } void clear() { used_size = 0; } void swap(vector &other) { AprilUtils::swap(vec, other.vec); AprilUtils::swap(vector_size, other.vector_size); AprilUtils::swap(used_size, other.used_size); } iterator begin() { return vec; } const_iterator begin() const { return vec; } iterator end() { return vec+used_size; } const_iterator end() const { return vec+used_size; } }; } // namespace AprilUtils #endif april-ann-0.4.1/packages/basics/util/c_src/weak_ptr.h000066400000000000000000000126571263004425400224650ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef WEAK_PTR_H #define WEAK_PTR_H #include "april_assert.h" #include "error_print.h" #include "referenced.h" #include "shared_ptr.h" #include "unused_variable.h" namespace AprilUtils { /** * @brief A plain wrapper over a pointer. * * @note T can be any type, referenced or not referenced. * * The WeakPtr is constructed by passing a SharedPtr object. */ template class WeakPtr { WeakPtr(T *ptr=0) : ptr(ptr) { } WeakPtr &operator=(T *other) { reset(other); return *this; } /** * @brief Takes another pointer. */ void take(T *other) { reset(other); } /** * @brief Takes another pointer. */ void reset(T *other=0) { ptr = other; } public: /** * @brief Builds a WeakPtr from a given pointer, by default NULL. */ WeakPtr(); WeakPtr(WeakPtr &other) : ptr(other.ptr) { } template WeakPtr(SharedPtr &other) : ptr(other.ptr) { } WeakPtr(const WeakPtr &other) : ptr(other.ptr) { } WeakPtr(const SharedPtr &other) : ptr(other.ptr) { } template WeakPtr(WeakPtr &other) : ptr(other.ptr) { } template WeakPtr(SharedPtr &other) : ptr(other.ptr) { } template WeakPtr(const WeakPtr &other) : ptr(other.ptr) { } template WeakPtr(const SharedPtr &other) : ptr(other.ptr) { } /** * @brief Destructor. */ ~WeakPtr() { } /// True if the pointer is not empty. operator bool() const { return !empty(); } /// True if the pointer is empty. bool operator !() const { return empty(); } /** * @brief Dereferencing, returns the pointer itself. */ T *operator->() { return ptr; } /** * @brief Dereferencing, returns the pointer itself. */ const T *operator->() const { return ptr; } /** * @brief Dereferencing, returns a reference to the data. */ T &operator*() { return *ptr; } /** * @brief Dereferencing, returns a reference to the data. */ const T &operator*() const { return *ptr; } WeakPtr &operator=(WeakPtr &other) { reset(other.get()); return *this; } WeakPtr &operator=(SharedPtr &other) { reset(other.get()); return *this; } WeakPtr &operator=(const WeakPtr &other) { reset(other.ptr); return *this; } template WeakPtr &operator=(WeakPtr &other) { reset(other.get()); return *this; } template WeakPtr &operator=(SharedPtr &other) { reset(other.get()); return *this; } template WeakPtr &operator=(const WeakPtr &other) { reset(other.ptr); return *this; } template WeakPtr &operator=(const SharedPtr &other) { reset(other.ptr); return *this; } /** * @brief Operator[], returns a reference to the data. */ T &operator[](int i) { return ptr[i]; } /** * @brief Operator[], returns a reference to the data. */ const T &operator[](int i) const { return ptr[i]; } bool operator==(const WeakPtr &other) const { return ptr == other.ptr; } bool operator==(const SharedPtr &other) const { return ptr == other.ptr; } bool operator==(const T *&other) const { return ptr == other; } bool operator!=(const WeakPtr &other) const { return ptr != other.ptr; } bool operator!=(const SharedPtr &other) const { return ptr != other.ptr; } bool operator!=(const T *&other) const { return ptr != other; } /** * @brief Bypasses the pointer, but stills having it. */ T *get() { return ptr; } /** * @brief Bypasses the pointer, but stills having it. */ const T *get() const { return ptr; } /** * @brief Releases the pointer and assigns it to NULL. */ T *release() { T *tmp = ptr; ptr = 0; return tmp; } /** * @brief Returns a SharedPtr which takes the ownership of the referenced * pointer. */ SharedPtr lock() { return SharedPtr(get()); } bool empty() const { return ptr == 0; }; private: T *ptr; }; template WeakPtr makeWeakPtr(T *ptr) { return WeakPtr(ptr); } } // namespace AprilUtils #endif // WEAK_PTR_H april-ann-0.4.1/packages/basics/util/c_src/words_table.h000066400000000000000000000043141263004425400231450ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Jorge Gorbe Moya, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef WORDS_TABLE_H #define WORDS_TABLE_H #include // para debug #include "referenced.h" #include "vector.h" using AprilUtils::vector; namespace AprilUtils { class WordsTable : public Referenced { vector table_first_index; vector words; public: WordsTable() { /** la palabra 0 esta reservada **/ table_first_index.push_back(0); /** centinela **/ table_first_index.push_back(0); } WordsTable(WordsTable *other, unsigned int *filter) { for (unsigned int i=0; itable_first_index.size(); ++i) { table_first_index.push_back(other->table_first_index[i]); } words.reserve(other->words.size()); for (unsigned int i=0; iwords.size(); ++i) { words[i] = filter[other->words[i]]; } } ~WordsTable() { } void insertWords(unsigned int *vec, unsigned int size) { for (unsigned int i=0; i 0 then print(prefix) end if verbosity > 1 then print("No documentation found.") end return end local function build_short(str, color1) if #prefix > 0 then return { prefix, ansi.fg[color1]..str or "", ansi.fg["default"] } else return { ansi.fg[color1]..str or "", ansi.fg["default"] } end end local function build_list(out, list, desc) if list then table.insert(out, { "\n"..ansi.fg["cyan"]..desc..ansi.fg["default"] }) local names_table = {} for name,_ in pairs(list) do table.insert(names_table,name) end table.sort(names_table, function(a,b) return tostring(a) 1 and verbosity > 1 then print("--------------------------------------------------------------\n") end --local name = current.name local out = {} table.insert(out, build_short(current.class, "bright_red")) if verbosity > 0 then if current.summary then local aux = " " local str = string.truncate(current.summary, COLWIDTH, aux..aux..aux) str = string.gsub(str, "%[(.*)%]", "["..ansi.fg["bright_yellow"].."%1".. ansi.fg["default"].."]") table.insert(out[#out], str) end end if verbosity > 1 then if current.description then local str = string.truncate(current.description, COLWIDTH, " ") str = string.gsub(str, "%[(.*)%]", "["..ansi.fg["bright_yellow"].."%1".. ansi.fg["default"].."]") table.insert(out, { "\n"..ansi.fg["cyan"].."description:"..ansi.fg["default"], str }) end build_list(out, current.params, "parameters:") build_list(out, current.outputs, "outputs:") end for i=1,#out do out[i] = table.concat(out[i], " ") end print(table.concat(out, "\n")) if verbosity > 1 then print("") end end end -- verbosity => 0 only names, 1 only summary, 2 all function april_help(object, verbosity) local verbosity = verbosity or 2 if verbosity > 0 then if ( luatype(object) == "table" and object.meta_instance and object.meta_instance.id ) then print(ansi.fg["cyan"].."ID: "..ansi.fg["default"]..object.meta_instance.id) elseif get_object_id(object) then print(ansi.fg["cyan"].."ID: "..ansi.fg["default"]..get_object_id(object)) end end local object = object or _G ---------------------------------------------------------------------------- -- AUXILIARY FUNCTIONS local function print_result(aux) local prev = { } table.sort(aux, function(a,b) return a[1] 0 then print(ansi.fg["cyan"].." -- "..title..ansi.fg["default"]) print_result(aux) end end local function print_inheritance(title, object) while ( getmetatable(object) and get_index(getmetatable(object)) and not rawequal(get_index(getmetatable(object)), object) ) do local mt = getmetatable(object) local superclass_name = (mt.id and mt.id:gsub(" class","")) or "UNKNOWN" object = get_index(mt) process_pairs(title..superclass_name, { object }, function(k,v) return luatype(v) == "function" end) end end ---------------------------------------------------------------------------- -- documentation april_print_doc(object, verbosity) if class.is_class(object) and DOC_TABLE[object.constructor] then print("--------------------------------------------------------------\n") -- constructor documentation is defined at class_table.constructor method april_print_doc(object.constructor, verbosity) end local mt = getmetatable(object) if mt then -- metatable constructor and destructor if mt.__call then if DOC_TABLE[mt.__call] then -- constructor documentation is defined at -- getmetatable(class_table).__call metamethod print("--------------------------------------------------------------\n") april_print_doc(mt.__call, verbosity) end end -- metatable constructor and destructor print("--------------------------------------------------------------\n") process_pairs("metatable", { mt, get_index(mt) }, function(i,v) return luatype(v) == "function" end) if get_index(mt) then print_inheritance("inherited metatable from ", get_index(mt)) end end if luatype(object) == "table" then -- OBJECT class content print("--------------------------------------------------------------\n") -- local print_data = function(d) print("\t * " .. d) end local classes = {} local funcs = {} local names = {} local vars = {} for i,v in pairs(object) do if i ~= "meta_instance" then if class.is_class(v) then table.insert(classes, {i, "", v}) elseif iscallable(v) then table.insert(funcs, {i, string.format("%8s",luatype(v)), v}) elseif luatype(v) == "table" and object.meta_instance then table.insert(names, {i, "", v}) else table.insert(vars, {i, string.format("%8s",luatype(v)), v}) end end end if #vars > 0 then print(ansi.fg["cyan"].." -- basic variables (string, number)".. ansi.fg["default"]) print_result(vars) end if #names > 0 then print(ansi.fg["cyan"].." -- names in the namespace"..ansi.fg["default"]) print_result(names) end if #classes > 0 then print(ansi.fg["cyan"].." -- classes in the namespace"..ansi.fg["default"]) print_result(classes) end if #funcs > 0 then print(ansi.fg["cyan"].." -- static functions or tables"..ansi.fg["default"]) print_result(funcs) end -- OBJECT meta_instance if object.meta_instance and get_index(object.meta_instance) then process_pairs("object metatable", { object.meta_instance }) process_pairs("object methods", { get_index(object.meta_instance) }, function(i,v) return luatype(v) == "function" end) -- print_inheritance("inherited methods from ", get_index(object.meta_instance)) end end print() end function april_dir(t, verbosity) april_help(t, 0) end local april_doc_mt = { __concat = function(a,b) local tt = luatype(b) if tt == "table" and april_doc_mt == getmetatable(b) then table.insert(a,b[1]) return a else for _,t in ipairs(a) do april_set_doc(b,t) end return b end end, } function april_doc(t) return setmetatable({t}, april_doc_mt) end ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- -- support for IPyLua do local insert = table.insert local concat = table.concat local function insert_list(html, plain, list) local names_table = {} for name,_ in pairs(list) do table.insert(names_table,name) end table.sort(names_table, function(a,b) return tostring(a)%s%s"):format(name,desc)) insert(plain, (" %s: %s\n"):format(name,desc)) end end -- TODO: implement with different verbosity levels local function help(object, verbosity) local doc_table = DOC_TABLE[object] local cls = class.of(object) local super = cls and class.super(cls) or nil local id = get_object_id(object) if not doc_table then if cls then doc_table = DOC_TABLE[cls] end if not doc_table then return end end local html = { "

", "

APRIL help

", "", "", (""):format(type(object)), } local plain = { ("LuaType: %s\n"):format(type(object)), } if id then insert(html, (""):format(id)) insert(plain, ("ID: %s\n"):format(id)) end if cls then local x = tostring(cls):gsub(" class$",""):gsub("^class ","") insert(html, (""):format(x)) insert(plain, ("Class: %s\n"):format(x)) end if super then local x = tostring(super):gsub(" class$",""):gsub("^class ","") insert(html, (""):format(x)) insert(plain, ("Super: %s\n"):format(x)) end if type(obj) == "function" then local definition = {} local info = debug.getinfo(obj) if info.what == "Lua" and info.source then local source = info.source local first = info.linedefined local iterator if source:sub(1,1) == "@" then iterator = table.pack( io.lines(source:sub(2)) ) else iterator = table.pack( source:gmatch("([^\r\n]+)") ) end local k=1 for line in table.unpack( iterator ) do if k == first then definition = line:match("^%s*(.*)%s*$") break end k=k+1 end if definition then insert(html, (""):format(definition)) insert(plain, ("LuaDef: %s\n"):format(definition)) end end end insert(html, "
KeyValue
LuaType%s
ID%s
Class%s
Super%s
LuaDef%s
") for idx,current in ipairs(doc_table) do insert(plain, "\n") insert(html, ("

Doc %d

"):format(idx)) insert(plain, ("Doc %d\n"):format(idx)) insert(html, "") insert(html, "") local definition = {} if current.outputs then if #current.outputs == 0 and next(current.outputs) then table.insert(definition, "table") else local outs = {} for i=1,#current.outputs do if current.outputs[i] == "..." then outs[i] = "..." break else outs[i] = "out"..i end end table.insert(definition, table.concat(outs,",")) end table.insert(definition, " = ") end if #definition>0 then table.insert(definition, "funcname(") end if current.params then if #current.params == 0 and next(current.params) then table.insert(definition, "table") else local args = {} for i=1,#current.params do if current.params[i] == "..." then args[i] = "..." break else args[i] = "arg"..i end end table.insert(definition, table.concat(args,",")) end end if #definition>0 then table.insert(definition, ")") definition = table.concat(definition) insert(html, (""):format(definition)) insert(plain, ("Def.: %s\n"):format(definition)) end if current.class then insert(html, (""):format(current.class)) insert(plain, ("DocClass: %s\n"):format(current.class)) end if current.summary then insert(html, (""):format(current.summary)) insert(plain, ("Summary: %s\n"):format(current.summary)) end if current.description then insert(html, (""):format(current.description)) insert(plain, ("Desc.: %s\n"):format(current.description)) end if current.params then insert(html, "") insert(plain, "Params:\n") insert_list(html, plain, current.params) end if current.outputs then insert(html, "") insert(plain, "Outputs:\n") insert_list(html, plain, current.outputs) end insert(html, "
KeyValue
Def.%s
DocClass%s
Summary%s
Desc.%s
Params
Outputs
") end insert(html, "
") return html,plain end local function help_function_wrapper(obj, verbosity) local html,plain = help(obj, verbosity) if html and plain then local data = { ["text/html"] = concat(html), ["text/plain"] = concat(plain), } return data end end local reg = debug.getregistry() local IPyLua = reg.IPyLua or {} reg.IPyLua = IPyLua local help_functions = IPyLua.help_functions or {} IPyLua.help_functions = help_functions table.insert(help_functions, help_function_wrapper) end april-ann-0.4.1/packages/basics/util/lua_src/cast.lua000066400000000000000000000025471263004425400224710ustar00rootroot00000000000000cast = cast or {} local registry = debug.getregistry() registry.luabind_cast = registry.luabind_cast or {} local luabind_cast = registry.luabind_cast assert(type(luabind_cast) == "table", "Registry 'luabind_cast' field should be a table") local function try_cast(obj, cls_id) local obj_id = type(obj) assert(obj_id ~= cls_id) local tbl = luabind_cast[obj_id] if tbl then local f = tbl[cls_id] if f then return f(obj) end end return nil,"Unable to locate cast function" end local function lookup(obj, metainst) local obj_id = type(obj) local cls_id = assert(metainst.id, "Unable to locate 'id' field") -- base case if obj_id == cls_id then return obj end -- general case, traverse cls table recursively local metainst2 = getmetatable(metainst.index_table) if not metainst2 then return nil,"Incorrect derived class" end if rawequal(metainst, metainst2) then return nil,"Unable casting to given class" end local obj,msg = lookup(obj, metainst2) if obj then obj,msg = try_cast(obj, cls_id) end return obj,msg end assert(not cast.to, "cast.to has been set, it cannot be overwritten") cast.to = function(obj, cls) assert(class.is_class(cls), "Needs a class as 2nd argument") local metainst = assert(cls.meta_instance, "Needs a target class as 2nd argument") return lookup(obj, metainst) end april-ann-0.4.1/packages/basics/util/lua_src/field_manager.lua000066400000000000000000000046241263004425400243120ustar00rootroot00000000000000-- wrapper para field_manager field_manager = field_manager or {} field_manager.__index = field_manager setmetatable(field_manager, field_manager) -- constructor function field_manager:__call() local obj = { fields = {} } setmetatable(obj, self) return obj end -- devuelve un campo del field_manager function field_manager:get_field(name) return self.fields[name] end -- function field_manager:load_lines(s) if type(s) ~= 'table' or type(s.filename) ~= 'string' or type(s.field) ~= 'string' then error("Error in field_manager load_lines method incorrect arguments\n") end local aux = {} for line in io.lines(s.filename) do table.insert(aux, line) end self.fields[s.field] = aux end -- function field_manager:apply(s) -- comprobar argumentos if type(s) ~= 'table' or type(s.output_fields)~= 'table' or type(s.input_fields) ~= 'table' or type(s.the_function) ~= 'function' then error("Error in field_manager apply method incorrect arguments\n") end -- comprobar que el campo input_fields tiene al menos un campo local num_fields = #s.input_fields if num_fields == 0 then error("Error in field_manager apply method at least one input field is needed\n") end -- comprobar que todos los campos de input_fields son adecuados for i,fieldname in ipairs(s.input_fields) do if type(self.fields[fieldname]) ~= 'table' then error(string.format("Error in field_manager apply method ".. "data_field %s not found incorrect arguments\n",fieldname)) end end local num_results = #s.output_fields -- crear las tablas de resultados si hace falta: for j=1,num_results do if self.fields[s.output_fields[j]] == nil then self.fields[s.output_fields[j]] = {} end end -- iterar sobre los datos local size_data = #self.fields[s.input_fields[1]] for i = 1,size_data do -- aplicar funcion al dato i-esimo local argumentos = {} for j=1,num_fields do table.insert(argumentos,self.fields[s.input_fields[j]][i]) end table.insert(argumentos,i) local resul = {s.the_function(table.unpack(argumentos))} if #resul ~= num_results then error(string.format("Error in field_manager apply method at index %d",i)) end -- meter los datos for j=1,num_results do self.fields[s.output_fields[j]][i] = resul[j] end end end function field_manager:delete_field(fieldname) self.fields[fieldname] = nil end april-ann-0.4.1/packages/basics/util/lua_src/pipe.lua000066400000000000000000000023001263004425400224570ustar00rootroot00000000000000-- The pipe class is a wrapper around two C POSIX pipes (binded in APRIL-ANN) -- and has a simple interface which allow to configure the pipe for a -- child/parent pair, allowing to communicate both ends using the pipe. local pipe,pipe_methods = class("util.double_pipe") util = util or {} util.double_pipe = pipe function pipe:constructor() self.p1 = { util.pipe() } self.p2 = { util.pipe() } end function pipe:destructor() self:close() end function pipe_methods:set_as_child() self.IN = self.p2[1] self.p2[2]:close() self.OUT = self.p1[2] self.p1[1]:close() self.p1 = nil self.p2 = nil return self end function pipe_methods:set_as_parent() self.IN = self.p1[1] self.p1[2]:close() self.OUT = self.p2[2] self.p2[1]:close() self.p1 = nil self.p2 = nil return self end function pipe_methods:close() if self.IN then self.IN:close() end if self.OUT then self.OUT:close() end if self.p1 then self.p1[1]:close() self.p1[2]:close() end if self.p2 then self.p2[1]:close() self.p2[2]:close() end end function pipe_methods:write(...) return self.OUT:write(...) end function pipe_methods:read(...) return self.IN:read(...) end function pipe_methods:flush() self.OUT:flush() end april-ann-0.4.1/packages/basics/util/lua_src/set.lua000066400000000000000000000112421263004425400223220ustar00rootroot00000000000000local set,set_methods = class("set") _G.set = set function set:constructor(tbl) self:clear() tbl = tbl or {} for k,v in ipairs(tbl) do self:add(v) end end function set_methods:add(v) local tv = type(v) assert(tv == "number" or tv == "string", "Only numbers or strings allowed") local data = self.data local k = data[v] if not k then self.n = self.n+1 k = self.n data[v] = k end return k end function set_methods:clear() self.n = 0 self.data = {} return self end function set_methods:keys() return iterator(pairs(self.data)):select(1):table() end function set_methods:clone() return set(self:ctor_params()) end function set_methods:ctor_name() return "set" end function set_methods:ctor_params() return self:keys() end function set_methods:discard(v) local data = self.data local k = data[v] if k then data[v] = nil self.n = self.n - 1 end return self end function set_methods:difference(...) local others = table.pack(...) local result = {} for v,k in pairs(self.data) do local found = false for i=1,#others do if others[i].data[v] then found = true break end end if not found then result[#result+1] = v end end return set(result) end function set_methods:difference_update(...) local others = table.pack(...) for v,k in pairs(self.data) do for i=1,#others do if others[i].data[v] then self:remove(v) break end end end return self end function set_methods:intersection(...) local others = table.pack(...) local result = {} for v,k in pairs(self.data) do local fail = false for i=1,#others do if not others[i].data[v] then fail = true break end end if not fail then result[#result+1] = v end end return set(result) end function set_methods:intersection_update(...) local others = table.pack(...) for v,k in pairs(self.data) do for i=1,#others do if not others[i].data[v] then self:remove(v) break end end end return self end function set_methods:isdisjoint(other) local disjoint = true for v,k in pairs(self.data) do if other.data[v] then disjoint = false break end end return disjoint end function set_methods:issubset(other) local subset = true for v,k in pairs(self.data) do if not other.data[v] then subset = false break end end return subset end function set_methods:issuperset(other) return other:issubset(self) end function set_methods:pop() local v = next(self.data) self:remove(v) return v end function set_methods:remove(v) assert(self.data[v], "Element not found") self.data[v] = nil self.n = self.n - 1 end -- function set_methods:symmetric_difference(...) -- end -- function set_methods:symmetric_difference_update(...) -- end function set_methods:union(...) local result = self:clone() return result:update(...) end function set_methods:update(...) local others = table.pack(...) for i=1,#others do for v,k in pairs(others[i].data) do self:add(v) end end return self end function set_methods:consult(v) return self.data[v] or false end function set_methods:iterate() return coroutine.wrap(function() for name,_ in pairs(self.data) do coroutine.yield(name) end end) end class.extend_metamethod(set, "__tostring", function(self) local t = iterator(pairs(self.data)):select(1): take(10):map(tostring):table() table.sort(t) if #self > 10 then table.insert(t, "...") end return table.concat{"set{ ",table.concat(t, ", ")," } ", "N=", #self } end) class.extend_metamethod(set, "__eq", function(self, other) return self:issubset(other) and self:issuperset(other) end) class.extend_metamethod(set, "__lt", function(self, other) return self:issubset(other) and #self < #other end) class.extend_metamethod(set, "__len", function(self, other) return self.n end) class.extend_metamethod(set, "__sub", function(self, other) return self:difference(other) end) class.extend_metamethod(set, "__add", function(self, other) return self:union(other) end) -- cross-product -- class.extend_metamethod(set, "__mul", -- function(self, other) -- return ... -- end) -- set partition -- class.extend_metamethod(set, "__div", -- function(self, other) -- end) april-ann-0.4.1/packages/basics/util/lua_src/type.lua000066400000000000000000000001721263004425400225100ustar00rootroot00000000000000luatype = luatype or type function type(x) local real_type = luatype(x) return get_object_id(x) or real_type end april-ann-0.4.1/packages/basics/util/lua_src/util.lua000066400000000000000000001016511263004425400225100ustar00rootroot00000000000000------------------------------------------------------------------------------ local setmetatable = setmetatable local getmetatable = getmetatable local string = string local table = table local math = math local pairs = pairs local ipairs = ipairs local assert = assert -- Returns __index field from a metatable. When __index field is a function, it -- is expected to find index_table field with all the available methods. local function get_index(mt) if type(mt.__index) == "function" then return mt.index_table else return mt.__index end end ------------------------------------------------------------------------------ -- DEPRECATED isa = make_deprecated_function("isa", "class.is_a", class.is_a) class_extension = make_deprecated_function("class_extension", "class.extend", class.extend) class_get = make_deprecated_function("class_get", "class.consult", class.consult) class_get_value_of_key = make_deprecated_function("class_get_value_of_key", "class.consult", class.consult) is_class = make_deprecated_function("is_class", "class.is_class", class.is_class) ------------------------------------------------------------------------------ -- Clones the function and its upvalues local function clone_function(func,lookup_table) local lookup_table = lookup_table or {} -- clone by using a string dump local ok,func_dump = pcall(string.dump, func) local func_clone = (ok and loadstring(func_dump)) or func if func_clone ~= func then -- copy upvalues local i = 1 while true do local name,value = debug.getupvalue(func,i) if not name then break end if name == "_ENV" then debug.setupvalue(func_clone, i, value) else debug.setupvalue(func_clone, i, util.clone(value, lookup_table)) end i = i + 1 end end return func_clone end ------------------------------------------------------------------------------ function april_assert(condition, ...) if not condition then if next({...}) then local s,r = pcall(function (...) return(string.format(...)) end, ...) if s then error("assertion failed!: " .. r, 2) end end error("assertion failed!", 2) end return condition end ------------------------------------------------------------------------------ function sorted_pairs(tbl,cmp) local keys = {} for k in pairs(tbl) do keys[#keys+1] = k end table.sort(keys) return coroutine.wrap(function() local keys,tbl = keys,tbl for _,k in ipairs(keys) do coroutine.yield(k,tbl[k]) end end) end ------------------------------------------------------------------------------ pprint = function(...) local args = table.pack(...) for i,v in ipairs(args) do if type(v) == "table" then args[i] = util.to_lua_string(v, "ascii") else args[i] = tostring(v) end end print(table.unpack(args)) end ------------------------------------------------------------------------------ local LUA_BIND_CPP_PROPERTIES = {} setmetatable(LUA_BIND_CPP_PROPERTIES, { mode='k' }) -- table with weak keys function has_lua_properties_table(obj) assert(luatype(obj)=="userdata", "This functions only works with userdata") return LUA_BIND_CPP_PROPERTIES[obj] end function get_lua_properties_table(obj) assert(luatype(obj)=="userdata", "This functions only works with userdata") LUA_BIND_CPP_PROPERTIES[obj] = LUA_BIND_CPP_PROPERTIES[obj] or {} return LUA_BIND_CPP_PROPERTIES[obj] end function set_lua_properties_table(obj, t) assert(luatype(obj)=="userdata", "This functions only works with userdata") LUA_BIND_CPP_PROPERTIES[obj] = t return obj end ------------------------------------------------------------------------------ function get_table_from_dotted_string(dotted_string, create, basetable) local create = create or false local basetable = basetable or _G local t = string.tokenize(dotted_string, ".") if not create and not basetable[t[1]] then return nil end basetable[t[1]] = basetable[t[1]] or {} local current = basetable[t[1]] for i=2,#t do if not create and not current[t[i]] then return nil end current[t[i]] = current[t[i]] or {} current = current[t[i]] end return current end function check_version(major_num,minor_num,commit_num) local major_v,minor_v,commit_v = util.version() local major_num = major_num or major_v local minor_num = minor_num or minor_v local commit_num = commit_num or commit_v if major_num == major_v and minor_num == minor_v and commit_num==commit_v then return true else fprintf(io.stderr, "Incorrect version number, expected %d.%d commit %d, found %d.%d commit %d\n", major_num, minor_num, commit_num, major_v, minor_v, commit_v) return false end end -- makes a FAKE wrapper around a class, so you can re-implement the functions function class_wrapper(obj,wrapper) local wrapper = wrapper or {} local current = obj while (getmetatable(current) and get_index(getmetatable(current)) and not rawequal(get_index(getmetatable(current)),current)) do current = get_index(getmetatable(current)) for i,v in pairs(current) do if rawget(wrapper,i) == nil then if type(v) == "function" then wrapper[i] = function(first, ...) if rawequal(first,wrapper) then return obj[i](obj, ...) else return obj[i](...) end end -- function else -- if type(v) == "function" wrapper[i] = v end -- if type(v) == "function" ... else end -- if wrapper[i] == nil end -- for end -- while if getmetatable(wrapper) and get_index(getmetatable(wrapper)) then if getmetatable(get_index(getmetatable(wrapper))) then error("class_wrapper not works with derived or nil_safe objects") else setmetatable(get_index(getmetatable(wrapper)), getmetatable(obj)) end else wrapper = class_instance(wrapper, get_table_from_dotted_string(get_object_id(obj))) end return wrapper end function april_list(t) for i,v in pairs(t) do print(i,v) end end function get_object_id(obj) local id = nil if getmetatable(obj) then id = getmetatable(obj).id end return id end get_object_cls = class.of function april_print_script_header(arg,file) local file = file or io.stdout fprintf(file,"# HOST: %s\n", (io.popen("hostname", "r"):read("*l"))) fprintf(file,"# DATE: %s\n", os.date()) fprintf(file,"# VERSION: %d.%d COMMIT %s %s\n", util.version()) if arg and arg[0] then fprintf(file,"# CMD: %s %s\n", arg[0], table.concat(arg, " ")) end end -- auxiliary function for bind local function merge_unpack(t1, t2, i, j, n, m) i,j = i or 1, j or 1 n,m = n or t1.n, m or t2.n if i <= n then if t1[i] ~= nil then return t1[i],merge_unpack(t1, t2, i+1, j, n, m) else return t2[j],merge_unpack(t1, t2, i+1, j+1, n, m) end elseif j <= m then return t2[j],merge_unpack(t1, t2, i, j+1, n, m) end end -- allow to bind arguments to any Lua function (only variadic arguments) function bind(func, ...) local args = table.pack(...) if args.n == 1 then assert(args[1] ~= nil) return function(...) return func(args[1],...) end elseif args.n == 2 then assert(args[2] ~= nil) if args[1] ~= nil then return function(...) return func(args[1],args[2],...) end else return function(a,...) return func(a,args[2],...) end end else return function(...) return func(merge_unpack(args, table.pack(...))) end end end -- inspired by Penlight string_lambda: -- http://stevedonovan.github.io/Penlight/api/libraries/pl.utils.html#string_lambda local lambda do local memory = {} lambda = setmetatable({ clear = function() memory = {} end, }, { __call = function(self,fstr) local fun = memory[fstr] if not fun then local args,code = fstr:match("^%s*|(.+)|(.+)$") assert(args and code, "Needs args and code sections, e.g., |args|code") local fun_src = ("return function(%s) return %s end"):format(args,code) fun = assert(loadstring(fun_src))() memory[fstr] = fun end return fun end, }) end _G.lambda = lambda -- declare as global -- unpacks together several tables, by recursion (it is limited to short tables) local function private_munpack(i, j, m, ...) local n = select('#', ...) i,j = i or 1, j or 1 if i <= n then local t = select(i, ...) local m = m or t.n or #t if j <= m then return t[j],private_munpack(i, j+1, m, ...) else return private_munpack(i+1, 1, nil, ...) end end end function multiple_unpack(...) if select('#', ...) == 1 then return table.unpack(...) else return private_munpack(1, 1, nil, ...) end end -- http://lua-users.org/wiki/IteratorsTutorial function multiple_ipairs(...) local t = {...} local tmp = {...} -- if nothing to iterate over just return a dummy iterator if #tmp==0 then return function() end, nil, nil end local function mult_ipairs_it(t, i) i = i+1 local all_nil = true for j=1,#t do local val = t[j][i] if val ~= nil then all_nil = false end tmp[j] = val end if all_nil then return nil end return i, unpack(tmp) end return mult_ipairs_it, t, 0 end function filter(func, ...) assert(func, "filter: needs a function as first argument") local t,key,value = {} for key,value in ... do local v = value or key if func(v) then table.insert(t,v) end end return t end function map(func, ...) if not func then func = function(v) return v end end local t,key,value = {} for key,value in ... do if not value then key,value = #t+1,key end local r = func(value) if r then t[key] = r end end return t end function map2(func, ...) if not func then func = function(k,v) return v end end local t,key,value = {} for key,value in ... do if not value then key,value = #t+1,key end local r = func(key,value) if r then t[key] = r end end return t end function mapn(func, f, s, v) if not func then func = function(k,...) return ... end end local t = {} local tmp = table.pack(f(s,v)) while tmp[1] ~= nil do t[v] = func(table.unpack(tmp)) tmp = table.pack(f(s,tmp[1])) end return t end function glob(...) local r = {} for i,expr in ipairs(table.pack(...)) do local f = io.popen("ls -d "..expr) for i in f:lines() do table.insert(r,i) end f:close() end return r end -- executes in parallel a function, and returns the concatenation of all results function parallel_foreach(num_processes, list_number_or_iterator, func) local tt = type(list_number_or_iterator) assert(tt == "number" or tt == "table" or class.is_a(list_number_or_iterator, iterator), "Needs an APRIL-ANN iterator, table or number as 2nd argument") local data_it -- in any case, convert list_number_or_iterator into an iterator if tt == "number" then data_it = iterator.range(list_number_or_iterator) else data_it = iterator(list_number_or_iterator) end if num_processes == 1 then -- special case for only 1 process local out = {} while true do local arg = table.pack(data_it()) if arg[1] == nil then break end out[#out + 1] = util.pack( func(table.unpack(arg)) ) end return out else -- general case for N processes local OMP_NUM_THREADS = util.omp_get_num_threads() util.omp_set_num_threads(1) local outputs = iterator(range(1,num_processes)): map(function(idx) return os.tmpname() end):table() local id,pid = util.split_process(num_processes) local id_rem = id-1 local f = io.open(outputs[id], "w") fprintf(f, "return {\n") -- traverse all iterator values local index = 0 while true do local arg = table.pack(data_it()) if arg[1] == nil then break end index = index + 1 if (index%num_processes) == id_rem then -- data correspond to current process table.insert(arg, id) local ret = util.pack( func(table.unpack(arg)) ) if ret ~= nil then fprintf(f,"[%d] = %s,\n", index, util.to_lua_string(ret, "binary")) end end end fprintf(f, "}\n") f:close() -- waits for all childrens util.wait() if id > 1 then os.exit(0) end util.omp_set_num_threads(OMP_NUM_THREADS) -- maps all the outputs to a table return iterator(ipairs(outputs)): map(function(index,filename) local t = util.deserialize(filename) os.remove(filename) -- multiple outputs from this filename for k,v in pairs(t) do coroutine.yield(k,v) end end):table() end end function clrscr() io.write("\027[2J") -- ANSI clear screen io.write("\027[H") -- ANSI home cursor end function printf(...) io.write(string.format(...)) end function fprintf(file,...) file:write(string.format(...)) end function check_mandatory_table_fields(fields, t) for _,name in ipairs(fields) do table.insert(ret, t[name] or error("The "..name.." field is mandatory")) end end -- -- local params = get_table_fields{ -- begin_token = { type_match = "string", mandatory = false, default = "" }, -- end_token = { type_match = "string", mandatory = false, default = "" }, -- unknown_word = { type_match = "string", mandatory = false, default = "" }, -- factors = { type_match = "table", mandatory = true, -- getter = get_table_fields_ipairs{ -- vocabulary = { isa_match(lexClass), mandatory = true }, -- layers = { type_match = "table", mandatory = true, -- getter = get_table_fields_ipairs{ -- actf = { type_match = "string", mandatory = true }, -- size = { type_match = "number", mandatory = true }, -- }, -- }, -- }, -- }, -- } local valid_get_table_fields_params_attributes = { type_match = true, isa_match = true, mandatory = true, getter = true, default = true } function get_table_fields(params, t, ignore_other_fields) local is_a = class.is_a local type = type local pairs = pairs local ipairs = ipairs local luatype = luatype -- local params = params or {} local t = t or {} local ret = {} for key,value in pairs(t) do if not params[key] then if ignore_other_fields then ret[key] = value else error("Unknown field: " .. key) end end end for key,data in pairs(params) do if params[key] then local data = data or {} for k,_ in pairs(data) do if not valid_get_table_fields_params_attributes[k] then error("Incorrect parameter to function get_table_fields: " .. k) end end -- each param has type_match, mandatory, default, and getter local v = t[key] if v == nil then v = data.default end if v == nil and data.mandatory then error("Mandatory field not found: " .. key) end if v ~= nil and data.type_match and (luatype(v) ~= data.type_match or type(v) ~= data.type_match) then if data.type_match ~= "function" or not iscallable(v) then error("Incorrect type '" .. type(v) .. "' for field '" .. key .. "'") end end if v ~= nil and data.isa_match and not is_a(v, data.isa_match) then error("Incorrect field isa_match predicate: " .. key) end if data.getter then v=(t[key]~=nil and data.getter(t[key])) or nil end ret[key] = v end -- if params[key] then ... end -- for key,data in pairs(params) ... return ret end function get_table_fields_ipairs(...) local arg = table.pack(...) return function(t) local table = table local t = t or {} local ret = {} for i,v in ipairs(t) do table.insert(ret, get_table_fields(table.unpack(arg), v)) end return ret end end function get_table_fields_recursive(...) local arg = table.pack(...) return function(t) local t = t or {} return get_table_fields(table.unpack(arg), t) end end --------------------------------------------------------------- ------------------------ MATH UTILS --------------------------- --------------------------------------------------------------- -- log addition function math.logadd(a,b) if a > b then return a + math.log1p(math.exp(b-a)) else return b + math.log1p(math.exp(a-b)) end end -- auxiliary function for fast development of reductions function math.lnot(a) return not a end -- auxiliary function for fast development of reductions function math.lor(a,b) return a or b end -- auxiliary function for fast development of reductions function math.land(a,b) return a and b end -- auxiliary function for fast development of reductions function math.ge(a,b) assert(a and b, "Needs one argument, you can use bind function to freeze any arg") return a>=b end -- auxiliary function for fast development of reductions function math.gt(a,b) assert(a and b, "Needs one argument, you can use bind function to freeze any arg") return a>b end -- auxiliary function for fast development of reductions function math.le(a,b) assert(a and b, "Needs one argument, you can use bind function to freeze any arg") return a<=b end -- auxiliary function for fast development of reductions function math.lt(a,b) assert(a and b, "Needs one argument, you can use bind function to freeze any arg") return a 0 then return math.floor(val + 0.5) end return -math.floor(-val + 0.5) end function math.clamp(value,lower,upper) assert(lower<=upper) -- sanity check return math.max(lower,math.min(value,upper)) end function math.median(t, ini, fin) error("Removed, use a matrix and stats.percentile() instead") end function math.mean(t, ini, fin) error("Removed, use a matrix and stats.amean() instead") end function math.std(t, ini, fin) error("Removed, use a matrix and stats.std() instead") end -- computes the sign of a number function math.sign(v) return (v>0 and 1) or (v<0 and -1) or 0 end --------------------------------------------------------------- ------------------------ STRING UTILS ------------------------- --------------------------------------------------------------- getmetatable("").__mod = function(self,t) assert(type(t) == "table", "Needs a table as parameter") return self:gsub("$(%a[%a%d]*)",t):format(table.unpack(t)) end function string.truncate(str, columns, prefix) local columns = columns - #prefix - 1 local lines = string.tokenize(str, "\n") local out = { { } } for _,line in ipairs(lines) do local words = string.tokenize(line, " ") local size = 0 for i,w in ipairs(words) do if #w + size > columns then size = 0 table.insert(out, { prefix }) end table.insert(out[#out], w) size = size + #w end end for i=1,#out do out[i] = table.concat(out[i], " ") end return table.concat(out, "\n") end function string.basename(path) local name = string.match(path, "([^/]+)$") return name end function string.remove_extension(path) local name,ext = string.match(path, "(.*)[.]([^.]*)$") return name,ext end function string.get_extension(path) local ext = string.match(path, ".*[.]([^.]*)$") return ext end function string.get_path(path_with_filename, sep) local sep=sep or'/' return path_with_filename:match("(.*"..sep..")") or "./" end string.dirname = string.get_path -- synonim function string.words_of(t) return string.gmatch(t, "[^%s]+") end function string.lines_of(t) return string.gmatch(t,"[^\n]+") end function string.chars_of_iterator(s,v) if v < string.len(s) then v = v+1 return v,string.sub(s,v,v) end end function string.chars_of(s) return string.chars_of_iterator,s,0 end function string.tokenize(str,sep) local sep = sep or ' \t\n\r' local list = {} for token in string.gmatch(str, '[^'..sep..']+') do table.insert(list,token) end return list end function string.tokenize_width(str,width) local width = width or 1 local list = {} for i = 1,string.len(str)-width+1,width do table.insert(list, string.sub(str,i,i+width-1)) end return list end -- function string.split (text, ...) -- local delimiter = ((arg.n > 0) and arg[1]) or ' ' -- local list = {} -- local first,last -- local pos = 1 -- if string.find("", delimiter, 1, true) then -- -- this would result in endless loops -- error("delimiter matches empty string!") -- end -- while 1 do -- first, last = string.find(text, delimiter, pos,true) -- if first then -- found? -- table.insert(list, string.sub(text, pos, first-1)) -- pos = last+1 -- else -- table.insert(list, string.sub(text, pos)) -- return list -- end -- end -- end -- function string.join (list,...) -- local delimiter = ((arg.n > 0) and arg[1]) or ' ' -- return table.concat(list,delimiter) -- end string.join = table.concat --------------------------------------------------------------- ------------------------ TABLE UTILS -------------------------- --------------------------------------------------------------- function table.clear(t) for k,v in pairs(t) do t[k] = nil end end function table.unpack_on(t, dest, overwrite) for i,j in pairs(t) do april_assert(overwrite or not dest[i], "Redefinition of key %s", i) dest[i] = j end end function table.invert(t) local n = {} for i,j in pairs(t) do n[j] = i end return n end function table.slice(t, ini, fin) local aux = {} for i=ini,fin do table.insert(aux, t[i]) end return aux end function table.search_key_from_value(t,value) for i,j in pairs(t) do if j == value then return i end end end function table.imap(t,f) return map(f, ipairs(t)) end function table.map(t,f) return map(f, pairs(t)) end function table.imap2(t,f) return map2(f, ipairs(t)) end function table.map2(t,f) return map2(f, pairs(t)) end function table.reduce(t,f,initial_value) return reduce(f, initial_value, ipairs(t)) end function table.ifilter(t,f) local n = {} for i,j in ipairs(t) do if f(i,j) then table.insert(n, j) end end return n end function table.filter(t,f) local n = {} for i,j in pairs(t) do if f(i,j) then n[i]=j end end return n end function table.join(t1,t2) local result={} local k=1 if t1 and #t1 > 0 then for _,j in ipairs(t1) do table.insert(result, j) end end if t2 and #t2 > 0 then for _,j in ipairs(t2) do table.insert(result, j) end end return result end function table.merge(t1,t2) local result = util.clone(t1) for k,v in pairs(t2) do result[k] = util.clone(v) end return result end -- Warning: this function makes a DEEP copy of LUA tables, but userdata objects -- are copied as references function table.deep_copy(t, lookup_table) local copy = {} for i,v in pairs(t) do if luatype(v) ~= "table" then copy[i] = v else lookup_table = lookup_table or {} lookup_table[t] = copy if lookup_table[v] then copy[i] = lookup_table[v] -- we already copied this table. reuse the copy. else copy[i] = table.deep_copy(v,lookup_table) -- not yet copied. copy it. end end end return copy end ----- -- to string ----- -- devuelve el valor maximo de una tabla function table.max(t) local max,index for i,j in pairs(t) do if max==nil or j>max then index = i max = j end end return max,index end -- devuelve el valor minimo de una tabla function table.min(t) local min,index for i,j in pairs(t) do if min==nil or jstring, associates to", "each parameter name a description.", "The description string could be a table,", "which will be contatenated with ' '.", }, ["outputs"] = { "A dictionary string=>string, associates to", "each output name a description.", "The description string could be a table,", "which will be contatenated with ' '.", }, }, }) april_set_doc(map, { class = "function", summary = "An implementation of python map function", description = { "This function returns a table which is the result of", "apply a given function to all the elements of a set.", "The set of elements is traversed using iterator functions.", "The table contains as many elements as the set, and only", "keeps the first returned value of the function (or a table", "if the function returns a table).", }, params = { { "A function to be applied to all elements values [optional].", "If not given, the identity function will be used. " }, "An iterator function which returns the whole set of elements", "First argument to the iterator (normally the caller object) [optional]", "Second argument [optional]", "..." }, outputs = { { "A table with the key,value pairs. Keys are", "the same as iterator function returns, but values", "are after application of given function", }, }, }) april_set_doc(map2, { class = "function", summary = "An implementation of python map function", description = { "This function returns a table which is the result of", "apply a given function to all the elements of a set.", "The set of elements is traversed using iterator functions.", "The table contains as many elements as the set, and only", "keeps the first returned value of the function (or a table", "if the function returns a table).", }, params = { { "A function to be applied to all element key,value pairs [optional].", "If not given, the identity function will be used. " }, "An iterator function which returns the whole set of elements", "First argument to the iterator (normally the caller object) [optional]", "Second argument [optional]", "..." }, outputs = { { "A table with the key,value pairs. Keys are", "the same as iterator function returns, but values", "are after application of given function", }, } }) april_set_doc(signal.register, { class="function", summary="Registers execution of Lua function with a given signal", description = { "This function fails if the given signal was registered before", "by other function different than this.", "If a nil value is given for the function, the signal will", "be ignored.", }, params = { "A signal number, use the helpers signal.SIG...", "A lua function", }, }) april_set_doc(signal.release, { class="function", summary="Releases the Lua function associated with the given signal", description = { "This function fails if the given signal was registered before", "by other function different than signal.register(...).", }, params = { "A signal number, use the helpers signal.SIG_...", }, }) -------------------------------------------- april_set_doc(util.stopwatch,{ class = "class", summary = "Stopwatch class for time measurement", }) april_set_doc(util.stopwatch,{ class = "function", summary = "Constructor of stopwatch", }) april_set_doc(util.stopwatch.."go", { class = "method", summary = "Starts timer", }) april_set_doc(util.stopwatch.."stop", { class = "method", summary = "Stops timer", }) april_set_doc(util.stopwatch.."reset",{ class = "method", summary = "Resets timer", }) april_set_doc(util.stopwatch.."read",{ class = "method", summary = "Resets timer", outputs = { "Elapsed CPU time in sec.", "Elapsed wall time in sec." }, }) april_set_doc(util.stopwatch.."is_on",{ class = "method", summary = "Is on predicate", outputs = { "A boolean indicating object status", }, }) april_set_doc(util.stopwatch.."clone",{ class = "method", summary = "Deep copy", outputs = { "A deep copy of the caller object", }, }) april-ann-0.4.1/packages/basics/util/lua_src/util_serialization.lua000066400000000000000000000350071263004425400254460ustar00rootroot00000000000000local MAGIC = "-- LS0001" local FIND_MASK = "^" .. MAGIC:gsub("%-","%%-") local DEFAULT_BLOCK_SIZE = 2^20 local ENV_TAG = function() return "ENV dummy function" end -- dummy function local NIL_TAG = function() return "NIL dummy function" end -- dummy function ----------------------------------------------------------------------- __ipairs_iterator__ = select(1,ipairs({})) __pairs_iterator__ = select(1,pairs({})) local builtin = { [__ipairs_iterator__] = "__ipairs_iterator__", [__pairs_iterator__] = "__pairs_iterator__", [ENV_TAG] = "_ENV", [NIL_TAG] = "nil", } local blacklist = { _ENV = true, _G = true, debug = true, package = true, } local update_builtin_environment do local type = luatype or type function update_builtin_environment(tbl, prefix, visited) tbl, prefix, visited = tbl or _G, prefix or "", visited or {} if visited[tbl] then return end visited[tbl] = true for k,v in pairs(tbl) do if type(k) == "string" and not blacklist[k] then local next_prefix = (#prefix>0) and ("%s.%s"):format(prefix,k) or k if type(v) == "table" then update_builtin_environment(v, next_prefix, visited) elseif type(v) == "function" and not builtin[v] then builtin[v] = next_prefix end end end end end update_builtin_environment() ----------------------------------------------------------------------- -- adding serialization to iterator class class.extend(iterator, "ctor_name", function(self) return "iterator" end) class.extend(iterator, "ctor_params", function(self) return self:get() end) ----------------------------------------------------------------------- -- utilities for function serialization local function char(c) return ("\\%03d"):format(c:byte()) end local function szstr(s) return ('"%s"'):format(s:gsub("[^ !#-~]", char)) end function util.function_setupvalues(func, upvalues) for i,value in pairs(upvalues) do if value == ENV_TAG then debug.setupvalue(func, i, _ENV) elseif value == NIL_TAG then debug.setupvalue(func, i, nil) else debug.setupvalue(func, i, value) end end return func end function util.function_to_lua_string(func,format) -- local func_dump = string.format("assert(load(%q))", string.dump(func)) local upvalues = {} local i = 1 while true do local name,value = debug.getupvalue(func,i) if not name then break end -- global environment upvalue and nil are special if name == "_ENV" then value = ENV_TAG elseif value==nil then value = NIL_TAG end upvalues[i] = value i = i + 1 end -- local t = { "util.function_setupvalues(", func_dump, ",", table.tostring(upvalues,format), ")" } return table.concat(t, "") end function table.tostring(t,format) format = format or "binary" if t.to_lua_string then return t:to_lua_string(format) end local out = {} -- first serialize the array part of the table local j=1 while t[j] ~= nil do local v = t[j] local value local tt = luatype(v) if tt == "table" then value = table.tostring(v,format) elseif tt == "string" then value = string.format("%q",v) elseif tt == "userdata" then assert(v.to_lua_string, "Needs to_lua_string method") value = v:to_lua_string(format) elseif tt == "function" then value = util.function_to_lua_string(v,format) else value = (v==math.huge) and "math.huge" or tostring(v) end table.insert(out, value) j=j+1 end -- extract all keys removing array part local keys = iterator(pairs(t)):select(1): filter(function(key) local k = tonumber(key) return not k or k<=0 or k>=j end):table() -- sort the keys in order to obtain a deterministic result table.sort(keys, function(a,b) return tostring(a) < tostring(b) end) -- serialize non array part of the table for _,i in ipairs(keys) do local v = t[i] local key local value if luatype(i) == "string" then key = string.format("[%q]=",i) elseif tonumber(i) then key = "[".. ( (i==math.huge) and "math.huge" or i ) .."]".."=" else key = string.format("[%q]=",tostring(i)) end local tt = luatype(v) if tt == "table" then value = table.tostring(v,format) elseif tt == "string" then value = string.format("%q",v) elseif tt == "userdata" then assert(v.to_lua_string, "Needs to_lua_string method") value = v:to_lua_string(format) elseif tt == "function" then value = util.function_to_lua_string(v,format) else value = (v == math.huge) and "math.huge" or tostring(v) end table.insert(out, key .. value) end return "{"..table.concat(out,",").."}" end function util.to_lua_string(data,format) local tt = luatype(data) if tt == "table" then if data.to_lua_string then return data:to_lua_string(format) else return table.tostring(data,format) end elseif tt == "string" then return string.format("%q", data) elseif tt == "function" then return util.function_to_lua_string(data,format) elseif tt == "userdata" then local idx = getmetatable(data) assert(idx, "Userdata needs a to_lua_string(format) method") idx = get_index(idx) assert(idx and idx.to_lua_string, "Userdata needs a to_lua_string(format) method") return data:to_lua_string(format) else return (data==math.huge) and "math.huge" or tostring(data) end end -- forward declaration local serialize do local non_structured = { string=true, number=true, boolean=true, } -- mapper class, it allows to map any Lua object to integers, allowing to -- enumerate uniquely all serialized objects local mapper_mt = { __index = { -- searchs a Lua object and stores it if needed add = function(self, obj) local data = self.data local id = data[obj] if not id then local n=self.n+1 id=n data[obj]=n self.n=n end return id end, -- returns the integer associated with a given Lua object (or nil in case -- of failure) consult = function(self, obj) return self.data[obj] end } } local function mapper() return setmetatable({ n=0, data={} }, mapper_mt) end -- lua_string_stream class, inserts Lua strings into a Lua table, -- and at the end it is possible to concatenate them all together. local lua_string_stream_mt = { __index = { write = function(self,data) table.insert(self, data) end, concat = function(self) return table.concat(self) end, is_lua_string_stream = true, }, } local function lua_string_stream() return setmetatable({}, lua_string_stream_mt) end -- normalizes values converting them into strings local function value2str(data, tt) local tt = tt or type(data) assert(tt ~= "thread", "Unable to serialize coroutines") if tt == "string" then return "%q"%{data} else return (data == math.huge) and "math.huge" or tostring(data) end end local function non_structured_split(data) local n = 0 local non_st = {} for k,v in pairs(data) do local tk = type(k) local tv = type(v) if non_structured[tk] and non_structured[tv] then non_st[k]=v n=n+1 end end return n,non_st end -- transforms a given Lua object (data), returning a string with the -- transformed object local function transform(map, varname, data, destination) local tt = type(data) -- plain types are returned as is if non_structured[tt] then return value2str(data, tt) end local id = map:consult(data) -- If data is not found in the map, it is necessary to process it and -- transform all of its dependencies. Otherwise, the id is used to retrieve -- the transformed data from previously id position in varname. if not id then id = map:add(data) if tt == "table" then -- split table into non-structured table data (string and numbers) local n,non_st = non_structured_split(data) -- creates a new table, and subsequently traverses all its content destination:write("%s[%d]="%{varname,id}) if n==0 then destination:write("{}") -- empty table else destination:write(table.tostring(non_st)) end -- table with data destination:write("\n") for k,v in pairs(data) do if not non_st[k] then local kstr = transform(map, varname, k, destination) local vstr = transform(map, varname, v, destination) destination:write("%s[%d][%s]=%s\n"%{varname,id,kstr,vstr}) end end elseif tt == "function" then if not builtin[data] then -- serializes the function with all of its upvalues -- NOTE that upvalues which are plain objects (strings or integers) -- are not shared between functions, but tables and userdata objects -- will be shared when serializing together several functions. local upvalues = {} local i = 1 while true do local name,value = debug.getupvalue(data,i) if not name then break end -- global environment upvalue and nil are special if name == "_ENV" then value = ENV_TAG elseif value==nil then value = NIL_TAG end upvalues[i] = value i = i + 1 end local ok,upv_str = pcall(transform, map, varname, upvalues, destination) if not ok then error(upv_str) end local ok,aux = pcall(string.dump, data) if not ok then error(aux) end local func_dump = "assert(load(%q))"%{ aux } destination:write("%s[%d]=util.function_setupvalues(%s,%s)\n"% {varname,id,func_dump,upv_str}) else local func_dump = "%s"%{ builtin[data] } destination:write("%s[%d]=%s\n"%{varname,id,func_dump}) end elseif class.of(data) then local serialize = getmetatable(data).serialize if serialize then destination:write("%s[%d]="%{varname,id}) if destination.is_lua_string_stream then destination:write("%s"%{serialize(data)}) else serialize(data, destination) end destination:write("\n") else -- it is an object, so we need to use its introspection methods assert(data.ctor_params, "Userdata needs a function called ctor_params to be serializable") assert(data.ctor_name, "Userdata needs a function called ctor_name to be serializable") local ctor_requires = data.ctor_requires and data:ctor_requires() or {} for i=1,#ctor_requires,2 do destination:write('local %s = require"%s"\n'%{ ctor_requires[i+1], ctor_requires[i] }) end local params = table.pack( data:ctor_params() ) local ctor_name = data:ctor_name() local params_str = "" if params.n > 0 then local needs_unpack = true if params.n == 1 then params = params[1] needs_unpack=false else params.n = nil end params_str = transform(map, varname, params, destination) if needs_unpack then params_str = "table.unpack(%s)"%{params_str} end end destination:write("%s[%d]=%s(%s)\n"%{varname,id,ctor_name,params_str}) end elseif class.is_class(data) then -- general case local cls_id = data.meta_instance.id local value = 'assert(class.find("%s"), "Unable locate class %s")'%{cls_id,cls_id} destination:write("%s[%d]=%s\n"%{varname,id,value}) else -- general case local value = value2str(data) destination:write("%s[%d]=%s\n"%{varname,id,value}) end end return "%s[%d]"%{varname,id} end serialize = april_doc{ class = "function", summary = "Serializes an object to a filename or a string", params = { "Any object, table, string, number, ...", "A filename [optional], if not given an string would be returned", "Format string: 'ascii' or 'binary' [optional]", }, outputs = { "In case of nil second argument, this function", "returns a string with the serialized object.", }, } .. function(data, destination, format) local version = { util.version() } table.insert(version, os.date()) local comment = "-- version info { major, minor, commit number, commit hash, date }" local version_info = "\n%s\n-- %s\n"%{ comment, util.to_lua_string(version, format) } -- local map = mapper() local destination = destination or lua_string_stream() local do_close = false if type(destination)=="string" then destination = io.open(destination, "w") do_close = true end local varname = "_" destination:write(MAGIC) destination:write("\n") destination:write("local %s={}\n"%{varname}) local str = transform(map, "_", data, destination, format) destination:write("return %s%s"%{str,version_info}) if type(destination) == "table" and destination.concat then return destination:concat() elseif do_close then destination:close() end end end local deserialize deserialize = april_doc{ class = "function", summary = "Deserializes an object from a filename or a string", params = { "A string with a filename, a serialized string or an opened file", { "... a variadic list of arguments to be passed to", "the object during deserialization", }, }, outputs = { "A deserialized object", }, } .. function(dest, ...) local result if type(dest) == "string" then if dest:find(FIND_MASK) or dest:find("^return ") then -- it is a previously serialized string local loader = assert( load(dest) ) return loader(...) else local f = april_assert(io.open(dest), "Unable to locate %s\n", dest) return deserialize(f, ...) end elseif iscallable(dest) then -- DEPRECATED: to be removed local f = assert( load(dest()) ) return f(...) else assert(dest.read, "Needs a string or an opened file") local loader = assert( load(dest:lines(DEFAULT_BLOCK_SIZE)) ) return loader(...) end end ------------------------------------------------------------------------------ util.serialize = serialize util.deserialize = deserialize april-ann-0.4.1/packages/basics/util/package.lua000066400000000000000000000023401263004425400214710ustar00rootroot00000000000000package{ name = "util", version = "1.0", depends = { "class", "iterator" }, keywords = { }, description = "", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_util.lua.cc" , dest_dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test-functional-programming.lua", "test/test.lua", "test/test_set.lua", }, }, c_unit_test{ file = { "test/all_util_unit_test.cc" }, }, }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", dest_dir = "build", -- flags = "-std=c99", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_util.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/util/test/000077500000000000000000000000001263004425400203535ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/util/test/all_util_unit_test.cc000066400000000000000000000010311263004425400245600ustar00rootroot00000000000000#include "gtest.h" // all the test .cc files #include "test_buffer_list.cc" #include "test_context.cc" #include "test_constString.cc" #include "test_fifo.cc" #include "test_fifo_block.cc" #include "test_geometry.cc" #include "test_hash_table.cc" #include "test_hash_table_empty_value.cc" #include "test_list.cc" #include "test_logbase.cc" #include "test_max_min_finder.cc" #include "test_maxiphobic_minheap.cc" #include "test_open_adressing_hash.cc" #include "test_slist.cc" #include "test_smart_ptr.cc" APRILANN_GTEST_MAIN(test_util) april-ann-0.4.1/packages/basics/util/test/compile_test_hash_table.sh000066400000000000000000000000431263004425400255450ustar00rootroot00000000000000g++ -I ../c_src test_hash_table.cc april-ann-0.4.1/packages/basics/util/test/compile_test_open_adressing_hash.sh000077500000000000000000000000541263004425400274630ustar00rootroot00000000000000g++ -I ../c_src test_open_adressing_hash.cc april-ann-0.4.1/packages/basics/util/test/file.txt000066400000000000000000000001101263004425400220230ustar00rootroot00000000000000Esta | es | una | linea. Otra mas. Otra linea; |||||||| y una en blanco april-ann-0.4.1/packages/basics/util/test/test-signal.lua000066400000000000000000000002071263004425400233070ustar00rootroot00000000000000signal.register(signal.SIGQUIT, function() print("HOLA") end) print(io.read("*l")) signal.release(signal.SIGQUIT) print(io.read("*l")) april-ann-0.4.1/packages/basics/util/test/test.lua000066400000000000000000000036741263004425400220470ustar00rootroot00000000000000local check = utest.check local T = utest.test T("GenericOptionsTest", function() check(function() return util.options.test() end) local tbl,str2 = util.options.test() check.TRUE(tbl.clock1) check.TRUE(tbl.clock2) check.TRUE(class.is_a(tbl.clock1, util.stopwatch)) check.TRUE(class.is_a(tbl.clock2, util.stopwatch)) check.eq(tbl.str, "Hello world!") check.eq(str2, util.to_lua_string(tbl)) end) T("BindFunctionTest", function() -- bind function local f = bind(math.add, 5) local g = bind(math.div, nil, 3) check.eq( f(3), 8 ) check.eq( g(6), 2 ) end) T("MultipleUnpackTest", function() local t = table.pack( multiple_unpack({1,2,3},{4,5},{6,7,8}) ) for i=1,#t do check.eq(t[i], i) end local t = table.pack( multiple_unpack{1,2,3,4,5,6,7,8,9} ) for i=1,#t do check.eq(t[i], i) end local t = table.pack( multiple_unpack(table.pack(1, nil, 3, nil), table.pack(5, nil, nil, 8)) ) check.eq(t.n, 8) for i=1,t.n do check.TRUE(t[i] == i or t[i] == nil) end end) T("SerializationTest", function() local t = {1,2,3,a={2,3},c=util.stopwatch()} local t2 = util.deserialize(util.serialize(t)) check.eq(t2[1],1) check.eq(t2[2],2) check.eq(t2[3],3) check.eq(t2.a[1],2) check.eq(t2.a[2],3) check.eq(type(t2.c), "util.stopwatch") end) T("LambdaTest", function() local f = lambda'|x|3*x' local g = bind(lambda'|f,x|f(x)^2', f) check.eq(f(4),12) check.eq(g(4),144) end) T("CastTest", function() local tmp = os.tmpname() local f = aprilio.stream.file(tmp, "w") local f1 = cast.to(f, aprilio.stream) check.TRUE( class.is_a(f1, aprilio.stream) ) local f2 = cast.to(f, aprilio.stream.file) check.TRUE( class.is_a(f2, aprilio.stream.file) ) check.TRUE( class.is_a(f1, aprilio.stream.file) ) check.errored(function() assert(cast.to(f, dataset)) end) f:close() os.remove(tmp) end)april-ann-0.4.1/packages/basics/util/test/test_buffer_list.cc000066400000000000000000000017511263004425400242310ustar00rootroot00000000000000#include "buffer_list.h" #include "binarizer.h" #include "gtest.h" #include using std::cout; using std::endl; using namespace AprilUtils; #define FORMAT_STRING "hola mundo! %d+%d=%d," #define BUFFER_CONTENT "!!!$78ASQ88D #include #include "constString.h" #include "gtest.h" using namespace std; using namespace AprilUtils; #define N 4 namespace test_conststring { TEST(ConstStringTest, All) { const char *strings[N] = { "aaaa", "aab", "aa", "aaa" }; for (int i=0; i= s2, strcmp(strings[i],strings[j]) >= 0 ); EXPECT_EQ( s1 > s2, strcmp(strings[i],strings[j]) > 0 ); } } } } #undef N april-ann-0.4.1/packages/basics/util/test/test_context.cc000066400000000000000000000022261263004425400234070ustar00rootroot00000000000000#include #include "context.h" #include "gtest.h" using AprilUtils::context; using namespace std; using namespace AprilUtils; namespace test_context { // test suite= ContextTest, test name= All TEST(ContextTest, All) { int output[] = { 10, 10, 10, 10, 20, 30, 40, 50, 60, 70, 70, 70, 70 }; int output_pos = 0; context c(3,3); c.insert(10); int *p = new int(20); c.insert(p); c.insert(30); EXPECT_FALSE( c.ready() ); // Not ready yet c.insert(40); for (int i=-3; i<4; ++i) { EXPECT_EQ( c[i], output[i+3+output_pos] ); } c.insert(50); ++output_pos; for (int i=-3; i<4; ++i) { EXPECT_EQ( c[i], output[i+3+output_pos] ); } c.insert(60); ++output_pos; for (int i=-3; i<4; ++i) { EXPECT_EQ( c[i], output[i+3+output_pos] ); } c.insert(70); ++output_pos; for (int i=-3; i<4; ++i) { EXPECT_EQ( c[i], output[i+3+output_pos] ); } c.end_input(); c.shift(); while (c.ready()) { ++output_pos; for (int i=-3; i<4; ++i) { EXPECT_EQ( c[i], output[i+3+output_pos] ); } c.shift(); EXPECT_LT(output_pos, 13); } } } april-ann-0.4.1/packages/basics/util/test/test_cronometro.lua000066400000000000000000000005701263004425400243060ustar00rootroot00000000000000 wop = util.stopwatch() wop:reset() wop:go() local a = 0 for i=0,10000 do a = a+1 end wop:stop() print("ha tardado:",wop:read()) if wop:is_on() then print("el cronometro esta en marcha") else print("el cronometro esta parado") end wop2 = wop:clone() wop2:go() local a = 0 for i=0,500000000 do a = a+1 end wop2:stop() print("ha tardado:",wop2:read()) april-ann-0.4.1/packages/basics/util/test/test_fifo.cc000066400000000000000000000013001263004425400226360ustar00rootroot00000000000000#include using namespace std; #include "fifo.h" #include "gtest.h" using namespace AprilUtils; namespace test_fifo { TEST(FifoTest, All) { AprilUtils::fifo f; EXPECT_TRUE( f.empty() ); for (int i=10; i>=0; --i) { f.put(i); EXPECT_EQ( f.size(), 10 - i + 1 ); } EXPECT_FALSE( f.empty() ); f.drop_by_value(4); EXPECT_EQ( f.size(), 10 ); int j; for (int i=10; i>4; --i) { EXPECT_TRUE( f.get(j) ); EXPECT_EQ( j, i ); } for (int i=3; i>=0; --i) { EXPECT_TRUE( f.get(j) ); EXPECT_EQ( j, i ); } EXPECT_FALSE( f.get(j) ); EXPECT_TRUE( f.empty() ); EXPECT_EQ( f.size(), 0 ); } } #undef COMMANDS april-ann-0.4.1/packages/basics/util/test/test_fifo_block.cc000066400000000000000000000040141263004425400240150ustar00rootroot00000000000000#include #include "fifo_block.h" #include "gtest.h" using namespace std; using namespace AprilUtils; #define N 20 #define EXTRACTN 5 #define BACKN 5 #define BSIZE 7u namespace test_fifo_block { TEST(FifoBlockTest, All) { typedef AprilUtils::fifo_block fifo_block_type; fifo_block_type fifobint; int i,v; EXPECT_EQ( fifobint.block_size(), BSIZE ); EXPECT_TRUE( fifobint.begin() == fifobint.end() ); EXPECT_TRUE( fifobint.is_end(fifobint.begin()) ); EXPECT_EQ( fifobint.size(), 0u ); EXPECT_TRUE( fifobint.empty() ); // add N elements for (i=0; i(una_copia.count()) ); // iterator traversal of copy and original fifo_block_type::iterator orig_r = fifobint.begin(), r; for (r = una_copia.begin(); r != una_copia.end() && !fifobint.is_end(orig_r); ++r, ++orig_r) { ASSERT_EQ( *r, *orig_r ); } ASSERT_TRUE( una_copia.is_end(r) ); ASSERT_TRUE( r == una_copia.end() ); ASSERT_TRUE( fifobint.is_end(orig_r) ); ASSERT_TRUE( orig_r == fifobint.end() ); // extract 5 elements from original object for (i=0; i #include "geometry.h" #include "gtest.h" using namespace std; using namespace AprilUtils; namespace test_geometry { TEST(GeometryTest, All) { // Given two points (2,2) -> (6,3) AprilUtils::Point2D p1 = AprilUtils::Point2D(3,2); AprilUtils::Point2D p2 = AprilUtils::Point2D(6,3); //Define the line AprilUtils::line morgan = AprilUtils::line(p1,p2); EXPECT_FLOAT_EQ( morgan.getSlope(), 0.33333334f ); EXPECT_FLOAT_EQ( morgan.getYintercept(), 1.0f ); // Create a new line AprilUtils::Point2D p3 = AprilUtils::Point2D(4, 1); AprilUtils::Point2D p4 = AprilUtils::Point2D(6, 0.5); AprilUtils::line rect2 = AprilUtils::line(p3,p4); EXPECT_FLOAT_EQ( rect2.getSlope(), -0.25f ); EXPECT_FLOAT_EQ( rect2.getYintercept(), 2.0f ); // Check the intersection bool flag; Point2D pInt = morgan.intersection(rect2, flag); EXPECT_FLOAT_EQ( pInt.x, 1.714286f ); EXPECT_FLOAT_EQ( pInt.y, 1.571429f ); //Check the point distance Point2D p5 = Point2D(4,4); float dist = 0.0f; Point2D cp = morgan.closestPoint(p5,dist); EXPECT_FLOAT_EQ( p5.x, 4.0f ); EXPECT_FLOAT_EQ( p5.y, 4.0f ); EXPECT_FLOAT_EQ( cp.x, 4.5f ); EXPECT_FLOAT_EQ( cp.y, 2.5f ); EXPECT_FLOAT_EQ( dist, 1.581139f ); } } april-ann-0.4.1/packages/basics/util/test/test_hash_table.cc000066400000000000000000000051431263004425400240160ustar00rootroot00000000000000#include "gtest.h" #include "hash_table.h" #include "aux_hash_table.h" using namespace AprilUtils; #include #include using std::cout; using std::endl; #define hola "hola" #define hello "hello" #define adios "adios" #define ciao "ciao!" #define bye "bye" #define x "x" #define y "y" #define z "z" #define uno "uno" #define dos "dos" #define tres "tres" #define cuatro "cuatro" #define cinco "cinco" #define U1 "1" #define U2 "2" #define U3 "3" #define U4 "4" #define U5 "5" namespace test_hash_table { typedef AprilUtils::hash hash_test; void process_pair(hash_test::value_type p) { ASSERT_STRNE( p.second, adios ); } struct X { int data; bool operator == (const X& other) const { return data == other.data; } }; bool predicado(hash_test::value_type p) { return (!strcmp(p.second, adios)); } TEST(HashTable, StringStringHashTable) { hash_test a_table; // EXPECT_EQ( a_table.size(), 0 ); a_table[hola] = hello; a_table[adios] = bye; a_table.insert(adios,ciao); a_table[x] = adios; a_table[y] = adios; a_table[z] = adios; EXPECT_STREQ( a_table[adios], ciao ); EXPECT_EQ( a_table.size(), 5 ); a_table.erase(adios); EXPECT_FALSE( a_table.search(adios) ); EXPECT_EQ( a_table.size(), 4 ); // a_table[uno] = U1; a_table[dos] = U2; a_table[tres] = U3; a_table[cuatro] = U4; a_table[cinco] = U5; EXPECT_EQ( a_table.size(), 9 ); // int count = 0; for (hash_test::const_iterator i=a_table.begin(); i != a_table.end(); ++i) { ++count; EXPECT_STREQ( (*i).first, i->first ); EXPECT_STREQ( (*i).second, i->second ); } EXPECT_EQ( count, a_table.size() ); // Borramos todas las entradas con valor 'adios' a_table.delete_if(predicado); EXPECT_EQ( a_table.size(), 6 ); // Redimensionamos la tabla a_table.resize(128); // Y ahora con for_each std::for_each(a_table.begin(), a_table.end(), process_pair); } TEST(HashTable, HashFcnAndEqualKey) { X a,b; a.data=3; b.data=3; // Test con tabla con HashFcn y EqualKey genericas" << endl; AprilUtils::hash t; t[a] = 4; t[b] = 99; for (AprilUtils::hash::iterator i=t.begin(); i!=t.end(); i++) { ASSERT_EQ( i->first.data, 3 ); ASSERT_EQ( i->second, 99 ); } ASSERT_EQ( t.size(), 1 ); } } #undef hola #undef hello #undef adios #undef ciao #undef bye #undef x #undef y #undef z #undef uno #undef dos #undef tres #undef cuatro #undef cinco #undef U1 #undef U2 #undef U3 #undef U4 #undef U5 april-ann-0.4.1/packages/basics/util/test/test_hash_table_empty_value.cc000066400000000000000000000030051263004425400264230ustar00rootroot00000000000000#include "aux_hash_table.h" #include "gtest.h" #include "hash_table.h" #include "null_types.h" using namespace AprilUtils; #include #include using std::cout; using std::endl; typedef AprilUtils::hash hash_test; #define hola "hola" #define adios "adios" #define uno "uno" #define dos "dos" #define tres "tres" #define cuatro "cuatro" #define cinco "cinco" namespace test_hash_table_empty_value { void check_pair(hash_test::value_type p) { EXPECT_STRNE( p.first, adios ); } TEST(HashTableEmptyValues, All) { hash_test a_table; EXPECT_EQ( a_table.size(), 0 ); EXPECT_TRUE( a_table.empty() ); a_table[hola] = NullType(); a_table[adios] = NullType(); a_table.insert(adios,NullType()); a_table.erase(adios); EXPECT_EQ( a_table.size(), 1 ); EXPECT_FALSE( a_table.empty() ); EXPECT_FALSE( a_table.search(adios) ); // insert 5 new elements a_table[uno] = NullType(); a_table[dos] = NullType(); a_table[tres] = NullType(); a_table[cuatro] = NullType(); a_table[cinco] = NullType(); EXPECT_EQ( a_table.size(), 6 ); // iterator traversal for (hash_test::const_iterator i=a_table.begin(); i != a_table.end(); ++i) { EXPECT_EQ( (*i).first, i->first ); check_pair( *i ); } // for_each traversal std::for_each(a_table.begin(), a_table.end(), check_pair); } } #undef hola #undef adios #undef uno #undef dos #undef tres #undef cuatro #undef cinco april-ann-0.4.1/packages/basics/util/test/test_list.cc000066400000000000000000000103621263004425400226760ustar00rootroot00000000000000#define USE_ITERATOR_TAGS #include "gtest.h" #include "list.h" #include #include using std::cout; using std::endl; using namespace AprilUtils; #define N 10u namespace test_list { struct checkValue { int value; checkValue(int v) : value(v) { } void operator()(const checkValue &a) { EXPECT_EQ( a.value, value ); } }; struct checkNotValue { int value; checkNotValue(int v) : value(v) { } void operator()(const checkNotValue &a) { EXPECT_NE( a.value, value ); } }; struct checkLessEqualValue { int value; checkLessEqualValue(int v) : value(v) { } void operator()(const checkLessEqualValue &a) { EXPECT_LE( a.value, value ); } }; bool predicado(int x) { return x>90; } void check_int(int i) { EXPECT_TRUE( 0 <= i && i <= 9 ); } TEST(ListTest, Test1) { int j; list l; EXPECT_TRUE( l.empty() ); EXPECT_EQ( l.size(), 0u ); // push elements int data[N] = { 4, 5, 6, 7, 3, 2, 1, 8, 9, 0 }; for (unsigned int i=0; i::iterator it = l.begin(); it != l.end(); ++it) { check_int( *it ); } for (list::const_iterator it = l.begin(); it != l.end(); ++it) { check_int( *it ); } // list with elements [4,8) taken from l list::iterator first=l.begin(); list::iterator last =l.end(); for (int i=0; i<4; i++) first++; for (int i=0; i<2; i++) last--; list l4(first,last); EXPECT_EQ( l4.size(), 4u ); j=4; for (list::iterator it = l4.begin(); it != l4.end(); ++it) { EXPECT_EQ( *it, data[j++] ); } // pop l.pop_front(); j=1; for (list::iterator it = l.begin(); it != l.end(); ++it) { EXPECT_EQ( *it, data[j++] ); } EXPECT_EQ( l.size(), N - 1u ); // pop l.pop_back(); j=1; for (list::iterator it = l.begin(); it != l.end(); ++it) { EXPECT_EQ( *it, data[j++] ); } EXPECT_EQ( l.size(), N - 2u ); EXPECT_FALSE( l.empty() ); // insert l at l4 l4.insert(++l4.begin(), l.begin(), l.end()); EXPECT_EQ( l4.size(), 4 + l.size() ); // insert 5 times 999 l4.insert(--l4.end(), 5, 999); EXPECT_EQ( l4.size(), 4 + l.size() + 5 ); l4.insert(l4.end(), -6789); EXPECT_EQ( l4.size(), 4 + l.size() + 5 + 1 ); // erase second and third elements last = ++l4.begin(); first = last++; ++last; l4.erase(first, last); EXPECT_EQ( l4.size(), 4 + l.size() + 5 + 1 - 2 ); // resizing l4.resize(10u); EXPECT_EQ( l4.size(), 10u ); EXPECT_FALSE( l4.empty() ); // resize with adding -1 values at end l4.resize(12u, -1); EXPECT_EQ( l4.size(), 12u ); EXPECT_EQ( l4.back(), -1 ); // splice l4.splice(++l4.begin(), l); EXPECT_EQ( l.size(), 0u ); EXPECT_TRUE( l.empty() ); EXPECT_EQ( l4.size(), 12u + N - 2u ); // remove l4.remove(6); std::for_each(l4.begin(), l4.end(), checkNotValue(6)); // remove if x>90 l4.remove_if(predicado); std::for_each(l4.begin(), l4.end(), checkLessEqualValue(90)); // now some STL algorithms ;) l4.erase(std::find(l4.begin(), l4.end(), 7)); list::iterator i = std::find(l4.begin(), l4.end(), 5); l4.splice(l4.begin(), l4, i); *l4.begin()=99; } TEST(ListTest, Test2) { // 12 elements with value 10 list l2(12, 10); std::for_each(l2.begin(), l2.end(), checkValue(10)); // 10 elements with value -1234 list l3(10, -1234); std::for_each(l3.begin(), l3.end(), checkValue(-1234)); l2.swap(l3); std::for_each(l2.begin(), l2.end(), checkValue(-1234)); std::for_each(l3.begin(), l3.end(), checkValue(10)); // l3.clear(); EXPECT_EQ( l3.size(), 0u ); EXPECT_TRUE( l3.empty() ); } } #undef N april-ann-0.4.1/packages/basics/util/test/test_logbase.cc000066400000000000000000000017241263004425400233410ustar00rootroot00000000000000#include #include "gtest.h" #include "logbase.h" #define EPSILON 1e-05 using namespace AprilUtils; namespace test_logbase { TEST(LogbaseTest,All) { log_double a,b; int i=0; a = log_double::from_double(0); b = log_double::from_double(0.0001); EXPECT_EQ( a, log_double::zero() ); EXPECT_DOUBLE_EQ( b.log(), -9.210340371976182 ); for (i=1; i<=10; i++) { a += b; EXPECT_NEAR( b.to_double() * i, a.to_double(), EPSILON ); } log_float x = log_float::from_float(3.0f); log_double y = log_double::from_double(5.0); log_double z = x+y; EXPECT_NEAR( z.log(), 2.0794415416798357, EPSILON ); EXPECT_NEAR( z.to_double(), 8.0, EPSILON ); z=x*y; EXPECT_NEAR( z.log(), 2.70805020110221, EPSILON ); EXPECT_NEAR( z.to_double(), 15.0, EPSILON ); z=x/y; EXPECT_NEAR( z.log(), -0.5108256237659905, EPSILON ); EXPECT_NEAR( z.to_double(), 0.6, EPSILON ); } } #undef EPSILON april-ann-0.4.1/packages/basics/util/test/test_max_min_finder.cc000066400000000000000000000015211263004425400246770ustar00rootroot00000000000000#include #include #include "gtest.h" #include "vector.h" #include "max_min_finder.h" using namespace AprilUtils; #define N 14 #define MAXN 2u namespace test_max_min_finder { TEST(MaxMinFinderTest,All) { AprilUtils::vector resultado; const int ci = 6; const int cd = 6; bool findmax = true; bool findmin = false; max_min_finder finder(ci,cd,findmax,&resultado,findmin,0); int data[N] = { -2, 4, 6, 10, 4, 2, 1, 0, 3, 4, 6, 3, 2, 0 }; for (int i=0; i::iterator r = resultado.begin(); r != resultado.end(); ++r, ++j) { EXPECT_EQ( *r, expected[j] ); } } } #undef N #undef MAXN april-ann-0.4.1/packages/basics/util/test/test_maxiphobic_minheap.cc000066400000000000000000000015151263004425400255470ustar00rootroot00000000000000#include "gtest.h" #include "maxiphobic_minheap.h" #include #include #include using std::rand; using std::srand; using namespace AprilUtils; #define NUM_QUEUES 100000 #define NUM_ELEMENTS 10000000 namespace test_maxiphobic_minheap { TEST(MaxiphobicMinheapTest,All) { maxiphobic_minheap h[NUM_QUEUES]; srand(time(NULL)); for (int i=0; i #include using std::cout; using std::endl; #include "aux_hash_table.h" #include "gtest.h" #include "open_addressing_hash.h" #include "unused_variable.h" using namespace AprilUtils; #define NULL_STRING "" #define hola "hola" #define hello "hello" #define adios "adios" #define ciao "ciao!" #define bye "bye" #define x "x" #define y "y" #define z "z" #define uno "uno" #define dos "dos" #define tres "tres" #define cuatro "cuatro" #define cinco "cinco" #define U1 "1" #define U2 "2" #define U3 "3" #define U4 "4" #define U5 "5" namespace test_open_adressing_hash { typedef open_addr_hash hash_test; void process_pair(hash_test::value_type p) { UNUSED_VARIABLE(p); } struct X { int data; X() : data(0) { } bool operator == (const X& other) const { return data == other.data; } }; bool predicado(hash_test::value_type p) { return (!strcmp(p.second, adios)); } TEST(OpenAdressingHashTable, StringStringHashTable) { hash_test a_table(NULL_STRING); // EXPECT_EQ( a_table.size(), 0 ); a_table[hola] = hello; a_table[adios] = bye; a_table.insert(adios,ciao); a_table[x] = adios; a_table[y] = adios; a_table[z] = adios; EXPECT_STREQ( a_table[adios], ciao ); EXPECT_EQ( a_table.size(), 5 ); // a_table[uno] = U1; a_table[dos] = U2; a_table[tres] = U3; a_table[cuatro] = U4; a_table[cinco] = U5; EXPECT_EQ( a_table.size(), 10 ); // int count = 0; for (hash_test::const_iterator i=a_table.begin(); i != a_table.end(); ++i) { ++count; EXPECT_STREQ( (*i).first, i->first ); EXPECT_STREQ( (*i).second, i->second ); } EXPECT_EQ( count, a_table.size() ); // Redimensionamos la tabla a_table.resize(128); // Y ahora con for_each std::for_each(a_table.begin(), a_table.end(), process_pair); } TEST(OpenAdressingHashTable, HashFcnAndEqualKey) { X a,b,zero; a.data=3; b.data=3; // Test con tabla con HashFcn y EqualKey genericas" << endl; AprilUtils::open_addr_hash t( zero ); t[a] = 4; t[b] = 99; for (AprilUtils::open_addr_hash::iterator i=t.begin(); i!=t.end(); i++) { ASSERT_EQ( i->first.data, 3 ); ASSERT_EQ( i->second, 99 ); } ASSERT_EQ( t.size(), 1 ); } } #undef hola #undef hello #undef adios #undef ciao #undef bye #undef x #undef y #undef z #undef uno #undef dos #undef tres #undef cuatro #undef cinco #undef U1 #undef U2 #undef U3 #undef U4 #undef U5 #undef NULL_STRING april-ann-0.4.1/packages/basics/util/test/test_open_adressing_hash_timestamp.cc000066400000000000000000000040401263004425400300050ustar00rootroot00000000000000 #include #include using std::cout; using std::endl; #include "open_addressing_hash_timestamp.h" #include "aux_hash_table.h" using namespace AprilUtils; using namespace hash_aux; typedef open_addr_hash_timestamp hash_test; int print_pair(hash_test::value_type p) { cout << p.first << "->" << p.second << endl; } bool predicado(hash_test::value_type p) { return (!strcmp(p.second, "adios")); } int main() { hash_test a_table; cout << "La tabla tiene " << a_table.size() << " entradas" << endl; a_table["hola"] = "hello"; a_table["adios"] = "bye"; a_table.insert("adios","ciao!"); a_table["x"] = "adios"; a_table["y"] = "adios"; a_table["z"] = "adios"; cout << "a_table[adios] = " << a_table["adios"] << endl; cout << "La tabla tiene " << a_table.size() << " entradas" << endl; cout << "Ahora borramos todas las entradas" << endl; a_table.clear(); cout << "La tabla tiene " << a_table.size() << " entradas" << endl; a_table["hola"] = "hi"; a_table["adios"] = "ciao"; cout << "a_table[adios] " << (a_table.search("adios") ? "esta" : "no es encuentra") << endl; cout << "La tabla tiene " << a_table.size() << " entradas" << " y " << a_table.bucket_count() << " buckets" << endl; cout << "Insertamos elementos nuevos." << endl; a_table["uno"] = "1"; a_table["dos"] = "2"; a_table["tres"] = "3"; a_table["cuatro"] = "4"; a_table["cinco"] = "5"; a_table["seis"] = "6"; a_table["siete"] = "7"; a_table["ocho"] = "8"; a_table["nueve"] = "9"; a_table["diez"] = "10"; a_table["once"] = "11"; a_table["doce"] = "12"; cout << "La tabla tiene " << a_table.size() << " entradas" << " y " << a_table.bucket_count() << " buckets" << endl; cout << "Recorrido con un iterador:" << endl; for (hash_test::const_iterator i=a_table.begin(); i != a_table.end(); ++i) { cout << (*i).first << "->" << i->second << endl; } cout << "Y ahora con for_each" << endl; std::for_each(a_table.begin(), a_table.end(), print_pair); return 0; } april-ann-0.4.1/packages/basics/util/test/test_qsort.cc000066400000000000000000000011471263004425400230740ustar00rootroot00000000000000#include using namespace std; #include "qsort.h" using namespace AprilUtils; int main() { // Lectura de datos e invocación de la función de sort int i,leido,indDat; const int maxVec = 1024; int v[maxVec]; cout << "Prueba de la función QuickSort\n" << "Introduce valores a ordenar (fin con ^D):\n"; indDat=0; while (indDat < maxVec && cin >> leido) { v[indDat] = leido; indDat++; } AprilUtils::Sort(v,indDat); // ordenamos el vector cout << "El vector ordenado:\n"; for(i=0; i < indDat; i++) cout << v[i] << (((i % 10 == 9) || (i == indDat-1)) ? '\n' : ' '); } april-ann-0.4.1/packages/basics/util/test/test_qsort_partq.cc000066400000000000000000000010301263004425400242720ustar00rootroot00000000000000#include using namespace std; #include "../c_src/qsort.h" using namespace AprilUtils; int main() { // Lectura de datos e invocación de la función de sort int i,leido,indDat; const int maxVec = 1024; int v[maxVec]; cout << "Prueba de partq\n" << "Introduce valores (fin con ^D):\n"; indDat=0; while (indDat < maxVec && cin >> leido) { v[indDat] = leido; indDat++; } AprilUtils::PartQ queue; queue.configure(v,indDat); while (queue.extractMin(leido)) { cout << leido << endl; } } april-ann-0.4.1/packages/basics/util/test/test_qsort_selection.cc000066400000000000000000000012751263004425400251430ustar00rootroot00000000000000#include using namespace std; #include "../c_src/qsort.h" using namespace AprilUtils; int main() { // Lectura de datos e invocación de la función de sort int i,leido,indDat; const int maxVec = 1024; int v[maxVec]; cout << "Prueba de la función Selection\n" << "Introduce el valor k y luego los valores (fin con ^D):\n"; int k; cin >> k; indDat=0; while (indDat < maxVec && cin >> leido) { v[indDat] = leido; indDat++; } int valor = AprilUtils::Selection(v,indDat,k-1); cout << "El " << k << "-esimo menor es " << valor << endl; cout << "Los " << k << " menores elementos (desordenados) son:\n"; for (int i=0; i #include #include #include "gtest.h" #include "slist.h" #define N 5u using std::cout; using std::endl; using namespace AprilUtils; namespace slist_test { void check_ne_3(int i) { EXPECT_NE( i, 3 ); } TEST(SlistTest, All) { int data[N] = { 1, 2, 3, 4, 99 }; AprilUtils::slist l; EXPECT_EQ( l.size(), 0u ); EXPECT_TRUE( l.empty() ); for (unsigned int i=0; i::iterator it = l.begin(); AprilUtils::slist::const_iterator c_it = l.begin(); EXPECT_TRUE( l.begin() != l.end() ); EXPECT_TRUE( it != l.end() ); EXPECT_TRUE( c_it != l.end() ); // iterator traversal int j = 0; for (AprilUtils::slist::iterator i = l.begin(); i != l.end(); i++,j++) EXPECT_EQ( *i, data[j] ); // const_iterator traversal j=0; for (AprilUtils::slist::const_iterator i = l.begin(); i != l.end(); i++,j++) EXPECT_EQ( *i, data[j] ); // replace 3 by 99 std::replace(l.begin(), l.end(), 3, 99); // traversal checking all != 3 std::for_each(l.begin(), l.end(), check_ne_3); // TODO: Un test para slist::transfer_front_to_front() // TODO: Un test para slist::transfer_front_to_back() } } #undef N april-ann-0.4.1/packages/basics/util/test/test_smart_ptr.cc000066400000000000000000000035071263004425400237410ustar00rootroot00000000000000#include "gtest.h" #include "smart_ptr.h" using std::cout; using std::endl; using namespace AprilUtils; namespace smart_ptr_test { class A : public Referenced { public: A() : Referenced() { ++ctor_count; } virtual ~A() { ++dtor_count; } static int ctor_count; static int dtor_count; }; int A::ctor_count = 0; int A::dtor_count = 0; class B : public A { public: B() : A() { ++ctor_count; } virtual ~B() { ++dtor_count; } static int ctor_count; static int dtor_count; }; int B::ctor_count = 0; int B::dtor_count = 0; static void resetCounts() { A::ctor_count = 0; A::dtor_count = 0; B::ctor_count = 0; B::dtor_count = 0; } //////////////////////////////////////////////////////////////////////////// template static Ptr source() { return Ptr(new T); } template static void sink(Ptr) { } //////////////////////////////////////////////////////////////////////////// /* TEST(SmartPtrTest, UniquePtr) { resetCounts(); sink(source, A>()); sink(source, B>()); EXPECT_EQ( A::ctor_count, 2 ); EXPECT_EQ( A::dtor_count, 2 ); EXPECT_EQ( B::ctor_count, 1 ); EXPECT_EQ( B::dtor_count, 1 ); } */ TEST(SmartPtrTest, SharedPtr) { resetCounts(); sink(source, A>()); sink(source, B>()); EXPECT_EQ( A::ctor_count, 2 ); EXPECT_EQ( A::dtor_count, 2 ); EXPECT_EQ( B::ctor_count, 1 ); EXPECT_EQ( B::dtor_count, 1 ); } TEST(SmartPtrTest, WeakPtr) { resetCounts(); sink(WeakPtr( SharedPtr(new A)) ); sink(WeakPtr( SharedPtr(new B)) ); EXPECT_EQ( A::ctor_count, 2 ); EXPECT_EQ( A::dtor_count, 2 ); EXPECT_EQ( B::ctor_count, 1 ); EXPECT_EQ( B::dtor_count, 1 ); } } #undef N april-ann-0.4.1/packages/basics/util/test/test_stringQueue.cc000066400000000000000000000004271263004425400242370ustar00rootroot00000000000000#include #include "../c_src/stringQueue.cc" using namespace AprilUtils; int main() { StringQueue s; for (int i=0; i<10; ++i) s.printf("hola mundo %d\n",i); int t; std::cout << s.exportBuffer(t) << std::endl; std::cout << "ocupa: " << t << std::endl; } april-ann-0.4.1/packages/basics/util/test/test_vector.cc000066400000000000000000000006251263004425400232260ustar00rootroot00000000000000#include "vector.h" #include using namespace AprilUtils; using std::cout; using std::endl; int main() { vector v1; v1.push_back(1); v1.push_back(2); v1.push_back(3); v1.push_back(4); vector v2; v2.push_back(30); v2.push_back(20); v2.push_back(10); v1.swap(v2); for (int i=0; i 0, "samples table is empty") local best,argbest = table.pack(eval(samples[1], 1)),samples[1] for i=2,#samples do local current = table.pack(eval(samples[i], i)) if current[1] < best[1] then best,argbest = current,samples[i] end end return argbest,table.unpack(best) end -- returns a model which forwards computation is a combination of N sampled -- parameters function bayesian.build_bayes_comb(t) local params = get_table_fields( { forward = { mandatory = true, type_match = "function" }, shuffle = { isa_match = random, mandatory = false, default=nil }, samples = { type_match = "table", mandatory = true }, N = { type_match = "number", mandatory = true, default=100 }, }, t, true) assert(#params.samples > 0, "samples table is empty") return ann.components.wrapper{ state = { N = params.N, samples = params.samples, rnd = params.shuffle, forward = params.forward, }, weights = params.samples[#params.samples], forward = function(self,input) local forward = self.state.forward local N = self.state.N local rnd = self.state.rnd local samples = self.state.samples local invN = 1/N local which = rnd:choose(samples) local out = forward(which, input) assert(class.is_a(out, matrix), "The forward function must return a matrix") local output = out:clone():scal(invN) for i=2,N do local which = rnd:choose(samples) local out = forward(which, input) output:axpy(invN, out) end return output end, } end ------------------------------------------------------------------------------ april-ann-0.4.1/packages/bayesian/lua_src/hmc.lua000066400000000000000000000255271263004425400216630ustar00rootroot00000000000000get_table_from_dotted_string("bayesian.optimizer", true) -- Hamiltonian Monte-Carlo implementation with a basic on-line adaptation of -- epsilon, bounded by [epsilon_min,epsilon_max]. -- Radford M. Neal. MCMC using Hamiltonian dynamics. 2010 -- http://www.cs.toronto.edu/~radford/ham-mcmc.abstract.html -- Mathew D. Hoffman, Andrew Gelman. The No-U-Turn Sampler: Adaptively Setting -- Path Lengths in Hamiltonian Monte Carlo. JMLR 2014. -- http://www.stat.columbia.edu/~gelman/research/published/nuts.pdf -- http://deeplearning.net/tutorial/hmc.html -- @param eval is a function a function which returns L(Theta),dL/dTheta. It is -- implemented to minimize the negative of the log-likelihood (maximize the -- log-likelihood). -- -- @param theta is a matrix, a table of matrices. local function hmc(self, eval, theta) local state = self.state -- local energies = state.energies local math_log = math.log local math_clamp = math.clamp local md = matrix.dict local priors = state.priors local samples = state.samples local origw = theta -- local acc_decay = self:get_option("acc_decay") local alpha = self:get_option("alpha") local epsilon = state.epsilon or self:get_option("epsilon") local epsilon_dec = self:get_option("epsilon_dec") local epsilon_inc = self:get_option("epsilon_inc") local epsilon_max = self:get_option("epsilon_max") local epsilon_min = self:get_option("epsilon_min") local nsteps = self:get_option("nsteps") local rng = state.rng or random(self:get_option("seed")) local scale = self:get_option("scale") local thin = self:get_option("thin") local mass = self:get_option("mass") local persistence = self:get_option("persistence") local target_acceptance_rate = self:get_option("target_acceptance_rate") -- assert(persistence >= 0.0 and persistence <= 1.0, "Incorrect persistence ratio") local inv_mass = 1.0/mass local spersistence = math.sqrt(1 - persistence*persistence) state.acceptance_rate = state.acceptance_rate -- local eval_with_priors = function(w, ...) local aux = table.pack( eval(w, ...) ) local grads = aux[2] priors:update_gradients_with_priors(w, grads) return table.unpack(aux) end -- -- kinetic energy associated with given velocity local kinetic_energy = function(vel) return 0.5 * md.dot(vel,vel) end -- -- executes the simulation chain of HMC using leapfrog updates local simulation = function(pos, vel, epsilon, nsteps) -- -- receives the optimizer table, a matrix dict with positions, other with -- velocities, and the epsilon for the step local leapfrog = function(pos, vel, epsilon, i) -- from pos(t) and vel(t - eps/2), compute vel(t + eps/2) local _,grads = eval_with_priors(origw, i) md.axpy(vel, -epsilon, grads) -- from vel(t + eps/2) compute pos(t + eps) md.axpy(pos, epsilon*inv_mass, vel) -- local eval_result,grads = eval_with_priors(origw, i) -- md.axpy(vel, -epsilon*0.5, grads) end -- -- compute velocity at time: t + eps/2 local initial_energy,grads = eval_with_priors(origw, 0) initial_energy = scale*initial_energy + priors:compute_neg_log_prior(pos) md.axpy(vel, -0.5*epsilon, grads) -- compute position at time: t + eps md.axpy(pos, epsilon*inv_mass, vel) -- compute from 2 to nsteps leapfrog updates for i=2,nsteps do leapfrog(pos, vel, epsilon, i-1) end -- compute velocity at time: t + nsteps*eps local final_energy,grads = eval_with_priors(origw, nsteps) final_energy = scale*final_energy + priors:compute_neg_log_prior(pos) md.axpy(vel, -0.5*epsilon, grads) return initial_energy, final_energy end -- -- metropolis hastings reject procedure local metropolis_hastings = function(initial_p, final_p) local alpha = initial_p - final_p local accept_threshold = math_log(rng:randDblExc()) return accept_threshold < alpha end -- -- priors sampling priors:sample(rng, theta) -- -- one HMC sample procedure local norm01 = state.norm01 or stats.dist.normal() local theta0 = md.clone(theta) -- for in case of rejection local vel = self.state.vel local vel0 -- only if persistent -- sample velocity from a standard normal distribution if persistence == 0.0 or not vel then vel = vel or md.clone_only_dims(theta) for _,v in pairs(vel) do norm01:sample(rng, v:rewrap(v:size(), 1)) end else vel0 = md.clone(vel) -- for in case of rejection md.scal(vel, -persistence) for _,v in pairs(vel) do local aux = matrix(v:size(),1) norm01:sample(rng, aux) v:rewrap(v:size(),1):axpy(spersistence, aux) end end -- epsilon perturbation local p_epsilon = epsilon + rng:randNorm(0,alpha*alpha) local initial_kinetic = kinetic_energy(vel) * inv_mass -- simulate the HMC mechanics local initial_energy, final_energy = simulation(theta, vel, p_epsilon, nsteps) md.scal(vel, -1.0) local final_kinetic = kinetic_energy(vel) * inv_mass -- rejection based in metropolis hastings local accept = metropolis_hastings(initial_energy + initial_kinetic, final_energy + final_kinetic) -- local energy = final_energy local ok = pcall(theta.prune_subnormal_and_check_normal, theta) -- if not ok then print(ok, "PROBLEM") end if not accept or not ok then energy = initial_energy md.copy(theta, theta0) if persistent then md.copy(vel, vel0) end end local accepted = (accept and 1) or 0 -- accept rate update (exponential mean) assert(acc_decay > 0.0 and acc_decay < 1.0) -- self:count_one() if self:get_count() % thin == 0 then table.insert(samples, md.clone(theta)) table.insert(energies, energy) end local acceptance_rate if state.acceptance_rate then acceptance_rate = acc_decay * state.acceptance_rate + (1.0 - acc_decay) * accepted else acceptance_rate = accepted end -- sanity check assert(epsilon_inc > 1.0 and epsilon_dec < 1.0 and epsilon_dec > 0.0) -- depending in the acceptance_rate, the epsilon is updated to increase mixing -- if acc rate is greater than target, or to decrease mixing otherwise if acceptance_rate > target_acceptance_rate then epsilon = epsilon*epsilon_inc else epsilon = epsilon*epsilon_dec end epsilon = math_clamp(epsilon, epsilon_min, epsilon_max) -- state.acceptance_rate = acceptance_rate state.accepted = accept state.energy = energy state.initial_energy = initial_energy state.final_energy = final_energy state.initial_kinetic = initial_kinetic state.final_kinetic = final_kinetic state.epsilon = epsilon state.norm01 = norm01 state.rng = rng state.vel = vel -- -- if #samples > samples_max_size then -- local next_samples = {} -- local permutation = rng:shuffle(#samples) -- for i=1,samples_max_size do -- -- table.insert(next_samples, rng:choose(samples)) -- table.insert(next_samples, samples[permutation[i]]) -- end -- samples = next_samples -- collectgarbage("collect") -- end -- print("\t\t ACCEPTED:", #samples, accepted, currentN, accepted/currentN) return eval_with_priors(origw, nsteps+1) end local hmc_class,hmc_methods = class("bayesian.optimizer.hmc", ann.optimizer) bayesian.optimizer.hmc = hmc_class -- global environment function hmc_class:constructor(g_options, l_options, count, state) -- the base optimizer, with the supported learning parameters ann.optimizer.constructor(self,{ { "thin", "Take 1-of-thin samples (1)" }, { "acc_decay", "Acceptance average mean decay (0.95)" }, { "alpha", "Step length perturbation stddev (0.1)" }, { "mass", "Mass of particles (1)" }, { "nsteps", "Number of Leap-Frog steps (20)" }, { "epsilon", "Initial epsilon value (0.01)" }, { "epsilon_inc", "Epsilon increment (1.02)" }, { "epsilon_dec", "Epsilon decrement (0.98)" }, { "epsilon_min", "Epsilon lower bound (1e-04)" }, { "epsilon_max", "Epsilon upper bound (1.0)" }, { "persistence", "Momenta persistence, 0 for non-persistent (0)" }, { "scale", "Energy function scale (1)" }, { "seed", "Seed for random number generator (time)" }, { "target_acceptance_rate", "Desired acceptance rate (0.65)" }, }, g_options, l_options, count) self.state = state or { accepted = false, acceptance_rate = nil, final_energy = 0.0, final_kinetic = 0.0, initial_energy = 0.0, initial_kinetic = 0.0, energy = 0.0, epsilon = nil, priors = bayesian.priors(), samples = {}, energies = {}, rng = nil, } self:set_option("thin", 1) self:set_option("acc_decay", 0.95) self:set_option("alpha", 0.1) self:set_option("mass", 1) self:set_option("nsteps", 20) self:set_option("epsilon", 0.01) self:set_option("epsilon_inc", 1.02) self:set_option("epsilon_dec", 0.98) self:set_option("epsilon_min", 1e-04) self:set_option("epsilon_max", 1.0) self:set_option("persistence", 0.0) self:set_option("scale", 1.0) self:set_option("target_acceptance_rate", 0.65) end hmc_methods.execute = hmc function hmc_methods:clone() local obj = bayesian.optimizer.hmc() obj.count = self.count obj.layerwise_options = table.deep_copy(self.layerwise_options) obj.global_options = table.deep_copy(self.global_options) for k,v in pairs(self.state) do obj.state[k] = v end for k,v in pairs(self.state.samples) do obj.state.samples[k] = v:clone() end return obj end function hmc_methods:ctor_name() return "bayesian.optimizer.hmc" end function hmc_methods:ctor_params() return self.global_options,self.layerwise_options,self.count,self.state end function hmc_methods:start_burnin() self.state.samples = {} self.state.energies = {} end function hmc_methods:finish_burnin() self.state.samples = {} self.state.energies = {} end function hmc_methods:get_samples() return self.state.samples end function hmc_methods:get_state_string() return "%6d %11g :: %6d %11g %6.2f%% %s"% { self:get_count(), self.state.energy, #self.state.samples, self.state.epsilon, self.state.acceptance_rate*100, (self.state.accepted and "**") or "" } end function hmc_methods:get_state_table() return self.state end function hmc_methods:get_priors() return self.state.priors end local hmc_properties = { gradient = true, } function hmc_methods:needs_property(name) return hmc_properties[name] end april-ann-0.4.1/packages/bayesian/lua_src/metropolis.lua000066400000000000000000000165201263004425400233020ustar00rootroot00000000000000get_table_from_dotted_string("bayesian.optimizer", true) -- Random walk Metropolis update with normal proposals -- @param eval is a function a function which returns L(Theta). It is -- implemented to minimize the negative of the log-likelihood (maximize the -- log-likelihood). -- -- @param theta is a matrix, a table of matrices. local function metropolis(self, eval, theta) local state = self.state -- local energies = state.energies local math_log = math.log local math_clamp = math.clamp local md = matrix.dict local priors = state.priors local samples = state.samples local origw = theta -- local acc_decay = self:get_option("acc_decay") local epsilon = state.epsilon or self:get_option("epsilon") local epsilon_dec = self:get_option("epsilon_dec") local epsilon_inc = self:get_option("epsilon_inc") local epsilon_max = self:get_option("epsilon_max") local epsilon_min = self:get_option("epsilon_min") local rng = state.rng or random(self:get_option("seed")) local scale = self:get_option("scale") local thin = self:get_option("thin") local target_acceptance_rate = self:get_option("target_acceptance_rate") -- -- metropolis hastings reject procedure local metropolis_hastings = function(initial_p, final_p) local alpha = initial_p - final_p local accept_threshold = math_log(rng:randDblExc()) return accept_threshold < alpha end -- -- one METROPOLIS sample procedure local norm01 = state.norm01 or stats.dist.normal() local theta0 = md.clone(theta) -- for in case of rejection local eval0_result = table.pack( eval(origw, 0) ) local initial_energy = scale*eval0_result[1] for _,v in pairs(theta) do local aux = matrix.as(v) norm01:sample(rng, aux:rewrap(v:size(),1)) v:axpy(epsilon, aux) end local eval1_result = table.pack( eval(origw, 1) ) local final_energy = scale*eval1_result[1] -- rejection based in metropolis hastings local accept = metropolis_hastings(initial_energy, final_energy) -- local result = eval1_result local energy = final_energy local ok = pcall(md.prune_subnormal_and_check_normal, theta) -- if not ok then print(ok, "PROBLEM") end if not accept or not ok then energy = initial_energy result = eval0_result md.copy(theta,theta0) end local accepted = (accept and 1) or 0 -- accept rate update (exponential mean) assert(acc_decay > 0.0 and acc_decay < 1.0) -- self:count_one() if self:get_count() % thin == 0 then table.insert(samples, md.clone(theta)) table.insert(energies, energy) end local acceptance_rate if state.acceptance_rate then acceptance_rate = acc_decay * state.acceptance_rate + (1.0 - acc_decay) * accepted else acceptance_rate = accepted end -- sanity check assert(epsilon_inc > 1.0 and epsilon_dec < 1.0 and epsilon_dec > 0.0) -- depending in the acceptance_rate, the epsilon is updated to increase mixing -- if acc rate is greater than target, or to decrease mixing otherwise if acceptance_rate > target_acceptance_rate then epsilon = epsilon*epsilon_inc else epsilon = epsilon*epsilon_dec end epsilon = math_clamp(epsilon, epsilon_min, epsilon_max) -- state.acceptance_rate = acceptance_rate state.accepted = accept state.energy = energy state.initial_energy = initial_energy state.final_energy = final_energy state.epsilon = epsilon state.rng = rng state.vel = vel state.norm01 = norm01 -- -- if #samples > samples_max_size then -- local next_samples = {} -- local permutation = rng:shuffle(#samples) -- for i=1,samples_max_size do -- -- table.insert(next_samples, rng:choose(samples)) -- table.insert(next_samples, samples[permutation[i]]) -- end -- samples = next_samples -- collectgarbage("collect") -- end -- print("\t\t ACCEPTED:", #samples, accepted, currentN, accepted/currentN) return table.unpack(eval0_result) end local metropolis_class,metropolis_methods = class("bayesian.optimizer.metropolis", ann.optimizer) bayesian.optimizer.metropolis = metropolis_class -- global environment function metropolis_class:constructor(g_options, l_options, count, state) -- the base optimizer, with the supported learning parameters ann.optimizer.constructor(self, { { "thin", "Take 1-of-thin samples (1)" }, { "acc_decay", "Acceptance average mean decay (0.95)" }, { "target_acceptance_rate", "Desired acceptance rate (0.65)" }, { "epsilon", "Initial epsilon value (0.01)" }, { "epsilon_inc", "Epsilon increment (1.02)" }, { "epsilon_dec", "Epsilon decrement (0.98)" }, { "epsilon_min", "Epsilon lower bound (1e-04)" }, { "epsilon_max", "Epsilon upper bound (1.0)" }, { "scale", "Energy function scale (1)" }, { "seed", "Seed for random number generator (time)" }, }, g_options, l_options, count) self.state = state or { accepted = false, acceptance_rate = nil, final_energy = 0.0, final_kinetic = 0.0, initial_energy = 0.0, initial_kinetic = 0.0, energy = 0.0, epsilon = nil, priors = bayesian.priors(), samples = {}, energies = {}, rng = nil, } self:set_option("thin", 1) self:set_option("acc_decay", 0.95) self:set_option("epsilon", 0.1) self:set_option("epsilon_inc", 1.02) self:set_option("epsilon_dec", 0.98) self:set_option("epsilon_min", 1e-04) self:set_option("epsilon_max", 1.0) self:set_option("scale", 1) self:set_option("target_acceptance_rate", 0.40) return self end metropolis_methods.execute = metropolis function metropolis_methods:clone() local obj = bayesian.optimizer.metropolis() obj.count = self.count obj.layerwise_options = table.deep_copy(self.layerwise_options) obj.global_options = table.deep_copy(self.global_options) for k,v in pairs(self.state) do obj.state[k] = v end for k,v in pairs(self.state.samples) do obj.state.samples[k] = v:clone() end return obj end function metropolis_methods:ctor_name() return "bayesian.optimizer.hmc" end function metropolis_methods:ctor_params() return self.global_options,self.layerwise_options,self.count,self.state end function metropolis_methods:start_burnin() self.state.samples = {} self.state.energies = {} end function metropolis_methods:finish_burnin() self.state.samples = {} self.state.energies = {} end function metropolis_methods:get_samples() return self.state.samples end function metropolis_methods:get_state_string() return "%6d %11g :: %6d %11g %6.2f%% %s"% { self:get_count(), self.state.energy, #self.state.samples, self.state.epsilon, self.state.acceptance_rate*100, (self.state.accepted and "**") or "" } end function metropolis_methods:get_state_table() return self.state end function metropolis_methods:get_priors() return self.state.priors end local metropolis_properties = { } function metropolis_methods:needs_property(name) return metropolis_properties[name] end april-ann-0.4.1/packages/bayesian/lua_src/nuts.lua000066400000000000000000000225341263004425400221000ustar00rootroot00000000000000get_table_from_dotted_string("bayesian.optimizer", true) -- Radford M. Neal. MCMC using Hamiltonian dynamics. 2010 -- http://www.cs.toronto.edu/~radford/ham-mcmc.abstract.html -- Mathew D. Hoffman, Andrew Gelman. The No-U-Turn Sampler: Adaptively Setting -- Path Lengths in Hamiltonian Monte Carlo. JMLR 2014. -- http://www.stat.columbia.edu/~gelman/research/published/nuts.pdf -- http://deeplearning.net/tutorial/hmc.html -- eval is a function a function which returns L(Theta),dL/dTheta. It is -- implemented to minimize the negative of the log-likelihood (maximize the -- log-likelihood) local function nuts(self, eval, theta) local theta = wrap_matrices(theta) local state = self.state local samples = state.samples local epsilon = state.epsilon or self:get_option("epsilon") local rng = state.rng or random(self:get_option("seed")) local thin = self:get_option("thin") local acc_decay = self:get_option("acc_decay") local alpha = self:get_option("alpha") local beta = self:get_option("beta") local var = self:get_option("var") local nsteps = self:get_option("nsteps") local epsilon_inc = self:get_option("epsilon_inc") local epsilon_dec = self:get_option("epsilon_dec") local epsilon_min = self:get_option("epsilon_min") local epsilon_max = self:get_option("epsilon_max") local scale = self:get_option("scale") local target_acceptance_rate = self:get_option("target_acceptance_rate") local inv_var = 1.0/var state.acceptance_rate = state.acceptance_rate or target_acceptance_rate*0.5 -- -- kinetic energy associated with given velocity kinetic_energy = function(vel) return 0.5 * vel:dot(vel) end -- -- executes the simulation chain of HMC using leapfrog updates simulation = function(pos, vel, epsilon, nsteps) -- -- receives the optimizer table, a matrix dict with positions, other with -- velocities, and the epsilon for the step leapfrog = function(pos, vel, epsilon) -- from pos(t) and vel(t - eps/2), compute vel(t + eps/2) local energy,grads = eval() grads = wrap_matrices(grads) vel:axpy(-epsilon, grads:scal(scale)) -- from vel(t + eps/2) compute pos(t + eps) pos:axpy(epsilon*inv_var, vel) -- local eval_result,grads = eval() -- vel:axpy(-epsilon*0.5, grads) return energy end -- -- compute velocity at time: t + eps/2 local initial_energy,grads = eval() grads = wrap_matrices(grads) vel:axpy(-0.5*epsilon, grads:scal(scale)) -- compute position at time: t + eps pos:axpy(epsilon*inv_var, vel) -- compute from 2 to nsteps leapfrog updates for i=2,nsteps do leapfrog(pos, vel, epsilon) end -- compute velocity at time: t + nsteps*eps local final_energy,grads = eval() grads = wrap_matrices(grads) vel:axpy(-0.5*epsilon, grads:scal(scale)) return initial_energy, final_energy end -- -- metropolis hastings reject procedure function metropolis_hastings(initial_p, final_p) local alpha = initial_p - final_p local accept_threshold = math.log(rng:randDblExc()) return accept_threshold < alpha end -- -- one HMC sample procedure local norm01 = stats.dist.normal() local theta0 = theta:clone() local vel = theta:clone_only_dims() -- sample velocity from a standard normal distribution for name,v in pairs(vel) do norm01:sample(rng, v:rewrap(v:size(), 1)) end -- epsilon perturbation local lambda = ((rng:rand() < beta) and -1) or 1 local p_epsilon = lambda * epsilon * (1.0 + alpha * rng:randNorm(0,1)) local initial_kinetic = kinetic_energy(vel) * inv_var local initial_energy,grads = eval() grads = wrap_matrices(grads) local initial_joint = scale*initial_energy + initial_kinetic local logu = rnd:rand(0, math.exp(-initial_joint)) -- simulate the HMC mechanics local initial_energy, final_energy = simulation(theta, vel, p_epsilon, nsteps) vel:scal(-1.0) local final_kinetic = kinetic_energy(vel) * inv_var -- rejection based in metropolis hastings local accept = metropolis_hastings(scale*initial_energy + initial_kinetic, scale*final_energy + final_kinetic) -- local energy = final_energy local ok = pcall(theta.prune_subnormal_and_check_normal, theta) -- if not ok then print(ok, "PROBLEM") end if not accept or not ok then energy = initial_energy theta:copy(theta0) end local accepted = (accept and 1) or 0 -- accept rate update (exponential mean) assert(acc_decay > 0.0 and acc_decay < 1.0) -- self:count_one() if self:get_count() % thin == 0 then table.insert(samples, theta:clone()) end local acceptance_rate = acc_decay * state.acceptance_rate + (1.0 - acc_decay) * accepted -- sanity check assert(epsilon_inc > 1.0 and epsilon_dec < 1.0 and epsilon_dec > 0.0) -- depending in the acceptance_rate, the epsilon is updated to increase mixing -- if acc rate is greater than target, or to decrease mixing otherwise if acceptance_rate > target_acceptance_rate then epsilon = epsilon*epsilon_inc else epsilon = epsilon*epsilon_dec end epsilon = math.clamp(epsilon, epsilon_min, epsilon_max) -- state.acceptance_rate = acceptance_rate state.accepted = accept state.energy = energy state.initial_energy = initial_energy state.final_energy = final_energy state.initial_kinetic = initial_kinetic state.final_kinetic = final_kinetic state.epsilon = epsilon state.rng = rng -- -- if #samples > samples_max_size then -- local next_samples = {} -- local permutation = rng:shuffle(#samples) -- for i=1,samples_max_size do -- -- table.insert(next_samples, rng:choose(samples)) -- table.insert(next_samples, samples[permutation[i]]) -- end -- samples = next_samples -- collectgarbage("collect") -- end -- print("\t\t ACCEPTED:", #samples, accepted, currentN, accepted/currentN) return eval() end local nuts_class,nuts_methods = class("bayesian.optimizer.nuts", ann.optimizer) bayesian.optimizer.nuts = nuts_class -- global environment function nuts_class:constructor(g_options, l_options, count, state) -- the base optimizer, with the supported learning parameters ann.optimizer.constructor(self, { { "thin", "Take 1-of-thin samples (1)" }, { "acc_decay", "Acceptance average mean decay (0.95)" }, { "target_acceptance_rate", "Desired acceptance rate (0.65)" }, { "alpha", "Step length perturbation size (0.1)" }, { "beta", "Step length sign change prob (0.5)" }, { "var", "Variance of particles (1)" }, { "nsteps", "Number of Leap-Frog steps (20)" }, { "epsilon", "Initial epsilon value (0.01)" }, { "epsilon_inc", "Epsilon increment (1.02)" }, { "epsilon_dec", "Epsilon decrement (0.98)" }, { "epsilon_min", "Epsilon lower bound (1e-04)" }, { "epsilon_max", "Epsilon upper bound (1.0)" }, { "scale", "Energy function scale (1)" }, { "seed", "Seed for random number generator (time)" }, }, g_options, l_options, count) self.state = state or { accepted = false, acceptance_rate = nil, final_energy = 0.0, final_kinetic = 0.0, initial_energy = 0.0, initial_kinetic = 0.0, energy = 0.0, epsilon = nil, samples = {}, rng = nil, } self:set_option("thin", 1) self:set_option("acc_decay", 0.95) self:set_option("target_acceptance_rate", 0.65) self:set_option("alpha", 0.1) self:set_option("beta", 0.5) self:set_option("var", 1) self:set_option("nsteps", 20) self:set_option("epsilon", 0.01) self:set_option("epsilon_inc", 1.02) self:set_option("epsilon_dec", 0.98) self:set_option("epsilon_min", 1e-04) self:set_option("epsilon_max", 1.0) self:set_option("scale", 1.0) return self end nuts_methods.execute = nuts function nuts_methods:clone() local obj = bayesian.optimizer.nuts() obj.count = self.count obj.layerwise_options = table.deep_copy(self.layerwise_options) obj.global_options = table.deep_copy(self.global_options) obj.state = {} for k,v in pairs(self.state) do obj.state[k] = v end for k,v in pairs(self.state.samples) do obj.state.samples[k] = v:clone() end return obj end function nuts_methods:ctor_name() return "bayesian.optimizer.hmc" end function nuts_methods:ctor_params() return self.global_options,self.layerwise_options,self.count,self.state end function nuts_methods:start_burnin() self.state.samples = {} end function nuts_methods:finish_burnin() self.state.samples = {} end function nuts_methods:get_samples() return self.state.samples end function nuts_methods:get_state_string() return "%5d %12.6f :: %d %.6f %6.2f%% %s"% { self:get_count(), self.state.energy, #self.state.samples, self.state.epsilon, self.state.acceptance_rate*100, (self.state.accept and "**") or "" } end function nuts_methods:get_state_table() return self.state end april-ann-0.4.1/packages/bayesian/lua_src/priors.lua000066400000000000000000000102641263004425400224220ustar00rootroot00000000000000get_table_from_dotted_string("bayesian", true) ------------------------------------------------------------------------------ local make_value = function(value) return { t="value", value=value } end local make_dist = function(dist, arg) return { t="dist", dist=dist, arg=arg } end local make_transform = function(func, arg) return { t="transform", func=func, arg=arg } end local normalize_shape = function(d, w) if w then if d:size() == 1 and w:dim(2) ~= 1 then return w:rewrap(w:size(),1) else april_assert(d:size() == w:dim(2), "Incompatible matrix size, found %dx%d, expected %dx%d", w:dim(1), w:dim(2), w:dim(1), d:size()) end end return w end local sampling_funcs = { value = function(v) return function() return v.value end end, dist = function(v, outcomes) local arg = {} for i=1,#v.arg do arg[i] = april_assert(outcomes[v.arg[i]], "Undefined value of '%s'", v.arg[i]) end local d = stats.dist[v.dist](table.unpack(arg)) v.obj = d return function(rng, w) local w = normalize_shape(d, w) return d:sample(rng, w) end end, transform = function(v, outcomes) local arg = {} for i=1,#v.arg do arg[i] = april_assert(outcomes[v.arg[i]], "Undefined value of '%s'", v.arg[i]) if isa(arg[i], matrix) then arg[i] = arg[i]:clone() end end local r = v.func(table.unpack(arg)) return function() return r end end, } ----------------------------------------------------------------------------- local priors_class,priors_methods = class("bayesian.priors") bayesian.priors = priors_class -- global environment function priors_class:constructor(tree,order,outcomes) self.tree = tree or {} self.order = order or {} self.outcomes = outcomes or {} end function priors_methods:compute_neg_log_prior(weights) error("NOT IMPLEMENTED") local logprob = 0.0 for name,m in pairs(self.outcomes) do local d = self.tree[name].obj if d then local out = d:logpdf(m) logprob = logprob + out:sum() end end for name,w in pairs(weights) do local v = self.tree[name] if v and v.obj then local d = v.obj local w = normalize_shape(d, w) local out = d:logpdf(w) logprob = logprob + out:sum() end end return -logprob end function priors_methods:ctor_name() return "bayesian.priors" end function priors_methods:ctor_params() return self.tree,self.order,self.outcomes end function priors_methods:value(name, value) april_assert(not self.tree[name], "Redifition of value '%s'", target) table.insert(self.order, name) self.tree[name] = make_value(value) return name end function priors_methods:follows(target, dist, ...) assert(type(dist) == "string", "Expected a string with the distribution name") april_assert(stats.dist[dist], "Unknown distribution %s\n", dist) april_assert(not self.tree[target], "Redifition of target '%s' dist", target) table.insert(self.order, target) self.tree[target] = make_dist(dist, { ... }) return target end function priors_methods:transform(target, func, ...) april_assert(not self.tree[target], "Redifition of trans. '%s'", target) table.insert(self.order, target) self.tree[target] = make_transform(func, { ... }) return target end function priors_methods:sample(rng, weights) local outcomes = {} for _,name in ipairs(self.order) do local v = assert( self.tree[name] ) local s = sampling_funcs[v.t](v, outcomes) local w = weights(name) if not w then outcomes[name] = s(rng, w) end -- if w then w:copy(outcomes[name]) end end self.outcomes = outcomes return outcomes end function priors_methods:update_gradients_with_priors(weights, grads) for name,w in pairs(weights) do local wgrads = assert( grads(name) ) local v = self.tree[name] if v then assert(v.t == "dist", "Expected a distribution") local d = assert(v.obj, "Needs to call sample before") local w = normalize_shape(d, w) local wgrads = normalize_shape(d, wgrads) d:logpdf_derivative(w, wgrads) end end end ------------------------------------------------------------------------------ april-ann-0.4.1/packages/bayesian/package.lua000066400000000000000000000024051263004425400210450ustar00rootroot00000000000000 package{ name = "bayesian", version = "1.0", depends = { "util", "matrix", "dataset", "trainable", "random", "stats" }, keywords = { "Bayesian optimization algorithms" }, description = "", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, -- target{ -- name = "test", -- execute_script{ -- file={ -- "test/test_hmc.lua", -- }, -- }, -- }, target{ name = "provide", depends = "init", -- copy{ file= "c_src/*.h", dest_dir = "include" }, -- provide_bind{ file = "binding/bind_optimizer.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, -- object{ -- file = "c_src/*.cc", -- include_dirs = "${include_dirs}", -- dest_dir = "build", -- }, luac{ orig_dir = "lua_src", dest_dir = "build", }, -- build_bind{ -- file = "binding/bind_optimizer.lua.cc", -- dest_dir = "build", -- } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/bayesian/test/000077500000000000000000000000001263004425400177255ustar00rootroot00000000000000april-ann-0.4.1/packages/bayesian/test/demo_hmc.lua000066400000000000000000000024241263004425400222050ustar00rootroot00000000000000local gp = require "april_tools.gnuplot"() local rnd = random(1234) local x = stats.dist.normal(0,1):sample(rnd, matrix(2,1)):transpose() -- A = inv([1, 1.98; 1.98, 4]); local A = matrix(2,2,{ 50.251256, -24.874372, -24.874372, 12.562814 }) function plot_samples(samples) local data = matrix(#samples,2) for i=1,#samples do data(i,':'):copy(samples[i]("x")) end local mu = data:sum(1)/data:dim(1) local data_centered = data:clone() for i=1,data_centered:dim(1) do data_centered(i,':'):axpy(-1.0, mu) end local stddev = (data^2):sum(1):scal(1/data:dim(1)):sqrt() local cov = (data_centered:transpose() * data_centered) / data:dim(1) print(mu) print(stddev) print(cov) gp:plot{ data=data, u='1:2', w='p' } io.read("*l") gp:close() end function correlated_normal(params) local grad = params.x * A local logp = -0.5 * grad:dot(params.x) return -logp, { x=grad } end ---------------------------------------------------------------------------- local hmc = bayesian.optimizer.hmc() hmc:set_option("seed", 4676) hmc:start_burnin() for i=1,5000 do hmc:execute(correlated_normal, {x=x}) end hmc:finish_burnin() for i=1,5000 do hmc:execute(correlated_normal, {x=x}) end print(hmc:get_state_string()) plot_samples(hmc:get_samples()) april-ann-0.4.1/packages/bayesian/test/demo_metropolis.lua000066400000000000000000000024171263004425400236350ustar00rootroot00000000000000local gp = require "april_tools.gnuplot"() local rnd = random(1234) local x = stats.dist.normal(0,1):sample(rnd, matrix(2,1)):transpose() -- A = inv([1, 1.98; 1.98, 4]); local A = matrix(2,2,{ 50.251256, -24.874372, -24.874372, 12.562814 }) function plot_samples(samples) local data = matrix(#samples,2) for i=1,#samples do data(i,':'):copy(samples[i]("x")) end local mu = data:sum(1)/data:dim(1) local data_centered = data:clone() for i=1,data_centered:dim(1) do data_centered(i,':'):axpy(-1.0, mu) end local stddev = (data^2):sum(1):scal(1/data:dim(1)):sqrt() local cov = (data_centered:transpose() * data_centered) / data:dim(1) print(mu) print(stddev) print(cov) gp:plot{ data=data, u='1:2', w='p' } io.read("*l") gp:close() end function correlated_normal(params) local grad = params.x * A local logp = -0.5 * grad:dot(params.x) return -logp end ---------------------------------------------------------------------------- local opt = bayesian.optimizer.metropolis() opt:set_option("seed", 4676) opt:start_burnin() for i=1,5000 do opt:execute(correlated_normal, {x=x}) end opt:finish_burnin() for i=1,5000 do opt:execute(correlated_normal, {x=x}) end print(opt:get_state_string()) plot_samples(opt:get_samples()) april-ann-0.4.1/packages/bayesian/test/test_digits_hmc.lua000066400000000000000000000155541263004425400236130ustar00rootroot00000000000000-- un generador de valores aleatorios... y otros parametros local bunch_size = 128 local weights_random = random(1234) local description = "256 inputs 10 log_softmax" local inf = -0.1 local sup = 0.1 local shuffle_random = random(5678) local rnd = random(123824) local burnin = 3000 local max_epochs = 3000 local nchains = 1 -------------------------------------------------------------- local m1 = ImageIO.read(string.get_path(arg[0]) .. "../../../TEST/digitos/digits.png"):to_grayscale():invert_colors():matrix() local train_input = dataset.matrix(m1, { patternSize = {16,16}, offset = {0,0}, numSteps = {80,10}, stepSize = {16,16}, orderStep = {1,0} }) local val_input = dataset.matrix(m1, { patternSize = {16,16}, offset = {1280,0}, numSteps = {20,10}, stepSize = {16,16}, orderStep = {1,0} }) -- una matriz pequenya la podemos cargar directamente local m2 = matrix(10,{1,0,0,0,0,0,0,0,0,0}) -- ojito con este dataset, fijaros que usa una matriz de dim 1 y talla -- 10 PERO avanza con valor -1 y la considera CIRCULAR en su unica -- dimension local train_output = dataset.matrix(m2, { patternSize = {10}, offset = {0}, numSteps = {800}, stepSize = {-1}, circular = {true} }) local val_output = dataset.matrix(m2, { patternSize = {10}, offset = {0}, numSteps = {200}, stepSize = {-1}, circular = {true} }) local thenet = ann.mlp.all_all.generate(description) local trainer = trainable.supervised_trainer(thenet, ann.loss.multi_class_cross_entropy(), bunch_size, bayesian.optimizer.hmc()) trainer:build() trainer:set_option("alpha", 0.2) trainer:set_option("epsilon", 0.1) trainer:set_option("epsilon_max", 80) trainer:set_option("epsilon_min", 1e-40) trainer:set_option("mass", 1) trainer:set_option("nsteps", 10) -- trainer:set_option("persistence", 0.90) trainer:set_option("scale", bunch_size) trainer:set_option("seed", 74967) -- ------------------------------------------------------- -- hierarchical model local hmc = trainer:get_optimizer() local priors = hmc:get_priors() -- -- local w_mu = priors:value("w_mu", 0) local w_var = priors:value("w_var", 1000) for wname,_ in trainer:iterate_weights() do priors:follows(wname, "normal", w_mu, w_var) end ------------------------------------------------------- local trainers = {} for i=1,nchains do local tr = trainer:clone() tr:randomize_weights{ random = weights_random, inf = inf, sup = sup, use_fanin = true, } table.insert(trainers, tr) end -- datos para entrenar local datosentrenar = { input_dataset = train_input, output_dataset = train_output, shuffle = shuffle_random, replacement = bunch_size, } local datosvalidar = { input_dataset = val_input, output_dataset = val_output, bunch_size = 32, } local totalepocas = 0 -- local errorval = trainer:validate_dataset(datosvalidar) -- print("# Initial validation error:", errorval) local clock = util.stopwatch() clock:go() for j=1,#trainers do trainers[j]:get_optimizer():start_burnin() end for i=1,burnin do for j=1,#trainers do trainers[j]:train_dataset(datosentrenar) print(trainers[j]:get_optimizer():get_state_string()) end end for j=1,#trainers do trainers[j]:get_optimizer():finish_burnin() end for i=1,max_epochs do for j=1,#trainers do trainers[j]:train_dataset(datosentrenar) print(trainers[j]:get_optimizer():get_state_string()) end end for j=1,#trainers do local thenet = trainers[j]:get_component() local hmc = trainers[j]:get_optimizer() -- Bayesian combination of N sampled weights local bayesian_model = bayesian.build_bayes_comb{ forward = function(weights, input) thenet:build{ weights = weights } return thenet:forward(input) end, N=1000, shuffle=rnd, samples=hmc:get_samples(), } local bayesian_trainer = trainable.supervised_trainer(bayesian_model, ann.loss.zero_one(), 32) bayesian_trainer:build() print("TR", bayesian_trainer:validate_dataset({ input_dataset=datosentrenar.input_dataset, output_dataset=datosentrenar.output_dataset, })) print("VA", bayesian_trainer:validate_dataset(datosvalidar)) -- MAP on validation trainers[j]:set_loss_function(ann.loss.zero_one()) local energies = hmc:get_state_table().energies local map_weigths = bayesian.get_MAP_weights(function(weights, i) return energies[i] -- trainers[j]:build{ weights = weights } -- return trainers[j]:validate_dataset(datosvalidar) end, hmc:get_samples()) trainers[j]:build{ weights = map_weights } print("TR", trainers[j]:validate_dataset({ input_dataset=datosentrenar.input_dataset, output_dataset=datosentrenar.output_dataset, })) print("VA", trainers[j]:validate_dataset(datosvalidar)) local img = ann.connections.input_filters_image(map_weigths("w1"), {16,16}) ImageIO.write(img, "/tmp/filters.png") map_weigths("w1"):toTabFilename("w1.txt") end clock:stop() local cpu,wall = clock:read() printf("Wall total time: %.3f per epoch: %.3f\n", wall, wall/max_epochs) printf("CPU total time: %.3f per epoch: %.3f\n", cpu, cpu/max_epochs) -- print("Test passed! OK!") april-ann-0.4.1/packages/bayesian/test/test_digits_metropolis.lua000066400000000000000000000147611263004425400252400ustar00rootroot00000000000000-- un generador de valores aleatorios... y otros parametros local bunch_size = 1024 local weights_random = random(1234) local description = "256 inputs 10 log_softmax" local inf = -0.1 local sup = 0.1 local shuffle_random = random(5678) local rnd = random(123824) local burnin = 3000 local max_epochs = 3000 local nchains = 1 -------------------------------------------------------------- local m1 = ImageIO.read(string.get_path(arg[0]) .. "../../../TEST/digitos/digits.png"):to_grayscale():invert_colors():matrix() local train_input = dataset.matrix(m1, { patternSize = {16,16}, offset = {0,0}, numSteps = {80,10}, stepSize = {16,16}, orderStep = {1,0} }) local val_input = dataset.matrix(m1, { patternSize = {16,16}, offset = {1280,0}, numSteps = {20,10}, stepSize = {16,16}, orderStep = {1,0} }) -- una matriz pequenya la podemos cargar directamente local m2 = matrix(10,{1,0,0,0,0,0,0,0,0,0}) -- ojito con este dataset, fijaros que usa una matriz de dim 1 y talla -- 10 PERO avanza con valor -1 y la considera CIRCULAR en su unica -- dimension local train_output = dataset.matrix(m2, { patternSize = {10}, offset = {0}, numSteps = {800}, stepSize = {-1}, circular = {true} }) local val_output = dataset.matrix(m2, { patternSize = {10}, offset = {0}, numSteps = {200}, stepSize = {-1}, circular = {true} }) local thenet = ann.mlp.all_all.generate(description) local trainer = trainable.supervised_trainer(thenet, ann.loss.multi_class_cross_entropy(), bunch_size, bayesian.optimizer.metropolis()) trainer:build() trainer:set_option("scale", bunch_size) trainer:set_option("seed", 74967) -- ------------------------------------------------------- -- hierarchical model -- local hmc = trainer:get_optimizer() -- local priors = hmc:get_priors() -- -- -- local w_mu = priors:value("w_mu", 0) -- local w_var = priors:value("w_var", 1) -- for wname,_ in trainer:iterate_weights() do -- priors:dist(wname, "normal", w_mu, w_var) -- end ------------------------------------------------------- local trainers = {} for i=1,nchains do local tr = trainer:clone() tr:randomize_weights{ random = weights_random, inf = inf, sup = sup, use_fanin = true, } table.insert(trainers, tr) end -- datos para entrenar local datosentrenar = { input_dataset = train_input, output_dataset = train_output, shuffle = shuffle_random, replacement = bunch_size, } local datosvalidar = { input_dataset = val_input, output_dataset = val_output, bunch_size = 32, } local totalepocas = 0 -- local errorval = trainer:validate_dataset(datosvalidar) -- print("# Initial validation error:", errorval) local clock = util.stopwatch() clock:go() for j=1,#trainers do trainers[j]:get_optimizer():start_burnin() end for i=1,burnin do for j=1,#trainers do trainers[j]:train_dataset(datosentrenar) print(trainers[j]:get_optimizer():get_state_string()) end end for j=1,#trainers do trainers[j]:get_optimizer():finish_burnin() end for i=1,max_epochs do for j=1,#trainers do trainers[j]:train_dataset(datosentrenar) print(trainers[j]:get_optimizer():get_state_string()) end end for j=1,#trainers do local thenet = trainers[j]:get_component() local hmc = trainers[j]:get_optimizer() -- Bayesian combination of N sampled weights local bayesian_model = bayesian.build_bayes_comb{ forward = function(weights, input) thenet:build{ weights = weights } return thenet:forward(input) end, N=1000, shuffle=rnd, samples=hmc:get_samples(), } local bayesian_trainer = trainable.supervised_trainer(bayesian_model, ann.loss.zero_one(), 32) bayesian_trainer:build() print("TR", bayesian_trainer:validate_dataset({ input_dataset=datosentrenar.input_dataset, output_dataset=datosentrenar.output_dataset, })) print("VA", bayesian_trainer:validate_dataset(datosvalidar)) -- MAP on validation trainers[j]:set_loss_function(ann.loss.zero_one()) local map_weigths = bayesian.get_MAP_weights(function(weights) trainers[j]:build{ weights = weights } return trainers[j]:validate_dataset(datosvalidar) end, hmc:get_samples(), hmc:get_state_table().energies) trainers[j]:build{ weights = map_weights } print("TR", trainers[j]:validate_dataset({ input_dataset=datosentrenar.input_dataset, output_dataset=datosentrenar.output_dataset, })) print("VA", trainers[j]:validate_dataset(datosvalidar)) local img = ann.connections.input_filters_image(map_weigths("w1"), {16,16}) ImageIO.write(img, "/tmp/filters.png") end clock:stop() local cpu,wall = clock:read() printf("Wall total time: %.3f per epoch: %.3f\n", wall, wall/max_epochs) printf("CPU total time: %.3f per epoch: %.3f\n", cpu, cpu/max_epochs) -- print("Test passed! OK!") april-ann-0.4.1/packages/clustering/000077500000000000000000000000001263004425400173325ustar00rootroot00000000000000april-ann-0.4.1/packages/clustering/kmeans/000077500000000000000000000000001263004425400206105ustar00rootroot00000000000000april-ann-0.4.1/packages/clustering/kmeans/matrix/000077500000000000000000000000001263004425400221145ustar00rootroot00000000000000april-ann-0.4.1/packages/clustering/kmeans/matrix/lua_src/000077500000000000000000000000001263004425400235445ustar00rootroot00000000000000april-ann-0.4.1/packages/clustering/kmeans/matrix/lua_src/kmeans_matrix.lua000066400000000000000000000270421263004425400271160ustar00rootroot00000000000000-- local funcs = get_table_from_dotted_string("clustering.kmeans.matrix",true) local BSIZE=1024 ------------------- -- FIND CLUSTERS -- ------------------- -- fill vector T with the index of centroid associated to each sample -- --@param X samples, NxD matrix (N rows D columns) --@param C centroids, KxD matrix --@param T vector de tags de talla N, si este punter val 0 no es fa res function funcs.find_clusters(X,C,T,verbose) assert(X and class.is_a(X,matrix), "A matrix needed as 1st argument") assert(C and class.is_a(C,matrix), "A matrix needed as 2nd argument") local Xdim = X:dim() local Cdim = C:dim() assert(#Xdim == 2, "Data matrix must be bi-dimensional") assert(#Cdim == 2, "Centroids matrix must be bi-dimensional") local N = Xdim[1] -- number of samples local D = Xdim[2] -- number of features (dimensions) local K = Cdim[1] -- number of clusters april_assert(Cdim[2] == D, "Different columns found between data and centroids: %d ~= %d\n", D, Cdim[2]) local T = T or matrixInt32(N,1) april_assert(#T:dim() == 2 and T:dim(1) == N and T:dim(2) == 1 and class.is_a(T,matrixInt32), "The tags matrix must be bi-dimensional matrixInt32 and with size %dx1\n", N) -- local auxXblock,mins local Mnew = matrix local M2Y = Mnew(BSIZE,K) local CScores = Mnew(K):zeros() local CSqScores = Mnew(K):zeros() local Ccont = matrixInt32(K):zeros() local score = 0.0 -- compute Ysquare local Ysq = C:clone():pow(2):sum(2) -- vector of size K -- traverse in BSIZE blocks for b=1,N,BSIZE do local block_size = math.min(BSIZE,N-b+1) if block_size ~= BSIZE then mins,auxXblock = nil,nil end local Xblock = X:slice({b,1},{block_size,D}) local M2Yblock = M2Y:slice({1,1},{block_size,K}) -- STEP 1: multiply Xblock by C to compute clusters distances M2Yblock:gemm{ A=Xblock, B=C, trans_A=false, trans_B=true, alpha=-2.0, beta=0.0 } -- STEP 2: sums Y**2 local M2Yrow for i=1,block_size do M2Yrow = M2Yblock:select(1,i,M2Yrow) M2Yrow:axpy(1.0,Ysq) end -- for i=1,block_size do -- STEP 3: compute closest centroid mins,argmins = M2Yblock:min(2,mins,T:slice({b,1},{block_size,1})) -- STEP 4: accumulate score auxXblock = auxXblock or Xblock:clone() local scores = auxXblock:copy(Xblock):pow(2):sum(2):axpy(1.0,mins) for i=1,K do local v = scores:get(i,1) local pos = argmins:get(i,1) local aux = CScores:get(pos) CScores:set(pos, aux + v) aux = CSqScores:get(pos) CSqScores:set(pos, aux + v*v) Ccont:set(pos, Ccont:get(pos) + 1) end -- for i=1,K do -- sum all scores score = score + mins:sum() end -- for b=1,N,BSIZE for k=1,K do local sc,c = CScores:get(k),Ccont:get(k) local kdist = sc / c score = score + sc if verbose then printf("# Cluster %d, %d/%d (%0.3f%%), samples, dt: %0.9f\n", k, c ,N, c*100.0/N, kdist) end end score = score/N return score,T end ---------------------------- -- __call BASIC ALGORITHM -- ---------------------------- function funcs.basic(X,C,params) local params = get_table_fields( { threshold = { mandatory=false, type_match="number", default=1e-5 }, max_iter = { mandatory=false, type_match="number", default=100 }, verbose = { mandatory=false }, }, params) assert(X and class.is_a(X,matrix), "A matrix needed as 1st argument") assert(C and class.is_a(C,matrix), "A matrix needed as 2nd argument") local Xdim = X:dim() local Cdim = C:dim() assert(#Xdim == 2, "Data matrix must be bi-dimensional") assert(#Cdim == 2, "Centroids matrix must be bi-dimensional") local N = Xdim[1] -- number of samples local D = Xdim[2] -- number of features (dimensions) local K = Cdim[1] -- number of clusters april_assert(Cdim[2] == D, "Different columns found between data and centroids: %d ~= %d\n", D, Cdim[2]) local max_iter = params.max_iter local threshold = params.threshold local Mnew = matrix local M2Y = Mnew(BSIZE,K) local Csum = Mnew(K,D) local Csq = Mnew(K,D) local Ccont = Mnew(K) local iter = 0 local score local discrepancy repeat local Csum_row,Csq_row,X_row,mins,argmins,auxXblock -- compute Ysquare local Ysq = C:clone():pow(2):sum(2) -- vector of size K -- counters set to zero Csum:zeros() Csq:zeros() Ccont:zeros() score = 0.0 discrepancy = 0.0 -- traverse in blocks of BSIZE for b=1,N,BSIZE do local block_size = math.min(BSIZE,N-b+1) if block_size ~= BSIZE then mins,argmins,auxXblock = nil,nil,nil end local Xblock = X:slice({b,1},{block_size,D}) local M2Yblock = M2Y:slice({1,1},{block_size,K}) -- STEP 1: multiply Xblock by C to compute clusters distances M2Yblock:gemm{ A=Xblock, B=C, trans_A=false, trans_B=true, alpha=-2.0, beta=0.0 } -- STEP 2: sums Y**2 local M2Yrow for i=1,block_size do M2Yrow = M2Yblock:select(1,i,M2Yrow) M2Yrow:axpy(1.0,Ysq) end -- for i=1,block_size do -- STEP 3: compute closest centroid mins,argmins = M2Yblock:min(2,mins,argmins) -- STEP 4: accumulate score auxXblock = auxXblock or matrix.as(Xblock) auxXblock = auxXblock:copy(Xblock):pow(2) local scores = auxXblock:pow(2):sum(2):axpy(1.0,mins) score = score + mins:sum() for i=1,block_size do local cpos = argmins:get(i,1) Csum_row = Csum:select(1,cpos,Csum_row) Csq_row = Csq:select(1,cpos,Csq_row) X_row = Xblock:select(1,i) X_row2 = auxXblock:select(1,i) Csum_row:axpy(1.0, X_row) Csq_row:axpy(1.0, X_row2) Ccont:set(cpos, Ccont:get(cpos) + 1) end end -- STEP 5: compute discrepancy with previous iteration for i=1,K do local count = Ccont:get(i) if count > 0 then local rcount = 1/count local csum_i,c_i = Csum(i,':'),C(i,':') csum_i:scal(rcount) Csq(i,':'):scal(rcount) local diff = (csum_i - c_i):abs():sum() discrepancy = discrepancy + diff c_i:copy(csum_i) end end -- iter = iter + 1 if params.verbose then printf("# Iteration %d. Centroids Discrepancy: %g\n", iter,discrepancy) end io.stdout:flush() until iter == params.max_iter or discrepancy < params.threshold -- STEP 6: compute distortion if params.verbose then for i=1,K do printf("# Cluster %d: %d/%d samples ( %.3f%% )\n", i,Ccont:get(i),N,Ccont:get(i)*100.0/N) end end local norm2 = X:norm2() score = (score + norm2*norm2) / N return score,C end ----------------------------- -- __call REFINE ALGORITHM -- ----------------------------- --[[ refine initialization for kmeans, see paper @inproceedings{bradley1998refining, title={Refining initial points for k-means clustering}, author={Bradley, P.S. and Fayyad, U.M.}, booktitle={Proceedings of the Fifteenth International Conference on Machine Learning}, volume={66}, year={1998}, organization={San Francisco, CA, USA} } matrix C does NOT contain centroids, it is used to return the resulting centroids returns best distortion --]] function funcs.refine(X,C,params) local params = get_table_fields( { subsamples = { mandatory=false, type_match="number", default=10 }, percentage = { mandatory=false, type_match="number", default=0.01 }, random = { mandatory=true, isa_match=random }, threshold = { mandatory=false, type_match="number", default=1e-5 }, max_iter = { mandatory=false, type_match="number", default=100 }, verbose = { mandatory=false }, }, params) assert(X and class.is_a(X,matrix), "A matrix needed as 1st argument") assert(C and class.is_a(C,matrix), "A matrix needed as 2nd argument") local Xdim = X:dim() local Cdim = C:dim() assert(#Xdim == 2, "Data matrix must be bi-dimensional") assert(#Cdim == 2, "Centroids matrix must be bi-dimensional") local N = Xdim[1] -- number of samples local D = Xdim[2] -- number of features (dimensions) local K = Cdim[1] -- number of clusters local J = params.subsamples local rnd = params.random april_assert(Cdim[2] == D, "Different columns found between data and centroids: %d ~= %d\n", D, Cdim[2]) local num_samples = math.max(K, math.round(N * params.percentage)) local Mnew = matrix local S = Mnew(num_samples, D) local CM = Mnew(J, K, D) local FM = matrix.as(CM) local function get_row_idx() return rnd:randInt(1,N) end -- auxiliary variables which store temporal matrices local Xrow,Crow,Srow,CMiter,FMiter -- cluster initialization for c=1,K do local row = get_row_idx() Xrow = X:select(1,row,Xrow) Crow = C:select(1,c,Crow) Crow:copy(Xrow) end -- compute J kmeans subsamples for j=1,J do -- subsampling for s=1,num_samples do local row = get_row_idx() -- copy random row to matrix S Xrow = X:select(1,row,Xrow) Srow = S:select(1,s,Srow) Srow:copy(Xrow) end -- copy centroids from C to CM CMiter = CM:select(1,j,CMiter) CMiter:copy(C) if params.verbose then printf("# REFINE: %d J %d\n", num_samples, j) end io.stdout:flush() funcs.basic(S,CMiter,{ max_iter=params.max_iter, threshold = params.threshold, verbose = params.verbose }) end -- here we have J different sets of K centroids in matrix CM FM:copy(CM) -- look for the best set FMiter = FM:select(1,1,FMiter) local best_score = funcs.basic(X,FMiter,{verbose = params.verbose}) local best_J = 1 for j=2,J do FMiter = FM:select(1,j,FMiter) local score = funcs.basic(X,FMiter,{verbose = params.verbose}) if score < best_score then best_score,best_J = score,j end end -- copy the best centroids to C C:copy(FM:select(1,best_J,FMiter)) return best_score,C end ----------------------- -- __call METAMETHOD -- ----------------------- local function metatable_call(self,params) local params = get_table_fields( { data = { mandatory=true, isa_match=matrix, default=nil }, K = { mandatory=false, type_match="number", default=nil }, distance = { mandatory=false, type_match="string", default="euclidean" }, subsamples = { mandatory=false, type_match="number" }, percentage = { mandatory=false, type_match="number" }, random = { mandatory=false, isa_match=random, default=nil }, centroids = { mandatory=false, isa_match=matrix, default=nil }, threshold = { mandatory=false, type_match="number" }, max_iter = { mandatory=false, type_match="number" }, verbose = { mandatory=false }, }, params) -- sanity checks april_assert(params.distance == "euclidean", "Distance %s not supported\n", params.distance) assert(params.K or params.centroids, "Parameter K or centroids must be defined") if params.K and params.centroids then assert(params.centroids:dim(1) == params.K, "Centroids matrix dim(1) is different of given K parameter") end -- local centroids = params.centroids local data = params.data local distortion if not centroids then assert(random, "Field random is mandatory when not given centroids") centroids = matrix(params.K,data:dim(2)) distortion = funcs.refine(data, centroids, { max_iter = params.max_iter, random = params.random, threshold = params.threshold, percentage = params.percentage, subsamples = params.subsamples, verbose = params.verbose }) end distortion = funcs.basic(data, centroids, { max_iter = params.max_iter, threshold = params.threshold, verbose = params.verbose }) return distortion,centroids end setmetatable(funcs, { __call = metatable_call }) return funcs april-ann-0.4.1/packages/clustering/kmeans/matrix/package.lua000066400000000000000000000024261263004425400242160ustar00rootroot00000000000000 package{ name = "clustering.kmeans.matrix", version = "1.0", depends = { "util", "dataset", "matrix", "random", "mathcore" }, keywords = { "clustering", "K-means" }, description = "K-means clustering algorithm", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test.lua", "test/test_refine.lua", }, }, }, target{ name = "provide", depends = "init", --copy{ file= "c_src/*.h", dest_dir = "include" }, --provide_bind{ file = "binding/bind_kmeans_matrix.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, -- object{ -- file = "c_src/*.cc", -- include_dirs = "${include_dirs}", -- dest_dir = "build", -- }, luac{ orig_dir = "lua_src", dest_dir = "build", }, -- build_bind{ -- file = "binding/bind_kmeans_matrix.lua.cc", -- dest_dir = "build", -- } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/clustering/kmeans/matrix/test/000077500000000000000000000000001263004425400230735ustar00rootroot00000000000000april-ann-0.4.1/packages/clustering/kmeans/matrix/test/data.txt000066400000000000000000000352341263004425400245540ustar00rootroot00000000000000100 16 ascii -1.49383 -1.11884 0.412841 -0.386154 -1.31948 -0.166529 -1.49352 -0.0358276 0.234186 -0.44173 1.79381 -0.836024 -0.0698595 0.286595 -0.653472 -1.05435 -1.23726 -0.792613 0.437342 -0.31071 -1.09998 -0.187008 -1.39263 -0.0617716 0.137347 -0.372681 1.42874 -0.749145 0.0120808 0.199252 -0.559779 -0.974969 -1.0382 -0.516389 0.403518 -0.303574 -0.906858 -0.137893 -1.30932 -0.0144967 0.0130425 -0.291268 1.12405 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0.273633 -0.351357 -1.16593 0.176417 -1.6816 0.231072 -0.0344756 -0.627727 1.83771 -1.17747 -0.0407077 0.218003 -0.637949 -0.994239 -1.6017 -1.21142 0.272223 -0.354628 -1.16261 0.178225 -1.68508 0.233089 -0.0374788 -0.628977 1.83477 -1.17911 -0.0432108 0.217467 -0.640826 -0.99028 -1.59315 -1.20136 0.272474 -0.353547 -1.15239 0.181291 -1.684 0.235314 -0.044234 -0.627469 1.82169 -1.17896 -0.0406552 0.21457 -0.638046 -0.984534 -1.58017 -1.18942 0.273817 -0.351065 -1.13942 0.186542 -1.6808 0.238967 -0.0530806 -0.625908 1.80614 -1.17954 -0.035587 0.210219 -0.63237 -0.978187 -1.56692 -1.1715 0.273199 -0.349672 -1.12541 0.19128 -1.67672 0.243616 -0.0621001 -0.623994 1.78646 -1.17989 -0.030933 0.204891 -0.627011 -0.97096 -1.55947 -1.15802 0.270858 -0.348237 -1.11257 0.193756 -1.67384 0.245902 -0.0693673 -0.624216 1.77007 -1.18179 -0.0270049 0.198746 -0.623691 -0.963103 -1.56488 -1.15952 0.267412 -0.350495 -1.10854 0.196149 -1.67622 0.24875 -0.072317 -0.630668 1.7698 -1.18807 -0.0284003 0.195538 -0.625178 -0.959527 -1.58616 -1.18223 0.263415 -0.357148 -1.12024 0.198169 -1.68621 0.251601 -0.0682088 -0.642956 1.79323 -1.1983 -0.0373498 0.197494 -0.634365 -0.963392 -1.62162 -1.22542 0.261504 -0.364264 -1.14765 0.198877 -1.70235 0.254015 -0.0571156 -0.655369 1.84228 -1.2113 -0.0497596 0.206088 -0.647771 -0.975569 -1.65505 -1.27018 0.261101 -0.369721 -1.17999 0.198726 -1.7189 0.255125 -0.0423893 -0.666324 1.89669 -1.22298 -0.0620274 0.21847 -0.661243 -0.992572 -1.67633 -1.30138 0.260489 -0.370958 -1.20474 0.199421 -1.72942 0.253713 -0.0301797 -0.67393 1.93499 -1.22787 -0.0715798 0.2306 -0.669616 -1.00784 april-ann-0.4.1/packages/clustering/kmeans/matrix/test/pruebasimple1.lua000066400000000000000000000006431263004425400263520ustar00rootroot00000000000000x = {} for i=1,5 do table.insert(x,i) table.insert(x,i) end data = matrix(5,2,x) clusters = matrix(2,2,{ 0,0, 1,1, }) K = 2 res, C = clustering.kmeans.matrix({ data = data, K = K, centroids = clusters }) print(clusters) print("Distorsion:",res) points = matrix(2,2,{ 0,0, 10,10, }) score,tags=clustering.kmeans.matrix.find_clusters(points,clusters) print(tags) april-ann-0.4.1/packages/clustering/kmeans/matrix/test/test.lua000066400000000000000000000022271263004425400245600ustar00rootroot00000000000000local T = utest.test local check = utest.check T("KMeansMatrixTest", function() local filename = arg[1] or string.get_path(arg[0]) .. 'data.txt' local K = arg[2] or 2 local data = matrix.fromFilename(filename) local clusters = data({1,K},':'):clone() -- print(clusters) local clock = util.stopwatch() clock:go() local res = clustering.kmeans.matrix{ data=data, centroids=clusters } clock:stop() local cpu, wall = clock:read() -- print(cpu, wall) check.number_eq(res, 0.053190536499023, nil, "result check") check.eq(clusters, matrix(2,16, { -1.51381, -1.09521, 0.276019, -0.352453, -1.08768, 0.167996, -1.64307, 0.227699, -0.0660796, -0.596381, 1.70157, -1.14844, -0.0181014, 0.187125, -0.618449, -0.946881, -1.28483, -0.798679, 0.282941, -0.365985, -0.942726, 0.103687, -1.52005, 0.176974, -0.0922824, -0.481356, 1.38082, -1.02229, 0.0243497, 0.133867, -0.588762, -0.853817, }), "clusters check") end) april-ann-0.4.1/packages/clustering/kmeans/matrix/test/test_refine.lua000066400000000000000000000017671263004425400261200ustar00rootroot00000000000000local T = utest.test local check = utest.check T("KMeansMatrixRefineTest", function() local filename = arg[1] or string.get_path(arg[0]) .. 'data.txt' local data = matrix.fromFilename(filename) local K = 2 local res,C = clustering.kmeans.matrix({ data = data, K = K, random = random(1234) }) check.number_eq(res, 0.053191109336913, nil, "result check") check.eq(C, matrix(2,16, { -1.28483, -0.798679, 0.282941, -0.365985, -0.942726, 0.103687, -1.52005, 0.176974, -0.0922824, -0.481356, 1.38082, -1.02229, 0.0243497, 0.133867, -0.588762, -0.853817, -1.51381, -1.09521, 0.276019, -0.352453, -1.08768, 0.167996, -1.64307, 0.227699, -0.0660796, -0.596381, 1.70157, -1.14844, -0.0181014, 0.187125, -0.618449, -0.946881, }), "clusters check") end) april-ann-0.4.1/packages/functions/000077500000000000000000000000001263004425400171635ustar00rootroot00000000000000april-ann-0.4.1/packages/functions/binding/000077500000000000000000000000001263004425400205755ustar00rootroot00000000000000april-ann-0.4.1/packages/functions/binding/bind_function_interface.lua.cc000066400000000000000000000042551263004425400265330ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "bind_april_io.h" #include "bind_tokens.h" //BIND_END //BIND_HEADER_H #include "function_interface.h" #include "identity_function.h" using namespace Functions; using Basics::Token; //BIND_END //BIND_LUACLASSNAME Serializable aprilio.serializable //BIND_LUACLASSNAME FunctionInterface functions //BIND_CPP_CLASS FunctionInterface //BIND_SUBCLASS_OF FunctionInterface Serializable //BIND_CONSTRUCTOR FunctionInterface { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD FunctionInterface get_input_size { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(uint, obj->getInputSize()); } //BIND_END //BIND_METHOD FunctionInterface get_output_size { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(uint, obj->getOutputSize()); } //BIND_END //BIND_METHOD FunctionInterface calculate { LUABIND_CHECK_ARGN(==,1); Token *input; LUABIND_GET_PARAMETER(1, Token, input); LUABIND_RETURN(Token, obj->calculate(input)); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME IdentityFunction functions.identity //BIND_CPP_CLASS IdentityFunction //BIND_SUBCLASS_OF IdentityFunction FunctionInterface //BIND_CONSTRUCTOR IdentityFunction { LUABIND_CHECK_ARGN(==,0); obj = new IdentityFunction(); LUABIND_RETURN(IdentityFunction, obj); } //BIND_END april-ann-0.4.1/packages/functions/binding/bind_function_interface.lua.cc.bak000066400000000000000000000144401263004425400272640ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "bind_dataset.h" //BIND_END //BIND_HEADER_H #include "function_interface.h" #include "datasettoken_producer.h" #include "datasettoken_consumer.h" using namespace Functions; //BIND_END //BIND_LUACLASSNAME FunctionBase __function_base__ //BIND_CPP_CLASS FunctionBase //BIND_CONSTRUCTOR FunctionBase { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD FunctionBase get_input_size { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(uint, obj->getInputSize()); } //BIND_END //BIND_METHOD FunctionBase get_output_size { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(uint, obj->getOutputSize()); } //BIND_END /////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME TokenTokenFunctionInterface __function_interface_token_token__ //BIND_CPP_CLASS TokenTokenFunctionInterface //BIND_SUBCLASS_OF TokenTokenFunctionInterface FunctionBase //BIND_CONSTRUCTOR TokenTokenFunctionInterface { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD TokenTokenFunctionInterface calculate //DOC_BEGIN // calculate(input) : table /// Execute the calculate method of a function, and returns a Lua table with the function output /// @param input A Lua table with the functions input //DOC_END { unsigned int input_size, output_size = obj->getOutputSize(); Token *input, *output = new float[output_size]; LUABIND_CHECK_ARGN(==,1); LUABIND_TABLE_GETN(1, input_size); if (input_size != obj->getInputSize()) LUABIND_ERROR("Incorrect input size!!!\n"); input = new float[input_size]; LUABIND_TABLE_TO_VECTOR(1, float, input, input_size); if (!obj->calculate(input, input_size, output, output_size)) LUABIND_ERROR("Impossible to execute calculate method!!!\n"); LUABIND_VECTOR_TO_NEW_TABLE(float, output, output_size); LUABIND_RETURN_FROM_STACK(-1); delete[] input; delete[] output; } //BIND_END //BIND_METHOD FloatFloatFunctionInterface calculate_in_pipeline //DOC_BEGIN // calculate_in_pipeline{ consumer, producer } /// Execute the calculate in pipeline method of a function /// @param input A Lua table with the functions input //DOC_END { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "producer", "consumer", "input_size", "output_size", (const char *)0); // de tipo float => float FloatDataProducer *producer; unsigned int input_size; FloatDataConsumer *consumer; unsigned int output_size; LUABIND_GET_TABLE_PARAMETER(1, producer, FloatDataProducer, producer); LUABIND_GET_TABLE_PARAMETER(1, consumer, FloatDataConsumer, consumer); LUABIND_GET_TABLE_PARAMETER(1, input_size, uint, input_size); LUABIND_GET_TABLE_PARAMETER(1, output_size, uint, output_size); obj->calculateInPipeline(producer, input_size, consumer, output_size); } //BIND_END //////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME FloatDataProducer __float_data_producer__ //BIND_CPP_CLASS FloatDataProducer //BIND_CONSTRUCTOR FloatDataProducer { LUABIND_ERROR("this is an abstract class"); return 0; } //BIND_END //BIND_DESTRUCTOR FloatDataProducer { } //BIND_END //BIND_METHOD FloatDataProducer reset { obj->reset(); } //BIND_END //BIND_LUACLASSNAME FloatDataConsumer __float_data_consumer__ //BIND_CPP_CLASS FloatDataConsumer //BIND_CONSTRUCTOR FloatDataConsumer { LUABIND_ERROR("this is an abstract class"); return 0; } //BIND_END //BIND_DESTRUCTOR FloatDataConsumer { } //BIND_END //BIND_METHOD FloatDataConsumer reset { obj->reset(); } //BIND_END //BIND_LUACLASSNAME LogFloatDataProducer __logfloat_data_producer__ //BIND_CPP_CLASS LogFloatDataProducer //BIND_CONSTRUCTOR LogFloatDataProducer { LUABIND_ERROR("this is an abstract class"); return 0; } //BIND_END //BIND_DESTRUCTOR LogFloatDataProducer { } //BIND_END //BIND_METHOD LogFloatDataProducer reset { obj->reset(); } //BIND_END //BIND_LUACLASSNAME DoubleDataProducer __double_data_producer__ //BIND_CPP_CLASS DoubleDataProducer //BIND_CONSTRUCTOR DoubleDataProducer { LUABIND_ERROR("this is an abstract class"); return 0; } //BIND_END //BIND_DESTRUCTOR DoubleDataProducer { } //BIND_END //BIND_METHOD DoubleDataProducer reset { obj->reset(); } //BIND_END //BIND_LUACLASSNAME LogFloatDataConsumer __logfloat_data_consumer__ //BIND_CPP_CLASS LogFloatDataConsumer //BIND_CONSTRUCTOR LogFloatDataConsumer { LUABIND_ERROR("this is an abstract class"); return 0; } //BIND_END //BIND_DESTRUCTOR LogFloatDataConsumer { } //BIND_END //BIND_METHOD LogFloatDataConsumer reset { obj->reset(); } //BIND_END //////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME DataSetFloatProducer functions.producer.dataset //BIND_CPP_CLASS DataSetFloatProducer //BIND_SUBCLASS_OF DataSetFloatProducer FloatDataProducer //BIND_CONSTRUCTOR DataSetFloatProducer { DataSetFloat *ds; LUABIND_GET_PARAMETER(1, DataSetFloat, ds); obj = new DataSetFloatProducer(ds); LUABIND_RETURN(DataSetFloatProducer, obj); } //BIND_END //////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME DataSetFloatConsumer functions.consumer.dataset //BIND_CPP_CLASS DataSetFloatConsumer //BIND_SUBCLASS_OF DataSetFloatConsumer FloatDataConsumer //BIND_CONSTRUCTOR DataSetFloatConsumer { DataSetFloat *ds; LUABIND_GET_PARAMETER(1, DataSetFloat, ds); obj = new DataSetFloatConsumer(ds); LUABIND_RETURN(DataSetFloatConsumer, obj); } //BIND_END april-ann-0.4.1/packages/functions/c_src/000077500000000000000000000000001263004425400202545ustar00rootroot00000000000000april-ann-0.4.1/packages/functions/c_src/function_interface.h000066400000000000000000000045171263004425400243010ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef FUNCTION_INTERFACE_H #define FUNCTION_INTERFACE_H #include "error_print.h" #include "serializable.h" #include "token_base.h" /// Generic functions that receive and produce Basics::Token pointers. namespace Functions { /// A virtual class that serves as high level interface. /** A FunctionInterface is an abstraction of an object which represents a mathematical function. It adds to the interface abstract methods which calculates output vector given input vector. Every function is feeded with an input Token and produces an output Token. */ class FunctionInterface : public AprilIO::Serializable { public: FunctionInterface() : Serializable() { } virtual ~FunctionInterface() { } /// It returns the input (or domain) size of the function. virtual unsigned int getInputSize() const = 0; /// It returns the output (or range) size of the function. virtual unsigned int getOutputSize() const = 0; /** * @brief A new abstract method that computes output vector given input * vector. * * The function doesn't receive the ownership of the given Basics::Token. * * @note ANN based filters would IncRef and DecRef the given input * Basics::Token, so be careful with this. * * @note Some functions work in-place, so take it into account. * * @todo const Token *input */ virtual Basics::Token *calculate(Basics::Token *input) = 0; }; } #endif //FUNCTION_INTERFACE_H april-ann-0.4.1/packages/functions/c_src/identity_function.h000066400000000000000000000030011263004425400241550ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef IDENTITY_FUNCTION_H #define IDENTITY_FUNCTION_H #include "function_interface.h" namespace Functions { class IdentityFunction : public FunctionInterface { public: IdentityFunction() : FunctionInterface() { } virtual ~IdentityFunction() { } /// It returns the input (or domain) size of the function. virtual unsigned int getInputSize() const { return 0; } /// It returns the output (or range) size of the function. virtual unsigned int getOutputSize() const { return 0; } virtual Basics::Token *calculate(Basics::Token *input) { return input; } }; } #endif // IDENTITY_FUNCTION_H april-ann-0.4.1/packages/functions/c_src/old/000077500000000000000000000000001263004425400210325ustar00rootroot00000000000000april-ann-0.4.1/packages/functions/c_src/old/contextualizer_producer.cc000066400000000000000000000054301263004425400263260ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "contextualizer_producer.h" namespace Functions { FloatContextualizerProducerFromDouble:: FloatContextualizerProducerFromDouble(DataProducer *orig_producer, int input_size, int left_context, int right_context, float *means=0, float *devs =0) : orig_producer(orig_producer), input_size(input_size), left_context(left_context), right_context(right_context), means(means), devs(devs), ctxt(left_context,right_context,input_size) { output_size = input_size*(left_context+1+right_context); IncRef(orig_producer); } FloatContextualizerProducerFromDouble::~FloatContextualizerProducerFromDouble() { DecRef(orig_producer); delete[] means; delete[] devs; } float* FloatContextualizerProducerFromDouble::get() { float *resul = 0; // if contextualizer mode is end, shift sliding window if (ctxt.is_ended()) { ctxt.shift(); } else { // we are not at the end, a new data vector will be pushed into // contextualizer object do { double *double_vec = orig_producer->get(); float *vec = 0; if (double_vec != 0) { vec = new float[input_size]; // normalize substracting mean and dividing by standard deviation if (means!=0 && devs!=0) for (int i=0; ireset(); } } april-ann-0.4.1/packages/functions/c_src/old/contextualizer_producer.h000066400000000000000000000047751263004425400262030ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef CONTEXTUALIZER_PRODUCER_H #define CONTEXTUALIZER_PRODUCER_H #include "function_interface.h" #include "context.h" namespace Functions { /// A specialization of FloatDataProducer which gets data from another producer. /** A specialization of FloatDataProducer class which works as a source of data vectors. Data vectors are stored at the internal DoubleDataProducer attribute. A context is added to data vectors, in order to being used as inputs of classifiers, as for example a neural network. Also, this object could normalize the data vectors substracting the mean and dividing by the standard deviation. */ class FloatContextualizerProducerFromDouble : public DataProducer { /// Internal DoubleDataProducer source DataProducer *orig_producer; /// Size of vectors at orig_producer int input_size; /// Size of vectros after context addition int output_size; /// Left context added to data vectors int left_context; /// Right context added to data vectors int right_context; /// Means vector, for mean normalization of data. float *means; /// Standard deviations vector, for variance normalization of data float *devs; /// Context object, it implements the contextualizer logic AprilUtils::context_of_vectors ctxt; public: FloatContextualizerProducerFromDouble(DataProducer *orig_producer, int input_size, int left_context, int right_context, float *means, float *devs); ~FloatContextualizerProducerFromDouble(); float *get(); void reset(); }; } #endif // CONTEXTUALIZER_PRODUCER_H april-ann-0.4.1/packages/functions/c_src/old/datasettoken_consumer.cc000066400000000000000000000032261263004425400257450ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "datasettoken_consumer.h" namespace Functions { DataSetTokenConsumer::DataSetTokenConsumer(DataSetToken *ds) : ds(ds) { IncRef(ds); ipat = 0; } DataSetTokenConsumer::~DataSetTokenConsumer() { DecRef(ds); } void DataSetTokenConsumer::put(Token *pattern) { // check for a NULL pointer and check the number of patterns with the // counter value if (pattern != 0 && static_cast(ipat) < ds->numPatterns()) { IncRef(pattern); ds->putPattern(ipat++, pattern); DecRef(pattern); } } void DataSetTokenConsumer::reset() { // with every reset, this consumer will overwrite the entire DataSetToken ipat = 0; } void DataSetTokenConsumer::destroy() { // nothing more to do, only reset the counter ipat = 0; } } april-ann-0.4.1/packages/functions/c_src/old/datasettoken_consumer.h000066400000000000000000000032021263004425400256010ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "function_interface.h" #include "datasetToken.h" namespace Functions { /// A specialization of DataConsumer which put data into a dataset. /** A specialization of FloatDataConsumer class which works as a sink of data vectors. Data vectros will be stored in the internal DataSetToken attribute. The DataSetToken must have enough space for all consumed vectors. */ class DataSetTokenConsumer : public DataConsumer{ /// Internal DataSetToken where tokens will be stored. DataSetToken *ds; /// Auxiliar iterator counter of how many vectors were processed. unsigned int ipat; public: DataSetTokenConsumer(DataSetToken *ds); ~DataSetTokenConsumer(); void put(Token *pattern); void reset(); void destroy(); }; } april-ann-0.4.1/packages/functions/c_src/old/datasettoken_producer.cc000066400000000000000000000030711263004425400257330ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "datasetfloat_producer.h" namespace Functions { DataSetFloatProducer::DataSetFloatProducer(DataSetFloat *ds) : ds(ds) { IncRef(ds); ipat = 0; } DataSetFloatProducer::~DataSetFloatProducer() { DecRef(ds); } float *DataSetFloatProducer::get() { float *pattern = 0; // check the number of produced data vectors, if the maximum is achieved, a // NULL pointer will be returned if (static_cast(ipat) < ds->numPatterns()) { pattern = new float[ds->patternSize()]; ds->getPattern(ipat++, pattern); } return pattern; } void DataSetFloatProducer::reset() { ipat = 0; } void DataSetFloatProducer::destroy() { ipat = 0; } } april-ann-0.4.1/packages/functions/c_src/old/datasettoken_producer.h000066400000000000000000000030551263004425400255770ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "function_interface.h" #include "datasetFloat.h" namespace Functions { /// A specialization of FloatDataProducer which gets data from a dataset. /** A specialization of FloatDataProducer class which works as a source of data vectors. Data vectros are stored at the internal DataSetFloat attribute. */ class DataSetFloatProducer : public FloatDataProducer{ /// The internal DataSetFloat source. DataSetFloat *ds; /// An auxiliar counter which indicates the number of vectros produced. unsigned int ipat; public: DataSetFloatProducer(DataSetFloat *ds); ~DataSetFloatProducer(); float *get(); void reset(); void destroy(); }; } april-ann-0.4.1/packages/functions/c_src/old/function_interface.h000066400000000000000000000117671263004425400250640ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef FUNCTION_INTERFACE_H #define FUNCTION_INTERFACE_H #include "logbase.h" #include "error_print.h" #include "referenced.h" #include "token_base.h" namespace Functions { /// A pure abstract class that serves as interface. /** A DataProducer is an abstraction of an object which produces a sequence a vectors of a given type, followed by a 0 indicating sequence ending. The object could be reinitialized (if it is possible) using the reset method. Finally, it could be destroyed using destroy method. Destroy method is needed to make feasible the destruction of a DataProducer without calling its destructor, forcing the object to send a 0 in the next get() call. */ class DataProducer : public Referenced { public: /// Returns a pointer and its property. A 0 inidicates data sequence ending. virtual Token *get() = 0; /// Reinitialize the sequence iterator if it is possible. virtual void reset() = 0; /// It destroys the object content and forces to return a 0 on next get(). virtual void destroy() { } }; /// A pure abstract class that serves as interface. /** A DataConsumer is an abstraction of an object which consumes a sequence of vectors of a given type, followed by a 0 indicating sequence ending. The object could be reinitialized (if it is possible) using the reset method. Finally, it could be destroyed using destroy method. Destroy method is needed to make feasible the destruction of a DataConsumer without calling its destructor, forcing the object to send a 0 in the next get() call. */ class DataConsumer : public Referenced { public: /// Receives a pointer and its property. It receive a 0 at sequence ending. virtual void put(Token *) = 0; /// Reinitialize the sequence iterator if it is possible. virtual void reset() = 0; /// It destroys the object content. virtual void destroy() { } }; /// A virtual class that serves as high level interface. /** A FunctionInterface is an abstraction of an object which represents a mathematical function. It adds to the interface abstract methods which calculates output vector given input vector, and a basic implementation of a method that consumes input vectors (from a DataProducer) and produces output vectros (to a DataConsumer). Every function is feeded with an input Token and produces an output Token. */ class FunctionInterface : public Referenced { public: FunctionInterface() : Referenced() { } virtual ~FunctionInterface() { } /// It returns the input (or domain) size of the function. virtual unsigned int getInputSize() const = 0; /// It returns the output (or range) size of the function. virtual unsigned int getOutputSize() const = 0; /// A new abstract method that computes output vector given input vector. virtual Token *calculate(const Token *input) = 0; /// Method for flow computation of outputs in a pipeline system. /** This method process a flow of data vectors, computed by a DataProducer, and produces an output vector for each of them. Output vectors are given to a DataConsumer. The end of the flow is indicated by DataProducer using a 0 pointer. Is mandatory to produces a 0 pointer to feed the DataConsumer when the flow ends. Input vector pointer is property of this method, needs to be freed. Output vector pointer is property of the DataConsumer object. */ virtual void calculateInPipeline(DataProducer *producer, DataConsumer *consumer) { Token *input; // we read from producer input until a 0 while( (input = producer->get()) != 0) { // we get the input increasing its reference counter IncRef(input); Token *output = calculate(input); // we get the output increasing its reference counter IncRef(output); consumer->put(output); // we lose input and output decreasing reference counters DecRef(output); DecRef(input); } // is mandatory to send this 0 to the consumer when the flow of data ends consumer->put(0); } }; } #endif //FUNCTION_INTERFACE_H april-ann-0.4.1/packages/functions/doc/000077500000000000000000000000001263004425400177305ustar00rootroot00000000000000april-ann-0.4.1/packages/functions/doc/function_interface.dox000066400000000000000000000000651263004425400243120ustar00rootroot00000000000000/** \page __global__ FunctionInterface */ april-ann-0.4.1/packages/functions/package.lua000066400000000000000000000021431263004425400212610ustar00rootroot00000000000000 package{ name = "functions", version = "1.0", depends = { "util", "tokens", "aprilio" }, keywords = { "Functions" }, description = "Define interfaces and methods for work with functions", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_function_interface.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_function_interface.lua.cc", dest_dir = "build", } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/hmm_trainer/000077500000000000000000000000001263004425400174605ustar00rootroot00000000000000april-ann-0.4.1/packages/hmm_trainer/binding/000077500000000000000000000000001263004425400210725ustar00rootroot00000000000000april-ann-0.4.1/packages/hmm_trainer/binding/bind_hmm_trainer.lua.cc000066400000000000000000000250641263004425400254710ustar00rootroot00000000000000//BIND_HEADER_H #include "utilLua.h" #include "hmm_trainer.h" #include "bind_matrix.h" using namespace HMMs; //BIND_END //BIND_HEADER_C using namespace AprilUtils; //BIND_END //BIND_LUACLASSNAME hmm_trainer hmm_trainer //BIND_CPP_CLASS hmm_trainer //BIND_LUACLASSNAME hmm_trainer_model hmm_trainer_model //BIND_CPP_CLASS hmm_trainer_model //BIND_CONSTRUCTOR hmm_trainer hmm_trainer { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(hmm_trainer, new hmm_trainer()); } //BIND_END //BIND_DESTRUCTOR hmm_trainer { } //BIND_END //BIND_METHOD hmm_trainer check_cls_emission { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, number); int emis; LUABIND_GET_PARAMETER(1, int, emis); obj->check_cls_emission(emis-1); // restamos 1 } //BIND_END //BIND_METHOD hmm_trainer new_cls_state { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(number, obj->new_cls_state()); } //BIND_END //BIND_METHOD hmm_trainer new_cls_transition { LUABIND_CHECK_ARGN(==,1); int cls_state; LUABIND_GET_PARAMETER(1, int, cls_state); LUABIND_RETURN(number, obj->new_cls_transition(cls_state)); } //BIND_END //BIND_METHOD hmm_trainer get_num_cls_emissions { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(number, obj->get_num_cls_emissions()); } //BIND_END //BIND_METHOD hmm_trainer set_a_priori_emissions { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, table); int len; float *vec; len = table_to_float_vector(L,&vec); if (obj->get_num_cls_emissions() == 0) obj->check_cls_emission(len-1); else if (len != obj->get_num_cls_emissions()) { lua_pushfstring(L,"hmm_trainer set_a_priori_emission " "method: incorrect number of a prioris: " "%d en lugar de %d", len, obj->get_num_cls_emissions()); lua_error(L); } for (int i=0; iset_apriori_cls_emission(i,log_float::from_float(vec[i])); delete[] vec; } //BIND_END //BIND_METHOD hmm_trainer get_a_priori_emissions { LUABIND_CHECK_ARGN(==,0); lua_newtable(L); int nclsemis = obj->get_num_cls_emissions(); for (int i=0; iget_apriori_cls_emission(i).to_float()); lua_rawseti(L,-2,i+1); } return 1; } //BIND_END //BIND_METHOD hmm_trainer get_transition_probability { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, number); int index; LUABIND_GET_PARAMETER(1, int, index); LUABIND_RETURN(number, obj->get_cls_transition_prob(index).to_float()); } //BIND_END //BIND_METHOD hmm_trainer get_transition_logprobability { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, number); int index; LUABIND_GET_PARAMETER(1, int, index); LUABIND_RETURN(number, obj->get_cls_transition_prob(index).log()); } //BIND_END //BIND_METHOD hmm_trainer print { LUABIND_CHECK_ARGN(==,0); obj->print(); } //BIND_END //BIND_CONSTRUCTOR hmm_trainer_model { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, hmm_trainer); hmm_trainer *the_trainer = lua_tohmm_trainer(L,1); LUABIND_RETURN(hmm_trainer_model, new hmm_trainer_model(the_trainer)); } //BIND_END //BIND_DESTRUCTOR hmm_trainer_model { } //BIND_END //BIND_METHOD hmm_trainer_model print { LUABIND_CHECK_ARGN(==,0); obj->print(); } //BIND_END //BIND_METHOD hmm_trainer_model print_dot { LUABIND_CHECK_ARGN(==,0); obj->print_dot(); } //BIND_END //BIND_METHOD hmm_trainer begin_expectation { LUABIND_CHECK_ARGN(==,0); obj->begin_expectation(); } //BIND_END //BIND_METHOD hmm_trainer end_expectation { bool update_trans_prob=true; bool update_a_priori_emission=true; int argn = lua_gettop(L); // number of arguments if (argn == 1 && lua_istable(L,1)) { lua_pushstring(L, "update_trans_prob"); lua_gettable(L, 1); if (lua_isboolean(L, -1)) update_trans_prob = (bool)lua_toboolean(L, -1); lua_pop(L,1); // lua_pushstring(L, "update_a_priori_emission"); lua_gettable(L, 1); if (lua_isboolean(L, -1)) update_a_priori_emission = (bool)lua_toboolean(L, -1); lua_pop(L,1); } // obj->end_expectation(update_trans_prob,update_a_priori_emission); } //BIND_END //BIND_METHOD hmm_trainer_model new_state { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(number, obj->new_state()); } //BIND_END //BIND_METHOD hmm_trainer_model set_initial_state { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, number); int st; LUABIND_GET_PARAMETER(1, int, st); obj->set_initial_state(st); } //BIND_END //BIND_METHOD hmm_trainer_model set_final_state { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, number); int st; LUABIND_GET_PARAMETER(1, int, st); obj->set_final_state(st); } //BIND_END //BIND_METHOD hmm_trainer_model new_transition { LUABIND_CHECK_ARGN(>=,5); LUABIND_CHECK_ARGN(<=,6); LUABIND_CHECK_PARAMETER(1, number); LUABIND_CHECK_PARAMETER(2, number); LUABIND_CHECK_PARAMETER(3, number); LUABIND_CHECK_PARAMETER(4, number); LUABIND_CHECK_PARAMETER(5, number); int from, to, emission, cls_trns; LUABIND_GET_PARAMETER(1, int, from); LUABIND_GET_PARAMETER(2, int, to); LUABIND_GET_PARAMETER(3, int, emission); emission -= 1; // OJO QUE RESTAMOS 1 LUABIND_GET_PARAMETER(4, int, cls_trns); log_float prb= log_float(lua_tonumber(L,5)); // Va en base logarítmica const char *output = 0; if (lua_isstring(L,6)) { output = lua_tostring(L,6); } obj->new_transition(from,to,emission,cls_trns,prb,output); } //BIND_END //BIND_METHOD hmm_trainer_model prepare_model { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(bool, obj->prepare_model()); } //BIND_END //BIND_METHOD hmm_trainer_model get_num_states_transitions { LUABIND_CHECK_ARGN(==,0); int states,transitions; obj->get_information(states,transitions); LUABIND_RETURN(int, states); LUABIND_RETURN(int, transitions); } //BIND_END //BIND_METHOD hmm_trainer_model viterbi { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "input_emission", "output_emission_seq", "output_emission", "state_probabilities", "do_expectation", "emission_in_log_base", "count_value", (const char *)0); // MatrixFloat *input_matemi, *output_matemi_seq, *output_matemi; MatrixFloat *state_probabilities; bool do_expectation, emission_in_log_base; LUABIND_GET_TABLE_PARAMETER(1, input_emission, MatrixFloat, input_matemi); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, output_emission_seq, MatrixFloat, output_matemi_seq, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, output_emission, MatrixFloat, output_matemi, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, state_probabilities, MatrixFloat, state_probabilities, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, do_expectation, bool, do_expectation, false); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, emission_in_log_base, bool, emission_in_log_base, false); // Modificar el valor a sumar en cada cuenta, de esa forma se pueden // ponderar las cuentas de diferentes frases dando mas pesos a unas // que a otras float count_value; LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, count_value, float, count_value, 1.0f); // char *output; log_float resul = obj->viterbi(input_matemi, emission_in_log_base, do_expectation, output_matemi, output_matemi_seq, state_probabilities, &output, count_value); LUABIND_RETURN(float, resul.log()); // devuelve log(probabilidad) LUABIND_RETURN(string, output); delete[] output; } //BIND_END //BIND_METHOD hmm_trainer_model forward_backward { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, table); // lua_pushstring(L, "input_emission"); lua_gettable(L,1); if (lua_isnil(L,-1)) { lua_pushstring(L,"hmm_trainer_model: input_emission not found"); lua_error(L); } MatrixFloat* input_matemi = lua_toMatrixFloat(L,-1); // por defecto utiliza la misma matriz para dejar el resultado: MatrixFloat* output_matemi = input_matemi; lua_pop(L,1); if (input_matemi->getNumDim() != 2) { lua_pushstring(L,"hmm_trainer model forward_backward method: " "emission matrix must have dim 2"); lua_error(L); } // lua_pushstring(L, "output_emission"); lua_gettable(L,1); if (!lua_isnil(L,-1)) { output_matemi = lua_toMatrixFloat(L,-1); // TODO: comprobar matriz es ok } lua_pop(L,1); // por defecto hace do_expectation: bool do_expectation = true; lua_pushstring(L, "do_expectation"); lua_gettable(L,1); if (!lua_isnil(L,-1)) { do_expectation = lua_toboolean(L,-1); } lua_pop(L,1); // obj->forward_backward(input_matemi,output_matemi,do_expectation); } //BIND_END //BIND_CLASS_METHOD hmm_trainer to_log { LUABIND_CHECK_ARGN(>=,1); int argn = lua_gettop(L); // number of arguments if (lua_isMatrixFloat(L,1)) { MatrixFloat* mat = lua_toMatrixFloat(L,1); log_float *aux = new log_float(mat->getDimSize(1)); if (argn > 1) { for (int i=0;igetDimSize(1);i++) { lua_rawgeti(L, 2, i+1); float f = lua_tonumber(L,-1); lua_pop(L,1); aux[i] = log_float::from_float(f); // TODO: revisar este codigo // antes ponia: aux[i] = log_float::from_float(aux[i]); } } else { for (int i=0;igetDimSize(1);i++) { aux[i] = log_float::one(); } } MatrixFloat::iterator mat_it(mat->begin()); for (int i=0;igetDimSize(0);i++) { for (int j=0;jgetDimSize(1);j++,++mat_it) *mat_it = (log_float::from_float(*mat_it) / aux[j]).log(); } } if (lua_isnumber(L,1)) { float num = lua_tonumber(L,1); lua_pushnumber(L,log_float::from_float(num).log()); return 1; } } //BIND_END //BIND_CLASS_METHOD hmm_trainer from_log { LUABIND_CHECK_ARGN(==,1); if (lua_isMatrixFloat(L,1)) { MatrixFloat* mat = lua_toMatrixFloat(L,1); for (MatrixFloat::iterator mat_it(mat->begin()); mat_it!=mat->end(); ++mat_it) *mat_it = log_float(*mat_it).to_float(); } if (lua_isnumber(L,1)) { float num = lua_tonumber(L,1); lua_pushnumber(L,log_float(num).to_float()); return 1; } } //BIND_END //BIND_FUNCTION HMMTrainer.utils.initial_emission_alignment { LUABIND_CHECK_ARGN(==,2); int npat; LUABIND_GET_PARAMETER(2, int, npat); lua_pop(L,1); int *seq_emission; int nsts = table_to_int_vector(L,&seq_emission); // creamos una matriz de dim 1 con npat valores: MatrixFloat* mat = new MatrixFloat(1, &npat); // repartimos los npat valores en nsts posiciones int cociente = npat/nsts; int resto = npat%nsts; int i,r,v; float s; for (i=0,r=0; i < nsts; i++) { v = cociente; if (resto>0) { v++; resto--; } s = seq_emission[i]; for (;v>0;v--) { (*mat)(r) = s; r++; } } delete[] seq_emission; LUABIND_RETURN(MatrixFloat, mat); } //BIND_END april-ann-0.4.1/packages/hmm_trainer/c_src/000077500000000000000000000000001263004425400205515ustar00rootroot00000000000000april-ann-0.4.1/packages/hmm_trainer/c_src/hmm_trainer.cc000066400000000000000000001033701263004425400233710ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "error_print.h" #include "hmm_trainer.h" #include #include #include // para exit #include #include "april_assert.h" using namespace AprilUtils; using namespace Basics; namespace HMMs { hmm_trainer::hmm_trainer() { num_cls_states = 0; num_cls_transitions = 0; num_cls_emissions = 0; vsz_cls_states = 4; vsz_cls_transitions = 4; vsz_cls_emissions = 4; cls_transition = new hmm_trainer_cls_transition[vsz_cls_transitions]; cls_state = new hmm_trainer_cls_state[vsz_cls_states]; apriori_cls_emission = new log_float[vsz_cls_emissions]; acum_cls_emission = new log_double[vsz_cls_emissions]; // inicializar aprioris, como si no hubiese el calculo de aprioris: for (int i=0; i= vsz_cls_states) { while (st >= vsz_cls_states) vsz_cls_states *= 2; hmm_trainer_cls_state *old_cls_state = cls_state; cls_state = new hmm_trainer_cls_state[vsz_cls_states]; for (int i=0; i= num_cls_states) num_cls_states = st+1; } int hmm_trainer::new_cls_state() { int aux = num_cls_states; check_cls_state(aux); cls_state[aux].cls_tr_list = -1; // lista vacia return aux; } void hmm_trainer::check_cls_transition(int tr) { if (tr >= vsz_cls_transitions) { while (tr >= vsz_cls_transitions) vsz_cls_transitions *= 2; hmm_trainer_cls_transition *old_cls_transition = cls_transition; cls_transition = new hmm_trainer_cls_transition[vsz_cls_transitions]; for (int i=0; i= num_cls_transitions) num_cls_transitions = tr+1; } int hmm_trainer::new_cls_transition(int c_st) { int aux = num_cls_transitions; check_cls_transition(aux); cls_transition[aux].prob = log_float::zero(); cls_transition[aux].emission = 0; // cualquier valor >=0 if (c_st == -1) cls_transition[aux].next = -1; else { cls_transition[aux].next = cls_state[c_st].cls_tr_list; cls_state[c_st].cls_tr_list = aux; } return aux; } void hmm_trainer::check_cls_emission(int emis) { if (emis >= vsz_cls_emissions) { while (emis >= vsz_cls_emissions) vsz_cls_emissions *= 2; delete[] apriori_cls_emission; delete[] acum_cls_emission; apriori_cls_emission = new log_float[vsz_cls_emissions]; acum_cls_emission = new log_double[vsz_cls_emissions]; // inicializar aprioris, como si no hubiese el cálculo de // aprioris: for (int i=0; i= num_cls_emissions) { for (int i=num_cls_emissions; i<=emis; i++) apriori_cls_emission[i] = log_float::one(); num_cls_emissions = emis+1; } } void hmm_trainer::begin_expectation() { for (int i=0;i %f = %f/%f\n", rt, cls_transition[rt].prob.to_double(), (cls_transition[rt].acum / sumatotal).to_double(), cls_transition[rt].acum.log(), sumatotal.log()); auxprob = cls_transition[rt].acum / sumatotal; if (auxprob < minprob) minprob = auxprob; } } } if (minprob > log_float::zero()) { #endif // recalcular las probabilidades de las transiciones for (int i=0;i %f = exp(%f)/exp(%f)\n", // rt, cls_transition[rt].prob.to_float(), // (cls_transition[rt].acum / sumatotal).to_float(), // cls_transition[rt].acum.log(), sumatotal.log()); cls_transition[rt].prob = cls_transition[rt].acum / sumatotal; } } } #ifdef CHECK_HMMTRAINER_TRANS_PROB_DIFERENT_ZERO } // if minprob > 0.0 #endif } // if update... if (update_a_priori_emission) { // recalcular las probabilidades a priori de los tipos de emisión maxpracum = acum_cls_emission[0]; for (int i=1;i %f = exp(%f)/exp(%f)\n", // i, apriori_cls_emission[i].to_float(), // (acum_cls_emission[i] / sumatotal).to_float(), // acum_cls_emission[i].log(),sumatotal.log()); apriori_cls_emission[i] = acum_cls_emission[i] / sumatotal; // PARCHE FEO HEURISTICO: <- IMPORTANTE if (apriori_cls_emission[i] <= log_float::from_float(1e-20)) apriori_cls_emission[i] = log_float::from_float(1e20); } } } void hmm_trainer::print() const { } hmm_trainer_model::hmm_trainer_model(hmm_trainer *the_trainer) { created = false; num_states = 0; num_transitions = 0; initial_state =-1; final_state =-1; list_transitions= 0; transition = 0; //ranking = 0; trainer = the_trainer; IncRef(trainer); } int hmm_trainer_model::new_state() { int aux = num_states; num_states++; return aux; } void hmm_trainer_model::new_transition(int from, int to, int emission, int cls_transition, log_float prob, const char *output) { num_transitions++; hmm_aux_transition *aux = new hmm_aux_transition; aux->from = from; aux->to = to; aux->emission = emission; trainer->check_cls_emission(emission); aux->id = cls_transition; aux->prob = prob; aux->next = list_transitions; list_transitions = aux; if (output == 0) aux->output = 0; else { aux->output = new char[strlen(output)+1]; strcpy(aux->output,output); } } // clase auxiliar para calcular el orden topologico: struct list_top_order { int state; list_top_order *next; list_top_order(int st, list_top_order *nxt) : state(st), next(nxt) {} }; bool hmm_trainer_model::prepare_model() { // llamarlo una vez introducido todo if (num_transitions <= 0 || initial_state < 0 || final_state < 0) { ERROR_PRINT3("prepare_model(): num_transitions(%d) <= 0 || " "initial_state(%d) < 0 || final_state(%d) < 0\n", num_transitions, initial_state, final_state); return false; } // calcular orden de los estados que induce un orden sobre las // transiciones para que las de tipo lambda funcionen correctamente: transition = new hmm_trainer_transition[num_transitions]; // lista para guardar, para cada estado, las transiciones // que salen de ese estado: hmm_aux_transition **salen_de = new hmm_aux_transition*[num_states]; // numlambdas cuenta num tr. lambda q llegan a cada estado int *numlambdas = new int[num_states]; // ranking cuenta el camino de lambdas más largo que llega a cada // estado: // ranking = new int[num_states]; // first_transition= new int[num_states+1]; for (int i=0;inext; aux->next = salen_de[aux->from]; salen_de[aux->from] = aux; if (aux->emission < 0) { // y si es de tipo lambda numlambdas[aux->to]++; } } // generamos una lista con los estados con 0 transiciones lambda en // su entrada: list_top_order *listop = 0; for (int i=0;inext; int st = a->state; delete a; // procesar todas las transiciones que salen de st while (salen_de[st] != 0) { int emis = salen_de[st]->emission; int dest = salen_de[st]->to; transition[itr].from = salen_de[st]->from; transition[itr].to = dest; transition[itr].output= salen_de[st]->output; transition[itr].cls_transition = salen_de[st]->id; trainer->set_cls_transition_emission(salen_de[st]->id,emis); trainer->set_cls_transition_prob(salen_de[st]->id,salen_de[st]->prob); itr++; if (emis < 0) { // si es transicion lambda: // if (ranking[dest] < ranking[st]+1) // actualizar ranking // ranking[dest] = ranking[st]+1; // estado destino numlambdas[dest]--; // meterlo en lista para orden topologico if (numlambdas[dest] == 0) // si hace falta listop = new list_top_order(dest,listop); } // eliminar la transicion de la lista: hmm_aux_transition* aux = salen_de[st]; salen_de[st] = salen_de[st]->next; delete aux; } } // while (listop != 0); delete[] salen_de; delete[] numlambdas; // comprobar que el grafo no tenia ciclos de tr. lambda itr deberia // valer num_transitions if (itr != num_transitions) { delete[] transition; transition=0; // delete[] ranking; ranking=0; //delete[] first_transition; first_transition=0; ERROR_PRINT2("prepare_model(): error, itr(%d) != num_transitions(%d)\n", itr, num_transitions); return false; } created = true; return true; } hmm_trainer_model::~hmm_trainer_model() { DecRef(trainer); if (transition != 0) { for (int i=0; iget_cls_transition_prob(i); } inline int hmm_trainer_model::transition_emission(int tr) { int i = transition[tr].cls_transition; return trainer->get_cls_transition_emission(i); } void hmm_trainer_model::print() const { printf("num_states = %d\nnum_transitions = %d\n", num_states,num_transitions); printf("initial_state = %d\nfinal_state = %d\n", initial_state,final_state); if (created) { printf("hmm_trainer_model closed\n"); printf("Transition vector:\n"); for (int i=0;i cls_tr %3d, " "from %3d to %3d output \"%s\"\n", i,clst, transition[i].from, transition[i].to, ((transition[i].output==0) ? "" : transition[i].output)); printf(" cls_tr %3d emission %d prob %f\n", clst, trainer->get_cls_transition_emission(clst), trainer->get_cls_transition_prob(clst).to_float()); } } else { printf("hmm_trainer_model to be closed\n"); printf("List of transitions before closing the model:\n"); for (const hmm_aux_transition *r = list_transitions; r != 0; r = r->next) printf("from %3d to %3d with emission %3d and" " id %3d, output=\"%s\"\n", r->from,r->to,r->emission,r->id, ((r->output==0) ? "" : r->output)); } } void hmm_trainer_model::print_dot() const { if (created) { printf("digraph automata {\n"); for (int i=0;i %3d [label=\"<%d> %d/%f/%s\"];\n", transition[i].from, transition[i].to, clst, trainer->get_cls_transition_emission(clst), trainer->get_cls_transition_prob(clst).to_float(), ((transition[i].output==0) ? "" : transition[i].output)); } printf("}\n"); } } // clase auxiliar para imprimir la salida struct list_output { char *output; list_output *next; }; log_float hmm_trainer_model::viterbi(const MatrixFloat *emission, bool emission_in_log_base, bool do_expectation, MatrixFloat *reest_emission, MatrixFloat *seq_reest_emission, MatrixFloat *state_probabilities, char **output_str, float count_value) { log_float logf_count_value = log_float::from_float(count_value); log_double logd_count_value = log_double::from_double((double)count_value); // int length_sequence = emission->getDimSize(0); int sz_emission_frame= emission->getDimSize(1); int sizepath = (length_sequence+1)*num_states; int *path = new int[sizepath]; for (int i=0; iapriori_cls_emission; float *femission; // una fila matriz emission int *fpath; // recorre fila sq matriz path int sq; // recorre secuencia int tr; // recorre transiciones int st; // recorre estados // inicializar probnow a las probabilidades etapa actual, pero lo // ponemos en la siguiente pq se intercambian los vectores: for (st=0; stbegin()); // bucle ppal: for (sq=0,fpath=path+num_states; sq probnxt log_float *swap = probnow; probnow = probnxt; probnxt = swap; // inicializar vectores probnxt for (st=0; st= 0) { // transicion no lambda nscr *= vemission[emis]; if (nscr > probnxt[dest]) { // maximizar prob probnxt[dest] = nscr; fpath[dest] = tr; } } else { // transicion lambda if (nscr > probnow[dest]) { // maximizar prob probnow[dest] = nscr; // restamos num_states pq es fila anterior fpath[dest-num_states] = tr; } } } // end for tr recorre transiciones } // end for sq recorre secuencia // transiciones lambda ultima iteracion: for (tr=0; tr probnxt[dest]) { // maximizar prob probnxt[dest] = nscr; // restamos num_states pq es fila anterior fpath[dest-num_states] = tr; } } } // end for tr recorre transiciones // para recuperar la cadena de salida: int outputsz = 0; // longitud de la salida int theoutputlistsize = 0; list_output *theoutputlist = 0; // devolver las probabilidades de cada estado al finalizar if (state_probabilities) { april_assert(state_probabilities->getNumDim() == 1 && state_probabilities->getDimSize(0) == num_states); MatrixFloat::iterator st_prob_it(state_probabilities->begin()); for (int i=0;i= 0) { if (do_expectation) { // acumular valores para algoritmo EM int clstr = transition[tr].cls_transition; trainer->acum_tran_prob(clstr, logf_count_value); } int emis = transition_emission(tr); if (emis >= 0) { // acumular para calcular prob. a priori de las emisiones if (do_expectation) trainer->acum_cls_emission[emis] += logd_count_value; // guardar la emision: if (seq_reest_emission) (*seq_reest_emission)(sq) = emis+1; if (reest_emission) (*reest_emission)(sq,emis) = 1.0f; } // salida: if (transition[tr].output != 0) { list_output *aux = new list_output; aux->output = transition[tr].output; aux->next = theoutputlist; theoutputlist = aux; theoutputlistsize++; outputsz += strlen(transition[tr].output); } // pasar al estado anterior: if (emis >= 0) { sq--; fpath-=num_states; } st = transition[tr].from; tr = fpath[st]; } // while (tr >= 0); // generar cadena de salida: if (theoutputlistsize > 0) outputsz += theoutputlistsize-1; outputsz++; // para el '\0' char *outputstr = new char[outputsz]; char *r = outputstr; while (theoutputlist) { list_output *aux = theoutputlist; theoutputlist = theoutputlist->next; strcpy(r,aux->output); r += strlen(aux->output); if (theoutputlist) { *r = ' '; r++; } delete aux; } *r = '\0'; *output_str = outputstr; // liberar recursos delete[] path; delete[] probnow; delete[] probnxt; delete[] vemission; // devolver maxprob return output_prob; } // end viterbi method void hmm_trainer_model::forward(MatrixFloat *emission, log_float *alpha) { // alpha es una matriz de tamanyo: length_sequence+1 filas por // num_states columnas creada en el metodo forward_backward donde // guardamos probabilidades denominadas usualmente "alpha" en la // literatura, se guardan en formato log_float. Asumimos que esta // matriz ha sido inicializada a valor log_float::zero() int length_sequence = emission->getDimSize(0); int sz_emission_frame= emission->getDimSize(1); log_float *vemission = new log_float[sz_emission_frame]; const log_float *apriori = trainer->apriori_cls_emission; float *femission; // recorre fila matriz emission int sq; // recorre secuencia int tr; // recorre transiciones // probnow recorre desde la fila 0 de la matriz alpha hasta la fila // length_sequence-1 que es la penúltima. // probnxt recorre desde la fila 1 (la segunda) de la matriz alpha // hasta la ultima fila que es length_sequence log_float *probnow = alpha; log_float *probnxt = 0; // fila siguiente: probnow + num_states; // alpha esta inicializada a log_float::zero(), falta este caso // inicial: probnow[initial_state] = log_float::one(); // bucle ppal for (sq=0, femission=emission->getRawDataAccess()->getPPALForReadAndWrite(); sq= 0) // transicion no lambda probnxt[dest] += nscr*vemission[emis]; else // transicion lambda probnow[dest] += nscr; } } // end for sq recorre secuencia // caso especial: tratar las transiciones lambda de la ultima // iteracion, ultima fila de la matriz (apuntada por probnxt) for (tr=0; trgetDimSize(0); int sz_emission_frame = input_emission->getDimSize(1); const log_float *apriori= trainer->apriori_cls_emission; // femission recorre filas de la matriz emission desde la ultima // hasta la primera: float *femission= input_emission->getRawDataAccess()->getPPALForReadAndWrite()+(length_sequence-1)*sz_emission_frame; float *desired_emission = output_emission->getRawDataAccess()->getPPALForReadAndWrite()+(length_sequence-1)*sz_emission_frame; // recorre la matriz alpha desde la PENULTIMA fila, que corresponde // a haber consumido todas las tramas menos una: log_float *f_alpha = alpha+(length_sequence-1)*num_states; int sq; // recorre secuencia int tr; // recorre transiciones int st; // recorre estados // a diferencia del metodo forward, probnow y probprv son dos // vectores que vamos intercambiando, se llama probprv porque vamos // hacia atrás: log_float *probnow = new log_float[num_states]; log_float *probprv = new log_float[num_states]; // para calcular la salida deseada, que luego se copiara a emission: log_float *desired = new log_float[sz_emission_frame]; // para pasar emission a base logaritmica y dividir por a priories: log_float *vemission= new log_float[sz_emission_frame]; // inicializar probprv (que luego sera probnow por el swap) // en Jelinek paso 2 pagina 32 dice inicializar todo a uno :| for (st=0; st probnow log_float *swap = probnow; probnow = probprv; probprv = swap; // inicializar vector probprv for (st=0; st=0; tr--) { int orig = transition[tr].to; // puesto deliberadamente al reves int dest = transition[tr].from; // puesto deliberadamente al reves int emis = transition_emission(tr); log_float nscr = probnow[orig] * transition_prob(tr); if (emis >= 0) // transicion no lambda probprv[dest] += nscr*vemission[emis]; else // transicion lambda probnow[dest] += nscr; } // end for tr recorre transiciones // ahora tenemos en provprv el de la iteracion siguiente a falta // de las transiciones lambda, y de regalo tenemos el de la actual // YA con sus transiciones lambda: // inicializar vector desired: for (int i=0; i= 0) { // no es transicion lambda pstar = f_alpha[orig] * transition_prob(tr) * probnow[dest] * vemission[emis]; desired[emis] += pstar; // salida deseada para entrenar posterioris trainer->acum_tran_prob(clstr, pstar); // prob. transicion } else { // transicion lambda utiliza alpha de la fila siguiente: pstar = f_alpha[num_states+orig] * transition_prob(tr) * probnow[dest]; trainer->acum_tran_prob(clstr, pstar); // prob. transicion } } // for q recorre transiciones else // solamente el calculo de la salida deseada for (tr=0; tr= 0) { // no es transicion lambda pstar = f_alpha[orig] * transition_prob(tr) * probnow[dest] * vemission[emis]; desired[emis] += pstar; // salida deseada para entrenar posterioris } } // for q recorre transiciones // ya podemos reescribir la fila con la salida deseada: log_float acum= desired[0]; for (int i=1; iacum_apriori_cls_emission(i,aux); desired_emission[i] = aux.to_float(); } // pasamos a la fila de emision anterior: femission -= sz_emission_frame; desired_emission -= sz_emission_frame; f_alpha -= num_states; } // end for sq que cuenta la secuencia if (do_expectation) { // caso especial que se hace aparte: calculamos beta en la columna // inicial del trellis, correspondiente a no haber consumido ninguna // trama, que se utiliza para estimar las probabilidades de // transitar en las transiciones lambda en el instante inicial: // recorrer transiciones AL REVES por lo del orden topologico para // tratar bien las transiciones lambda: for (tr=num_transitions-1; tr>=0; tr--) { int orig = transition[tr].to; // puesto deliberadamente al reves int dest = transition[tr].from; // puesto deliberadamente al reves int emis = transition_emission(tr); if (emis < 0) // transicion lambda probprv[dest] += probprv[orig] * transition_prob(tr); } // end for tr recorre transiciones // utilizar f_alpha y probprv para actualizar la información en la // matriz de emision utilizando P^*{t^i=t} (capitulo 2 Jelinek 1997) f_alpha += num_states; // deshacer for (tr=0; tracum_tran_prob(clstr, pstar); // prob. transicion } } // for q recorre transiciones } delete[] probnow; delete[] probprv; delete[] vemission; delete[] desired; } // end method void hmm_trainer_model::forward_backward(MatrixFloat *input_emission, MatrixFloat *output_emission, bool do_expectation) { int length_sequence = input_emission->getDimSize(0); // todo: comprobar que output_emission tiene las mismas dim. int alpha_size = (length_sequence+1)*num_states; log_float *alpha = new log_float[alpha_size]; for (int i=0; i0 para todos los estados, necesariamente el grafo es cclico y debemos reportar el error. Iteramos: - Sacar un estado cuya cuenta sea 0, le asignamos un valor en el orden topolgico. - Recorremos las transiciones que salen de ese estado y restamos uno a la cuenta de los estados destino. Si alguno de esos estados decrementa su cuenta a 0, lo metemos en la lista. Una vez ordenados los estados, ordenamos las transiciones: Recorremos los estados en el orden establecido. Para cada estado, metemos: - Primero las transiciones no lambda que LLEGAN a ese estado. ---------------------------------------------------------------------- Algoritmo para el constructor: - Recibimos bsicamente lo que recibe el constructor lua. - Debemos repartir las transiciones de la manera siguiente: * Transiciones con origen 0 deben ser lambda y sirven para acumular la probabilidad inicial. * Transiciones con destino -1 deben ser lambda y especifican la probabilidad de ser un estado final. * Las otras transiciones se guardan en una lista asociada al estado origen. Cada estado tiene 2 listas, una para las transiciones lambda y otra para el resto. - Deberamos comprobar que las transiciones tengan un estado origen del mismo tipo que el especificado en la clase de transicin, que la suma de probabilidades que salen de cada estado vale 1. - Por otra parte, en la construccin del hmm_trainer, no tiene por qu cumplirse que la suma de probabilidades que salen de cada estado sea 1, puesto que podran estar ligadas varias transiciones que salen de un mismo estado. Pero s que tendramos que comprobar que cada estado de un tipo usa todas las transiciones y el mismo nmero de veces >=1. - Hemos eliminado las transiciones con origen == 0 y las que tienen destino ==-1. El resto las hemos metido en sendas listas por cada estado. Le toca el turno al algoritmo que obtiene el orden topolgico y reordena las transiciones. That's all folks! ---------------------------------------------------------------------- april-ann-0.4.1/packages/hmm_trainer/lua_src/000077500000000000000000000000001263004425400211105ustar00rootroot00000000000000april-ann-0.4.1/packages/hmm_trainer/lua_src/hmm_trainer.lua000066400000000000000000000760261263004425400241330ustar00rootroot00000000000000-- modelo = {name="nombre", -- transitions={ -- {from="...", to="....", prob=... , id="....", emission="...",output="..."} -- ... -- } -- initial="...", -- final="..." -- } -- Namespace HMMTrainer -- Clase HMMTrainer.trainer -- metodos: -- constructor -> crea un trainer vacio -- model -> toma una descripcion de un modelo como la de la -- tabla de arriba y devuelve un objeto Lua de tipo -- HMMTrainer.model, que ademas incorpora al diccionario -- self.models -- -- add_to_dict -> para añadir un model al diccionario, estos modelos -- se utilizan para expandir otros modelos -- -- get_cls_transition_prob -> devuelve la probabilidad de transitar -- de una clase de transicion -- -- expand -> utilizado en model:generate_C_model() para expandir -- recursivamente un modelo -- -- Clase HMMTrainer.model -- metodos: -- generate_C_model -> crea un objeto C++ de tipo hmm_trainer_model -- con los datos contenidos en el modelo Lua, realizando -- expansión recursiva de las transiciones segun sea -- necesario -- Namespace utils -- funciones: -- generate_hmm3st_desc -> crea descripcion de modelo lineal de 3 estados -- str2model_desc -> crea una descripcion de modelo a partir de una palabra local trainer, trainer_methods = class("HMMTrainer.trainer") HMMTrainer = HMMTrainer or {} -- global environment HMMTrainer.trainer = trainer -- global environment function trainer:constructor() self.trainer = hmm_trainer() -- Objeto trainer en C -- tabla cadena_id --> par (cls_state, cls_transition) indices -- en el vector del hmm_trainer C++ self.linked_ids = {} -- tabla nombre_modelo --> modelo lua -- TODO: Cuando se meten cosas aqui? self.models = {} end local model,model_methods = class("HMMTrainer.model") HMMTrainer.model = model function trainer_methods:model(m) -- Creamos una tabla lua con las transiciones de m, -- sustituyendo los nombres de los estados en .from y .to -- por numeros -- Asignamos el numero 1 al inicial y el 2 al final local state_numbers = {} state_numbers[m.initial] = 1 state_numbers[m.final] = 2 if m.initial == m.final then error("El estado inicial y el final no pueden coincidir: ".. m.name) end local num = 3 local newtrans = {} for i, t in ipairs(m.transitions) do if not(state_numbers[t.from]) then state_numbers[t.from] = num num = num+1 end if not(state_numbers[t.to]) then state_numbers[t.to] = num num = num+1 end newtrans[i] = { from = state_numbers[t.from], to = state_numbers[t.to], emission = t.emission, lprob = t.lprob or math.log(t.prob), id = t.id, output = t.output, } end -- Creamos un modelo lua con las transiciones renumeradas local res = HMMTrainer.model() res.name = m.name res.initial = state_numbers[m.initial] res.final = state_numbers[m.final] res.transitions = newtrans res.trainer = self res.num_states = num-1 return res end function model_methods:update_probs() for i,t in ipairs(self.transitions) do t.lprob = self.trainer:get_cls_transition_logprob(t.id) end end function HMMTrainer.model.from_table(t) local res = HMMTrainer.model() for k,v in pairs(t) do res[k] = v end return res end function model_methods:to_string() local str = {} table.insert(str, "{\n") table.insert(str, "\tname = '".. string.gsub(self.name,"'","\\'") .. "',") table.insert(str, "\tinitial = " .. self.initial .. ",") table.insert(str, "\tfinal = " .. self.final .. ",") table.insert(str, "\tnum_states = " .. self.num_states .. ",") table.insert(str, "\ttransitions = {") for i,t in ipairs(self.transitions) do table.insert(str,"\t\t{") table.insert(str, "\t\t\tfrom = " .. t.from ..",") table.insert(str, "\t\t\tto = " .. t.to ..",") table.insert(str, "\t\t\temission = " .. t.emission ..",") table.insert(str, "\t\t\tlprob = " .. t.lprob ..",") if t.id then table.insert(str, "\t\t\tid = '" .. string.gsub(t.id,"'","\\'") .."',") end if t.output then table.insert(str, "\t\t\toutput = '" .. string.gsub(t.output,"'","\\'").."'") end table.insert(str,"\t\t},") end table.insert(str, "\t}") table.insert(str, "}") return table.concat(str, "\n") end -- Ejemplo de un automata en SLF: -- # Define size of network: N=num nodes and L=num arcs -- N=6 L=7 -- # List nodes: I=node-number, W=word -- I=0 W=start -- I=1 W=end -- I=2 W=bit -- I=3 W=but -- I=4 W=!NULL -- I=5 W=!NULL -- # List arcs: J=arc-number, S=start-node, E=end-node -- # l=x is used to attach log transition probability -- J=0 S=0 E=4 l=-1.1 -- J=1 S=4 E=2 -- J=2 S=4 E=3 -- J=3 S=2 E=5 -- J=4 S=3 E=5 -- J=5 S=5 E=4 -- J=6 S=5 E=1 function model_methods:to_slf() local next_state = 1 local next_transition = 1 local str = {} local id2state = {} local state2id = {} for i,t in ipairs(self.transitions) do local from local to if state2id[t.from] then from = state2id[t.from] else from = next_state state2id[t.from] = next_state next_state = next_state + 1 end if state2id[t.to] then to = state2id[t.to] else to = next_state state2id[t.to] = next_state next_state = next_state + 1 end if t.emission == 0 then -- transicion LAMBDA table.insert(str, "J=" .. next_transition .. " S=" .. from .. " E=".. to .. " l=".. t.lprob) id2state[from] = t.from id2state[to] = t.to next_transition = next_transition+1 else table.insert(str, "J=" .. next_transition .. " S=" .. from .. " E=" .. next_state .. " l=" .. t.lprob) table.insert(str, "J=" .. next_transition+1 .. " S=" .. next_state .. " E=" .. to) id2state[from] = t.from id2state[next_state] = t.emission id2state[to] = t.to next_state = next_state+1 next_transition = next_transition+2 end end local first_state = state2id[self.initial] local last_state = state2id[self.final] local str2 = {} table.insert(str2, "VERSION=1.0") table.insert(str2, "N=".. (next_state+1) .. " L=".. (next_transition+1)) table.insert(str2,"I=0 W=!NULL") -- FIRST STATE DUMMY for i=1,next_state-1 do if type(id2state[i])=='string' then table.insert(str2,"I=".. i .." W=".. id2state[i]) else table.insert(str2,"I=".. i .." W=!NULL") end end table.insert(str2,"I=".. next_state .." W=!NULL") -- LAST STATE DUMMY table.insert(str2, "J=0 S=0 E=".. first_state .." l=0") -- TRANSITION TO FIRST STATE FROM DUMMY table.insert(str, "J=".. next_transition .. " S="..last_state .. " E=".. next_state .." l=0") -- TRANSITION TO LAST STATE FROM DUMMY return table.concat(str2, "\n").."\n"..table.concat(str, "\n").."\n" end function trainer_methods:add_to_dict(m, name) if name==nil then name = m.name end self.models[name] = m end function trainer_methods:get_cls_transition_prob(tr_id) if self.linked_ids[tr_id] then local index = self.linked_ids[tr_id][2] -- cls_t return self.trainer:get_transition_probability(index) else -- FIXME: ATENCION este if puede causar que algunos bugs no se -- puedan encontrar... por eso la razon del print de abajo ;) -- print ("EOEO, esto es para debug... estamos solicitando informacion".. -- " de una transicion que no existe en el modelo") return 0.0 end end function trainer_methods:get_cls_transition_logprob(tr_id) if self.linked_ids[tr_id] then local index = self.linked_ids[tr_id][2] -- cls_t return self.trainer:get_transition_logprobability(index) else -- FIXME: ATENCION este if puede causar que algunos bugs no se -- puedan encontrar... por eso la razon del print de abajo ;) -- print ("EOEO, esto es para debug... estamos solicitando informacion".. -- " de una transicion que no existe en el modelo") return 0.0 end end -- Expande recursivamente el modelo C referenciado por c_obj -- utilizando el modelo lua m function trainer_methods:expand(m, c_obj, upper_prob, ini, fin, cls_ini, cls_fin, upper_output) local indices={ [m.initial]=ini, [m.final]=fin, } local cls_states={ [ini]=cls_ini, [fin]=cls_fin } upper_output = upper_output or "" for _, t in ipairs(m.transitions) do local prb = t.lprob if t.from == m.initial then prb = prb + upper_prob end indices[t.from] = indices[t.from] or c_obj:new_state() indices[t.to] = indices[t.to] or c_obj:new_state() local orig = indices[t.from] local dest = indices[t.to] local cls_s = cls_states[orig] if t.id == "fixed" then if (cls_s ~= nil and cls_s ~= -1) then print("warning conflicto en transicion de tipo fixed modelo ".. m.name.." transicion "..orig.."->"..dest.."cls_s = "..cls_s) end cls_states[orig] = -1 cls_s = -1 end if type(t.emission) == 'string' then -- expandible if self.models[t.emission]==nil then error("Se esta intentando expandir un modelo inexistente: "..t.emission) end local ci,cf ci,cf = self:expand(self.models[t.emission], c_obj, prb, orig, dest, cls_states[orig], cls_states[dest], (t.output or "")..upper_output) cls_states[orig] = ci cls_states[dest] = cf else -- no es expandible local cls_t if t.id then -- transicion con nombre if t.id == "fixed" then cls_t = self.trainer:new_cls_transition(-1) elseif self.linked_ids[t.id] then -- nombre ya en la tabla if cls_s ~= nil and cls_s ~= self.linked_ids[t.id][1] then error ("Automata inconsistente") end cls_t = self.linked_ids[t.id][2] else -- con nombre pero no en la tabla (todavia) if not(cls_s) then cls_s = self.trainer:new_cls_state() cls_states[orig] = cls_s end cls_t = self.trainer:new_cls_transition(cls_s) self.linked_ids[t.id] = {cls_s, cls_t} end else -- transicion anonima y no fija if (not cls_s) then cls_s = self.trainer:new_cls_state() cls_states[orig] = cls_s end cls_t = self.trainer:new_cls_transition(cls_s) end local outstr = t.output if dest == fin then outstr = (outstr or "")..upper_output if outstr == "" then outstr = nil end end c_obj:new_transition(orig, dest, t.emission, cls_t, prb, outstr) end end return cls_states[ini],cls_states[fin] end function model_methods:generate_C_model() -- genera un objeto C de tipo hmm_trainer_model a -- partir de un objeto Lua tipo HMMTrainer.model -- expandiendo las transiciones sobre la marcha directamente en C local c_obj = hmm_trainer_model(self.trainer.trainer) local ini = c_obj:new_state() local fin = c_obj:new_state() c_obj:set_initial_state(ini) c_obj:set_final_state(fin) self.trainer:expand(self, c_obj, 0, ini, fin, nil, nil) if not c_obj:prepare_model() then error("El modelo no es correcto") end return c_obj end HMMTrainer.utils= HMMTrainer.utils or {} -- otro namespace function HMMTrainer.utils.name_mangling_unit(unit) local ret = unit if #unit == 1 then ret = "-".. unit .."+" else if string.find(unit, "-") == nil then ret = "-" .. ret end if string.find(unit, "+") == nil then ret = ret .. "+" end end return ret end function HMMTrainer.utils.generate_allograph_hmm_desc(name,allographs,emissions,ploops,pskips,output) if not pskips then pskips = {} end local transitions={} local result = { name = name } local num_emissions = #emissions -- transicion estado inicial table.insert(transitions, { from = name.."ini", to = name.."1", prob = 1, emission = 0 }) -- primera transicion, siempre es necesaria table.insert(transitions, { from = name.."1", to = name.."2", prob = 1, emission = emissions[1], id = name.."1_2" }) for j=2,num_emissions do local pskip = 0.0 -- skip de j a j+2 if pskips[j - 1] and j+1 <= num_emissions then if pskips[j-1] > 0.0 then -- TODO: Esto solo permite skips del primer al tercer estado -- del modelo table.insert(transitions, { from = name .. tostring(j), to = name .. tostring(j+2), prob = pskips[j-1], emission = 0, id = name .. tostring(j) .. "_" .. tostring(j+2) }) pskip = pskips[j-1] end end -- loop sobre j table.insert(transitions, { from = name .. tostring(j), to = name .. tostring(j), prob = ploops[j-1], emission = emissions[j-1], id = name .. tostring(j) .. "_" .. tostring(j) }) -- de j a j+1 table.insert(transitions, { from = name .. tostring(j), to = name .. tostring(j+1), prob = 1-ploops[j-1]-pskip, emission = emissions[j], id = name .. tostring(j) .. "_" .. tostring(j+1) }) end -- loop sobre num_emissions + 1 table.insert(transitions, { from = name .. tostring(num_emissions+1), to = name .. tostring(num_emissions+1), prob = ploops[num_emissions], emission = emissions[num_emissions], id = name .. tostring(num_emissions+1) .. "_" .. tostring(num_emissions+1)}) table.insert(transitions, { from = name .. tostring(num_emissions+1), to = name.."fin", prob = 1-ploops[num_emissions], emission = 0, id = name .. tostring(num_emissions+1) .. "_fin", output = output }) result.transitions = transitions result.initial = name.."ini" result.final = name.."fin" return result end function HMMTrainer.utils.generate_lr_hmm_desc(name,emissions,ploops,pskips,output) if not pskips then pskips = {} end local transitions={} local result = { name = name } local num_emissions = #emissions -- transicion estado inicial table.insert(transitions, { from = name.."ini", to = name.."1", prob = 1, emission = 0 }) -- primera transicion, siempre es necesaria table.insert(transitions, { from = name.."1", to = name.."2", prob = 1, emission = emissions[1], id = name.."1_2" }) for j=2,num_emissions do local pskip = 0.0 -- skip de j a j+2 if pskips[j - 1] and j+1 <= num_emissions then if pskips[j-1] > 0.0 then -- TODO: Esto solo permite skips del primer al tercer estado -- del modelo table.insert(transitions, { from = name .. tostring(j), to = name .. tostring(j+2), prob = pskips[j-1], emission = 0, id = name .. tostring(j) .. "_" .. tostring(j+2) }) pskip = pskips[j-1] end end -- loop sobre j table.insert(transitions, { from = name .. tostring(j), to = name .. tostring(j), prob = ploops[j-1], emission = emissions[j-1], id = name .. tostring(j) .. "_" .. tostring(j) }) -- de j a j+1 table.insert(transitions, { from = name .. tostring(j), to = name .. tostring(j+1), prob = 1-ploops[j-1]-pskip, emission = emissions[j], id = name .. tostring(j) .. "_" .. tostring(j+1) }) end -- loop sobre num_emissions + 1 table.insert(transitions, { from = name .. tostring(num_emissions+1), to = name .. tostring(num_emissions+1), prob = ploops[num_emissions], emission = emissions[num_emissions], id = name .. tostring(num_emissions+1) .. "_" .. tostring(num_emissions+1)}) table.insert(transitions, { from = name .. tostring(num_emissions+1), to = name.."fin", prob = 1-ploops[num_emissions], emission = 0, id = name .. tostring(num_emissions+1) .. "_fin", output = output }) result.transitions = transitions result.initial = name.."ini" result.final = name.."fin" return result end function HMMTrainer.utils.generate_hmm3st_desc(g, e, p1, p2, p3) print("HMMTrainer.utils.generate_hmm3st_desc IS DEPRECATED") return HMMTrainer.utils.generate_lr_hmm_desc(g,{e,e+1,e+2},{p1,p2,p3}) -- -- Crea una tabla con una descripcion de un modelo -- -- lineal con 4 estados para el grafema g -- local result={} -- result.name = g -- result.transitions = { -- {from=g.."ini", to=g.."1", prob=1, emission=0, }, --id=g.."ini1" -- {from=g.."1", to=g.."2", prob=1, emission=e[1], id=g.."12"}, -- {from=g.."2", to=g.."2", prob=p1, emission=e[1], id=g.."22"}, -- {from=g.."2", to=g.."3", prob=1-p1, emission=e[2], id=g.."23"}, -- {from=g.."3", to=g.."3", prob=p2, emission=e[2], id=g.."33"}, -- {from=g.."3", to=g.."4", prob=1-p2, emission=e[3], id=g.."34"}, -- {from=g.."4", to=g.."4", prob=p3, emission=e[3], id=g.."44"}, -- {from=g.."4", to=g.."fin", prob=1-p3, emission=0, id=g.."4fin"}, -- } -- result.initial=g.."ini" -- result.final=g.."fin" -- return result end function HMMTrainer.utils.str2model_desc(str,optional_symbols,output) optional_symbols = optional_symbols or {} -- optional_symbols es un vector del tipo -- {'a'=0.5,'b'=0.7,...} local stringlen = string.len(str) local result={ name =str, transitions={}, initial="0", final =tostring(stringlen), } for i = 1,stringlen do local chr = string.sub(str,i,i) if i==stringlen and output ~= nil then -- la ultima transición emite el output table.insert(result.transitions, {from=tostring(i-1), to=tostring(i), prob=1, emission=chr, id="fixed", output = output } ) else table.insert(result.transitions, {from=tostring(i-1), to=tostring(i), prob=1, emission=chr, id="fixed"} ) end if optional_symbols[chr] then if i==stringlen and output ~= nil then table.insert(result.transitions, {from=tostring(i-1), to=tostring(i), prob=optional_symbols[chr], emission=0, id="fixed", output = output} ) else table.insert(result.transitions, {from=tostring(i-1), to=tostring(i), prob=optional_symbols[chr], emission=0, id="fixed"} ) end end end return result end function HMMTrainer.utils.tbl2model_desc(tbl,optional_symbols,output) optional_symbols = optional_symbols or {} -- optional_symbols es un vector del tipo -- {'a'=0.5,'b'=0.7,...} local tablelen = #tbl local result={ name =table.concat(tbl), transitions={}, initial="0", final =tostring(tablelen), } for i = 1,tablelen do local chr = tbl[i] if i==tablelen and output ~= nil then -- la ultima transición emite el output table.insert(result.transitions, {from=tostring(i-1), to=tostring(i), prob=1, emission=chr, id="fixed", output = output } ) else if output == nil then table.insert(result.transitions, {from=tostring(i-1), to=tostring(i), prob=1, emission=chr, id="fixed"} ) else table.insert(result.transitions, {from=tostring(i-1), to=tostring(i), prob=1, emission=chr, id="fixed" } ) end end if optional_symbols[chr] then if i==stringlen and output ~= nil then table.insert(result.transitions, {from=tostring(i-1), to=tostring(i), prob=optional_symbols[chr], emission=0, id="fixed", output = output} ) else table.insert(result.transitions, {from=tostring(i-1), to=tostring(i), prob=optional_symbols[chr], emission=0, id="fixed" } ) end end end return result end -- Esta funcion recibe un diccionario abierto como fichero (tipo HTK), -- un tiedlist y una tabla de simbolos opcionales, y genera para cada -- palabra del diccionario una descripcion tipo HMMTrainer en forma de -- mini lexico en arbol con las pronunciaciones multiples de cada -- palabra. Esta tabla de descripciones debe despues ser utilizada -- para generar modelos C de un trainer. De este modo se permite poder -- coger una secuencia de palabras de la cual no se tiene la -- transcripcion fonetica y expandar las palabras con los mini lexicos -- en arbol generados aqui. function HMMTrainer.utils.dictionary2lextree(dict_file, tied, optional_symbols, trainer) local mangling = {} optional_symbols = optional_symbols or error ("Needs a table ['a'=0.5, 'b'=0.7, ...] ".. "with optional symbols (for silences") -- tabla donde dejar asociado a cada palabra el conjunto de -- transcripciones que se han encontrado local word2units = {} -- para cad linea del diccionario for line in dict_file:lines() do -- troceamos las linea y sacamos los datos. El formato es el -- siguiente: -- OUTSYM [WORD] PROB U0 U1 U2 U3 ... local l = string.tokenize(line) local outsym = l[1] local begin_units = 2 local prob = 1 local w = outsym if #l>1 and string.sub(l[2],1,1)=="[" and string.sub(l[2],#l[2],#l[2])=="]" then -- leemos la palabra w = string.sub(l[2], 2, #l[2]-1) begin_units = begin_units + 1 end if w ~= outsym then error ("Mandatary: word == outsym!!!") end local units = {} if tonumber(l[begin_units]) ~= nil then -- leemos la probabilidad prob = tonumber(l[begin_units]) begin_units = begin_units + 1 end -- leemos las unidades for i=begin_units,#l do table.insert(units, l[i]) end word2units[w] = word2units[w] or {} if #units > 0 then -- guardamos la secuencia en la tabla table.insert(word2units[w], units) end end -- En esta tabla se guarda para cada palabra una descripcion de un -- modelo HMMTrainer en forma de arbol con todas sus posibles -- pronunciaciones local word2lextree = {} for word,units in pairs(word2units) do -- Funcion auxiliar que comprueba si ya existe una transicion en el -- modelo desde from hasta to function exists_transition(model, from, to) for _, t in pairs(model.transitions) do if t.from==from and t.to==to and t.emission ~= 0 then return true end end return false end -- Funcion auxiliar que comprueba si ya existe una transicion -- lambda en el modelo desde from hasta to function exists_lambda(model, from, to) for _, t in pairs(model.transitions) do if t.from==from and t.to==to and t.emission==0 then return true end end return false end -- rellenamos la tabla result con el arbol de prefijos local result = {} result.name=word result.initial="__initial" result.final="__final" result.transitions={} -- para cada posible pronunciacion for _,units_seq in ipairs(units) do local cur_prefix="__initial" local ant_prefix local triphone_seq = tied:search_triphone_sequence(units_seq) for i=1,#units_seq do ant_prefix=cur_prefix cur_prefix=cur_prefix .. " " .. units_seq[i] -- prefijo de longitud i if not exists_transition(result, ant_prefix, cur_prefix) then table.insert(result.transitions, {from=ant_prefix, to=cur_prefix, emission=tied:get_model(triphone_seq[i]), prob=1, id="fixed" } ) end if (optional_symbols[units_seq[i]] and not exists_lambda(result, ant_prefix, cur_prefix, units_seq[i])) then table.insert(result.transitions, {from=ant_prefix, to=cur_prefix, emission=0, prob=optional_symbols[units_seq[i]], id="fixed" } ) end end if not exists_transition(result, cur_prefix, "__final") then table.insert(result.transitions, {from=cur_prefix, to="__final", emission=0, prob=1, id="fixed"} ) end end if #units > 0 then table.insert(word2lextree, result) if trainer then local aux = trainer:model(result) mangling[word] = "__"..word.."__" trainer:add_to_dict(aux, mangling[word]) end end end return word2lextree,mangling end function HMMTrainer.utils.strtable2tree(str_tbl, voc, exclude_words) if not exclude_words then exclude_words = {} end -- Funcion auxiliar que comprueba si ya existe una transicion en el -- modelo desde from hasta to function exists_transition(model, from, to) for _, t in pairs(model.transitions) do if t.from==from and t.to==to then return true end end return false end local invert_str_tbl = table.invert(str_tbl) local result={} result.name="prefixtree" -- FIXME: Cambiar? result.initial="__initial" result.final="__final" result.transitions={} for _, word in pairs(str_tbl) do if not exclude_words[word] then -- Recorremos los prefijos de word y vamos creando -- transiciones segun sea necesario i=1 local cur_prefix="__initial" local ant_prefix local cur_chr while i<=string.len(word) do ant_prefix=cur_prefix cur_prefix=string.sub(word, 1, i) -- prefijo de longitud i cur_chr=string.sub(word, i, i) if not exists_transition(result, ant_prefix, cur_prefix) then table.insert(result.transitions, {from=ant_prefix, to=cur_prefix, emission=cur_chr, prob=1, id="fixed"} ) end i=i+1 end -- La ultima transicion lleva como output la palabra if not exists_transition(result, cur_prefix, "__final") then local out = cur_prefix if voc then out = voc[invert_str_tbl[cur_prefix]] end table.insert(result.transitions, {from=cur_prefix, to="__final", emission=0, prob=1, id="fixed", output=out} ) end end end return result end function HMMTrainer.utils.dictionary2tree(dictionary, tied, exclude_words) error ("DEPRECATED") -- if not exclude_words then exclude_words = {} end -- -- Funcion auxiliar que comprueba si ya existe una transicion en el -- -- modelo desde from hasta to -- function exists_transition(model, from, to) -- for _, t in pairs(model.transitions) do -- if t.from==from and t.to==to then -- return true -- end -- end -- return false -- end -- local result={} -- result.name="prefixtree" -- FIXME: Cambiar? -- result.initial="__initial" -- result.final="__final" -- result.transitions={} -- for word, word_info in pairs(dictionary.lex) do -- if not exclude_words[word] then -- for _,word_phones in ipairs(word_info.units) do -- local word_tied_phones = word_phones -- if tied then -- word_tied_phones = tied:search_triphone_sequence(word_phones) -- end -- -- Recorremos los prefijos de word_tied_phones y vamos creando -- -- transiciones segun sea necesario -- i=1 -- local cur_prefix="__initial" -- local ant_prefix -- local cur_chr -- while i<=#word_tied_phones do -- ant_prefix=cur_prefix -- cur_prefix=table.concat(word_tied_phones, "", 1, i-1) -- cur_chr=HMMTrainer.utils.name_mangling_unit(word_tied_phones[i]) -- if not exists_transition(result, ant_prefix, cur_prefix) then -- table.insert(result.transitions, -- {from=ant_prefix, -- to=cur_prefix, -- emission=cur_chr, -- prob=1, id="fixed"} ) -- end -- i=i+1 -- end -- -- La ultima transicion lleva como output la palabra -- if not exists_transition(result, cur_prefix, "__final") then -- local out = word_info.outsym -- table.insert(result.transitions, -- {from=cur_prefix, -- to="__final", -- emission=0, -- prob=1, id="fixed", -- output=out} ) -- end -- end -- end -- end -- return result end -- DE MOMENTO ESTA FUNCION SOLO GENERA MODELOS LR CON SKIPS -- TODO: Hacer que pueda generar cualquier tipo de descripcion -- j j+1 j+2 j+3 j+4 -- 0.000000e+00 1.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 -- 0.000000e+00 7.768173e-01 2.231827e-01 0.000000e+00 0.000000e+00 -- 0.000000e+00 0.000000e+00 6.739026e-01 3.260975e-01 0.000000e+00 -- 0.000000e+00 0.000000e+00 0.000000e+00 4.722403e-01 5.277597e-01 -- 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 function HMMTrainer.utils.generate_hmm_desc_from_transP(name, emissions, transition_matrix, output) -- numero de estados en la matriz local numstates = transition_matrix:dim()[1] -- tabla de transiciones del modelo local transitions = { {from = "ini", to = name.."1", prob=1, emission=0} } -- índice de las transiciones de la tabla transitions que llegan al -- estado final local transitions_to_last_state = {} -- indica si el estado final de la matriz tiene transiciones de -- salida local exists_last_state_transitions = false -- Recorremos la matriz generando transiciones for state=1,numstates do for deststate=1,numstates do -- probabilidad en la matriz local prob = transition_matrix:get(state,deststate) if prob > 0.0 then -- el indice de emision siempre es el estado al que llegamos -- con la transicion, menos 1 local emissid = deststate - 1 table.insert(transitions, { from = name .. tostring(state), to = name .. tostring(deststate), prob = prob, emission = emissions[emissid] or 0, id = name .. tostring(state) .. "_" .. tostring(deststate) }) -- Guardamos las transiciones que llegan al último estado -- (emitirán el output) if deststate == numstates then table.insert(transitions_to_last_state, #transitions) end -- El último estado tiene transiciones? if state == numstates then exists_last_state_transitions = true end end end end -- indicamos que estados son iniciales y finales local ini = "ini" local fin = name..tostring(numstates) if exists_last_state_transitions then -- si el último estado tenía transiciones, creamos uno nuevo que -- no las tenga, que tendrá el output y transita con lambda table.insert(transitions, { from = name .. tostring(numstates), to = name .. tostring(numstates+1), prob = 1, emission = 0, output = output, }) -- el nuevo estado será el final fin = name..tostring(numstates+1) else -- si el último estado no tiene transiciones, entonces metemos en -- todas las transiciones que van a él el output indicado para -- este modelo for i,tr in ipairs(transitions_to_last_state) do transitions[tr].output = output end end -- devolvemos la tabla: return { name = name, initial = ini, final = fin, transitions = transitions, } end function HMMTrainer.utils.apply_gsf_to_desc(desc,factor) -- iterar sobre transitions de desc for i,t in ipairs(desc.transitions) do if t.lprob == nil then t.lprob = math.log(t.prob) t.prob = nil end t.lprob = t.lprob * factor -- elevar prob al factor end end function HMMTrainer.utils.print_dot(model) print("digraph automata {"); for i,v in ipairs(model.transitions) do printf("%s -> %s [label=\"" .. v.emission .. "/" .. (v.lprob or math.log(v.prob)) .. "/" .. (v.output or "").."\"];\n", string.gsub(v.from, "[<>]", ""), string.gsub(v.to, "[<>]", "")) end print("}") end april-ann-0.4.1/packages/hmm_trainer/lua_src/read_arpa.lua000066400000000000000000000206001263004425400235270ustar00rootroot00000000000000-- modelo = {name="nombre", -- transitions={ -- {from="...", to="....", prob=... , id="....", emission="...",output="..."} -- ... -- } -- initial="...", -- final="..." -- } HMMTrainer = HMMTrainer or {} -- namespace -- Recibe una tabla con estos argumentos: -- file -- filename, solo se usa si no hay file -- vocabulary es OPCIONAL -- bccue es OPCIONAL -- bccue es OPCIONAL function HMMTrainer.read_arpa(tbl) local line,which_n,how_many_ngrams,orig,last_orig,dest,word,dest_backoff local n = 1 local nstates, ntrans local ngram_count={} local next_state=0 local next_trans=0 local states={} -- string -> number local next_word=1 local vocabulary -- string -> number if tbl.vocabulary then vocabulary = tbl.vocabulary else vocabulary = lexClass() end local log10 = math.log(10) local logZero = -1e12 -- representación de log(-infinito) local logOne = 0 local function arpa_prob(x) if x <= -99 then return logZero end return x*log10 end local file = tbl.file or io.open(tbl.filename) local bccue = tbl.bccue or '' -- begin context cue local eccue = tbl.eccue or '' -- end context cue -- saltarselo todo hasta llegar a \data\ repeat line = file:read('*l') until line == '\\data\\' -- leer lineas tipo 'ngram numero=numero' repeat line = file:read('*l') _,_, which_n,how_many_ngrams = string.find(line,"^ngram (%d+)=(%d+)$") which_n = tonumber(which_n) how_many_ngrams = tonumber(how_many_ngrams) if which_n ~= nil then ngram_count[which_n]=how_many_ngrams if which_n>n then n = which_n end end until which_n == nil -- El numero de estados esta acotado superiormente por -- el numero de i-gramas + 1 con i=1..n-1 -- El numero de transiciones no-lambda esta acotado por -- el numero de i-gramas con i=1..n (algunos indican -- transiciones al estado final, que no codificamos expresamente) nstates=0 for i=1,n-1 do nstates = nstates + ngram_count[i] end ntrans = nstates + ngram_count[n] + 1 -- uno mas para poner el centinela en la tabla nstates = nstates + 2 local model = {} model.name = tbl.filename model.final = "final" model.transitions={} -- 0-grama states["_"] = next_state next_state = next_state + 1 last_orig=0 for i=1,n-1 do -- leemos hasta n-1 gramas -- buscamos la cadena abuscar = string.format("\\%d-grams:",i) while (line ~= abuscar) do line = file:read('*l') end --print(line) line = string.gsub(file:read('*l'),"_","\\_") while line ~= "" do w = string.tokenize(line) -- example: -0.544068 b a -0.3521825 ---------------------------------------------- prob = arpa_prob(tonumber(w[1])) -- i-grama w1 w2 ... wi-1 wi -- índices 2 3 ... i i+1 word = w[i+1] orig_name = '_'..table.concat(w,"_",2,i) orig = states[orig_name] if orig < last_orig then t = table.invert(states) print (last_orig, t[last_orig], "->", orig, t[orig]) error (".arpa file is not sorted") elseif orig > last_orig then -- si cambia orig, establecemos first_transition del nuevo origen --for rft = last_orig+1,orig do --model:set_state_first_transition(rft, next_trans) --end end last_orig=orig if word == eccue then -- final -- caso w1 ... w_{i-1} es final con prob prob --model:set_state_final_prob(orig, prob) table.insert(model.transitions, {from=orig_name, to="final", lprob=prob, emission=0}) if not vocabulary:getWordId(word) then if tbl.vocabulary then error("read_arpa found unknown word when using a fixed vocabulary: " .. word) end vocabulary:addWord{ id = next_word, word = word, outsym = word, } next_word = next_word + 1 end else if w[i+2] then bow = arpa_prob(tonumber(w[i+2])) else bow = logOne end -- creamos una transición para subir: -- de w1_...w_{i-1} a w1_...w_i -- esto implica asignar un numero nuevo al -- estado destino dest_name = '_'..table.concat(w,"_",2,i+1) states[dest_name] = next_state dest = next_state --model:set_state_name(dest,'_'..table.concat(w,"_",2,i+1)) next_state = next_state + 1 if not vocabulary:getWordId(word) then if tbl.vocabulary then error("read_arpa found unknown word when using a fixed vocabulary: " .. word) end vocabulary:addWord{ id = next_word, word = word, outsym = word, } next_word = next_word + 1 end if prob > logZero then -- este if hay que validarlo table.insert(model.transitions, { from=orig_name, to=dest_name, lprob=prob, emission=word}) --model:set_trans_word(next_trans,vocabulary[word]) --model:set_trans_prob(next_trans,prob) --model:set_trans_dest(next_trans,dest) next_trans = next_trans + 1 end -- transición de bajada: -- transicion nula w1_...w_{i} a w2_...w_{i} -- orig_backoff=dest dest_backoff_name = '_'..table.concat(w,"_",3,i+1) dest_backoff = states[dest_backoff_name] -- print("dest_backoff=", '_'..table.concat(w,"_",3,i+1), dest_backoff) if prob > logZero then -- este if hay que validarlo table.insert(model.transitions, {from=dest_name, to=dest_backoff_name, lprob=bow, emission=0}) end --model:set_state_bo_prob(dest, bow) --model:set_state_bo_dest_state(dest, dest_backoff) end ---------------------------------------------- line = string.gsub(file:read('*l'),"_","\\_") end end --leemos n gramas abuscar = string.format("\\%d-grams:",n) while (line ~= abuscar) do line = file:read('*l') end --print(line) line = string.gsub(file:read('*l'),"_","\\_") while line ~= "" do w = string.tokenize(line) ---------------------------------------------- prob = arpa_prob(tonumber(w[1])) -- n-grama w1 w2 ... wn-1 wn -- índices 2 3 ... n n+1 word = w[n+1] orig_name = '_'..table.concat(w,"_",2,n) orig = states[orig_name] if orig < last_orig then t = table.invert(states) print (last_orig, t[last_orig], "->", orig, t[orig]) error (".arpa file is not sorted") elseif orig > last_orig then -- si cambia orig, establecemos first_transition del nuevo origen --for rft = last_orig+1,orig do --model:set_state_first_transition(rft, next_trans) --end end last_orig=orig if word == eccue then -- final -- caso w1 ... w_{n-1} es final con prob prob --model:set_state_final_prob(orig, prob) if prob > logZero then -- este if hay que validarlo table.insert(model.transitions, {from=orig_name, to="final", lprob=prob, emission=0}) end if not vocabulary:getWordId(word) then if tbl.vocabulary then error("read_arpa found unknown word when using a fixed vocabulary: " .. word) end vocabulary:addWord{ id = next_word, word = word, outsym = word, } next_word = next_word + 1 end else -- creamos una transición de un n-grama a otro: -- de w1_...w_{n-1} a w2_...w_n dest_name = '_'..table.concat(w,"_",3,n+1) dest = states[dest_name] if not vocabulary:getWordId(word) then if tbl.vocabulary then error("read_arpa found unknown word when using a fixed vocabulary: " .. word) end vocabulary:addWord{ id = next_word, word = word, outsym = word, } next_word = next_word + 1 end if prob > logZero then -- este if hay que validarlo table.insert(model.transitions, {from=orig_name, to=dest_name, lprob=prob, emission=word}) --model:set_trans_word(next_trans,vocabulary[word]) --model:set_trans_prob(next_trans,prob) --model:set_trans_dest(next_trans,dest) next_trans = next_trans + 1 end end ---------------------------------------------- line = string.gsub(file:read('*l'),"_","\\_") end -- crear centinela en tabla transiciones --for rft = last_orig+1,next_state do --model:set_state_first_transition(rft, next_trans) --end -- establecer estado inicial: if n>1 then --model:set_initial_state(states["_"..bccue]) model.initial = "_"..bccue else --model:set_initial_state(states["_"]) model.initial = "_" end -- cerrar el fichero, si toca if tbl.file == nil then -- lo hemos abierto nosotros con io.open file:close() end -- establecer numero de estados y de transiciones --model:set_number_states_and_trans(next_state, next_trans) return model,vocabulary,states end -- descomentar para testear: -- f = io.open(arg[1],"r") -- m = ngram.read_arpa(f) -- m:print() april-ann-0.4.1/packages/hmm_trainer/package.lua000066400000000000000000000024321263004425400215570ustar00rootroot00000000000000 package{ name = "hmm_trainer", version = "1.0", depends = { "util", "matrix", "lexClass", "tied_model_manager" }, keywords = { "hmm_trainer" }, description = "left to right hidden markov model", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, --copy{ file= "c_src/dataset.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_hmm_trainer.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", debug="yes", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_hmm_trainer.lua.cc", dest_dir = "build" , debug="yes", } }, target{ name = "document", document_src{ file= {"c_src/*.h", "c_src/*.c", "c_src/*.cc"}, }, document_bind{ file= {"binding/*.lua.cc"} }, }, } april-ann-0.4.1/packages/hmm_trainer/test/000077500000000000000000000000001263004425400204375ustar00rootroot00000000000000april-ann-0.4.1/packages/hmm_trainer/test/ejemplo.lua000066400000000000000000000037431263004425400226040ustar00rootroot00000000000000function print_model(m) print("name=", m.name) print("transitions={") for _,t in pairs(m.transitions) do printf("{from=%s, to=%s, prob=%s, emission=%s, output=%s, id=%s}\n", t.from, t.to, t.prob, t.emission or "nil", t.output or "", t.id or "nil") end print"}" print("initial=", m.initial) print("final=", m.final) end --[[ x=HMMTrainer:new(100,100,500) m1={ name="modelo 1", transitions={ {from="ini", to="a", prob=1, emission=3}, {from="a", to="a", prob=0.5, emission=3, id="t1"}, {from="a", to="b", prob=0.5, emission=5, id="t2"}, {from="b", to="b", prob=0.3, emission=5}, {from="b", to="fin", prob=0.7} }, initial="ini", final="fin" } m2={ name="modelo 2", transitions={ {from="ini", to="a", prob=1, emission=7}, {from="a", to="a", prob=0.7, emission=7}, {from="a", to="b", prob=0.3, emission=3}, {from="b", to="b", prob=0.5, emission=3, id="t1"}, {from="b", to="fin", prob=0.5, id="t2"} }, initial="ini", final="fin", } --]] m3={ name="modelo 3", transitions={ {from="ini", to="x", prob=1, emission=1}, {from="x", to="x", prob=0.1, emission=1}, {from="x", to="y", prob=0.9, emission=2}, {from="y", to="y", prob=0.4, emission=2, id="t1"}, {from="y", to="z", prob=0.6, emission=3, id="t2"}, {from="z", to="z", prob=0.2, emission=3}, {from="z", to="fin", prob=0.8} }, initial="ini", final="fin" } m_ex=expand_model(m3,"x","y", m1) x:model(m_ex) --]] ---[[ tbl={} tbl.c=HMMTrainer.utils.generate_hmm3st_desc("c",1,0.5,0.5,0.5) tbl.a=HMMTrainer.utils.generate_hmm3st_desc("a",4,0.5,0.5,0.5) tbl.s=HMMTrainer.utils.generate_hmm3st_desc("s",7,0.5,0.5,0.5) tbl.o=HMMTrainer.utils.generate_hmm3st_desc("o",10,0.5,0.5,0.5) t=HMMTrainer.trainer() m1=t:model(HMMTrainer.utils.strtable2tree({"casa", "caso", "saca", "saco"})) mc=t:model(tbl.c) ma=t:model(tbl.a) ms=t:model(tbl.s) mo=t:model(tbl.o) t:add_to_dict(mc) t:add_to_dict(ma) t:add_to_dict(ms) t:add_to_dict(mo) printf("\n------------\n") m1c = m1:generate_C_model() m1c:print_dot() april-ann-0.4.1/packages/hmm_trainer/test/entrena.lua000066400000000000000000000263611263004425400226060ustar00rootroot00000000000000function generate_models_from_alphabet(alphabet) local result = {} local i=1 local chr while i<= string.len(alphabet) do chr = string.sub(alphabet,i,i) result[chr]=generate_model(chr, 3*(i-1)+1, 0.5, 0.5, 0.5) i=i+1 end return result end function generate_alphabet_from_wordlist(wordlist) local alphabet={} local i local chr local result="" for _, word in pairs(wordlist) do i=1 while i <= string.len(word) do chr=string.sub(word, i,i) alphabet[chr]=true i=i+1 end end for k,v in pairs(alphabet) do result=result..k end return result end function generate_models_from_wordlist(wordlist, alphabet_models) local result = {} for _,word in pairs(wordlist) do result[word]=str2model(word, alphabet_models) end return result end function normalizar_mdt(lista_matrices) local utable = {} for i,mat in pairs(lista_matrices) do table.insert(utable,dataset.matrix(mat)) end local dts = dataset.union(utable) local lctable = {} local m,dt m,dt = dts:mean_deviation() for i=1,dts:patternSize() do table.insert(lctable,{{0,-m[i]/dt[i]},{i,1/dt[i]}}) end local daux = dataset.linearcomb(dts,lctable) -- normalizamos for i=1,dts:numPatterns() do dts:putPattern(i,daux:getPattern(i)) end end function normalizar_minmax(lista_matrices) local utable = {} for i,mat in pairs(lista_matrices) do table.insert(utable,dataset.matrix(mat)) end local dts = dataset.union(utable) local lctable = {} local m,dt mi,ma = dts:min_max() for i=1,dts:patternSize() do local r = 1/(ma[i]-mi[i]) table.insert(lctable,{{0,-mi[i]},{i,r}}) end local daux = dataset.linearcomb(dts,lctable) -- normalizamos for i=1,dts:numPatterns() do dts:putPattern(i,daux:getPattern(i)) end end function load_list_images(filename) local name = {} local image = {} local file=io.open(filename) for l in file:lines() do local t = string.tokenize(l,"\t") if (t[1]~=nil and t[2]~=nil) then table.insert(image,t[1]) table.insert(name,t[2]) end end file:close() return name,image end -- recibe una tabla con los nombres de fichero de las imagenes y la -- cadena con los parametros, -- devuelve una tabla con los parametros function load_and_param_images(IMG_DIR, imagetable, params) local params_table = {} for i, imgname in ipairs(imagetable) do printf("loading %s ...\n", IMG_DIR.."/"..imgname) local img = Image.load_pgm_gz(IMG_DIR.."/"..imgname) table.insert(params_table, param.extract(img, params)) -- = param_moises(img_s) end normalizar_mdt(params_table) --normalizar_minmax(params_table) return params_table end function param_m2d(mat,ctxtizq,ctxtder) local conf = { patternSize = {ctxtizq+1+ctxtder,mat:dim()[2]}, offset = {-ctxtizq,0}, numSteps = {mat:dim()[1],1}, stepSize = {1,1}, -- second is don't care } --print("mat es",mat,table.concat(mat:dim(),"x")) return dataset.matrix(mat,conf) end -- recibe dos tablas, la primera con el nombre y la segunda con la -- matriz de parametros de la imagen correspondiente en el mismo -- indice function images_each_word(name_t, param_t,ctxtizq,ctxtder) local iew = {} for i, name in ipairs(name_t) do if iew[name] == nil then iew[name] = {} end table.insert(iew[name], param_m2d(param_t[i],ctxtizq,ctxtder)) end return iew end -- Devuelve una tabla con la secuencia de emisiones -- de una palabra function word_emissions(word, alphabet) local result={} local chr local emission local i=1 while i <= string.len(word) do chr=string.sub(word,i,i) emission = 3*(string.find(alphabet, chr, 1, true) - 1)+1 result[3*(i-1)+1] = emission result[3*(i-1)+2] = emission+1 result[3*(i-1)+3] = emission+2 i = i+1 end return result end ---------------------------------------------------------------------- -- programa ppal ---------------------------------------------------------------------- PARAMETROS = "Tsiepdqa" filename_trn = "../entrenamiento/lista.txt" filename_val = "../validacion/lista.txt" filename_tst = "../test/lista.txt" dir_trn = "../entrenamiento" dir_val = "../validacion" dir_tst = "../test" -- Cargamos la lista de imagenes name_tbl_trn,imagename_tbl_trn = load_list_images(filename_trn) name_tbl_val,imagename_tbl_val = load_list_images(filename_val) name_tbl_tst,imagename_tbl_tst = load_list_images(filename_tst) -- Parametrizamos las imagenes params_tbl_trn = load_and_param_images(dir_trn,imagename_tbl_trn, PARAMETROS) params_tbl_val = load_and_param_images(dir_val,imagename_tbl_val, PARAMETROS) params_tbl_tst = load_and_param_images(dir_tst,imagename_tbl_tst, PARAMETROS) inv_name_tbl = {} for key,tbl in ipairs{name_tbl_trn,name_tbl_val,name_tbl_tst} do for i,j in ipairs(tbl) do inv_name_tbl[j] = true end end name_tbl = {} for nam,v in pairs(inv_name_tbl) do table.insert(name_tbl,nam) end table.sort(name_tbl) printf("lista nombres: %s\n",table.concat(name_tbl,";")) -- En caso de querer fijar un alfabeto,modificar aqui alphabet=generate_alphabet_from_wordlist(name_tbl) -- Generamos los modelos para cada letra y para cada palabra, model_tbl=generate_models_from_alphabet(alphabet) temp_mtbl=generate_models_from_wordlist(name_tbl, model_tbl) for k,v in pairs(temp_mtbl) do -- Evitamos reemplazar los modelos de las letras individuales -- porque valen igual y tienen menos estados "dummy" if not model_tbl[k] then model_tbl[k]=v end end -- Generamos el modelo en arbol tree = strtable2tree(name_tbl) tree = expand_model(tree, model_tbl) function print_model(m) print("name=", m.name) print("transitions={") for _,t in pairs(m.transitions) do printf("{from=%s, to=%s, prob=%s, emission=%s, output=%s, id=%s}\n", t.from, t.to, t.prob, t.emission or "nil", t.output or "", t.id or "nil") end print"}" print("initial=", m.initial) print("final=", m.final) end print_model(tree) model_tbl["__tree"]=tree -- ahora vamos a entrenar, para ello necesitamos una red neuronal con -- tantas entradas como: num_parametros * (ctxt_izq+1+ctxt_der) num_parametros = string.len(PARAMETROS) ctxt_izq = 4 ctxt_der = 4 iew_trn = images_each_word(name_tbl_trn,params_tbl_trn,ctxt_izq,ctxt_der) iew_val = images_each_word(name_tbl_val,params_tbl_val,ctxt_izq,ctxt_der) iew_tst = images_each_word(name_tbl_tst,params_tbl_tst,ctxt_izq,ctxt_der) -- iew es una tabla que a cada palabra del lexico le asocia una lista -- de imagenes ya parametrizadas en forma de datasets -- numero de salidas de la red neuronal: num_salidas = 3*string.len(alphabet) -- dataset auxiliar: casiuno = 0.9 casicero = (1-casiuno)/(num_salidas-1) ds_ident = dataset.identity(num_salidas,casicero,casiuno) ma_alignments = {} -- matrices ds_alignments = {} -- matrices for word,dstable in pairs(iew_trn) do -- ahora generamos una tabla similar a iew, reemplazamos cada -- dataset por una matriz de dim 1 y de talla el numPatterns, -- inicializamos la matriz, la metemos en un dataset.index ma_alignments[word] = {} ds_alignments[word] = {} for i,ds in ipairs(dstable) do local seq_emission = word_emissions(word, alphabet) local a = hmm_trainer.initial_emission_alignment(seq_emission, ds:numPatterns()) local b = dataset.indexed(dataset.matrix(a), {ds_ident}):toMatrix() table.insert(ma_alignments[word], b) table.insert(ds_alignments[word], dataset.matrix(b) ) end end -- creamos la red neuronal... semilla = 1234 num_entradas = num_parametros*(1+ctxt_izq+ctxt_der) num_ocultas1 = 100 num_ocultas2 = 100 aleat = random(semilla) lared = Mlp(string.format("%d inputs %d logistic %d logistic %d softmax", num_entradas, num_ocultas1, num_ocultas2, num_salidas)) lared:generate(aleat, -0.7, 0.7) -- creamos el HMMTrainer y los modelos trainer, models = create_hmm_trainer_from_models_list(model_tbl, num_salidas) -- recopilamos datos para entrenar: todas_entradas = {} todas_salidas = {} for word,dstable in pairs(iew_trn) do local t = ds_alignments[word] for i,ds in ipairs(dstable) do table.insert(todas_entradas,ds) table.insert(todas_salidas,t[i]) end end train_input = dataset.union(todas_entradas) train_output = dataset.union(todas_salidas) datosentrenar = { learning_rate = 0.05, momentum = 0.05, weight_decay = 1e-7, input_dataset = train_input, output_dataset = train_output, shuffle = aleat } printf([[ Entrenamos una red neuronal con %d patrones de talla %d y %d valores de salida ]], train_input:numPatterns(), train_input:patternSize(), train_output:patternSize()) veces_train = 10 veces_em = 500 trainer.trainer:set_a_priori_emissions(train_output:mean()) for iterem = 1,veces_em do printf("------------------------------\nIteracion %d de EM\n", iterem) -- entrenamos la red neuronal for epoch = 1,veces_train do errortrain = lared:train(datosentrenar) printf("em %4d epoch %4d mse_train %.7f\n", iterem,epoch,errortrain) end iews = { entrenamiento= iew_trn, validacion = iew_val, test = iew_tst, } for partitionname,iew in pairs(iews) do aciertos = 0 totales = 0 mconf = {} for word,dstable in pairs(iew) do themodel = models[word] collectgarbage() -- para evitar crecimiento excesivo de memoria for otherkey,dsparam in ipairs(dstable) do -- reentrenar la cadena mat: -- primero, generar la matriz con las emisiones: local matemission = matrix(dsparam:numPatterns(),num_salidas) -- utilizarla con la red neuronal lared:use_dataset{ input_dataset = dsparam, output_dataset = dataset.matrix(matemission) } prob, rword = models["__tree"]:viterbi{ input_emission = matemission, do_expectation = false, } mconf[word] = mconf[word] or {} mconf[word][rword] = (mconf[word][rword] or 0)+1 --printf("confmat%3d%s: %-10s -> %-10s\n",iterem,partitionname,word,rword) totales = totales+1 if (word == rword) then aciertos = aciertos+1 end end end -- recorre iew for a,b in pairs(mconf) do for c,d in pairs(b) do printf("conf: %3d %-10s %-10s (%3d)-> %-10s\n",iterem,partitionname,a,d,c) end end printf("Porcentaje de aciertos iter %d en %s: %.2f%%\n", iterem,partitionname,100*aciertos/totales) -- printf("matriz confusión:\n%14s","") -- for a,b in ipairs(name_tbl) do -- printf("%10s ",b); -- end -- printf("\n") -- local empt = {} -- for a,b in ipairs(name_tbl) do -- printf("%14s",b) -- for c,d in ipairs(name_tbl) do -- e = mconf[b] or empt -- printf("%14d ",(e[d] or 0)) -- end -- printf("\n") -- end end -- recorre iews -- EXPECTATION trainer.trainer:begin_expectation() for word,dstable in pairs(iew_trn) do themodel = models[word] for i,mat in ipairs(ma_alignments[word]) do -- reentrenar la cadena mat: -- primero, generar la matriz con las emisiones: local dsparam = dstable[i] -- utilizarla con la red neuronal lared:use_dataset{ input_dataset = dsparam, output_dataset = ds_alignments[word][i] } themodel:viterbi{ input_emission = mat, do_expectation = true, output_emission= mat } end end trainer.trainer:end_expectation() filenet = string.format("redes/hmm%d.net",iterem) print("salvando "..filenet) lared:save(filenet,"ascii") end april-ann-0.4.1/packages/hmm_trainer/test/mini.arpa000066400000000000000000000006631263004425400222450ustar00rootroot00000000000000 \data\ ngram 1=5 ngram 2=11 ngram 3=2 \1-grams: -0.6766936 -99 -0.1983676 -0.4336556 wa 0.07463366 -0.5006024 wb 7.078244 -0.9777236 wc -0.1014576 \2-grams: -0.2218488 wa -0.1760913 -0.69897 wb -0.60206 wa -0.90309 wa wa -0.30103 wa wb -0.845098 wb -0.544068 wb wa -0.3521825 -0.845098 wb wb -0.544068 wb wc -0.4771213 wc -0.4771213 wc wa \3-grams: -0.1760913 wa wb -0.1760913 wb wa \end\ april-ann-0.4.1/packages/hmm_trainer/test/segmentacion-letras.lua000066400000000000000000000025411263004425400251100ustar00rootroot00000000000000function generate_segmentation_image(imgfile, emission_sequence) -- Genera una imagen con la palabra en text_image con sus letras -- separadas segun la secuencia de emisiones para el alfabeto dado. local text_image=Image.load_pgm_gz(imgfile) local result=text_image:clone() local e = dataset.matrix(emission_sequence) local width, height = text_image:geometry() -- width no se usa local cur_emission local prev_emission local ncambios=0 local factor=1 for col, pat in e:patterns() do cur_emission = pat[1] -- si la letra actual es distinta a la anterior, pintamos una -- franja en negativo if prev_emission then if cur_emission ~= prev_emission then ncambios=ncambios+1 if ncambios==3 then if factor==1 then factor = 0.9 else factor = 1 end ncambios=0 end end end for i=0,height-1 do color = 1-result:getpixel(col-1,i) if color < 0 then color = 0 end if color > 1 then color = 1 end result:putpixel(col-1, i, 1-factor*color) end prev_emission = cur_emission end return result end ---- Programa principal IMG_DIR="../test" tabla=dofile(arg[1]) -- Toma como parametro un fichero alignment*.lua DEST_DIR=arg[2] suffix=arg[3] for _, t in ipairs(tabla) do img = generate_segmentation_image(IMG_DIR.."/"..t[2], t[3]) Image.save(img, DEST_DIR.."/"..t[2].."_"..suffix..".pgm") end april-ann-0.4.1/packages/hmm_trainer/test/slf2hmm_trainer.py000077500000000000000000000033311263004425400241100ustar00rootroot00000000000000#!/usr/bin/python import re import sys if sys.argv[2]=="p": probs=True else: probs=False f=file(sys.argv[1], 'r') lines = f.readlines() sizespec = re.compile('N=([0-9]+)\s+L=([0-9]+)') node = re.compile('I=([0-9]+)\s+W=(\S*)') if probs: arc = re.compile('J=([0-9]+)\s+S=([0-9]+)\s+E=([0-9]+)\s+l=(\S+)') else: arc = re.compile('J=([0-9]+)\s+S=([0-9]+)\s+E=([0-9]+)') # find sizespec i=0 while True: m = sizespec.match(lines[i]) i+=1 if m: break num_states = int(m.group(1)) num_transitions = int(m.group(2)) #print num_states, num_transitions state_words={} # read states for l in lines[i:i+num_states]: id, word = node.match(l).groups() state_words[id] = word #print "node:", id, word i += num_states #read transitions transitions=[] for l in lines[i:i+num_transitions]: if probs: id, start, end, lprob = arc.match(l).groups() transitions.append((id, start, end, state_words[end], lprob)) else: id, start, end = arc.match(l).groups() transitions.append((id, start, end, state_words[end])) #print "arc:", id, start, end #FIXME: Find initial and final states by looking for source and sink states #print transitions in april HMM desc format print "return {" print '\tname = "%s",'%(sys.argv[1]) print "\ttransitions = {" for t in transitions: if probs: if t[3]=='!NULL': print '\t\t{from="%s", to="%s", emission=0, lprob=%s},'%(t[1], t[2], t[4]) else: print '\t\t{from="%s", to="%s", emission="%s", lprob=%s},'%(t[1], t[2], t[3], t[4]) else: if t[3]=='!NULL': print '\t\t{from="%s", to="%s", emission=0, lprob=0},'%(t[1], t[2]) else: print '\t\t{from="%s", to="%s", emission="%s", lprob=0},'%(t[1], t[2], t[3]) print "\t}," print '\tinitial="0",' print '\tfinal="1",' print"}" april-ann-0.4.1/packages/hmm_trainer/test/test-dot.lua000066400000000000000000000007561263004425400227150ustar00rootroot00000000000000function print_model(m) print("name=", m.name) print("transitions={") for _,t in pairs(m.transitions) do printf("{from=%s, to=%s, prob=%s, emission=%s, output=%s, id=%s}\n", t.from, t.to, t.prob, t.emission or "nil", t.output or "", t.id or "nil") end print"}" print("initial=", m.initial) print("final=", m.final) end ---[[ m1=strtable2tree({"casa", "caso", "saca", "saco","sacar"}) --]] cadena=model2dot(m1) print(cadena) f=io.open("test.dot","w") f:write(cadena) f:close() april-ann-0.4.1/packages/hmm_trainer/test/test_arpa.lua000066400000000000000000000033621263004425400231300ustar00rootroot00000000000000trainer = HMMTrainer.trainer() desc_ngrama = trainer:model(HMMTrainer.read_arpa({ filename="mini.arpa", vocabulary=lexClass({"","","wa","wb","wc"}), phone_vocabulary={"","","wa", "wb", "wc"}, })) desc_a = trainer:model(HMMTrainer.utils.str2model_desc("wa", {}, "a")) desc_b = trainer:model(HMMTrainer.utils.str2model_desc("wb", {}, "b")) desc_c = trainer:model(HMMTrainer.utils.str2model_desc("wc", {}, "c")) phone_a = trainer:model(HMMTrainer.utils.generate_lr_hmm_desc("a", {1,2}, {0.5,0.5}, {0.0,0.0})) phone_b = trainer:model(HMMTrainer.utils.generate_lr_hmm_desc("b", {3,4}, {0.5,0.5}, {0.0,0.0})) phone_c = trainer:model(HMMTrainer.utils.generate_lr_hmm_desc("c", {5,6}, {0.5,0.5}, {0.0,0.0})) phone_w = trainer:model({ name = "w", transitions={{from="ini", to="fin", prob=1, emission=0}}, initial="ini", final="fin" }) phone_ini = trainer:model({ name = "", transitions={{from="ini", to="fin", prob=1, emission=0}}, initial="ini", final="fin" }) phone_fin = trainer:model({ name = "", transitions={{from="ini", to="fin", prob=1, emission=0}}, initial="ini", final="fin" }) trainer:add_to_dict(desc_ngrama) trainer:add_to_dict(desc_a) trainer:add_to_dict(desc_b) trainer:add_to_dict(desc_c) trainer:add_to_dict(phone_a) trainer:add_to_dict(phone_b) trainer:add_to_dict(phone_c) trainer:add_to_dict(phone_w) trainer:add_to_dict(phone_ini) trainer:add_to_dict(phone_fin) m = trainer.models["mini.arpa"]:generate_C_model() m:print_dot() april-ann-0.4.1/packages/hmm_trainer/test/test_hmm-output.log000066400000000000000000000022541263004425400243230ustar00rootroot000000000000001 -> 0.5,0.20000000298023,0.10000000149012,0.30000001192093 2 -> 0.40000000596046,0.30000001192093,0.89999997615814,0.60000002384186 3 -> 0.30000001192093,0.10000000149012,0.20000000298023,0.69999998807907 4 -> 0.20000000298023,0.40000000596046,0.60000002384186,0.10000000149012 5 -> 0.5,0.30000001192093,0.20000000298023,0.5 6 -> 0.20000000298023,0.10000000149012,0.10000000149012,0.40000000596046 el clon 1 -> 0.5,0.20000000298023,0.10000000149012,0.30000001192093 2 -> 0.40000000596046,0.30000001192093,0.89999997615814,0.60000002384186 3 -> 0.30000001192093,0.10000000149012,0.20000000298023,0.69999998807907 4 -> 0.20000000298023,0.40000000596046,0.60000002384186,0.10000000149012 5 -> 0.5,0.30000001192093,0.20000000298023,0.5 6 -> 0.20000000298023,0.10000000149012,0.10000000149012,0.40000000596046 ------------------------------------ begin expectation probamos fb: viterbi fin llamada viterbi mprob= -7.982993,str: 'de1a2 de2a4 de4a4 de4a2 de2a4 de4a4 de4a2 de2a3' end expectation las emisiones tras aplicar viterbi: 1 -> 1,0,0,0 (1) 2 -> 0,0,1,0 (3) 3 -> 0,0,0,1 (4) 4 -> 0,0,1,0 (3) 5 -> 0,0,0,1 (4) 6 -> 0,1,0,0 (2) 0.16666665673256,0.26506406068802,0.28042408823967,0.28784519433975 april-ann-0.4.1/packages/hmm_trainer/test/test_hmm.lua000066400000000000000000000042361263004425400227670ustar00rootroot00000000000000 -- print"alineamiento inicial" -- ---------------------------------------------------------------------- -- a = hmm_trainer.initial_emission_alignment({1,2,3,4},10) -- ---------------------------------------------------------------------- -- for i,j in dataset.matrix(a):patterns() do -- printf("%2d -> %s\n",i,string.join(j,",")) -- end -- os.exit(0) m = matrix.fromString[[ * 4 ascii 0.5 0.2 0.1 0.3 0.4 0.3 0.9 0.6 0.3 0.1 0.2 0.7 0.2 0.4 0.6 0.1 0.5 0.3 0.2 0.5 0.2 0.1 0.1 0.4 ]] m2 = m:clone() mseq = matrix(m:dim()[1]) for i,j in dataset.matrix(m):patterns() do printf("%d -> %s\n",i,string.join(j,",")) end print"el clon" for i,j in dataset.matrix(m2):patterns() do printf("%d -> %s\n",i,string.join(j,",")) end print"------------------------------------" ------------------------------------------- --hmm_trainer.to_log(m) ------------------------------------------- -- for i,j in dataset.matrix(m):patterns() do -- printf("%d -> %s\n",i,string.join(j,",")) -- end t = HMMTrainer.trainer() -- :new{num_emissions=4, num_states=4, num_transitions=6} m1 = t:model{ name="test model", transitions={ {from="1", to="2", prob=1, emission=1, output="de1a2"}, {from="2", to="2", prob=0.3, emission=2, output="de2a2"}, {from="2", to="3", prob=0.3, emission=2, output="de2a3"}, {from="2", to="4", prob=0.4, emission=3, output="de2a4"}, {from="4", to="2", prob=0.5, emission=0, output="de4a2"}, {from="4", to="4", prob=0.5, emission=4, output="de4a4"} }, initial="1", final="3" } print"begin expectation" t.trainer:begin_expectation() m1_C = m1:generate_C_model() print"probamos fb:" m1_C:forward_backward{ input_emission=m } print"viterbi" mprob, str = m1_C:viterbi{ input_emission = m, do_expectation = true, output_emission = m, output_emission_seq = mseq, } print"fin llamada viterbi" printf("mprob= %f,str: '%s'\n",mprob,str); print"end expectation" t.trainer:end_expectation() mseqds = dataset.matrix(mseq) print"las emisiones tras aplicar viterbi:" for i,j in dataset.matrix(m):patterns() do printf("%d -> %s (%d)\n",i,string.join(j,","),mseqds:getPattern(i)[1]) end kk = t.trainer:get_a_priori_emissions() print(table.concat(kk,",")) april-ann-0.4.1/packages/hmm_trainer/test/test_tree-output.log000066400000000000000000000022521263004425400244770ustar00rootroot00000000000000digraph automata { 0 [label="0"]; 1 [label="1"]; 2 [label="2"]; 3 [label="3"]; 4 [label="4"]; 5 [label="5"]; 6 [label="6"]; 7 [label="7"]; 8 [label="8"]; 9 [label="9"]; 10 [label="10"]; 11 [label="11"]; 12 [label="12"]; 13 [label="13"]; 14 [label="14"]; 15 [label="15"]; 16 [label="16"]; 16 -> 14 [label="<17> -1/1.000000/"]; 14 -> 1 [label="<18> -1/1.000000/caso"]; 13 -> 11 [label="<7> -1/1.000000/"]; 11 -> 1 [label="<13> -1/1.000000/casa"]; 10 -> 8 [label="<11> -1/1.000000/"]; 8 -> 12 [label="<12> -1/1.000000/"]; 8 -> 15 [label="<14> -1/1.000000/"]; 15 -> 16 [label="<15> 3/0.500000/"]; 15 -> 15 [label="<16> 3/0.500000/"]; 12 -> 13 [label="<5> 1/0.500000/"]; 12 -> 12 [label="<6> 1/0.500000/"]; 7 -> 5 [label="<7> -1/1.000000/"]; 5 -> 9 [label="<8> -1/1.000000/"]; 9 -> 10 [label="<9> 2/0.500000/"]; 9 -> 9 [label="<10> 2/0.500000/"]; 4 -> 2 [label="<3> -1/1.000000/"]; 2 -> 6 [label="<4> -1/1.000000/"]; 6 -> 7 [label="<5> 1/0.500000/"]; 6 -> 6 [label="<6> 1/0.500000/"]; 0 -> 3 [label="<0> -1/1.000000/"]; 3 -> 4 [label="<1> 0/0.500000/"]; 3 -> 3 [label="<2> 0/0.500000/"]; } april-ann-0.4.1/packages/hmm_trainer/test/test_tree.lua000066400000000000000000000012471263004425400231440ustar00rootroot00000000000000trainer = HMMTrainer.trainer() for i,letra in ipairs{"c","a","s","o"} do lettermodel = trainer:model{ name = letra, initial = "ini", final = "fin", transitions = { {from="ini", to="1", emission=0, prob=1}, {from="1", to="2", emission=i, id=letra.."12", prob=0.5}, {from="1", to="1", emission=i, id=letra.."11", prob=0.5}, {from="2", to="fin", emission=0, id=letra.."2f", prob=1}, } } trainer:add_to_dict(lettermodel) end vocabulario = { "casa", "caso", } arbol = HMMTrainer.utils.strtable2tree(vocabulario) modelarbol = trainer:model(arbol) modelarbol_c = modelarbol:generate_C_model() modelarbol_c:print_dot() april-ann-0.4.1/packages/hmm_trainer/test/ver_error.lua000066400000000000000000000243071263004425400231550ustar00rootroot00000000000000function generate_models_from_alphabet(alphabet) local result = {} local i=1 local chr while i<= string.len(alphabet) do chr = string.sub(alphabet,i,i) result[chr]=generate_model(chr, 3*(i-1)+1, 0.5, 0.5, 0.5) i=i+1 end return result end function generate_alphabet_from_wordlist(wordlist) local alphabet={} local i local chr local result="" for _, word in pairs(wordlist) do i=1 while i <= string.len(word) do chr=string.sub(word, i,i) alphabet[chr]=true i=i+1 end end for k,v in pairs(alphabet) do result=result..k end return result end function generate_models_from_wordlist(wordlist, alphabet_models) local result = {} for _,word in pairs(wordlist) do result[word]=str2model(word, alphabet_models) end return result end function normalizar_mdt(lista_matrices) local utable = {} for i,mat in pairs(lista_matrices) do table.insert(utable,dataset.matrix(mat)) end local dts = dataset.union(utable) local lctable = {} local m,dt m,dt = dts:mean_deviation() for i=1,dts:patternSize() do table.insert(lctable,{{0,-m[i]/dt[i]},{i,1/dt[i]}}) end local daux = dataset.linearcomb(dts,lctable) -- normalizamos for i=1,dts:numPatterns() do dts:putPattern(i,daux:getPattern(i)) end end function normalizar_minmax(lista_matrices) local utable = {} for i,mat in pairs(lista_matrices) do table.insert(utable,dataset.matrix(mat)) end local dts = dataset.union(utable) local lctable = {} local m,dt mi,ma = dts:min_max() for i=1,dts:patternSize() do local r = 1/(ma[i]-mi[i]) table.insert(lctable,{{0,-mi[i]},{i,r}}) end local daux = dataset.linearcomb(dts,lctable) -- normalizamos for i=1,dts:numPatterns() do dts:putPattern(i,daux:getPattern(i)) end end function load_list_images(filename) local name = {} local image = {} local file=io.open(filename) for l in file:lines() do local t = string.tokenize(l,"\t") if (t[1]~=nil and t[2]~=nil) then table.insert(image,t[1]) table.insert(name,t[2]) end end file:close() return name,image end -- recibe una tabla con los nombres de fichero de las imagenes y la -- cadena con los parametros, -- devuelve una tabla con los parametros function load_and_param_images(imagetable, params) local params_table = {} for i, imgname in ipairs(imagetable) do printf("loading %s ...\n", IMG_DIR.."/"..imgname) local img = Image.load_pgm_gz(IMG_DIR.."/"..imgname) table.insert(params_table, param.extract(img, params)) -- = param_moises(img_s) end normalizar_mdt(params_table) --normalizar_minmax(params_table) return params_table end function param_m2d(mat,ctxtizq,ctxtder) local conf = { patternSize = {ctxtizq+1+ctxtder,mat:dim()[2]}, offset = {-ctxtizq,0}, numSteps = {mat:dim()[1],1}, stepSize = {1,1}, -- second is don't care } --print("mat es",mat,table.concat(mat:dim(),"x")) return dataset.matrix(mat,conf) end -- recibe dos tablas, la primera con el nombre y la segunda con la -- matriz de parametros de la imagen correspondiente en el mismo -- indice function images_each_word(name_t, param_t,ctxtizq,ctxtder) local iew = {} for i, name in ipairs(name_t) do if iew[name] == nil then iew[name] = {} end table.insert(iew[name], param_m2d(param_t[i],ctxtizq,ctxtder)) end return iew end function classify_word(models,emismatrix) local minscore,bestword for w,m in pairs(models) do local scr = m:viterbi(emismatrix) if (minscore==nil or minscore>scr) then minscore=scr bestword=w end end return bestword,minscore end -- Devuelve una tabla con la secuencia de emisiones -- de una palabra function word_emissions(word, alphabet) local result={} local chr local emission local i=1 while i <= string.len(word) do chr=string.sub(word,i,i) emission = 3*(string.find(alphabet, chr, 1, true) - 1)+1 result[3*(i-1)+1] = emission result[3*(i-1)+2] = emission+1 result[3*(i-1)+3] = emission+2 i = i+1 end return result end ---------------------------------------------------------------------- -- programa ppal ---------------------------------------------------------------------- PARAMETROS = "Tqah" --"Tsiepdqa" filename = arg[1] IMG_DIR = arg[2] -- Cargamos la lista de imagenes name_tbl,imagename_tbl = load_list_images(filename) -- Parametrizamos las imagenes params_tbl = load_and_param_images(imagename_tbl, PARAMETROS) -- En caso de querer fijar un alfabeto,modificar aqui alphabet=generate_alphabet_from_wordlist(name_tbl) -- Generamos los modelos para cada letra y para cada palabra, model_tbl=generate_models_from_alphabet(alphabet) temp_mtbl=generate_models_from_wordlist(name_tbl, model_tbl) for k,v in pairs(temp_mtbl) do -- Evitamos reemplazar los modelos de las letras individuales -- porque valen igual y tienen menos estados "dummy" if not model_tbl[k] then model_tbl[k]=v end end -- Generamos el modelo en arbol tree = strtable2tree(name_tbl) tree = expand_model(tree, model_tbl) function print_model(m) print("name=", m.name) print("transitions={") for _,t in pairs(m.transitions) do printf("{from=%s, to=%s, prob=%s, emission=%s, output=%s, id=%s}\n", t.from, t.to, t.prob, t.emission or "nil", t.output or "", t.id or "nil") end print"}" print("initial=", m.initial) print("final=", m.final) end print_model(tree) model_tbl["__tree"]=tree -- ahora vamos a entrenar, para ello necesitamos una red neuronal con -- tantas entradas como: num_parametros * (ctxt_izq+1+ctxt_der) num_parametros = string.len(PARAMETROS) ctxt_izq = 5 ctxt_der = 5 iew = images_each_word(name_tbl,params_tbl,ctxt_izq,ctxt_der) -- iew es una tabla que a cada palabra del lexico le asocia una lista -- de imagenes ya parametrizadas en forma de datasets -- numero de salidas de la red neuronal: num_salidas = 3*string.len(alphabet) -- dataset auxiliar: casiuno = 1 -- 0.9 casicero = (1-casiuno)/(num_salidas-1) ds_ident = dataset.identity(num_salidas,casicero,casiuno) ma_alignments = {} -- matrices ds_alignments = {} -- matrices for word,dstable in pairs(iew) do -- ahora generamos una tabla similar a iew, reemplazamos cada -- dataset por una matriz de dim 1 y de talla el numPatterns, -- inicializamos la matriz, la metemos en un dataset.index ma_alignments[word] = {} ds_alignments[word] = {} for i,ds in ipairs(dstable) do local seq_emission = word_emissions(word, alphabet) local a = hmm_trainer.initial_emission_alignment(seq_emission, ds:numPatterns()) local b = dataset.indexed(dataset.matrix(a), {ds_ident}):toMatrix() table.insert(ma_alignments[word], b) table.insert(ds_alignments[word], dataset.matrix(b) ) -- printf("word %s seqemission = %s\nalignment:\n",word,table.concat(seq_emission,",")) -- for r,s in dataset.matrix(b):patterns() do -- printf("%3d -> %s\n",r,table.concat(s,",")) -- end end end -- creamos la red neuronal... semilla = 1234 num_entradas = num_parametros*(1+ctxt_izq+ctxt_der) num_ocultas1 = 50 num_ocultas2 = 100 aleat = random(semilla) lared = Mlp(string.format("%d inputs %d logistic %d logistic %d softmax", num_entradas, num_ocultas1, num_ocultas2, num_salidas)) lared:generate(aleat, -0.7, 0.7) -- creamos el HMMTrainer y los modelos trainer, models = create_hmm_trainer_from_models_list(model_tbl, num_salidas) -- recopilamos datos para entrenar: todas_entradas = {} todas_salidas = {} for word,dstable in pairs(iew) do local t = ds_alignments[word] for i,ds in ipairs(dstable) do table.insert(todas_entradas,ds) table.insert(todas_salidas,t[i]) end end train_input = dataset.union(todas_entradas) train_output = dataset.union(todas_salidas) datosentrenar = { learning_rate = 0.2, momentum = 0.1, weight_decay = 1e-7, input_dataset = train_input, output_dataset = train_output, shuffle = aleat } printf([[ Entrenamos una red neuronal con %d patrones de talla %d y %d valores de salida ]], train_input:numPatterns(), train_input:patternSize(), train_output:patternSize()) veces_train = 0 -- debe ser 20 veces_em = 500 printf("medias: %s\n",table.concat(train_output:mean(),",")) trainer.trainer:set_a_priori_emissions(train_output:mean()) for iterem = 1,veces_em do printf("------------------------------\nIteracion %d de EM\n", iterem) -- entrenamos la red neuronal for epoch = 1,veces_train do errortrain = lared:train(datosentrenar) printf("em %4d epoch %4d mse_train %.7f\n", iterem,epoch,errortrain) end veces_train = 10 datosentrenar.learning_rate = 0.05 datosentrenar.momentum = 0.05 aciertos = 0 totales = 0 -- la utilizamos para realizar alineamiento forzado viterbi: trainer.trainer:begin_expectation() for word,dstable in pairs(iew) do themodel = models[word] for i,mat in ipairs(ma_alignments[word]) do -- reentrenar la cadena mat: -- primero, generar la matriz con las emisiones: local dsparam = dstable[i] --print("antes de aplicar use:") --for i,j in ds_alignments[word][i]:patterns() do -- printf("%3d -> %s\n",i,table.concat(j,",")) --end -- utilizarla con la red neuronal --[[ lared:use_dataset{ input_dataset = dsparam, output_dataset = ds_alignments[word][i] } --]] --print("despues de aplicar use:") --for i,j in ds_alignments[word][i]:patterns() do -- printf("%3d -> %s\n",i,table.concat(j,",")) --end --rword,minscr = classify_word(model,matemision) printf("mat es una matrix %s\n",table.concat(mat:dim(),"x")) prob, rword = models["__tree"]:viterbi{ input_emission = mat, do_expectation = false, } fprintf(io.stderr,"%-10s -> %-10s %f\n",word,rword,prob) os.exit(0) totales = totales+1 if (word == rword) then aciertos = aciertos+1 end themodel:viterbi{ input_emission = mat, do_expectation = true, output_emission= mat } end end trainer.trainer:end_expectation() printf("Porcentaje de aciertos entrenamiento: %.2f%%\n", 100*aciertos/totales) filenet = string.format("hmm%d.net",iterem) print("salvando "..filenet) lared:save(filenet,"ascii") end april-ann-0.4.1/packages/imaging/000077500000000000000000000000001263004425400165665ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/Image/000077500000000000000000000000001263004425400176105ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/Image/binding/000077500000000000000000000000001263004425400212225ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/Image/binding/bind_image.lua.cc000066400000000000000000000254471263004425400244030ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "bind_image_RGB.h" using AprilUtils::constString; //BIND_END //BIND_HEADER_H #include "utilMatrixFloat.h" #include "utilImageFloat.h" #include "bind_matrix.h" #include "bind_affine_transform.h" #include #include "datasetFloat.h" #include "dataset.h" #include "bind_dataset.h" using namespace Imaging; //BIND_END //BIND_LUACLASSNAME ImageFloat Image //BIND_CPP_CLASS ImageFloat //BIND_CONSTRUCTOR ImageFloat // este constructor recibe una matrix { int argn; argn = lua_gettop(L); // number of arguments Basics::MatrixFloat *mat; LUABIND_GET_PARAMETER(1, MatrixFloat, mat); if (mat->getNumDim() != 2) { lua_pushstring(L,"image : matrix of dimension 2 is required"); lua_error(L); } int width=mat->getDimSize(1); int height=mat->getDimSize(0); int offsetx=0; int offsety=0; if (argn == 2 && lua_isstring(L,2)) { // format x{+-}{+-} constString cs = constString(lua_tostring(L,2),lua_strlen(L,2)); if (!(cs.extract_int(&width, 10, "x") && (cs.skip(1),cs.extract_int(&height, 10, "+-")) && (cs.skip(1),cs.extract_int(&offsetx, 10, "+-")) && (cs.skip(1),cs.extract_int(&offsety)))) { lua_pushstring(L,"image crop: bad format string"); lua_error(L); } } if (argn == 5) { LUABIND_GET_PARAMETER(2, int, width); LUABIND_GET_PARAMETER(3, int, height); LUABIND_GET_PARAMETER(4, int, offsetx); LUABIND_GET_PARAMETER(5, int, offsety); } obj = new ImageFloat(mat,width,height,offsetx,offsety); LUABIND_RETURN(ImageFloat, obj); } //BIND_END //BIND_DESTRUCTOR ImageFloat { } //BIND_END //BIND_METHOD ImageFloat crop { int argn = lua_gettop(L); // number of arguments int width=0,height=0,offsetx=0,offsety=0; if (argn == 1) { if (!lua_isstring(L,1)) { lua_pushstring(L,"image crop: 1 argument must be x{+-}{+-}"); lua_error(L); } constString cs = constString(lua_tostring(L,1),lua_strlen(L,1)); if (!(cs.extract_int(&width, 10, "x") && (cs.skip(1),cs.extract_int(&height, 10, "+-")) && (cs.skip(1),cs.extract_int(&offsetx, 10, "+-")) && (cs.skip(1),cs.extract_int(&offsety)))) { lua_pushstring(L,"image crop: bad format string"); lua_error(L); } } else if (argn == 4) { LUABIND_GET_PARAMETER(1, int, width); LUABIND_GET_PARAMETER(2, int, height); LUABIND_GET_PARAMETER(3, int, offsetx); LUABIND_GET_PARAMETER(4, int, offsety); } else { LUABIND_ERROR("invalid number of arguments. You must use crop(\"x{+-}{+-}\") or " "crop(width, height, x, y)."); } ImageFloat *cropimage = obj->crop(width,height,offsetx,offsety); LUABIND_RETURN(ImageFloat, cropimage); } //BIND_END //BIND_METHOD ImageFloat info { LUABIND_ERROR("ERROR: ImageFloat.info() is deprecated\n" " Use matrix() or geometry() as needed.\n"); LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(MatrixFloat, obj->getMatrix()); LUABIND_RETURN(int, obj->width()); LUABIND_RETURN(int, obj->height()); LUABIND_RETURN(int, obj->offset_width()); LUABIND_RETURN(int, obj->offset_height()); } //BIND_END //BIND_METHOD ImageFloat matrix { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(MatrixFloat, obj->getMatrix()); } //BIND_END //BIND_METHOD ImageFloat geometry { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(int, obj->width()); LUABIND_RETURN(int, obj->height()); LUABIND_RETURN(int, obj->offset_width()); LUABIND_RETURN(int, obj->offset_height()); } //BIND_END //BIND_METHOD ImageFloat getpixel { int x,y; LUABIND_CHECK_ARGN(==,2); LUABIND_GET_PARAMETER(1, int, x); LUABIND_GET_PARAMETER(2, int, y); float pixelvalue = obj->operator()(x,y); LUABIND_RETURN(float, pixelvalue); } //BIND_END //BIND_METHOD ImageFloat putpixel { int x,y; float pixelvalue; LUABIND_CHECK_ARGN(==,3); LUABIND_GET_PARAMETER(1, int, x); LUABIND_GET_PARAMETER(2, int, y); LUABIND_GET_PARAMETER(3, float, pixelvalue); // check range if ((pixelvalue < 0) || (pixelvalue > 1)) { LUABIND_ERROR("pixel value must be in range [0,1]"); } obj->operator()(x,y) = pixelvalue; return 0; } //BIND_END //BIND_METHOD ImageFloat clone { LUABIND_CHECK_ARGN(==,0); ImageFloat *theclone = obj->clone(); LUABIND_RETURN(ImageFloat, theclone); } //BIND_END //BIND_METHOD ImageFloat projection_h { LUABIND_CHECK_ARGN(==,0); Basics::MatrixFloat *mat; obj->projection_h(&mat); LUABIND_RETURN(MatrixFloat, mat); } //BIND_END //BIND_METHOD ImageFloat projection_v { LUABIND_CHECK_ARGN(==,0); Basics::MatrixFloat *mat; obj->projection_v(&mat); LUABIND_RETURN(MatrixFloat, mat); } //BIND_END //BIND_METHOD ImageFloat shear_h { float angle; float default_value; const char *units; LUABIND_CHECK_ARGN(>=,1); LUABIND_GET_PARAMETER(1, float, angle); LUABIND_GET_OPTIONAL_PARAMETER(2, string, units, "rad"); LUABIND_GET_OPTIONAL_PARAMETER(3, float, default_value, CTEBLANCO); constString csopt = constString(units); if (csopt == "deg") angle = angle/180.0f*M_PI; else if (csopt == "grad") angle = angle/200.0f*M_PI; ImageFloat *result = obj->shear_h(angle, default_value); LUABIND_RETURN(ImageFloat, result); } //BIND_END //BIND_METHOD ImageFloat shear_h_inplace { float angle; float default_value; const char *units; LUABIND_CHECK_ARGN(>=,1); LUABIND_GET_PARAMETER(1, float, angle); LUABIND_GET_OPTIONAL_PARAMETER(2, string, units, "rad"); LUABIND_GET_OPTIONAL_PARAMETER(3, float, default_value, CTEBLANCO); constString csopt = constString(units); if (csopt == "deg") angle = angle/180.0f*M_PI; else if (csopt == "grad") angle = angle/200.0f*M_PI; obj->shear_h_inplace(angle, default_value); return 0; } //BIND_END //BIND_METHOD ImageFloat min_bounding_box { float threshold; LUABIND_CHECK_ARGN(==,1); LUABIND_GET_PARAMETER(1, float, threshold); int w,h,x,y; obj->min_bounding_box(threshold, &w, &h, &x, &y); LUABIND_RETURN(int, w); LUABIND_RETURN(int, h); LUABIND_RETURN(int, x); LUABIND_RETURN(int, y); } //BIND_END //BIND_METHOD ImageFloat copy { ImageFloat *src; int dst_x, dst_y; LUABIND_CHECK_ARGN(==, 3); LUABIND_GET_PARAMETER(1, ImageFloat, src); LUABIND_GET_PARAMETER(2, int, dst_x); LUABIND_GET_PARAMETER(3, int, dst_y); obj->copy(src, dst_x, dst_y); return 0; } //BIND_END //BIND_METHOD ImageFloat substract { ImageFloat *img; LUABIND_CHECK_ARGN(==,1); LUABIND_GET_PARAMETER(1, ImageFloat, img); ImageFloat *res = obj->substract_image(img, 0.0, 1.0); LUABIND_RETURN(ImageFloat, res); } //BIND_END //BIND_METHOD ImageFloat threshold { LUABIND_CHECK_ARGN(==,2); float low, high; LUABIND_GET_PARAMETER(1, float, low); LUABIND_GET_PARAMETER(2, float, high); obj->threshold_image(low, high,0.0, 1.0); return 0; } //BIND_END //BIND_METHOD ImageFloat rotate90cw { int param; // must be +1 or -1 LUABIND_CHECK_ARGN(==,1); LUABIND_GET_PARAMETER(1, int, param); ImageFloat *res = 0; if (param == 1) res = obj->rotate90_cw(); else if (param == -1) res = obj->rotate90_ccw(); else{ LUABIND_ERROR("the argument of rotate90cw must be +1 or -1"); } LUABIND_RETURN(ImageFloat, res); } //BIND_END //BIND_METHOD ImageFloat invert_colors { LUABIND_CHECK_ARGN(==,0); ImageFloat *res = obj->invert_colors(); LUABIND_RETURN(ImageFloat, res); } //BIND_END //BIND_METHOD ImageFloat remove_blank_columns { LUABIND_CHECK_ARGN(==,0); ImageFloat *res; res=obj->remove_blank_columns(); LUABIND_RETURN(ImageFloat, res); } //BIND_END //BIND_METHOD ImageFloat add_rows { LUABIND_CHECK_ARGN(==,3); int top_rows, bottom_rows; float value = 0.0; LUABIND_GET_PARAMETER(1, int, top_rows); LUABIND_GET_PARAMETER(2, int, bottom_rows); LUABIND_GET_PARAMETER(3, float, value); ImageFloat *res; res=obj->add_rows(top_rows, bottom_rows, value); LUABIND_RETURN(ImageFloat, res); } //BIND_END //BIND_METHOD ImageFloat convolution5x5 { LUABIND_CHECK_ARGN(>,0); LUABIND_CHECK_ARGN(<,3); LUABIND_CHECK_PARAMETER(1, table); float kernel[25]; LUABIND_TABLE_TO_VECTOR(1, float, kernel, 25); ImageFloat *res; if (lua_gettop(L) == 1) res = obj->convolution5x5(kernel); else { float default_value; LUABIND_GET_PARAMETER(2, float, default_value); res = obj->convolution5x5(kernel, default_value); } LUABIND_RETURN(ImageFloat, res); } //BIND_END //BIND_METHOD ImageFloat resize { LUABIND_CHECK_ARGN(==, 2); int x, y; LUABIND_GET_PARAMETER(1, int, x); LUABIND_GET_PARAMETER(2, int, y); ImageFloat *res = obj->resize(x,y); LUABIND_RETURN(ImageFloat, res); } //BIND_END //BIND_METHOD ImageFloat upsample { LUABIND_CHECK_ARGN(==, 2); int x, y; LUABIND_GET_PARAMETER(1, int, x); LUABIND_GET_PARAMETER(2, int, y); ImageFloat *res = obj->upsample(x,y); LUABIND_RETURN(ImageFloat, res); } //BIND_END //BIND_METHOD ImageFloat affine_transform { Basics::AffineTransform2D *trans; float default_value; int offset_x, offset_y; ImageFloat *res; LUABIND_CHECK_ARGN(==, 2); LUABIND_GET_PARAMETER(1, AffineTransform2D, trans); LUABIND_GET_PARAMETER(2, float, default_value); res = obj->affine_transform(trans, default_value, &offset_x, &offset_y); LUABIND_RETURN(ImageFloat, res); LUABIND_RETURN(int, offset_x); LUABIND_RETURN(int, offset_y); } //BIND_END //BIND_METHOD ImageFloat to_RGB { LUABIND_CHECK_ARGN(==,0); ImageFloatRGB *res = grayscale_to_RGB(obj); LUABIND_RETURN(ImageFloatRGB, res); } //BIND_END //BIND_METHOD ImageFloat comb_lineal_forward { LUABIND_CHECK_ARGN(==, 7); int x, y, alto, ancho, minialto, miniancho, output_size; Basics::LinearCombConfFloat *cl; LUABIND_GET_PARAMETER(1, int, x); LUABIND_GET_PARAMETER(2, int, y); LUABIND_GET_PARAMETER(3, int, ancho); LUABIND_GET_PARAMETER(4, int, alto); LUABIND_GET_PARAMETER(5, int, miniancho); LUABIND_GET_PARAMETER(6, int, minialto); LUABIND_GET_PARAMETER(7, LinearCombConfFloat, cl); Basics::MatrixFloat *res = obj->comb_lineal_forward(x,y,ancho, alto, miniancho, minialto, cl); LUABIND_RETURN(MatrixFloat, res); } //BIND_END april-ann-0.4.1/packages/imaging/Image/binding/bind_image_RGB.lua.cc000066400000000000000000000224041263004425400250630ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "bind_image.h" using namespace AprilUtils; using namespace AprilMath; using namespace Basics; //BIND_END //BIND_HEADER_H #include "utilMatrixFloat.h" #include "utilImageFloat.h" #include "bind_matrix.h" #include "bind_affine_transform.h" #include using namespace Imaging; //BIND_END //BIND_LUACLASSNAME ImageFloatRGB ImageRGB //BIND_CPP_CLASS ImageFloatRGB //BIND_CONSTRUCTOR ImageFloatRGB // este constructor recibe una matrix { LUABIND_CHECK_ARGN(==,1); Basics::MatrixFloat *img; LUABIND_GET_PARAMETER(1, MatrixFloat, img); if (img->getNumDim() != 3) LUABIND_ERROR("Needs a matrix with 3 dimensions"); if (img->getDimSize(2) != 3) LUABIND_ERROR("Needs a matrix with 3 components (R,G,B) at the 3rd dimension"); if (!img->isSimple()) LUABIND_ERROR("ImageRGB needs a simple matrix: row_major and contiguous\n"); GPUMirroredMemoryBlock *float_rgb_mem; float_rgb_mem = img->getRawDataAccess()->reinterpretAs(); int dims[2] = { img->getDimSize(0), img->getDimSize(1) }; Basics::Matrix *img_rgb = new Basics::Matrix(2, dims, float_rgb_mem); // obj = new ImageFloatRGB(img_rgb); LUABIND_RETURN(ImageFloatRGB, obj); } //BIND_END //BIND_FUNCTION ImageRGB.empty { int w,h; LUABIND_CHECK_ARGN(==,2); LUABIND_GET_PARAMETER(1, int, w); LUABIND_GET_PARAMETER(2, int, h); Basics::Matrix *m = new Basics::Matrix(2, w, h); ImageFloatRGB *result = new ImageFloatRGB(m); LUABIND_RETURN(ImageFloatRGB, result); } //BIND_END //BIND_DESTRUCTOR ImageFloatRGB { } //BIND_END //BIND_METHOD ImageFloatRGB crop { int argn = lua_gettop(L); // number of arguments int width=0,height=0,offsetx=0,offsety=0; if (argn == 1) { if (!lua_isstring(L,1)) { lua_pushstring(L,"image crop: 1 argument must be x{+-}{+-}"); lua_error(L); } constString cs = constString(lua_tostring(L,1),lua_strlen(L,1)); if (!(cs.extract_int(&width, 10, "x") && (cs.skip(1),cs.extract_int(&height, 10, "+-")) && (cs.skip(1),cs.extract_int(&offsetx, 10, "+-")) && (cs.skip(1),cs.extract_int(&offsety)))) { lua_pushstring(L,"image crop: bad format string"); lua_error(L); } } else if (argn == 4) { LUABIND_GET_PARAMETER(1, int, width); LUABIND_GET_PARAMETER(2, int, height); LUABIND_GET_PARAMETER(3, int, offsetx); LUABIND_GET_PARAMETER(4, int, offsety); } else { LUABIND_ERROR("invalid number of arguments. You must use crop(\"x{+-}{+-}\") or " "crop(width, height, x, y)."); } ImageFloatRGB *cropimage = obj->crop(width,height,offsetx,offsety); LUABIND_RETURN(ImageFloatRGB, cropimage); } //BIND_END //BIND_METHOD ImageFloatRGB info { fprintf(stderr, "WARNING: ImageFloatRGB.info() is deprecated\n" " Use matrix() or geometry() as needed.\n"); LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(string, ""); LUABIND_RETURN(int, obj->width()); LUABIND_RETURN(int, obj->height()); LUABIND_RETURN(int, obj->offset_width()); LUABIND_RETURN(int, obj->offset_height()); } //BIND_END //BIND_METHOD ImageFloatRGB matrix { LUABIND_CHECK_ARGN(==,0); Basics::Matrix *img_rgb = obj->getMatrix(); AprilMath::GPUMirroredMemoryBlock *mat_mem; mat_mem = img_rgb->getRawDataAccess()->reinterpretAs(); int dims[3] = { img_rgb->getDimSize(0), img_rgb->getDimSize(1), 3 }; Basics::MatrixFloat *output = new Basics::MatrixFloat(3, dims, mat_mem); LUABIND_RETURN(MatrixFloat, output); } //BIND_END //BIND_METHOD ImageFloatRGB geometry { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(int, obj->width()); LUABIND_RETURN(int, obj->height()); LUABIND_RETURN(int, obj->offset_width()); LUABIND_RETURN(int, obj->offset_height()); } //BIND_END //BIND_METHOD ImageFloatRGB getpixel { int x,y; LUABIND_CHECK_ARGN(==,2); LUABIND_GET_PARAMETER(1, int, x); LUABIND_GET_PARAMETER(2, int, y); FloatRGB rgb = obj->operator()(x,y); LUABIND_RETURN(float, rgb.r); LUABIND_RETURN(float, rgb.g); LUABIND_RETURN(float, rgb.b); } //BIND_END //BIND_METHOD ImageFloatRGB putpixel { int x,y; float r, g, b; LUABIND_CHECK_ARGN(==,5); LUABIND_GET_PARAMETER(1, int, x); LUABIND_GET_PARAMETER(2, int, y); LUABIND_GET_PARAMETER(3, float, r); LUABIND_GET_PARAMETER(4, float, g); LUABIND_GET_PARAMETER(5, float, b); obj->operator()(x,y) = FloatRGB(r,g,b); return 0; } //BIND_END //BIND_METHOD ImageFloatRGB clone { LUABIND_CHECK_ARGN(==,0); ImageFloatRGB *theclone = obj->clone(); LUABIND_RETURN(ImageFloatRGB, theclone); } //BIND_END //BIND_METHOD ImageFloatRGB shear_h { float angle; float default_r, default_g, default_b; const char *units; LUABIND_CHECK_ARGN(>=,4); LUABIND_GET_PARAMETER(1, float, angle); LUABIND_GET_PARAMETER(2, float, default_r); LUABIND_GET_PARAMETER(3, float, default_g); LUABIND_GET_PARAMETER(4, float, default_b); LUABIND_GET_OPTIONAL_PARAMETER(5, string, units, "rad"); constString csopt = constString(units); if (csopt == "deg") angle = angle/180.0f*M_PI; else if (csopt == "grad") angle = angle/200.0f*M_PI; ImageFloatRGB *result = obj->shear_h(angle, FloatRGB(default_r, default_g, default_b)); LUABIND_RETURN(ImageFloatRGB, result); } //BIND_END //BIND_METHOD ImageFloatRGB shear_h_inplace { float angle; float default_r, default_g, default_b; const char *units; LUABIND_CHECK_ARGN(>=,4); LUABIND_GET_PARAMETER(1, float, angle); LUABIND_GET_PARAMETER(2, float, default_r); LUABIND_GET_PARAMETER(3, float, default_g); LUABIND_GET_PARAMETER(4, float, default_b); LUABIND_GET_OPTIONAL_PARAMETER(5, string, units, "rad"); constString csopt = constString(units); if (csopt == "deg") angle = angle/180.0f*M_PI; else if (csopt == "grad") angle = angle/200.0f*M_PI; obj->shear_h_inplace(angle, FloatRGB(default_r, default_g, default_b)); return 0; } //BIND_END //BIND_METHOD ImageFloatRGB copy { ImageFloatRGB *src; int dst_x, dst_y; LUABIND_CHECK_ARGN(==, 3); LUABIND_GET_PARAMETER(1, ImageFloatRGB, src); LUABIND_GET_PARAMETER(2, int, dst_x); LUABIND_GET_PARAMETER(3, int, dst_y); obj->copy(src, dst_x, dst_y); return 0; } //BIND_END //BIND_METHOD ImageFloatRGB rotate90cw { int param; // must be +1 or -1 LUABIND_CHECK_ARGN(==,1); LUABIND_GET_PARAMETER(1, int, param); ImageFloatRGB *res = 0; if (param == 1) res = obj->rotate90_cw(); else if (param == -1) res = obj->rotate90_ccw(); else{ LUABIND_ERROR("the argument of rotate90cw must be +1 or -1"); } LUABIND_RETURN(ImageFloatRGB, res); } //BIND_END //BIND_METHOD ImageFloatRGB invert_colors { LUABIND_CHECK_ARGN(==,0); ImageFloatRGB *res = obj->invert_colors(); LUABIND_RETURN(ImageFloatRGB, res); } //BIND_END //BIND_METHOD ImageFloatRGB convolution5x5 { LUABIND_CHECK_ARGN(>,0); LUABIND_CHECK_ARGN(<,5); LUABIND_CHECK_PARAMETER(1, table); float kernel[25]; LUABIND_TABLE_TO_VECTOR(1, float, kernel, 25); ImageFloatRGB *res; if (lua_gettop(L) == 1) res = obj->convolution5x5(kernel); else { float default_r, default_g, default_b; LUABIND_GET_PARAMETER(2, float, default_r); LUABIND_GET_PARAMETER(3, float, default_g); LUABIND_GET_PARAMETER(4, float, default_b); res = obj->convolution5x5(kernel, FloatRGB(default_r, default_g, default_b)); } LUABIND_RETURN(ImageFloatRGB, res); } //BIND_END //BIND_METHOD ImageFloatRGB resize { LUABIND_CHECK_ARGN(==, 2); int x, y; LUABIND_GET_PARAMETER(1, int, x); LUABIND_GET_PARAMETER(2, int, y); ImageFloatRGB *res = obj->resize(x,y); LUABIND_RETURN(ImageFloatRGB, res); } //BIND_END //BIND_METHOD ImageFloatRGB affine_transform { Basics::AffineTransform2D *trans; float default_r, default_g, default_b; int offset_x, offset_y; ImageFloatRGB *res; LUABIND_CHECK_ARGN(==, 4); LUABIND_GET_PARAMETER(1, AffineTransform2D, trans); LUABIND_GET_PARAMETER(2, float, default_r); LUABIND_GET_PARAMETER(3, float, default_g); LUABIND_GET_PARAMETER(4, float, default_b); res = obj->affine_transform(trans, FloatRGB(default_r, default_g, default_b), &offset_x, &offset_y); LUABIND_RETURN(ImageFloatRGB, res); LUABIND_RETURN(int, offset_x); LUABIND_RETURN(int, offset_y); } //BIND_END //BIND_METHOD ImageFloatRGB to_grayscale { LUABIND_CHECK_ARGN(==,0); ImageFloat *res = RGB_to_grayscale(obj); LUABIND_RETURN(ImageFloat, res); } //BIND_END april-ann-0.4.1/packages/imaging/Image/c_src/000077500000000000000000000000001263004425400207015ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/Image/c_src/floatrgb.cc000066400000000000000000000127741263004425400230230ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "floatrgb.h" #include "matrix_ext.h" namespace Imaging { FloatRGB operator + (FloatRGB x, FloatRGB y) { return FloatRGB(x.r + y.r, x.g + y.g, x.b + y.b); } FloatRGB operator - (FloatRGB x, FloatRGB y) { return FloatRGB(x.r - y.r, x.g - y.g, x.b - y.b); } FloatRGB operator * (FloatRGB x, FloatRGB y) { return FloatRGB(x.r * y.r, x.g * y.g, x.b * y.b); } FloatRGB operator / (FloatRGB x, FloatRGB y) { return FloatRGB(x.r / y.r, x.g / y.g, x.b / y.b); } FloatRGB operator + (FloatRGB x, float y) { return x+FloatRGB(y); } FloatRGB operator - (FloatRGB x, float y) { return x-FloatRGB(y); } FloatRGB operator * (FloatRGB x, float y) { return x*FloatRGB(y); } FloatRGB operator / (FloatRGB x, float y) { return x/FloatRGB(y); } FloatRGB operator + (float x, FloatRGB y) { return FloatRGB(x)+y; } FloatRGB operator - (float x, FloatRGB y) { return FloatRGB(x)-y; } FloatRGB operator * (float x, FloatRGB y) { return FloatRGB(x)*y; } FloatRGB operator / (float x, FloatRGB y) { return FloatRGB(x)/y; } FloatRGB & operator += (FloatRGB &x, FloatRGB y) { x = x + y; return x; } FloatRGB & operator -= (FloatRGB &x, FloatRGB y) { x = x - y; return x; } FloatRGB & operator *= (FloatRGB &x, FloatRGB y) { x = x * y; return x; } FloatRGB & operator /= (FloatRGB &x, FloatRGB y) { x = x / y; return x; } FloatRGB & operator += (FloatRGB &x, float y) { x = x + y; return x; } FloatRGB & operator -= (FloatRGB &x, float y) { x = x - y; return x; } FloatRGB & operator *= (FloatRGB &x, float y) { x = x * y; return x; } FloatRGB & operator /= (FloatRGB &x, float y) { x = x / y; return x; } } // namespace Imaging namespace AprilUtils{ template<> Imaging::FloatRGB clamp(Imaging::FloatRGB val, Imaging::FloatRGB lower, Imaging::FloatRGB upper) { float r = clamp(val.r, lower.r, upper.r); float g = clamp(val.g, lower.g, upper.g); float b = clamp(val.b, lower.b, upper.b); return Imaging::FloatRGB(r,g,b); } } #include "copy.impl.h" namespace AprilMath { template void doCopy(int, const GPUMirroredMemoryBlock*, unsigned int, unsigned int, GPUMirroredMemoryBlock*, unsigned int, unsigned int, bool); namespace MatrixExt { namespace BLAS { template<> Basics::Matrix *matCopy(Basics::Matrix *dst, const Basics::Matrix *src) { if (!dst->sameDim(src)) ERROR_EXIT(128, "Incompatible matrix sizes\n"); Basics::Matrix::iterator dst_it(dst->begin()); Basics::Matrix::const_iterator src_it(src->begin()); while(dst_it != dst->end() && src_it != src->end()) { *dst_it = *src_it; ++dst_it; ++src_it; } return dst; } } namespace Initializers { template<> Basics::Matrix *matFill(Basics::Matrix *obj, const Imaging::FloatRGB value) { for (Basics::Matrix::iterator it(obj->begin()); it != obj->end(); ++it) { *it = value; } return obj; } } namespace Operations { template <> Basics::Matrix *matComplement(const Basics::Matrix *src, Basics::Matrix *dst) { april_assert( dst != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dst == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); if (!src->sameDim(dst)) ERROR_EXIT(128,"Incompatible matrix sizes\n"); Basics::Matrix::iterator dst_it(dst->begin()); for (Basics::Matrix::const_iterator src_it(src->begin()); src_it != dst->end(); ++src_it, ++dst_it) { *dst_it = 1.0f - *src_it; } return dst; } } } } april-ann-0.4.1/packages/imaging/Image/c_src/floatrgb.h000066400000000000000000000062331263004425400226560ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef FLOATRGB_H #define FLOATRGB_H #include "clamp.h" #include "matrix_ext.h" namespace Imaging { struct FloatRGB { float r,g,b; FloatRGB(): r(0.0f), g(0.0f), b(0.0f) {} FloatRGB(float r, float g, float b):r(r), g(g), b(b) {} explicit FloatRGB(float gray): r(gray), g(gray), b(gray) {} float to_grayscale() { return 0.3*r+0.59*g+0.11*b; } }; FloatRGB operator + (FloatRGB x, FloatRGB y); FloatRGB operator - (FloatRGB x, FloatRGB y); FloatRGB operator * (FloatRGB x, FloatRGB y); FloatRGB operator / (FloatRGB x, FloatRGB y); FloatRGB operator + (FloatRGB x, float y); FloatRGB operator - (FloatRGB x, float y); FloatRGB operator * (FloatRGB x, float y); FloatRGB operator / (FloatRGB x, float y); FloatRGB operator + (float x, FloatRGB y); FloatRGB operator - (float x, FloatRGB y); FloatRGB operator * (float x, FloatRGB y); FloatRGB operator / (float x, FloatRGB y); FloatRGB & operator += (FloatRGB &x, FloatRGB y); FloatRGB & operator -= (FloatRGB &x, FloatRGB y); FloatRGB & operator *= (FloatRGB &x, FloatRGB y); FloatRGB & operator /= (FloatRGB &x, FloatRGB y); FloatRGB & operator += (FloatRGB &x, float y); FloatRGB & operator -= (FloatRGB &x, float y); FloatRGB & operator *= (FloatRGB &x, float y); FloatRGB & operator /= (FloatRGB &x, float y); } // namespace Imaging namespace AprilUtils{ template<> Imaging::FloatRGB clamp(Imaging::FloatRGB val, Imaging::FloatRGB lower, Imaging::FloatRGB upper); } namespace AprilMath { namespace MatrixExt { namespace BLAS { template<> Basics::Matrix *matCopy(Basics::Matrix *dst, const Basics::Matrix *src); } namespace Initializers { template<> Basics::Matrix *matFill(Basics::Matrix *obj, const Imaging::FloatRGB value); } namespace Operations { template <> Basics::Matrix *matComplement(const Basics::Matrix *src, Basics::Matrix *dst); } } } #endif april-ann-0.4.1/packages/imaging/Image/c_src/image.cc000066400000000000000000000745621263004425400223100ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ /* * Fichero de implementacion (incluido por la cabecera image.h) * */ #ifndef IMAGE_CC #define IMAGE_CC #include #include #include #include "clamp.h" #include "floatrgb.h" #include "image.h" #include "maxmin.h" #include "smart_ptr.h" #include "unused_variable.h" namespace Imaging { template Image::Image(Basics::Matrix *mat) { if (!mat->isSimple()) ERROR_EXIT(128, "Image only works with contiguous matrices\n"); // if (mat->numDim != 2) { ... } // <- TODO matrix = mat; IncRef(matrix); // garbage collection } template Image::Image(Basics::Matrix *mat, int width, int height, int offset_w, int offset_h) { int pos[2] = { offset_h, offset_w }; int sizes[2] = { height, width }; matrix = new Basics::Matrix(mat, pos, sizes); IncRef(matrix); } template Image::Image(Image &other) { // copy constructor matrix = other.matrix; IncRef(matrix); } template Image::Image(int width, int height, T value) { int dims[2]; dims[0] = height; dims[1] = width; matrix = new Basics::Matrix(2, dims); AprilMath::MatrixExt::Initializers::matFill(matrix, value); IncRef(matrix); } template Image::~Image() { DecRef(matrix); // garbage collection } template Image* Image::crop(int width, int height, int offset_w, int offset_h) const { assert("Cropping region must be contained in source image" && (offset_w >= 0 && offset_h >=0 && offset_w+width <= this->width() && offset_h+height <= this->height())); return new Image(matrix, width, height, offset_w, offset_h); } template Image* Image::clone_subimage(int w, int h, int offset_w, int offset_h, T default_color) const { int dims[2]; dims[0] = h; dims[1] = w; Basics::Matrix *mat = new Basics::Matrix(2, dims); Image *img = new Image(mat); AprilMath::MatrixExt::Initializers::matFill(mat, default_color); // averiguar tamanyo subimage a copiar: int x_dest=0, y_dest=0; int w_crop=w, h_crop=h; int x_crop=offset_w, y_crop=offset_h; if (offset_w < 0) { // izquierda x_crop = 0; w_crop -= -offset_w; x_dest = offset_w; } if (offset_w + w > width()) { // derecha w_crop -= offset_w + w - width(); } if (offset_h < 0) { // arriba y_crop = 0; h_crop -= -offset_h; y_dest = offset_h; } if (offset_h + h > height()) { // abajo h_crop -= offset_h + h - height(); } if (w_crop > 0 && h_crop > 0) { img->copy(crop(w_crop,h_crop,x_crop,y_crop), x_dest, y_dest); } return img; } template Image* Image::crop_with_padding(int width, int height, int offset_w, int offset_h, T default_color) const { if (offset_w >= 0 && offset_h >=0 && offset_w+width <= this->width() && offset_h+height <= this->height()) return crop(width, height, offset_w, offset_h); else return clone_subimage(width, height, offset_w, offset_h, default_color); } template Image* Image::clone() const { return new Image(matrix->clone()); } template int Image::count_black_pixels(T threshold) const{ int count = 0; typename Basics::Matrix::random_access_iterator mat_it(matrix); for (int y = 0; y < this->height(); ++y) { for (int x = 0; x < this->width(); x++) { if(mat_it(y,x) < threshold) { ++count; } } } return count; } template void Image::projection_v(T *v) const { // v has size width for (int x=0;x::const_iterator mat_it(matrix->begin()); for (int y=0;y void Image::projection_v(Basics::Matrix **m) const { int dims[1]; dims[0] = width(); *m = new Basics::Matrix(1, dims); projection_v((*m)->getRawDataAccess()->getPPALForWrite()); } template void Image::projection_h(T *v) const { // v has size height typename Basics::Matrix::const_iterator mat_it(matrix->begin()); for (int y=0;y void Image::projection_h(Basics::Matrix **m) const { int dims[1]; dims[0] = height(); *m = new Basics::Matrix(1, dims); projection_h((*m)->getRawDataAccess()->getPPALForWrite()); } /** * * Horizontal shear transformation. * +-------+ +-------+ * | | |\ \ * | OLD | | \ NEW \ * | | |an\ \ * +-------+ |gle+-------+ * * @param angle - The transformation angle in radians. * @param default_value - The color of new corner pixels. * * @return A totally new Image instance, with an new underlying Matrix instance. */ template Image* Image::shear_h(double angle, T default_value) const { int dims[2]; //printf("angle = %frad = %fdeg\n",angle, angle*180/M_PI); dims[0]=height(); if (angle > 0) dims[1]=width()+int(height()*tan(angle))+1; else dims[1]=width()+int(height()*tan(-angle))+1; //printf("dims = %dfilas x %dcolumnas\n", dims[0], dims[1]); Basics::Matrix *mat = new Basics::Matrix(2, dims); Image *img = new Image(mat); if (angle > 0) { // Angle > 0 typename Basics::Matrix::const_iterator source_it(matrix->begin()); typename Basics::Matrix::iterator dest_it(mat->begin()); for (int line=0; line::const_iterator source_it(matrix->iteratorAt(height()-line-1,0)); typename Basics::Matrix::iterator dest_it(mat->iteratorAt(height()-line-1,0)); float x = line*tan(angle); float izq = x-int(x); float der = 1.0-izq; int x_int = int(x); // x contiene la posicion del pixel i-esimo // por tanto, debemos poner en blanco los pixels [0,x[ // copiar la fila original en [x, x+width] y seguir // con blanco hasta el final for (int i=0; i < x_int; i++, ++dest_it) { *dest_it = default_value; } // El primer pixel lo tratamos de forma "especial" // porque se obtiene a partir del primer pixel origen y el // color por defecto *dest_it = izq*default_value + der*(*source_it); T prev_source_value = *source_it; ++dest_it; ++source_it; for (int i=1; i < width(); i++, ++dest_it, ++source_it) { *dest_it = izq*prev_source_value + der*(*source_it); } *dest_it = izq*prev_source_value + der*default_value; ++dest_it; for (int i=x_int+width()+1; i void Image::shear_h_inplace(double angle, T default_value) { UNUSED_VARIABLE(angle); UNUSED_VARIABLE(default_value); ERROR_EXIT(128, "NOT IMPLEMENTED\n"); /* // inc_width contiene el incremento de tam. en x al hacer el shear // segun el signo de angle deberemos desplazar el resultado hacia // un lado u otro int inc_width; inc_width = int(height() * tan(angle) + 1); if (angle > 0) { // Angle > 0 // Tenemos que desplazar la imagen resultante hacia la izq. int old_width = width(); offset -= inc_width; width += inc_width; // Ahora la linea de origen y destino es la misma // Empezamos por el final T *source_line = matrix->getRawDataAccess()->getPPALForReadAndWrite() + offset + (height-1) * matrix_width(); T *dest_line = source_line; for (int line=0; linegetRawDataAccess()->getPPALForReadAndWrite() + offset + (height - 1) * matrix_width(); T *dest_line = source_line; for (int line = 0 ; line < height; line++){ float x = line*tan(angle); float izq = x-int(x); float der = 1.0-izq; int x_int = int(x); // x contiene la posicion del pixel i-esimo // yendo de derecha a izq debemos copiar // desde [0,old_width] hasta [x, old_width+x] // y luego rellenar [0, x[ con el color por defecto // Copiamos el ultimo pixel dest_line[old_width+x_int]=izq*source_line[old_width-1]+der*default_value; // Los de en medio for (int i=old_width-1; i >= 1; i--) dest_line[x_int+i]=izq*source_line[i-1]+der*source_line[i]; // El primero dest_line[x_int]=izq*default_value+der*source_line[0]; // y rellenamos el resto con el color por defecto for (int i=x_int-1; i>=0; i--) dest_line[i]=default_value; source_line -= matrix_width(); dest_line -= matrix_width(); } } return; */ } // FIXME: Mover a ocr template void Image::min_bounding_box(float threshold, int *w, int *h, int *x, int *y) const { // Buscamos el primer pixel no-blanco (inferior al umbral) de la imagen // desde arriba, abajo, izquierda y derecha y hacemos un crop. int upper = 0, lower = height() - 1, left = 0, right = width() - 1; int row, col; bool found; // Desde arriba found = false; row = 0; typename Basics::Matrix::const_random_access_iterator mat_it(matrix); while (row < height() && !found) { for (col = 0; col < width(); ++col) { T val = mat_it(row,col); if (val < threshold) { upper = row; found = true; } } ++row; } // Desde abajo row = height() - 1; found = false; while (row >= 0 && !found) { for (col = 0; col < width(); ++col) { T val = mat_it(row,col); if (val < threshold) { lower = row; found = true; } } --row; } // Desde la izquierda col = 0; found = false; while (col < width() && !found) { for (row = 0; row < height(); ++row) { T val = mat_it(row,col); if (val < threshold) { left = col; found = true; } } ++col; } // Desde la derecha col = width() - 1; found = false; while (col >= 0 && !found) { for (row = 0; row < height(); ++row) { T val = mat_it(row,col); if (val < threshold) { right = col; found = true; } } --col; } //printf("upper=%d, lower=%d, left=%d, right=%d\n", upper, lower, left, right); *w = right - left + 1; *h = lower - upper + 1; *x = left; *y = upper; } // Copia la imagen src a partir de las coordenadas (dst_x, dst_y) // Recorta si es necesario template void Image::copy(const Image *src, int dst_x, int dst_y) { // FIXME: review this new code int src_pos[2], sizes[2], dst_pos[2]; if (dst_y < 0) { src_pos[0] = -dst_y; dst_pos[0] = 0; } else { src_pos[0] = 0; dst_pos[0] = dst_y; } if (dst_x < 0) { src_pos[1] = -dst_x; dst_pos[1] = 0; } else { src_pos[1] = 0; dst_pos[1] = dst_x; } sizes[0] = AprilUtils::min(src->height() - src_pos[0], this->height() - dst_y); sizes[1] = AprilUtils::min(src->width() - src_pos[1], this->width() - dst_x); AprilUtils::SharedPtr< Basics::Matrix > src_submat = new Basics::Matrix(src->getMatrix(), src_pos, sizes, false); AprilUtils::SharedPtr< Basics::Matrix > dst_submat = new Basics::Matrix(this->getMatrix(), dst_pos, sizes, false); AprilMath::MatrixExt::BLAS::matCopy(dst_submat.get(), src_submat.get()); /* int x0=0, y0=0; if (dst_x < 0) x0 = -dst_x; if (dst_y < 0) y0 = -dst_y; for (int y=y0; (y < src->height()) && (y+dst_y < height()); ++y) for (int x=x0; (x < src->width()) && (x+dst_x < width()); ++x) (*this)(x+dst_x, y+dst_y)=(*src)(x, y); */ } template Image *Image::rotate90_cw() const { int dimensions[2]; dimensions[0] = width(); dimensions[1] = height(); Basics::Matrix *new_mat = new Basics::Matrix(2, dimensions); Image *result = new Image(new_mat); typename Basics::Matrix::const_random_access_iterator src_it(this->getMatrix()); typename Basics::Matrix::random_access_iterator dst_it(new_mat); for (int y=0; y < height(); ++y) { for (int x=0; x < width(); ++x) { //printf("(%d, %d) ---> (%d, %d)\n",x,y,height-1-y,x); dst_it(x, height() - 1 - y) = src_it(y, x); } } return result; } template Image *Image::rotate90_ccw() const { int dimensions[2]; dimensions[0] = width(); dimensions[1] = height(); Basics::Matrix *new_mat = new Basics::Matrix(2, dimensions); Image *result = new Image(new_mat); typename Basics::Matrix::const_random_access_iterator src_it(this->getMatrix()); typename Basics::Matrix::random_access_iterator dst_it(new_mat); for (int y=0; y < height(); ++y) { for (int x=0; x < width(); ++x) { dst_it(width() - 1 - x, y) = src_it(y, x); } } return result; } // Warning: This operation is not clearly defined for images // outside the range [0.0, 1.0] template Image *Image::invert_colors() const { Basics::Matrix *new_mat = matrix->clone(); Image *result = new Image(new_mat); AprilMath::MatrixExt::Operations::matComplement(new_mat); return result; } // FIXME: Mover a ocr template Image *Image::remove_blank_columns() const { const float UMBRAL_BINARIZADO = 0.5f; // Contamos las columnas en blanco de la imagen original int nblanco=0; typename Basics::Matrix::const_random_access_iterator src_it(this->getMatrix()); for (int x=0; x *new_mat = new Basics::Matrix(2, dimensions); Image *result = new Image(new_mat); typename Basics::Matrix::random_access_iterator dst_it(new_mat); // Copy column by column int xdest=0; for (int x=0; x Image *Image::add_rows(int top_rows, int bottom_rows, T value) const { int begin_padding[2] = { top_rows, 0 }, end_padding[2] = { bottom_rows, 0 }; Basics::Matrix *new_mat = matrix->padding(begin_padding, end_padding, value); Image *result = new Image(new_mat); return result; } /** * Aplica un kernel de convolucion de 5x5 a la imagen. Devuelve el resultado * en una imagen nueva. El kernel se organiza por filas: * * 0 1 2 3 4 * 5 6 7 8 9 * 10 11 12 13 14 * 15 16 17 18 19 * 20 21 22 23 24 */ template Image *Image::convolution5x5(float *k, T default_color) const { // the kernel has four dimensions int dimensions[4]; dimensions[0] = 1; dimensions[1] = 1; dimensions[2] = 5; dimensions[3] = 5; int rewrap_dims[2] = { height(), width() }; // prepare kernel memory block AprilMath::GPUMirroredMemoryBlock *k_mem_block = new AprilMath::GPUMirroredMemoryBlock(25, k); // prepare kernel matrix Basics::Matrix *kernel_mat = new Basics::Matrix(4, dimensions, k_mem_block); // add padding to image Basics::Matrix *padded_this_mat = matrix->padding(2, default_color); // execute convolution (D=2, step=NULL) Basics::Matrix *conv_result_mat = AprilMath::MatrixExt::Misc::matConvolution(padded_this_mat, 2, 0, kernel_mat); // rewrap conv_result_mat to be a 2-dimensional matrix Basics::Matrix *result_mat = conv_result_mat->rewrap(rewrap_dims, 2); Image *result = new Image(result_mat); // delete kernel_mat; delete padded_this_mat; delete conv_result_mat; // return result; } template Image *Image::resize(int dst_width, int dst_height) const { T default_value=T(); int dimensions[2]; dimensions[0] = dst_height; dimensions[1] = dst_width; Basics::Matrix *new_mat = new Basics::Matrix(2, dimensions); Image *result = new Image(new_mat); typename Basics::Matrix::random_access_iterator result_it(new_mat); // we go through the destination image for (int y=0; y (%f, %f)-(%f, %f) area= %f, sum=%f\n", x, y, x0, y0, x1, y1, area, sum); } } return result; } template Image *Image::upsample(int width_factor, int height_factor) const { T default_value=T(); int dimensions[2]; int dst_height = height()*height_factor; int dst_width = width()*width_factor; dimensions[0] = dst_height; dimensions[1] = dst_width; Basics::Matrix *new_mat = new Basics::Matrix(2, dimensions); Image *result = new Image(new_mat); typename Basics::Matrix::const_random_access_iterator src_it(this->getMatrix()); typename Basics::Matrix::random_access_iterator result_it(new_mat); // we go through the destination image, this algorithm is NOT the // best one for (int y=0; y Image *Image::affine_transform(Basics::AffineTransform2D *trans, T default_value, int *offset_x, int *offset_y) const { using AprilUtils::max; using AprilUtils::min; float c[6]; AprilUtils::SharedPtr inverse_mat = AprilMath::MatrixExt::LAPACK::matInv(trans); if (!inverse_mat->getIsContiguous()) { inverse_mat = inverse_mat->clone(); } const float *inverse = inverse_mat->getRawDataAccess()->getPPALForRead(); /* printf("--transform-------\n"); printf("%1.3f %1.3f %1.3f\n", c[0], c[1], c[2]); printf("%1.3f %1.3f %1.3f\n", c[3], c[4], c[5]); printf("0 0 1 \n"); printf("--inverse transform-------\n"); printf("%1.3f %1.3f %1.3f\n", inverse[0], inverse[1], inverse[2]); printf("%1.3f %1.3f %1.3f\n", inverse[3], inverse[4], inverse[5]); printf("0 0 1 \n"); */ // New image corners -> apply the inverse to points 0, 1, 2, 3 // // 0 +-----+ 1 // | | // 2 +-----+ 3 // int x0 = int(roundf(inverse[2])); int y0 = int(roundf(inverse[5])); int x1 = int(roundf((width()-1) *inverse[0] + inverse[2])); int y1 = int(roundf((width()-1) *inverse[3] + inverse[5])); int x2 = int(roundf((height()-1)*inverse[1] + inverse[2])); int y2 = int(roundf((height()-1)*inverse[4] + inverse[5])); int x3 = int(roundf((width()-1) *inverse[0] + (height()-1)*inverse[1] + inverse[2])); int y3 = int(roundf((width()-1) *inverse[3] + (height()-1)*inverse[4] + inverse[5])); inverse = 0; int xmax = int(roundf(max(x0, max(x1, max(x2, x3))))); int xmin = int(roundf(min(x0, min(x1, min(x2, x3))))); int ymax = int(roundf(max(y0, max(y1, max(y2, y3))))); int ymin = int(roundf(min(y0, min(y1, min(y2, y3))))); int dst_width = xmax-xmin+1; int dst_height = ymax-ymin+1; /* fprintf(stderr,"p0=(%d, %d) p1=(%d, %d) p2=(%d, %d) p3=(%d, %d) dst_width = %d, dst_height=%d x: %d-%d, y: %d-%d\n", x0, y0, x1, y1, x2, y2, x3, y3, dst_width, dst_height, xmin, xmax, ymin, ymax); */ int dimensions[2]; dimensions[0] = dst_height; dimensions[1] = dst_width; Basics::Matrix *new_mat = new Basics::Matrix(2, dimensions); Image *result = new Image(new_mat); typename Basics::Matrix::random_access_iterator result_it(new_mat); for (int y=ymin; y<=ymax; y++) { for (int x=xmin; x<=xmax; x++) { float srcx = c[0]*x+c[1]*y+c[2]; float srcy = c[3]*x+c[4]*y+c[5]; T value = getpixel_bilinear(srcx, srcy, default_value); //printf("dst=(%d,%d) --- src = (%f, %f) value=%f\n", x, y, srcx, srcy, value); result_it(y-ymin,x-xmin) = value; } } if (offset_x != 0) *offset_x = xmin; if (offset_y != 0) *offset_y = ymin; return result; } template Basics::Matrix * Image::comb_lineal_forward(int sx, int sy, int ancho, int alto, int miniancho, int minialto, Basics::LinearCombConf *conf) { using AprilUtils::max; using AprilUtils::min; int output_size = miniancho*minialto; // printf("Preparing Combination %d\n", conf->patternsize); Basics::Matrix *mat = new Basics::Matrix(1, output_size); typename Basics::Matrix::random_access_iterator mat_it(mat); typename Basics::Matrix::const_random_access_iterator this_it(this->getMatrix()); AprilMath::MatrixExt::Initializers::matFill(mat, T(0.0)); // FIXME: This is not working correctly if ancho y alto are not multiples of 2 int miny = max(sy-alto/2,0); int maxy = min(sy+alto/2-1, this->height()); int minx = max(sx-ancho/2,0); int maxx = min(sx+ancho/2-1, this->width()); int dx = (sx-ancho/2); int dy = (sy-alto/2); const float th = 1e-6; int *vec_tuplas = conf->numTuplas + (miny-dy)*ancho -dx; for (int y = miny; y < maxy; ++y,vec_tuplas+=ancho){ for (int x = minx; x < maxx; x++){ float value = this_it(y,x); if (value > th) { for (int j = vec_tuplas[x-1];jindices[j]; // FIXME sustituir por mat[dest], ahora no funciona mat_it(dest) += value*conf->pesos[j]; } } } } return mat; } template Image* Image::substract_image(Image *img, T low, T high) const { Basics::Matrix *mat; mat = AprilMath::MatrixExt::Misc:: matSubstraction(getMatrix(), img->getMatrix()); Image *res = new Image(mat); AprilMath::MatrixExt::Operations::matClamp(mat, low, high); return res; } template void Image::threshold_image(T threshold_low, T threshold_high, T value_low, T value_high ){ typename Basics::Matrix::iterator it(getMatrix()->begin()); for (int y = 0; y < this->height(); y++){ for (int x = 0; x < this->width(); x++, ++it){ T value = (*it); if (value < threshold_low) (*it) = value_low; else if (value > threshold_high) (*it) = value_high; } } } } // namespace Imaging #endif // IMAGE_CC april-ann-0.4.1/packages/imaging/Image/c_src/image.h000066400000000000000000000121761263004425400221430ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef IMAGE_H #define IMAGE_H #include #include "affine_transform.h" #include "dataset.h" #include "disallow_class_methods.h" #include "floatrgb.h" #include "matrix.h" #include "referenced.h" /// Classes and utilities related with image processing. namespace Imaging { template class Image : public Referenced { APRIL_DISALLOW_ASSIGN(Image); Basics::Matrix *matrix; // dimension 2 is assumed // int offset; // int width,height; public: //Constructors Image(Basics::Matrix *mat); Image(Basics::Matrix *mat, int width, int height, int offset_w, int offset_h); Image(int width, int height, T value=T()); // Image with a new Matrix, filled with value Image(Image &other); // copy constructor //Destructor... virtual ~Image(); //Methods Basics::Matrix *getMatrix() { return matrix; } const Basics::Matrix *getMatrix() const { return matrix; } T& operator () (int x, int y) { return (*matrix)(y, x); } T operator () (int x, int y) const { return (*matrix)(y, x); } // Bound-checking version of operator() T getpixel(int x, int y, T default_value) const { if (x>=0 && y>=0 && x(trunc(x))); float fy = fabsf(y - static_cast(trunc(y))); float dx = (x >= 0.0f ? 1.0f : -1.0f); float dy = (y >= 0.0f ? 1.0f : -1.0f); T h1 = (1-fx)*getpixel(int(x), int(y), default_value) + fx*getpixel(int(x+dx), int(y), default_value); T h2 = (1-fx)*getpixel(int(x), int(y+dy), default_value) + fx*getpixel(int(x+dx), int(y+dy), default_value); return (1-fy)*h1 + fy*h2; } int width() const { return matrix->getDimSize(1); } int height() const { return matrix->getDimSize(0); } // FIXME: implement this using Matrix int offset_width() const { return 0; } // FIXME: implement this using Matrix int offset_height() const { return 0; } int count_black_pixels(T threshold) const; Image *clone() const; Image *crop(int width, int height, int offset_w, int offset_h) const; Image *clone_subimage(int width, int height, int offset_w, int offset_h, T default_color) const; Image *crop_with_padding(int width, int height, int offset_w, int offset_h, T default_color) const; void projection_v(T *v) const ; // v is not created here void projection_v(Basics::Matrix **m) const; // creates matrix m void projection_h(T *v) const ; // v is not created here void projection_h(Basics::Matrix **m) const; // creates matrix m Image *shear_h(double radians, T default_color) const; void shear_h_inplace(double radians, T default_color); void min_bounding_box(float threshold, int *w, int *h, int *x, int *y) const; void copy(const Image *src, int dst_x, int dst_y); Image *rotate90_cw() const; // Rotate 90 degrees clockwise, creates a new image Image *rotate90_ccw() const; // Rotate 90 degrees counter-clockwise, new image Image *resize(int dst_width, int dst_height) const; // Resize an image Image *upsample(int width_factor, int height_factor) const; // upsample Image *invert_colors() const; // Invert the color of every pixel, new image Image *convolution5x5(float *k, T default_color=T()) const; Image *affine_transform(Basics::AffineTransform2D *trans, T default_value, int *offset_x=0, int *offset_y=0) const; Image *remove_blank_columns() const; Image *add_rows(int top_rows, int bottom_rows, T value) const; Image *substract_image(Image *img, T low, T high) const; Basics::Matrix *comb_lineal_forward(int x, int y, int ancho, int alto, int miniancho, int minialto, Basics::LinearCombConf *cl); void threshold_image(T low, T high, T value_low, T value_high); }; template<> Image *Image::convolution5x5(float *k, FloatRGB default_color) const; } /*** Implementacion ***/ #include "image.cc" #endif // IMAGE_H april-ann-0.4.1/packages/imaging/Image/c_src/utilImageFloat.cc000066400000000000000000000037531263004425400241260ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "utilImageFloat.h" namespace Imaging { ImageFloat *RGB_to_grayscale(ImageFloatRGB *src) { int dims[2]={src->height(), src->width()}; Basics::MatrixFloat *m = new Basics::MatrixFloat(2, dims); ImageFloat *result = new ImageFloat(m); for (int y=0; y < src->height(); y++) { for (int x=0; x < src->width(); x++) { FloatRGB rgb = (*src)(x,y); (*result)(x,y) = rgb.to_grayscale(); } } return result; } ImageFloatRGB *grayscale_to_RGB(ImageFloat *src) { int dims[2]={src->height(), src->width()}; Basics::Matrix *m = new Basics::Matrix(2, dims); ImageFloatRGB *result = new ImageFloatRGB(m); for (int y=0; y < src->height(); y++) { for (int x=0; x < src->width(); x++) { float val = (*src)(x,y); (*result)(x,y) = FloatRGB(val); } } return result; } template<> Image *Image::convolution5x5(float *k, FloatRGB default_color) const { UNUSED_VARIABLE(k); UNUSED_VARIABLE(default_color); ERROR_EXIT(256, "Not implemented for RGB images\n"); return 0; } } // namespace Imaging april-ann-0.4.1/packages/imaging/Image/c_src/utilImageFloat.h000066400000000000000000000022361263004425400237630ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef UTILIMAGEFLOAT #define UTILIMAGEFLOAT #include "utilMatrixFloat.h" #include "matrix.h" #include "image.h" #include "floatrgb.h" namespace Imaging { typedef Image ImageFloat; typedef Image ImageFloatRGB; ImageFloat *RGB_to_grayscale(ImageFloatRGB *src); ImageFloatRGB *grayscale_to_RGB(ImageFloat *src); } #endif // UTILIMAGEFLOAT april-ann-0.4.1/packages/imaging/Image/doc/000077500000000000000000000000001263004425400203555ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/Image/doc/image.dox000066400000000000000000000116421263004425400221570ustar00rootroot00000000000000/** \page image Image * Image.empty(x,y) crea una imagen de tamao x,y, inicializada con ceros, y la devuelve * Image.load(filename) carga una imagen desde fichero (OJO: utiliza convert, que debe estar instalado). Es un simple wrapper de matrix.loadImage(). * Image.load_pgm_gz(filename) carga una imagen desde un fichero PGM comprimido con gzip (.pgm.gz). (OJO: requiere zcat) * Image.save(img, filename) guarda la imagen indicada a un fichero PNM ------------------------------------------------------------------------------- Todas las funciones anteriores utilizan o devuelven objetos de tipo Image. Los objetos de tipo Image representan regiones rectangulares sobre una matriz, interpretadas como pixels en escala de grises. Por ejemplo, supongamos que disponemos de una matriz m de 240 filas y 320 columnas. Podemos definir una imagen I1 que contenga a toda la matriz, pero tambien podemos definir subimagenes sobre la misma matriz. /------------320---------------\ +------------------------------+ \ I1:| +-------------+ | | |I4:| +-----+ | | | | |I2:| | | | | | | | | | | | | | +-----+ | | 240 | +-------------+ | | | +----------------+ | | | I3:| | | | | +----------------+ | / +------------------------------+ Cada uno de estos objetos tiene los siguientes mtodos: - Image(m): constructor. Toma una matriz y devuelve una imagen con las mismas dimensiones. - Image(m, cropstring): constructor. Toma una matriz m y una cadena con la forma "widthxheight+offsetx+offsety". offsetx y offsety son las coordenadas de la esquina superior izquierda desde la esquina superior izquierda (0,0) de la matriz. - Image(m, width, height, offsetx, offsety): constructor. Igual que el anterior pero especificando los parmetros por separado. - crop(cropstring): devuelve una subimagen de si misma, con el tamao y el origen indicado en la cropstring - crop(width, height, offsetx, offsety): devuelve una subimagen con los parametros indicados. - info(): Devuelve, por este orden, la matriz subyacente ylos valores width, height, offsetx y offsety de la imagen. - info_bis(): Devuelve una tabla con las siguientes claves: - "matrix" - "width" - "height" - "offset_width" (offsetx) - "offset_height" (offsety) - getpixel(x,y): Devuelve el valor del pixel en las coordenadas(x,y) - putpixel(x,y,v): Pone el valor v en el pixel (x,y) - clone(): Crea una matriz nueva consistente en una copia de la submatriz definida por la imagen y devuelve Image(matriz_nueva). - projection_h(): Devuelve una matriz unidimensional de talla height en la que el elemento i-simo contiene la suma de los valores la fila i de la imagen - projection_v(): Devuelve una matriz unidimensional de talla width en la que el elemento i-simo contiene la suma de los valores de la columna i de la imagen - shear_h(angle, unit="rad", default_value=CTEBLANCO): - angle: valor numerico, angulo para el shear, valores positivos de angle producen el efecto en la direccion indicada en el dibujo. - unit: "rad", "deg" o "grad" (radianes, grados sexagesimales o grados centesimales) - default_value: valor con el que se rellenarn las areas nuevas de la imagen resultado. Por ejemplo, en el dibujo inferior, la esquina donde esta la palabra "angle" y la esquina opuesta. +-------+ +-------+ | | |\ \ | OLD | | \ NEW \ | | |an\ \ +-------+ |gle+-------+ - shear_h_inplace: igual que la anterior, pero actuando sobre la matriz original - min_bounding_box(umbral): Devuelve una imagen de tamao minimo tal que contenga todos los pixels negros de la imagen original. El parametro umbral determina que pixels seran considerados negros. - copy(img, x, y): Hace una copia de la imagen img en un rectangulo del mismo tamao con la esquina superior izquierda en la posicion (x,y) de la imagen actual. Los siguientes metodos estan pensados para aplicarse a imagenes que contengan lineas de texto. - slant_angle(): devuelve una estimacion del slant de la imagen. Aplicable principalmente a texto. - RLSA(umbral): Aplica el algoritmo RLSA (Run Length smoothing algorithm) a la imagen. - base_lines(): Devuelve dos valores con la posicion de las lineas base inferior y superior (en este orden) del texto. - rotate90cw(amount): Rota la imagen 90 en el sentido de las agujas del reloj. amount debe ser +1 o -1 (cuando es -1 se rota en el sentido contrario). - remove_blank_columns(): Elimina las columnas de una imagen que esten compuestas enteramente por pixels con un valor UMBRAL_BINARIZADO=0.5 definido en la propia funcion en C */ april-ann-0.4.1/packages/imaging/Image/doc/image.txt000066400000000000000000000116061263004425400222040ustar00rootroot00000000000000* Image.empty(x,y) crea una imagen de tamao x,y, inicializada con ceros, y la devuelve * Image.load(filename) carga una imagen desde fichero (OJO: utiliza convert, que debe estar instalado). Es un simple wrapper de matrix.loadImage(). * Image.load_pgm_gz(filename) carga una imagen desde un fichero PGM comprimido con gzip (.pgm.gz). (OJO: requiere zcat) * Image.save(img, filename) guarda la imagen indicada a un fichero PNM ------------------------------------------------------------------------------- Todas las funciones anteriores utilizan o devuelven objetos de tipo Image. Los objetos de tipo Image representan regiones rectangulares sobre una matriz, interpretadas como pixels en escala de grises. Por ejemplo, supongamos que disponemos de una matriz m de 240 filas y 320 columnas. Podemos definir una imagen I1 que contenga a toda la matriz, pero tambien podemos definir subimagenes sobre la misma matriz. /------------320---------------\ +------------------------------+ \ I1:| +-------------+ | | |I4:| +-----+ | | | | |I2:| | | | | | | | | | | | | | +-----+ | | 240 | +-------------+ | | | +----------------+ | | | I3:| | | | | +----------------+ | / +------------------------------+ Cada uno de estos objetos tiene los siguientes mtodos: - Image(m): constructor. Toma una matriz y devuelve una imagen con las mismas dimensiones. - Image(m, cropstring): constructor. Toma una matriz m y una cadena con la forma "widthxheight+offsetx+offsety". offsetx y offsety son las coordenadas de la esquina superior izquierda desde la esquina superior izquierda (0,0) de la matriz. - Image(m, width, height, offsetx, offsety): constructor. Igual que el anterior pero especificando los parmetros por separado. - crop(cropstring): devuelve una subimagen de si misma, con el tamao y el origen indicado en la cropstring - crop(width, height, offsetx, offsety): devuelve una subimagen con los parametros indicados. - info(): Devuelve, por este orden, la matriz subyacente ylos valores width, height, offsetx y offsety de la imagen. - info_bis(): Devuelve una tabla con las siguientes claves: - "matrix" - "width" - "height" - "offset_width" (offsetx) - "offset_height" (offsety) - getpixel(x,y): Devuelve el valor del pixel en las coordenadas(x,y) - putpixel(x,y,v): Pone el valor v en el pixel (x,y) - clone(): Crea una matriz nueva consistente en una copia de la submatriz definida por la imagen y devuelve Image(matriz_nueva). - projection_h(): Devuelve una matriz unidimensional de talla height en la que el elemento i-simo contiene la suma de los valores la fila i de la imagen - projection_v(): Devuelve una matriz unidimensional de talla width en la que el elemento i-simo contiene la suma de los valores de la columna i de la imagen - shear_h(angle, unit="rad", default_value=CTEBLANCO): - angle: valor numerico, angulo para el shear, valores positivos de angle producen el efecto en la direccion indicada en el dibujo. - unit: "rad", "deg" o "grad" (radianes, grados sexagesimales o grados centesimales) - default_value: valor con el que se rellenarn las areas nuevas de la imagen resultado. Por ejemplo, en el dibujo inferior, la esquina donde esta la palabra "angle" y la esquina opuesta. +-------+ +-------+ | | |\ \ | OLD | | \ NEW \ | | |an\ \ +-------+ |gle+-------+ - shear_h_inplace: igual que la anterior, pero actuando sobre la matriz original - min_bounding_box(umbral): Devuelve una imagen de tamao minimo tal que contenga todos los pixels negros de la imagen original. El parametro umbral determina que pixels seran considerados negros. - copy(img, x, y): Hace una copia de la imagen img en un rectangulo del mismo tamao con la esquina superior izquierda en la posicion (x,y) de la imagen actual. Los siguientes metodos estan pensados para aplicarse a imagenes que contengan lineas de texto. - slant_angle(): devuelve una estimacion del slant de la imagen. Aplicable principalmente a texto. - RLSA(umbral): Aplica el algoritmo RLSA (Run Length smoothing algorithm) a la imagen. - base_lines(): Devuelve dos valores con la posicion de las lineas base inferior y superior (en este orden) del texto. - rotate90cw(amount): Rota la imagen 90 en el sentido de las agujas del reloj. amount debe ser +1 o -1 (cuando es -1 se rota en el sentido contrario). - remove_blank_columns(): Elimina las columnas de una imagen que esten compuestas enteramente por pixels con un valor UMBRAL_BINARIZADO=0.5 definido en la propia funcion en C april-ann-0.4.1/packages/imaging/Image/lua_src/000077500000000000000000000000001263004425400212405ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/Image/lua_src/Image.lua000066400000000000000000000026031263004425400227660ustar00rootroot00000000000000function Image.meta_instance:__tostring() local w,h,x,y = self:geometry() local mat = self:matrix() local str = string.format("# Image %dx%d%+d%+d [%s]", w,h,x,y, mat:get_reference_string()) return str end function ImageRGB.meta_instance:__tostring() local w,h,x,y = self:geometry() local mat = self:matrix() local str = string.format("# ImageRGB %dx%d%+d%+d [%s]", w,h,x,y, mat:get_reference_string()) return str end function Image.empty(xsize, ysize) local m=matrix(ysize, xsize) -- OJO: ysize == numfilas, etc return Image(m) end function Image.load(filename) fprintf(io.stderr, "WARNING: Image.load() is deprecated!\n".. "Use ImageIO instead.\n") local m=matrix.loadImage(filename, "gray") return Image(m) end function Image.load_pgm_gz(filename) fprintf(io.stderr, "WARNING: Image.load_pgm_gz() is deprecated!\n".. "Use ImageIO instead.\n") local f=io.popen("zcat "..filename) local s=f:read("*a") f:close() return Image(matrix.fromPNM(s)) end function Image.save(img, filename) fprintf(io.stderr, "WARNING: Image.save() is deprecated!\n".. "Use ImageIO instead.\n") -- Clonamos la imagen para salvar a fichero solo el trozo indicado -- por el crop de la propia imagen, en lugar de TODA la matriz. local i=img:clone() local m=i:info() matrix.saveImage(m, filename) end april-ann-0.4.1/packages/imaging/Image/lua_src/ImageSVG.lua000066400000000000000000000171031263004425400233470ustar00rootroot00000000000000local imageSVG,imageSVG_methods = class("imageSVG") _G.imageSVG = imageSVG -- global environment local colors = { "red", "blue", "green", "orange", "purple","yellow"} function toImage64(filename) local f = io.open(filename) base64 = require("ee5_base64") local s64 = base64.encode(f:read("*all")) f:close() return s64 end function imageSVG:constructor(params) self.width = params.width or -1 self.height = params.height or -1 -- Header, body and footer are tables of strings self.header = {} self.body = {} self.footer = {} end function imageSVG_methods:setHeader() self.header = {} -- local swidth = tostring(self.width) or "100%" -- local sheight = tostring(self.height) or "100%" local swidth = (self.width ~= -1 and tostring(self.width)) or "100%" local sheight = (self.height ~= -1 and tostring(self.height)) or "100%" table.insert(self.header,string.format("\n", swidth, sheight)) end function imageSVG_methods:setFooter() self.footer = {} table.insert(self.footer, "") end -- Recieves a table with points x,y function imageSVG_methods:addPathFromTable(path, params) --params treatment local id = params.id or "" local stroke = params.stroke or "black" local stroke_width = params.stroke_width or "2" local buffer = {} table.insert(buffer, string.format("", stroke, stroke_width)) table.insert(self.body, table.concat(buffer)) end function imageSVG_methods:addPolygon(points, params) local id = params.id or "" local stroke = params.stroke or "black" local stroke_width = params.stroke_width or "2" local buffer = {} table.insert(buffer, string.format("", stroke, stroke_width)) table.insert(self.body, table.concat(buffer)) end function imageSVG_methods:getHeader() return table.concat(self.header, "\n") end function imageSVG_methods:getBody() return table.concat(self.body, "\n") end function imageSVG_methods:getFooter() return table.concat(self.footer, "\n") end function imageSVG_methods:getString() return table.concat({self:getHeader(), self:getBody(), self:getFooter()}) end function imageSVG_methods:write(filename) file = io.open(filename, "w") file:write(self:getHeader()) file:write(self:getBody()) file:write(self:getFooter()) end -- Each element of the table is a path function imageSVG_methods:addPaths(paths) for i, path in ipairs(paths) do local color = "black" color = colors[i%#colors+1] -- print(i, color, #path) self:addPathFromTable(path,{stroke = color, id = tostring(i)}) end end -- Each element of the table is a path function imageSVG_methods:addInterestPointPaths(paths, ...) params = table.pack(...) local num_classes = params.num_class or 5 for i, path in ipairs(paths) do -- Process the component -- local color = "black" color = colors[i%#colors+1] self:addPathFromTable(path,{stroke = color, id = tostring(i)}) end end -- Given a table with table of points, draw function imageSVG_methods:addPointsFromTables(tables, size) for i, points in ipairs(tables) do local color = "black" if (i <= #colors) then color = colors[i] end for j, point in ipairs(points) do self:addPoint(point, {color = color, side = size}) end end end function imageSVG_methods:resize(height, width) self.height = height self.width = width end -- Point is a table with two coordinates function imageSVG_methods:addCircle(point, params) local radius = params.radius or 1 local color = params.color or "green" local opacity = params.opacity or 1 local cx = point[1] local cy = point[2] table.insert(self.body,string.format("", cx, cy, radius, color, opacity)) end -- Point is a table with two coordinates function imageSVG_methods:addSquare(point, params) local side = params.side or 1 local color = params.color or "green" if params.cls then color = colors[params.cls] end local x = point[1] local y = point[2] table.insert(self.body,string.format("", x, y, side,side, color)) end function imageSVG_methods:addRect(rect, params) local color = params.color or "black" if params.cls then color = colors[params.cls] end local x = rect[1] local y = rect[2] local w = rect[3] - rect[1] local h = rect[4] - rect[2] table.insert(self.body,string.format(" ", x, y, w, h, color)) end function imageSVG_methods:addPoint(point, params) -- TODO: add confidence if params.conf then self:addCircle({point[1],point[2]}, {color = colors[params.cls] , radius = (params.conf*2)^2, opacity = 0.5}) end if params.circle then self:addCircle({point[1],point[2]}, {color = colors[params.cls] , radius = params.side}) else self:addSquare(point, params) end end function imageSVG_methods:addTriangle(point, params) local side = params.side or 1 if params.reverse then side = -side end local mid = point[2] - side local color = params.color or "black" local leftx, lefty = point[1]-side, point[2]+side local rightx, righty = point[1]+side, point[2]+side local spoints = string.format("%f,%f %f,%f %f,%f", point[1], mid, leftx, lefty, rightx, righty) table.insert(self.body, string.format('', spoints, color)) end function imageSVG_methods:addLine(ini_point, end_point, params) --local color = params.color or "black" table.insert(self.body, string.format('', ini_point[1], ini_point[2], end_point[1], end_point[2])) end -- Extra image function function imageSVG_methods:addImage(filename, width, height, offsetX, offsetY, absolute) absolute = absolute or false if absolute then filename = os.getenv("PWD").."/"..filename end table.insert(self.body, string.format("\n", offsetX, offsetY, width, height, filename)) end function imageSVG_methods:addEmbedImage(filename, width, height, offsetX, offsetY) local image64 = toImage64(filename) table.insert(self.body, string.format("", offsetX, offsetY, width, height, image64)) end function imageSVG.fromImageFile(filename, width, height, absolute) mySVG = imageSVG({width = width, height = height}) mySVG:setHeader() mySVG:setFooter() absolute = absolute or false mySVG:addImage(filename, width, height, 0, 0, absolute) return mySVG end april-ann-0.4.1/packages/imaging/Image/package.lua000066400000000000000000000030761263004425400217140ustar00rootroot00000000000000 package{ name = "Image", version = "1.0", depends = { "util", "matrix", "AffineTransform2D", "dataset"}, keywords = { "image" }, description = "Image processing module", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, copy{ file= "c_src/image.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_image.lua.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_image_RGB.lua.cc", dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp=true, object{ file = "c_src/image.cc", include_dirs = "${include_dirs}", dest_dir = "build", --debug = "yes", }, object{ file = "c_src/utilImageFloat.cc", include_dirs = "${include_dirs}", dest_dir = "build", --debug = "yes", }, object{ file = "c_src/floatrgb.cc", include_dirs = "${include_dirs}", dest_dir = "build", --debug = "yes", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_image.lua.cc", dest_dir = "build" }, build_bind{ file = "binding/bind_image_RGB.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{}, document_bind{}, }, } april-ann-0.4.1/packages/imaging/Image/test/000077500000000000000000000000001263004425400205675ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/Image/test/a01-000u-s00-02.png000066400000000000000000000665241263004425400231740ustar00rootroot00000000000000PNG  IHDRidjC pHYsHHFk>mIDATx]|7X`,mt` vW1P 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ImageIO={} ImageIO.handlers={} -- ImageIO.read: Reads a image from a file. -- -- params: -- filename: name of the image file to be read -- img_format[optional, defaults to the file extension]: image format -- -- return value: a ImageRGB containing the read image -- function ImageIO.read(filename, img_format) img_format = img_format or string.get_extension(filename) img_format = string.lower(img_format) local format_handler = ImageIO.handlers[img_format] if format_handler ~= nil then return format_handler.read(filename) else -- TODO: call convert, read ppm error(string.format("Image format '%s' not supported", img_format)) end end -- ImageIO.write: Writes a image to a file. -- -- params: -- img: a ImageRGB to be written -- filename: name of the image file to be written -- img_format[optional, defaults to the file extension]: image format -- -- return value: none -- function ImageIO.write(img, filename, img_format) -- TODO: Add proper grayscale image support if type(img) == "Image" then img = img:to_RGB() end img_format = img_format or string.get_extension(filename) img_format = string.lower(img_format) local format_handler = ImageIO.handlers[img_format] if format_handler ~= nil then return format_handler.write(img, filename) else -- TODO: write ppm, call convert error(string.format("Image format '%s' not supported", img_format)) end end april-ann-0.4.1/packages/imaging/ImageIO/package.lua000066400000000000000000000011071263004425400221350ustar00rootroot00000000000000 package{ name = "ImageIO", version = "1.0", depends = { "Image" }, keywords = { "image reader, image" }, description = "loads and saves RGB images", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, }, target{ name = "clean", delete{ dir = "build" }, }, target{ name = "build", depends = "init", use_timestamp = true, luac{ orig_dir = "lua_src", dest_dir = "build", }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/imaging/binarization_filter/000077500000000000000000000000001263004425400226245ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/binarization_filter/binding/000077500000000000000000000000001263004425400242365ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/binarization_filter/binding/bind_binarization_filter.lua.cc000066400000000000000000000052521263004425400323630ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco * Zamora-Martinez, Joan Pastor-Pellicer * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C //BIND_END //BIND_HEADER_H #include "bind_image.h" #include "binarization.h" #include "utilMatrixFloat.h" using namespace Imaging; //BIND_END //BIND_LUACLASSNAME ImageFloat Image //BIND_METHOD ImageFloat binarize_niblack { int radius; float k, minThreshold, maxThreshold; LUABIND_CHECK_ARGN(==, 4); LUABIND_GET_PARAMETER(1, int, radius); LUABIND_GET_PARAMETER(2, float, k); LUABIND_GET_PARAMETER(3, float, minThreshold); LUABIND_GET_PARAMETER(4, float, maxThreshold); if (radius < 1) LUABIND_ERROR("median filter, radius must be > 0"); LUABIND_RETURN(ImageFloat, binarize_niblack(obj,radius, k, minThreshold, maxThreshold)); } //BIND_END //BIND_METHOD ImageFloat binarize_niblack_simple { int radius; float k, minThreshold, maxThreshold; LUABIND_CHECK_ARGN(>=, 1); LUABIND_GET_PARAMETER(1, int, radius); LUABIND_GET_OPTIONAL_PARAMETER(2,float, k, 0.2); if (radius < 1) LUABIND_ERROR("median filter, radius must be > 0"); LUABIND_RETURN(ImageFloat, binarize_niblack_simple(obj,radius, k)); } //BIND_END //BIND_METHOD ImageFloat binarize_sauvola { int radius; int r; float k, minThreshold, maxThreshold; LUABIND_CHECK_ARGN(>=, 1); LUABIND_GET_PARAMETER(1, int, radius); LUABIND_GET_OPTIONAL_PARAMETER(2,float, k, 0.5); LUABIND_GET_OPTIONAL_PARAMETER(3,float, r, 128); if (radius < 1) LUABIND_ERROR("median filter, radius must be > 0"); LUABIND_RETURN(ImageFloat, binarize_sauvola(obj,radius, k, r)); } //BIND_END //BIND_METHOD ImageFloat binarize_otsus { LUABIND_CHECK_ARGN(==, 0); LUABIND_RETURN(ImageFloat, binarize_otsus(obj)); } //BIND_END //BIND_METHOD ImageFloat binarize_threshold { double threshold; LUABIND_CHECK_ARGN(==, 1); LUABIND_GET_PARAMETER(1, double, threshold); LUABIND_RETURN(ImageFloat, binarize_threshold(obj, threshold)); } //BIND_END april-ann-0.4.1/packages/imaging/binarization_filter/c_src/000077500000000000000000000000001263004425400237155ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/binarization_filter/c_src/binarization.cc000066400000000000000000000334651263004425400267300ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Jorge Gorbe Moya, Joan Pastor Pellicer * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include "binarization.h" namespace Imaging { ImageFloat *binarize_niblack(const ImageFloat *src, int windowRadius, float k, float minThreshold, float maxThreshold) { april_assert(src->width() > 0 && "Zero-sized image!"); april_assert(src->height() > 0 && "Zero-sized image!"); ImageFloat *result = new ImageFloat(src->width(), src->height()); ImageFloat *sum = new ImageFloat(src->width(), src->height()); ImageFloat *sumOfSquares = new ImageFloat(src->width(), src->height()); // each pixel in the "sum" image contains the sum of the pixels to the left // and above it, same for sumOfSquares // init to the upper-left corner pixel (*sum)(0,0) = (*src)(0,0); (*sumOfSquares)(0,0) = (*src)(0,0) * (*src)(0,0); // First row for (int x=1; x < src->width(); x++) { float current_pixel = (*src)(x,0); (*sum)(x,0) = (*sum)(x-1, 0) + current_pixel; (*sumOfSquares)(x,0) = (*sumOfSquares)(x-1, 0) + current_pixel * current_pixel; } // Rest of rows for (int y=1; y < src->height(); y++) for (int x=0; x < src->width(); x++) { float s = (*sum)(x,y-1); float s2 = (*sumOfSquares)(x,y-1); if (x>0) { s += (*sum)(x-1,y) - (*sum)(x-1,y-1); s2 += (*sumOfSquares)(x-1, y) - (*sumOfSquares)(x-1,y-1); } float current_pixel = (*src)(x,y); (*sum)(x,y) = s + current_pixel; (*sumOfSquares)(x,y) = s + current_pixel * current_pixel; } // Apply Niblack filter using sum and sumOfSquares for fast mean/std.dev. computation int windowSize = 2*windowRadius+1; int totalWindowPixels = windowSize*windowSize; for (int y=0; y < src->height(); y++) for (int x=0; x < src->width(); x++) { float val = (*src)(x,y); if (val < minThreshold) { (*result)(x,y) = 0; } else if (val > maxThreshold) { (*result)(x,y) = 1; } else { int windowUpper, windowLower, windowLeft, windowRight; windowUpper = (y-windowRadius < 0 ? 0 : y-windowRadius); windowLeft = (x-windowRadius < 0 ? 0 : x-windowRadius); windowLower = (y+windowRadius > src->height() - 1 ? src->height()-1 : y+windowRadius); windowRight = (x+windowRadius > src->width() - 1 ? src->width() -1 : x+windowRadius); // assume pixels outside the image are white (value = 1) int windowPixels = (windowRight-windowLeft+1) * (windowLower-windowUpper+1); float s = totalWindowPixels - windowPixels; float s2 = s; // 1 squared is 1, too s += (*sum)(windowRight, windowLower); s2 += (*sumOfSquares)(windowRight, windowLower); if (windowLeft > 0) { s -= (*sum)(windowLeft-1, windowLower); s2 -= (*sumOfSquares)(windowLeft-1, windowLower); } if (windowUpper > 0) { s -= (*sum)(windowRight, windowUpper-1); s2 -= (*sumOfSquares)(windowRight, windowUpper-1); } if (windowLeft > 0 && windowUpper > 0) { s += (*sum)(windowLeft-1, windowUpper-1); s2 += (*sumOfSquares)(windowLeft-1, windowUpper-1); } float mean = s/totalWindowPixels; float std_dev = sqrt(s2/totalWindowPixels - mean*mean); float threshold = mean + k*std_dev; (*result)(x,y) = val < threshold ? 0 : 1; } } return result; } ImageFloat *binarize_niblack_simple(const ImageFloat *src, int windowRadius, float k) { april_assert(src->width() > 0 && "Zero-sized image!"); april_assert(src->height() > 0 && "Zero-sized image!"); // Image Integral Matrix ImageFloat *result = new ImageFloat(src->width(), src->height()); double **M = new double*[src->width()]; for(int i = 0; i < src->width(); ++i) M[i] = new double[src->height()]; // Square Image Integral double **M2 = new double*[src->width()]; for(int i = 0; i < src->width(); ++i) M2[i] = new double[src->height()]; int env=windowRadius; for(int y = 0; y < src->height(); y++) for (int x = 0; x < src->width(); x++){ M[x][y]=(*src)(x,y); M2[x][y]=(*src)(x,y)*(*src)(x,y); if(x && y){ M[x][y]+=M[x-1][y]+M[x][y-1]-M[x-1][y-1]; M2[x][y]+=M2[x-1][y]+M2[x][y-1]-M2[x-1][y-1]; } else if(x && !y){ M[x][y]+=M[x-1][y]; M2[x][y]+=M2[x-1][y]; } else if(!x && y){ M[x][y]+=M[x][y-1]; M2[x][y]+=M2[x][y-1]; } } for(int y = 0; y < src->height(); y++){ for (int x = 0; x < src->width(); x++){ int limInf , limSup , limRight,limLeft = 0; int area = 1; // We take the limits of the enviroment if(x-env < 0){ limLeft = 0; } else limLeft=x-env; if(x+env >= src->width()){ limRight = src->width()-1; } else limRight=x+env; if(y-env < 0){ limSup = 0; } else limSup=y-env; if(y+env >= src->height()){ limInf = src->height()-1; } else limInf=y+env; area = (limInf-limSup+1)*(limRight-limLeft+1); //Calculate the mean double mean = double(M[limLeft][limSup]+ M[limRight][limInf] - M[limLeft][limInf] -M[limRight][limSup])/area; double mean2 = double(M2[limLeft][limSup]+ M2[limRight][limInf] - M2[limLeft][limInf] -M2[limRight][limSup])/area; //Compute the Standar Deviacion square(Mean^2-mean2) double sd = sqrt(mean2-mean*mean); //Apply the Threshold T=mean-0.2sd float T = mean - k*sd; (*result)(x,y) = (*src)(x,y) < T ? 0 : 1; } } for(int i = 0; i < src->width();++i){ delete []M[i]; delete []M2[i]; } delete []M; delete []M2; return result; } ImageFloat *binarize_sauvola(const ImageFloat *src, int windowRadius, float k, float r) { april_assert(src->width() > 0 && "Zero-sized image!"); april_assert(src->height() > 0 && "Zero-sized image!"); // Image Integral Matrix ImageFloat *result = new ImageFloat(src->width(), src->height()); double **M = new double*[src->width()]; for(int i = 0; i < src->width(); ++i) M[i] = new double[src->height()]; // Square Image Integral double **M2 = new double*[src->width()]; for(int i = 0; i < src->width(); ++i) M2[i] = new double[src->height()]; int env=windowRadius; for(int y = 0; y < src->height(); y++) for (int x = 0; x < src->width(); x++){ M[x][y]=(*src)(x,y); M2[x][y]=(*src)(x,y)*(*src)(x,y); if(x && y){ M[x][y]+=M[x-1][y]+M[x][y-1]-M[x-1][y-1]; M2[x][y]+=M2[x-1][y]+M2[x][y-1]-M2[x-1][y-1]; } else if(x && !y){ M[x][y]+=M[x-1][y]; M2[x][y]+=M2[x-1][y]; } else if(!x && y){ M[x][y]+=M[x][y-1]; M2[x][y]+=M2[x][y-1]; } } for(int y = 0; y < src->height(); y++){ for (int x = 0; x < src->width(); x++){ int limInf , limSup , limRight,limLeft = 0; int area = 1; // We take the limits of the enviroment if(x-env < 0){ limLeft = 0; } else limLeft=x-env; if(x+env >= src->width()){ limRight = src->width()-1; } else limRight=x+env; if(y-env < 0){ limSup = 0; } else limSup=y-env; if(y+env >= src->height()){ limInf = src->height()-1; } else limInf=y+env; area = (limInf-limSup+1)*(limRight-limLeft+1); //Calculate the mean double mean = double(M[limLeft][limSup]+ M[limRight][limInf] - M[limLeft][limInf] -M[limRight][limSup])/area; double mean2 = double(M2[limLeft][limSup]+ M2[limRight][limInf] - M2[limLeft][limInf] -M2[limRight][limSup])/area; //Compute the Standar Deviacion square(Mean^2-mean2) double sd = sqrt(mean2-mean*mean); //Apply the Threshold T=mean-0.2sd float T = mean *(1+k*(sd/(r-1))); (*result)(x,y) = (*src)(x,y) < T ? 0 : 1; } } for(int i = 0; i < src->width();++i){ delete []M[i]; delete []M2[i]; } delete []M; delete []M2; return result; } ImageFloat *binarize_otsus(const ImageFloat *src) { april_assert(src->width() > 0 && "Zero-sized image!"); april_assert(src->height() > 0 && "Zero-sized image!"); //Image Integral Matrix ImageFloat *result = new ImageFloat(src->width(), src->height()); //IncRef(result); int total = src->height()*src->width(); long h[256]; long double sum = 0.0; long double sumB = 0.0; long double wB = 0.0; long double wF = 0.0; long double mB; long double mF; long mmax = 0.0; long between = 0.0; double threshold1 = 0; double threshold2 = 0; double T = 0; // Prepare the gray histogram for (int i = 0; i< 256; i++) h[i] = 0; // Calculate the histogram for (int y = 0; y < src->height(); y++){ for (int x = 0; x < src->width(); x++){ // Samplear to 255 value int v = (int)round(((*src)(x,y)*255)); h[v]++; } } // Normalize data // Calculate sum of g * h[g]; for (int i = 0; i< 256; i++){ //h[i] = h[i]/total; sum += i*h[i]; } // For each histogram for(int i = 0; i < 256; i++){ wB += h[i]; if (wB == 0) continue; wF = total - wB; if(wF == 0) break; sumB += i*h[i]; mB = sumB / wB; mF = (sum - sumB) / wF; between = wB * wF * (mB - mF)*(mB-mF); if ( between >= mmax ) { threshold1 = i; if ( between > mmax ) { threshold2 = i; } mmax = between; } } T = (threshold1 + threshold2) / 2.0; //printf("Final threshold %f %f, %f\n", threshold1, threshold2, T); // Apply the new Threshold for(int y = 0; y < src->height(); y++) for (int x = 0; x < src->width(); x++){ float v = (int)((*src)(x,y)*256); //printf("(%d, %d) %f -> %f\n", x, y, v, T); if( v > T) (*result)(x,y) = 1; else (*result)(x,y) = 0; } return result; } ImageFloat *binarize_otsus_old(const ImageFloat *src) { april_assert(src->width() > 0 && "Zero-sized image!"); april_assert(src->height() > 0 && "Zero-sized image!"); //Image Integral Matrix ImageFloat *result = new ImageFloat(src->width(), src->height()); //IncRef(result); int ntotal = src->height()*src->width(); long double h[256]; int T = 0; long double csum = 0.0; long double sum = 0.0; long double sbmax = -1.0; double p1 = 0.0; double p2 = 0.0; // Prepare the gray histogram for (int i = 0; i< 256; i++) h[i] = 0; // Calculate the histogram for (int y = 0; y < src->height(); y++){ for (int x = 0; x < src->width(); x++){ // Samplear to 255 value int v = (int)round(((*src)(x,y)*255)); h[v]++; } } // Normalize data // Calculate sum of g * h[g]; for (int i = 0; i< 256; i++){ h[i] = h[i]/ntotal; sum += h[i]*i; } // For each histogram for(int g = 0; g < 256; g++){ double m1 = 0.0; double m2 = 0.0; double sb = 0.0; p1 += h[g]; if ( !p1 ) continue; p2 = 1 - p1; if (!p2) break; csum += g*h[g]; m1 = csum/p1; m2 = (sum - csum) / p2; sb = p1*p2*(m1-m2)*(m1-m2); // Take the best T who maximize inter-class variance if(sb > sbmax){ sbmax = sb; T = g; } } // Apply the new Threshold for(int y = 0; y < src->height(); y++) for (int x = 0; x < src->width(); x++){ int v = (int)((*src)(x,y)*256); if( v > T) (*result)(x,y) = 1; else (*result)(x,y) = 0; } return result; } ImageFloat *binarize_threshold(const ImageFloat *src, double threshold) { april_assert(src->width() > 0 && "Zero-sized image!"); april_assert(src->height() > 0 && "Zero-sized image!"); //Image Integral Matrix ImageFloat *result = new ImageFloat(src->width(), src->height()); // int ntotal = src->height()*src->width(); for (int y = 0; y < src->height(); y++){ for (int x = 0; x < src->width(); x++){ if ((*src)(x,y) < threshold) { (*result)(x,y) = 0; } else { (*result)(x,y) = 1; } } } return result; } } // namespace Imaging april-ann-0.4.1/packages/imaging/binarization_filter/c_src/binarization.h000066400000000000000000000031431263004425400265600ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Jorge Gorbe Moya, Joan Pastor Pellicer * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef BINARIZATION_H #define BINARIZATION_H #include "utilImageFloat.h" namespace Imaging { //// Computes Niblack normalization ImageFloat *binarize_niblack(const ImageFloat *src, int windowRadius, float k, float minThreshold, float maxThreshold); //// Another Niblack implementation ImageFloat *binarize_niblack_simple(const ImageFloat *src, int windowRadius, float k); // Sauvolas modification ImageFloat *binarize_sauvola(const ImageFloat *src, int windowRadius, float k, float r) ; //// Otsu's Binarization ImageFloat *binarize_otsus(const ImageFloat *src); /// Simple Image Thresholding ImageFloat *binarize_threshold(const ImageFloat *src, double threshold); } // namespace Imaging #endif april-ann-0.4.1/packages/imaging/binarization_filter/package.lua000066400000000000000000000021141263004425400247200ustar00rootroot00000000000000 package{ name = "binarization_filter", version = "1.0", depends = { "Image" }, keywords = { "image", "binarization filter" }, description = "Filter of images represented as matrix using datasets", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_binarization_filter.lua.cc", dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp=true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_binarization_filter.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{}, document_bind{}, }, } april-ann-0.4.1/packages/imaging/binarization_filter/test/000077500000000000000000000000001263004425400236035ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/binarization_filter/test/.gitignore000066400000000000000000000000251263004425400255700ustar00rootroot00000000000000# PNG Images # *.png april-ann-0.4.1/packages/imaging/binarization_filter/test/test.lua000066400000000000000000000006721263004425400252720ustar00rootroot00000000000000filename = arg[1] or 'D09TRHW01-1.png' win = arg[2] or 7 gray_image = ImageIO.read(filename):to_grayscale() black_image = gray_image:binarize_niblack_simple(7) ImageIO.write(black_image:to_RGB(),filename.."-niblack.png") black_image = gray_image:binarize_otsus() ImageIO.write(black_image:to_RGB(),filename.."-otsus.png") black_image = gray_image:binarize_threshold(0.7) ImageIO.write(black_image:to_RGB(),filename.."-threshold.png") april-ann-0.4.1/packages/imaging/image_cleaning/000077500000000000000000000000001263004425400215105ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/image_cleaning/.gitignore000066400000000000000000000000301263004425400234710ustar00rootroot00000000000000# VIM SWAP FILES .*.swp april-ann-0.4.1/packages/imaging/image_cleaning/binding/000077500000000000000000000000001263004425400231225ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/image_cleaning/binding/bind_image_cleaning.lua.cc000066400000000000000000000126711263004425400301360ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco * Zamora-Martinez, Joan Pastor-Pellicer * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_H #include #include #include "image_cleaning.h" #include "bind_dataset.h" #include "bind_image.h" #include "bind_matrix.h" //BIND_END ///////////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME ImageHistogram image.image_histogram //BIND_CPP_CLASS ImageHistogram //BIND_LUACLASSNAME ImageFloat Image //BIND_CONSTRUCTOR ImageHistogram //DOC_BEGIN // ImageHistogram() // @param number of gray_levels // @param number to compute the radius //DOC_END { LUABIND_CHECK_ARGN(==, 2); int gray_levels; ImageFloat *img; LUABIND_GET_PARAMETER(1, ImageFloat, img); LUABIND_GET_PARAMETER(2, int, gray_levels); ImageHistogram *obj = new ImageHistogram(img, gray_levels); LUABIND_RETURN(ImageHistogram, obj); } //BIND_END //BIND_CONSTRUCTOR ImageHistogram //DOC_BEGIN // ImageHistogram() // @param ImageFloat for compute the histogram // @param number of gray_levels //DOC_END { LUABIND_CHECK_ARGN(==, 2); int gray_levels; ImageFloat *img; LUABIND_GET_PARAMETER(1, ImageFloat, img); LUABIND_GET_PARAMETER(2, int, gray_levels); ImageHistogram *obj = new ImageHistogram(img, gray_levels); LUABIND_RETURN(ImageHistogram, obj); } //BIND_END //BIND_METHOD ImageHistogram generate_window_histogram //DOC_BEGIN // Returns the a 3-D matrix with the integral threshold counter at // each pixel // //DOC_END { LUABIND_CHECK_ARGN(==,1); int radius; LUABIND_GET_PARAMETER(1, int, radius); LUABIND_RETURN(MatrixFloat, obj->generateWindowHistogram(radius)); } //BIND_END //BIND_METHOD ImageHistogram get_integral_histogram //DOC_BEGIN // Returns the 3-D integral matrix with the histogram // //DOC_END { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(MatrixFloat, obj->getIntegralHistogram()); } //BIND_END //BIND_DESTRUCTOR ImageHistogram { } //BIND_END //BIND_METHOD ImageFloat get_window_histogram //DOC_BEGIN // Given a image return a 3-D matrix with the histogram // @param number of gray_levels // @param radius //DOC_END { int gray_levels; int radius; LUABIND_CHECK_ARGN(==,2); LUABIND_GET_PARAMETER(1, int, gray_levels); LUABIND_GET_PARAMETER(1, int, radius); ImageHistogram *hist = new ImageHistogram(obj, gray_levels); MatrixFloat *mHist = hist->generateWindowHistogram(radius); delete hist; LUABIND_RETURN(MatrixFloat, mHist); } //BIND_END //BIND_CLASS_METHOD ImageHistogram get_histogram //DOC_BEGIN // Fast for one shot! Returns the histogram of all the image //DOC_END { LUABIND_CHECK_ARGN(==, 2); int gray_levels; ImageFloat *img; LUABIND_GET_PARAMETER(1, ImageFloat, img); LUABIND_GET_PARAMETER(2, int, gray_levels); MatrixFloat *m = ImageHistogram::getHistogram(img, gray_levels); LUABIND_RETURN(MatrixFloat, m); } //BIND_END //BIND_METHOD ImageFloat get_horizontal_histogram //DOC_BEGIN // Returns horizontal for a each row the image //DOC_END { LUABIND_CHECK_ARGN(>=, 1); int radius; LUABIND_GET_OPTIONAL_PARAMETER(2, int, radius, 0); int gray_levels; LUABIND_GET_PARAMETER(1, int, gray_levels); ImageHistogram *hist = new ImageHistogram(obj, gray_levels); MatrixFloat *m = hist->getHorizontalHistogram(radius); delete hist; LUABIND_RETURN(MatrixFloat, m); } //BIND_END // //BIND_METHOD ImageFloat get_vertical_histogram //DOC_BEGIN // Returns vertical for a each row the image //DOC_END { LUABIND_CHECK_ARGN(>=, 1); int radius; LUABIND_GET_OPTIONAL_PARAMETER(2, int, radius, 0); int gray_levels; LUABIND_GET_PARAMETER(1, int, gray_levels); ImageHistogram *hist = new ImageHistogram(obj, gray_levels); MatrixFloat *m = hist->getVerticalHistogram(radius); delete hist; LUABIND_RETURN(MatrixFloat, m); } //BIND_END //BIND_METHOD ImageHistogram get_image_histogram //DOC_BEGIN // Returns the histogram of all the image //DOC_END { LUABIND_CHECK_ARGN(==, 0); MatrixFloat *m = obj->getImageHistogram(); LUABIND_RETURN(MatrixFloat, m); } //BIND_END //BIND_METHOD ImageHistogram get_horizontal_histogram //DOC_BEGIN // Returns horizontal for a each row the image //DOC_END { LUABIND_CHECK_ARGN(>=, 0); int radius; LUABIND_GET_OPTIONAL_PARAMETER(1, int, radius, 0); MatrixFloat *m = obj->getHorizontalHistogram(radius); LUABIND_RETURN(MatrixFloat, m); } //BIND_END // //BIND_METHOD ImageHistogram get_vertical_histogram //DOC_BEGIN // Returns vertical for a each row the image //DOC_END { LUABIND_CHECK_ARGN(>=, 0); int radius; LUABIND_GET_OPTIONAL_PARAMETER(1, int, radius, 0); MatrixFloat *m = obj->getVerticalHistogram(radius); LUABIND_RETURN(MatrixFloat, m); } //BIND_END ////////////////////////////////////////////////////////////////////// april-ann-0.4.1/packages/imaging/image_cleaning/c_src/000077500000000000000000000000001263004425400226015ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/image_cleaning/c_src/image_cleaning.cc000066400000000000000000000164451263004425400260440ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco * Zamora-Martinez, Joan Pastor-Pellicer * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License -- * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include "error_print.h" #include "maxmin.h" #include "image_cleaning.h" using AprilMath::MatrixExt::Initializers::matZeros; using namespace Basics; namespace Imaging { MatrixFloat *ImageHistogram::getHistogram(const ImageFloat *img, int gray_levels) { int width = img->width(); int height = img->height(); int dims[1]; dims[0] = gray_levels; MatrixFloat *matrix = new MatrixFloat(1,dims); matZeros(matrix); int total = height*width; for (int i = 0; i < height; ++i) { for (int j = 0; j < width; ++j) { int h = getIndex((*img)(j,i), gray_levels); (*matrix)(h) += 1; } } //Normalize the histogram for(int h = 0; h < gray_levels; ++h) { (*matrix)(h) /= total; } return matrix; } ImageHistogram::ImageHistogram(const ImageHistogram &other) : Referenced() { width = other.width; height = other.height; gray_levels = other.gray_levels; memcpy(other.integral_histogram, integral_histogram, width*height*gray_levels*sizeof(int)); } void ImageHistogram::computeIntegralHistogram(ImageFloat *img) { for (int i = 0; i < height; ++i) { for (int j = 0; j < width; ++j) { float value = (*img)(j,i); // Copy the last histogram // First point, nothing to copy if (i == 0 && j == 0); // First row else if (i == 0) { for (int h = 0; h < gray_levels; ++h) hist(i,j,h) = hist(i, j - 1, h); } // First column else if (j == 0) { for (int h = 0; h < gray_levels; ++h) hist(i, j, h) = hist(i - 1, j, h); } // else else { for (int h = 0; h < gray_levels; ++h) hist(i, j, h) = hist(i-1,j,h) + hist(i,j-1,h) - hist(i-1,j-1,h); } int h = getIndex(value, gray_levels); hist(i,j,h) = hist(i,j,h) + 1; // First row } } } MatrixFloat * ImageHistogram::generateWindowHistogram(int radius) { int dims[3]; dims[0] = height; dims[1] = width; dims[2] = gray_levels; using AprilUtils::max; using AprilUtils::min; MatrixFloat *matrix = new MatrixFloat(3,dims); april_assert(width > (2*radius+1) && height > (2*radius+1) && "The window is bigger than the image limits"); matZeros(matrix); for (int i = 0; i < height; ++i) { for (int j = 0; j < width; ++j) { // Top-Left Corner int top = max(0, i - radius); int left = max(0, j - radius); int bottom = min(height - 1 , i + radius); int right = min(width - 1, j + radius); int window = (bottom - top)*(right - left); int top_left, top_right, bottom_left, bottom_right; // Normalize by size int size = (bottom - top + 1)*(right-left + 1); for(int h = 0; h < gray_levels; ++h) { bottom_right = hist(bottom, right, h); top_left = top_right = bottom_left = 0; if (top != 0 && left != 0) { top_left = hist(top-1, left-1, h); bottom_left = hist(bottom, left-1, h); top_right = hist(top-1, right, h); } else if (top == 0 && left == 0); else if (top == 0) { bottom_left = hist(bottom, left-1, h); } else if(left == 0) { top_right = hist(top-1, right, h); } int value = bottom_right + top_left - bottom_left - top_right; (*matrix)(i, j, h) = (float)value/size; } } } return matrix; } MatrixFloat *ImageHistogram::getWindowHistogram(int x1, int y1, int x2, int y2){ int top = x1; int bottom = x2; int left = y1; int right = y2; // The returned matrix has the gray level histogram int dims[1]; dims[0] = this->gray_levels; MatrixFloat *matrix = new MatrixFloat(1, dims); matZeros(matrix); // Normalize by size int size = (bottom - top + 1)*(right-left + 1); int top_left, top_right, bottom_left, bottom_right; for(int h = 0; h < gray_levels; ++h) { bottom_right = hist(bottom, right, h); top_left = top_right = bottom_left = 0; if (top != 0 && left != 0) { top_left = hist(top-1, left-1, h); bottom_left = hist(bottom, left-1, h); top_right = hist(top-1, right, h); } else if (top == 0 && left == 0); else if (top == 0) { bottom_left = hist(bottom, left-1, h); } else if(left == 0) { top_right = hist(top-1, right, h); } int value = bottom_right + top_left - bottom_left - top_right; (*matrix)(h) = (float)value/size; } return matrix; } MatrixFloat * ImageHistogram::getImageHistogram() { return getWindowHistogram(0,0, height - 1, width - 1); } MatrixFloat * ImageHistogram::getHorizontalHistogram(int radius) { using AprilUtils::max; using AprilUtils::min; int dims[2]; dims[0] = this->height; dims[1] = this->gray_levels; MatrixFloat *vHist = new MatrixFloat(2,dims); for (int i = 0; i < this->height; ++i) { // FIXME: Memory allocation on each line MatrixFloat *m = getWindowHistogram(max(i - radius,0) ,0, min(height-1, i + radius), width-1); // TODO: Copy on efficient way for (int h = 0; h < this->gray_levels; ++h) (*vHist)(i,h) = (*m)(h); delete m; } return vHist; } MatrixFloat * ImageHistogram::getVerticalHistogram(int radius) { using AprilUtils::max; using AprilUtils::min; int dims[2]; dims[0] = this->width; dims[1] = this->gray_levels; MatrixFloat *vHist = new MatrixFloat(2,dims); for (int i = 0; i < this->width; ++i) { // FIXME: Memory allocation on each line MatrixFloat *m = getWindowHistogram(0,max(0, i-radius), height-1, min(width-1,i+radius)); // TODO: Copy on efficient way for (int h = 0; h < this->gray_levels; ++h) (*vHist)(i,h) = (*m)(h); delete m; } return vHist; } MatrixFloat * ImageHistogram::getIntegralHistogram(){ using AprilUtils::max; using AprilUtils::min; int dims[3]; dims[0] = height; dims[1] = width; dims[2] = gray_levels; MatrixFloat *matrix = new MatrixFloat(3, dims); for (int i = 0; i < height; ++i) { for (int j = 0; j < width; ++j) { for(int h = 0; h < gray_levels; ++h) { (*matrix)(i, j, h) = (float)hist(i, j, h); } } } return matrix; } } // namespace Imaging april-ann-0.4.1/packages/imaging/image_cleaning/c_src/image_cleaning.h000066400000000000000000000100531263004425400256730ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Joan Pastor- Pellicer, Salvador España-Boquera, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef IMAGE_CLEANING_H #define IMAGE_CLEANING_H #include #include "referenced.h" #include "datasetFloat.h" #include "utilImageFloat.h" #include "matrix.h" namespace Imaging { /** Class that contains the counters for calculate the histogram of a given image **/ //// Given a pixel value, returns the index of histogram inline int getIndex(float value, int gray_levels) { if (value >= 1) return gray_levels - 1; return (int) floor(value*gray_levels); } class ImageHistogram : public Referenced { public: int gray_levels; int *integral_histogram; int width, height; /// Creator recieves and image ImageHistogram(ImageFloat *img, int levels) : Referenced(), gray_levels(levels){ this->width = img->width(); this->height = img->height(); integral_histogram = new int[width*height*levels]; memset(integral_histogram, 0, width*height*levels); computeIntegralHistogram(img); } // Copy Constructor ImageHistogram(const ImageHistogram &other); /// Destructor ~ImageHistogram(){ delete []integral_histogram; }; //Clone ImageHistogram *clone() { return new ImageHistogram(*this); } //// Return the total gray levels int grayLevels() { return gray_levels; } /// Given a radius gets for each pixel the histogram of these window // centered pixel Basics::Matrix * generateWindowHistogram(int radius); //// Return a new copy of the integral matrix Basics::Matrix * getIntegralHistogram(); /// Compute all the image Histogram Basics::Matrix * getImageHistogram(); Basics::Matrix * getWindowHistogram(int x1, int y1, int x2, int y2); /// Returns a matrix of size Height*Levels Basics::Matrix *getVerticalHistogram(int radius = 0); /// Returns a matrix of size width*levels Basics::Matrix *getHorizontalHistogram(int radius = 0); ///Light and slow image histogram. It's used for computing the histogram of an image on a traditional way (without computing the integral interval) static Basics::Matrix * getHistogram(const ImageFloat *img, int gray_levels); /*{ int width = img->width; int height = img->height; int dims[1]; dims[0] = gray_levels; Matrix *matrix = new Matrix(1,dims, 0.0); int total = height*width; for (int i = 0; i < height; ++i) { for (int j = 0; j < width; ++j) { int h = getIndex((*img)(i,j), gray_levels); (*matrix)(h) += 1; } } //Normalize the histogram for(int h = 0; h < gray_levels; ++h) { (*matrix)(h) /= total; } return matrix; }*/ protected: /// Accessor to the integral_histogram matrix inline int hist(int x,int y, int h) const { return integral_histogram[x*width*gray_levels + y*gray_levels+h]; } inline int & hist(int x, int y, int h) { return integral_histogram[x*width*gray_levels + y*gray_levels+h]; } //// Takes an Image and Fill the integral matrix void computeIntegralHistogram(ImageFloat *img); // ImageHistogram* clone(); }; } // namespace Imaging #endif april-ann-0.4.1/packages/imaging/image_cleaning/lua_src/000077500000000000000000000000001263004425400231405ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/image_cleaning/lua_src/image_cleaning.lua000066400000000000000000000247111263004425400265720ustar00rootroot00000000000000image = image or {} image.image_cleaning = image.image_cleaning or {} -- Apply neural filter to an image function image.image_cleaning.apply_filter_std(img, neighbors, clean_net) -- Generate the dataset local mImg = img:matrix() local tDim = mImg:dim() local side = neighbors*2 + 1 local dsParams = { patternSize = { side, side }, offset = { -neighbors, -neighbors }, stepSize = { 1,1 }, numSteps = tDim, defaultValue = 1, circular = { false, false } } local dsInput = dataset.matrix(mImg, dsParams) -- Generate output dataset local mClean = matrix(tDim[1], tDim[2]) local paramsClean = { patternSize = {1, 1}, stepSize = {1, 1}, numSteps = { tDim[1], tDim[2] }, defaultValue = 0, } local dsClean = dataset.matrix(mClean, paramsClean) --Apply the net to the dataset -- clean_net:use_dataset { input_dataset = dsInput, output_dataset = dsClean } local imgClean = Image(mClean) return imgClean end -- Apply neural filter to an image function image.image_cleaning.apply_filter_histogram(img, neighbors, levels, radius, clean_net) local mImg = img:matrix() local tDim = mImg:dim() -- Compute image histogram local side = neighbors*2 + 1 local mHist = img:get_window_histogram(levels, radius) -- Generate the dataset local dsParams = { patternSize = { side, side }, offset = { -neighbors, -neighbors }, stepSize = { 1,1 }, numSteps = tDim, defaultValue = 0, circular = { false, false } } local dsHist = { patternSize = {1, 1, levels}, stepSize = {1, 1, levels}, numSteps = { mHist:dim()[1], mHist:dim()[2],1 }, defaultValue = 0, circular = {false, false, false} } local dsDirty = dataset.matrix(mImg, dsParams) local dsHist = dataset.matrix(mHist, dsHist) local dsInput = dataset.join{dsDirty, dsHist} -- Generate output dataset local mClean = matrix(tDim[1], tDim[2]) local paramsClean = { patternSize = {1, 1}, stepSize = {1, 1}, numSteps = { tDim[1], tDim[2] }, defaultValue = 0, } local dsClean = dataset.matrix(mClean, paramsClean) --Apply the net to the dataset -- clean_net:use_dataset { input_dataset = dsInput, output_dataset = dsClean } local imgClean = Image(mClean) return imgClean end -- Returns a Dataset for iterate the image pixel by pixel function image.image_cleaning.getSingleDataset(img, vecinos_salida) img_matrix = img:matrix() local lado_salida = (vecinos_salida*2+1) local params_limpia = { patternSize = {lado_salida, lado_salida}, offset = {-vecinos_salida, -vecinos_salida}, stepSize = {1,1}, numSteps = img_matrix:dim(), defaultValue = 1, -- 1 es blanco circular={false,false} } return dataset.matrix(img_matrix, params_limpia) end image.image_cleaning.getCleanParameters = april_doc{ class="function", summary="Function to generete a sets of parameters given an image. ", description= { "This function takes an image and generates feature for each pixel", "Some parameters include raw pixels values around the desired pixels", "other have agreggated values like histogram or median filter.", "The given dataset is optimized in order to do not have copies of duplicated features." }, params= { { "A image object."}, { "A table with parameters with the features to be extracted.", "All the features are optional and only will be generated the given features in the table", "- window = ... size of the side of a sliding window set to each pixel", "- histogram_levels = ... number of the values in the histogram, each the values is computed in range 1/histogram_levels", "- histogram_radio = ... size of the side of a sliding window around the pixel where the histogram will be computed", "- median = ... size of the side of a sliding window around the pixel where the median value is computed", "- vertical = ... if defined generates features of the vertical column of each pixel.", "- horizontal = ... if defined generates features of the vertical column of each pixel.", "- random_perturbation = ... adds a gaussian perturbation of mean 0.5", "- old = ... uses default 8 values for vertical and horizontal histogram", }, }, outputs= { {"It returns a width*height length dataset with the features for each pixel." }, } } .. function(img, params) local function getWindowDataset(img, x_window, y_window) local img_matrix = img:matrix() local ladox = x_window*2+1 local ladoy = y_window*2+1 local params_sucia = { patternSize = {ladoy,ladox}, offset = {-y_window,-x_window}, stepSize = {1,1}, numSteps = img_matrix:dim(), defaultValue = 0, -- 1 es blanco circular = {false,false} } return dataset.matrix(img_matrix, params_sucia) end local function getHistogramDataset(img, levels, radio) local mHist = img:get_window_histogram(levels, radio) local params_sucia_hist = { patternSize = {1,1, levels}, stepSize = {1,1, levels}, numSteps = {mHist:dim()[1], mHist:dim()[2], 1}, defaultValue = 0, circular = {false,false, false}, } return dataset.matrix(mHist, params_sucia_hist) end local function getVerticalHistogram(img, levels, radius) local mVert = img:get_vertical_histogram(levels, radius) local params_vert_hist = { patternSize = {1, levels}, stepSize = {0, 1, 0}, numSteps = { img:matrix():dim()[1], img:matrix():dim()[2], levels}, defaultValue = 0, circular = {false, false}, } return dataset.matrix(mVert, params_vert_hist) end local function getHorizontalHistogram(img, levels, radius) local mHor = img:get_horizontal_histogram(levels, radius) local params_hor_hist = { patternSize = {1, levels}, stepSize = {1,0,0}, numSteps = { img:matrix():dim()[1],img:matrix():dim()[2], levels}, defaultValue = 0, circular = {false, false}, } return dataset.matrix(mHor, params_hor_hist) end local function getMedian(img, radio_mediana, vecinos) local img_median = img:median_filter(radio_mediana) local lado_mediana = 1 + vecinos*2 params_median = { patternSize={lado_mediana,lado_mediana}, offset={-vecinos,-vecinos}, stepSize={1,1}, numSteps=img_median:matrix():dim(), defaultValue = 1, -- 1 es blanco circular={false,false} } return dataset.matrix(img_median:matrix(), params_median) end local table_datasets = {} if params.window then local ds_window = getWindowDataset(img, params.window, params.window) table.insert(table_datasets, ds_window) end if params.x_window and params.y_window then local ds_window = getWindowDataset(img, params.x_window, params.y_window) table.insert(table_datasets, ds_window) end if params.histogram_radio then local ds_hist = getHistogramDataset(img, params.histogram_levels, params.histogram_radio) table.insert(table_datasets, ds_hist) end if params.median then local ds_median = getMedian(img, params.median, 0) table.insert(table_datasets, ds_median) end local levels_hist = params.histogram_levels or 4 if params.old then levels_hist = 8 end if params.horizontal then --local ds_hor = getHorizontalHistogram(img, params.histogram_levels, params.horizontal) local ds_hor = getHorizontalHistogram(img, levels_hist, params.horizontal) table.insert(table_datasets, ds_hor) end if params.vertical then --local ds_ver = getVerticalHistogram(img, params.histogram_levels, params.vertical) local ds_ver = getVerticalHistogram(img, levels_hist, params.vertical) table.insert(table_datasets, ds_ver) end local ds_sucia = dataset.join(table_datasets) -- 5. Añadir perturbación -- anyadimos un ruido gaussiano a la imagen sucia if params.random_perturbation then ds_sucia = dataset.perturbation{ dataset = ds_sucia, random = params.random_perturbation or 123, mean = 0, -- de la gaussiana variance = params.variance_perturbation or 0.001, -- de la gaussiana } end return ds_sucia end function image.image_cleaning.getParametersFromString(param_str, old) params = {} -- window v = string.match(param_str, "v_(%d+)") if v then params.window = tonumber(v) end levels = string.match(param_str, "levels_(%d+)") -- histogram_levels if levels then params.histogram_levels = tonumber(levels) end -- histogram_radio histogram = string.match(param_str, "hist_(%d+)") if histogram then params.histogram_radio = tonumber(histogram) end -- median median = string.match(param_str, "median_(%d+)") if median then params.median = tonumber(median) end -- vertical vertical = string.match(param_str, "vertical_(%d+)") if vertical then params.vertical = tonumber(vertical) end -- horizontal horizontal = string.match(param_str, "horizontal_(%d+)") if horizontal then params.horizontal = tonumber(horizontal) end s = string.match(param_str, "s_(%d+)") if s then params.scale = tonumber(s) end params.old = old --[[for i, v in pairs(params) do print(i,v) end ]] return params end function image.image_cleaning.clean_image(img, net, params) -- Generates the parameters local dsInput = image.image_cleaning.getCleanParameters(img, params) local img_dims = img:matrix():dim() local mClean = matrix(img_dims[1], img_dims[2]) local paramsClean = { patternSize = {1, 1}, stepSize = {1, 1}, numSteps = { img_dims[1], img_dims[2] }, defaultValue = 0, } local dsClean = dataset.matrix(mClean, paramsClean) --print(dsInput:patternSize(), net:get_input_size()) -- Use the dataset net:use_dataset { input_dataset = dsInput, output_dataset = dsClean } -- Returns the image local imgClean = Image(mClean) return imgClean end april-ann-0.4.1/packages/imaging/image_cleaning/package.lua000066400000000000000000000021501263004425400236040ustar00rootroot00000000000000 package{ name = "image_cleaning", version = "1.0", depends = { "dataset", "Image" }, keywords = { "image", "cleaning", "tools" }, description = "some util classes and functions to measure image enhancement, cleaning or binarization", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_image_cleaning.lua.cc", dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp=true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_image_cleaning.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{}, document_bind{}, }, } april-ann-0.4.1/packages/imaging/image_cleaning/test/000077500000000000000000000000001263004425400224675ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/image_cleaning/test/.gitignore000066400000000000000000000000141263004425400244520ustar00rootroot00000000000000*.png *.PNG april-ann-0.4.1/packages/imaging/image_cleaning/test/test_filter.lua000066400000000000000000000006641263004425400255240ustar00rootroot00000000000000filename = arg[1] neighbors = tonumber(arg[2]) mlpFile = arg[3] bunchsize = tonumber(arg[4]) or 32 local fileout = string.remove_extension(filename).."-clean.png" print(filename.." -> "..fileout) local mlpClean = ann.mlp.all_all.load(mlpFile, bunchsize) local imgDirty = ImageIO.read(filename):to_grayscale() local imgClean = image.image_cleaning.apply_filter_std(imgDirty, neighbors, mlpClean) ImageIO.write(imgClean, fileout) april-ann-0.4.1/packages/imaging/image_cleaning/test/test_filter_hist.lua000066400000000000000000000010071263004425400265430ustar00rootroot00000000000000filename = arg[1] neighbors = tonumber(arg[2]) levels = tonumber(arg[3]) radius = tonumber(arg[4]) mlpFile = arg[5] bunchsize = tonumber(arg[6]) or 32 local fileout = string.remove_extension(filename).."-clean_hist.png" print(filename.." -> "..fileout) local mlpClean = ann.mlp.all_all.load(mlpFile, bunchsize) local imgDirty = ImageIO.read(filename):to_grayscale() local imgClean = image.image_cleaning.apply_filter_histogram(imgDirty, neighbors, levels, radius, mlpClean) ImageIO.write(imgClean, fileout) april-ann-0.4.1/packages/imaging/image_cleaning/test/test_histograms.lua000066400000000000000000000023421263004425400264120ustar00rootroot00000000000000 m = matrix.fromString[[ 4 2 ascii 1 0 1 1 1 0 1 0 ]] myImg = Image(m) local height = m:dim()[1] local width = m:dim()[2] print("Image", height, width) print("Integral Histogram Computation") levels = 2 myHist = image.image_histogram(myImg, levels) hist = myHist:get_image_histogram() print(hist:dim()[1]) for i =1, levels do print(i,hist:get(i)) end print("Greedy Histogram Computation") levels = 2 hist = image.image_histogram.get_histogram(myImg, levels) print(hist:dim()[1]) for i =1, levels do print(i,hist:get(i)) end print("Horizontal Histogram Computation") hist = myHist:get_horizontal_histogram() for i = 1, height do for l =1, levels do print(i,l, hist:get(i,l)) end end print("Horizontal Radio Histogram Computation") hist = myHist:get_horizontal_histogram(1) for i = 1, height do for l =1, levels do print(i,l, hist:get(i,l)) end end print("Vertical Histogram Computation") hist = myHist:get_vertical_histogram() for i = 1, width do for l =1, levels do print(i,l, hist:get(i,l)) end end print("Vertical window histogram Computation") hist = myHist:get_vertical_histogram(1) for i = 1, width do for l =1, levels do print(i,l, hist:get(i,l)) end end april-ann-0.4.1/packages/imaging/image_cleaning/test/test_image.lua000066400000000000000000000003551263004425400253160ustar00rootroot00000000000000-- Create a simple Hist object -- Open the image imgFile = arg[1] or "D09TEH01.png" print("ImgFile " .. imgFile) myImg = ImageIO.read(imgFile):to_grayscale() mHistogram = myImg:get_window_histogram(4,5) print("Histogram ", mHistogram) april-ann-0.4.1/packages/imaging/image_cleaning/test/test_matrix.lua000066400000000000000000000007641263004425400255440ustar00rootroot00000000000000 m = matrix.fromString[[ 4 4 ascii 1 0 1 0 1 1 0 1 1 0 1 1 0 0 1 0 ]] myImg = Image(m) myHist = image.image_histogram(myImg,2) hist_integral = myHist:get_integral_histogram() local height = m:dim()[1] local width = m:dim()[2] -- print(hist_integral:toString()) printf("Image Histogram!\n") hist_window = myHist:generate_window_histogram(1) for i = 1, height do for j = 1, width do printf("%f ", hist_window:get(i,j,2)) end printf("\n"); end print(hist_window:toString()) april-ann-0.4.1/packages/imaging/image_cleaning/test/test_simple.lua000066400000000000000000000004211263004425400255170ustar00rootroot00000000000000-- Create a simple Hist object -- Open the image imgFile = arg[1] or "D09TEH01.png" print("ImgFile " .. imgFile) myImg = ImageIO.read(imgFile):to_grayscale() myHist = image.image_histogram(myImg, 4) printf("Histogram created with %d gray levels\n", myHist:gray_levels() ) april-ann-0.4.1/packages/imaging/image_connected_components/000077500000000000000000000000001263004425400241375ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/image_connected_components/binding/000077500000000000000000000000001263004425400255515ustar00rootroot00000000000000bind_image_connected_components.lua.cc000066400000000000000000000065341263004425400351360ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/image_connected_components/binding/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco * Zamora-Martinez, Joan Pastor-Pellicer * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "matrixInt32.h" #include "matrixFloat.h" #include "utilImageFloat.h" using namespace Basics; using namespace AprilUtils; //BIND_END //BIND_HEADER_H #include #include #include "bind_dataset.h" #include "bind_image.h" #include "bind_image_RGB.h" #include "bind_matrix_int32.h" #include "image_connected_components.h" #include "utilImageFloat.h" #include "utilMatrixFloat.h" using namespace Imaging; //BIND_END //BIND_FUNCTION image.test_connected_components { const ImageFloat *img; LUABIND_GET_PARAMETER(1, ImageFloat, img); ImageConnectedComponents components = ImageConnectedComponents(img); LUABIND_RETURN(int, components.size); } //BIND_END ///////////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME ImageConnectedComponents image.connected_components //BIND_CPP_CLASS ImageConnectedComponents //BIND_CONSTRUCTOR ImageConnectedComponents //DOC_BEGIN //DOC_END { LUABIND_CHECK_ARGN(==,1); ImageFloat *img; LUABIND_GET_PARAMETER(1, ImageFloat, img); ImageConnectedComponents *obj = new ImageConnectedComponents(img); obj->getColoredImage(); LUABIND_RETURN(ImageConnectedComponents, obj); } //BIND_END //BIND_METHOD ImageConnectedComponents get_size { LUABIND_RETURN(int,obj->size); } //BIND_END //BIND_METHOD ImageConnectedComponents get_colored_image { LUABIND_RETURN(ImageFloatRGB, obj->getColoredImage()); } //BIND_END //BIND_METHOD ImageConnectedComponents get_pixel_matrix { LUABIND_RETURN(MatrixInt32, obj->getPixelMatrix()); } //BIND_END //BIND_METHOD ImageConnectedComponents connected { LUABIND_CHECK_ARGN(==, 4); int x1, y1, x2, y2; LUABIND_GET_PARAMETER(1, int, x1); LUABIND_GET_PARAMETER(2, int, y1); LUABIND_GET_PARAMETER(3, int, x2); LUABIND_GET_PARAMETER(4, int, y2); LUABIND_RETURN(bool, obj->connected(x1, y1, x2, y2)); } //BIND_END //BIND_METHOD ImageConnectedComponents get_bounding_boxes { LUABIND_CHECK_ARGN(==, 0); int size; vector *bbs = obj->getBoundingBoxes(); size = (int) bbs->size(); lua_createtable(L, size, 0); for (size_t i = 0; i < bbs->size(); ++i) { lua_createtable(L, 4, 0); lua_pushint(L,(*bbs)[i].x1); lua_rawseti(L, -2, 1); lua_pushint(L, (*bbs)[i].y1); lua_rawseti(L, -2, 2); lua_pushint(L, (*bbs)[i].x2); lua_rawseti(L, -2, 3); lua_pushint(L, (*bbs)[i].y2); lua_rawseti(L, -2, 4); lua_rawseti(L, -2, i+1); } delete bbs; LUABIND_RETURN_FROM_STACK(-1); } //BIND_END april-ann-0.4.1/packages/imaging/image_connected_components/c_src/000077500000000000000000000000001263004425400252305ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/image_connected_components/c_src/image_connected_components.cc000066400000000000000000000145741263004425400331230ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco * Zamora-Martinez, Joan Pastor-Pellicer * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "image_connected_components.h" using namespace AprilUtils; using namespace Basics; namespace Imaging { namespace rgb_colors { typedef enum { RED, GREEN, BLUE, YELLOW, ORANGE, PURPLE, PINK, BROWN, BLACK } COLOR; float colors[BLACK+1][3] = { { 1, 0, 0}, { 0, 1, 0}, { 0, 0, 1}, { 0, 1, 1}, { 1, 0.5, 1}, {1, 1, 0}, {1, 0, 1}, {0.4, 0.2, 0.5}, {0, 0, 0}, }; float * getIndexColor(int index) { return colors[index%BLACK]; } } inline int to_index(const ImageFloat *img, int x, int y) { return y*img->width() + x; } inline void to_coords(const ImageFloat *img, int index, int &x, int &y) { y = index/img->width(); x = index%img->width(); } void ImageConnectedComponents::dfs_component(int x, int y, int current_component, int ¤t_pixel){ const int dir = 8; int directions[dir][2] = { {-1, -1}, {0, -1}, {1, -1}, {-1, 0}, {1, 0}, {-1, 1}, {0, 1}, {1, 1}}; for (int i = 0; i < dir; ++i) { int newx = x + directions[i][0]; int newy = y + directions[i][1]; int new_index = to_index(img, newx, newy); if (newx < 0 || newx >= img->width() || newy < 0 || newy >= img->height() || pixelComponents[new_index]) continue; if ((*img)(newx, newy) < threshold) {// If it is black components[current_pixel++] = new_index; } if ((*img)(x, y) < threshold || (*img)(newx, newy) < threshold) { pixelComponents[new_index] = current_component; dfs_component(newx, newy, current_component, current_pixel); } } } ImageConnectedComponents::ImageConnectedComponents(const ImageFloat *img, float threshold):threshold(threshold) { // 1. Create a Integer Matrix of the same size of the original image this->img = img; pixelComponents = vector(img->width()*img->height(), 0); // 2. Count the number of black pixels int black_pixels = img->count_black_pixels(threshold); // 3. Create a component of the size black pixels components = vector(black_pixels); indexComponents = vector(); int current_component = 0; int current_pixel = 0; // 4. Compute the connected components. for (int y = 0; y < img->height(); ++y) { for (int x = 0; x < img->width(); ++x) { int index = to_index(img, x, y); if ((*img)(x,y) < threshold && !pixelComponents[index]) { pixelComponents[index] = ++current_component; components[current_pixel++] = index; //DFS over the pixel dfs_component(x, y, current_component, current_pixel); indexComponents.push_back(current_pixel); } } } size = current_component; } MatrixInt32 * ImageConnectedComponents::getPixelMatrix(){ int dims[] = {img->height(), img->width()}; MatrixInt32 *m = new MatrixInt32(2,dims); for (int y = 0; y < img->height(); ++y) { for (int x = 0; x < img->width(); ++x) { int index = to_index(img, x, y); int value = pixelComponents[index]; (*m)(y,x) = value; } } return m; } ImageFloatRGB *ImageConnectedComponents::getColoredImage() { using rgb_colors::getIndexColor; Matrix *m = new Matrix(2, img->height(), img->width()); AprilMath::MatrixExt::Initializers::matFill(m, FloatRGB(1, 1, 1)); ImageFloatRGB *result = new ImageFloatRGB(m); int first = 0; for (int cc = 0; cc < size; ++cc) { // printf("Component %d %d\n", cc, indexComponents[cc]); for (int i = first; i < indexComponents[cc]; ++i) { float *color = getIndexColor(cc); int index = components[i]; int x, y; to_coords(img, index, x, y); (*m)(y,x) = FloatRGB(color[0], color[1], color[2]); } first = indexComponents[cc]; } return result; } bool ImageConnectedComponents::connected(int x1, int y1, int x2, int y2) { april_assert(x1 <= img->width() && x1 > 0 && y1 <= img->height() && y1 > 0 && "X1, Y1 point out of bounds"); april_assert(x2 <= img->width() && x2 > 0 && y2 <= img->height() && y2 > 0 && "X2, Y2 point out of bounds"); int index1 = to_index(img, x1, y1); int index2 = to_index(img, x2, y2); if (!pixelComponents[index1] && !pixelComponents[index2]) { fprintf(stderr, "Warning! One of the point is not in a component\n"); return false; } return pixelComponents[index1] == pixelComponents[index2]; } int ImageConnectedComponents::getComponent(int x, int y) { int index = to_index(img, x, y); return pixelComponents[index] -1; } bounding_box ImageConnectedComponents::getComponentBoundingBox(int component) { assert(component >= 0 && component < size && "The component is not corrected"); int from = component ? indexComponents[component-1] : 0; int to = indexComponents[component]; int x1 = img->width(); int y1 = img->height(); int x2 = 0; int y2 = 0; for (int i = from; i < to; ++i) { int x, y; int pointIndex = components[i]; to_coords(img, pointIndex, x, y); x1 = min(x1, x); y1 = min(y1, y); x2 = max(x2, x); y2 = max(y2, y); } return bounding_box(x1,y1, x2, y2); } vector * ImageConnectedComponents::getBoundingBoxes() { vector *bbs = new vector(); for (int i = 0; i < size; ++i) { bbs->push_back(getComponentBoundingBox(i)); } return bbs; } } // namespace Imaging april-ann-0.4.1/packages/imaging/image_connected_components/c_src/image_connected_components.h000066400000000000000000000042441263004425400327560ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco * Zamora-Martinez, Joan Pastor-Pellicer * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef IMAGE_CONNECTED_COMPONENTS_H #define IMAGE_CONNECTED_COMPONENTS_H #include "matrixInt32.h" #include "utilImageFloat.h" #include "vector.h" namespace Imaging { struct bounding_box { int x1, y1; int x2, y2; bounding_box(){}; bounding_box(int x1, int y1, int x2, int y2): x1(x1),y1(y1),x2(x2),y2(y2){} }; class ImageConnectedComponents: public Referenced{ // Matrix of the size of the image that is used to AprilUtils::vector pixelComponents; // Vector that stores the black pixels sorted by components AprilUtils::vector components; // index that delimites the CCs in components AprilUtils::vector indexComponents; //black threshold float threshold; const ImageFloat *img; public: int size; ImageConnectedComponents(const ImageFloat *img, float threshold = 0.7); ~ImageConnectedComponents(){}; private: void dfs_component(int x, int y, int current_component, int ¤t_pixel); public: Basics::MatrixInt32 *getPixelMatrix(); bool connected(int x1, int y1, int x2, int y2); int getComponent(int x, int y); ImageFloatRGB *getColoredImage(); bounding_box getComponentBoundingBox(int component); AprilUtils::vector *getBoundingBoxes(); }; } // namespace Imaging #endif april-ann-0.4.1/packages/imaging/image_connected_components/package.lua000066400000000000000000000021001263004425400262260ustar00rootroot00000000000000package{ name = "image_connected_components", version = "1.0", depends = {"util", "matrix", "dataset", "Image" }, keywords = { }, description = "A new awesome april package!", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_image_connected_components.lua.cc", dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp=true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_image_connected_components.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{}, document_bind{}, }, } april-ann-0.4.1/packages/imaging/image_connected_components/test/000077500000000000000000000000001263004425400251165ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/image_connected_components/test/testCC.lua000066400000000000000000000013051263004425400270050ustar00rootroot00000000000000-- Create a simple matrix -- m = matrix(5, 6, { 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1}) -- Create the image local myImg = Image(m) local n_comps = image.test_connected_components(myImg) print (myImg:geometry()) print(n_comps) local comps = image.connected_components(myImg) local index_matrix = comps:get_pixel_matrix() local color_matrix = comps:get_colored_image() ImageIO.write(color_matrix, "matrix.png", "png") print (m) print (index_matrix) print ("Bounding boxes") bbs = comps:get_bounding_boxes() for i,v in ipairs(bbs) do print (v[1], v[2], v[3], v[4]) end april-ann-0.4.1/packages/imaging/image_metrics/000077500000000000000000000000001263004425400213765ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/image_metrics/binding/000077500000000000000000000000001263004425400230105ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/image_metrics/binding/bind_image_metrics.lua.cc000066400000000000000000000113031263004425400277010ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco * Zamora-Martinez, Joan Pastor-Pellicer * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "bind_dataset.h" using namespace Basics; //BIND_END //BIND_HEADER_H #include #include #include "image_metrics.h" using namespace Imaging; //BIND_END ///////////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME ImageMetrics image.image_metrics //BIND_CPP_CLASS ImageMetrics //BIND_CONSTRUCTOR ImageMetrics //DOC_BEGIN // ImageMetrics() // Creates an object for counter ant recover stadistics from comparision of images. // White Pixels are representad as 1, and black as 0 //DOC_END { ImageMetrics *obj = new ImageMetrics(); LUABIND_RETURN(ImageMetrics, obj); } //BIND_END //BIND_METHOD ImageMetrics process_dataset //DOC_BEGIN //Compute the comparition two datasets (extracted from images) to the metric class // //@param predicted dataset with the predicted values //@param ground_truth dataset with the ground_truth values //@param binary (optional) if enabled perform true/false comparision given a threshold //@param threshold Necessary for binary classification //DOC_END { LUABIND_CHECK_ARGN(==,1); check_table_fields(L, 1, "predicted", "ground_truth", "binary", "threshold", (const char *)0); DataSetFloat *ds, *GT; bool binary; float threshold; LUABIND_GET_TABLE_PARAMETER(1, predicted, DataSetFloat, ds); LUABIND_GET_TABLE_PARAMETER(1, ground_truth, DataSetFloat, GT); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, binary, bool, binary, false); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, threshold, float, threshold, 0.5); obj->processDataset(ds,GT,binary,threshold); } //BIND_END //BIND_METHOD ImageMetrics process_sample //DOC_BEGIN //compute only one sample //@param pred predicted sample (i.e pixel) //@param reference ground_truth sample //DOC_END { float pred, ref; LUABIND_CHECK_ARGN(==,2); LUABIND_GET_PARAMETER(1,float,pred); LUABIND_GET_PARAMETER(2,float,ref); obj->processSample(pred,ref); } //BIND_END //BIND_METHOD ImageMetrics get_metrics //DOC_BEGIN //@returns a table with this information F-measure, Precission, Recall, GA, True Negative Rate and Accuracy //DOC_END { LUABIND_CHECK_ARGN(==,0); double FM,PR,RC,GA,TNR,ACC,MSE, PSNR, BRP, BRR, FNR; obj->getMetrics(FM,PR,RC,GA,MSE, TNR,ACC, PSNR, BRP, BRR, FNR); /* LUABIND_RETURN(float,FM); LUABIND_RETURN(float,PR); LUABIND_RETURN(float,RC); LUABIND_RETURN(float,GA); LUABIND_RETURN(float,MSE); LUABIND_RETURN(float,TNR); LUABIND_RETURN(float,ACC); */ lua_newtable(L); lua_pushnumber(L,FM); lua_setfield(L,-2,"FM"); lua_pushnumber(L,PR); lua_setfield(L,-2,"PR"); lua_pushnumber(L,RC); lua_setfield(L,-2,"RC"); lua_pushnumber(L,GA); lua_setfield(L,-2,"GA"); lua_pushnumber(L,MSE); lua_setfield(L,-2,"MSE"); lua_pushnumber(L,TNR); lua_setfield(L,-2,"TNR"); lua_pushnumber(L,ACC); lua_setfield(L,-2,"ACC"); lua_pushnumber(L, PSNR); lua_setfield(L,-2,"PSNR"); lua_pushnumber(L,BRP); lua_setfield(L,-2,"BRP"); lua_pushnumber(L,BRR); lua_setfield(L,-2,"BRT"); lua_pushnumber(L,FNR); lua_setfield(L,-2,"FNR"); LUABIND_RETURN_FROM_STACK(-1); } //BIND_END //BIND_METHOD ImageMetrics combine //DOC_BEGIN //Add the information of the parameter Metrics to the metrics information //@param ImageMetric1 Object with image metrics information to add to the actual instance //DOC_END { LUABIND_CHECK_ARGN(==,1); ImageMetrics *im1; LUABIND_GET_PARAMETER(1, ImageMetrics, im1); obj->combine(*im1); } //BIND_END //BIND_METHOD ImageMetrics clone { LUABIND_CHECK_ARGN(==,0); LUABIND_RETURN(ImageMetrics,obj->clone()); } //BIND_END //BIND_METHOD ImageMetrics clear { LUABIND_CHECK_ARGN(==,0); obj->clear(); } //BIND_END //BIND_METHOD ImageMetrics nSamples { LUABIND_CHECK_ARGN(==,0); int nSamples = obj->nSamples(); LUABIND_RETURN(int,nSamples); } //BIND_END ////////////////////////////////////////////////////////////////////// april-ann-0.4.1/packages/imaging/image_metrics/c_src/000077500000000000000000000000001263004425400224675ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/image_metrics/c_src/image_metrics.cc000066400000000000000000000132711263004425400256120ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco * Zamora-Martinez, Joan Pastor-Pellicer * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "error_print.h" #include "image_metrics.h" #include namespace Imaging { void ImageMetrics::processSample(float pred, float ref){ double act_tp; double act_fp; double act_tn; double act_fn; //tp p(pred=black | ref = black) act_tp = (1-pred)*(1-ref); //fp p(pred=black | ref = white) act_fp = (1-pred)*(ref); //fn p(pred = white | ref = white) act_tn = (pred)*(ref); //tp p(pred = white | ref = black) act_fn = (pred)*(1-ref); true_positives += act_tp; false_positives += act_fp; true_negatives += act_tn; false_negatives += act_fn; //SSE double act_sse = (pred-ref)*(pred-ref); SSE += act_sse; ++n_samples; } // TODO: Overload the + operator void ImageMetrics::clear(){ true_positives = 0.0; false_positives = 0.0; true_negatives = 0.0; false_negatives = 0.0; SSE = 0.0; n_samples = 0; } int ImageMetrics::nSamples(){ return n_samples; } void ImageMetrics::combine(ImageMetrics &m1){ true_positives += m1.true_positives; false_positives += m1.false_positives; true_negatives += m1.true_negatives; false_negatives += m1.false_negatives; SSE += m1.SSE; n_samples += m1.n_samples; } bool ImageMetrics::getMetrics(double &FM, double &PR, double &RC, double &GA,double &MSE, double &TNR, double &ACC, double &PSNR, double &BRP, double &BRR, double &FNR){ if (n_samples == 0) { FM = PR = RC = GA = MSE = TNR = ACC = BRP = BRR = FNR = 0.0f; return false; } PR = true_positives/(true_positives+false_positives); RC = true_positives/(true_positives+false_negatives); if(PR > 1 || RC > 1) { fprintf(stderr,"TP: %f, FP: %f, TN: %f, FN: %f (%lld)\n",true_positives, false_positives, true_negatives, false_negatives,n_samples); exit(0); } if (true_positives == 0) FM = 0.0; else FM = 2*PR*RC/(PR+RC); double b = (true_positives); double B = (true_positives+false_negatives); double w = (true_negatives); double W = (false_positives+true_negatives); // GA GA = sqrt((b*w)/(B*W)); // TNR TNR = true_negatives/(true_negatives+false_positives); // FNR FNR = false_positives/(true_negatives+false_positives); // ACC ACC = (true_positives+true_negatives)/(true_positives+true_negatives+false_positives+false_negatives); // MSE MSE = SSE/n_samples; // PSNR PSNR = 10 * log10(1./MSE); // BRP Black Ratio (Image Predicted) BRP = b/n_samples; // BRP Black Ratio (Reference) BRR = B/n_samples; return true; } void ImageMetrics::processDataset(Basics::DataSetFloat *ds, Basics::DataSetFloat *GT, bool binary, float threshold) { // Error control if (ds->numPatterns() != GT->numPatterns()) { ERROR_PRINT2("F measure: diferent numPatterns(): %d != %d\n", ds->numPatterns(), GT->numPatterns()); exit(128); } if (ds->patternSize() != GT->patternSize()) { ERROR_PRINT2("F measure: diferent patternSize(): %d != %d\n", ds->patternSize(), GT->patternSize()); exit(128); } if (ds->patternSize() != 1) { ERROR_PRINT1("F measure: patternSize must be 1, and is %d\n", ds->patternSize()); exit(128); } /////////////////////////////////////////////////////////////// const long int patSize = ds->patternSize(); const long int numPats = ds->numPatterns(); if (patSize != 1) { ERROR_PRINT("F measure: patternSize different of 1\n"); exit(128); } // // float *pat_ds = new float[patSize], *pat_GT = new float[patSize]; for (long int i=0; igetPattern(i, pat_ds); GT->getPattern(i, pat_GT); /* if ( pat_GT[0] > 1 || pat_GT[0] < 0) fprintf(stderr, "Warning! Pattern Ground Truth value not in 0 ~ 1 range. Pat: %ld, value: %f\n",i, pat_GT[0]); if ( pat_ds[0] > 1 || pat_ds[0] < 0) fprintf(stderr, "Warning! Pattern predicted value not in 0 ~ 1 range. Pat: %ld, value: %f\n",i, pat_ds[0]); */ if (pat_GT[0] > 1) pat_GT[0] = 1.0; if (pat_GT[0] < 0) pat_GT[0] = 0.0; if (pat_ds[0] > 1) pat_ds[0] = 1.0; if (pat_ds[0] < 0) pat_ds[0] = 0.0; if (binary){ pat_ds[0] = (pat_ds[0] <= threshold)? 0 : 1; pat_GT[0] = (pat_GT[0] <= threshold)? 0 : 1; } processSample(pat_ds[0], pat_GT[0]); } delete[] pat_ds; delete[] pat_GT; return; } ImageMetrics* ImageMetrics::clone() { return new ImageMetrics(true_positives, false_positives, true_negatives, false_negatives, SSE, n_samples); } } // namespace Imaging april-ann-0.4.1/packages/imaging/image_metrics/c_src/image_metrics.h000066400000000000000000000057031263004425400254550ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco * Zamora-Martinez, Joan Pastor-Pellicer * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef IMAGE_METRICS_H #define IMAGE_METRICS_H #include "referenced.h" #include "datasetFloat.h" #include "utilImageFloat.h" namespace Imaging { /** Class that contains the counters for calculate the metrics on two different datasets (predicted and reference) The counters are doubles, but they can be used as integer (binary classification problem) or doubles (real values classification) **/ class ImageMetrics : public Referenced { public: /// Classification Counters double true_positives; double false_positives; double true_negatives; double false_negatives; //// The SSE cannot be computed throw the counters double SSE; long long int n_samples; //// Creator ImageMetrics(double tp=0.0f, double fp=0.0f, double tn=0.0f, double fn=0.0f, double SSE=0.0, long int n_samples=0) : true_positives(tp), false_positives(fp), true_negatives(tn), false_negatives(fn), SSE(SSE), n_samples(n_samples) { } //// Add one sample to the counters void processSample(float pred, float ref); //// Takes two datasets and add the information to the counters void processDataset(Basics::DataSetFloat *ds, Basics::DataSetFloat *GT, bool binary, float threshold); /** Returns differents measures FM - Fmeasure PR - Precission RC - Recall GA - Geometrical Arithmetic TNR - True Negative Rate PSNR - Peak signal-to-noise ratio ACC - Acurracy BRP - Black Rate Predicted (ratio of black pixels in prediction) BRR - Black Rate Reference **/ bool getMetrics(double &FM, double &PR, double &RC, double &GA, double &MSE, double &TNR, double &ACC, double &PSNR, double &BRP, double &BRR, double &FNR); //// Take a classes and add the counters to this void combine(ImageMetrics &m1); //// Return the total number of samples int nSamples(); //// Reset the counters void clear(); ImageMetrics* clone(); }; } // namespace Imaging #endif april-ann-0.4.1/packages/imaging/image_metrics/lua_src/000077500000000000000000000000001263004425400230265ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/image_metrics/lua_src/image_metrics.lua000066400000000000000000000030251263004425400263410ustar00rootroot00000000000000--ImageMetrics = ImageMetrics or {} image = image or {} image.image_metrics = image.image_metrics or {} function image.image_metrics.hello() print("Hola mundo") end -- Range indica el primer elemento de la columna, puede ser nil function image.image_metrics.printMetrics(metrics, range, params) results = metrics:get_metrics() if range ~= nil then printf("%s\t",range) end for i,p in ipairs(params) do printf("%0.4f\t",results[p]) end printf("\n") end local function processImages(self, clean_img, gt_img, threshold) -- Load a dataset over the image and call process_dataset local dim_clean = clean_img:matrix():dim() local clean_params = { patternSize = {1, 1}, offset = {0,0}, stepSize = {1,1}, numSteps = dim_clean, defaultValue = 1, -- 1 es blanco circular={false,false} } local dim_gt = gt_img:matrix():dim() local gt_params = { patternSize = {1, 1}, stepSize = {1,1}, numSteps = dim_gt, defaultValue = 1, -- 1 es blanco circular={false,false} } local ds_gt = dataset.matrix(clean_img:matrix(), clean_params) local ds_clean = dataset.matrix(gt_img:matrix(), gt_params) self:process_dataset( { predicted = ds_clean, ground_truth = ds_gt, binary = threshold and true or false, threshold = threshold } ) end class.extend(image.image_metrics, "processImages", processImages) april-ann-0.4.1/packages/imaging/image_metrics/package.lua000066400000000000000000000021201263004425400234670ustar00rootroot00000000000000 package{ name = "image_metrics", version = "1.0", depends = { "dataset", "Image" }, keywords = { "image", "f-measure", "mse" }, description = "some metrics to measure image enhancement, cleaning or binarization", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_image_metrics.lua.cc", dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp=true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_image_metrics.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{}, document_bind{}, }, } april-ann-0.4.1/packages/imaging/image_metrics/test/000077500000000000000000000000001263004425400223555ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/image_metrics/test/.gitignore000066400000000000000000000000251263004425400243420ustar00rootroot00000000000000# PNG Images # *.png april-ann-0.4.1/packages/imaging/image_metrics/test/test.lua000066400000000000000000000007041263004425400240400ustar00rootroot00000000000000 ref = matrix.fromString[[ 10 1 ascii 1 1 1 1 1 1 1 0 0 0]] pred = matrix.fromString[[ 10 1 ascii 0 0 1 1 1 1 1 0 0 0]] ds = dataset.matrix(pred) gt = dataset.matrix(ref) myMetrics = image.image_metrics() myMetrics:process_dataset({ predicted = ds, ground_truth = gt }) res = myMetrics:get_metrics() printf("FMeasure: %f, PR: %f, RC: %f, RC, GA:%f,MSE: %f, TNR: %f, ACC: %f\n",res.FM, res.PR, res.RC, res.GA, res.MSE, res.TNR, res.ACC) april-ann-0.4.1/packages/imaging/image_metrics/test/test_images.lua000066400000000000000000000023761263004425400253740ustar00rootroot00000000000000if #arg ~= 2 then return end pred_img = ImageIO.read(arg[1]):to_grayscale() gt_img = ImageIO.read(arg[2]):to_grayscale() local params_ref = { patternSize = {1,1}, offset = {0,0}, stepSize = {1,1}, numSteps = pred_img:matrix():dim() } local params_gt = { patternSize = {1,1}, offset = {0,0}, stepSize = {1,1}, numSteps = gt_img:matrix():dim() } ds = dataset.matrix(pred_img:matrix(),params_ref) gt = dataset.matrix(gt_img:matrix(),params_gt) myMetrics = image.image_metrics() myMetrics:process_dataset({ predicted = ds, ground_truth = gt }) T = myMetrics:get_metrics() printf("FMeasure: %f, PR: %d, RC: %f, MSE: %f, GA:%f, TNR: %f, ACC: %f, MPM: %f \n", T["FM"], T["RC"], T["PR"], T["MSE"],T["GA"], T["TNR"], T["ACC"], T["MPM"]) myMetricsBin = image.image_metrics() myMetricsBin:process_dataset({ predicted = ds, ground_truth = gt, binary = true, threshold = 0.5 }) T = myMetricsBin:get_metrics() printf("FMeasure: %f, PR: %d, RC: %f, MSE: %f, GA:%f, TNR: %f, ACC: %f, MPM: %f \n", T["FM"], T["RC"], T["PR"], T["MSE"],T["GA"], T["TNR"], T["ACC"], T["MPM"]) local params = {"MSE", "MPM", "FM" } image.image_metrics.printMetrics(myMetricsBin, "image1", params) --myMetricsBin:printMetrics("image1", params) april-ann-0.4.1/packages/imaging/interest_points/000077500000000000000000000000001263004425400220175ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/interest_points/binding/000077500000000000000000000000001263004425400234315ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/interest_points/binding/bind_interest_points.lua.cc000066400000000000000000000257721263004425400307620ustar00rootroot00000000000000//BIND_HEADER_C #include "interest_points.h" using namespace AprilUtils; using namespace Basics; using namespace Imaging; //BIND_END //BIND_HEADER_H #include "interest_points.h" #include "utilImageFloat.h" #include "bind_image.h" #include "bind_image_RGB.h" #include "vector.h" #include "pair.h" #include #include using namespace InterestPoints; //BIND_END //BIND_FUNCTION interest_points.extract_points_from_image_old { using AprilUtils::vector; LUABIND_CHECK_ARGN(==,1); ImageFloat *img; LUABIND_GET_PARAMETER(1, ImageFloat, img); vector *result=InterestPoints::extract_points_from_image_old(img); lua_createtable(L, result->size(), 0); for (unsigned int i=1; i <= result->size(); i++) { lua_createtable(L, 2, 0); lua_pushnumber(L, (*result)[i-1].x); lua_rawseti(L, -2, 1); lua_pushnumber(L, (*result)[i-1].y); lua_rawseti(L, -2, 2); lua_rawseti(L, -2, i); } LUABIND_RETURN_FROM_STACK(-1); delete result; } //BIND_END //BIND_FUNCTION interest_points.extract_points_from_image { using AprilUtils::vector; LUABIND_CHECK_ARGN(==,1); ImageFloat *img; LUABIND_GET_PARAMETER(1, ImageFloat, img); vector *local_minima = new vector(); vector *local_maxima = new vector(); InterestPoints::extract_points_from_image(img, local_maxima, local_minima); lua_createtable(L, local_minima->size(), 0); for (unsigned int i=1; i <= local_minima->size(); i++) { lua_createtable(L, 2, 0); lua_pushnumber(L, (*local_minima)[i-1].x); lua_rawseti(L, -2, 1); lua_pushnumber(L, (*local_minima)[i-1].y); lua_rawseti(L, -2, 2); lua_rawseti(L, -2, i); } lua_createtable(L, local_maxima->size(), 0); for (unsigned int i=1; i <= local_maxima->size(); i++) { lua_createtable(L, 2, 0); lua_pushnumber(L, (*local_maxima)[i-1].x); lua_rawseti(L, -2, 1); lua_pushnumber(L, (*local_maxima)[i-1].y); lua_rawseti(L, -2, 2); lua_rawseti(L, -2, i); } delete local_minima; delete local_maxima; return 2; } //BIND_END //BIND_FUNCTION interest_points.classify_pixel { // Recibe una imagen y la lista de puntos de interés LUABIND_CHECK_ARGN(==,5); ImageFloat *img; int points; LUABIND_GET_PARAMETER(1, ImageFloat, img); LUABIND_CHECK_PARAMETER(2, table); LUABIND_CHECK_PARAMETER(3, table); LUABIND_CHECK_PARAMETER(4, table); LUABIND_CHECK_PARAMETER(5, table); int point_vector_length[4]; vector point_vector[4]; for (int vec=0; vec<4; vec++) { LUABIND_TABLE_GETN(vec+2, point_vector_length[vec]); point_vector[vec].resize(point_vector_length[vec]); for (int i=1; i <= point_vector_length[vec]; ++i) { lua_rawgeti(L,vec+2,i); // punto i-esimo, es una tabla, los vectores estan en pila[4-7] lua_rawgeti(L,-1,1); // x LUABIND_GET_PARAMETER(-1, float, point_vector[vec][i-1].x); lua_pop(L,1); // la quitamos de la pila lua_rawgeti(L,-1,2); // y LUABIND_GET_PARAMETER(-1, float, point_vector[vec][i-1].y); lua_pop(L,2); // la quitamos de la pila, tb la tabla } } MatrixFloat *transitions = NULL; ImageFloat *result = InterestPoints::get_pixel_area(img, point_vector[0], point_vector[1], point_vector[2], point_vector[3], &transitions); LUABIND_RETURN(ImageFloat, result); LUABIND_RETURN(MatrixFloat, transitions); } //BIND_END //BIND_FUNCTION interest_points.get_image_matrix_from_index { LUABIND_CHECK_ARGN(==,4); DataSetFloat *dsOut, *indexed; int height, width; LUABIND_GET_PARAMETER(1, DataSetFloat, dsOut); LUABIND_GET_PARAMETER(2, DataSetFloat, indexed); LUABIND_GET_PARAMETER(3, int, width); LUABIND_GET_PARAMETER(4, int, height); MatrixFloat *mat = InterestPoints::get_image_matrix_from_index(dsOut, indexed, width, height, 3); LUABIND_RETURN(MatrixFloat, mat); } //BIND_END //BIND_FUNCTION interest_points.get_image_area_from_dataset { LUABIND_CHECK_ARGN(>=,4); DataSetFloat *dsOut, *indexed; float threshold; int height, width; LUABIND_GET_PARAMETER(1, DataSetFloat, dsOut); LUABIND_GET_PARAMETER(2, DataSetFloat, indexed); LUABIND_GET_PARAMETER(3, int, width); LUABIND_GET_PARAMETER(4, int, height); LUABIND_GET_OPTIONAL_PARAMETER(5, float, threshold, 0.7); ImageFloat *img = InterestPoints::get_image_area_from_dataset(dsOut, indexed, width, height, 3, threshold); ImageFloatRGB *rgb = InterestPoints::area_to_rgb(img); LUABIND_RETURN(ImageFloatRGB, rgb); LUABIND_RETURN(ImageFloat, img); } //BIND_END //BIND_FUNCTION interest_points.area_to_rgb { LUABIND_CHECK_ARGN(==,1); ImageFloat *img; LUABIND_GET_PARAMETER(1, ImageFloat, img); ImageFloatRGB *result = InterestPoints::area_to_rgb(img); LUABIND_RETURN(ImageFloatRGB, result); } //BIND_END //BIND_FUNCTION interest_points.refine_colored { LUABIND_CHECK_ARGN(==,2); MatrixFloat *mat; ImageFloat *img; LUABIND_GET_PARAMETER(1, ImageFloat, img); LUABIND_GET_PARAMETER(2, MatrixFloat, mat); ImageFloat *result = InterestPoints::refine_colored(img, mat); LUABIND_RETURN(ImageFloat, result); } //BIND_END ////BIND_FUNCTION interest_points.get_indexes_from_colored { // Recibe una imagen y la lista de puntos de interés LUABIND_CHECK_ARGN(>=,1); LUABIND_CHECK_ARGN(<=,2); ImageFloat *img; ImageFloat *img2; int points; LUABIND_GET_PARAMETER(1, ImageFloat, img); LUABIND_GET_OPTIONAL_PARAMETER(2, ImageFloat, img2, NULL); MatrixFloat *m_pixels; MatrixFloat *result = InterestPoints::get_indexes_from_colored(img, img2); LUABIND_RETURN(MatrixFloat, result); } //BIND_END //----------------------------------------- // // CLASS INTEREST POINTS // //----------------------------------------- //BIND_LUACLASSNAME SetPoints interest_points.SetPoints //BIND_CPP_CLASS SetPoints //BIND_CONSTRUCTOR SetPoints //DOC_BEGIN //DOC_END { using InterestPoints::SetPoints; LUABIND_CHECK_ARGN(==,1); ImageFloat *img; LUABIND_GET_PARAMETER(1, ImageFloat, img); SetPoints *obj = new SetPoints(img); LUABIND_RETURN(SetPoints, obj); } //BIND_END //BIND_METHOD SetPoints getNumPoints { LUABIND_RETURN(int, obj->getNumPoints()); } //BIND_END //BIND_METHOD SetPoints addPoint { LUABIND_CHECK_ARGN(==, 2); LUABIND_CHECK_PARAMETER(1, int); LUABIND_CHECK_PARAMETER(2, table); // Recieves a table of 3-elements {x, y, c, type} // Sometimes can include a 5th element with the log-probability int elems; int comp = 1; LUABIND_GET_PARAMETER(1, int, comp); LUABIND_TABLE_GETN(1, elems); int x, y, c; bool type = true; float log_prob = 0.0; lua_rawgeti(L, -1, 1); x = (int)lua_tonumber(L,-1); lua_pop(L,1); lua_rawgeti(L, -1, 2); y = (int)lua_tonumber(L,-1); lua_pop(L,1); lua_rawgeti(L, -1, 3); c = (int)lua_tonumber(L,-1); lua_pop(L,1); lua_rawgeti(L, -1, 4); type = (int)lua_tonumber(L,-1); lua_pop(L,1); bool class_type = (type == 0); if (elems > 4) { lua_rawgeti(L, -1, 4+c); log_prob = lua_tonumber(L,-1); } obj->addPoint(comp, x, y, c, class_type, log_prob); } //BIND_END //BIND_METHOD SetPoints printComponents { obj->print_components(); } //BIND_END //BIND_METHOD SetPoints sortByConfidence { obj->sort_by_confidence(); } //BIND_END //BIND_METHOD SetPoints sortByX { obj->sort_by_x(); } //BIND_END //BIND_METHOD SetPoints getSize { LUABIND_RETURN(int, obj->getSize()); } //BIND_END //BIND_METHOD SetPoints getComponentPoints { // Devuelve una lista de listas de tuplas ;) const vector *v = obj->getComponents(); int tupla_len = 3; // Outer list lua_createtable (L, v->size(), 0); //fprintf(stderr, "GetComponent Size %d (%d) Points: %d\n", v->size(), obj->getSize(), obj->getNumPoints()); for(int i=0; i < (int)v->size(); ++i) { int component_size = (*v)[i].size(); //Inner list lua_createtable (L, component_size, 0); for (int j = 0; j < component_size; ++j) { // Tuple list lua_createtable (L, 3, 0); lua_pushint(L,(*v)[i][j].x); lua_rawseti(L,-2, 1); lua_pushint(L,(*v)[i][j].y); lua_rawseti(L,-2, 2); lua_pushint(L,(*v)[i][j].point_class); lua_rawseti(L,-2, 3); // Add the tuple to the outer list lua_rawseti(L, -2, j+1); } lua_rawseti(L,-2, i+1); } LUABIND_RETURN_FROM_STACK(-1); } //BIND_END /*** Connected Points ***/ //BIND_LUACLASSNAME ConnectedPoints interest_points.ConnectedPoints //BIND_CPP_CLASS ConnectedPoints //BIND_SUBCLASS_OF ConnectedPoints SetPoints //BIND_CONSTRUCTOR ConnectedPoints //DOC_BEGIN //DOC_END { using InterestPoints::ConnectedPoints; LUABIND_CHECK_ARGN(==,1); ImageFloat *img; LUABIND_GET_PARAMETER(1, ImageFloat, img); ConnectedPoints *obj = new ConnectedPoints(img); LUABIND_RETURN(ConnectedPoints, obj); } //BIND_END //BIND_METHOD ConnectedPoints addPoint { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); // Recieves a table of 3-elements {x, y, c, type} // Sometimes can include a 5th element with the log-probability int elems; LUABIND_TABLE_GETN(1, elems); int x, y, c; bool type = true; float log_prob = 0.0; lua_rawgeti(L, -1, 1); x = (int)lua_tonumber(L,-1); lua_pop(L,1); lua_rawgeti(L, -1, 2); y = (int)lua_tonumber(L,-1); lua_pop(L,1); lua_rawgeti(L, -1, 3); c = (int)lua_tonumber(L,-1); lua_pop(L,1); lua_rawgeti(L, -1, 4); type = (int)lua_tonumber(L,-1); lua_pop(L,1); bool class_type = (type == 0); if (elems > 4) { lua_rawgeti(L, -1, 4+c); log_prob = lua_tonumber(L,-1); } obj->addPoint(x, y, c, class_type, log_prob); } //BIND_END //BIND_METHOD ConnectedPoints computeComponents { LUABIND_CHECK_ARGN(==,0); SetPoints *sp = obj->computePoints(); LUABIND_RETURN(SetPoints, sp); } //BIND_END //BIND_METHOD SetPoints getLinearRegression { //Used for drawing the line regression lua_createtable(L, obj->getSize(), 0); int comp = 1; for (int i = 0; i < obj->getSize(); ++i) { PointComponent component = obj->getComponent(i); line *myLine = component.get_regression_line(); if (!myLine){ continue; } // Compute most left and most right points component.sort_by_x(); interest_point p1 = component[0]; interest_point p2 = component[component.size()-1]; float dist = 0.0; Point2D cp1 = myLine->closestPoint(p1,dist); Point2D cp2 = myLine->closestPoint(p2,dist); //ini point and end point lua_createtable(L,2,0); lua_createtable(L,2,0); lua_pushint(L, (int)cp1.x); lua_rawseti(L, -2, 1); lua_pushint(L, (int)cp1.y); lua_rawseti(L, -2, 2); lua_rawseti(L,-2, 1); lua_createtable(L, 2,0); lua_pushint(L, (int)cp2.x); lua_rawseti(L, -2, 1); lua_pushint(L, (int)cp2.y); lua_rawseti(L, -2, 2); lua_rawseti(L, -2, 2); lua_rawseti(L, -2, comp); printf("Componente: %d, Punto A: (%d %d) (%f %f), Punto B: (%d, %d) (%f, %f)\n", i, p1.x, p1.y,cp1.x,cp1.y, p2.x, p2.y, cp2.x, cp2.y); printf("Slope: %f, intercept %f\n", myLine->getSlope(), myLine->getYintercept()); comp++; } //Returns a table of 2 points LUABIND_RETURN_FROM_STACK(-1); } //BIND_END april-ann-0.4.1/packages/imaging/interest_points/c_src/000077500000000000000000000000001263004425400231105ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/interest_points/c_src/interest_points.cc000066400000000000000000001076451263004425400266650ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco * Zamora-Martinez, Joan Pastor-Pellicer * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "interest_points.h" #include "utilImageFloat.h" #include "utilMatrixFloat.h" #include "vector.h" #include "pair.h" #include "swap.h" #include "max_min_finder.h" // para buscar_extremos_trazo #include "qsort.h" #include #include #include "linear_least_squares.h" using AprilMath::MatrixExt::Initializers::matFill; using namespace AprilUtils; using namespace Basics; using namespace Imaging; /*::vector; using AprilUtils::pair; using AprilUtils::min; using AprilUtils::max; using AprilUtils::max_finder; using AprilUtils::min_finder; using AprilUtils::swap; using AprilUtils::Point2D; */ namespace InterestPoints { struct xy { // un punto que se compara por la y int x, y; xy (int x = 0, int y = 0):x (x), y (y) { } bool operator== (const xy & other) const { return y == other.y; } bool operator< (const xy & other) const { return y < other. y; } }; inline void process_stroke_max (max_finder < xy > &finder, vector < xy > *strokep) { vector < xy > &stroke = *strokep; // mas comodo int sz = stroke.size (); if (sz > 2) { for (int i = 0; i < sz; ++i) finder.put (stroke[i]); finder.end_sequence (); } stroke.clear (); } inline void process_stroke_min (min_finder < xy > &finder, vector < xy > *strokep) { vector < xy > &stroke = *strokep; // mas comodo int sz = stroke.size (); if (sz > 2) { for (int i = 0; i < sz; ++i) finder.put (stroke[i]); finder.end_sequence (); } stroke.clear (); } inline void process_neighborns (vector < Point2D > &v, int line_ini[], int line_end[], int y) { int new_x = line_ini[y] + (line_end[y] - line_ini[y]) / 2; // printf("Adding %d %d\n",new_x, y); v.push_back (Point2D (new_x, y)); line_ini[y] = line_end[y] = -2; } // If several points have the same y, only keep the central one within // a stroke, i.e a straight_line inline void remove_neighborns (vector < Point2D > &v, int dup_int, int h) { int x_act = 0; int * line_ini = new int[h]; int * line_end = new int[h]; vector < Point2D > nV; for (int i = 0; i < h; ++i) line_ini[i] = line_end[i] = -2; int sz = v.size (); for (int p = 0; p < sz; ++p) { int x = v[p].x; int y = v[p].y; // printf("Point %d %d (%d/%d)\n", x, y, x_act, nV.size()); if (x != x_act) x_act = x; //Case 1: new line if (line_end[y] != x - 1) { // Check if is there any line if (line_end[y] != -2) { process_neighborns (nV, line_ini, line_end, y); } line_ini[y] = line_end[y] = x; } else { //Case 2: continue line line_end[y] = x; if (line_end[y] - line_ini[y] > dup_int) { // Process the line process_neighborns (nV, line_ini, line_end, y); } } } // Check if exists unprocessed_neighborns for (int i = 0; i < h; ++i) { if (line_end[i] != -2) { process_neighborns (nV, line_ini, line_end, i); } } v.swap (nV); delete[]line_ini; delete[]line_end; } // Returns true if white, false if not // It is assumed that white is 1 and 0 // otherwise use flag reverse inline bool is_white (float value, float threshold, bool reverse = false) { if (value > threshold) return true xor reverse; if (value == threshold) return true; return false xor reverse; } // Returns true if white, false if not // It is assumed that white is 1 and 0 // otherwise use flag reverse inline bool is_black (float value, float threshold, bool reverse=false) { if (value < threshold) return true xor reverse; if (value == threshold) return true; return false xor reverse; } AprilUtils::vector < Point2D > *extract_points_from_image_old ( ImageFloat * pimg, float threshold_white, float threshold_black, int local_context, int duplicate_interval) { ImageFloat & img = *pimg; // mas comodo int x, y, h = img.height(), w = img.width(); int * stamp_max = new int[h]; int * stamp_min = new int[h]; vector < xy > **stroke_vec_max = new vector < xy > *[h]; // resultado vector < xy > **stroke_vec_min = new vector < xy > *[h]; // resultado for (y = 0; y < h; ++y) { stroke_vec_max[y] = new vector < xy >; stroke_vec_min[y] = new vector < xy >; stamp_max[y] = -1; stamp_min[y] = -1; } vector < xy > result_xy; max_finder < xy > maxf (local_context, local_context, &result_xy); min_finder < xy > minf (local_context, local_context, &result_xy); // avanzamos columna a columna por toda la imagen for (x = 0; x < w; ++x) { // el borde inferior de los trazos, subiendo en la columna for (y = h - 1; y > 0; --y) { if ((y == h - 1 || is_white (img (x, y + 1), threshold_white)) && (is_black (img (x, y - 1), threshold_black))) { int index = -1; if (stamp_max[y] == x) index = y; else if (y - 1 >= 0 && stamp_max[y - 1] == x) index = y - 1; else if (y + 1 < h && stamp_max[y + 1] == x) index = y + 1; else if (y - 2 >= 0 && stamp_max[y - 2] == x) index = y - 2; else if (y + 2 < h && stamp_max[y + 2] == x) index = y + 2; else { process_stroke_max (maxf, stroke_vec_max[y]); index = y; } stroke_vec_max[index]->push_back (xy (x, y)); if (index != y) { swap (stroke_vec_max[y], stroke_vec_max[index]); } stamp_max[y] = x + 1; // --y; } } // el borde superior de los trazos, bajando en la columna for (y = 0; y < h - 1; ++y) { if (is_black (img (x, y + 1), threshold_black) && (y == 0 || is_white (img (x, y - 1), threshold_white))) { int index = -1; if (stamp_min[y] == x) index = y; else if (y - 1 >= 0 && stamp_min[y - 1] == x) index = y - 1; else if (y + 1 < h && stamp_min[y + 1] == x) index = y + 1; else if (y - 2 >= 0 && stamp_min[y - 2] == x) index = y - 2; else if (y + 2 < h && stamp_min[y + 2] == x) index = y + 2; else { process_stroke_min (minf, stroke_vec_min[y]); index = y; } stroke_vec_min[index]->push_back (xy (x, y)); if (index != y) { swap (stroke_vec_min[y], stroke_vec_min[index]); } stamp_min[y] = x + 1; ++y; } } } for (y = 0; y < h; ++y) { process_stroke_max (maxf, stroke_vec_max[y]); process_stroke_min (minf, stroke_vec_min[y]); delete stroke_vec_max[y]; delete stroke_vec_min[y]; } delete[]stroke_vec_max; delete[]stroke_vec_min; delete[]stamp_max; delete[]stamp_min; // convertir stroke_set a Point2D int sz = result_xy.size (); vector < Point2D > *result_Point2D = new vector < Point2D > (sz); vector < Point2D > &vec = *result_Point2D; for (int i = 0; i < sz; ++i) { vec[i].x = result_xy[i].x; vec[i].y = result_xy[i].y; } //Delete duplicates remove_neighborns (vec, duplicate_interval, h); return result_Point2D; } void extract_points_from_image (ImageFloat * pimg, vector < Point2D > *local_minima, vector < Point2D > *local_maxima, float threshold_white, float threshold_black, int local_context, int duplicate_interval, bool reverse) { ImageFloat & img = *pimg; // mas comodo int x, y, h = img.height(), w = img.width(); int * stamp_max = new int[h]; int * stamp_min = new int[h]; vector < xy > **stroke_vec_max = new vector < xy > *[h]; // resultado vector < xy > **stroke_vec_min = new vector < xy > *[h]; // resultado for (y = 0; y < h; ++y) { stroke_vec_max[y] = new vector < xy >; stroke_vec_min[y] = new vector < xy >; stamp_max[y] = -1; stamp_min[y] = -1; } vector < xy > result_max; vector < xy > result_min; max_finder < xy > maxf (local_context, local_context, &result_max); min_finder < xy > minf (local_context, local_context, &result_min); // avanzamos columna a columna por toda la imagen for (x = 0; x < w; ++x) { // el borde inferior de los trazos, subiendo en la columna for (y = h - 1; y > 0; --y) { if ((y == h - 1 || is_white (img (x, y + 1), threshold_white, reverse)) && (is_black (img (x, y - 1), threshold_black, reverse))) { // procesar el pixel int index = -1; if (stamp_max[y] == x) index = y; else if (y - 1 >= 0 && stamp_max[y - 1] == x) index = y - 1; else if (y + 1 < h && stamp_max[y + 1] == x) index = y + 1; else if (y - 2 >= 0 && stamp_max[y - 2] == x) index = y - 2; else if (y + 2 < h && stamp_max[y + 2] == x) index = y + 2; else { process_stroke_max (maxf, stroke_vec_max[y]); index = y; } stroke_vec_max[index]->push_back (xy (x, y)); if (index != y) { swap (stroke_vec_max[y], stroke_vec_max[index]); } stamp_max[y] = x + 1; // --y; } } // el borde superior de los trazos, bajando en la columna for (y = 0; y < h - 1; ++y) { if (is_black (img (x, y + 1), threshold_black,reverse) && (y == 0 || is_white (img (x, y - 1), threshold_white, reverse))) { int index = -1; if (stamp_min[y] == x) index = y; else if (y - 1 >= 0 && stamp_min[y - 1] == x) index = y - 1; else if (y + 1 < h && stamp_min[y + 1] == x) index = y + 1; else if (y - 2 >= 0 && stamp_min[y - 2] == x) index = y - 2; else if (y + 2 < h && stamp_min[y + 2] == x) index = y + 2; else { process_stroke_min (minf, stroke_vec_min[y]); index = y; } stroke_vec_min[index]->push_back (xy (x, y)); if (index != y) { swap (stroke_vec_min[y], stroke_vec_min[index]); } stamp_min[y] = x + 1; ++y; } } } for (y = 0; y < h; ++y) { process_stroke_max (maxf, stroke_vec_max[y]); process_stroke_min (minf, stroke_vec_min[y]); delete stroke_vec_max[y]; delete stroke_vec_min[y]; } delete[]stroke_vec_max; delete[]stroke_vec_min; delete[]stamp_max; delete[]stamp_min; // convertir stroke_set a Point2D int sz = result_min.size (); //printf("Local maxima %d\n", sz); vector < Point2D > &vec_max = *local_maxima; for (int i = 0; i < sz; ++i) { local_maxima->push_back (Point2D (result_min[i].x, result_min[i].y)); } //Delete duplicates remove_neighborns (vec_max, duplicate_interval, h); /// return result_Point2D; sz = result_max.size (); //printf("Local minima %d\n", sz); //vector *result_Point2D_max = new vector(sz); vector < Point2D > &vec_min = *local_minima; for (int i = 0; i < sz; ++i) { local_minima->push_back (Point2D (result_max[i].x, result_max[i].y)); // vec_max[i].x = result_max[i].x; // vec_max[i].y = result_max[i].y; } //Delete duplicates remove_neighborns (vec_min, duplicate_interval, h); /// return result_Point2D; } static Point2D get_next_point(vector v, int index, int width, float default_y) { assert(index+1 >= 0 && "Invalid index"); if (v.size() > 0) { if (index < int(v.size())-1) { return v[index+1]; } else { return Point2D(width-1.0f, v.back().y); } } else { return Point2D(width-1.0f, default_y); } } static Point2D get_first_point(vector v, float default_y, int *index) { Point2D result; if (!v.empty()) { result.x = 0; result.y = v[0].y; if (v[0].x == 0) { *index = 0; // index is the last index we have used in v } else { *index = -1; } } else { result.x = 0.0f; result.y = default_y; *index = -1; } return result; } static void classify_pixel(ImageFloat *img, ImageFloat *result, int col, int ini_row, int end_row, float value) { for(int row = ini_row; row < end_row; ++row) { if (is_black((*img)(col,row), 0.8)) { (*result)(col,row) = value; } } } enum AREAS { UNK, ASC, BODY, DESC }; const float ASC_CODE = 0.2; const float BODY_CODE = 0.4; const float DESC_CODE = 0.6; const float UNK_CODE = 0.8; static int get_tag(float value) { float eps = 0.05; int tag = 0; // Get the label if (value <= ASC_CODE+eps) { tag = 1; } else if(value <= BODY_CODE+eps) { tag = 2; } else if(value <= DESC_CODE+eps) { tag = 3; } return tag; } ImageFloatRGB * area_to_rgb(ImageFloat *img) { int width = img->width(); int height = img->height(); float eps = 0.05; ImageFloatRGB *rgb = new ImageFloatRGB(width, height, FloatRGB(1.0,1.0,1.0)); for (int y = 0; y < height; ++y) for(int x = 0; x < width; ++x) { float value = (*img)(x,y); if (is_black(value, UNK_CODE+eps)) { // Get the label if (value <= ASC_CODE+eps) { (*rgb)(x,y) = FloatRGB(1.0,0.0,0.0); } else if(value <= BODY_CODE+eps) { (*rgb)(x,y) = FloatRGB(0.0,1.0,0.0); } else if(value <= DESC_CODE+eps) { (*rgb)(x,y) = FloatRGB(0.0,0.0,1.0); } else { (*rgb)(x,y) = FloatRGB(0.5,0.5,0.5); } } } return rgb; } ImageFloat *refine_colored(ImageFloat *img, MatrixFloat *mat, int num_classes) { int height = img->height(); int width = img->width(); int dims[2] = {height, width}; MatrixFloat::random_access_iterator mat_it(mat); MatrixFloat *result_mat = new MatrixFloat(2, dims); matFill(result_mat, 1.0f); ImageFloat *result = new ImageFloat(result_mat); //FIX_ME // Use Integral Image (image_histograms package) int dim_scores[2] = {height+1, num_classes}; MatrixFloat *scores = new MatrixFloat(2, dim_scores); // Accesor MatrixFloat::random_access_iterator scores_it(scores); // Columns for (int x = 0; x < width; ++x) { //Baseline //FROM DOWN TO UP for (int c = 0; c < num_classes; ++c) { scores_it(height,c) = 0; } for (int y = height-1; y >= 0; --y) { for (int c = 0; c <= num_classes; ++c) { scores_it(y,c) = scores_it(y+1, c) + mat_it(y,x,c); } } // Find baseline transition int max_value = -999999; int argmax_value = 0; for (int y = height-1; y >= 0; --y) { float base_score = scores_it(y,2) - 2*scores_it(y, 0) - 2*scores_it(y, 1); //printf("%d %d %f\n", x, y, base_score); if (base_score > max_value) { argmax_value = y; max_value = base_score; } } int y_base = argmax_value; // Find topline transition max_value = -99999; for (int y = y_base; y >= 0; --y) { float base_score = scores_it(y, 1) - 2*scores_it(y, 0) - 2*scores_it(y, 2); if (base_score > max_value) { argmax_value = y; max_value = base_score; } } //Topline int y_top = argmax_value; classify_pixel(img, result, x, 0, y_top, ASC_CODE); classify_pixel(img, result, x, y_top, y_base, BODY_CODE); classify_pixel(img, result, x, y_base, height, DESC_CODE); } return result; } ImageFloat *get_image_area_from_dataset(DataSetFloat *ds_out, DataSetFloat *indexed, int width, int height, int num_classes = 3, float threshold) { assert(ds_out->numPatterns() == indexed->numPatterns() && "The number of patterns does not fit"); int numPats = ds_out->numPatterns(); int dims[2] = {height, width}; MatrixFloat *result_mat = new MatrixFloat(2, dims); matFill(result_mat, 1.0f); ImageFloat *result = new ImageFloat(result_mat); float ipat; float *ftag = new float[num_classes]; // Get the softmax index for (int i = 0; i < numPats; ++i) { indexed->getPattern(i,&ipat); int index = (int) ipat; ds_out->getPattern(i, ftag); int row = index/width; int column = index%width; int tag = AprilUtils::argmax(ftag, num_classes)+1; float prob = exp(AprilUtils::max(ftag, num_classes)); float value = 1.0; switch(tag) { case 1: value = ASC_CODE; break; case 2: value = BODY_CODE; break; case 3: value = DESC_CODE; break; default: break; } if (prob < threshold) value = UNK_CODE; (*result)(column, row) = value; } return result; } // Returns a 3D matrix. 2 first dimensions are the dimensions of the imgage. // The third dimension are the values of the softmax computed for the image MatrixFloat *get_image_matrix_from_index(DataSetFloat *ds_out, DataSetFloat *indexed, int width, int height, int num_classes) { assert(ds_out->numPatterns() == indexed->numPatterns() && "The number of patterns does not fit"); int numPats = ds_out->numPatterns(); int dims[3] = {height, width, num_classes}; MatrixFloat *result_mat = new MatrixFloat(3, dims); MatrixFloat::random_access_iterator it(result_mat); matFill(result_mat, 0.0f); float ipat; float *ftag = new float[num_classes]; // Get the softmax index for (int i = 0; i < numPats; ++i) { indexed->getPattern(i,&ipat); int index = (int) ipat; //Result mat is a matrix in row major (y, x) int row = (index/width); int column = (index%width); ds_out->getPattern(i, ftag);; for (int c = 0; c < num_classes; ++c) { it(row, column,c) = exp(ftag[c]); } // int tag = AprilUtils::argmax(ftag, num_classes)+1; } delete []ftag; return result_mat; } ImageFloat *get_pixel_area(ImageFloat *source, vector ascenders, vector upper_baseline, vector lower_baseline, vector descenders, MatrixFloat **transitions ){ if (upper_baseline.empty() || lower_baseline.empty()) ERROR_EXIT(128, "Upper/Lower baseline munst not be empty"); april_assert(!upper_baseline.empty() && "Upper baseline must not be empty"); april_assert(!lower_baseline.empty() && "Lower baseline must not be empty"); //FILE *ft son las transiciones int width = source->width(); int height = source->height(); /* Definimos 4 alturas relevantes en las imagenes * * IMAGEN DESTINO IMAGEN ORIGEN * * - 0 --------------------------- cur_asc - * | ascenders | * - dst_upper ----------------- cur_upper - * | body | * - dst_lower ----------------- cur_lower - * | descenders | * - dst_height-1 --------------- cur_desc - */ int tdims[2] = {width, 4}; (*transitions) = new MatrixFloat(2, tdims); MatrixFloat::random_access_iterator trans(*transitions); int dims[2] = {height, width}; MatrixFloat *result_mat = new MatrixFloat(2, dims); matFill(result_mat, 1.0f); ImageFloat *result = new ImageFloat(result_mat); int asc_idx = 0; int upper_idx = 0; int lower_idx = 0; int desc_idx = 0; Point2D next_asc, next_upper, next_lower, next_desc; Point2D prev_asc, prev_upper, prev_lower, prev_desc; prev_asc = get_first_point(ascenders, 0.0f, &asc_idx); next_asc = get_next_point(ascenders, asc_idx, width, 0.0f); asc_idx++; prev_desc = get_first_point(descenders, height-1.0f, &desc_idx); next_desc = get_next_point(descenders, desc_idx, width, height-1.0f); desc_idx++; // Default value won't be used due to precondition prev_upper = get_first_point(upper_baseline, -9999.9f, &upper_idx); next_upper = get_next_point(upper_baseline, upper_idx, width, -9999.9f); upper_idx++; // Default value won't be used due to precondition prev_lower = get_first_point(lower_baseline, -9999.9f, &lower_idx); next_lower = get_next_point(lower_baseline, lower_idx, width, -9999.9f); lower_idx++; /* int body_columns=0; float body_size_sum=0.0f; */ int BASELINE_SLACK=int(0.02f*height); for (int column = 0; column < width; column++) { if (column > next_asc.x) { prev_asc = next_asc; next_asc = get_next_point(ascenders, asc_idx, width, 0.0f); asc_idx++; } if (column > next_desc.x) { prev_desc = next_desc; next_desc = get_next_point(descenders, desc_idx, width, height-1.0f); desc_idx++; } if (column > next_upper.x) { prev_upper = next_upper; next_upper = get_next_point(upper_baseline, upper_idx, width, 9999.9f); upper_idx++; } if (column > next_lower.x) { prev_lower = next_lower; next_lower = get_next_point(lower_baseline, lower_idx, width, 9999.9f); lower_idx++; } float cur_upper = max(0.0f, prev_upper.y + ((column - prev_upper.x) / (next_upper.x-prev_upper.x)) * (next_upper.y - prev_upper.y) - BASELINE_SLACK); float cur_lower = min(height - 1.0f, prev_lower.y + ((column - prev_lower.x) / (next_lower.x - prev_lower.x)) * (next_lower.y - prev_lower.y) + BASELINE_SLACK); if (cur_upper > cur_lower) { swap(cur_upper, cur_lower); } float cur_asc = min(cur_upper, prev_asc.y + ((column - prev_asc.x) / (next_asc.x - prev_asc.x) ) * (next_asc.y - prev_asc.y)); float cur_desc = max(cur_lower, prev_desc.y + ((column - prev_desc.x) / (next_desc.x - prev_desc.x)) * (next_desc.y - prev_desc.y)); // Classify the pixels int asc = round(cur_asc); int upper = round(cur_upper); int lower = round(cur_lower); int desc = round(cur_desc); trans(column, 0) = asc; trans(column, 1) = upper; trans(column, 2) = lower; trans(column, 3) = desc; // printf("%d %d %d %d %d\n", column, asc, upper, lower, desc); classify_pixel(source, result, column, asc, upper, ASC_CODE); classify_pixel(source, result, column, upper, lower, BODY_CODE); classify_pixel(source, result, column, lower, desc, DESC_CODE); } return result; } /* * Img2 is used to compute a indexed softmax value using the indexes from the first image * in this case the matrix will have 3 columns: index class_img class_img2 * useful to compute the error of an image */ MatrixFloat * get_indexes_from_colored(ImageFloat *img, ImageFloat *img2) { // Compute the number of pixels int total = 0; int width = img->width(); int height = img->height(); // float eps = 0.05; for (int col = 0; col < width; ++col) { for(int row = 0; row < height; ++row) { if (is_black((*img)(col,row),0.8)) total++; } } int n_imgs = 1; if (img2) { n_imgs = 2; } int dims[2] = {total,n_imgs + 1}; MatrixFloat * m_pixels = new MatrixFloat(2, dims); int current = 0; for (int col= 0; col < width; ++col){ for(int row = 0; row < height; ++row) { float value = (*img)(col,row); float tag = 0; float index = (row)*width+col+1; if (is_black(value,0.8)) { tag = get_tag(value); (*m_pixels)(current,0) = index; (*m_pixels)(current,1) = tag; if (img2) { float value2 = (*img2)(col,row); int tag2 = get_tag(value2); (*m_pixels)(current,2) = tag2; } current++; } } } return m_pixels; } // Class Set Points SetPoints::SetPoints(ImageFloat *img) { // Compute connected components of the image this->img = img; ccPoints = new vector< PointComponent >(); size = 0; num_points = 0; } void SetPoints::addPoint(int component, interest_point ip){ if (component < 0 || component >= size){ fprintf(stderr, "Warning the component %d does not exist!! (Total components %d)\n", component, size); return; } (*ccPoints)[component].push_back(ip); ++num_points; } void SetPoints::addComponent() { if ((size_t) size != ccPoints->size()) fprintf(stderr, "Size sincronization error %d %lu\n", size, ccPoints->size()); april_assert("Size sincronization error" && (size_t)size == ccPoints->size()); (*ccPoints).push_back(PointComponent()); ++size; } // Class Interest Points ConnectedPoints::ConnectedPoints(ImageFloat *img): SetPoints::SetPoints(img){ // Compute connected components of the image imgCCs = new ImageConnectedComponents(img); ccPoints->resize(imgCCs->size); size = imgCCs->size; fprintf(stderr, "Hay %d componentes\n", imgCCs->size); num_points = 0; } void SetPoints::addComponent(PointComponent &component) { if ((size_t) size != ccPoints->size()) fprintf(stderr, "Size sincronization error %d %lu\n", size, ccPoints->size()); april_assert("Size sincronization error" && (size_t)size == ccPoints->size()); (*ccPoints).push_back(component); ++size; } void ConnectedPoints::addPoint(interest_point ip) { int x, y; x = ip.x; // It is local maxima, add 1 to the y for take the component if( ip.natural_type) { y = ip.y + 1; } else { y = ip.y - 1; } int component = this->imgCCs->getComponent(x,y); if (component >= 0) { SetPoints::addPoint(component,ip); ++num_points; } else { fprintf(stderr,"Warning the point of interest (%d,%d,%d, %d) is not in any component (%d, %d)\n", ip.x, ip.y, ip.point_class, ip.natural_type, x, y); } } /** * * Points comparatarors * **/ bool componentComparator(PointComponent &v1, PointComponent &v2) { if (v1.size() == 0) { return false; } if (v2.size() == 0) { return true; } return v1[0] < v2[0]; } bool interestPointXComparator(interest_point &v1, interest_point &v2) { return v1.x < v2.x; } void PointComponent::sort_by_confidence() { if (size() > 0) AprilUtils::Sort(&(*this)[0], (int)size()); } void PointComponent::sort_by_x() { AprilUtils::Sort(&(*this)[0], size(), interestPointXComparator); } void SetPoints::sort_by_confidence() { if (!size) return; for (int i = 0; i < size; ++i) { (*ccPoints)[i].sort_by_confidence(); } } void SetPoints::sort_by_x() { // Sort first by confidence and then sort by x each component sort_by_confidence(); for (int i = 0; i < size; ++i) { (*ccPoints)[i].sort_by_x(); } } void SetPoints::print_components() { for(int i = 0; i < size; ++i) { printf("Component %d\n", i); printf("\t size %ld\n", (*ccPoints)[i].size()); for (PointComponent::iterator it = (*ccPoints)[i].begin(); it != (*ccPoints)[i].end(); ++it) { printf("\t%d %d %d (%f)\n", it->x, it->y, it->point_class, it->log_prob); } } } // Takes float SetPoints::component_affinity(int component, interest_point &ip) { if (component < 0 || component >= size){ fprintf(stderr, "Warning (similarity)! The component %d does not exist!! (Total components %d\n", component, size); return 0.0; } // If the component is empty the affinity is the probability of the point (logscale) PointComponent &cc = (*ccPoints)[component]; float score_max = 0.0; if (cc.size() == 0) return ip.log_prob; for (size_t p = 0; p < cc.size(); ++p){ score_max = max(score_max, similarity(cc[p], ip)); } return score_max; } float angle_diff(interest_point &a, interest_point &b) { float alpha = a.angle(b); return min(fabs(alpha), fabs(2*M_PI-alpha)); } float SetPoints::similarity(interest_point &ip1, interest_point &ip2) { float alpha_threshold = M_PI/8; interest_point *a = &ip1; interest_point *b = &ip2; // Two cases // Are the same class if (ip1.point_class == ip2.point_class) { if (a->x > b->x){ a = &ip2; b = &ip1; } //float alpha = fmod(a->angle(*b)+2*M_PI + alpha_threshold/2, (2*M_PI)); float alpha = angle_diff(*a, *b); if (alpha < alpha_threshold) return 1.0; } else { // They're are different classes return 1.0; } return 0.0; } /* SetPoints * ConnectedPoints::computePoints() { SetPoints * mySet = new SetPoints(img); int cini = -1; int cfin = 0; int threshold = 1.0; // Process each connected component for (int cc = 0; cc < size; ++cc) { printf("Computing connected component %d/%d\n", cc, size); if (!(*ccPoints)[cc].size()) continue; //Add an empty set cini = cfin; cfin++; mySet->addComponent(); for (size_t p = 0; p < (*ccPoints)[cc].size(); ++p) { bool added = false; // for (interest_point ip : (*ccPoints)[cc]) { for (int current_set = cini; current_set < cfin; ++current_set) { float affinity = mySet->component_affinity(current_set, (*ccPoints)[cc][p]); if (affinity >= threshold){ //Add the point mySet->addPoint(current_set, (*ccPoints)[cc][p]); added = true; break; } //added } //components if (!added) { // Check if it is the first point if (p) { ++cfin; mySet->addComponent(); } mySet->addPoint(cfin-1, (*ccPoints)[cc][p]); } }//Point } return mySet; }*/ SetPoints * ConnectedPoints::computePoints() { SetPoints * mySet = new SetPoints(img); float threshold = 100.0; //Process each component for (int cc = 0; cc < size; ++cc) { PointComponent &component = (*ccPoints)[cc]; int n_points = component.size(); if (n_points == 0) continue; PointComponent *base_line = component.get_points_by_type(BASELINE); double sse = base_line->line_least_squares(); //Compute the regression over the points of the line printf("%d %d %f %f\n", cc, (int)base_line->size(),sse, sse/n_points); if (sse/n_points < threshold) { mySet->addComponent(*base_line); } } return mySet; } PointComponent *PointComponent::get_points_by_type(const int point_class, const float min_prob) { // TODO: Check if cc is on the range PointComponent *l = new PointComponent(); for(size_t i = 0; i < size(); ++i) { interest_point v = (*this)[i]; if (v.point_class == point_class and v.log_prob > min_prob) { l->push_back(v); } } return l; } line * PointComponent::get_regression_line() { // TODO: Move to geometry size_t n = this->size(); if (n <= 1) return NULL; double *vx = new double[n]; double *vy = new double[n]; for (size_t i = 0; i < n; ++i) { vx[i] = (*this)[i].x; vy[i] = (*this)[i].y; } double a, b; least_squares(vx,vy, n, a, b); delete []vx; delete []vy; return new line(b,a); } double PointComponent::line_least_squares() { size_t n = size(); if (n <= 1) return 0.0; line *myLine = this->get_regression_line(); double sse = 0.0; for (size_t i = 0; i < size(); ++i) { double dist = myLine->distance((*this)[i]); sse += dist*dist; } delete myLine; return sse; } } // namespace InterestPoints april-ann-0.4.1/packages/imaging/interest_points/c_src/interest_points.h000066400000000000000000000160031263004425400265120ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco * Zamora-Martinez, Joan Pastor-Pellicer * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef INTEREST_POINTS_H #define INTEREST_POINTS_H #include #include "image.h" #include "image_connected_components.h" #include "datasetFloat.h" #include "utilImageFloat.h" #include "pair.h" #include "vector.h" #include "geometry.h" using AprilUtils::vector; using AprilUtils::Point2D; /** * @brief Functions and other utilities for InterestPoints approach. * @note Published at: * - S. España-Boquera, M.J. Castro-Bleda, J. Gorbe-Moya, F. Zamora-Martínez, * *Improving Offline Handwritten Text Recognition with Hybrid HMM/ANN * Models*, IEEE TPAMI 33(4), 767-769, 2011 * - J. Gorbe-Moya, S. España-Boquera, F. Zamora-Martínez, M.J. Castro-Bleda, * *Handwritten Text Normalization by using Local Extrema Classification*. * PRIS, 164-172, 2008. */ namespace InterestPoints { enum {ASCENDER=1, TOPLINE, CENTRAL, BASELINE, DESCENDER, OTHER}; /** * @brief Given an Image returns a vector with the local maxima and local minima of the given image. * * @param[in] pimg Pointer to the image * @param[in] threshold_white More than this value is considered black * @param[in] threshold_black Less than this value is set to white * @param[in] local_context The number of pixels in stroke that is used to compute the local maxima/minima * @param[in] duplicate_interval The minimum distance of locals within the same stroke */ AprilUtils::vector* extract_points_from_image_old(Imaging::ImageFloat *pimg, float threshold_white = 0.6, float threshold_black = 0.4, int local_context = 6, int duplicate_interval = 5); /** * @brief Given an Image returns a vector with the local maxima and local minima of the given image. * * @param[in] pimg Pointer to the image * @param[out] local_minima Return the points of the local minima contour * @param[out] local_maxima Return the points of the local a contour * @param[in] threshold_white More than this value is considered black * @param[in] threshold_black Less than this value is set to white * @param[in] local_context The number of pixels in stroke that is used to compute the local maxima/minima * @param[in] duplicate_interval The minimum distance of locals within the same stroke */ void extract_points_from_image(Imaging::ImageFloat *pimg, AprilUtils::vector *local_minima, AprilUtils::vector *local_maxima, float threshold_white= 0.4, float threshold_black = 0.6, int local_context = 6, int duplicate_interval = 3, bool reverse = true); Imaging::ImageFloatRGB * area_to_rgb(Imaging::ImageFloat *img); /* * * * */ Imaging::ImageFloat *get_pixel_area(Imaging::ImageFloat *source, AprilUtils::vector ascenders, AprilUtils::vector upper_baseline, AprilUtils::vector lower_baseline, AprilUtils::vector descenders, Basics::MatrixFloat **transitions); Basics::MatrixFloat *get_image_matrix_from_index(Basics::DataSetFloat *ds_out, Basics::DataSetFloat *indexed, int width, int height, int num_classes = 3); Imaging::ImageFloat *get_image_area_from_dataset(Basics::DataSetFloat *ds_out, Basics::DataSetFloat *indexed, int width, int height, int num_classes, float threshold = 0.8); Basics::MatrixFloat * get_indexes_from_colored(Imaging::ImageFloat *img, Imaging::ImageFloat *img2=NULL); Imaging::ImageFloat *refine_colored(Imaging::ImageFloat *img, Basics::MatrixFloat *mat, int num_classes = 3); struct interest_point:AprilUtils::Point { bool natural_type; int point_class; float log_prob; interest_point() {} interest_point(int x, int y, int point_class, bool type, float log_prob): Point(x,y), natural_type(type), point_class(point_class), log_prob(log_prob) {} bool operator< (interest_point &ip) { return this->log_prob > ip.log_prob; } float angle(interest_point &ip) { float deltaY = ip.y - this->y; float deltaX = ip.x - this->x; return atan2(deltaY, deltaX); } }; class PointComponent:public vector { public: PointComponent(int size):vector(size){}; PointComponent():vector(){}; double line_least_squares(); PointComponent *get_points_by_type(const int point_class, \ const float min_prob = -999999.00); void sort_by_confidence(); void sort_by_x(); AprilUtils::line *get_regression_line(); }; class SetPoints: public Referenced { protected: vector< PointComponent > *ccPoints; int size; int num_points; Imaging::ImageFloat *img; public: SetPoints(Imaging::ImageFloat *img); void addComponent(); void addComponent(PointComponent &); int getNumPoints() { return num_points;}; int getSize() { return size;} PointComponent &getComponent(int cc) { return (*ccPoints)[cc]; } void addPoint(int component, interest_point ip); void addPoint(int component, int x, int y, int c, bool natural_type, float log_prob = 0.0) { addPoint(component, interest_point(x,y,c,natural_type,log_prob)); } void print_components(); void sort_by_confidence(); void sort_by_x(); const vector *getComponents() { return ccPoints; } ~SetPoints(){ delete ccPoints; }; float component_affinity(int component, interest_point &ip); float similarity(interest_point &ip1, interest_point &ip2); }; class ConnectedPoints: public SetPoints { private: Imaging::ImageConnectedComponents *imgCCs; public: ConnectedPoints(Imaging::ImageFloat *img); void addPoint(interest_point ip); void addPoint(int x, int y, int c, bool natural_type, float log_prob = 0.0) { addPoint(interest_point(x,y,c,natural_type,log_prob)); }; SetPoints *computePoints(); ~ConnectedPoints() { delete imgCCs; }; }; } #endif april-ann-0.4.1/packages/imaging/interest_points/lua_src/000077500000000000000000000000001263004425400234475ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/interest_points/lua_src/interest_points.lua000066400000000000000000000647741263004425400274250ustar00rootroot00000000000000interest_points = interest_points or {} local pointClassifier,methods = class("interest_points.pointClassifier") interest_points.pointClassifier = pointClassifier april_set_doc(interest_points.pointClassifier, { class = "class", summary = "Util for computing EyeFish transformation", description ={ "This class prepare the linear transformation.", }, }) april_set_doc(interest_points.pointClassifier, { class = "method", summary = "Constructor", description ={ "This class prepare the linear transformation.", }, outputs = {"A Point Classifier object"}, }) function pointClassifier:constructor(ancho, alto, miniancho, minialto, reverse_old) -- prepara la configuracion para aplicar el ojo de pez con dataset.linear_comb -- local functions ------ convertir local function convertir(v,N) -- toma el vector y lo escala en N partes local total = 0 local M = #v for i=1,M do total=total+v[i] end local resul = {} local pedazo = total/N local indice = 1 local queda = pedazo for i=1,M do local trozo = v[i] while trozo > 0 and indice<=N do if trozo >= queda then table.insert(resul,{i,indice,queda/v[i]}) trozo = trozo-queda queda = pedazo indice = indice+1 else table.insert(resul,{i,indice,trozo/v[i]}) queda = queda-trozo trozo = 0 end end end return resul end ------ crear_vector_estrecho local function crear_vector_estrecho(lado) local v = {} for i=1,lado do v[i] = 0.1+math.pow(1-math.pow(math.abs(i-0.5-(lado/2))/lado,2.5),300) end return v end ------ crear_vector_suave local function crear_vector_suave(lado) local v = {} for i=1,lado do v[i] = 0.1+math.pow(1-math.pow(math.abs(i-0.5-(lado/2))/lado,2),10) end return v end -- Funcion para invertir_tlc (Forwar tlc) local function invertir_tlc(tlc) local threshold = 0 local inv_tlc = {} for i, lsources in pairs(tlc) do for j, v in ipairs(lsources) do local src, w = unpack(v) if inv_tlc[src] == nil then inv_tlc[src] = {} end if (w > threshold) then table.insert(inv_tlc[src], {i-1, w}) end end end return inv_tlc end -- function body local vancho = crear_vector_estrecho(ancho) local valto = crear_vector_suave(alto) local r_ancho = convertir(vancho,miniancho) local r_alto = convertir(valto,minialto) local lenr_ancho = #r_ancho local lenr_alto = #r_alto local tlc = {} -- tabla linear combination for i=1,lenr_alto do local y1,y,pesoy = unpack(r_alto[i]) for j=1,lenr_ancho do local x1,x,pesox = unpack(r_ancho[j]) local minipos = (y-1)*miniancho+x -- la posicion x,y en la matriz resultante if tlc[minipos] == nil then tlc[minipos] = {} end local pos = (y1-1)*ancho+x1 table.insert(tlc[minipos],{pos,pesox*pesoy}) end end -- normalizar cada cosa: for i,j in pairs(tlc) do local total = 0 for k,l in ipairs(j) do total = total+l[2] end for k,l in ipairs(j) do l[2] = l[2]/total end end self.ancho = ancho self.alto = alto self.miniancho = miniancho self.minialto = minialto self.table_inv = invertir_tlc(tlc) self.inv_tlc = dataset.linear_comb_conf(self.table_inv) self.tlc = dataset.linear_comb_conf(tlc) self.white = (reverse_old and 1) or 1 self.reverse_old = reverse_old end --------------------------------------------------- -- crop_image(img, x, y, tlc) -> table --------------------------------------------------- function methods:crop_image(img, x, y) return self:applyLinearComb(img, x, y):getPattern(1) end methods.getFishDs = april_doc{ class = "method", summary = "Main function for obtaining the FishEye Dataset", description ={ "Recieves an image and a point a generates the corresponding dataset", }, params = { "An Image object", "X coordinate of the point", "Y coordinate of the point" }, outputs = {"A Point Classifier object"}, } .. function(self, img, x, y) local mFish = img:comb_lineal_forward(x,y, self.ancho, self.alto, self.miniancho, self.minialto, self.inv_tlc):clamp(0,1) if self.reverse_old then mFish:complement() end local m = mFish:rewrap(self.minialto,self.miniancho) -- ImageIO.write(Image(m),"kk.png") -- ImageIO.write(img,"kk2.png") local dsFish = dataset.matrix(mFish, { patternSize={self.miniancho*self.minialto}, stepSize={self.miniancho*self.minialto}, numSteps={1}, }) return dsFish end function methods:applyLinearComb(img, x, y) local mat, _, _, dx, dy = img:matrix(),img:geometry() local ds = dataset.matrix(mat, { patternSize={self.alto,self.ancho}, offset={(y+dy)-self.alto/2,(x+dx)-self.ancho/2}, numSteps={1,1}, defaultValue = self.white, -- pixel blanco }) local dslc = dataset.linearcomb(ds,self.tlc) return dslc end ------------------------------------------------------------------------------- -- Given a point an mlp, return the output of the net with that point (window) ----------------------------------------------------------------------------- methods.compute_point = april_doc{ class = "method", summary = "Gets the net output for one point", description ={ "Given a point and mlp, return the output of the net for that point", }, params = { "An Image object", "X coordinate of the point", "Y coordinate of the point" }, outputs = {"Table with the values of the softmax"}, } .. function(self, img, x, y, mlp) local dsPoint = self:getFishDs(img, x, y) local dsOut = mlp:use_dataset{ input_dataset = dsPoint } return dsOut:getPattern(1) end methods.getPointClass = april_doc{ class = "method", summary = "Gets the corresponding class for the point", description ={ "Given a point and mlp, return the max index for that point", }, params = { "An Image object", "X coordinate of the point", "Y coordinate of the point" }, outputs = {"Integer of the winning class"}, } .. function(self, img, x, y, mlp) return self.compute_point(img, x, y, mlp):max() end --Gets a dataset and returns a table with the indexes of the major class function interest_points.getIndexSoftmax(dsOut) local tResult = {} for i, v in dsOut:patterns() do _, p = table.max(v) table.insert(tResult, p) end return tResult end methods.compute_points = april_doc{ class = "method", summary = "Return a dataset with the output of the net", description ={ "Given a list of points and mlp, return the dataset corresponding to output of the mlp to that set of points", }, params = { "An Image object", "List of points Tuples(x,y)", "Trainable Object" }, outputs = {"Dataset of size Num_Classes x Num_Points"}, } .. function(self, img, points, mlp) --Compute the matrix (Forward) local fishEyes = {} for i, point in ipairs(points) do x,y = unpack(point) local dsFish = self:getFishDs(img, x, y) table.insert(fishEyes, dsFish) end local dsFishes = dataset.union(fishEyes) -- Classify the datasets local dsOut = mlp:use_dataset({input_dataset=dsFishes}) return dsOut end ---------------------------------------------------------- -- Given a image extract all the points and classify them -- ------------------------------------------------------- function methods:classify_points(img, points, mlp) local dsOut = self:compute_points(img, points, mlp) local classes = interest_points.getIndexSoftmax(dsOut) local res = {} for i, c in ipairs(classes) do x, y = unpack(points[i]) table.insert(res, {x,y,c, dsOut:getPattern(i)}) -- table.insert(res, {x,y,c, dsOut:getPattern(i)[c]}) -- Get the confidence end --[[ local scores = self:compute_points(img, points, mlp) local res = {} for i, score in ipairs(scores) do x = points[i][1] y = points[i][2] _, c = score:max() table.insert(res, {x, y, c}) end return res --]] return res end function methods:extract_points(img, mlpUppers, mlpLowers) local uppers, lowers local img_orig = img if (self.reverse_old) then img = img:invert_colors() end -- The extraction is done by reversing the image uppers, lowers = interest_points.extract_points_from_image(img) img = img_orig -- Compute uppers local uppers_classified = self:classify_points(img, uppers, mlpUppers) -- Compute uppers local lowers_classified = self:classify_points(img, lowers, mlpLowers) return uppers_classified, lowers_classified end ---------------------------------------------------------------------------- -- table_points a (x, y, c) table where c is the majority class of the point -- Utility function that gets a list of points and the class of the points -- ------------------------------------------------------------------------- function interest_points.sort_by_class(table_points, classes) local res = {} for c = 1, classes do table.insert(res, {}) end for _, point in ipairs(table_points) do x, y, c = unpack(point) table.insert(res[c], {x,y}) end return res end function interest_points.filter_points(points, h, w) local ASCENDER=1 local UPPER_BASELINE=2 local BODY=3 local LOWER_BASELINE=4 local DESCENDER=5 local function filtrar_repetidos(mark_index) for x,tblx in pairs(mark_index) do for _, class in pairs({ASCENDER, UPPER_BASELINE}) do if mark_index[x][class] ~= nil and #mark_index[x][class] >= 2 then local ymin = mark_index[x][class][1] for idx, y in ipairs(mark_index[x][class]) do if y < ymin then ymin = y end end local tbl_body = table.ifilter(mark_index[x][class], function(k,v) return v ~= ymin end) mark_index[x][class] = {ymin} mark_index[x][BODY] = table.join(mark_index[x][BODY], tbl_body) --print("x=",x,"class=",class,"ymin=",ymin,"tbl:", table.concat(mark_index[x][class]), -- "body: ",table.concat(tbl_body, ","))--,"body_old:", table.concat(mark_index[x][BODY], ",")) end end for _, class in pairs({DESCENDER, LOWER_BASELINE}) do if mark_index[x][class] ~= nil and #mark_index[x][class] >= 2 then --print("#mark_index[x][class]=", #mark_index[x][class]) local ymax = mark_index[x][class][1] for idx, y in ipairs(mark_index[x][class]) do if y > ymax then ymax = y end end local tbl_body = table.ifilter(mark_index[x][class], function(k,v) return v ~= ymax end) mark_index[x][class] = {ymax} mark_index[x][BODY] = table.join(mark_index[x][BODY], tbl_body) --print("x=",x,"class=",class,"ymax=",ymax,"tbl:", table.concat(mark_index[x][class]), -- "body: ",table.concat(tbl_body, ","))--,"body_old:", table.concat(mark_index[x][BODY], ",")) end end end end ------------------------------------------- -- filtrar_repetidos_array(tbl, func) -> table -- Elimina elementos con la x repetida de una tabla ordenada de puntos, dejando el que cumpla func (tipicamente min o max) ------------------------------------------- local function filtrar_repetidos_array(tbl, func) local result = {} local y for i=1,#tbl do if y == nil then y = tbl[i][2] end if tbl[i+1]~= nil and tbl[i+1][1] == tbl[i][1] then y = func(y, tbl[i+1][2]) else table.insert(result,{tbl[i][1], y}) y=nil end end return result end --------------------------- -- argmax(tbl) -> value -- Devuelve el x tal que tbl[x] = max(tbl[i] para todo i en tbl) --------------------------- local function argmax(tbl) local wmax = 1 local max = tbl[1] for i,j in ipairs(tbl) do if j > max then wmax = i max = j end end if max ~= nil then return wmax,max else return nil, nil end end ------------------------------------------------------------- -- get_first_point(tbl, width, default_y) -> point, index ------------------------------------------------------------- local function get_first_point(tbl, width, default_y) if #tbl == 0 then return {0, default_y}, 0 else local result = {0, tbl[1][2]} if tbl[1][1] == 0 then return result, 1 else return result, 0 end end end --------------------------------------------------------------- -- get_next_point(tbl, index, width, default_y) -> point --------------------------------------------------------------- local function get_next_point(tbl, index, width, default_y) if index+1 < 1 then error("invalid index") end if #tbl > 0 then if index < #tbl then return tbl[index+1] else return {width-1, tbl[#tbl][2]} end else return {width-1, default_y} end end local body = {} ------------------------------------------------------------- -- get_first_point(tbl, width, default_y) -> point, index ------------------------------------------------------------- local function get_first_point(tbl, width, default_y) if #tbl == 0 then return {0, default_y}, 0 else local result = {0, tbl[1][2]} if tbl[1][1] == 0 then return result, 1 else return result, 0 end end end --------------------------------------------------------------- -- get_next_point(tbl, index, width, default_y) -> point --------------------------------------------------------------- local function get_next_point(tbl, index, width, default_y) if index+1 < 1 then error("invalid index") end if #tbl > 0 then if index < #tbl then return tbl[index+1] else return {width-1, tbl[#tbl][2]} end else return {width-1, default_y} end end local function filter_repeated(tbl, func) print ("Filtering") local result = {} local y for i=1,#tbl do if y == nil then y = tbl[i][2] end if i+1 <= #tbl and tbl[i+1][1] == tbl[i][1] then y = func(y, tbl[i+1][2]) else table.insert(result,{tbl[i][1], y}) y=nil end end return result end -- Mark index is genereted given the classe local mark_index = {} for i, t in ipairs(points) do for _, p in ipairs(t) do x, y = unpack(p) if not mark_index[x] then mark_index[x] = {} end if not mark_index[x][i] then mark_index[x][i] = {} end table.insert(mark_index[x][i],y) end end filtrar_repetidos(mark_index) -- START local tables = {{},{},{},{},{}} for x, t in pairs(mark_index) do for class, y_tbl in pairs(t) do for _,y in ipairs(y_tbl) do table.insert(tables[class], {x,y}) end end end for class=1,5 do table.sort(tables[class], function(a,b) return a[1] next_asc[1] or i == #tables[BODY] then local x,y = unpack(highest) local asc_y = prev_asc[2] + ((x-prev_asc[1])/(next_asc[1]-prev_asc[1]))*(next_asc[2]-prev_asc[2]) --printf("---> highest=(%d,%d), asc_y=%d\n", x,y, asc_y) if y < asc_y then table.insert(new_ascenders, highest) --printf("inserted ascender: (%d, %d)\n", x, y) end while p[1] > next_asc[1] do prev_asc = next_asc next_asc = get_next_point(tables[ASCENDER], asc_idx, w, 0) asc_idx = asc_idx+1 end highest = p end if p[2] < highest[2] then highest=p end end tables[ASCENDER] = table.join(tables[ASCENDER], new_ascenders) table.sort(tables[ASCENDER], function(a,b) return a[1] next_desc[1] or i == #tables[BODY] then local x,y = unpack(lowest) local desc_y = prev_desc[2] + ((x-prev_desc[1])/(next_desc[1]-prev_desc[1]))*(next_desc[2]-prev_desc[2]) --printf("---> lowest=(%d,%d), desc_y=%d\n", x,y, desc_y) if y > desc_y then table.insert(new_descenders, lowest) --printf("inserted descender: (%d, %d)\n", x, y) end while p[1] > next_desc[1] do prev_desc = next_desc next_desc = get_next_point(tables[DESCENDER], desc_idx, w, h-1) desc_idx = desc_idx + 1 end lowest = p end if p[2] > lowest[2] then lowest=p end end tables[DESCENDER] = table.join(tables[DESCENDER], new_descenders) table.sort(tables[DESCENDER], function(a,b) return a[1] threshold and ((upper and class < 3) or (class >3)) then table.insert(result, point) end end return result end -- Given a list of points (x,y,c,confidence) -- returns 5 tables function interest_points.classified_to_tables(num_classes, ...) -- TODO add confidence threshold! local result = {} for i = 1, num_classes do table.insert(result, {}) end points = {...} for i, t in ipairs(points) do for j, v in ipairs(t) do c = v[3] table.insert(result[c],{v[1],v[2]}) end end for i, t in ipairs(result) do table.sort(t, function(a,b) return a[1] < b[1] end) end return result end ---------------------------------------------------- -- Util functions -- Recieve a table with the tag classes -- Returns a Sparse (softmax) vector of the tags -- ------------------------------------------------ function interest_points.loadTagDataset(points, numClasses) local numClasses = numClasses or 5 local mOut = matrix(#points, points) local dsOut if numClasses == 2 then dsOut = dataset.matrix(mOut) else local dsIndex = dataset.identity(numClasses) local dsOutIndex = dataset.matrix(mOut) dsOut = dataset.indexed(dsOutIndex, {dsIndex}) end return dsOut end ------------------------ -- -- Recieves an image and a interest point table, x_window and y_window parameters, -- and return a returns a dataset of size num_points*((xwindow+1+xwindow*)*(y_window+1+ỳ_window)) -- -- --------------------------- function dataset.interest_point(img, table_points, x_window, y_window, num_classes, reverse) local img_matrix = img:matrix() local white = 1 if reverse then white = 0 end -- Create the dataset over the image local params_img = { patternSize = {y_window*2+1, x_window*2+1}, offset = {-y_window, -x_window}, stepSize = {1,1}, numSteps = img_matrix:dim(), defaultValue = white, circular = {false, false} } local dsImg = dataset.matrix(img_matrix, params_img) -- Create the indexed point -- the table is composed by elems (x, y, c) -- En la imagen es x, y i en la matriz y x local tIndexes = table.imap(table_points, function (elem) local index = elem[2]*img_matrix:dim(2)+elem[1] assert(index <= img_matrix:size()) return index end) local dsIndexes = dataset.matrix(matrix(tIndexes)) local dsPoints = dataset.indexed(dsIndexes, {dsImg}) local dsOut = nil local points if #table_points[1] >= 3 then points = table.imap(table_points, function (elem) return elem[3] end) end return dsPoints, points and interest_points.loadTagDataset(points, num_classes) end --------------------------------------- -- Convolutional and Square point extractor ----------------------------------------- function interest_points.extract_points_NN(img, trainer_uppers, trainer_lowers, x_window, y_window, resize_factor, num_classes) local uppers, lowers local width, height = img:geometry() local new_width = math.floor(width/resize_factor) local new_height = math.floor(height/resize_factor) if resize_factor > 1 then img = img:resize(new_width,new_height) end function get_points_from_NN(points, trainer) local dsIn = dataset.interest_point(img, points, x_window, y_window, num_classes, true) -- Classify the points local dsPred = trainer:use_dataset({input_dataset=dsIn}) local classes = interest_points.getIndexSoftmax(dsPred) local res = {} for i, c in ipairs(classes) do x, y = unpack(points[i]) table.insert(res, {x,y,c, dsPred:getPattern(i)}) -- table.insert(res, {x,y,c, dsOut:getPattern(i)[c]}) -- Get the confidence end return res end uppers, lowers = interest_points.extract_points_from_image(img) --print(line, img, table_points, x_window, y_window,num_classes, true) print(#uppers, #lowers) local uppers_classified = get_points_from_NN(uppers, trainer_uppers) local lowers_classified = get_points_from_NN(lowers, trainer_lowers) function resize_points(points) for i, v in ipairs(points) do v[1] = v[1]*resize_factor v[2] = v[2]*resize_factor end end resize_points(uppers_classified) resize_points(lowers_classified) --local uppers_classified = {} --local lowers_classified = {} print(#uppers_classified,#lowers_classified) return uppers_classified, lowers_classified end april-ann-0.4.1/packages/imaging/interest_points/package.lua000066400000000000000000000021711263004425400241160ustar00rootroot00000000000000 package{ name = "interest_points", version = "1.0", depends = { "dataset", "Image", "image_connected_components" }, keywords = { "image", "interest_points", "line", "ocr" }, description = "Utils for detect and classify interest points in an images", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_interest_points.lua.cc", dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp=true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_interest_points.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{}, document_bind{}, }, } 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-10.371561050415 -9.0806922912598 -0.87448835372925 -0.54378223419189 -6.1053285598755 67 96 3 1 -9.4367942810059 -9.121488571167 -0.014119148254395 -4.3103942871094 -7.8174886703491 106 97 4 1 -10.315668106079 -9.277925491333 -1.4404673576355 -0.27432060241699 -5.81982421875 103 98 4 1 -11.371447563171 -10.758012771606 -2.9234249591827 -0.058065414428711 -5.9408397674561 51 103 3 1 -7.3356132507324 -9.6029806137085 -0.22178411483765 -1.8878886699677 -3.0618443489075 59 104 3 1 -7.085307598114 -9.8843812942505 -0.58906197547913 -1.1020393371582 -2.188619852066 55 106 4 1 -7.6995968818665 -10.85724067688 -1.8543300628662 -0.40707588195801 -1.7294833660126 april-ann-0.4.1/packages/imaging/interest_points/test/testAreaPixel.lua000066400000000000000000000023101263004425400262470ustar00rootroot00000000000000imgFile = "sample_iam.png" pointsFile = "sample_iam.txt" img = ImageIO.read(imgFile):to_grayscale() points = {{},{},{},{},{}} -- Open the interest points list for line in io.open(pointsFile, "r"):lines() do point = map(tonumber, ipairs(string.tokenize(line))) if point[3] <= 5 then table.insert(points[point[3]], point) end end for i,v in ipairs(points) do print (i, #v) end result = interest_points.classify_pixel(img, points[1], points[2],points[4], points[5]) ImageIO.write(result,"classified.png", "png") -- Load The dataset image local m_indexes = interest_points.get_indexes_from_colored(result) local num_classes = 3; w,h = result:geometry() print(w, h) local dsIndex = dataset.identity(num_classes) local dsPositions = dataset.matrix(m_indexes,{ patternSize = {1,1}, offset = {0,0}, numSteps = {m_indexes:dim(1),1}, }) local dsTags = dataset.matrix(m_indexes,{ patternSize = {1,1}, offset = {0,1}, numSteps = {m_indexes:dim(1),1}, }) local dsSoftmax = dataset.indexed(dsTags, {dsIndex}) local computed = interest_points.get_image_area_from_dataset(dsSoftmax, dsPositions, w, h) ImageIO.write(computed,"computed.png", "png") april-ann-0.4.1/packages/imaging/interest_points/test/testConnected.lua000066400000000000000000000004261263004425400263050ustar00rootroot00000000000000imgFile = arg[1] netFile = arg[2] local width = 500 local height = 250 local miniwidth = 50 local miniheight = 30 img = ImageIO.read(imgFile):to_grayscale() -- Generates the CCs of the image cps = interest_points.ConnectedPoints(img) -- compute interest_points print(cps) april-ann-0.4.1/packages/imaging/interest_points/test/testConnectedSample1.lua000066400000000000000000000021511263004425400275250ustar00rootroot00000000000000imgFile = "sample2.png" pointsFile = "sample2.txt" img = ImageIO.read(imgFile):to_grayscale() -- Generates the CCs of the image cps = interest_points.ConnectedPoints(img) -- Open the interest points list for line in io.open(pointsFile, "r"):lines() do point = map(tonumber, ipairs(string.tokenize(line))) print (point[3]) if point[3] == 4 then print("Adding ", point[1], point[2], point[3]) cps:addPoint(point) end end print("Total added: ", cps:getNumPoints()) print("Components\n") cps:printComponents() cps:sortByX() print("Sorted components\n") cps:printComponents() t = cps:getComponentPoints() print("I have ", #t, "components") for i,component in ipairs(t) do print ("Component ", i) --component, #component) for j, point in ipairs(component) do print(point[1], point[2], point[3]) end end width, height = img:geometry() mySVG = imageSVG.fromImageFile(imgFile, width, height) mySVG:addPaths(t) mySVG:write("sample2.svg") print("Computing components") sp = cps:computeComponents() print(sp:getNumPoints()) print("New component\n") sp:printComponents() april-ann-0.4.1/packages/imaging/interest_points/test/test_interest_points.lua000066400000000000000000000012121263004425400277650ustar00rootroot00000000000000imgFile = arg[1] img = ImageIO.read(imgFile):to_grayscale() --mySVG = imageSVG({width=300, height = 300}) --mySVG:setHeader({}) --mySVG:setFooter({}) w, h = img:geometry() print(w, h) mySVG = imageSVG.fromImageFile(imgFile, w, h) --img = img:invert_colors() uppers, lowers = interest_points.extract_points_from_image(img) print(#uppers) print(#lowers) print("uppers", uppers[1][1], uppers[1][2]) outFile = string.remove_extension(imgFile)..".svg" for _, p in ipairs(uppers) do mySVG:addSquare(p, {}) end for _, p in ipairs(lowers) do mySVG:addSquare(p, {color = "red"}) end mySVG:write(outFile) print(#uppers) print(#lowers) april-ann-0.4.1/packages/imaging/interest_points/test/test_interest_points2.lua000066400000000000000000000026151263004425400300570ustar00rootroot00000000000000imgFile = arg[1] mlpFile = arg[2] bunchsize = arg[3] or 64 img = ImageIO.read(imgFile):to_grayscale() -- Load the image print (img_inv, img) w, h = img:geometry() print(mlpFile) mlp = ann.mlp.all_all.load(mlpFile, bunchsize) trainer = trainable.supervised_trainer(mlp, nil, bunch_size) mySVG = imageSVG.fromImageFile(imgFile, w, h) --img = img:invert_colors() uppers, lowers = interest_points.extract_points_from_image(img) print(#uppers) print(#lowers) outFile = string.remove_extension(imgFile)..".svg" point = uppers[1] pc = interest_points.pointClassifier(500,250,50, 30, false) res = pc:compute_point(img, point, trainer) cl = pc:classify_point(img, point, trainer) -- Classify uppers local uppers_classified = pc:classify_points(img, uppers, trainer) --local uppers_res = pc:compute_points(img_inv, uppers, mlp) --- Transform in tables local tables = interest_points.sort_by_class(uppers_classified, 5) mySVG:addPointsFromTables(tables) print("Tables: ", #tables) for i=1, 5 do print(i, #tables[i]) end -- Classify lowers local lowers_classified = pc:classify_points(img, lowers, trainer) local lower_res = pc:compute_points(img, uppers, trainer) --- Transform in tables tables = interest_points.sort_by_class(lowers_classified, 5) mySVG:addPointsFromTables(tables) print("Tables: ", #tables) for i=1, 5 do print(i, #tables[i]) end --]] mySVG:write(outFile) print(#uppers) print(#lowers) april-ann-0.4.1/packages/imaging/libpng/000077500000000000000000000000001263004425400200415ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/libpng/binding/000077500000000000000000000000001263004425400214535ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/libpng/binding/bind_libpng.lua.cc000066400000000000000000000050641263004425400250160ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_H #include "libpng.h" #include "constString.h" #include "bind_image_RGB.h" //BIND_END //BIND_HEADER_C #include "bind_april_io.h" #include "smart_ptr.h" //BIND_END //BIND_FUNCTION libpng.read { AprilUtils::constString cs; LUABIND_CHECK_ARGN(==, 1); AprilUtils::SharedPtr stream; if (lua_isstring(L,1)) { LUABIND_GET_PARAMETER(1,constString,cs); const char *filename = (const char *)cs; stream = new AprilIO::FileStream(filename, "r"); } else { stream = lua_toAuxStreamInterface(L,1); } ImageFloatRGB *res = Imaging::LibPNG::readPNG(stream.get()); if (res == NULL) { LUABIND_ERROR("libpng.read failed"); } LUABIND_RETURN(ImageFloatRGB, res); } //BIND_END //BIND_FUNCTION libpng.write { ImageFloatRGB *img; AprilUtils::constString cs; LUABIND_CHECK_ARGN(>=, 1); LUABIND_CHECK_ARGN(<=, 2); LUABIND_GET_PARAMETER(1,ImageFloatRGB,img); const int n = lua_gettop(L); AprilUtils::SharedPtr stream; if (n == 2) { if (lua_isstring(L,2)) { LUABIND_GET_PARAMETER(2,constString,cs); const char *filename = (const char *)cs; stream = new AprilIO::FileStream(filename, "w"); } else { stream = lua_toAuxStreamInterface(L,2); } } else { stream = new AprilIO::OutputLuaStringStream(L); } bool ok = Imaging::LibPNG::writePNG(img, stream.get()); if (!ok) { LUABIND_ERROR("libpng.write failed"); } if (n == 1) { AprilIO::OutputLuaStringStream *lua_stream; lua_stream = (AprilIO::OutputLuaStringStream*)(stream.get()); LUABIND_INCREASE_NUM_RETURNS( lua_stream->push(L) ); } else { LUABIND_RETURN(StreamInterface, stream.get()); } } //BIND_END april-ann-0.4.1/packages/imaging/libpng/c_src/000077500000000000000000000000001263004425400211325ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/libpng/c_src/libpng.cc000066400000000000000000000211661263004425400227220ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include #include "clamp.h" #include "libpng.h" #include "stream.h" using namespace AprilIO; namespace Imaging { namespace LibPNG { static void read_data_fn(png_structp png_ptr, png_bytep dest, png_size_t len) { StreamInterface *fp = (StreamInterface*)png_get_io_ptr(png_ptr); size_t result = fp->get((char*)dest, len); if (result != len) { png_error(png_ptr, "EOF"); } } static void write_data_fn(png_structp png_ptr, png_bytep source, png_size_t len) { StreamInterface *fp = (StreamInterface*)png_get_io_ptr(png_ptr); size_t result = fp->put((const char*)source, len); if (result != len) { png_error(png_ptr, "EOF"); } } static void output_flush_fn(png_structp png_ptr) { StreamInterface *fp = (StreamInterface*)png_get_io_ptr(png_ptr); fp->flush(); } ImageFloatRGB *readPNG(AprilIO::StreamInterface *fp) { png_structp png_ptr; png_infop info_ptr; png_uint_32 width, height; int bit_depth, color_type; unsigned char *image_data; if (!fp->good()) { fprintf(stderr, "LibPNG::readPNG() -> cannot read from stream\n"); return NULL; } // Check signature unsigned char sig[8]; if (fp->get((char*)sig, 8u) < 8u) { fprintf(stderr, "LibPNG::readPNG() -> cannot read signature from stream\n"); return NULL; } if (!png_check_sig(sig, 8)) { fprintf(stderr, "LibPNG::readPNG() -> stream is not a PNG\n"); return NULL; } // Create read and info structs png_ptr = png_create_read_struct(PNG_LIBPNG_VER_STRING, NULL, NULL, NULL); if (!png_ptr) { fprintf(stderr, "LibPNG::readPNG() -> cannot allocate memory for png_struct\n"); return NULL; } info_ptr = png_create_info_struct(png_ptr); if (!info_ptr) { png_destroy_read_struct(&png_ptr, &info_ptr, NULL); fprintf(stderr, "LibPNG::readPNG() -> cannot allocate memory for png_struct\n"); return NULL; } // Set error handling and init I/O if (setjmp(png_jmpbuf(png_ptr))) { png_destroy_read_struct(&png_ptr, &info_ptr, NULL); fprintf(stderr, "Error while initializing I/O\n"); return NULL; } // png_init_io(png_ptr, fp); png_set_read_fn(png_ptr, fp, read_data_fn); png_set_sig_bytes(png_ptr, 8); // 8 bytes already skipped // Read PNG info ; get image attributes png_read_info(png_ptr, info_ptr); png_get_IHDR(png_ptr, info_ptr, &width, &height, &bit_depth, &color_type, NULL, NULL, NULL); // ignore alpha png_set_strip_alpha(png_ptr); // Expand palette to full RGB if (color_type == PNG_COLOR_TYPE_PALETTE) png_set_palette_to_rgb(png_ptr); // Expand low-bit-depth grayscale to 8 bit if (color_type == PNG_COLOR_TYPE_GRAY && bit_depth < 8) png_set_expand_gray_1_2_4_to_8(png_ptr); // Expand grayscale to RGB if (color_type == PNG_COLOR_TYPE_GRAY) png_set_gray_to_rgb(png_ptr); // Reduce depth to 8 bits/channel if needed if (bit_depth == 16) png_set_strip_16(png_ptr); // Prepare to read pixels if (setjmp(png_jmpbuf(png_ptr))) { png_destroy_read_struct(&png_ptr, &info_ptr, NULL); fprintf(stderr, "Error while reading PNG image from stream\n"); return NULL; } png_uint_32 rowbytes; int channels; png_read_update_info(png_ptr, info_ptr); rowbytes = png_get_rowbytes(png_ptr, info_ptr); channels = (int)png_get_channels(png_ptr, info_ptr); image_data = new unsigned char[rowbytes*height]; // libpng needs an array with pointers to the beginning of each row png_bytep *row_pointers = new png_bytep[height]; for (unsigned int i=0; i(height), static_cast(width)}; Basics::Matrix *m = new Basics::Matrix(2, dims); AprilMath::MatrixExt::Initializers::matFill(m, FloatRGB(0.0f,0.0f,0.0f)); ImageFloatRGB *res = new ImageFloatRGB(m); unsigned char *p = image_data; for (unsigned int y=0; ywidth(); // Open file for writing if (!fp->good()) { fprintf(stderr, "LibPNG::writePNG() -> cannot write at stream\n"); return false; } // Create png struct and info struct png_ptr = png_create_write_struct(PNG_LIBPNG_VER_STRING, NULL, NULL, NULL); if (!png_ptr) { fprintf(stderr, "LibPNG::writePNG() -> cannot allocate memory for png_struct\n"); goto finish; } info_ptr = png_create_info_struct(png_ptr); if (!info_ptr) { fprintf(stderr, "LibPNG::writePNG() -> cannot allocate memory for png_struct\n"); goto destroy_png_struct; } // Init I/O if (setjmp(png_jmpbuf(png_ptr))) { fprintf(stderr, "LibPNG::writePNG() -> Error while initializing I/O\n"); goto destroy_png_struct; } // png_init_io(png_ptr, fp); png_set_write_fn(png_ptr, fp, write_data_fn, output_flush_fn); // Write header (fixed to RGB, 24bpp) if (setjmp(png_jmpbuf(png_ptr))) { fprintf(stderr, "LibPNG::writePNG() -> Error while writing header\n"); goto destroy_png_struct; } png_set_IHDR(png_ptr, info_ptr, img->width(), img->height(), 8, PNG_COLOR_TYPE_RGB, PNG_INTERLACE_NONE, PNG_COMPRESSION_TYPE_BASE, PNG_FILTER_TYPE_BASE); png_write_info(png_ptr, info_ptr); // Create aux pixel buffer image_data = new unsigned char[img->width() * img->height() * 3]; p = image_data; for (int y=0; y < img->height(); y++) { for (int x=0; x < img->width(); x++) { FloatRGB c = (*img)(x,y); *p++ = (unsigned char)(AprilUtils::clamp(c.r, 0.0f, 1.0f)*255.0f); *p++ = (unsigned char)(AprilUtils::clamp(c.g, 0.0f, 1.0f)*255.0f); *p++ = (unsigned char)(AprilUtils::clamp(c.b, 0.0f, 1.0f)*255.0f); } } // Create row_pointers array row_pointers = new png_bytep[img->height()]; for (int i=0; i < img->height(); i++) row_pointers[i] = image_data + i*rowbytes; // Write pixel data if (setjmp(png_jmpbuf(png_ptr))) { fprintf(stderr, "LibPNG::writePNG() -> Error while writing pixel data\n"); goto delete_aux_buffers; } png_write_image(png_ptr, row_pointers); // End write if (setjmp(png_jmpbuf(png_ptr))) { fprintf(stderr, "LibPNG::writePNG() -> Error while ending write\n"); goto delete_aux_buffers; } png_write_end(png_ptr, NULL); success = true; // Cleanup (various stages) delete_aux_buffers: delete[] row_pointers; delete[] image_data; destroy_png_struct: png_destroy_write_struct(&png_ptr, &info_ptr); finish: return success; } } // namespace LibPNG } // namespace Imaging april-ann-0.4.1/packages/imaging/libpng/c_src/libpng.h000066400000000000000000000021171263004425400225570ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LIBPNG_H #define LIBPNG_H #include "utilImageFloat.h" #include namespace Imaging { namespace LibPNG { ImageFloatRGB* readPNG(AprilIO::StreamInterface *fp); // returns NULL if error bool writePNG(ImageFloatRGB *img, AprilIO::StreamInterface *fp); } } #endif april-ann-0.4.1/packages/imaging/libpng/lua_src/000077500000000000000000000000001263004425400214715ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/libpng/lua_src/libpng.lua000066400000000000000000000011611263004425400234460ustar00rootroot00000000000000ImageIO.handlers["png"] = { read=libpng.read, write=libpng.write } -- support for IPyLua local function ImageRGB_show(obj) local data = { ["text/plain"] = tostring(obj), ["image/png"] = ee5_base64.encode(libpng.write(obj)), } local w,h = obj:geometry() local metadata = { ["image/png"] = { width = w, height = h } } return data,metadata end -- support for IPyLua class.extend_metamethod(ImageRGB, "ipylua_show", ImageRGB_show) local function Image_show(obj) local obj = obj:to_RGB() return ImageRGB_show(obj) end -- support for IPyLua class.extend_metamethod(Image, "ipylua_show", Image_show) april-ann-0.4.1/packages/imaging/libpng/package.lua000066400000000000000000000021311263004425400221340ustar00rootroot00000000000000 package{ name = "libpng", version = "1.0", depends = { "Image", "ImageIO", "util", "aprilio" }, pkgconfig_depends = { "libpng" }, keywords = { "libpng" }, description = "loads and saves PNG images", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_libpng.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_libpng.lua.cc", dest_dir = "build", } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/imaging/libtiff/000077500000000000000000000000001263004425400202055ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/libtiff/binding/000077500000000000000000000000001263004425400216175ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/libtiff/binding/bind_libtiff.lua.cc000066400000000000000000000032511263004425400253220ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C //BIND_END //BIND_HEADER_H #include "libtiff.h" #include "constString.h" #include "bind_image_RGB.h" //BIND_END //BIND_FUNCTION libtiff.read { constString cs; LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, string); LUABIND_GET_PARAMETER(1,constString,cs); const char *filename = (const char *)cs; ImageFloatRGB *res = LibTIFF::readTIFF(filename); if (res == NULL) LUABIND_ERROR("libtiff.read failed"); LUABIND_RETURN(ImageFloatRGB, res); } //BIND_END //BIND_FUNCTION libtiff.write { ImageFloatRGB *img; constString cs; LUABIND_CHECK_ARGN(==, 2); LUABIND_CHECK_PARAMETER(2, string); LUABIND_GET_PARAMETER(1,ImageFloatRGB,img); LUABIND_GET_PARAMETER(2,constString,cs); const char *filename = (const char *)cs; bool ok = LibTIFF::writeTIFF(img, filename); if (!ok) LUABIND_ERROR("libtiff.write failed"); } //BIND_END april-ann-0.4.1/packages/imaging/libtiff/c_src/000077500000000000000000000000001263004425400212765ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/libtiff/c_src/libtiff.cc000066400000000000000000000076451263004425400232400ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include #include "tiffio.h" #include "clamp.h" #include "libtiff.h" namespace LibTIFF { ImageFloatRGB *readTIFF(const char *filename) { TIFF* tif = TIFFOpen(filename, "r"); if (tif == NULL) { fprintf(stderr, "LibTIFF::readTIFF() -> TIFFOpen failed on %s\n", filename); return NULL; } int width, height; TIFFGetField(tif, TIFFTAG_IMAGEWIDTH, &width); TIFFGetField(tif, TIFFTAG_IMAGELENGTH, &height); int dims[2]={height, width}; int ok; Matrix *m = NULL; ImageFloatRGB *res = NULL; uint32_t *p = NULL; int npixels = width * height; uint32_t *raster = (uint32_t*) _TIFFmalloc(npixels * sizeof (uint32_t)); if (raster == NULL) { fprintf(stderr, "LibTIFF::readTIFF() -> _TIFFMalloc failed on %s\n", filename); goto close_file; } ok = TIFFReadRGBAImage(tif, width, height, raster, 0); if (!ok) { fprintf(stderr, "LibTIFF::readTIFF() -> TIFFReadRGBAImage failed on %s\n", filename); goto free_image_data; } m = new Matrix(2, dims, FloatRGB(0.0f,0.0f,0.0f)); res = new ImageFloatRGB(m); /* process raster data */ p = raster; for (int y = 0; y < height; y++) { for (int x = 0; x < width; x++) { uint32_t pixel = *p++; float r = TIFFGetR(pixel)/255.0f; float g = TIFFGetG(pixel)/255.0f; float b = TIFFGetB(pixel)/255.0f; (*res)(x,height-1-y) = FloatRGB(r,g,b); } } free_image_data: _TIFFfree(raster); close_file: TIFFClose(tif); return res; } bool writeTIFF(ImageFloatRGB *img, const char *filename) { bool result = false; TIFF* tif = TIFFOpen(filename, "w"); if (tif == NULL) { fprintf(stderr, "LibTIFF::writeTIFF() -> TIFFOpen failed on %s\n", filename); return result; } TIFFSetField(tif, TIFFTAG_IMAGEWIDTH, img->width); TIFFSetField(tif, TIFFTAG_IMAGELENGTH, img->height); TIFFSetField(tif, TIFFTAG_COMPRESSION, COMPRESSION_LZW); TIFFSetField(tif, TIFFTAG_PLANARCONFIG, PLANARCONFIG_CONTIG); TIFFSetField(tif, TIFFTAG_PHOTOMETRIC, PHOTOMETRIC_RGB); TIFFSetField(tif, TIFFTAG_BITSPERSAMPLE, 8); TIFFSetField(tif, TIFFTAG_SAMPLESPERPIXEL, 3); TIFFSetField(tif, TIFFTAG_ARTIST, ""); int size = (img->width * img->height * 3); int i; uint8_t* buffer; buffer = (uint8_t*)_TIFFmalloc((unsigned int)size); if (buffer == NULL) { fprintf(stderr, "LibTIFF::writeTIFF() -> _TIFFMalloc failed on %s\n", filename); goto close_file; } // copy data into buffer i=0; for (int y = 0; y < img->height; y++) { for (int x = 0; x < img->width; x++) { FloatRGB color((*img)(x,y)); buffer[i] = uint8_t(color.r*255.0f); buffer[i+1] = uint8_t(color.g*255.0f); buffer[i+2] = uint8_t(color.b*255.0f); i+=3; } } // Write the information to the file TIFFWriteEncodedStrip(tif, 0, buffer, size); // If we are here, file is OK result=true; _TIFFfree(buffer); close_file: TIFFClose(tif); return result; } } april-ann-0.4.1/packages/imaging/libtiff/c_src/libtiff.h000066400000000000000000000020471263004425400230710ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Jorge Gorbe Moya * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LIBTIFF_H #define LIBTIFF_H #include "utilImageFloat.h" #include namespace LibTIFF { ImageFloatRGB* readTIFF(const char *filename); // returns NULL if error bool writeTIFF(ImageFloatRGB *img, const char *filename); } #endif april-ann-0.4.1/packages/imaging/libtiff/lua_src/000077500000000000000000000000001263004425400216355ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/libtiff/lua_src/libtiff.lua000066400000000000000000000002341263004425400237560ustar00rootroot00000000000000local libtiff_handlers = { read=libtiff.read, write=libtiff.write } ImageIO.handlers["tif"] = libtiff_handlers ImageIO.handlers["tiff"] = libtiff_handlers april-ann-0.4.1/packages/imaging/libtiff/package.lua000066400000000000000000000021161263004425400223030ustar00rootroot00000000000000 package{ name = "libtiff", version = "1.0", depends = { "Image", "util", "ImageIO" }, keywords = { "libtiff" }, description = "loads and saves TIFF images", link_libraries = { "tiff" }, -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_libtiff.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_libtiff.lua.cc", dest_dir = "build", } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/imaging/median_filter/000077500000000000000000000000001263004425400213705ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/median_filter/binding/000077500000000000000000000000001263004425400230025ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/median_filter/binding/bind_median_filter.lua.cc000066400000000000000000000013011263004425400276620ustar00rootroot00000000000000//BIND_HEADER_C #include "bind_median_filter.h" #include "utilMatrixFloat.h" // #include "bind_image_RGB.h" #include "bind_image.h" //BIND_END //BIND_HEADER_H #include "bind_image.h" #include "median_filter.h" #include "utilMatrixFloat.h" // #include "utilImageFloat.h" // #include "bind_matrix.h" // #include "bind_affine_transform.h" // #include //BIND_END //BIND_LUACLASSNAME ImageFloat Image //BIND_METHOD ImageFloat median_filter // recibe el radio { int radio; LUABIND_CHECK_ARGN(==, 1); LUABIND_GET_PARAMETER(1, int, radio); if (radio < 1) { LUABIND_ERROR("median filter, radio must be > 0"); } LUABIND_RETURN(ImageFloat, Imaging::medianFilter(obj,radio)); } //BIND_END april-ann-0.4.1/packages/imaging/median_filter/c_src/000077500000000000000000000000001263004425400224615ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/median_filter/c_src/ctmf.c000066400000000000000000000363211263004425400235630ustar00rootroot00000000000000/* * ctmf.c - Constant-time median filtering * Copyright (C) 2006 Simon Perreault * * Reference: S. Perreault and P. Hébert, "Median Filtering in Constant Time", * IEEE Transactions on Image Processing, September 2007. * * This program has been obtained from http://nomis80.org/ctmf.html. No patent * covers this program, although it is subject to the following license: * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . * * Contact: * Laboratoire de vision et systèmes numériques * Pavillon Adrien-Pouliot * Université Laval * Sainte-Foy, Québec, Canada * G1K 7P4 * * perreaul@gel.ulaval.ca */ /* Standard C includes */ #include #include #include #include /* Type declarations */ #ifdef _MSC_VER #include typedef UINT8 uint8_t; typedef UINT16 uint16_t; typedef UINT32 uint32_t; #pragma warning( disable: 4799 ) #else #include #endif /* Intrinsic declarations */ #if defined(__SSE2__) || defined(__MMX__) #if defined(__SSE2__) #include #elif defined(__MMX__) #include #endif #if defined(__GNUC__) #include #elif defined(_MSC_VER) #include #endif #elif defined(__ALTIVEC__) #include #endif /* Compiler peculiarities */ #if defined(__GNUC__) #include #define inline __inline__ #define align(x) __attribute__ ((aligned (x))) #elif defined(_MSC_VER) #define inline __inline #define align(x) __declspec(align(x)) #else #define inline #define align(x) #endif #ifndef MIN #define MIN(a,b) ((a) > (b) ? (b) : (a)) #endif #ifndef MAX #define MAX(a,b) ((a) < (b) ? (b) : (a)) #endif /** * This structure represents a two-tier histogram. The first tier (known as the * "coarse" level) is 4 bit wide and the second tier (known as the "fine" level) * is 8 bit wide. Pixels inserted in the fine level also get inserted into the * coarse bucket designated by the 4 MSBs of the fine bucket value. * * The structure is aligned on 16 bytes, which is a prerequisite for SIMD * instructions. Each bucket is 16 bit wide, which means that extra care must be * taken to prevent overflow. */ typedef struct align(16) { uint16_t coarse[16]; uint16_t fine[16][16]; } Histogram; /** * HOP is short for Histogram OPeration. This macro makes an operation \a op on * histogram \a h for pixel value \a x. It takes care of handling both levels. */ #define HOP(h,x,op) \ h.coarse[x>>4] op; \ *((uint16_t*) h.fine + x) op; #define COP(c,j,x,op) \ h_coarse[ 16*(n*c+j) + (x>>4) ] op; \ h_fine[ 16 * (n*(16*c+(x>>4)) + j) + (x & 0xF) ] op; /** * Adds histograms \a x and \a y and stores the result in \a y. Makes use of * SSE2, MMX or Altivec, if available. */ #if defined(__SSE2__) static inline void histogram_add( const uint16_t x[16], uint16_t y[16] ) { *(__m128i*) &y[0] = _mm_add_epi16( *(__m128i*) &y[0], *(__m128i*) &x[0] ); *(__m128i*) &y[8] = _mm_add_epi16( *(__m128i*) &y[8], *(__m128i*) &x[8] ); } #elif defined(__MMX__) static inline void histogram_add( const uint16_t x[16], uint16_t y[16] ) { *(__m64*) &y[0] = _mm_add_pi16( *(__m64*) &y[0], *(__m64*) &x[0] ); *(__m64*) &y[4] = _mm_add_pi16( *(__m64*) &y[4], *(__m64*) &x[4] ); *(__m64*) &y[8] = _mm_add_pi16( *(__m64*) &y[8], *(__m64*) &x[8] ); *(__m64*) &y[12] = _mm_add_pi16( *(__m64*) &y[12], *(__m64*) &x[12] ); } #elif defined(__ALTIVEC__) static inline void histogram_add( const uint16_t x[16], uint16_t y[16] ) { *(vector unsigned short*) &y[0] = vec_add( *(vector unsigned short*) &y[0], *(vector unsigned short*) &x[0] ); *(vector unsigned short*) &y[8] = vec_add( *(vector unsigned short*) &y[8], *(vector unsigned short*) &x[8] ); } #else static inline void histogram_add( const uint16_t x[16], uint16_t y[16] ) { int i; for ( i = 0; i < 16; ++i ) { y[i] += x[i]; } } #endif /** * Subtracts histogram \a x from \a y and stores the result in \a y. Makes use * of SSE2, MMX or Altivec, if available. */ #if defined(__SSE2__) static inline void histogram_sub( const uint16_t x[16], uint16_t y[16] ) { *(__m128i*) &y[0] = _mm_sub_epi16( *(__m128i*) &y[0], *(__m128i*) &x[0] ); *(__m128i*) &y[8] = _mm_sub_epi16( *(__m128i*) &y[8], *(__m128i*) &x[8] ); } #elif defined(__MMX__) static inline void histogram_sub( const uint16_t x[16], uint16_t y[16] ) { *(__m64*) &y[0] = _mm_sub_pi16( *(__m64*) &y[0], *(__m64*) &x[0] ); *(__m64*) &y[4] = _mm_sub_pi16( *(__m64*) &y[4], *(__m64*) &x[4] ); *(__m64*) &y[8] = _mm_sub_pi16( *(__m64*) &y[8], *(__m64*) &x[8] ); *(__m64*) &y[12] = _mm_sub_pi16( *(__m64*) &y[12], *(__m64*) &x[12] ); } #elif defined(__ALTIVEC__) static inline void histogram_sub( const uint16_t x[16], uint16_t y[16] ) { *(vector unsigned short*) &y[0] = vec_sub( *(vector unsigned short*) &y[0], *(vector unsigned short*) &x[0] ); *(vector unsigned short*) &y[8] = vec_sub( *(vector unsigned short*) &y[8], *(vector unsigned short*) &x[8] ); } #else static inline void histogram_sub( const uint16_t x[16], uint16_t y[16] ) { int i; for ( i = 0; i < 16; ++i ) { y[i] -= x[i]; } } #endif static inline void histogram_muladd( const uint16_t a, const uint16_t x[16], uint16_t y[16] ) { int i; for ( i = 0; i < 16; ++i ) { y[i] += a * x[i]; } } static void ctmf_helper( const unsigned char* const src, unsigned char* const dst, const int width, const int height, const int src_step, const int dst_step, const int r, const int cn, const int pad_left, const int pad_right ) { const int m = height, n = width; int i, j, k, c; const unsigned char *p, *q; Histogram H[4]; uint16_t *h_coarse, *h_fine, luc[4][16]; assert( src ); assert( dst ); assert( r >= 0 ); assert( width >= 2*r+1 ); assert( height >= 2*r+1 ); assert( src_step != 0 ); assert( dst_step != 0 ); /* SSE2 and MMX need aligned memory, provided by _mm_malloc(). */ #if defined(__SSE2__) || defined(__MMX__) h_coarse = (uint16_t*) _mm_malloc( 1 * 16 * n * cn * sizeof(uint16_t), 16 ); h_fine = (uint16_t*) _mm_malloc( 16 * 16 * n * cn * sizeof(uint16_t), 16 ); memset( h_coarse, 0, 1 * 16 * n * cn * sizeof(uint16_t) ); memset( h_fine, 0, 16 * 16 * n * cn * sizeof(uint16_t) ); #else h_coarse = (uint16_t*) calloc( 1 * 16 * n * cn, sizeof(uint16_t) ); h_fine = (uint16_t*) calloc( 16 * 16 * n * cn, sizeof(uint16_t) ); #endif /* First row initialization */ for ( j = 0; j < n; ++j ) { for ( c = 0; c < cn; ++c ) { COP( c, j, src[cn*j+c], += r+1 ); } } for ( i = 0; i < r; ++i ) { for ( j = 0; j < n; ++j ) { for ( c = 0; c < cn; ++c ) { COP( c, j, src[src_step*i+cn*j+c], ++ ); } } } for ( i = 0; i < m; ++i ) { /* Update column histograms for entire row. */ p = src + src_step * MAX( 0, i-r-1 ); q = p + cn * n; for ( j = 0; p != q; ++j ) { for ( c = 0; c < cn; ++c, ++p ) { COP( c, j, *p, -- ); } } p = src + src_step * MIN( m-1, i+r ); q = p + cn * n; for ( j = 0; p != q; ++j ) { for ( c = 0; c < cn; ++c, ++p ) { COP( c, j, *p, ++ ); } } /* First column initialization */ memset( H, 0, cn*sizeof(H[0]) ); memset( luc, 0, cn*sizeof(luc[0]) ); if ( pad_left ) { for ( c = 0; c < cn; ++c ) { histogram_muladd( r, &h_coarse[16*n*c], H[c].coarse ); } } for ( j = 0; j < (pad_left ? r : 2*r); ++j ) { for ( c = 0; c < cn; ++c ) { histogram_add( &h_coarse[16*(n*c+j)], H[c].coarse ); } } for ( c = 0; c < cn; ++c ) { for ( k = 0; k < 16; ++k ) { histogram_muladd( 2*r+1, &h_fine[16*n*(16*c+k)], &H[c].fine[k][0] ); } } for ( j = pad_left ? 0 : r; j < (pad_right ? n : n-r); ++j ) { for ( c = 0; c < cn; ++c ) { const uint16_t t = 2*r*r + 2*r; uint16_t sum = 0, *segment; int b; histogram_add( &h_coarse[16*(n*c + MIN(j+r,n-1))], H[c].coarse ); /* Find median at coarse level */ for ( k = 0; k < 16 ; ++k ) { sum += H[c].coarse[k]; if ( sum > t ) { sum -= H[c].coarse[k]; break; } } assert( k < 16 ); /* Update corresponding histogram segment */ if ( luc[c][k] <= j-r ) { memset( &H[c].fine[k], 0, 16 * sizeof(uint16_t) ); for ( luc[c][k] = j-r; luc[c][k] < MIN(j+r+1,n); ++luc[c][k] ) { histogram_add( &h_fine[16*(n*(16*c+k)+luc[c][k])], H[c].fine[k] ); } if ( luc[c][k] < j+r+1 ) { histogram_muladd( j+r+1 - n, &h_fine[16*(n*(16*c+k)+(n-1))], &H[c].fine[k][0] ); luc[c][k] = j+r+1; } } else { for ( ; luc[c][k] < j+r+1; ++luc[c][k] ) { histogram_sub( &h_fine[16*(n*(16*c+k)+MAX(luc[c][k]-2*r-1,0))], H[c].fine[k] ); histogram_add( &h_fine[16*(n*(16*c+k)+MIN(luc[c][k],n-1))], H[c].fine[k] ); } } histogram_sub( &h_coarse[16*(n*c+MAX(j-r,0))], H[c].coarse ); /* Find median in segment */ segment = H[c].fine[k]; for ( b = 0; b < 16 ; ++b ) { sum += segment[b]; if ( sum > t ) { dst[dst_step*i+cn*j+c] = 16*k + b; break; } } assert( b < 16 ); } } } #if defined(__SSE2__) || defined(__MMX__) _mm_empty(); _mm_free(h_coarse); _mm_free(h_fine); #else free(h_coarse); free(h_fine); #endif } /** * \brief Constant-time median filtering * * This function does a median filtering of an 8-bit image. The source image is * processed as if it was padded with zeros. The median kernel is square with * odd dimensions. Images of arbitrary size may be processed. * * To process multi-channel images, you must call this function multiple times, * changing the source and destination adresses and steps such that each channel * is processed as an independent single-channel image. * * Processing images of arbitrary bit depth is not supported. * * The computing time is O(1) per pixel, independent of the radius of the * filter. The algorithm's initialization is O(r*width), but it is negligible. * Memory usage is simple: it will be as big as the cache size, or smaller if * the image is small. For efficiency, the histograms' bins are 16-bit wide. * This may become too small and lead to overflow as \a r increases. * * \param src Source image data. * \param dst Destination image data. Must be preallocated. * \param width Image width, in pixels. * \param height Image height, in pixels. * \param src_step Distance between adjacent pixels on the same column in * the source image, in bytes. * \param dst_step Distance between adjacent pixels on the same column in * the destination image, in bytes. * \param r Median filter radius. The kernel will be a 2*r+1 by * 2*r+1 square. * \param cn Number of channels. For example, a grayscale image would * have cn=1 while an RGB image would have cn=3. * \param memsize Maximum amount of memory to use, in bytes. Set this to * the size of the L2 cache, then vary it slightly and * measure the processing time to find the optimal value. * For example, a 512 kB L2 cache would have * memsize=512*1024 initially. */ void ctmf( const unsigned char* const src, unsigned char* const dst, const int width, const int height, const int src_step, const int dst_step, const int r, const int cn, const long unsigned int memsize ) { /* * Processing the image in vertical stripes is an optimization made * necessary by the limited size of the CPU cache. Each histogram is 544 * bytes big and therefore I can fit a limited number of them in the cache. * That number may sometimes be smaller than the image width, which would be * the number of histograms I would need without stripes. * * I need to keep histograms in the cache so that they are available * quickly when processing a new row. Each row needs access to the previous * row's histograms. If there are too many histograms to fit in the cache, * thrashing to RAM happens. * * To solve this problem, I figure out the maximum number of histograms * that can fit in cache. From this is determined the number of stripes in * an image. The formulas below make the stripes all the same size and use * as few stripes as possible. * * Note that each stripe causes an overlap on the neighboring stripes, as * when mowing the lawn. That overlap is proportional to r. When the overlap * is a significant size in comparison with the stripe size, then we are not * O(1) anymore, but O(r). In fact, we have been O(r) all along, but the * initialization term was neglected, as it has been (and rightly so) in B. * Weiss, "Fast Median and Bilateral Filtering", SIGGRAPH, 2006. Processing * by stripes only makes that initialization term bigger. * * Also, note that the leftmost and rightmost stripes don't need overlap. * A flag is passed to ctmf_helper() so that it treats these cases as if the * image was zero-padded. */ int stripes = (int) ceil( (double) (width - 2*r) / (memsize / sizeof(Histogram) - 2*r) ); int stripe_size = (int) ceil( (double) ( width + stripes*2*r - 2*r ) / stripes ); int i; for ( i = 0; i < width; i += stripe_size - 2*r ) { int stripe = stripe_size; /* Make sure that the filter kernel fits into one stripe. */ if ( i + stripe_size - 2*r >= width || width - (i + stripe_size - 2*r) < 2*r+1 ) { stripe = width - i; } ctmf_helper( src + cn*i, dst + cn*i, stripe, height, src_step, dst_step, r, cn, i == 0, stripe == width - i ); if ( stripe == width - i ) { break; } } } april-ann-0.4.1/packages/imaging/median_filter/c_src/ctmf.h000066400000000000000000000004661263004425400235710ustar00rootroot00000000000000#ifndef CTMF_H #define CTMF_H #ifdef __cplusplus extern "C" { #endif void ctmf( const unsigned char* src, unsigned char* dst, int width, int height, int src_step_row, int dst_step_row, int r, int channels, unsigned long memsize ); #ifdef __cplusplus } #endif #endif april-ann-0.4.1/packages/imaging/median_filter/c_src/median_filter.cc000066400000000000000000000021611263004425400255720ustar00rootroot00000000000000#include "median_filter.h" #include "ctmf.h" #include "clamp.h" using AprilUtils::clamp; namespace Imaging { ImageFloat* medianFilter(ImageFloat *img, int radio) { int numpixels = img->width() * img->height(); unsigned char *src = new unsigned char[numpixels]; unsigned char *dst = new unsigned char[numpixels]; unsigned char *r = src; // copiamos la imagen a data: for (int y=0;yheight();++y) for (int x=0;xwidth();++x) *r++ = (unsigned char)(clamp((*img)(x,y), 0.0f, 1.0f)*255.0f); // llamamos a la funcion ctmf(src,dst,img->width(),img->height(), img->width(),img->width(), radio,1,512*1024); // escribimos el resultado en una imagen nueva int dims[2]; dims[0] = img->height(); dims[1] = img->width(); Basics::MatrixFloat *mat = new Basics::MatrixFloat(2,dims); ImageFloat *resul = new ImageFloat(mat); int i=0; for (Basics::MatrixFloat::iterator it(mat->begin()); it!=mat->end(); ++it, ++i) *it = dst[i]/255.0f; delete[] src; delete[] dst; return resul; } } // namespace Imaging april-ann-0.4.1/packages/imaging/median_filter/c_src/median_filter.h000066400000000000000000000002701263004425400254330ustar00rootroot00000000000000#ifndef MEDIAN_FILTER_H #define MEDIAN_FILTER_H #include "utilImageFloat.h" namespace Imaging { ImageFloat* medianFilter(ImageFloat *img, int radio); } #endif // MEDIAN_FILTER_H april-ann-0.4.1/packages/imaging/median_filter/doc/000077500000000000000000000000001263004425400221355ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/median_filter/doc/ctmf.pdf000066400000000000000000037402621263004425400235770ustar00rootroot00000000000000%PDF-1.2 7 0 obj << /Type/Encoding 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TD[(brute-force)-409(approach)-410(simply)-410(b)19(uilds)-408(a)-410(list)-410(of)-410(the)-410(pix)14(el)-409(v)24(alues)-409(in)-409(the)]TJ 0 -11.01 TD[(\002lter)-329(k)9(ernel)-328(and)-330(sorts)-329(them.)-330(The)-330(median)-329(is)-330(then)-330(the)-329(v)24(alue)-329(situated)-329(at)]TJ 0 -11 TD[(the)-356(middle)-357(of)-357(the)-357(list.)-357(In)-357(the)-357(general)-357(case,)-357(this)-357(algorithm')54(s)-356(per)19(-pix)15(el)]TJ 0 -11 TD[(comple)15(xity)-424(is)]TJ/F7 8.96 Tf 53.8 0 TD[(O)]TJ/F8 8.96 Tf 7.27 0 TD[(\()]TJ/F7 8.96 Tf 3.58 0 TD[(r)]TJ/F9 5.98 Tf 4.41 3.8 TD[(2)]TJ/F8 8.96 Tf 5.69 -3.8 TD[(log)]TJ/F7 8.96 Tf 13.43 0 TD[(r)]TJ/F8 8.96 Tf 4.42 0 TD[(\))]TJ/F1 8.96 Tf 3.58 0 TD[(,)-425(where)]TJ/F7 8.96 Tf 31.77 0 TD[(r)]TJ/F1 8.96 Tf 8.22 0 TD[(is)-425(the)-425(k)9(ernel)-425(radius.)-425(When)-425(the)]TJ -136.17 -11.01 TD[(number)-317(of)-317(possible)-317(pix)13(el)-316(v)24(alues)-316(is)-318(a)-317(constant,)-318(as)-317(is)-318(the)-317(case)-318(for)-317(8-bit)]TJ 0 -11 TD[(images,)-279(one)-279(can)-279(use)-280(a)-279(b)19(uck)10(et)-279(sort,)-279(which)-280(brings)-279(the)-280(comple)14(xity)-278(do)24(wn)]TJ 0 -11 TD[(to)]TJ/F7 8.96 Tf 10.11 0 TD[(O)]TJ/F8 8.96 Tf 7.26 0 TD[(\()]TJ/F7 8.96 Tf 3.59 0 TD[(r)]TJ/F9 5.98 Tf 4.41 3.8 TD[(2)]TJ/F8 8.96 Tf 4.15 -3.8 TD[(\))]TJ/F1 8.96 Tf 3.58 0 TD[(.)-350(This)-350(is)-350(still)-350(unw)9(orkable)-349(for)-350(an)14(y)-349(b)19(ut)-349(the)-350(smallest)-350(k)9(ernels.)]TJ -24.14 -10.97 TD[(The)-403(classic)-403(algorithm)-404([3],)-403(used)-404(in)-403(virtually)-404(all)-403(publicly)-404(a)19(v)25(ailable)]TJ -8.96 -11 TD[(implementations,)-552(e)14(xhibits)]TJ/F7 8.96 Tf 100.17 0 TD[(O)]TJ/F8 8.96 Tf 7.27 0 TD[(\()]TJ/F7 8.96 Tf 3.58 0 TD[(r)]TJ/F8 8.96 Tf 4.41 0 TD[(\))]TJ/F1 8.96 Tf 8.54 0 TD[(comple)14(xity)-552(\(see)-554(Algorithm)-553(1\).)-553(It)]TJ -123.97 -11 TD[(mak)10(es)-288(use)-289(of)-289(a)-289(histogram)-289(for)-289(accumulating)-289(pix)14(els)-287(in)-289(the)-289(k)9(ernel.)-288(Only)]TJ 0 -11.01 TD[(a)-363(part)-363(of)-364(it)-363(is)-364(modi\002ed)-363(when)-364(mo)14(ving)-362(from)-364(one)-364(pix)14(el)-362(to)-364(another)54(.)-362(As)]TJ 0 -11 TD[(illustrated)-309(in)-309(Figure)-309(1,)]TJ/F8 8.96 Tf 84.05 0 TD[(2)]TJ/F7 8.96 Tf 4.61 0 TD[(r)]TJ/F8 8.96 Tf 5.76 0 TD[(+)-151(1)]TJ/F1 8.96 Tf 15.91 0 TD[(additions)-309(and)]TJ/F8 8.96 Tf 51.36 0 TD[(2)]TJ/F7 8.96 Tf 4.6 0 TD[(r)]TJ/F8 8.96 Tf 5.77 0 TD[(+)-151(1)]TJ/F1 8.96 Tf 15.91 0 TD[(subtractions)-308(need)]TJ -187.97 -11 TD[(to)-341(be)-342(carried)-342(out)-342(for)-342(updating)-342(the)-342(histogram.)-341(Computing)-342(the)-342(median)]TJ 0 -11.01 TD[(from)-421(a)-421(histogram)-422(is)-421(done)-422(in)-421(constant)-422(time)-422(by)-421(summing)-422(the)-421(v)24(alues)]TJ 0 -11 TD[(from)-352(one)-353(end)-353(and)-353(stopping)-354(when)-353(the)-353(sum)-353(reaches)]TJ/F8 8.96 Tf 187.81 0 TD[(\(2)]TJ/F7 8.96 Tf 8.19 0 TD[(r)]TJ/F8 8.96 Tf 6.48 0 TD[(+)-230(1\))]TJ/F9 5.98 Tf 17.42 3.81 TD[(2)]TJ/F7 8.96 Tf 4.15 -3.81 TD[(=)]TJ/F8 8.96 Tf 4.61 0 TD[(2)]TJ/F1 8.96 Tf 4.6 0 TD[(.)-353(F)14(or)]TJ -233.26 -11 TD[(8-bit)-472(images,)-472(a)-473(histogram)-472(is)-473(made)-472(of)-473(256)-473(bins)-472(and)-473(therefore)-472(128)]TJ 0 -11 TD[(comparisons)-322(and)-324(127)-323(additions)-324(will)-323(be)-324(needed)-323(on)-323(a)19(v)15(erage.)-323(Note)-323(that)]TJ 0 -11.01 TD[(an)15(y)-386(other)-386(rank-order)-387(statistic)-387(can)-386(be)-387(computed)-387(in)-386(the)-387(same)-387(w)9(ay)-385(by)]TJ 0 -11 TD[(changing)-349(the)-350(stopping)-350(v)24(alue.)]TJ 8.96 -10.96 TD[(Ef)25(forts)-346(were)-346(made)-346(to)-347(impro)14(v)15(e)-345(the)-346(comple)14(xity)-346(of)-346(the)-346(median)-347(\002lter)]TJ -8.96 -11.01 TD[(be)15(yond)-346(linear)54(.)-345(A)-347(comple)14(xity)-345(of)]TJ/F7 8.96 Tf 118.08 0 TD[(O)]TJ/F8 8.96 Tf 7.27 0 TD[(\(log)]TJ/F9 5.98 Tf 15.48 3.81 TD[(2)]TJ/F7 8.96 Tf 5.69 -3.81 TD[(r)]TJ/F8 8.96 Tf 4.41 0 TD[(\))]TJ/F1 8.96 Tf 6.69 0 TD[(w)9(as)-345(attained)-347(by)-346(Gil)-347(et)-346(al.)]TJ -157.62 -11 TD[([4])-392(using)-394(a)-393(tree-based)-394(algorithm.)-393(In)-393(the)-394(same)-393(paper)-394(the)14(y)-392(claimed)-393(a)]TJ/F7 8.96 Tf 0 -11 TD[(O)]TJ/F8 8.96 Tf 7.26 0 TD[(\(log)]TJ/F7 8.96 Tf 17.02 0 TD[(r)]TJ/F8 8.96 Tf 4.41 0 TD[(\))]TJ/F1 8.96 Tf 6.21 0 TD[(lo)25(wer)-292(bound)-292(for)-293(an)14(y)-291(2-D)-293(median)-292(\002lter)-293(algorithm.)-292(Our)-293(w)9(ork)]TJ -34.9 -11.01 TD[(is)-318(most)-318(similar)-319(to)-319(that)-318(of)-319([5],)-319(where)-318(sorted)-319(lists)-318(were)-319(used)-319(instead)-318(of)]TJ 0 -11 TD[(histograms,)-305(which)-306(resulted)-306(in)-306(a)]TJ/F7 8.96 Tf 116.53 0 TD[(O)]TJ/F8 8.96 Tf 7.27 0 TD[(\()]TJ/F7 8.96 Tf 3.58 0 TD[(r)]TJ/F9 5.98 Tf 4.41 3.81 TD[(2)]TJ/F8 8.96 Tf 4.15 -3.81 TD[(\))]TJ/F1 8.96 Tf 6.33 0 TD[(comple)15(xity)-305(and)-306(w)9(as)-305(relati)24(v)15(ely)]TJ -142.27 -11 TD[(slo)25(w)65(.)-407(More)-407(recently)64(,)-407(W)79(eiss)-407([6])-408(de)24(v)15(eloped)-406(a)-408(method)-408(whose)-407(runtime)]TJ 0 -11.01 TD[(is)]TJ/F7 8.96 Tf 9.66 0 TD[(O)]TJ/F8 8.96 Tf 7.27 0 TD[(\(log)]TJ/F7 8.96 Tf 17.02 0 TD[(r)]TJ/F8 8.96 Tf 4.41 0 TD[(\))]TJ/F1 8.96 Tf 7.27 0 TD[(using)-411(a)-412(hierarch)4(y)-410(of)-412(histograms.)-411(In)-412(his)-411(approach,)-412(e)24(v)15(en)]TJ -45.63 -11 TD[(though)]TJ/F2 8.96 Tf 29.01 0 TD[(comple)19(xity)]TJ/F1 8.96 Tf 42.77 0 TD[(has)-458(been)-459(lo)24(wered,)]TJ/F2 8.96 Tf 72.1 0 TD[(simplicity)]TJ/F1 8.96 Tf 38.97 0 TD[(has)-459(been)-459(lost.)-459(W)79(e)]TJ -182.85 -11 TD[(stri)25(v)15(e)-336(for)-338(a)-337(simple)-337(and)-337(ef)24(\002cient)-336(algorithm,)-338(with)-337(applicability)-337(to)-337(both)]TJ 0 -11.01 TD[(CPU)-349(and)-350(custom)-350(hardw)9(are.)]TJ/F1 7.97 Tf 8.46 -16.07 TD[(The)-547(authors)-548(are)-548(with)-548(the)-548(Computer)-547(V)59(ision)-547(and)-548(Systems)-548(Lab,)-547(Uni)24(v)15(er)20(-)]TJ -8.46 -8.97 TD[(sit)]TJ 7.97 0.04 TD[(\264)]TJ -0.44 -0.04 TD[(e)-643(La)19(v)25(al,)-644(Qu)]TJ 43.76 0.04 TD[(\264)]TJ -0.45 -0.04 TD[(ebec,)-644(Canada.)-645(G1K)-644(7P4.)-645(Phone:)-644(\(418\))-644(656-2131)-644(#4479.)]TJ -50.84 -8.96 TD[(F)15(ax:)-349(\(418\))-350(656-3594.)-350(E-mail:)]TJ/F10 7.97 Tf 98.89 0 TD[(f)]TJ/F1 7.97 Tf 4.24 0 TD[(perreaul,hebert)]TJ/F10 7.97 Tf 48 0 TD[(g)]TJ/F1 7.97 Tf 4.24 0 TD[(@gel.ula)20(v)25(al.ca)]TJ ET q 0.486352 0 -0 0.486352 311.42 -163.71 cm /Im1 Do Q BT/F1 8.96 Tf 239.91 -176.91 TD[(Fig.)-353(1:)-354(In)-354(Huang')54(s)]TJ/F7 8.96 Tf 71.2 0 TD[(O)]TJ/F8 8.96 Tf 7.27 0 TD[(\()]TJ/F7 8.96 Tf 3.58 0 TD[(n)]TJ/F8 8.96 Tf 5.56 0 TD[(\))]TJ/F1 8.96 Tf 6.75 0 TD[(algorithm,)]TJ/F8 8.96 Tf 40.27 0 TD[(2)]TJ/F7 8.96 Tf 4.61 0 TD[(r)]TJ/F8 8.96 Tf 6.49 0 TD[(+)-230(1)]TJ/F1 8.96 Tf 17.01 0 TD[(pix)14(els)-353(must)-354(be)-353(added)-354(to)]TJ -162.74 -11 TD[(and)-391(subtracted)-392(from)-393(the)-392(k)9(ernel')55(s)-391(histogram)-392(when)-392(mo)14(ving)-391(from)-392(one)]TJ 0 -11.01 TD[(pix)15(el)-349(to)-350(the)-350(ne)14(xt.)-349(In)-350(this)-350(\002gure,)]TJ/F7 8.96 Tf 118.79 0 TD[(r)]TJ/F8 8.96 Tf 6.98 0 TD[(=)-285(2)]TJ/F1 8.96 Tf 14.33 0 TD[(.)]TJ ET 0.8 w 239.91 -213.98 m 490.9 -213.98 l S BT/F4 8.96 Tf 239.91 -223.09 TD[(Algorithm)-374(1)]TJ/F1 8.96 Tf 51.04 0 TD[(Huang')55(s)]TJ/F7 8.96 Tf 33.01 0 TD[(O)]TJ/F8 8.96 Tf 7.27 0 TD[(\()]TJ/F7 8.96 Tf 3.58 0 TD[(n)]TJ/F8 8.96 Tf 5.56 0 TD[(\))]TJ/F1 8.96 Tf 6.72 0 TD[(median)-349(\002ltering)-350(algorithm.)]TJ ET 0.4 w 239.91 -227.52 m 490.9 -227.52 l S BT/F4 8.96 Tf 239.91 -235.84 TD[(Input:)]TJ/F1 8.96 Tf 28.89 0 TD[(Image)]TJ/F7 8.96 Tf 25.53 0 TD[(X)]TJ/F1 8.96 Tf 11.45 0 TD[(of)-350(size)]TJ/F7 8.96 Tf 27.68 0 TD[(m)]TJ/F11 8.96 Tf 10.17 0 TD[(\243)]TJ/F7 8.96 Tf 9.21 0 TD[(n)]TJ/F1 8.96 Tf 5.56 0 TD[(,)-349(k)9(ernel)-349(radius)]TJ/F7 8.96 Tf 55.87 0 TD[(r)]TJ/F4 8.96 Tf -174.36 -11 TD[(Output:)]TJ/F1 8.96 Tf 35.36 0 TD[(Image)]TJ/F7 8.96 Tf 25.54 0 TD[(Y)]TJ/F1 8.96 Tf 10.53 0 TD[(of)-349(the)-350(same)-350(size)-350(as)]TJ/F7 8.96 Tf 73.93 0 TD[(X)]TJ/F1 8.96 Tf -136.4 -11.01 TD[(Initialize)-350(k)9(ernel)-349(histogram)]TJ/F7 8.96 Tf 99.44 0 TD[(H)]TJ/F4 8.96 Tf -99.44 -11 TD[(f)24(or)]TJ/F7 8.96 Tf 14.36 0 TD[(i)]TJ/F8 8.96 Tf 5.71 0 TD[(=)-285(1)]TJ/F1 8.96 Tf 17.47 0 TD[(to)]TJ/F7 8.96 Tf 10.11 0 TD[(m)]TJ/F4 8.96 Tf 11.26 0 TD[(do)]TJ -49.95 -11 TD[(f)24(or)]TJ/F7 8.96 Tf 14.36 0 TD[(j)]TJ/F8 8.96 Tf 6.84 0 TD[(=)-285(1)]TJ/F1 8.96 Tf 17.47 0 TD[(to)]TJ/F7 8.96 Tf 10.11 0 TD[(n)]TJ/F4 8.96 Tf 8.7 0 TD[(do)]TJ -48.51 -11.01 TD[(f)25(or)]TJ/F7 8.96 Tf 14.36 0 TD[(k)]TJ/F8 8.96 Tf 7.62 0 TD[(=)]TJ/F11 8.96 Tf 9.72 0 TD[(\241)]TJ/F7 8.96 Tf 7.17 0 TD[(r)]TJ/F1 8.96 Tf 7.55 0 TD[(to)]TJ/F7 8.96 Tf 10.11 0 TD[(r)]TJ/F4 8.96 Tf 7.55 0 TD[(do)]TJ/F1 8.96 Tf -55.12 -11 TD[(Remo)14(v)15(e)]TJ/F7 8.96 Tf 32.75 0 TD[(X)]TJ/F12 5.98 Tf 7.61 -1.06 TD[(i)]TJ/F9 5.98 Tf 2.66 0 TD[(+)]TJ/F12 5.98 Tf 5.59 0 TD[(k)-20(;j)]TJ/F13 5.98 Tf 9.74 0 TD[(\241)]TJ/F12 5.98 Tf 5.76 0 TD[(r)]TJ/F13 5.98 Tf 3.66 0 TD[(\241)]TJ/F9 5.98 Tf 5.75 0 TD[(1)]TJ/F1 8.96 Tf 7.29 1.06 TD[(from)]TJ/F7 8.96 Tf 20.56 0 TD[(H)]TJ/F1 8.96 Tf -101.37 -11 TD[(Add)]TJ/F7 8.96 Tf 18.58 0 TD[(X)]TJ/F12 5.98 Tf 7.61 -1.07 TD[(i)]TJ/F9 5.98 Tf 2.66 0 TD[(+)]TJ/F12 5.98 Tf 5.59 0 TD[(k)-20(;j)]TJ/F9 5.98 Tf 9.74 0 TD[(+)]TJ/F12 5.98 Tf 5.59 0 TD[(r)]TJ/F1 8.96 Tf 7.3 1.07 TD[(to)]TJ/F7 8.96 Tf 10.11 0 TD[(H)]TJ/F4 8.96 Tf -76.14 -11.01 TD[(end)-349(f)24(or)]TJ/F7 8.96 Tf 0 -11 TD[(Y)]TJ/F12 5.98 Tf 5.35 -1 TD[(i;j)]TJ/F11 8.96 Tf 11.39 1 TD[(\303)]TJ/F8 8.96 Tf 11.77 0 TD[(median\()]TJ/F7 8.96 Tf 32.76 0 TD[(H)]TJ/F8 8.96 Tf 8.33 0 TD[(\))]TJ/F4 8.96 Tf -78.57 -11 TD[(end)-350(f)24(or)]TJ -8.96 -11.01 TD[(end)-350(f)24(or)]TJ ET 0.4 w 239.91 -360.99 m 490.9 -360.99 l S BT/F1 8.96 Tf 248.87 -391.25 TD[(In)-307(this)-308(correspondence)-308(we)-307(propose)-308(a)-308(simple)]TJ/F7 8.96 Tf 162.69 0 TD[(O)]TJ/F8 8.96 Tf 7.27 0 TD[(\(1\))]TJ/F1 8.96 Tf 14.53 0 TD[(median)-307(\002ltering)]TJ -193.45 -11 TD[(algorithm)-266(similar)-267(in)-268(spirit)-267(to)-267(Huang')54(s.)-266(W)79(e)-266(sho)24(w)-266(a)-267(fe)24(w)-266(straightforw)9(ard)]TJ 0 -11.01 TD[(optimizations)-301(which)-301(enable)-301(it)-302(to)-301(become)-302(much)-301(f)9(aster)-301(than)-301(the)-301(classic)]TJ 0 -11 TD[(algorithm.)-326(W)79(e)-326(tak)9(e)-327(the)-327(opportunity)-327(to)-327(e)14(xamine)-326(wh)4(y)-326(the)-327(Gil-W)79(erman)]TJ 0 -11 TD[(lo)25(wer)-421(bound)-421(of)]TJ/F7 8.96 Tf 61.4 0 TD[(O)]TJ/F8 8.96 Tf 7.26 0 TD[(\(log)]TJ/F7 8.96 Tf 17.02 0 TD[(r)]TJ/F8 8.96 Tf 4.41 0 TD[(\))]TJ/F1 8.96 Tf 7.36 0 TD[(does)-422(not)-421(seem)-422(to)-421(hold.)-422(Then)-421(we)-422(e)14(xplore)]TJ -97.45 -11.01 TD[(e)15(xtensions)-279(to)-280(the)-280(ne)24(w)-279(\002lter)39(,)-279(namely)-280(application)-280(to)-280(higher)19(-precision)-279(or)]TJ 0 -11 TD[(higher)20(-dimensional)-389(data)-390(as)-390(well)-390(as)-390(a)-390(circular)-390(k)9(ernel)-388(approximation.)]TJ 0 -11 TD[(Finally)65(,)-472(timing)-474(results)-473(are)-473(sho)24(wn,)-472(asserting)-474(the)-473(practicality)-473(of)-473(our)]TJ 0 -11.01 TD[(approach.)]TJ/F1 8.96 Tf 52.79 -24.21 TD[(I)-49(I)-50(.)-550(F)]TJ/F1 7.17 Tf 19.47 0 TD[(R)-21(O)-62(M)]TJ/F7 8.96 Tf 19.4 0 TD[(O)]TJ/F8 8.96 Tf 7.26 0 TD[(\()]TJ/F7 8.96 Tf 3.59 0 TD[(r)]TJ/F8 8.96 Tf 4.41 0 TD[(\))]TJ/F1 7.17 Tf 6.05 0 TD[(T)-43(O)]TJ/F7 8.96 Tf 12.33 0 TD[(O)]TJ/F8 8.96 Tf 7.27 0 TD[(\(1\))]TJ/F1 8.96 Tf 14.23 0 TD[(C)]TJ/F1 7.17 Tf 6.43 0 TD[(O)-61(M)-63(P)-61(L)-62(E)-61(X)-62(I)-62(T)-61(Y)]TJ/F1 8.96 Tf -144.27 -14.62 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TD[(computations)-507(o)-1(f)-507(the)-508(k)9(ernel')55(s)-507(median,)-508(at)-507(most)]TJ/F8 8.96 Tf -76.12 -11 TD[(2)]TJ/F7 8.96 Tf 4.6 0 TD[(r)]TJ/F8 8.96 Tf 7.14 0 TD[(+)-303(1)]TJ/F1 8.96 Tf 18.51 0 TD[(of)-449(its)-448(\002ne)-449(le)24(v)15(el)-448(se)14(gments)-448(will)-448(e)24(v)15(er)-448(be)-449(useful.)-449(When)-449(pix)14(el)]TJ -30.25 -11 TD[(v)25(alues)-382(v)24(ary)-383(smoothly)-383(in)-384(the)-383(image,)-383(the)-384(actual)-383(\002gure)-384(is)-383(much)-383(lo)24(wer)]TJ 0 -11.01 TD[(because)-553(the)-554(same)-554(se)14(gment)-553(is)-553(accessed)-554(repetiti)24(v)15(ely)65(.)-553(Updating)-554(the)]TJ 0 -11 TD[(k)10(ernel)-393(histogram')54(s)-393(\002ne)-394(le)24(v)15(el)-394(with)-394(se)14(gments)-393(that)-394(will)-394(ne)24(v)15(er)-393(be)-394(used)]TJ 0 -11 TD[(can)-349(be)-350(skipped.)]TJ 8.96 -10.91 TD[(T)80(o)-314(do)-315(so,)-314(we)-315(need)-314(to)-315(maintain)-314(a)-315(list)-314(of)-315(the)-314(column)-315(inde)14(x)-313(at)-315(which)]TJ -8.96 -11 TD[(each)-491(se)14(gment)-491(w)9(as)-491(last)-492(updated.)-492(When)-492(mo)14(ving)-491(from)-492(one)-492(pix)14(el)-491(to)]TJ 0 -11 TD[(the)-450(ne)14(xt,)-451(we)-451(update)-451(both)-452(le)24(v)15(els)-450(of)-451(the)-451(ne)24(w)-451(column)-451(histogram)-451(b)19(ut)]TJ 0 -11.01 TD[(only)-495(the)-496(coarse)-496(le)24(v)15(el)-495(of)-496(the)-496(k)9(ernel)-494(histogram.)-496(Ne)14(xt,)-495(we)-496(compute)]TJ 0 -11 TD[(the)-405(k)9(ernel)-404(histogram')54(s)-405(median)-405(at)-406(the)-405(coarse)-406(le)24(v)15(el)-404(and)-406(determine)-405(in)]TJ 0 -11 TD[(which)-403(se)14(gment)-403(of)-404(the)-404(\002ne)-405(le)24(v)15(el)-403(the)-404(median)-404(resides.)-404(W)79(e)-403(then)-404(bring)]TJ 0 -11.01 TD[(that)-452(se)14(gment)-451(up)-452(to)-453(date)-452(by)-453(processing)-452(column)-453(histograms)-452(starting)]TJ 0 -11 TD[(from)-369(its)-371(last)-370(updated)-370(column.)-371(If)-370(that)-371(column)-370(is)-370(of)24(fset)-370(by)-370(more)-370(than)]TJ/F8 8.96 Tf 262.94 682.2 TD[(2)]TJ/F7 8.96 Tf 4.6 0 TD[(r)]TJ/F8 8.96 Tf 6.02 0 TD[(+)-179(1)]TJ/F1 8.96 Tf 16.29 0 TD[(pix)14(els)-323(from)-324(the)-324(current)-325(one,)-324(then)-324(there)-325(is)-324(no)-324(o)14(v)15(erlap)-323(between)]TJ -26.91 -11 TD[(the)-255(k)9(ernel)-255(at)-256(the)-256(old)-255(location)-256(and)-256(the)-256(current)-256(one.)-256(W)79(e)-255(therefore)-255(update)]TJ 0 -11 TD[(the)-260(histogram)-262(se)14(gment)-260(from)-261(scratch,)-261(skipping)-262(columns)-261(in)-261(the)-261(process.)]TJ 0 -11.01 TD[(It)-355(is)-356(in)-355(that)-356(case,)-356(by)-355(skipping)-356(columns,)-356(that)-356(we)-355(mak)9(e)-355(up)-356(in)-355(reduced)]TJ 0 -11 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Uh] :_e/K]uK,Փ/r:R FQ1IK]rp55)sj&)5PY )Q &3sݡȱQ-":E la}[V?+ ::63ģ("+;5 DOJ  D6fw] \u 5Xq~ k { 5?Xv4(K檳9RC_T*c_R[=ya˿Br endstream endobj 72 0 obj << /Length 2586 /Filter/FlateDecode /Name/Im7 /Type/XObject /Subtype/Form /BBox[0 0 2384 3370] /FormType 1 /Matrix[1 0 0 1 0 0] /Resources<< /ProcSet[/PDF] >> >> stream xɎ:0#l'F˼E)P@gU4"+.feNi1_[2_ ~/?-{Ђ^7t%T iUz!7f+VtUIhu\ 1 j$AB>*0JR]{$FAo{hdԙ hQy4K aD%XHt% 2M) ky,$" 0MK3fϭ KMrR IJnGL{hXX)݃kܡxB5nQw߼d ܷBĸ׸0RvqA1 "8S3᛽F{l]]Ҷ}['I6auNCҘE*#q-z,8)4tilnAX83vqAc9`7;غ@9@uO\T㗥W1l\k=oSVDS1--LbYthd c=0E2qYIH0 r"”|af6}:)Z03bq )EVo]~F,MD·8^SBcv sCzL`Tq9M`f o ;Sh U{=f`i0-Oaj1)Uy;LMa"ɂ#`zr|)hy-X0z|i䢯::#c#@w rZӀ/^Zy/mVOVF|E$}+VOz(nr|EZBؗR%&I,^QJ ^Z|l?DY[%"~Ye!%nY1{|l1) 8.C~^bcMb%?m^×o*ֺ 0I̩ToC\z oPTP»J71aIjWŅ*꬞):fB*֌GIѳNR[{=֙ЧmL(&aQX$Y+#, ~ޛtElg.(d` =,P<ےc;IZWB.[բ˺46BP+ RܢļvVPVhv{HqU/)YNP>Ȁ)ߤe]({O/:3Tڪ&2S`dS/R(ҘbU |Q 2Y "S$E/4;m]:R+yC8IAERN+ܴm]_HK6*8S`(RzY[vR,Rk^M!k*:mon8_(z[lEz[׆QiܖYЎ7 j*]AyB$ߪEC?8-c邢um8iMnFlܲ@!«B.~l7GEW|XܪEl) lMT}41> stream 0.00 g 0.00 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See the file COPYING (GNU General Public License) for license conditions. As a special exception, permission is granted to include this font program in a Postscript or PDF file that consists of a document that contains text to be displayed or printed using this font, regardless of the conditions or license applying to the document itself.) readonly def /Copyright (Copyright (URW)++,Copyright 1999 by (URW)++ Design & Development) readonly def /FullName (Nimbus Roman No9 L Regular) readonly def /FamilyName (Nimbus Roman No9 L) readonly def /Weight (Regular) readonly def /ItalicAngle 0.0 def /isFixedPitch false def /UnderlinePosition -100 def /UnderlineThickness 50 def end readonly def /FontName /NimbusRomNo9L-Regu def /PaintType 0 def /WMode 0 def /FontBBox {-168 -281 1000 924} readonly def /FontType 1 def /FontMatrix [0.001 0.0 0.0 0.001 0.0 0.0] readonly def /Encoding StandardEncoding def /UniqueID 5020931 def currentdict end currentfile eexec `,i"[[5j5mTʻ^+݄fKitrޟm%9۩*++`[&NfA-O!J"|UY+; <Ԟ2?.P2QhnDtw=y0)n*[ Y]~ ΁RzYi[AXm>mܘ4<Л1"%}ƛg)n+f]riZO uDnH1I QD23naVhR=DRG1a]L$6콗T|DŶ'{9?; 44Y;UF78ʄ5tQqw,FΆEy|"ǎx7mp(poj1'cKKߑhgB5lŶݷ@]/'E;h2 )Lwbq UC*=Iam C 7 7 Aq^[iZUVv#@{@AARqS\M HSm-?_xn+*H0V׊.\ q8|թȧ!(ѝ:MJIpc&$a3'ZQ;Pw~5> <>3MRAȔd$J_GkDAbDm J|Jl8E0ڮ)ӗ8KZƍb4#szVQlaB*y%ЬaGke]uwQ߿;~tl3BR^ [x%( gWH|ia&0i+bqx;~E^LLb?l7@REz  DNH=͹,i1Zo2^meߜ٣.=:;϶]FЊ`gVa;=^v 9H6 S@$>d CRV3ɛuy}T~$ #% a}9Nx|C{ePN(/F !]&$ bq+Y^n1#% N |,(X9 |lg] RѨǸ)&tQ%Z~ꪃiU Ss0~3)VxA7͜iD 4!YO^%4߬}KU@3GLut3k̜vPzq}_|pRXIt{?@(WO:İ1GC UmhmQ<[H0 )EsMrpgςG+5XBkK^ٝ䄭HD W}!kf>Ax檔;{s.'ǏW׺-`Yq)2B-s{evwS՞k?Bꬴoov8j 77&sK[M2{qO3ߥ>V OGr;]8Q ɴ &;i>2TCنT պؙL65)쥝W92ب7H'kՇ/xE$^&4U)PamxEpc9ݻEɜe6l(:klL\+j(}+*lD2~{;AiKp ch-gpq}eR8`I՚#,;L=ȝxSV?io퉽P| }>BBĭ˰0jK,`xgYt̠3(`Mo,+ؒn)^B 8\DS{"ՉvX>8V,+Sz[V=6SR4j7š?1@ʕ?Mo#6×rNgScć{f! 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$1^Ћŋ|c?@ 3!֭w=c{'P]KuA ^E4\.m33z7mq"2-Gake&^=4$9,kq$π"H LY,̲+RZ~2N^Mbwǂ@֣ -y -U_5d]jNŋBS{l=-[PYu1hvaL ) 1tr1Ĩӹ E=&P4nQ~hpntxw#[QmzCijw鋾7\hk&*/AKi iSZ~ ȧ@,rs+jYs];n' kFrvw(N9;vI`mln}aVYJMD)_G !c-p1X3ZPi>4K] 8Fb|8R-dS?΃_&0CFkCRDVIǀyl&ᶥ0B{N3 aq ;37533,W]T9,o!EM/}8HZKsq?L1k"9) z4K(_%Vį?$$bB`wyEA0&G_ĩJl HF3ݘˠ(ljVxs.+jF*/\dpMX{:֯k`ܖ'ѯ$mSqSnTs %K2u`, ]y]c dUp13q|ޒn4\<ŅS ッJ|{7Ak`E3=2p\5Luv|OR@z"=qUMG.ih\xu@TDJyNuSOUzw:WhΑ˸+Nvle+E|vMRaK@D >JjN槆z feSX6fTE5`nUJ:W uDụC2w@=S2ǗǨUnmFˁ NZ/nJ9< W&aPVtN^ºgl}flɁ1IÅL@2L\CFML;-vELAHMPK1u.L/xIπO.ϒMa D8z$(w25y  %#g&EY`q/jMw$=k˔#jB`wYl(VUxkpZ/5V1g`(WZ94{PϖZ!FZhsiYب <xYaBnAVn[ 80[D{_l u&ݏש*oEg_ lQwϟep4kd$b5DNQbғ}~^!$;Zm~T#\$6VbD|&m { ROE#QʧJ╍䗨?^D+o?ǡꛤAl ;=0_ ܊i[kymˀW7;M2 )4?A$ Rrd=ֶ{FsO[*!@nņN*eU/B"3bq+?`t 5Yh,tjz֖A*Zo&;Hz Sua-_OfU'#J)/%Bx)-H+F3(nrNԓv;74*`]=a7+֩en"3ڦ_ pkFpngC(\giوEW4g_~kCqw4V3OW1I"ˑvXCU`(z_f!A s4  K„7s˵,tw<4J۲o {0*ڲ#V/(ঞ=( `s[z  lfg޳q}̻:NIo9rxfwO<ϻ t4yڑI>¼iC >ͩ %L^kJ AH!Xc"f7r[+ӴBVz:GDk߉&{|v]0] ehEGPekP,W1~ pi6[cwTR,~X?xLf`]ӓLi];Jao޷{cbkGnSZW3aqė?dTYy^EUL,^F3'U7>W9-*MfQy6lUT(m\,--؎2EL}5Y8O)["tE7#}+%/Zz.?yB> endobj 11 0 obj << /Length1 1662 /Length2 43244 /Length3 532 /Length 45438 >> stream %!PS-AdobeFont-1.0: NimbusRomNo9L-ReguItal 1.05 %%CreationDate: Wed Dec 22 1999 % Copyright (URW)++,Copyright 1999 by (URW)++ Design & Development % (URW)++,Copyright 1999 by (URW)++ Design & Development % See the file COPYING (GNU General Public License) for license conditions. % As a special exception, permission is granted to include this font % program in a Postscript or PDF file that consists of a document that % contains text to be displayed or printed using this font, regardless % of the conditions or license applying to the document itself. 12 dict begin /FontInfo 10 dict dup begin /version (1.05) readonly def /Notice ((URW)++,Copyright 1999 by (URW)++ Design & Development. See the file COPYING (GNU General Public License) for license conditions. As a special exception, permission is granted to include this font program in a Postscript or PDF file that consists of a document that contains text to be displayed or printed using this font, regardless of the conditions or license applying to the document itself.) readonly def /Copyright (Copyright (URW)++,Copyright 1999 by (URW)++ Design & Development) readonly def /FullName (Nimbus Roman No9 L Regular Italic) readonly def /FamilyName (Nimbus Roman No9 L) readonly def /Weight (Regular) readonly def /ItalicAngle -15.5 def /isFixedPitch false def /UnderlinePosition -100 def /UnderlineThickness 50 def end readonly def /FontName /NimbusRomNo9L-ReguItal def /PaintType 0 def /WMode 0 def /FontBBox {-169 -270 1010 924} readonly def /FontType 1 def /FontMatrix [0.001 0.0 0.0 0.001 0.0 0.0] readonly def /Encoding StandardEncoding def /UniqueID 5020937 def currentdict end currentfile eexec `,i"[[5j5mTʻ^+݄fKitrޟm%9۩*++`[&NfA-O!J"|UY+; <Ԟ2?.P2QhnDtw=y0)n*[ Y]~ ΁RzYi[AXm>m_mcbk$uصC4uli"bcB|*/?;f-ߣI4BkG3 +_v=`d޸3xFVT }HNx)cl6dB[KB9rraJP)iޏf_X#8=W|pS;ˑ߶1\2[a$EW/MMH9U -+V/g] t<*GP(gl(}`ZdIԅ6iP$J[E#x]TDݻ Z[?HX(7t&ɳ=}YM@SHM\X_XwŸ N?dw߀\ėˁ|J&`:Bf2Yrx0AQp` ,/̜V#SE>ret5Җ t3J@_,(ȃv=WGSTqc)!,̢ױ)'zZtHr+`!&_P졆o=pC#03ao$?gaeޫ8[4[x60Ia?>t5WQٗXEjU2sC wΗw~GGbb:d-fb[dԲL% ~Ρ;gÂ'rxR#VE51L*}Oğa/-vC>9yk`;J!C z5)E N~4;eGΜ>sܺѠ?·2T@5l4%HI⚂.oQ_WӐw'S#6⽪ +ބ3SZY!˽mL"0Mk |g O!52-e8OXru74,ۥ0y\ʨ!WzL[GzR}"ߘl~NJu<0Ԥ:I!h"`ɐ4^7hL͎RA}CA_ki(oyA8^<,D1GF~QGOȮ\{J)&D,yfZ53[]oTٸu\qh[VXcuGI0Xy0Zt#{V(#8d79#j]ԨPi7LlZ}?Z?`ŋ O:%/<ҩ,,n 6< -TLQTa9Qf ; jDo#t%CYpDp?^)P*$l +`2~+9t\!+;Ts=@_y2 nkSuC㞂TIr1 "%ٕޯ p]lU ?wв`W0ygFܭ X2q8I'T?i eϷ[{PXCct[&/NL9E9M۰d^o ܠC@"eOf*yh {'=7oEHZ)b_&\/'X m^~85}N8.*HOMr+\8w^Hڲ"Pa[q=_yOBV +bsg,K[C\ӝaOvas!= e)uT79`qN ¼{:E j 2qXb1߆/Fㄋsgh ersbmMݺi#n&ϟ"1JB15:6yU>y |ɥhNs)9td:xhAi5ҳLȑؗ3yDc(ĉ2f{YO98h^1Hp8hNF /xO7~:Eꁼm,!A-!EM~Z|3i:K[0:ߥUAjf)k\loJp>>>m-tx *“-tF&չ0פr:@qXhƉf/eNc#"~a"w@1tGP~֍W$pE1%; O$-Q-<=~q_wAGwݿOF'c^\2I) QDZՄ^3'Xբ?xM/ >: ",;ɖq#/ruqRx}iK@4=] ѯc օpa+4 t!} Gcԑ؈iER?U-4K`2B^;zcryt T*1CKMDL(fLMcY .+>;g SI\1(s FLC:D/%쐪hmJ c -Qz5EC:މ> Fk> :@1`nIfз˘I=~5<*9HJ~:Ǘw$.t(՝Qճ8]7QOAx DV4-aro[#+\gP%E MAR~\$Prɺ껡2 ]Tk~`c4*\GqMf&5ߪ'kbm,m&:u9']+!2>#b+f_A xV@s!&h )㶛*?V_X.`۩ m׉. =@ P؞{ !_yODJyssSZ?1$mAɭa%bOy%[9t,G$mlWL6>1җa+*<`pv{*x:H5O9>S9Opi,X՜7ytMBq7P"S.'[ {PFjb"`ãVeѭK /C'/ĉUTy_8/صɉ6:Gp.aWwH^D>8 Z7h-l @Sj-hgo;`~m !UOdjN$,cmnO6nw`CO}JV^ySgtւ#˥>tӄ{西1+4YOe3htVyjCBQUgRHvv\fy, \Zz nFZ# Ԫ|Vx83G%6,kI~n0Ӟq-T@_DZ%lWjtmk,Llbc!_{ѕ^lI܆6 y'j%BݴjK?0 ۘ%95 4僸Ʀmū!bΗ"n$dCh(tZ[XS{t~Yg0[%Ԫ֋a HX%,D-tpffag6ShTD [VA3!geC(w,2hM  OJ[r%;Z[+z SJl햿d{ zqK1=R'Q9۽ 1Ӯy6y%/4QSsk@jgYߪNJR Y(~X푒^z;eezYLh%OnheAhU |:;ʶ8dnU/_e:Zx挰ަVh]~Ԙ,% b656l+>xk̡2Syx6 R62NH\61NnIׁ<=5c#OuU^׍phi2_:Ek'c%c30z K[2˂oG72Änף7)cOj+;zv6r^33mR%ޯF$du&6o޺&^xv]B]t;FKktb31hLF_]T狍'9 ,iRBD-lz?SPƱ,(!'a{ӾmIcO5~lĜ ƚޣ{O//UWW_p4g4r]w=T,5MlYHU},=dfdG1G)Qe !RHd2]uZ)(^Ԉ!};QDebi(PrX_Jg!D@"%H)9YiCgӓ^Է1 ZBPz29V?"|a^#:yawqWA, k?ezbu-d C@^j=!YsK 6Z+zDLoҳg ϥ&|noH|$fԘ=]h?)me6W%nWE)::+ 9ٓb ;R+R-fiSxLI*GzY`jiU=u*<CDÄx5)T;6tvFu_zgx-WU(*Y_4k7O&ҥNqwvs4ӫOadB1ɗge@.P9uD+Me>z|O{ BȪtNxZ2xG`Y,ncT{wMf ҏ17|T w?Wt>jDN_C$Lp)/'a7w(XѨ[xлWcp@g W-z-d`kmםù~h1q ;uQט/]jXDv)NOFW֟kqBo !LT^w$Tu\n!b&N 2CSK53bsG0܄q4SQN]Sqg_0 1?`v:т8Rx⣶ȣzvH80R4InC )WUm?3KƼz鮕~QQ3NJurp+~:fZ@]aw"F_hmk(ԗ1^!:L;?>}:toȳ<;֦.BѷMJeH06H=;D7J%S,:>5Iag25B+W_@B/ܶ ʁm[7XՑtsAͮ2C5/mlۯU1g0Ϲy܈F2/e8*qI|5+z(&ΨU^PRNSC\ ztd?XHx2v%9SI&ttd\% ^uCrOޘ?'8mlt _ov7ؗm@{Y},ID;̳pO"Dץ"~nOzݮTk|AEN[a^wCv.C SNWߙ_3D0ѡۑ.w(ctv>2 CTdUwF@ £`Bͽf\QXl"X!DI(7TҰɮ[l+*<*Y4\ZqOG4H63ÆQA_(\X\JbEiSiFj!IrL <*'pAiqDI+{ym? 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See the file COPYING (GNU General Public License) for license conditions. As a special exception, permission is granted to include this font program in a Postscript or PDF file that consists of a document that contains text to be displayed or printed using this font, regardless of the conditions or license applying to the document itself.) readonly def /Copyright (Copyright (URW)++,Copyright 1999 by (URW)++ Design & Development) readonly def /FullName (Nimbus Roman No9 L Medium Italic) readonly def /FamilyName (Nimbus Roman No9 L) readonly def /Weight (Bold) readonly def /ItalicAngle -15.3 def /isFixedPitch false def /UnderlinePosition -100 def /UnderlineThickness 50 def end readonly def /FontName /NimbusRomNo9L-MediItal def /PaintType 0 def /WMode 0 def /FontBBox {-200 -324 996 964} readonly def /FontType 1 def /FontMatrix [0.001 0.0 0.0 0.001 0.0 0.0] readonly def /Encoding StandardEncoding def /UniqueID 5020939 def currentdict end currentfile eexec `,i"[[5j5mTʻ^+݄fKitrޟm%9۩*++`[&NfA-O!J"|UY+; <Ԟ2?.P2QhnDtw=y0)n*[ Y]~ ΁RzYi[AXm>mPhɊP)cJ&/FFZ >o^A9vX f9&7G~2z 3DؼԯïI/Cj3nOz-G9k0ES`ټ"m* &%{c2n4zyh>8u)E"+-v/O5:Saޖis&F0кxH D 'i@cw݊SzÚ5Ak8P{&}5@鴕GT?T[N;}xc=WlBrg ܅+L6y(օKGg(⤝W6)ڙyc$0`Ɣd1}`}x%%Gk0ލN=4yX0ۚj9e5te <^{O ?^ч~uF|J#, &"U6o=BQG@%1-IGn a5B[vPե_b)DWT~BQMmmR &iaa7`Orp iD UvJ./ kmݪ!0@>,$$kQK*ۙPIr2ΛJ4g [{؁aGϋfj?dAB˹!oO: I ?L?m֚vαWv[2N ! 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See the file COPYING (GNU General Public License) for license conditions. As a special exception, permission is granted to include this font program in a Postscript or PDF file that consists of a document that contains text to be displayed or printed using this font, regardless of the conditions or license applying to the document itself.) readonly def /Copyright (Copyright (URW)++,Copyright 1999 by (URW)++ Design & Development) readonly def /FullName (Nimbus Roman No9 L Medium) readonly def /FamilyName (Nimbus Roman No9 L) readonly def /Weight (Bold) readonly def /ItalicAngle 0.0 def /isFixedPitch false def /UnderlinePosition -100 def /UnderlineThickness 50 def end readonly def /FontName /NimbusRomNo9L-Medi def /PaintType 0 def /WMode 0 def /FontBBox {-168 -341 1000 960} readonly def /FontType 1 def /FontMatrix [0.001 0.0 0.0 0.001 0.0 0.0] readonly def /Encoding StandardEncoding def /UniqueID 5020933 def currentdict end currentfile eexec `,i"[[5j5mTʻ^+݄fKitrޟm%9۩*++`[&NfA-O!J"|UY+; <Ԟ2?.P2QhnDtw=y0)n*[ Y]~ ΁RzYi[AXm>m$Jin`hf$:Y< kx\M y~r0gZb %f%;kցƹ GTN}fRz낇O lӼ2_񑆺͟Q)@dSX%Pd@eYہ~9+2ցwA-"͡nLZ Œh큡AIfW#^g0w4=l]I"m^8&1y)"nsmu4/2a %rOlܱG@ao <]0dQо(zOhY yx]?C~~N=9ď/wcg" IWgÒęAevsj18-셒kvpUXgt˗dW;3%_QqC6CW11 4/hVv;r ,IKSg K!ۢJV;q#رzlּ7ة'N5^΍ůc97SW.:daSs_)}`YY[쥅ί>jf7Ҏy08)!HT$ȐP}do4bO:)uB3.uvbf3$K5T/#щRnmbwƒ7V?--4ODN^et0.׺tm݉OFDT)G;,G`j:z:eȝ`͵a+1S:HˎlINaL0TV*̡Cmށ-LOVIGLw?qv'g;kSg $iy·: )HիVJH 3$)f(BWH0b,ҬW.*:QAG璻  a= @V8`}tjV>%s׽Z:AܝoEz75Z!WAZ˸f*M!g"rjGX5K m^" ~Yauʔ[Yl@5Pjث<&/+$òm %~KU C>w(GǹlZ`xBdn&fٺ-2qgVxc?Xi1mG'k^wehUÊҖ'sT'vZ=. 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All Rights Reserved. 11 dict begin /FontInfo 7 dict dup begin /version (1.100) readonly def /Notice (Copyright (C) 1997 American Mathematical Society. All Rights Reserved) readonly def /FullName (CMMI8) readonly def /FamilyName (Computer Modern) readonly def /Weight (Medium) readonly def /ItalicAngle -14.04 def /isFixedPitch false def end readonly def /FontName /CMMI8 def /PaintType 0 def /FontType 1 def /FontMatrix [0.001 0 0 0.001 0 0] readonly def /Encoding 256 array 0 1 255 {1 index exch /.notdef put} for dup 161 /Gamma put dup 162 /Delta put dup 163 /Theta put dup 164 /Lambda put dup 165 /Xi put dup 166 /Pi put dup 167 /Sigma put dup 168 /Upsilon put dup 169 /Phi put dup 170 /Psi put dup 173 /Omega put dup 174 /alpha put dup 175 /beta put dup 176 /gamma put dup 177 /delta put dup 178 /epsilon1 put dup 179 /zeta put dup 180 /eta put dup 181 /theta put dup 182 /iota put dup 183 /kappa put dup 184 /lambda put dup 185 /mu put dup 186 /nu put dup 187 /xi put dup 188 /pi put dup 189 /rho put dup 190 /sigma put dup 191 /tau put dup 192 /upsilon put dup 193 /phi put dup 194 /chi put dup 195 /psi put dup 196 /tie put dup 0 /Gamma put dup 1 /Delta put dup 2 /Theta put dup 3 /Lambda put dup 4 /Xi put dup 5 /Pi put dup 6 /Sigma put dup 7 /Upsilon put dup 8 /Phi put dup 9 /Psi put dup 10 /Omega put dup 11 /alpha put dup 12 /beta put dup 13 /gamma put dup 14 /delta put dup 15 /epsilon1 put dup 16 /zeta put dup 17 /eta put dup 18 /theta put dup 19 /iota put dup 20 /kappa put dup 21 /lambda put dup 22 /mu put dup 23 /nu put dup 24 /xi put dup 25 /pi put dup 26 /rho put dup 27 /sigma put dup 28 /tau put dup 29 /upsilon put dup 30 /phi put dup 31 /chi put dup 32 /psi put dup 33 /omega put dup 34 /epsilon put dup 35 /theta1 put dup 36 /pi1 put dup 37 /rho1 put dup 38 /sigma1 put dup 39 /phi1 put dup 40 /arrowlefttophalf put dup 41 /arrowleftbothalf put dup 42 /arrowrighttophalf put dup 43 /arrowrightbothalf put dup 44 /arrowhookleft put dup 45 /arrowhookright put dup 46 /triangleright put dup 47 /triangleleft put dup 48 /zerooldstyle put dup 49 /oneoldstyle put dup 50 /twooldstyle put dup 51 /threeoldstyle put dup 52 /fouroldstyle put dup 53 /fiveoldstyle put dup 54 /sixoldstyle put dup 55 /sevenoldstyle put dup 56 /eightoldstyle put dup 57 /nineoldstyle put dup 58 /period put dup 59 /comma put dup 60 /less put dup 61 /slash put dup 62 /greater put dup 63 /star put dup 64 /partialdiff put dup 65 /A put dup 66 /B put dup 67 /C put dup 68 /D put dup 69 /E put dup 70 /F put dup 71 /G put dup 72 /H put dup 73 /I put dup 74 /J put dup 75 /K put dup 76 /L put dup 77 /M put dup 78 /N put dup 79 /O put dup 80 /P put dup 81 /Q put dup 82 /R put dup 83 /S put dup 84 /T put dup 85 /U put dup 86 /V put dup 87 /W put dup 88 /X put dup 89 /Y put dup 90 /Z put dup 91 /flat put dup 92 /natural put dup 93 /sharp put dup 94 /slurbelow put dup 95 /slurabove put dup 96 /lscript put dup 97 /a put dup 98 /b put dup 99 /c put dup 100 /d put dup 101 /e put dup 102 /f put dup 103 /g put dup 104 /h put dup 105 /i put dup 106 /j put dup 107 /k put dup 108 /l put dup 109 /m put dup 110 /n put dup 111 /o put dup 112 /p put dup 113 /q put dup 114 /r put dup 115 /s put dup 116 /t put dup 117 /u put dup 118 /v put dup 119 /w put dup 120 /x put dup 121 /y put dup 122 /z put dup 123 /dotlessi put dup 124 /dotlessj put dup 125 /weierstrass put dup 126 /vector put dup 127 /tie put dup 128 /psi put dup 160 /space put readonly def /FontBBox{-24 -250 1110 750}readonly def /UniqueID 5087383 def currentdict end currentfile eexec 4y9B0i H1r^ v.Hntµ'W"xp'DpԄ&,6 6WS:W0H:eTA7J.>Դ{8"ahγDn'$8NC z[wM 3FSj'SKx=xr!0u\/0:jm;FS'01NJ)m+yA%״~zlL/ڌ%FR$tY፟z^NWUmm:s&l!V~ZO};S)4ҭpkB3)S̬19"cHkh}(Jw䉅C&wV>GT|#İ V_]AFȸS#HTkYp_Km\ {ck3IUS V'z3",éuR`{W\T{bv59iq Y{F35͉FVA"Z:z:e>yö[eNJo&l:A8*1SuQO#vAL_qK׮k69k*[ۀǸOP*Ɍonͷu ݧRK|/I 'E#>AWZSI8 +[H~4aA1R#wjW+ơwX.rJ>:M7WXkH"q%=t>]HIZXqqp1Em@bT!a%.Piq~+xu6\ }5+0 Qjrq; `.;C) nVĻs-{qk*iˆ! 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All Rights Reserved. 11 dict begin /FontInfo 7 dict dup begin /version (1.0) readonly def /Notice (Copyright (C) 1997 American Mathematical Society. All Rights Reserved) readonly def /FullName (CMR8) readonly def /FamilyName (Computer Modern) readonly def /Weight (Medium) readonly def /ItalicAngle 0 def /isFixedPitch false def end readonly def /FontName /CMR8 def /PaintType 0 def /FontType 1 def /FontMatrix [0.001 0 0 0.001 0 0] readonly def /Encoding 256 array 0 1 255 {1 index exch /.notdef put} for dup 161 /Gamma put dup 162 /Delta put dup 163 /Theta put dup 164 /Lambda put dup 165 /Xi put dup 166 /Pi put dup 167 /Sigma put dup 168 /Upsilon put dup 169 /Phi put dup 170 /Psi put dup 173 /Omega put dup 174 /ff put dup 175 /fi put dup 176 /fl put dup 177 /ffi put dup 178 /ffl put dup 179 /dotlessi put dup 180 /dotlessj put dup 181 /grave put dup 182 /acute put dup 183 /caron put dup 184 /breve put dup 185 /macron put dup 186 /ring put dup 187 /cedilla put dup 188 /germandbls put dup 189 /ae put dup 190 /oe put dup 191 /oslash put dup 192 /AE put dup 193 /OE put dup 194 /Oslash put dup 195 /suppress put dup 196 /dieresis put dup 0 /Gamma put dup 1 /Delta put dup 2 /Theta put dup 3 /Lambda put dup 4 /Xi put dup 5 /Pi put dup 6 /Sigma put dup 7 /Upsilon put dup 8 /Phi put dup 9 /Psi put dup 10 /Omega put dup 11 /ff put dup 12 /fi put dup 13 /fl put dup 14 /ffi put dup 15 /ffl put dup 16 /dotlessi put dup 17 /dotlessj put dup 18 /grave put dup 19 /acute put dup 20 /caron put dup 21 /breve put dup 22 /macron put dup 23 /ring put dup 24 /cedilla put dup 25 /germandbls put dup 26 /ae put dup 27 /oe put dup 28 /oslash put dup 29 /AE put dup 30 /OE put dup 31 /Oslash put dup 32 /suppress put dup 33 /exclam put dup 34 /quotedblright put dup 35 /numbersign put dup 36 /dollar put dup 37 /percent put dup 38 /ampersand put dup 39 /quoteright put dup 40 /parenleft put dup 41 /parenright put dup 42 /asterisk put dup 43 /plus put dup 44 /comma put dup 45 /hyphen put dup 46 /period put dup 47 /slash put dup 48 /zero put dup 49 /one put dup 50 /two put dup 51 /three put dup 52 /four put dup 53 /five put dup 54 /six put dup 55 /seven put dup 56 /eight put dup 57 /nine put dup 58 /colon put dup 59 /semicolon put dup 60 /exclamdown put dup 61 /equal put dup 62 /questiondown put dup 63 /question put dup 64 /at put dup 65 /A put dup 66 /B put dup 67 /C put dup 68 /D put dup 69 /E put dup 70 /F put dup 71 /G put dup 72 /H put dup 73 /I put dup 74 /J put dup 75 /K put dup 76 /L put dup 77 /M put dup 78 /N put dup 79 /O put dup 80 /P put dup 81 /Q put dup 82 /R put dup 83 /S put dup 84 /T put dup 85 /U put dup 86 /V put dup 87 /W put dup 88 /X put dup 89 /Y put dup 90 /Z put dup 91 /bracketleft put dup 92 /quotedblleft put dup 93 /bracketright put dup 94 /circumflex put dup 95 /dotaccent put dup 96 /quoteleft put dup 97 /a put dup 98 /b put dup 99 /c put dup 100 /d put dup 101 /e put dup 102 /f put dup 103 /g put dup 104 /h put dup 105 /i put dup 106 /j put dup 107 /k put dup 108 /l put dup 109 /m put dup 110 /n put dup 111 /o put dup 112 /p put dup 113 /q put dup 114 /r put dup 115 /s put dup 116 /t put dup 117 /u put dup 118 /v put dup 119 /w put dup 120 /x put dup 121 /y put dup 122 /z put dup 123 /endash put dup 124 /emdash put dup 125 /hungarumlaut put dup 126 /tilde put dup 127 /dieresis put dup 128 /suppress put dup 160 /space put readonly def /FontBBox{-36 -250 1070 750}readonly def /UniqueID 5000791 def currentdict end currentfile eexec i_,+`"WP 5 l.jkP P(?~M;^yy*f˼[:-Z/e_[+5{^dtp!~dZ+س:cEwK+_nCdZy2}m3U@-UӴHhX.⤠HH<;]|& :|p[C#\zC)k;rc‘nZ E~ N K EAE6z\$Vӹ _t #mȚVxb6@mNl4qXZ;w)Ee&}9Nqqu-:^g9 MtC]ٖ#塌 #v:ˆ8NHI^R9kGfUna2WC$K28(b;Gj24츠*??3w@f$bXXOŻlk:7& -%S\aGT9[]x]Als .#! $2Ê]G;bBI_J>0f- LҐ-sld|i?%(Ө`" #-Iژ/h[(`Rg7B K|H%ƖR OšD.c3U C<#HGrѱti>6,sr0+P`أs OEwtPjȁc,șKd)#,fgWTYc:&H5PE\ɫGà%P2F3aط (hY%:d 9>ݥo%n K3)ssxrꌣr^qZÊ۠@  ld()MK-`V;ЈԚץlt"InQ {g'#yMw|gV]n/=3e9e_o f-G7DsrXN5&y 3m V,֌|[]&/۹5-90D}5HzY ~:YVGD6Vghզc#!WnhZ- (3g1?R\EWhdB*fa&r݇v8;T[6&tV7aa@'<59kJ\eb# sWiuPps !e XpEG u#) . 6JO*щ$'Ee[cL5bSVe[e<=P.·nj+PAEO:-k %km d{^:rgC=bWb&(c 45-9@uH= NԋAr3`- ]{4iN:cf'?4x2IdD'vp,ؓi&1;y EMs_a:_oM!o)R~X%Éʈe]FOW [5z 67 ES,\Ɛ =R9:ϳ%'|3&\.ԋ`W%Z/F&4DaIW (0wYV&"M:>a&ڈJa2DM\u jcDcк&FωhmO= e" ")4v}8J˦N IC,UQv W_{7gͬ0^ॡJ[€@f1*ë|\zʳl*ٟ ;Fz! 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ZIH^AlkVp'9S]"6ONAsoy;R7y($qu\U2ٜԗ9{W|q NR.CʢZw*WYVRҥ [Lh0\P:t8EL5ag(QG ;OV 7RO~fFjP׿l}Ďu ׳hX]P\/ ^iu_ , Q~Қ}az@`C )}(G҅t N $@Hc ,ľ1.V@d oNplҗ ʣk< ګ/ g:tV~;|y~o|F*y+`8k!6 c>SsZR̳Di'md)0爤:¡Є}LwNvzdh5fcXfȅɒ?UĔlUq`s^IK%`G (G9"#"G)\x R:zEq@L0WFRD8\ u\4㡕OڂĄ ja6YޚC c$Al %Iy'>I"C(qLzS; i!F b z`ENnץ=3G쌟m̰y&^{cM.yg@r^-wFW04'ޘ_2Դ;-+J xax*tX%s^8tJǐhG]sUw rgN2qH !hb ܍DA ~#|AJS>#m~$<Zl8x)'H{?+%jw >LCuݎITp 6RZwj8.#?/GI5BgaSlbĔ(x 8f2or?ˉ7Xz 3).h9rV>õL{gцMaL~{ 8 skGbp~_->NSO$t !P΢{Db]k.LM+=KDE=;'+2g,=t7dҤdEiƿrH2vuZPZ'i;q:3~5e/#uaԅf-$` Z@ueްEaEz`'ݮCˁ'p ׊ xmժ^5k;d"Mnh\8?%~<' XҪHGػSga} mryQҭκ}`bIPCHJ7~7Ԇ=MиKvܲ $;T=n$+\7WiqZ!%Ÿ6GVp L)j8}T+f9&ʹGXW`Ka,5-HY=G)|YWhU禄ͭ>7yVϣUM4ݑ|u*|Vϯ4v78Jxu 0Sk7YXaD1,RߵƷҏ$lj:=*t>7( CjcjX{[Q4rctv;]l(㡪,ݓ~p HtCSu>1?0*m]i厞NRGKkJU&v zO`Qw[2RYf?zxLA"҇be]$.;z|՝#)>j,>Mh\A%鞯`rKؤVE^tٯ̡oi4Z_ u5>k/ڤpug F\O~Vs„WLf{xYe7q hݞ\I"@UġS [@eQ-K`50T؍E[Đo029@! ^grK]OcKQڀp%)'мAqE;\ŝ88AW;Փ g^вP=C:ZTL ֻD{b+7? !jx/:hLvAH4>jAeJsVƁsܽ]I%`A.<_Mn>}nY]=1vץViUç) C:2`Ayޣ傞_ n(|{G掻 a]`Vll':=\o08qo~"{x>"훩&ܾ?>=bȭeP&e }&Q =%Iw5Rv/8+`b[bڇK "zo?|0XrDAѳW; 6EǜU16>|3N]373arN#)/ ?TW1DLoP%;AIZ ¦dv}*[E[DPEJF!LPCh%Q"Lp똟u>8kF ? I.Rڒ=۲{ǧ6|zt; ݰ'Jˢ<):$-z˪f&s~(0wfTO`>& G~!ᎇTu~n0V"knӄ=pdiH^ZmxK~;$aG5`mX~>7o.K1N9ڬ-TrןkH:F;A`p izY9"mS(`1oO`~.zDuWCuLFyAX'"i4cOU VO O"/+ACz^d BkpTCn2l6`kS`$J.('23kEטS. ,w]B!/AAL_k TA,{nuCb ؀v( |(KI]X0#xlwΰq(췒8y2Sfl|6Id>(-]lW壡^` J47;C ` > endobj 28 0 obj << /Length1 3664 /Length2 26750 /Length3 533 /Length 30947 >> stream %!PS-AdobeFont-1.1: CMMI9 1.100 %%CreationDate: 1996 Jul 23 07:53:55 % Copyright (C) 1997 American Mathematical Society. All Rights Reserved. 11 dict begin /FontInfo 7 dict dup begin /version (1.100) readonly def /Notice (Copyright (C) 1997 American Mathematical Society. All Rights Reserved) readonly def /FullName (CMMI9) readonly def /FamilyName (Computer Modern) readonly def /Weight (Medium) readonly def /ItalicAngle -14.04 def /isFixedPitch false def end readonly def /FontName /CMMI9 def /PaintType 0 def /FontType 1 def /FontMatrix [0.001 0 0 0.001 0 0] readonly def /Encoding 256 array 0 1 255 {1 index exch /.notdef put} for dup 161 /Gamma put dup 162 /Delta put dup 163 /Theta put dup 164 /Lambda put dup 165 /Xi put dup 166 /Pi put dup 167 /Sigma put dup 168 /Upsilon put dup 169 /Phi put dup 170 /Psi put dup 173 /Omega put dup 174 /alpha put dup 175 /beta put dup 176 /gamma put dup 177 /delta put dup 178 /epsilon1 put dup 179 /zeta put dup 180 /eta put dup 181 /theta put dup 182 /iota put dup 183 /kappa put dup 184 /lambda put dup 185 /mu put dup 186 /nu put dup 187 /xi put dup 188 /pi put dup 189 /rho put dup 190 /sigma put dup 191 /tau put dup 192 /upsilon put dup 193 /phi put dup 194 /chi put dup 195 /psi put dup 196 /tie put dup 0 /Gamma put dup 1 /Delta put dup 2 /Theta put dup 3 /Lambda put dup 4 /Xi put dup 5 /Pi put dup 6 /Sigma put dup 7 /Upsilon put dup 8 /Phi put dup 9 /Psi put dup 10 /Omega put dup 11 /alpha put dup 12 /beta put dup 13 /gamma put dup 14 /delta put dup 15 /epsilon1 put dup 16 /zeta put dup 17 /eta put dup 18 /theta put dup 19 /iota put dup 20 /kappa put dup 21 /lambda put dup 22 /mu put dup 23 /nu put dup 24 /xi put dup 25 /pi put dup 26 /rho put dup 27 /sigma put dup 28 /tau put dup 29 /upsilon put dup 30 /phi put dup 31 /chi put dup 32 /psi put dup 33 /omega put dup 34 /epsilon put dup 35 /theta1 put dup 36 /pi1 put dup 37 /rho1 put dup 38 /sigma1 put dup 39 /phi1 put dup 40 /arrowlefttophalf put dup 41 /arrowleftbothalf put dup 42 /arrowrighttophalf put dup 43 /arrowrightbothalf put dup 44 /arrowhookleft put dup 45 /arrowhookright put dup 46 /triangleright put dup 47 /triangleleft put dup 48 /zerooldstyle put dup 49 /oneoldstyle put dup 50 /twooldstyle put dup 51 /threeoldstyle put dup 52 /fouroldstyle put dup 53 /fiveoldstyle put dup 54 /sixoldstyle put dup 55 /sevenoldstyle put dup 56 /eightoldstyle put dup 57 /nineoldstyle put dup 58 /period put dup 59 /comma put dup 60 /less put dup 61 /slash put dup 62 /greater put dup 63 /star put dup 64 /partialdiff put dup 65 /A put dup 66 /B put dup 67 /C put dup 68 /D put dup 69 /E put dup 70 /F put dup 71 /G put dup 72 /H put dup 73 /I put dup 74 /J put dup 75 /K put dup 76 /L put dup 77 /M put dup 78 /N put dup 79 /O put dup 80 /P put dup 81 /Q put dup 82 /R put dup 83 /S put dup 84 /T put dup 85 /U put dup 86 /V put dup 87 /W put dup 88 /X put dup 89 /Y put dup 90 /Z put dup 91 /flat put dup 92 /natural put dup 93 /sharp put dup 94 /slurbelow put dup 95 /slurabove put dup 96 /lscript put dup 97 /a put dup 98 /b put dup 99 /c put dup 100 /d put dup 101 /e put dup 102 /f put dup 103 /g put dup 104 /h put dup 105 /i put dup 106 /j put dup 107 /k put dup 108 /l put dup 109 /m put dup 110 /n put dup 111 /o put dup 112 /p put dup 113 /q put dup 114 /r put dup 115 /s put dup 116 /t put dup 117 /u put dup 118 /v put dup 119 /w put dup 120 /x put dup 121 /y put dup 122 /z put dup 123 /dotlessi put dup 124 /dotlessj put dup 125 /weierstrass put dup 126 /vector put dup 127 /tie put dup 128 /psi put dup 160 /space put readonly def /FontBBox{-29 -250 1075 750}readonly def /UniqueID 5087384 def currentdict end currentfile eexec 4y9B0i H1r^ v.Hntµ'W"xp'DpԄ&,6 6WS:W0H:eTA7J.>Դ{8"ahγDn'$8NC z[wM 3FSj'SKx=x ՊE@ؗ&$F׵̽U e?bhvhcxN(01*H dn%oɟLaEn.'s:fd#~W /Sk_6їS0N_<hBH>(H#U#ȸE Of߱?h''HKchTOo<=7@ȱON-&g~|%RYQ~iwo+7 \Pj\> ,n|Rn59 ř%DL )2ϟՀc49 u|;j Zd@*& {u!7wLCWHjŖ⮓-,D7)[a<|*"O4gvшU\܋|:ps,e%>I>AL#PlGu@#z 8Jy.u,HapL٠pZV"hAcfE hVi@IYH2U ``zs.tNLbj:`I'Q΃]ѽi@X>Hռ y3|qd>HxqM5";8nޖT?j@rU˷C, yz4;Vױ:GoJt9}䖁xxHek}k5LmR رȼÙ0:O*;wL]F|62IJ_jqMt,P" t U`&*MB9W1=y~f г] @N'r U\+q$a+!oFZW$F?R鵪oЋ?&dMNose9J2V$XBgy5rIWC3zEx"i^EՓ4iD^;:$Ig8jOU0}Wʚu=ſƋm7*ٹwS,:n*Jn"E M }7,w/{`-Y4;'8⾢KQ 0X ƲZcfi:9SևΔX*P3W/7 !tB{HǎQp1+S+W{h ƛ2ÿgCF|Оhr(+ Y*U/K, ҋKFzh %uK[z2e;΂P {jQQaCh R\&ojrcT+V_ dKG\^XcVzc ̀6^oOx00ED3 >&d)i['ݵ~,|np"]5"83l& ߶~y9g=BɈiGa 7 q&QzA^g#~2pu;姌^$y;Os~a nN8ݗ2 iXl~7=P瘰_Go #Lr ?ɜ2xBBU )U4UTF*:U63\ #?e,v)tO`qQ:]-WT\)t4n2j"$l@ (tۯ,-O(Aӭ4(<,jzPKKN3̨|< =W [4#MVL\A71G+tJCdMOFۜf4΢?5(?us8&8XݦųS752rȰXtm ,}"lxQ 30k[J{Fr֚BG`83Xue,V>˦3utUt*+FlsO{zy@!q+бe;k7wIȍ$^9; YT.9_0׼8*7IXRojU&Y xPOڎc /L΂+=A|1Tdgkah ,y6,8 zg.ʙ%7 aFD*VpCX0j1Fgv7 _eGGC99݂S>#5N㖜2x F:+{29b[CStc!ṗVʬ=Q&96".颔0ܠ[V`lA}Y0|ջG=Y8WMN&_G\ +"sYU4ێĝu! ](r"K00w9&ORVW]ȈWJ6_u3Qf9JoFbt]n_|izDr(WR[@#h6+ //AJr[`wveq<͸nz&Ӿz%$?! 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{V VF6]%hOV]TCbC/a)J5d39zTvFAHV#`Ӟ(]WGm(nRĥE͇ڣsOԀZ yofI6|m 8j%ZuȻ"߀> *tꃱοPר4StY, C?W>iy3i5DbdHq#{qѥD9 + & _ط[G^i<[+=0 y)0 6S sΜ}é2$7P8T^e3 +JrxAu\*e 0bvEiD w4˗QK΄9{^Z3Ts$pJO|ϕ{ô7;2Xܢ'8 4S!twȓjen i&k;xZ4A*Uʝ, jϥ:@Wcdb莚sǞ~EקۇEqJoxk%A)&OհΠ ;GE^]s$e_k1h|nY<͝/̈́e|cZQ!}rU@t!hR۞@%{b2lЦr`wJ%>\'5;m̒61`qUmva,5"9=q[ uu } ȉQLD]Nʇ2UJkkI+d:>hh>-RT*cE-ϻ( (ELz_܂:b!=bE#:tnt D3?VH~FL|xvD!/ +jP&^v% EC-#[%%j[W+X`I=:O+BZirsm$,YUrCԿubސwHɰ!)j#0ׯan8qJoFk SCLv v[$~gYocw*NAaCQ"| tp&_v-8v_21ugf\AM>O%ʮ/S(YbT'k!XA ܭ՞C?z ?'Xv ;MBP^.[jj\UbdCDW h$ zgj&.83a)tѻdѨTuάwȊZ*L cFj(ɭ )v%>w6YR<,o\t݃V)[&Ty~vcW-|FOi,I#|6Qg݁~#ۗ) jwɕt~\' 3{Cರgy@@ih?qYл2(GEW_zalgD>@}NkԐT!4ZZ0ϫۥXGH nl 颅:txD$V "92`2q넘X[߼4@u.ߍXM4μ搛=: wMt}4w߼O\(Cֆfxak9'ZcxV$T*{|ȉ:ϒLt)ߓx\"Z30000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 cleartomark endstream endobj 32 0 obj << /Type/FontDescriptor /CapHeight 850 /Ascent 850 /Descent -200 /FontBBox[-39 -250 1036 750] /FontName/CMR9 /ItalicAngle 0 /StemV 74 /FontFile 31 0 R /Flags 4 >> endobj 31 0 obj << /Length1 3603 /Length2 21130 /Length3 533 /Length 25266 >> stream %!PS-AdobeFont-1.1: CMR9 1.0 %%CreationDate: 1991 Aug 20 16:39:59 % Copyright (C) 1997 American Mathematical Society. All Rights Reserved. 11 dict begin /FontInfo 7 dict dup begin /version (1.0) readonly def /Notice (Copyright (C) 1997 American Mathematical Society. All Rights Reserved) readonly def /FullName (CMR9) readonly def /FamilyName (Computer Modern) readonly def /Weight (Medium) readonly def /ItalicAngle 0 def /isFixedPitch false def end readonly def /FontName /CMR9 def /PaintType 0 def /FontType 1 def /FontMatrix [0.001 0 0 0.001 0 0] readonly def /Encoding 256 array 0 1 255 {1 index exch /.notdef put} for dup 161 /Gamma put dup 162 /Delta put dup 163 /Theta put dup 164 /Lambda put dup 165 /Xi put dup 166 /Pi put dup 167 /Sigma put dup 168 /Upsilon put dup 169 /Phi put dup 170 /Psi put dup 173 /Omega put dup 174 /ff put dup 175 /fi put dup 176 /fl put dup 177 /ffi put dup 178 /ffl put dup 179 /dotlessi put dup 180 /dotlessj put dup 181 /grave put dup 182 /acute put dup 183 /caron put dup 184 /breve put dup 185 /macron put dup 186 /ring put dup 187 /cedilla put dup 188 /germandbls put dup 189 /ae put dup 190 /oe put dup 191 /oslash put dup 192 /AE put dup 193 /OE put dup 194 /Oslash put dup 195 /suppress put dup 196 /dieresis put dup 0 /Gamma put dup 1 /Delta put dup 2 /Theta put dup 3 /Lambda put dup 4 /Xi put dup 5 /Pi put dup 6 /Sigma put dup 7 /Upsilon put dup 8 /Phi put dup 9 /Psi put dup 10 /Omega put dup 11 /ff put dup 12 /fi put dup 13 /fl put dup 14 /ffi put dup 15 /ffl put dup 16 /dotlessi put dup 17 /dotlessj put dup 18 /grave put dup 19 /acute put dup 20 /caron put dup 21 /breve put dup 22 /macron put dup 23 /ring put dup 24 /cedilla put dup 25 /germandbls put dup 26 /ae put dup 27 /oe put dup 28 /oslash put dup 29 /AE put dup 30 /OE put dup 31 /Oslash put dup 32 /suppress put dup 33 /exclam put dup 34 /quotedblright put dup 35 /numbersign put dup 36 /dollar put dup 37 /percent put dup 38 /ampersand put dup 39 /quoteright put dup 40 /parenleft put dup 41 /parenright put dup 42 /asterisk put dup 43 /plus put dup 44 /comma put dup 45 /hyphen put dup 46 /period put dup 47 /slash put dup 48 /zero put dup 49 /one put dup 50 /two put dup 51 /three put dup 52 /four put dup 53 /five put dup 54 /six put dup 55 /seven put dup 56 /eight put dup 57 /nine put dup 58 /colon put dup 59 /semicolon put dup 60 /exclamdown put dup 61 /equal put dup 62 /questiondown put dup 63 /question put dup 64 /at put dup 65 /A put dup 66 /B put dup 67 /C put dup 68 /D put dup 69 /E put dup 70 /F put dup 71 /G put dup 72 /H put dup 73 /I put dup 74 /J put dup 75 /K put dup 76 /L put dup 77 /M put dup 78 /N put dup 79 /O put dup 80 /P put dup 81 /Q put dup 82 /R put dup 83 /S put dup 84 /T put dup 85 /U put dup 86 /V put dup 87 /W put dup 88 /X put dup 89 /Y put dup 90 /Z put dup 91 /bracketleft put dup 92 /quotedblleft put dup 93 /bracketright put dup 94 /circumflex put dup 95 /dotaccent put dup 96 /quoteleft put dup 97 /a put dup 98 /b put dup 99 /c put dup 100 /d put dup 101 /e put dup 102 /f put dup 103 /g put dup 104 /h put dup 105 /i put dup 106 /j put dup 107 /k put dup 108 /l put dup 109 /m put dup 110 /n put dup 111 /o put dup 112 /p put dup 113 /q put dup 114 /r put dup 115 /s put dup 116 /t put dup 117 /u put dup 118 /v put dup 119 /w put dup 120 /x put dup 121 /y put dup 122 /z put dup 123 /endash put dup 124 /emdash put dup 125 /hungarumlaut put dup 126 /tilde put dup 127 /dieresis put dup 128 /suppress put dup 160 /space put readonly def /FontBBox{-39 -250 1036 750}readonly def /UniqueID 5000792 def currentdict end currentfile eexec i_,+`"WP 5 l.jkP P(?~M;^yy*f˼[:-Z/e_[+5{^dtp!~dZ+س:cEwK+_nCdZy2}m3U@-UӴHh[ a2:Y ]<}3bפ@ie3d_5=vHD`8niњ9T lZEz' +; UsF>zJ2(^K0ҀT}ΜhiG hy+vR3~ًʑ9v&ZŔ S"JD{^\ PO3PeYO;$T@ud] {UC]&Kln:FEs(!+,#QdB&U/G-twhPǟ.w*vA%HSAJqc٭ZF!>˄»#[b ec~( l5A;%0K3xЖ@ HɖSxfo"z5 `Rg!-:e9yGP\e2twK TÄphܰW\V/Z!v`,%^BjC%0Sdz/5ɪP_0"3`/Ҝ^*y^ EP"qqJ ,`1 ʥ?HiUu6H(XR:VQjSsl( jB5"؃{UpoxBx41E3:SƽWh=" -@;qjh2!!U9mBLD'[\rG qO}@D;_֜mUfQyHEӌ? 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Ԥ'ƁPDOdRH<%KWR^[YB)>Wб AME~h*ؤYt *5DsOLZ6VK ]h59u Ο(sG`>4bfݴ@y۹#kL\A6dϤ;<'QMʌku|2o ha&M=znU_W FMb SIi1 9C.s ( _Oo0jplV]A)ԩ}A *;j͆|\_tb&-A= V D{?,`lBq6`2:ym!kYfi<52?EM΋Qpp~Ƀeo3S77b5aR9@#@p?za*<{z2+s#4iYz$&l@ASdIY'#×s.t65&4.bDI%4;u{؉=әS(\ Y5%,x)vhf͒/ >H Lg2HkAЩQzݖ`o7T547n-_Я N+0peW2wwjngK뾕\ߒg*Ri4|"3ti4`6`|Ne \O{]8<[m!O"9p|4SE2uwQbu:ZE|xc`rMF, B{Ss3M~S>ɆzUaGIUPKQDoGsHҢd侷zӒg4R-裗l21%L]·y'+-'oW欢2J#yO_5\o=H$9:6\9f$i-gթfhs֑ڏ [2=^@ 'ȉh݇ȕ<5ӃPㄕ8tǭ2:㝓\Y+< YJ Sj!՟GKKV P\4Hf_[ʵbDݨiog3mjOD9ElCûhL"!lEdgSTɽYY1928uh=`yٙj0;+^xnS)|w劶ۤyh?QQS9H.=W%o /&vGrBDBXDN:@Ǝڔ6u-y.5 DME~p,38UH{nՄ뗇7eu3x?G'ЩU~/Xc@4SGoF [wb4 ;cRcsj>XdU^} 4),)oN1]֣5)؃>4;Oϔv[G7FIҠX hН5HH ֯l%.eʶ]щtŤ*,WzbTZ4 װ1PF(8 L;lJD5I5&5lII 6(ӽ'z{3z؞& .qbgPJ3Lz7aȥu>(uvF\V`K>SnVw mѲmח۰ 2=kgX0~Uf|V [JPß7ԜV32(5 ,T>AP+ZÓ;ׇw߶plhP=.PCM.9v ޝ./6t_wln/W.D~isL"|j&?KP)>Y ~z#(L º S ߋ??bP  Wȏ(uY#|Z8j+pAXR* ޫYy[dlu1K>u?*}P%^B|,qsMpjY`7}A-k2x/|,`ޜVT3fP.xhePqWP<| h2UWO`xi%3ck͏8Q.mm{#i/Ɵό왪WN Wax<}&Q9uZ p0=Oܞ9as*(IxX+y'L`P;o31 KTP}47O j4 WRRxBJO}SnI0r_RNJ]X4]Icּ2Gę~-N?Xx~ʷbz-Qڐ'Z HyY40@8Vreneu$\c%!Q@M\,,菽ӧ|s۠d'/Iiwx,E7O6GƢFuB.'!bؙ6$] 5/M[XwO$G!HP43<#!T*$T)bwALiuƊ{9ٽqQ {u#C˂0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 cleartomark endstream endobj 35 0 obj << /Type/FontDescriptor /CapHeight 850 /Ascent 850 /Descent -200 /FontBBox[-20 -250 1193 750] /FontName/CMR6 /ItalicAngle 0 /StemV 83 /FontFile 34 0 R /Flags 4 >> endobj 34 0 obj << /Length1 3603 /Length2 21052 /Length3 533 /Length 25188 >> stream %!PS-AdobeFont-1.1: CMR6 1.0 %%CreationDate: 1991 Aug 20 16:39:02 % Copyright (C) 1997 American Mathematical Society. All Rights Reserved. 11 dict begin /FontInfo 7 dict dup begin /version (1.0) readonly def /Notice (Copyright (C) 1997 American Mathematical Society. All Rights Reserved) readonly def /FullName (CMR6) readonly def /FamilyName (Computer Modern) readonly def /Weight (Medium) readonly def /ItalicAngle 0 def /isFixedPitch false def end readonly def /FontName /CMR6 def /PaintType 0 def /FontType 1 def /FontMatrix [0.001 0 0 0.001 0 0] readonly def /Encoding 256 array 0 1 255 {1 index exch /.notdef put} for dup 161 /Gamma put dup 162 /Delta put dup 163 /Theta put dup 164 /Lambda put dup 165 /Xi put dup 166 /Pi put dup 167 /Sigma put dup 168 /Upsilon put dup 169 /Phi put dup 170 /Psi put dup 173 /Omega put dup 174 /ff put dup 175 /fi put dup 176 /fl put dup 177 /ffi put dup 178 /ffl put dup 179 /dotlessi put dup 180 /dotlessj put dup 181 /grave put dup 182 /acute put dup 183 /caron put dup 184 /breve put dup 185 /macron put dup 186 /ring put dup 187 /cedilla put dup 188 /germandbls put dup 189 /ae put dup 190 /oe put dup 191 /oslash put dup 192 /AE put dup 193 /OE put dup 194 /Oslash put dup 195 /suppress put dup 196 /dieresis put dup 0 /Gamma put dup 1 /Delta put dup 2 /Theta put dup 3 /Lambda put dup 4 /Xi put dup 5 /Pi put dup 6 /Sigma put dup 7 /Upsilon put dup 8 /Phi put dup 9 /Psi put dup 10 /Omega put dup 11 /ff put dup 12 /fi put dup 13 /fl put dup 14 /ffi put dup 15 /ffl put dup 16 /dotlessi put dup 17 /dotlessj put dup 18 /grave put dup 19 /acute put dup 20 /caron put dup 21 /breve put dup 22 /macron put dup 23 /ring put dup 24 /cedilla put dup 25 /germandbls put dup 26 /ae put dup 27 /oe put dup 28 /oslash put dup 29 /AE put dup 30 /OE put dup 31 /Oslash put dup 32 /suppress put dup 33 /exclam put dup 34 /quotedblright put dup 35 /numbersign put dup 36 /dollar put dup 37 /percent put dup 38 /ampersand put dup 39 /quoteright put dup 40 /parenleft put dup 41 /parenright put dup 42 /asterisk put dup 43 /plus put dup 44 /comma put dup 45 /hyphen put dup 46 /period put dup 47 /slash put dup 48 /zero put dup 49 /one put dup 50 /two put dup 51 /three put dup 52 /four put dup 53 /five put dup 54 /six put dup 55 /seven put dup 56 /eight put dup 57 /nine put dup 58 /colon put dup 59 /semicolon put dup 60 /exclamdown put dup 61 /equal put dup 62 /questiondown put dup 63 /question put dup 64 /at put dup 65 /A put dup 66 /B put dup 67 /C put dup 68 /D put dup 69 /E put dup 70 /F put dup 71 /G put dup 72 /H put dup 73 /I put dup 74 /J put dup 75 /K put dup 76 /L put dup 77 /M put dup 78 /N put dup 79 /O put dup 80 /P put dup 81 /Q put dup 82 /R put dup 83 /S put dup 84 /T put dup 85 /U put dup 86 /V put dup 87 /W put dup 88 /X put dup 89 /Y put dup 90 /Z put dup 91 /bracketleft put dup 92 /quotedblleft put dup 93 /bracketright put dup 94 /circumflex put dup 95 /dotaccent put dup 96 /quoteleft put dup 97 /a put dup 98 /b put dup 99 /c put dup 100 /d put dup 101 /e put dup 102 /f put dup 103 /g put dup 104 /h put dup 105 /i put dup 106 /j put dup 107 /k put dup 108 /l put dup 109 /m put dup 110 /n put dup 111 /o put dup 112 /p put dup 113 /q put dup 114 /r put dup 115 /s put dup 116 /t put dup 117 /u put dup 118 /v put dup 119 /w put dup 120 /x put dup 121 /y put dup 122 /z put dup 123 /endash put dup 124 /emdash put dup 125 /hungarumlaut put dup 126 /tilde put dup 127 /dieresis put dup 128 /suppress put dup 160 /space put readonly def /FontBBox{-20 -250 1193 750}readonly def /UniqueID 5000789 def currentdict end currentfile eexec i_,+`"WP 5 l.jkP P(?~M;^yy*f˼[:-Z/e_[+5{^dtp!~dZ+س:cEwK+_nCdZy2}m3U@-UӴHhX.⤠HH<;]|& :|p[C#\zC)k;rc‘nZ E~ N K?=}'z݈ IS;ڄWFsqWeOCPp~G'c &SqF6h]xF>vVMN5r8L)ш0S˵/ w+:9UuF@0.Jto*6(Rps+T?RO~_xw`3j%2ryK4˚XYWؼ!.KFnȔpc-Y.4@~^FeK![bиWh2C7`C2+m̌x 2CgnkhA.搱 npT Q{PuqnK,ve?+s{o{orQڎ_y BVoO1s }z ǣ[ AMB[s'?,a\1 0"(wrSajW"Ŋ~"!m8W\p+`N& 0lKG^t*aCRҞcM&Hn,@IE<ίpγtȻw*>F8Ťn-Vв^eÃ۱;Xϋ S$mZ5ӀK>"u{ ʸv(en[R =4eQ ]k S]O7(7#XޖGhf"7c aef.6@Q*cV2 rܽ dqPu~~@'-עs`gSHH8 癊cIoLbHiS~nF0N96ϴ-Q+P&Z(X-J90c5 ~Fu SA7Eh_W0EL5ɶ{R_|8Dx>JHy8c&"R9x`&̝.Z[͋B*nCBrw̴,aGIrASG5kAZn>[x/^-?904fQHZbʕNzybalyz6fvql㧩~Ft03D "o) \ w"tBa^-h:xװ5*x]0]5I'&͏ YONA+v借ª@Dj k F=uO|mDe1zsݣ *b*)?V_%IjQ1Sy|M|, )ոo\CЌ*ƨzۓ?@ZXQp!¹@:5 KKu"1KYlG9G*gQdרJ0@Z(ra>!X73Qعv48U 90{3bE \V7BUxh F)4mihv`J!4 8"g дICמ|1 xJPCh!B.CcC{\III;Zv$˒j͔@n_2k"yx跨ޢ5j/K;LNKoSAe}dR=" zR5Gϙr uԻ,. ,.b[ ́w d^; btj…Dxy02Ƹ5Ž1QF:JD $%(O9OrXc_n!y_F LV!&Ij|^}y+!:_{= 7m%ǏC >cbkV8O&^ yX֒F o|Z2^f3Y,* /?gon-0Ҷ{i ¯raE%R_+3n 6L~JBuDa/LȰj1za 8/> YT5F X[_=r0Hqm|!@>/w|gAcoj\$ZlUuɟ񞒧)s/f6[$ (>a?;țLV3aRo3M4>ƑUE~ω*LD}f >u8i(m]g ias|{ dv_6>섟|~OsC ^c1$ &tJ([ wҙyA#>g)}BFT0ֺaL1 9bj qm.|o%f16-'̇'1aT(v%Ȃ:[DԳ#MXxRr *{o4u}* !.&VY>pzpRS/5qǺC]M7¶&nz.'^ʶRmD%c E8]' + $<~EdKJ1a|(F2d$PteJ1)Y̢F! u##abف(44Ir\BYlWUlVi#bBsOkP'Kx;H'3Xn8x[2ɸ۹.pE'&TA2Elnߴᱴak%x62i*&\gɚׄj#߸! <_gAsgk|D@}dh`014);ZRIJa31;GrgCn|3?F5/ŭb Q'z6~'>w9'`@(X WFm~ύ9ɳoAl b%N7  G柗E'qUA JȤ"o1` SH-"cd3 或ⵤ7;Ȟo'@ziƎ޴O\&j*f;1^wgu+7z6LNN݇ny/<)#"(@某9 "/p\O`_k]7l_3tջ#i>\ ^-1,thr:'!||>6hhD ?A\M:P(T)8.L}＞K Y8]>B_orqϓNQ:щ|βyug fJa9gYl=9WgAka̕YAa.k|oQ5k-io ާ◵tW,YG1:=wz͌^O-Nqe;cuBVL&JѪEϔv(K*XTiO`9΀$h)f1|ίm=s;'!Qၙa"Sܜ9 PeS_ҝ;ari0t+Ob$SUzX3r6{ei<FLu hDF58M;:,  /j%l@v{'[gEC+l>ܱ{`O*#3٦)&ȰЯl AV%PyKxp1voED1ݾH/ V)U%N +%C& r1v5) ص~ omL\!݀N?n5"]k5w&=8<ds"㥮U/&nײ|Zay:]:ȠOn9!ܹ[1yAܚڵ ӀAS7|ύT!S쑅{qӔ׌L)؆xJ9L#oZ؁*j2ͼY1 h\fW[D{mVuɺH -g`+ڵ̇ixƋGY#x'q\6i z!SEL#.GimķNbu{+]X}8ؖ 43C@lLpMՕΟXG% uHF5 cP[DuX#>,-2b=`÷ҖOOM$GpȌSVv|Y(sZPIVnv|Kv_lLↇ{o4C5Zlw}M@$G﷤)]D/b{ιpe%+9RH~1ey'^!%Q=u1+R4RP:=-w]qp& Wwuhf"N<@BLYڛJfԱ4zƓ}wS zFWbf T/4OTYʰ@9a̾I~kLqՄ.qN 6ۃumc7U7֬-HYb r3x77n:&u{ cLEwDͨ"lb\R+/+ZQtV=L;%&L]Gjs*_hB.UmtcXxaըw*CrIΧf0GC;"JAbAXmuc;o,t٭AfJW[Jy=Bƚp`ܒcW/IxװڈA bc4I'N:9;]'YQz(9lqhEv-.^0wïOo-P07C^F̫ GĢ"g}Xߺh; y.<-YjZ&Yb[eIx#Et5I;N` LNJr ^*hB_R/\Qz#5[&㱆mf)%>=$]JgWSIcLO`E)@w{P!]m<0!7,G#$'GEid)E(ߓZG٭q(I&%]г67gȔP˿əљ59$DjUEYZVy,"ih9lEUS9 Zrvxa;̞W]̮#Ncb9y/IE$; 69U9ߤ2ױ900ӊ@r ~2 QE$7F(.V|Π riU&E!Q8ŗE,uhV5,t[!W9AELV$ĥ7HzFǼ^G)~-p}l_UGfwv M˨^}I1 {i>} v8d=$j' V?m4F-q-}HGGN'O]#R0lRtTe'L=Q "C 988PҟI RQqfUsY$zϠ7N^4TL#;_{_ z-7cZr @.KR\f#w.>:D${I4w|%kuû_;$h(!qBlo!6l(#tOWZs7*ұif~r׹xj&XOhXblQG;W=Z g藘bXPIk@4\`3JgZCdB [̯8ˮEZRpNX9&%l(]4Re:\͡>ۚ["涳qn@ù ,? 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All Rights Reserved. 11 dict begin /FontInfo 7 dict dup begin /version (1.0) readonly def /Notice (Copyright (C) 1997 American Mathematical Society. All Rights Reserved) readonly def /FullName (CMSY8) readonly def /FamilyName (Computer Modern) readonly def /Weight (Medium) readonly def /ItalicAngle -14.035 def /isFixedPitch false def end readonly def /FontName /CMSY8 def /PaintType 0 def /FontType 1 def /FontMatrix [0.001 0 0 0.001 0 0] readonly def /Encoding 256 array 0 1 255 {1 index exch /.notdef put} for dup 161 /minus put dup 162 /periodcentered put dup 163 /multiply put dup 164 /asteriskmath put dup 165 /divide put dup 166 /diamondmath put dup 167 /plusminus put dup 168 /minusplus put dup 169 /circleplus put dup 170 /circleminus put dup 173 /circlemultiply put dup 174 /circledivide put dup 175 /circledot put dup 176 /circlecopyrt put dup 177 /openbullet put dup 178 /bullet put dup 179 /equivasymptotic put dup 180 /equivalence put dup 181 /reflexsubset put dup 182 /reflexsuperset put dup 183 /lessequal put dup 184 /greaterequal put dup 185 /precedesequal put dup 186 /followsequal put dup 187 /similar put dup 188 /approxequal put dup 189 /propersubset put dup 190 /propersuperset put dup 191 /lessmuch put dup 192 /greatermuch put dup 193 /precedes put dup 194 /follows put dup 195 /arrowleft put dup 196 /spade put dup 0 /minus put dup 1 /periodcentered put dup 2 /multiply put dup 3 /asteriskmath put dup 4 /divide put dup 5 /diamondmath put dup 6 /plusminus put dup 7 /minusplus put dup 8 /circleplus put dup 9 /circleminus put dup 10 /circlemultiply put dup 11 /circledivide put dup 12 /circledot put dup 13 /circlecopyrt put dup 14 /openbullet put dup 15 /bullet put dup 16 /equivasymptotic put dup 17 /equivalence put dup 18 /reflexsubset put dup 19 /reflexsuperset put dup 20 /lessequal put dup 21 /greaterequal put dup 22 /precedesequal put dup 23 /followsequal put dup 24 /similar put dup 25 /approxequal put dup 26 /propersubset put dup 27 /propersuperset put dup 28 /lessmuch put dup 29 /greatermuch put dup 30 /precedes put dup 31 /follows put dup 32 /arrowleft put dup 33 /arrowright put dup 34 /arrowup put dup 35 /arrowdown put dup 36 /arrowboth put dup 37 /arrownortheast put dup 38 /arrowsoutheast put dup 39 /similarequal put dup 40 /arrowdblleft put dup 41 /arrowdblright put dup 42 /arrowdblup put dup 43 /arrowdbldown put dup 44 /arrowdblboth put dup 45 /arrownorthwest put dup 46 /arrowsouthwest put dup 47 /proportional put dup 48 /prime put dup 49 /infinity put dup 50 /element put dup 51 /owner put dup 52 /triangle put dup 53 /triangleinv put dup 54 /negationslash put dup 55 /mapsto put dup 56 /universal put dup 57 /existential put dup 58 /logicalnot put dup 59 /emptyset put dup 60 /Rfractur put dup 61 /Ifractur put dup 62 /latticetop put dup 63 /perpendicular put dup 64 /aleph put dup 65 /A put dup 66 /B put dup 67 /C put dup 68 /D put dup 69 /E put dup 70 /F put dup 71 /G put dup 72 /H put dup 73 /I put dup 74 /J put dup 75 /K put dup 76 /L put dup 77 /M put dup 78 /N put dup 79 /O put dup 80 /P put dup 81 /Q put dup 82 /R put dup 83 /S put dup 84 /T put dup 85 /U put dup 86 /V put dup 87 /W put dup 88 /X put dup 89 /Y put dup 90 /Z put dup 91 /union put dup 92 /intersection put dup 93 /unionmulti put dup 94 /logicaland put dup 95 /logicalor put dup 96 /turnstileleft put dup 97 /turnstileright put dup 98 /floorleft put dup 99 /floorright put dup 100 /ceilingleft put dup 101 /ceilingright put dup 102 /braceleft put dup 103 /braceright put dup 104 /angbracketleft put dup 105 /angbracketright put dup 106 /bar put dup 107 /bardbl put dup 108 /arrowbothv put dup 109 /arrowdblbothv put dup 110 /backslash put dup 111 /wreathproduct put dup 112 /radical put dup 113 /coproduct put dup 114 /nabla put dup 115 /integral put dup 116 /unionsq put dup 117 /intersectionsq put dup 118 /subsetsqequal put dup 119 /supersetsqequal put dup 120 /section put dup 121 /dagger put dup 122 /daggerdbl put dup 123 /paragraph put dup 124 /club put dup 125 /diamond put dup 126 /heart put dup 127 /spade put dup 128 /arrowleft put readonly def /FontBBox{-30 -955 1185 779}readonly def /UniqueID 5000818 def currentdict end currentfile eexec i_,+`"Wٰ'Z1NςRoN]+,󡈙5Н; lƸKprKn YOu^ a4B0P$~MMmv0vV )6 6 7N!$IE9aJg%d^kQ G20,D+4~Q|w^e1v|0Sp;K ']da{$K**o)&Fy Ětcz~v$jg&qA+sVt؆[>1rm;(Fxjf|uJm+#f`xB-H;U^* O[A[;ސIzG<-*螨wt2*%PNϜbI~^n2r Q{ؘwYXEFt2o6ڐCn6< (,1diw`z`,cZ2ݽ $2!ak/&;)zygqeuVBcŗG@qD_V4+癪qiЃ GQ"5Ps9r7x]7eBïzG.\X,~I$=J/9el_ŅAͽH 2NHhZ` (1h_!F= X)kʦzINt1< c?cB½OK$l/-zϛ $̹%$oE>0qr݉q]Ä%Mjp z>-tn4og9)05~UF J`-K}G!765wF`C1UMՔ=_%K]?qfN_Å'ʍ7%5dNGl~W%=9:(DC5IP01X."¿ $Z^ _TP3kiOw;? 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C`Usg!u*zU߉uxYNd90  +o`gsj*T(ͳ^UIӊxn "}5+prDMEFҌkq~w*:{ chu5Ɲn hy_//݄DwPh@cc/|mX _ ^p\cӜ>4 c]T!vf67w;I+e7fCӱ,q|JijvJ+ο:.PEQOX^å\o VOPJzP+߾ΗB n유'jW$uz,.D5l -iğDqNx%SR؉<`D׭^_/`SSsPJ9red2]V\,Lm=̈_i;\dh6'֓J>b;eMoҒ)/UݸcX<@_X{Q~XN0} qj˅C+b2ޱ&SɌ3r4թ'Ù7ee#ʓZSyƪLPN5a>i1s.1O Z &~'%П쒢lomyj_GRwp9 >G\OO$Bwun`nU"BT`[+T.' :|qOuem3g8d'Z4mD^shYm\fr3U|ax$Qi%)"hP~ep}7D$ &8Hm JnOU'amվC= 38 #Ξ6mcB'\[4y5hVbL<ܨ<*{x|ؓ}5[6ft/Q_z0ᦁ !)c{U b!Fm0;D)/wN Bn?i~(,w-L }TP/"lgW1~h1І[\S\%ޜr1K%{+Ș>rmH[PC:ыbQ[YdKfG)Or0ҳvJ> pظ:NRPlUVӠ{^̇r]Kb"HF7btHp8Y'aJݪl )@lNB+#8b!!YF407psp %7ӡ NW m_Sg{N ߭@*&w#mj*%jy1h-[5H?P?>Mӗ˹zr$<(xĿi3H")ԛCMPxvBsqlvTk+nSfOh1*Q @sPNr]sa#x,9p85 }2Nj4o݋5(T[^9TA%ۜ#}/ZƐ5aڒv(O~j H6S픦= ^?a{cu'm%qQP>E/ϗX0WϖIsF:N?PݾqWڒe/{M<4( "2 soA(k08zނZup)# XV[qiF%z>]>Y/Y߈S;AUX\WxČI,T'a6ܭ)pHJSB9}$q>k4AgSoH8)lb!G۶n[=yv٨O%Lv'ڑX0Jld BBH߾]E%JHyɺNJ &h8$[t?-,Aƌc %3=8[BhB~k&CЫÍo)Q[V ٘7:kwq7WfI'nbvniݒ"CU0a`k/FCގAX⒉q^x1¶f2*"+8 p0ͣ|NF']r '+)_6 KW%3%o#jJ C4OdIEiD &KGuE'Yi"DIm95 qQޤq-De+2\!iĬV%^OLi X$(FCavd4y&~'џAc1#E[Xu,sqݙ}wn-Όn6] 9eB܊9d{!>V;n$RxT 刦6qhϋ +· [˜YˇieHdW8If+mШJQ7 d[F9\A6;c\)ShoH2} P9A}2B~)"UZ[- #U1Ͱ7i7r*nMtLK=o]+oBsmD̖8DE*ƹI\$'_ `_lm&$>xT+O Q ʬcS8nY`1f/z`Y64,LwJ}KQiiw`qj1}k#*[XK*Į`ޗ@G^5 T"Y3:/)} fiY70VuJ*7Qc"qrT>C)U}YsxQΌܖcxE^e#Z\I b^9 C L>l8 ˬW=)cFl6ќ UrË$4I-Gz$F#-2(nϤJ^QXDmi:)|Dm-yV|֩nC7-*1 R[\P|S} iѩ$(m<0t-W{5'9PC6niܠDž 1=17I5j8f d $~(S}%~:v5SW0].].G,GŰWM\ rZ,yUd0L2ʆ*(v܄Z))`@o6 Rq^8g2?B'Ǩǡ}PG6aPz$34~NX&`8*/_[}ϳ h9`"uY-aTZ/ qcȔcMд %7 ?{̵W2vPp`ԝ>E]:DB uozUx̘yL5ޱifˡLy̯3m1شbssp >-N9ܣY=j&G{2SY]9jc]`'>,tCo;2eq/AjL|(ޚVL +"G-uE1ig(K=%cW޺y Qk;rK.hᱞId95-kZ4iz !"E5@DX[QZ8%Lx@i*+z z9Q~#*ZV7k*tDD꿄˳k]pϫ6n\r9o^Yݼ*7 xBwH$^KCEGI̅ ]ks*6}ClA0_8It@=.ߝkq qT$s Ý曐FyC3kPI7MRTcCyJC)>]]|V*”*3ը³V2$580:+Srz&[DySE}ku LWݩ 0AeeGoF7a8#.LS2XPRg sdZB# LO`q[E瘔N*HD!a.W]J4̱\n gJYPjMuΝ%afPr֓%NC3/'IXcktcz>Xh }5̈́is(*T+^Ui3 8*}`p}°3mM[\9Pޱq}6Q\hF鈎`tKyKd4Yk=8=,ڂrKhZP,V"}622{6(PKG{ut}=i?^:*['O.F ~حrgp99ڸh< 主|aˋ}sf>k\t q&n5^I=4P /}w@mHiR/#{wܕ>Jg>vi6s@9[e;&6Нݼ% NIy%/ׯd6defȐYh%o{2%XI ^.ѓF}V\>/{jp*Ead3" yW((%J3kⅪx3[!Ǎuyi'>~JKe-M.EStFl ZDGk;u]*:+AULSgV-g7McD/7bNw6@\<4h QtwJY@T)2O3 |teu\l$t;|q%}!swm;|Fum[KuzkN 3lyCmc8 i? U'Fbt3>.*72k֙ˊ-ɠNrhk_b'1 wU a#h, ?I9ܥq F~av:bF!csFs8AZ<Πub1^rr5jnAr)\XbuI8mͥZ5Tfv/x[߈G%GCJ_Ws[QDŎjnP A֣+9"^҃ҧu^2nWk2Zw0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 cleartomark endstream endobj 43 0 obj << /Type/FontDescriptor /CapHeight 850 /Ascent 850 /Descent -200 /FontBBox[-30 -958 1146 777] /FontName/CMSY9 /ItalicAngle -14.035 /StemV 87 /FontFile 42 0 R /Flags 68 >> endobj 42 0 obj << /Length1 4310 /Length2 22083 /Length3 533 /Length 26926 >> stream %!PS-AdobeFont-1.1: CMSY9 1.0 %%CreationDate: 1991 Aug 15 07:22:27 % Copyright (C) 1997 American Mathematical Society. All Rights Reserved. 11 dict begin /FontInfo 7 dict dup begin /version (1.0) readonly def /Notice (Copyright (C) 1997 American Mathematical Society. All Rights Reserved) readonly def /FullName (CMSY9) readonly def /FamilyName (Computer Modern) readonly def /Weight (Medium) readonly def /ItalicAngle -14.035 def /isFixedPitch false def end readonly def /FontName /CMSY9 def /PaintType 0 def /FontType 1 def /FontMatrix [0.001 0 0 0.001 0 0] readonly def /Encoding 256 array 0 1 255 {1 index exch /.notdef put} for dup 161 /minus put dup 162 /periodcentered put dup 163 /multiply put dup 164 /asteriskmath put dup 165 /divide put dup 166 /diamondmath put dup 167 /plusminus put dup 168 /minusplus put dup 169 /circleplus put dup 170 /circleminus put dup 173 /circlemultiply put dup 174 /circledivide put dup 175 /circledot put dup 176 /circlecopyrt put dup 177 /openbullet put dup 178 /bullet put dup 179 /equivasymptotic put dup 180 /equivalence put dup 181 /reflexsubset put dup 182 /reflexsuperset put dup 183 /lessequal put dup 184 /greaterequal put dup 185 /precedesequal put dup 186 /followsequal put dup 187 /similar put dup 188 /approxequal put dup 189 /propersubset put dup 190 /propersuperset put dup 191 /lessmuch put dup 192 /greatermuch put dup 193 /precedes put dup 194 /follows put dup 195 /arrowleft put dup 196 /spade put dup 0 /minus put dup 1 /periodcentered put dup 2 /multiply put dup 3 /asteriskmath put dup 4 /divide put dup 5 /diamondmath put dup 6 /plusminus put dup 7 /minusplus put dup 8 /circleplus put dup 9 /circleminus put dup 10 /circlemultiply put dup 11 /circledivide put dup 12 /circledot put dup 13 /circlecopyrt put dup 14 /openbullet put dup 15 /bullet put dup 16 /equivasymptotic put dup 17 /equivalence put dup 18 /reflexsubset put dup 19 /reflexsuperset put dup 20 /lessequal put dup 21 /greaterequal put dup 22 /precedesequal put dup 23 /followsequal put dup 24 /similar put dup 25 /approxequal put dup 26 /propersubset put dup 27 /propersuperset put dup 28 /lessmuch put dup 29 /greatermuch put dup 30 /precedes put dup 31 /follows put dup 32 /arrowleft put dup 33 /arrowright put dup 34 /arrowup put dup 35 /arrowdown put dup 36 /arrowboth put dup 37 /arrownortheast put dup 38 /arrowsoutheast put dup 39 /similarequal put dup 40 /arrowdblleft put dup 41 /arrowdblright put dup 42 /arrowdblup put dup 43 /arrowdbldown put dup 44 /arrowdblboth put dup 45 /arrownorthwest put dup 46 /arrowsouthwest put dup 47 /proportional put dup 48 /prime put dup 49 /infinity put dup 50 /element put dup 51 /owner put dup 52 /triangle put dup 53 /triangleinv put dup 54 /negationslash put dup 55 /mapsto put dup 56 /universal put dup 57 /existential put dup 58 /logicalnot put dup 59 /emptyset put dup 60 /Rfractur put dup 61 /Ifractur put dup 62 /latticetop put dup 63 /perpendicular put dup 64 /aleph put dup 65 /A put dup 66 /B put dup 67 /C put dup 68 /D put dup 69 /E put dup 70 /F put dup 71 /G put dup 72 /H put dup 73 /I put dup 74 /J put dup 75 /K put dup 76 /L put dup 77 /M put dup 78 /N put dup 79 /O put dup 80 /P put dup 81 /Q put dup 82 /R put dup 83 /S put dup 84 /T put dup 85 /U put dup 86 /V put dup 87 /W put dup 88 /X put dup 89 /Y put dup 90 /Z put dup 91 /union put dup 92 /intersection put dup 93 /unionmulti put dup 94 /logicaland put dup 95 /logicalor put dup 96 /turnstileleft put dup 97 /turnstileright put dup 98 /floorleft put dup 99 /floorright put dup 100 /ceilingleft put dup 101 /ceilingright put dup 102 /braceleft put dup 103 /braceright put dup 104 /angbracketleft put dup 105 /angbracketright put dup 106 /bar put dup 107 /bardbl put dup 108 /arrowbothv put dup 109 /arrowdblbothv put dup 110 /backslash put dup 111 /wreathproduct put dup 112 /radical put dup 113 /coproduct put dup 114 /nabla put dup 115 /integral put dup 116 /unionsq put dup 117 /intersectionsq put dup 118 /subsetsqequal put dup 119 /supersetsqequal put dup 120 /section put dup 121 /dagger put dup 122 /daggerdbl put dup 123 /paragraph put dup 124 /club put dup 125 /diamond put dup 126 /heart put dup 127 /spade put dup 128 /arrowleft put readonly def /FontBBox{-30 -958 1146 777}readonly def /UniqueID 5000819 def currentdict end currentfile eexec i_,+`"Wٰ'Z1NςRoN]+,󡈙5Н; lƸ:(1Zz fT%|#!q'/:;Ę=of0"ީ^ƫ*R|** GyMH_ij|Y cd8л&_ c;8t*"/ DFF c6swi'?#wBs`lt 9AQR~@T%&MWevń뿨eEynd LmwCS6XͲ~֥.LgOo?~]Z&m (aE=LݾAl6}ЦE=f]TsN^ X/Y~(|UKKrQ#0 Iarw UAʄoվ4Mc4}qf%Q@$pzi%\5g:mK ?[Yqbo9>迶,+6ݺ[aejGmkIqwdpV>!N"NE YS]jw 㾍ËѼb3hJ觙nO7S˴ Ff!7- ԪIșPchg!^J.•~=5JKE+-KqtN;3=9"gu^%x p8-c',U·O)aQS me!'*G<…4vҫ B̏xzder0P"[oEwd7yn=XAu\!٥Y!E`J)>$J;ppRVn>UO :wK:j7aq5 D tB> 刕碶_D5@q>Ǩo6Էt|/D!6@TY>@:!;gB.h 9XK0xhluK\Ε@[s EBh_oas뺞2mK8tN2;2D*mF;yB(ϴeYp'ϣ5t^6@fa6a.vBU ^K?Ļ '4IYᑧ~xJSmj!qjU) KY2~!O&$>h?>pG9#-,n4/ 0:EY-K("Ob).'0` pVӠn V$FMf1DV)WTNS9PN nвD#GEwuA v\»'؆&TljmDV)6m'Z,S@E:øY.(rb_Yl$!,<|R1Dw⸆w|Ip.#`sMNJИO}X@%/9Nn]3 UxtpjșuQԼu qs ˉ'JTi~laj- 蚟3uk ސPl=QB`H-)r)l]OLv5moYXσH%w1(gj%'4j˃:ICL4tm`rwK){ᜠf+,4!Y"gp[HifOhЛis ?!t\CZ@qۆlHV8hR0˔7`d(T={9'E7n41Թ.1%,ĺOXmj_ 䦿oY偑(?gi66ǃҁST$#I6T~7垖.xJ4 +^X}efxi|~!Y]F-<\dgԕ'wU."'+KݒUF;O븀!Xmr*mstϽXZ}:#ǎR>6EJVޓCˉV}K5,mnÜ䞁g)6>z" EMfc!OxP2^t&idvx+;^I4)ԗ9K+T(&ᄂ%'_{ 3:MX$R|1_Hͪ҆nFZޤy=n08drI݈uYW=],bS7X٣4nrTվ㥛n&ŧWMS7t.\#ZNK17k,AÃ8Ƶ *|JH\J]~ɿyjoSt_\;TΑ ˺= CGX4ы; N+4ҫ1sċxb RUgk㫩Gɧ\ A}?C%( ^N!,ԘyOUJ{!O.Q$^.Fs c_*gߦ_dEA] C WKV]SJ1Yvq >=@(e$na7Kƞ1u`3]iRĦoױ.A!?\s! Vr=R#fFwUmM$% ]oaჀq;{|pS)F&Ya1LӸb3Y8x0)ou4I1&e YˁLkk6\*<9:%Δ􀑁S ZWAڝ.6,O. 0L]ctv(?{IM'OG0zJFV*bxC\i^O:1gr^UV9JE&v,D92g!eX~>ThvDϰ2UJH&+t:R3%1豼kr yapn_ܺŵTR˗kqKW@`ky7wJs8_:rL<Ȣa3PB{.އIۜ+f6I4~%O.̂a2qїQX`F~l&Dn3ɠ{_-zU;RoS :0W1:&[= N=>C9>ӈLڴTWDa[ngh$XSZ,t ?\3YO? }tT  6^jmo6]Qvy+mWi^5bʭDSq毗͸ṙJ.-rdwXFnۡJj3Qt7 Zhn!4;L5ԨQu[X=+ fʜQcrC FjD2m4W>NCD^Ѥf1=uy4! ZP:m1^lun%H ,#w QWV ? ? տ z60k 4?yAǶ^"2-w.aĕ"A4 ). _/ٽIUz&1 ;/ BѪuq5/F{2/ ƴ2'_[oKV$d=c~C-jq҃,;q *wǞ1QI+AF9Rxˣ?wAjU T(ٌR=D, m'$B-J{/u]ùN.~ 2b+ꫣ Qu!tB/mzL?W2 #R-/m5' ՒZ J0י1Oj2"Zf%w$~\U ?N>(ķXBVHWg+ ϙmu*]r O1ʹVfĭضvT:f)%:Bc%,e$ޭ&O֎3 ؾB#`CgFow[;,VP@X$K"/|Zۄ8}}ԧqEmj3P=VnK7@ sDDeEB>([$kՅRfo&Ul>PkM*4N1CxHnzךP5F`$lE! : qa$ X vO!a-;"(n(4nrdp6m@:_})we΅²x"j4У?嵻0p -[)a 3AjR)_/"0U'.xbU&6vknepdvr„fGWݎ]hy%F4ZXcv·='Π&Sދu᳷E^>/xz^:/zrb7,zn;ZLiq ;FcX,[tA1$Y8`?sfB4>0`KJ5@TlӰh֬AK":>~, sSC`~Ysl1ʇO^ȃTW rѝXdlC`ſH+}a>oIrXBR0QIj`[}b*k38oJ(ɡ#R.JJ \< H.,X~(&<κl3̎ =ii|)7ʮTo 4qf f< m3d-:]b?D3i2%%+nM 7iUd.JXDt*zGz̐'(dS^͚8"ͶףJio3Q!b+q48 cpuU{ve\a,n@$qi㘏BEymnI^ƿ.Ú1.Xpc]ez^.^FWi7Ѱ?9H[Ѝšf\\|Xsu& b2BQ/ab' ʫ9*?D IYV!jՑ VCqe-k*a'u%4,\xvˇףVEY 0-hzQjN+^iO# }2SBbs%` $xn "6~oV^^2]_fn?qfH SK&5n e?\yv_|nsԌ$|+v^$ RID_p=d  EO5 ^B0YxO?2Tjl&Tu:Nm;Bj{9- /6rA*@\eft0.R҂3ĬCXJM 1»= =w]`y>N}r/wTxQهjaEzBqx:@Ȳ%M./ByYŻ:):鑗؄En|.jƞQL*x_^b!H 4Ki`n egC1#N_bsVrȰ``[T ]䮜%Xk(wDv.q1%ZD(R%ECg}Y ˯ r4m #ke7ޭjgMJm{fjt*]˳ts,1߁&aBhTrY818&"e*@'taLV~hb#rꗾ#-j~i;>K`JAK(0K"^>bt?^hOU]8n@AZphP{cMN/+;X?E1vk9\tfj Pά4=Yvf|GxP\YxSS so!Ccɰc\\IR1O˛ cZϳ_oBKóI!;w+BHW#Ej^m) d!sV}NSĥ{Xpulhu)PB8򧙟Ap(u@ =gcoSl-/w' ՉdGc=I`1ox1'৳::0,}>ao36 u{j;ӍO!eM<읇[KCOC*.;+aS'2O( Ǫr{ZR~zŐ߹.|Xu2[~DUOqqgK#<12S1\vƕЉ)M:WJrTԂCnxT(|iqӼ \%xdW|Мt2.׶!TS^iQfQO8`Ҹ{Y{:qĄ5QOf 5 O¾\/ 4@ 6 %S,ۨZ"Bzњq`DxM۟5 3 /s"Uǂ3X]A8WCb$="Q쭸(gU3u>'p#)qP0K:{Gc|rEG{)DTP:駑B,߳lqy('&&:U^E.Y$thN7DI=M&auMqhʵa#ڦdtIӡ(X _fVr]-נ4 W.K@偯tpekۡ9*kt #QL!A-˹pRjf*bmlT(+yLfZ8M~iAP!Y]|j%,wx7o4U{xv| Ż}M9c2WD8bǡPYѓ9]ϫ;a>ܾ g ([Mv:bg/cpXș2#j:uLa3V!q'}9v͌R׎\9:, fB# ?izult>7Ui[WܙW AqQf!j|XB#osbwA~J(3aggD%-iZ)Ke{aSz(Bט?j|{tGLf@]-h_Y!<ceD2:Y&u1k •ơUހ 4B:AwXsU~Kl"K࿲z}M;x8mx] N,oHF ضP`^®{U:L#OW#5 GWB;MiֻTV#]Ey|3=ІשǽA".1p4@ 3IUִQ ʮ;P $AҢUFpl 01U#p -8u7`Jrg^)XoGAI3ZLAЉlvG%]_#?t2oa~` *qx3~['$[9 $d64i1574yGV:r}P!\N -. 8ַ npaWG /<9՟^lt==7%]2TuOdt\ o$rFBe]EBGõ 4CPC|j_m} 4Ia)Q_G^YB7wbW"%Х RpکwI-č'ķ<ϜU0| ҍTLh>ţOPZY6hHgi3A[IS1`k[\nV%Jl4E ?i:`Mi}D=sZ\F8 A3q_a[E?"LIH7OSX@6L/]n~xQ)"u]ca z}3(FWxM, ]]F}ו\D?=r xOF9z\A$\ԭ&Kg!Jeᠢ5䦀%E%EݛsygoC쀞ߞq/+.bAAqD[%$:b87d'aр~.(66acEH1č[TU}itkV:*j}|0}3EfoĊtgp,Mnq* blg獃R*ok U d F6t!DTQ_\ +S;A2Ƶ뻨x돹EL!/Q.H1_* DʋnNxW6o"Ed ;O"S6eMfKAjl$mtKys\W<۝JCLӅ٫(H)~E _p -lÂɆayAwsVgSRGL9n,' a?1/M:hF륙ꊏdSB2HLzFv.h9ǣ GxM(XS*r,$+%IMmԑ3 "%Wbp-M ԩrh t6ѼOj?]_ "5ou Nš:\KHG8lw 5&?Doݮ s.IcԂ!pAmwc&f61vb[e5R((AcZ|Ѣ9rtK B@BS'SzԵ.F(PInM.ȲNb2kH~G?kշq28 f3<TyuM3`S{ Gel2u&06U}5R\?lt1XQSzim;>i"cɵj/T\ұf(1o슴u'm تn|U 7)RJ RIҋTĪ(2Q>V(w&0\ WKu1@kyf'撵4jY˓(llF;B 䳻}^*]`!Ӌy2ݥ? +jץ/dd*}[~D+PzA">VxEHW<ȫG%ަ*4p{e:9Mjjݹwd(|ۃz&eDf .%OaHPYzro9zN-v {;ÛŒ j츖Em496Ub-8e{?U7P->G] Iwf!>ey &@~j?;>jqj P^넁ى&ry Nɢ9! 8>F|b#z[baL~[߻%<IG Лz c :btXg/vQ=&F?8jX1IfEm MeXFf^qXEu4)uZEE,YM$oPR;mu)I7ۉdq;fY?M㪛.h`zT^[ e *&2b*7܋s4(gKarNWsc5ߝ%nΩXi'ubOvu!oJd3[GNH[utA`1W iO6/.3{1tNl @Bi5Hf3 FL =y6@'B$ $N2;2N<ނiE꽎{#&#}Az&ԡ0I4~/HPtP'<CH;y$ณ,q5K8Axq>u6Juǹc }Ufzϡ=m#I%$y_P" oŽt9-HM%Fj )QT!#.TX$srm\%9srO>%}]@JvzV3MI}`Bq/U@RdUPО\DcB 7iY< rNUN0?dJ@jqs`I:Ų#:h_`gf4*L0%\*J(6_1ͻ#W>dF4*s=Cǣ~c[d/Tӊ :0nI9Ңa=*_&CWm5 ʒV xgX \{7ef؉?OB^tpdZ}ۋ.̋7u$q<`?]ǎ.I Jb,MM8 E5a%Nڊ1?J|2ҡb7\MWyu,J IOȹga5$y1UxrPBÀ5p[[F;uN:#Cr1T\E$FW~u _l.k+_BoQ2&KCNZ;L8j:JM)N$PÔՑڎ?X"0rڽSK(uOYNډ h"2fH߭Ɯ9E+|K+;}pt_dd{`8ک+g+#P$s'?XT>Ac(>L4d,}s\L.&QLMqjonL6FՇo2RHm# xyI,dbB~YӮ&5!, 0).yC|u:;WX) 6KNX ?9$eLQM蓝ap,@cI 9O7g*}+9e{ăZ@CV͗$d*a3Ȟ:4aՆ|3b BiAaB/DCg~Q5|!!f.,|jJ'8&迓 Q8땷J?b1f$g"!Mr W6J)ҚYdc8Wt`M>@n$bj"F)Qk"-:c+һ_íۤ`9"{`S?f:Xiux>T;?W]XwJ|,1B>3PB[^CJi^O.(Uȥtt|m}j!pÍĻ(T-S\Ag++[8K`[ .?\3˂xØɚݣ*vY D KqtOnLRKKnG AvН\P{8}l%ǃC1R!T'j|>v5\?b(WEێO7iXL [;^^ڧ5cwқ ;Gשx2*ƂK؛UB)hW}7u9<~̕jM: ɖD0J/yd1O,6lH[V +3_q:rZPT?*Q6Xe:ƯGZi[҃FT`/B!ZOd:fvwlGݎaXݐ**&RbV.k[ {L. J=%Nږnuq4~6(C )QjQʲؙL^P2P HTE#7x[ŭ%ƫҩ%Y:䯚U]myڋ=8K *Zq?>X4?FSC_qcwV&\g쾜\ ٕ('< L)fЧKW̺4*P_.4~Y%[[HɂL@R:+.;]M, gZ`#Uq'O>Jm9 aJ#´;#gǭ7m | ]6py:V_y w-k:Kև(L\c]8p"A 5g A X<~,'YAa?zhBgF2ՌO+-q|eGͦ{RDEo%NK#y[?EvLs:n7"-孷.R:s W<*-dCd+  Sɛ`wV AFj c6L$gf!f u랸ΝcE(3>e$oܝennIng,4E)Z7 ?QJnP $>ѓkaYe,%'=SK[:QI^(FxDz¼|Q`I"xӝCb<5g(qs˺lu2_# .7Pv)>^d%@)2nkVUqS?W8=zP.SyP->A|ںJm* vB~Lvu=PmbU3*"˂Sٽjžx.A =8< Rt,gtLԁ鮵 +DžwP%ʄ뤫N']Wq. ghb1 cԭ{P݄\l\DU?XY֍4ve5*(+vމDNv-DLSj8L7 [&>ؗ>ٮn{Yhr Zˆ"}A"j{**ra(jQP2n-w%ہqɜ2o#+rMrVA:Ѓk!sİH e wаs"7ߨ#߬(ݙiuf?Ȏ)(:q~czPI TYN>sD@ 'Q˹933\UL'7zF.*Keꣅ#;lGs]Fի1vM9RFCqKDžc '9#P<ݼ?`S'YL ?m2x;gmӰ(ږW'5ߡB`z٥#;jUzܭ٨6j6N3/"FO'?=KmՀ Pz$+$!rČfEk*d ݠ~UY%K0W#C"WvzPr 7[-$IRAgJk##>0Mx2ƼdHHhv(9HNE&Ց^&60yǔgHws,ȿՀ1i#47Kq;AluA@GrƋb%c+=߳3nuV!7dꑺ`&QKlϺ*^i=.Ƀ%VHKͫ^BWAs[ΨftΟ;6rXmRN2NـYx/ 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000000000000000 cleartomark endstream endobj 46 0 obj << /Type/FontDescriptor /CapHeight 850 /Ascent 850 /Descent -200 /FontBBox[11 -250 1241 750] /FontName/CMMI6 /ItalicAngle -14.04 /StemV 85 /FontFile 45 0 R /Flags 68 >> endobj 45 0 obj << /Length1 3663 /Length2 27056 /Length3 533 /Length 31252 >> stream %!PS-AdobeFont-1.1: CMMI6 1.100 %%CreationDate: 1996 Jul 23 07:53:52 % Copyright (C) 1997 American Mathematical Society. All Rights Reserved. 11 dict begin /FontInfo 7 dict dup begin /version (1.100) readonly def /Notice (Copyright (C) 1997 American Mathematical Society. All Rights Reserved) readonly def /FullName (CMMI6) readonly def /FamilyName (Computer Modern) readonly def /Weight (Medium) readonly def /ItalicAngle -14.04 def /isFixedPitch false def end readonly def /FontName /CMMI6 def /PaintType 0 def /FontType 1 def /FontMatrix [0.001 0 0 0.001 0 0] readonly def /Encoding 256 array 0 1 255 {1 index exch /.notdef put} for dup 161 /Gamma put dup 162 /Delta put dup 163 /Theta put dup 164 /Lambda put dup 165 /Xi put dup 166 /Pi put dup 167 /Sigma put dup 168 /Upsilon put dup 169 /Phi put dup 170 /Psi put dup 173 /Omega put dup 174 /alpha put dup 175 /beta put dup 176 /gamma put dup 177 /delta put dup 178 /epsilon1 put dup 179 /zeta put dup 180 /eta put dup 181 /theta put dup 182 /iota put dup 183 /kappa put dup 184 /lambda put dup 185 /mu put dup 186 /nu put dup 187 /xi put dup 188 /pi put dup 189 /rho put dup 190 /sigma put dup 191 /tau put dup 192 /upsilon put dup 193 /phi put dup 194 /chi put dup 195 /psi put dup 196 /tie put dup 0 /Gamma put dup 1 /Delta put dup 2 /Theta put dup 3 /Lambda put dup 4 /Xi put dup 5 /Pi put dup 6 /Sigma put dup 7 /Upsilon put dup 8 /Phi put dup 9 /Psi put dup 10 /Omega put dup 11 /alpha put dup 12 /beta put dup 13 /gamma put dup 14 /delta put dup 15 /epsilon1 put dup 16 /zeta put dup 17 /eta put dup 18 /theta put dup 19 /iota put dup 20 /kappa put dup 21 /lambda put dup 22 /mu put dup 23 /nu put dup 24 /xi put dup 25 /pi put dup 26 /rho put dup 27 /sigma put dup 28 /tau put dup 29 /upsilon put dup 30 /phi put dup 31 /chi put dup 32 /psi put dup 33 /omega put dup 34 /epsilon put dup 35 /theta1 put dup 36 /pi1 put dup 37 /rho1 put dup 38 /sigma1 put dup 39 /phi1 put dup 40 /arrowlefttophalf put dup 41 /arrowleftbothalf put dup 42 /arrowrighttophalf put dup 43 /arrowrightbothalf put dup 44 /arrowhookleft put dup 45 /arrowhookright put dup 46 /triangleright put dup 47 /triangleleft put dup 48 /zerooldstyle put dup 49 /oneoldstyle put dup 50 /twooldstyle put dup 51 /threeoldstyle put dup 52 /fouroldstyle put dup 53 /fiveoldstyle put dup 54 /sixoldstyle put dup 55 /sevenoldstyle put dup 56 /eightoldstyle put dup 57 /nineoldstyle put dup 58 /period put dup 59 /comma put dup 60 /less put dup 61 /slash put dup 62 /greater put dup 63 /star put dup 64 /partialdiff put dup 65 /A put dup 66 /B put dup 67 /C put dup 68 /D put dup 69 /E put dup 70 /F put dup 71 /G put dup 72 /H put dup 73 /I put dup 74 /J put dup 75 /K put dup 76 /L put dup 77 /M put dup 78 /N put dup 79 /O put dup 80 /P put dup 81 /Q put dup 82 /R put dup 83 /S put dup 84 /T put dup 85 /U put dup 86 /V put dup 87 /W put dup 88 /X put dup 89 /Y put dup 90 /Z put dup 91 /flat put dup 92 /natural put dup 93 /sharp put dup 94 /slurbelow put dup 95 /slurabove put dup 96 /lscript put dup 97 /a put dup 98 /b put dup 99 /c put dup 100 /d put dup 101 /e put dup 102 /f put dup 103 /g put dup 104 /h put dup 105 /i put dup 106 /j put dup 107 /k put dup 108 /l put dup 109 /m put dup 110 /n put dup 111 /o put dup 112 /p put dup 113 /q put dup 114 /r put dup 115 /s put dup 116 /t put dup 117 /u put dup 118 /v put dup 119 /w put dup 120 /x put dup 121 /y put dup 122 /z put dup 123 /dotlessi put dup 124 /dotlessj put dup 125 /weierstrass put dup 126 /vector put dup 127 /tie put dup 128 /psi put dup 160 /space put readonly def /FontBBox{11 -250 1241 750}readonly def /UniqueID 5087381 def currentdict end currentfile eexec 4y9B0i H1r^ v.Hntµ'W"xp'DpԄ&,6 6WS:W0H:eTA7J.>Դ{8"ahγDn'$8NC z[wM 3FSj'SKx=xr!0u\/0:jm;FS'01NJ)m+yA%״~zg~A%GW" Hc*Ʊ߃8[2qq3A>G~.dz:> F 9u9D>dKuC{{o|j!yH9MB7k0 \2~$k/kmtm9}a _ Wd=:xyV/7%CL S츩RrBs jD=eG"17GL&WÍƥh0=T$K};[Q[vمB2[k(3BŵbZP9$Z 2uR538M/R'28JT} <~A\p|@XvnUaB>v8=A]'錣Vx_ks@tԂZBs|޹4ڀG";63U`Z9vj#>S@B.::`+U\j%x:n#b)Paj6bevH/6 255Va6 C=  i*eaLަNڕXQ&bĕԽ[iEqr=dZG׍hk0.YbD Xޓy}]#Xju3Jj%s3pc d(y`>FX$V%p)w\W6zy-Kv/Qj~IZ9,ʼ~[]neIMrcW }؆"t8P$jmnC@Q5涙&6k Тr~<ƊzHjilVҨ`iQ]x_t1ʍ,e2QABu–̅8W}y2 tчE5m$|55@x?Һ!}4ߢ4yv%׫,@g.ԹlU SjA'Z50bn]ǙgF*❱KD<%-bS H$ߌh.@A?-w `V&2\Ci;O=M4MĘ08hs餂#_cnܼNλK9!!p@JSϡPVByo5$hCG5*8vA*DPxڿr{-G0t"3a}eQG .P/w.VWcety[-ZKtHo2ilgWUmEea o}Ew2;5(b=$^!gr5G.3 $?IYmք49³Q oJuZQR^#iZ@ K JϴbFqtc1oUNؖx*]1l[|cykBk~ WqVLj+z$$}^ġx=*ly:cYBJd$H&+]7Ge鞉ѶۨTm朚v?xj4$ݕʢg!r!skXTONzMeM*%U$!6 =K }8M9CEvI@T88M ~MlQ% i*@+lSpddI 3;2^s$(OQ<ҬaߒS}CxC]:h)s ᧶?vUH" ,S]a\4i,Qۚ^D7o[ޣ>9ʦBo!S_dBjAa' ͭH^Є[TۺǘFɸ[6Ԧnu1%="paP(hW7E-޲\%Yb% QUoîT0ȿxI ɚwa B/!!WZXO}ڼ^ϲ@h+(OJ.~zUQVR-NRWDCH͇~jA|wG-{0ZY5XB:uQwBS/a.m'Bhӽ/ENޕeWD} Gl?Bo+&H8ZaUY߼:W4*nP+4!ˍ" . .SdP rus?:AJ(\R"b"[zPshk=);QXh2޺Dzh g/E9 PT G|lsѻ|h0LsOWSЮ rH&g6 !)361_εO4BPC,_4O)o-Ťk൒()ɟ擔5; 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JCPиn5j|3|` GBb{K(g)ַput:˺;YYMR5^V. }NMUGd[*T1D/e=4sDսe @iDZBh5G7VΪQW Y"qk:EWN~0*H:㎈G9^ӂNS'/UxC0{19tfiS 9!IKfު %XxT o&|m S-XTGҏu&vg:YN5T:gAX,6_a1+³~H44 bBtgu RMӌʊ Kp^>L-T_X0slHjg7@6C |pؚ mzT&: ;q;& xDxL }!R]"L5dW1h{4#Ā,Rą`ZĬWl vx)ƍzyE5D=!RoEᆨRҽ-AOJ^3"/}) 2ܰxCLDkACqVv/eLD&TWW@q4@^K~ 1/^fGsj^f9)Ӏ 9 D%}r](:&&OhT_w.)A jSl !vN|`N۴-4ۮe3*;^u䌸T_t>|8є28eOM|!zi.3RH0bHsAJ S*^9{5„qS~ZH ]WV2YܷXa/}=Ǜ:%ZI5r`&k,HPks&Ppцe/Gǽ^ H:k 楠 <$閎fӮ;,,kH+ HAL̀ _vX]jM&XWb7, 8W5" XO:#Omo#Hmk T>p{'*d+E ds,x.1ܹ%'BmiI@hdōm[M 9< dV2fYod0GH(i\7L"߯dk{x݉aM![jb:*WvX :~OEæٜ+Zȝ鑑[b|HCNm@`kIu'!`zKuꆏVNwX~+>g˂N Yu:σj rB=cW R;9GMBFFu"`δwH1%h$.sd8! ɁsE\*R w*F-[Ur1Ae\(l{,,_n$Mb}mMĘ1 q hyn3K pK8˖u5gi4 -&}/頑Kk [9}z=!žSXy#ގcy I~˵/&[͚c&rCaӓM= z[GksV7Oߜ%Ѽ_ct.pDqjI9cH%89|{g~vչC'ɹu,u|N֓ʵX`[APC<ה#4hy68mL KV)dj]u6#VOl_Q8dް'l>܋'@<窈ܢc?g:Z2zle2(;e;pu7p[j~4X[s?Q]9.[tIn{]R_>hyVwbgW>Ij?<*Zf9˔/Qgo-ٱ87@Gn8=vUyckx{OF׭K2]f#Ϫw؟.r7p8Z[PӢ,0Sn啃mzl-"OyX>3#r/$ftAJl>$UM9Ν۹O9dmf* -]qЫйo̧Sc[#qKJ$+F ?x VK}MkL"aR! 3F\.CJY{'*5Fkayn0ȮupTaü%[qU|槻܊׭T9I(3_!096GQY΀E^4H_t]jGѴ1KcH >ky ~RF~B'QZC (9ª. t$9cl-rEỿX *niuK'|-wԚgvQCSYAof301W9ek s!!?ֲ?Hէ++FrCU0 *aWŝR~XW:zHx> endobj 48 0 obj << /Length1 4309 /Length2 22148 /Length3 533 /Length 26990 >> stream %!PS-AdobeFont-1.1: CMSY6 1.0 %%CreationDate: 1991 Aug 15 07:21:34 % Copyright (C) 1997 American Mathematical Society. All Rights Reserved. 11 dict begin /FontInfo 7 dict dup begin /version (1.0) readonly def /Notice (Copyright (C) 1997 American Mathematical Society. All Rights Reserved) readonly def /FullName (CMSY6) readonly def /FamilyName (Computer Modern) readonly def /Weight (Medium) readonly def /ItalicAngle -14.035 def /isFixedPitch false def end readonly def /FontName /CMSY6 def /PaintType 0 def /FontType 1 def /FontMatrix [0.001 0 0 0.001 0 0] readonly def /Encoding 256 array 0 1 255 {1 index exch /.notdef put} for dup 161 /minus put dup 162 /periodcentered put dup 163 /multiply put dup 164 /asteriskmath put dup 165 /divide put dup 166 /diamondmath put dup 167 /plusminus put dup 168 /minusplus put dup 169 /circleplus put dup 170 /circleminus put dup 173 /circlemultiply put dup 174 /circledivide put dup 175 /circledot put dup 176 /circlecopyrt put dup 177 /openbullet put dup 178 /bullet put dup 179 /equivasymptotic put dup 180 /equivalence put dup 181 /reflexsubset put dup 182 /reflexsuperset put dup 183 /lessequal put dup 184 /greaterequal put dup 185 /precedesequal put dup 186 /followsequal put dup 187 /similar put dup 188 /approxequal put dup 189 /propersubset put dup 190 /propersuperset put dup 191 /lessmuch put dup 192 /greatermuch put dup 193 /precedes put dup 194 /follows put dup 195 /arrowleft put dup 196 /spade put dup 0 /minus put dup 1 /periodcentered put dup 2 /multiply put dup 3 /asteriskmath put dup 4 /divide put dup 5 /diamondmath put dup 6 /plusminus put dup 7 /minusplus put dup 8 /circleplus put dup 9 /circleminus put dup 10 /circlemultiply put dup 11 /circledivide put dup 12 /circledot put dup 13 /circlecopyrt put dup 14 /openbullet put dup 15 /bullet put dup 16 /equivasymptotic put dup 17 /equivalence put dup 18 /reflexsubset put dup 19 /reflexsuperset put dup 20 /lessequal put dup 21 /greaterequal put dup 22 /precedesequal put dup 23 /followsequal put dup 24 /similar put dup 25 /approxequal put dup 26 /propersubset put dup 27 /propersuperset put dup 28 /lessmuch put dup 29 /greatermuch put dup 30 /precedes put dup 31 /follows put dup 32 /arrowleft put dup 33 /arrowright put dup 34 /arrowup put dup 35 /arrowdown put dup 36 /arrowboth put dup 37 /arrownortheast put dup 38 /arrowsoutheast put dup 39 /similarequal put dup 40 /arrowdblleft put dup 41 /arrowdblright put dup 42 /arrowdblup put dup 43 /arrowdbldown put dup 44 /arrowdblboth put dup 45 /arrownorthwest put dup 46 /arrowsouthwest put dup 47 /proportional put dup 48 /prime put dup 49 /infinity put dup 50 /element put dup 51 /owner put dup 52 /triangle put dup 53 /triangleinv put dup 54 /negationslash put dup 55 /mapsto put dup 56 /universal put dup 57 /existential put dup 58 /logicalnot put dup 59 /emptyset put dup 60 /Rfractur put dup 61 /Ifractur put dup 62 /latticetop put dup 63 /perpendicular put dup 64 /aleph put dup 65 /A put dup 66 /B put dup 67 /C put dup 68 /D put dup 69 /E put dup 70 /F put dup 71 /G put dup 72 /H put dup 73 /I put dup 74 /J put dup 75 /K put dup 76 /L put dup 77 /M put dup 78 /N put dup 79 /O put dup 80 /P put dup 81 /Q put dup 82 /R put dup 83 /S put dup 84 /T put dup 85 /U put dup 86 /V put dup 87 /W put dup 88 /X put dup 89 /Y put dup 90 /Z put dup 91 /union put dup 92 /intersection put dup 93 /unionmulti put dup 94 /logicaland put dup 95 /logicalor put dup 96 /turnstileleft put dup 97 /turnstileright put dup 98 /floorleft put dup 99 /floorright put dup 100 /ceilingleft put dup 101 /ceilingright put dup 102 /braceleft put dup 103 /braceright put dup 104 /angbracketleft put dup 105 /angbracketright put dup 106 /bar put dup 107 /bardbl put dup 108 /arrowbothv put dup 109 /arrowdblbothv put dup 110 /backslash put dup 111 /wreathproduct put dup 112 /radical put dup 113 /coproduct put dup 114 /nabla put dup 115 /integral put dup 116 /unionsq put dup 117 /intersectionsq put dup 118 /subsetsqequal put dup 119 /supersetsqequal put dup 120 /section put dup 121 /dagger put dup 122 /daggerdbl put dup 123 /paragraph put dup 124 /club put dup 125 /diamond put dup 126 /heart put dup 127 /spade put dup 128 /arrowleft put readonly def /FontBBox{-4 -948 1329 786}readonly def /UniqueID 5000816 def currentdict end currentfile eexec i_,+`"Wٰ'Z1NςRoN]+,󡈙5Н; 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target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_median_filter.lua.cc", dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp=true, object{ file = "c_src/ctmf.c", --include_dirs = "${include_dirs}", dest_dir = "build", }, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_median_filter.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{}, document_bind{}, }, } april-ann-0.4.1/packages/imaging/median_filter/test/000077500000000000000000000000001263004425400223475ustar00rootroot00000000000000april-ann-0.4.1/packages/imaging/median_filter/test/median_filter.lua000066400000000000000000000005601263004425400256550ustar00rootroot00000000000000-- usage: april median_filter.lua orig.png radio dest.png orig_filename = arg[1] radio = tonumber(arg[2]) dest_filename = arg[3] print"loading" image = ImageIO.read(orig_filename, "png"):to_grayscale() print"filtering" print(image) dest_image = image:median_filter(radio) print"saving" ImageIO.write(dest_image:to_RGB(), dest_filename, "png") print"done!" april-ann-0.4.1/packages/knn/000077500000000000000000000000001263004425400157415ustar00rootroot00000000000000april-ann-0.4.1/packages/knn/kdtree/000077500000000000000000000000001263004425400172175ustar00rootroot00000000000000april-ann-0.4.1/packages/knn/kdtree/binding/000077500000000000000000000000001263004425400206315ustar00rootroot00000000000000april-ann-0.4.1/packages/knn/kdtree/binding/bind_kdtree.lua.cc000066400000000000000000000070661263004425400242030ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "bind_matrix.h" #include "bind_mtrand.h" #include "matrixFloat.h" //BIND_END //BIND_HEADER_H #include "kdtree.h" using namespace KNN; //BIND_END ///////////////////////////////////////////////////// // KDTree // ///////////////////////////////////////////////////// //BIND_LUACLASSNAME KDTreeFloat knn.kdtree //BIND_CPP_CLASS KDTreeFloat //BIND_CONSTRUCTOR KDTreeFloat { LUABIND_CHECK_ARGN(==,2); int D; MTRand *random; LUABIND_GET_PARAMETER(1,int,D); LUABIND_GET_PARAMETER(2,MTRand,random); obj = new KDTree(D,random); LUABIND_RETURN(KDTreeFloat, obj); } //BIND_END //BIND_METHOD KDTreeFloat push { LUABIND_CHECK_ARGN(==,1); Basics::MatrixFloat *m; LUABIND_GET_PARAMETER(1,MatrixFloat,m); obj->pushMatrix(m); LUABIND_RETURN(KDTreeFloat, obj); } //BIND_END //BIND_METHOD KDTreeFloat build { obj->build(); LUABIND_RETURN(KDTreeFloat, obj); } //BIND_END //BIND_METHOD KDTreeFloat print { obj->print(); LUABIND_RETURN(KDTreeFloat, obj); } //BIND_END //BIND_METHOD KDTreeFloat searchNN { Basics::MatrixFloat *point; double distance; LUABIND_GET_PARAMETER(1,MatrixFloat,point); int idx = obj->searchNN(point,distance,0); LUABIND_RETURN(int, idx+1); LUABIND_RETURN(double, distance); } //BIND_END //BIND_METHOD KDTreeFloat searchKNN { Basics::MatrixFloat *point; int K; LUABIND_GET_PARAMETER(1,int,K); LUABIND_GET_PARAMETER(2,MatrixFloat,point); AprilUtils::vector indices; AprilUtils::vector distances; obj->searchKNN(K,point,indices,distances,0); april_assert(indices.size() == distances.size()); lua_newtable(L); // stack: newtable for (size_t i=0; igetMatrixAndRow(index-1,row); int coords[2] = { row, 0 }; int sizes[2] = { 1, obj->getDimSize() }; LUABIND_RETURN(MatrixFloat, new Basics::MatrixFloat(m, coords, sizes, false)); LUABIND_RETURN(MatrixFloat, m); } //BIND_END //BIND_METHOD KDTreeFloat size { LUABIND_RETURN(int,obj->size()); } //BIND_END //BIND_METHOD KDTreeFloat stats { int number_of_processed_points = obj->getNumProcessedPoints(); LUABIND_RETURN(int, number_of_processed_points); } //BIND_END april-ann-0.4.1/packages/knn/kdtree/c_src/000077500000000000000000000000001263004425400203105ustar00rootroot00000000000000april-ann-0.4.1/packages/knn/kdtree/c_src/kdtree.cc000066400000000000000000000016261263004425400221020ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "matrixFloat.h" #include "kdtree.h" namespace KNN { template class KDTree; } april-ann-0.4.1/packages/knn/kdtree/c_src/kdtree.h000066400000000000000000000374551263004425400217550ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef KDTREE_H #define KDTREE_H #include #include "disallow_class_methods.h" #include "matrix.h" #include "maxmin.h" #include "MersenneTwister.h" #include "min_heap.h" #include "pair.h" #include "point.h" #include "qsort.h" #include "referenced.h" /// K-Nearest-Neighbors. namespace KNN { /// KDTree class for KNN search. It is not a complete KDTree, it isn't allow /// to insert or remove points. All data is pushed as bi-dimensional matrices, /// and after that the KDTree is build. template class KDTree : public Referenced { APRIL_DISALLOW_COPY_AND_ASSIGN(KDTree); typedef AprilUtils::vector< Point > PointsList; static const size_t MEDIAN_APPROX_SIZE=40; // For median computation struct MedianCompare { const int axis; MedianCompare(int axis) : axis(axis) { } bool operator()(const Point &a, const Point &b) const { return a[axis] < b[axis]; } }; // Node of the KDTree class KDNode { APRIL_DISALLOW_ASSIGN(KDNode); Point point; KDNode *left; KDNode *right; const T split_value; ///< Used to split the hyperspace in two. public: KDNode(Point &point, KDNode *left, KDNode *right, T split_value) : point(point), left(left), right(right), split_value(split_value) { } ~KDNode() { delete left; delete right; } const Point &getPoint() const { return point; } const KDNode *getLeft() const { return left; } const KDNode *getRight() const { return right; } T getSplitValue() const { return split_value; } }; /// Class base for KNN search. It implements the interface for searching /// decisions, stores the k-best (or 1-best), and indicates when to stop. class Searcher { APRIL_DISALLOW_COPY_AND_ASSIGN(Searcher); public: Searcher() { } virtual ~Searcher() { } virtual void process(const Point &node_point) = 0; virtual int side(const T split_value, const int axis) const = 0; virtual bool leftIntersection(const T split_value, const int axis) const = 0; virtual bool rightIntersection(const T split_value, const int axis) const = 0; }; /// Specialization of Searcher for the NN search class OneBestSearcher : public Searcher { APRIL_DISALLOW_COPY_AND_ASSIGN(OneBestSearcher); Point &X; int best_id; double best_distance; const int D; public: OneBestSearcher(Point &X, const int D) : Searcher(), X(X), best_id(-1), best_distance(DBL_MAX), D(D) { } virtual ~OneBestSearcher() { } virtual void process(const Point &node_point) { const double current_distance = X.dist(node_point, D); if (current_distance < best_distance) { best_distance = current_distance; best_id = node_point.getId(); } } virtual int side(const T split_value, const int axis) const { if (X[axis] < split_value) return 0; else return 1; } virtual bool leftIntersection(const T split_value, const int axis) const { const double diff = X[axis] - split_value; const double intersection_distance = diff*diff; return !(intersection_distance > best_distance) || X[axis] best_distance) || !(X[axis] &a, const AprilUtils::pair &b) { // we use > instead of < to convert the min_heap into a max_heap return a.second > b.second; } }; /// Specialization of Searcher for the K-NN search. It uses a max_heap where /// the points are ordered by distance (desceding order), allowing to use /// the furthest point to define the hypersphere. class KBestSearcher : public Searcher { APRIL_DISALLOW_COPY_AND_ASSIGN(KBestSearcher); typedef AprilUtils::pair HeapNode; typedef AprilUtils::min_heap MaxHeapType; Point &X; double kbest_distance; const int D, K; MaxHeapType max_heap; public: KBestSearcher(const int K, Point &X, const int D) : Searcher(), X(X), kbest_distance(DBL_MAX), D(D), K(K), max_heap(K,KbestPairLess()) { } virtual ~KBestSearcher() { } virtual void process(const Point &node_point) { const double current_distance = X.dist(node_point, D); if (current_distance < kbest_distance || max_heap.size() < K) { HeapNode e(node_point.getId(), current_distance); if (max_heap.size() == K) max_heap.pop(); max_heap.push(e); const HeapNode &top = max_heap.top(); kbest_distance = top.second; } } virtual int side(const T split_value, const int axis) const { if (X[axis] < split_value) return 0; else return 1; } virtual bool leftIntersection(const T split_value, const int axis) const { const double diff = X[axis] - split_value; const double intersection_distance = diff*diff; return !(intersection_distance > kbest_distance) || X[axis] kbest_distance) || !(X[axis] &indices, AprilUtils::vector &distances) { indices.resize(max_heap.size()); distances.resize(max_heap.size()); for (int i=max_heap.size()-1; i>=0; --i) { april_assert(!max_heap.empty()); const HeapNode &top = max_heap.top(); indices[i] = top.first; distances[i] = top.second; max_heap.pop(); } } }; // properties const int D; ///< The number of dimensions int N; ///< The number of points /// A vector with matrices which contains the data AprilUtils::vector< Basics::Matrix* > matrix_vector; /// A vector with indices of first point index in matrix_vector AprilUtils::vector first_index; /// The root node of the KDTree KDNode *root; Basics::MTRand *random; ///< A random number generator // for stats int number_of_processed_points; // private methods /// Builds a point given its index Point makePoint(int index) { int row; Basics::Matrix *m = getMatrixAndRow(index,row); return Point(m, row, index); } /// Returns the position of the median given a list of point indices and the /// axis where to compare Point computeMedian(const PointsList *points, const int axis) const { const size_t size = AprilUtils::min(MEDIAN_APPROX_SIZE, points->size()); PointsList aux( static_cast(size) ); for (size_t i=0; irandInt(size-1)]; MedianCompare predicate(axis); return AprilUtils::Selection(aux.begin(), size, size/2, predicate); } /// Splits into two PointsList using the given pivot (excluding it) void split(const PointsList *points_list, const Point which, const int axis, PointsList *left, PointsList *right) { T value = which[axis]; for (const Point *it = points_list->begin(); it != points_list->end(); ++it) { if ( (*it) != which) { if ( (*it)[axis] < value ) left->push_back( *it ); else right->push_back(*it); } } } /// Builds recursively the KDTree, returning the node which contains all the /// underlying points KDNode *build(const PointsList *points_list, const int depth) { if (points_list == 0 || points_list->size() == 0) return 0; int axis = depth%D; Point median = computeMedian(points_list, axis); PointsList *left_split, *right_split; left_split = new PointsList(); right_split = new PointsList(); left_split->reserve(points_list->size()/2); right_split->reserve(points_list->size()/2); split(points_list, median, axis, left_split, right_split); // KDNode *node = new KDNode( median, build(left_split, depth+1), build(right_split, depth+1), median[axis]); // delete left_split; delete right_split; return node; } /// Generic search method, uses an instance of Searcher to compute /// intersections with hyperplane and the search hypersphere. void searchKNN(Searcher &searcher, const KDNode *node, const int depth) { if (node == 0) return; const Point &node_point = node->getPoint(); const T split_value = node->getSplitValue(); const KDNode *left = node->getLeft(); const KDNode *right = node->getRight(); const int axis = depth%D; // ++number_of_processed_points; searcher.process(node_point); switch(searcher.side(split_value,axis)) { case 0: searchKNN(searcher, left, depth+1); if (searcher.rightIntersection(split_value,axis)) searchKNN(searcher, right, depth+1); break; case 1: searchKNN(searcher, right, depth+1); if (searcher.leftIntersection(split_value,axis)) searchKNN(searcher, left, depth+1); break; default: ; } } /// For debugging purposes void print(const KDNode *node, int depth) { if (node == 0) return; for (int i=0; igetPoint().getId(), node->getSplitValue()); print(node->getLeft(), depth+1); print(node->getRight(), depth+1); } public: KDTree(const int D, Basics::MTRand *random) : D(D), N(0), root(0), random(random) { IncRef(random); first_index.push_back(0); } ~KDTree() { DecRef(random); for (typename AprilUtils::vector< Basics::Matrix* >::iterator it=matrix_vector.begin(); it != matrix_vector.end(); ++it) DecRef(*it); delete root; } /// Returns a matrix and a row from an index point Basics::Matrix *getMatrixAndRow(int index, int &row) { april_assert(index >= 0 && index < N); int izq,der,m; izq = 0; der = static_cast(first_index.size()); do { m = (izq+der)/2; if (first_index[m] <= index) izq = m; else der = m; } while (izq < der-1); row = index - first_index[izq]; return matrix_vector[izq]; } void pushMatrix(Basics::Matrix *m) { if (m->getNumDim() != 2) ERROR_EXIT(256, "Incorrect number of dimensions, expected bi-dimensional\n"); if (m->getDimSize(1) != D) ERROR_EXIT2(256, "Incorrect number of columns, expected %d, found %d\n", D, m->getDimSize(1)); // accumulate the number of rows in order to compute the total number of // points N += m->getDimSize(0); matrix_vector.push_back(m); IncRef(m); // first_index.push_back(N); } /// Builds the KDTree with all the pushed matrix data. Previous computation /// will be deleted if exists. void build() { delete root; PointsList *points_list = new PointsList(N); int i=0; for (size_t j=0; j *m = matrix_vector[j]; for (int row=0; rowgetDimSize(0); ++row, ++i) { april_assert(i(m, row, i); } } root = build(points_list, 0); delete points_list; } /// Method for 1-NN search, it receives a matrix with one point, and returns /// the best point index (in the order of they were pushed), the distance to /// the best, and a matrix with the best point (if needed, that is, result /// pointer != 0). int searchNN(Basics::Matrix *point_matrix, double &distance, Basics::Matrix **result) { if (root == 0) ERROR_EXIT(256, "Build method needs to be called before searching\n"); if (point_matrix->getNumDim() != 2 || point_matrix->getDimSize(0) != 1) ERROR_EXIT(256, "A bi-dimensional matrix with one row is needed\n"); if (point_matrix->getDimSize(1) != D) ERROR_EXIT2(256, "Incorrect number of columns, expected %d, found %d\n", D, point_matrix->getDimSize(1)); Point point(point_matrix, 0, -1); OneBestSearcher one_best(point,D); number_of_processed_points = 0; searchKNN(one_best, root, 0); int best_id = one_best.getOneBestIndex(); distance = one_best.getOneBestDistance(); if (result != 0) { int best_row; Basics::Matrix *best_matrix = getMatrixAndRow(best_id, best_row); int coords[2] = { best_row, 0 }; int sizes[2] = { 1, D }; *result = new Basics::Matrix(best_matrix, coords, sizes, false); } return best_id; } /// Method for K-NN search (with K>1). Tt receives a matrix with one point /// and the K value, and returns a vector of indices, a vector of distances, /// and a vector of matrices (if needed, that is, result pointer != 0). void searchKNN(int K, Basics::Matrix *point_matrix, AprilUtils::vector &indices, AprilUtils::vector &distances, AprilUtils::vector< Basics::Matrix *> *result=0) { if (root == 0) ERROR_EXIT(256, "Build method needs to be called before searching\n"); if (K == 1) { double distance; Basics::Matrix *resultM; int best_id = searchNN(point_matrix,distance,(result!=0)?(&resultM):0); indices.push_back(best_id); distances.push_back(distance); if (result) result->push_back(resultM); } else { if (point_matrix->getNumDim() != 2 || point_matrix->getDimSize(0) != 1) ERROR_EXIT(256, "A bi-dimensional matrix with one row is needed\n"); if (point_matrix->getDimSize(1) != D) ERROR_EXIT2(256, "Incorrect number of columns, expected %d, found %d\n", D, point_matrix->getDimSize(1)); Point point(point_matrix, 0, -1); KBestSearcher k_best(K,point,D); number_of_processed_points = 0; searchKNN(k_best, root, 0); k_best.getBestData(indices,distances); if (result != 0) { result->reserve(static_cast(indices.size())); for (size_t i=0; i *best_matrix = getMatrixAndRow(best_id, best_row); int coords[2] = { best_row, 0 }; int sizes[2] = { 1, D }; result->push_back(new Basics::Matrix(best_matrix, coords, sizes, false)); } } } } int getDimSize() const { return D; } int size() const { return N; } /// For debugging purposes void print() { if (root == 0) ERROR_EXIT(256, "Build method needs to be called before print\n"); print(root, 0); } int getNumProcessedPoints() const { return number_of_processed_points; } }; typedef KDTree KDTreeFloat; } #endif // KDTREE_H april-ann-0.4.1/packages/knn/kdtree/c_src/point.h000066400000000000000000000103051263004425400216110ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef KNN_POINT_H #define KNN_POINT_H #include "matrix.h" namespace KNN { /// Class which defines a sample (a point in the space) for the KNN algorithm /// and KDTree class. This class depends on a memory pointer which depends on /// a Matrix. To retain the Matrix, the KDTree class has the pointer to the /// Matrix object. template class Point { const T *base; int stride, id; public: /// Constant iterator over the point components class const_iterator { friend class Point; const T *ptr; int stride; const_iterator(const T *ptr, int stride) : ptr(ptr), stride(stride) { } public: const_iterator() : ptr(0) { } const_iterator(const const_iterator &other) : ptr(other.ptr), stride(other.stride) { } ~const_iterator() { } const_iterator &operator=(const const_iterator &other) { ptr = other->ptr; stride = other->stride; return *this; } const_iterator &operator++() { ptr+=stride; return *this; } const_iterator &operator--() { ptr-=stride; return *this; } const_iterator &operator+=(int v) { ptr+=stride*v; return *this; } const_iterator &operator-=(int v) { ptr-=stride*v; return *this; } const T &operator*() const { return *ptr; } const T *operator->() const { return ptr; } bool operator==(const const_iterator &other) const { return other.ptr == ptr; } bool operator!=(const const_iterator &other) const { return other.ptr != ptr; } bool operator<(const const_iterator &other) const { return other.ptr < ptr; } bool operator<=(const const_iterator &other) const { return other.ptr <= ptr; } bool operator>(const const_iterator &other) const { return other.ptr > ptr; } bool operator>=(const const_iterator &other) const { return other.ptr >= ptr; } }; // Point() : base(0) { } Point(const Point &other) : base(other.base), stride(other.stride), id(other.id) { } Point(const T *base, int stride, int id) : base(base), stride(stride), id(id) { } Point(const Basics::Matrix *m, int row, int id) :id(id) { april_assert(m->getNumDim() == 2); int coords[2] = { row, 0 }; base = m->getRawDataAccess()->getPPALForRead()+m->computeRawPos(coords); stride = m->getStrideSize(1); } ~Point() { } Point &operator=(const Point &other) { base = other.base; stride = other.stride; id = other.id; return *this; } bool operator==(const Point &other) const { return other.base == base; } bool operator!=(const Point &other) const { return other.base != base; } const T &operator[](int pos) const { return base[stride*pos]; } const_iterator begin() const { return const_iterator(base, stride); } const_iterator end(const int D) const { return const_iterator(base+D*stride, stride); } int getId() const { return id; } // WARNING: this function must to be redefined if the type T is not a plain // type (like a Complex number). double dist(const Point &other, const int D) const { const T *this_ptr = base; const T *other_ptr = other.base; double d = 0.0; for (int i=0; i max then best_class,max = c,counts[c] end end return best_class end function knn.kdtree.posteriorKNN(result, get_class_function) local posteriors = {} local cte local best,argbest=-math.huge,-1 local max=iterator(result):map(function(x) return -x[2] end):max() for i=1,#result do local c = get_class_function(result[i][1]) local logp = -result[i][2] - max posteriors[c] = (posteriors[c] and math.logadd(posteriors[c],logp)) or logp cte = (cte and math.logadd(cte,logp)) or logp end for i,v in pairs(posteriors) do local logp = v - cte posteriors[i] = logp if logp > best then best,argbest=logp,i end end return posteriors,argbest,best end function knn.kdtree.regressionKNN(result, get_target_function) local posteriors = {} local cte for i=1,#result do local logp = -result[i][2] posteriors[i] = logp cte = (cte and math.logadd(cte,logp)) or logp end local wrap_table = { matrix = function(a) return a end, matrixComplex = function(a) return a end, table = function(a) return matrix(#a, a) end, number = function(a) return matrix(1,{a}) end, } local wrap_func = function(a) return assert(wrap_table[type(a)](a), "Incorrect type returned by get_target_function, expected a matrix, a table or a number") end local logp = posteriors[1] - cte posteriors[1] = logp local result = wrap_func(get_target_function(result[1][1])):clone(): scal(math.exp(logp)) for i=2,#posteriors do local logp = posteriors[i] - cte posteriors[i] = logp local target = wrap_func(get_target_function(result[i][1])) result:axpy(math.exp(logp), target) end return result,posteriors end april-ann-0.4.1/packages/knn/kdtree/package.lua000066400000000000000000000022561263004425400213220ustar00rootroot00000000000000 package{ name = "knn.kdtree", version = "1.0", depends = { "util", "random", "matrix" }, keywords = { "KDTree for KNN utilities" }, description = "KDTree for KNN utilities", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test-digits.lua", }, }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_kdtree.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_kdtree.lua.cc", dest_dir = "build", } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/knn/kdtree/test/000077500000000000000000000000001263004425400201765ustar00rootroot00000000000000april-ann-0.4.1/packages/knn/kdtree/test/test-digits.lua000066400000000000000000000056711263004425400231520ustar00rootroot00000000000000local T = utest.test local check = utest.check T("KDTreeTest", function() local dir = string.get_path(arg[0]) local data = ImageIO.read(dir .. "../../../../TEST/digitos/digits.png"):to_grayscale():invert_colors():matrix() local TOP_PCA = 10 local EPSILON = 1e-05 local PCA_EPSILON = 0.024226 local KNN = 7 local DO_PCA = false local train_data = matrix(800,256) local val_data = matrix(200,256) local i=1 for sw in data:sliding_window{ size={16,16}, step={16,16}, numSteps={80,10} }:iterate() do train_data(i,':'):rewrap(16,16):copy(sw) i=i+1 end local i=1 for sw in data:sliding_window{ size={16,16}, step={16,16}, numSteps={20,10}, offset={1280,0} }:iterate() do val_data(i,':'):rewrap(16,16):copy(sw) i=i+1 end if DO_PCA then local U,S = stats.pca(train_data) train_data = stats.pca.whitening(train_data,U,S,PCA_EPSILON) -- print(stats.pca_threshold(S,0.99)) train_data = train_data(':',{1,TOP_PCA}) val_data = stats.pca.whitening(val_data,U,S,PCA_EPSILON) val_data = val_data(':',{1,TOP_PCA}) end -- local D = train_data:dim(2) local kdt = knn.kdtree(D,random(213824)) kdt:push(train_data) kdt:build() local errors=0 local errors2=0 for i=1,val_data:dim(1) do local pat = val_data(i,':') local result = kdt:searchKNN(KNN,pat) -- MAJORITY VOTE local best_class = knn.kdtree.classifyKNN(result, function(id) return (id-1)%10 end) local dist=result[1][2] -- print(i,best_class,counts[best_class]) local target_class = (i-1) % 10 -- POSTERIORS local posteriors = knn.kdtree.posteriorKNN(result, function(id) return (id-1)%10 end) local best_class2 = iterator(pairs(posteriors)):map(table.pack): reduce(function(acc,b) return (b[2]>acc[2] and { b[1], b[2] }) or acc end, { -1, -math.huge })[1] -- CLASSIFY if best_class2 ~= target_class then errors=errors+1 end -- -- iterator(ipairs(posteriors)):select(2):map(table.unpack):apply(print) -- NAIVE CLASSIFIER local naive_result = {} for j=1,train_data:dim(1) do local trainpat = train_data(j,':') local dist = (trainpat - pat):pow(2):sum() table.insert(naive_result, {j, dist}) end table.sort(naive_result, function(a,b) return a[2] < b[2] end) naive_result = table.slice(naive_result, 1, KNN) for j=1,KNN do check.number_eq(result[j][2], naive_result[j][2], nil, string.format("pattern %d knn %d", i, j)) end end -- print(100*errors/val_data:dim(1) .. "%", errors) end) april-ann-0.4.1/packages/knn/kdtree/test/test.lua000066400000000000000000000017771263004425400216740ustar00rootroot00000000000000local N = 1000000 local D = 6 local rnd = random(1234) local m1 = matrix(N,D):uniformf(-1,1,rnd) local m2 = matrix(N,D):uniformf(-1,1,rnd) -- local kdt = knn.kdtree(m1:dim(2),random(8424)) kdt:push(m1) kdt:push(m2) kdt:build() -- KDTREE SEARCH local p = matrix(1,D):uniformf(-1,1,rnd) local bestid,bestdist,best = kdt:searchNN(p) print(p) print(bestid, table.concat(kdt:get_point_matrix(bestid):toTable(), " ")) print(bestdist) print("stats:",kdt:stats()) -- KNN SEARCH local result = kdt:searchKNN(4,p) for i=1,#result do print(i, result[i][1], result[i][2], table.concat(kdt:get_point_matrix(result[i][1]):toTable(), " ")) end print("stats:",kdt:stats()) -- NAIVE LINEAR SEARCH local besti local bestd = math.huge for i=1,m1:dim(1) do local aux = m1(i,':') local d = (aux-p):pow(2):sum() if d < bestd then bestd,besti = d,i end end for i=1,m2:dim(1) do local aux = m2(i,':') local d = (aux-p):pow(2):sum() local j = m1:dim(1)+i if d < bestd then bestd,besti = d,j end end print(besti) print(bestd) april-ann-0.4.1/packages/language_model/000077500000000000000000000000001263004425400201165ustar00rootroot00000000000000april-ann-0.4.1/packages/language_model/LM_interface/000077500000000000000000000000001263004425400224465ustar00rootroot00000000000000april-ann-0.4.1/packages/language_model/LM_interface/binding/000077500000000000000000000000001263004425400240605ustar00rootroot00000000000000april-ann-0.4.1/packages/language_model/LM_interface/binding/bind_LM_interface.lua.cc000066400000000000000000000376161263004425400305100ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "bind_dataset.h" #include "bind_function_interface.h" #include "bind_LM_interface.h" #include "LM_interface.h" using namespace AprilUtils; using namespace Basics; using namespace Functions; //BIND_END //BIND_HEADER_H #include "LM_interface.h" #include "history_based_LM.h" #include "feature_based_LM.h" #include "bunch_hashed_LM.h" #include "skip_function.h" using namespace LanguageModels; using namespace LanguageModels::QueryFilters; class LuaArcsIteratorUInt32Logfloat : public Referenced { AprilUtils::SharedPtr lmi; uint32_t key; LMInterfaceUInt32LogFloat::ArcsIterator it; public: LuaArcsIteratorUInt32Logfloat(LMInterfaceUInt32LogFloat *lmi, LMInterfaceUInt32LogFloat::ArcsIterator const &it) : Referenced(), lmi(lmi), it(it) { } uint32_t get() { return *it; } void next() { ++it; } bool isEnd() { return it.isEnd(); } }; class QueryResultUInt32LogFloat : public Referenced { LMInterfaceUInt32LogFloat *lm_interface; const AprilUtils::vector &result; public: QueryResultUInt32LogFloat(LMInterfaceUInt32LogFloat *lm_interface) : lm_interface(lm_interface), result(lm_interface->getQueries()) { IncRef(lm_interface); } ~QueryResultUInt32LogFloat() { DecRef(lm_interface); } size_t size() const { return result.size(); } const LMInterfaceUInt32LogFloat::KeyScoreBurdenTuple &get(unsigned int i) const { return result[i]; } }; class GetResultUInt32LogFloat : public Referenced { AprilUtils::vector result; public: GetResultUInt32LogFloat() {} AprilUtils::vector &getVector() { return result; } size_t size() const { return result.size(); } const LMInterfaceUInt32LogFloat::KeyScoreBurdenTuple &get(unsigned int i) const { return result[i]; } void clear() { result.clear(); } }; class NextKeysResultUInt32 : public Referenced { AprilUtils::vector result; public: NextKeysResultUInt32() {} AprilUtils::vector &getVector() { return result; } size_t size() const { return result.size(); } const uint32_t &get(unsigned int i) const { return result[i]; } void clear() { result.clear(); } }; //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME LuaArcsIteratorUInt32Logfloat language_models.__arcs_iterator__ //BIND_CPP_CLASS LuaArcsIteratorUInt32Logfloat //BIND_CONSTRUCTOR LuaArcsIteratorUInt32Logfloat { LUABIND_ERROR("FORBIDDEN!!! call the corresponding method in language model"); } //BIND_END //BIND_METHOD LuaArcsIteratorUInt32Logfloat get { LUABIND_RETURN(uint, obj->get()); } //BIND_END //BIND_METHOD LuaArcsIteratorUInt32Logfloat next { obj->next(); } //BIND_END //BIND_METHOD LuaArcsIteratorUInt32Logfloat is_end { LUABIND_RETURN(bool, obj->isEnd()); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME QueryResultUInt32LogFloat language_models.__query_result__ //BIND_CPP_CLASS QueryResultUInt32LogFloat //BIND_CONSTRUCTOR QueryResultUInt32LogFloat { LUABIND_ERROR("FORBIDDEN!!! call method get_queries of a language model"); } //BIND_END //BIND_METHOD QueryResultUInt32LogFloat get { unsigned int i; LUABIND_GET_PARAMETER(1, uint, i); LMInterfaceUInt32LogFloat::KeyScoreBurdenTuple tuple = obj->get(i-1); LUABIND_RETURN(uint, tuple.key_score.key); LUABIND_RETURN(float, tuple.key_score.score.log()); LUABIND_RETURN(int, tuple.burden.id_key); LUABIND_RETURN(int, tuple.burden.id_word); } //BIND_END //BIND_METHOD QueryResultUInt32LogFloat to_table { lua_newtable(L); for (unsigned int i=0; isize(); ++i) { LMInterfaceUInt32LogFloat::KeyScoreBurdenTuple tuple = obj->get(i); lua_pushnumber(L, i+1); lua_newtable(L); // lua_pushnumber(L, 1); lua_pushuint(L, tuple.key_score.key); lua_settable(L, -3); // lua_pushnumber(L, 2); lua_pushfloat(L, tuple.key_score.score.log()); lua_settable(L, -3); // lua_pushnumber(L, 3); lua_pushint(L, tuple.burden.id_key); lua_settable(L, -3); // lua_pushnumber(L, 4); lua_pushint(L, tuple.burden.id_word); lua_settable(L, -3); // lua_settable(L, -3); } LUABIND_INCREASE_NUM_RETURNS(1); } //BIND_END //BIND_METHOD QueryResultUInt32LogFloat size { LUABIND_RETURN(uint, obj->size()); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME GetResultUInt32LogFloat language_models.__get_result__ //BIND_CPP_CLASS GetResultUInt32LogFloat //BIND_CONSTRUCTOR GetResultUInt32LogFloat { LUABIND_ERROR("FORBIDDEN!!! call method get of a language model"); } //BIND_END //BIND_METHOD GetResultUInt32LogFloat get { unsigned int i; LUABIND_GET_PARAMETER(1, uint, i); LMInterfaceUInt32LogFloat::KeyScoreBurdenTuple tuple = obj->get(i-1); LUABIND_RETURN(uint, tuple.key_score.key); LUABIND_RETURN(float, tuple.key_score.score.log()); LUABIND_RETURN(int, tuple.burden.id_key); LUABIND_RETURN(int, tuple.burden.id_word); } //BIND_END //BIND_METHOD GetResultUInt32LogFloat clear { obj->clear(); LUABIND_RETURN(GetResultUInt32LogFloat, obj); } //BIND_END //BIND_METHOD GetResultUInt32LogFloat size { LUABIND_RETURN(uint, obj->size()); } //BIND_END //BIND_METHOD GetResultUInt32LogFloat to_table { lua_newtable(L); for (unsigned int i=0; isize(); ++i) { LMInterfaceUInt32LogFloat::KeyScoreBurdenTuple tuple = obj->get(i); lua_pushnumber(L, i+1); lua_newtable(L); // lua_pushnumber(L, 1); lua_pushuint(L, tuple.key_score.key); lua_settable(L, -3); // lua_pushnumber(L, 2); lua_pushfloat(L, tuple.key_score.score.log()); lua_settable(L, -3); // lua_pushnumber(L, 3); lua_pushint(L, tuple.burden.id_key); lua_settable(L, -3); // lua_pushnumber(L, 4); lua_pushint(L, tuple.burden.id_word); lua_settable(L, -3); // lua_settable(L, -3); } LUABIND_INCREASE_NUM_RETURNS(1); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME NextKeysResultUInt32 language_models.__next_keys_result__ //BIND_CPP_CLASS NextKeysResultUInt32 //BIND_CONSTRUCTOR NextKeysResultUInt32 { LUABIND_ERROR("FORBIDDEN!!! call method get of a language model"); } //BIND_END //BIND_METHOD NextKeysResultUInt32 get { unsigned int i; LUABIND_GET_PARAMETER(1, uint, i); uint32_t key = obj->get(i-1); LUABIND_RETURN(uint, key); } //BIND_END //BIND_METHOD NextKeysResultUInt32 clear { obj->clear(); LUABIND_RETURN(NextKeysResultUInt32, obj); } //BIND_END //BIND_METHOD NextKeysResultUInt32 size { LUABIND_RETURN(uint, obj->size()); } //BIND_END //BIND_METHOD NextKeysResultUInt32 to_table { lua_newtable(L); for (unsigned int i=0; isize(); ++i) { uint32_t key = obj->get(i); lua_pushnumber(L, i+1); lua_pushuint(L, key); lua_settable(L, -3); } LUABIND_INCREASE_NUM_RETURNS(1); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME LMModelUInt32LogFloat language_models.model //BIND_CPP_CLASS LMModelUInt32LogFloat //BIND_CONSTRUCTOR LMModelUInt32LogFloat { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD LMModelUInt32LogFloat get_interface { LUABIND_RETURN(LMInterfaceUInt32LogFloat, obj->getInterface()); } //BIND_END //BIND_METHOD LMModelUInt32LogFloat is_deterministic { LUABIND_RETURN(boolean, obj->isDeterministic()); } //BIND_END //BIND_METHOD LMModelUInt32LogFloat ngram_order { LUABIND_RETURN(int, obj->ngramOrder()); } //BIND_END //BIND_METHOD LMModelUInt32LogFloat require_history_manager { LUABIND_RETURN(boolean, obj->requireHistoryManager()); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME LMInterfaceUInt32LogFloat language_models.interface //BIND_CPP_CLASS LMInterfaceUInt32LogFloat //BIND_CONSTRUCTOR LMInterfaceUInt32LogFloat { LUABIND_ERROR("Abstract class!!!"); } //BIND_END //BIND_METHOD LMInterfaceUInt32LogFloat get { uint32_t key, word; int burden_id_key=-1, burden_id_word=-1; float log_threshold; log_float threshold = log_float::zero(); GetResultUInt32LogFloat *result = 0; LUABIND_GET_PARAMETER(1, uint, key); LUABIND_GET_PARAMETER(2, uint, word); if (lua_istable(L,3)) { check_table_fields(L, 3, "threshold", "id_key", "id_word", "result", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(3, threshold, float, log_threshold, log_float::zero().log()); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(3, id_key, int, burden_id_key, -1); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(3, id_word, int, burden_id_word, -1); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(3, result, GetResultUInt32LogFloat, result, 0); threshold = log_float(log_threshold); } if (result == 0) result = new GetResultUInt32LogFloat; obj->get(key, word, LMInterfaceUInt32LogFloat::Burden(burden_id_key, burden_id_word), result->getVector(), threshold); LUABIND_RETURN(GetResultUInt32LogFloat, result); } //BIND_END //BIND_METHOD LMInterfaceUInt32LogFloat next_keys { uint32_t key, word; NextKeysResultUInt32 *result = 0; LUABIND_GET_PARAMETER(1, uint, key); LUABIND_GET_PARAMETER(2, uint, word); if (lua_istable(L,3)) { check_table_fields(L, 3, "result", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(3, result, NextKeysResultUInt32, result, 0); } if (result == 0) result = new NextKeysResultUInt32; obj->getNextKeys(key, word, result->getVector()); LUABIND_RETURN(NextKeysResultUInt32, result); } //BIND_END //BIND_METHOD LMInterfaceUInt32LogFloat clear_queries { obj->clearQueries(); LUABIND_RETURN(LMInterfaceUInt32LogFloat, obj); } //BIND_END //BIND_METHOD LMInterfaceUInt32LogFloat insert_query { uint32_t key, word; float log_threshold; log_float threshold = log_float::zero(); int burden_id_key=-1, burden_id_word=-1; LUABIND_GET_PARAMETER(1, uint, key); LUABIND_GET_PARAMETER(2, uint, word); if (lua_istable(L,3)) { check_table_fields(L, 3, "threshold", "id_key", "id_word", (const char *)0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(3, threshold, float, log_threshold, log_float::zero().log()); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(3, id_key, int, burden_id_key, -1); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(3, id_word, int, burden_id_word, -1); threshold = log_float(log_threshold); } obj->insertQuery(key, word, LMInterfaceUInt32LogFloat::Burden(burden_id_key, burden_id_word), threshold); LUABIND_RETURN(LMInterfaceUInt32LogFloat, obj); } //BIND_END //BIND_METHOD LMInterfaceUInt32LogFloat get_queries { QueryResultUInt32LogFloat *result = new QueryResultUInt32LogFloat(obj); LUABIND_RETURN(QueryResultUInt32LogFloat, result); } //BIND_END //BIND_METHOD LMInterfaceUInt32LogFloat get_initial_key { uint32_t key = obj->getInitialKey(); LUABIND_RETURN(uint, key); } //BIND_END //BIND_METHOD LMInterfaceUInt32LogFloat get_final_score { LUABIND_CHECK_ARGN(>=, 1); LUABIND_CHECK_ARGN(<=, 2); uint32_t key; LUABIND_GET_PARAMETER(1, uint, key); float log_threshold; LUABIND_GET_OPTIONAL_PARAMETER(2, float, log_threshold, log_float::zero().log()); log_float threshold = log_float(log_threshold); LUABIND_RETURN(float, obj->getFinalScore(key, threshold).log()); } //BIND_END //BIND_METHOD LMInterfaceUInt32LogFloat get_zero_key { uint32_t key; if (!obj->getZeroKey(key)) LUABIND_ERROR("Impossible to get zero key"); LUABIND_RETURN(uint, key); } //BIND_END //BIND_METHOD LMInterfaceUInt32LogFloat get_best_prob { uint32_t key; log_float score; if (lua_isnil(L,1)) { score = obj->getBestProb(); } else { LUABIND_GET_PARAMETER(1, uint, key); score = obj->getBestProb(key); } LUABIND_RETURN(float, score.log()); } //BIND_END ////////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME HistoryBasedLMUInt32LogFloat language_models.history_based_model //BIND_CPP_CLASS HistoryBasedLMUInt32LogFloat //BIND_SUBCLASS_OF HistoryBasedLMUInt32LogFloat LMModelUInt32LogFloat //BIND_CONSTRUCTOR HistoryBasedLMUInt32LogFloat { LUABIND_ERROR("Abstract class!!!"); } //BIND_END ////////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME HistoryBasedLMInterfaceUInt32LogFloat language_models.history_based_interface //BIND_CPP_CLASS HistoryBasedLMInterfaceUInt32LogFloat //BIND_SUBCLASS_OF HistoryBasedLMInterfaceUInt32LogFloat LMInterfaceUInt32LogFloat //BIND_CONSTRUCTOR HistoryBasedLMInterfaceUInt32LogFloat { LUABIND_ERROR("Abstract class!!!"); } //BIND_END ////////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME BunchHashedLMUInt32LogFloat language_models.bunch_hashed_model //BIND_CPP_CLASS BunchHashedLMUInt32LogFloat //BIND_SUBCLASS_OF BunchHashedLMUInt32LogFloat LMModelUInt32LogFloat //BIND_CONSTRUCTOR BunchHashedLMUInt32LogFloat { LUABIND_ERROR("Abstract class!!!"); } //BIND_END ////////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME BunchHashedLMInterfaceUInt32LogFloat language_models.bunch_hashed_interface //BIND_CPP_CLASS BunchHashedLMInterfaceUInt32LogFloat //BIND_SUBCLASS_OF BunchHashedLMInterfaceUInt32LogFloat LMInterfaceUInt32LogFloat //BIND_CONSTRUCTOR BunchHashedLMInterfaceUInt32LogFloat { LUABIND_ERROR("Abstract class!!!"); } //BIND_END ////////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME FeatureBasedLMUInt32LogFloat language_models.feature_based_model //BIND_CPP_CLASS FeatureBasedLMUInt32LogFloat //BIND_SUBCLASS_OF FeatureBasedLMUInt32LogFloat LMModelUInt32LogFloat //BIND_CONSTRUCTOR FeatureBasedLMUInt32LogFloat { LUABIND_ERROR("Abstract class!!!"); } //BIND_END ////////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME FeatureBasedLMInterfaceUInt32LogFloat language_models.feature_based_interface //BIND_CPP_CLASS FeatureBasedLMInterfaceUInt32LogFloat //BIND_SUBCLASS_OF FeatureBasedLMInterfaceUInt32LogFloat LMInterfaceUInt32LogFloat //BIND_CONSTRUCTOR FeatureBasedLMInterfaceUInt32LogFloat { LUABIND_ERROR("Abstract class!!!"); } //BIND_END ////////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME FunctionInterface functions //BIND_LUACLASSNAME DiceSkipFunction functions.dice_skip //BIND_CPP_CLASS DiceSkipFunction //BIND_SUBCLASS_OF DiceSkipFunction FunctionInterface //BIND_CONSTRUCTOR DiceSkipFunction { LUABIND_CHECK_ARGN(==,1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "dice", "random", "mask_value"); Dice *dice; MTRand *random; uint32_t mask_value; LUABIND_GET_TABLE_PARAMETER(1, dice, Dice, dice); LUABIND_GET_TABLE_PARAMETER(1, random, MTRand, random); LUABIND_GET_TABLE_PARAMETER(1, mask_value, uint, mask_value); obj = new DiceSkipFunction(dice, random, mask_value); LUABIND_RETURN(DiceSkipFunction, obj); } //BIND_END april-ann-0.4.1/packages/language_model/LM_interface/c_src/000077500000000000000000000000001263004425400235375ustar00rootroot00000000000000april-ann-0.4.1/packages/language_model/LM_interface/c_src/LM_interface.cc000066400000000000000000000020401263004425400263720ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "LM_interface.h" namespace LanguageModels { template<> class LMInterface; template<> class LMModel; } april-ann-0.4.1/packages/language_model/LM_interface/c_src/LM_interface.h000066400000000000000000000443771263004425400262570ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LANGUAGE_MODEL_INTERFACE_H #define LANGUAGE_MODEL_INTERFACE_H #include #include "logbase.h" #include "referenced.h" #include "smart_ptr.h" #include "unused_variable.h" #include "vector.h" namespace LanguageModels { /** * @brief The standard WordType is an unsigned integer of 32 bits. * * @note 4G words are possible to be represented. */ typedef uint32_t WordType; // forward declaration class LMHistoryManager; // Score is usually log_float // Key is usually uint32_t template class LMModel; // forward declaration /** * @brief LMInterface is the non-thread-safe warpper around a LMModel. * * The LMModel contains the 'static' (and usually thread-safe) data (e.g. the * actual automata, the MLPs of a NNLM, etc.) where as the LMInterface usually * contains other data structures to perform the actual computation of LM * queries. * * Two modes are available to query the language models: * * - One-by-one: get() based methods query the language model and store its * result into an AprilUtils::vector. * * - Bunch-mode: insertQuery(), getQueries(), clearQueries() methods allow to * list a bunch of queries into a temporary data structure using * insertQuery() method, the language model computes its output in the * getQueries() method, and finally the clearQueries() method allows to * reset the temporary list of queries. This mode uses the LMInterface * instance to store the state of the computation. * * @note Language models can be deterministic or not, therefore, this * interface methods produce lists of (key,score) pairs with @c size()>=0. * * @note In history based LMs this class contains a history manager, usually a * AprilUtils::TrieVector instance. * * @note Score is usually AprilUtils::log_float. * * @note Key is usually WordType (uint32_t). */ template class LMInterface : public Referenced { /// The LMModel is a friend class because LMInterface constructor is /// protected, and it is forced to be called from LMModel::getInterface() /// method. friend class LMModel; public: /// This is a tuple with a LM Ley and an associated Score. struct KeyScoreTuple { Key key; Score score; KeyScoreTuple() {} KeyScoreTuple(Key k, Score s) : key(k), score(s) {} }; /// This is the burden ignored by the LM but needed by our decoders. struct Burden { int32_t id_key; ///< Usually a number related with the context. int32_t id_word; ///< Usually a number related with the next word. Burden() {} Burden(int32_t id_key, int32_t id_word) : id_key(id_key), id_word(id_word) {} Burden(const Burden &other) : id_key(other.id_key), id_word(other.id_word) { } }; /** * @brief This struct is the result of a LM query. * * This struct is the result produced by the LM query, a pair of * (Key,S), which is the next LM Key and its associated S, and the * Burden struct, which currently contains two identifiers. */ struct KeyScoreBurdenTuple { KeyScoreTuple key_score; ///< The (Key,Score) pair. Burden burden; ///< The Burden related with this pair. KeyScoreBurdenTuple() {} KeyScoreBurdenTuple(Key k, Score s, Burden burden) : key_score(k,s), burden(burden) {} }; /// This struct is used for the insertQueries() method which receives several /// words together. struct WordIdScoreTuple { WordType word; int32_t id_word; ///< A half part of the Burden (see insertQueries()). Score score; WordIdScoreTuple() {} WordIdScoreTuple(WordType w, int32_t idw, Score s) : word(w), id_word(idw), score(s) {} }; /** * @brief Arcs iterator in a language model. * * Language models can different kinds of iterators for traverse different * arc kinds. For instance, in ngram models, once can traverse all arcs * outgoing from a given state ignoring backoff transitions. On the other * hand, once can traverse only backoff transitions, ignoring non-backoff * transitions. Language models implement different methods in final * classes, allowing to traverse the desired kind of arcs. The iterators are * generic, allowing to export them in the same way into Lua. An abstract * class, ArcsIterator::StateControl, is used to declare the interface * between the iterator and the language model. Derived classes from * LMInterface are required to implement properly the StateControl class. */ class ArcsIterator { public: /** * @brief This class implements the basic API needed for traverse * languages models using ArcsIterator class. * * @note The API receives a LMInterface pointer in methods which needs * to access LM data structures. So, minimum state is required in this * class, just to represent a position in the language model. The caller * is responsible to perform the call with the proper LM pointer. */ class StateControl { friend class ArcsIterator; public: virtual ~StateControl() {} private: /** * @brief This method traverses until next arc which is above threshold * * @note This method will update the state with end iterator state * when necessary. */ virtual void moveToNext(LMInterface *lm, Score threshold) = 0; /** * @brief This method returns a word * * @note If this method is called when state is end, the returned * value is undefined. */ virtual WordType getWord(LMInterface *lm) = 0; /// Compares two StateControl objects. virtual bool equals(const StateControl *other) const = 0; /// Copies other into this. virtual void copy(const StateControl *other) = 0; /// Returns a deep copy of this. virtual StateControl *clone() const = 0; /// Indicates if we achieved the end. virtual bool isEnd(LMInterface *lm) const = 0; }; private: LMInterface *lm; Score threshold; AprilUtils::UniquePtr state; public: ArcsIterator() {} ArcsIterator(ArcsIterator const &other) : lm(other.lm), threshold(other.threshold), state(other.state->clone()) {} ArcsIterator(LMInterface *lm, Score th, AprilUtils::UniquePtr state) : lm(lm), threshold(th), state(state) {} virtual bool operator!=(const ArcsIterator &other) const { return (*this) != other; } virtual bool operator==(const ArcsIterator &other) const { return ( this->lm==other.lm && this->threshold==other.threshold && state->equals(other.state.get()) ); } virtual ArcsIterator &operator=(ArcsIterator const &other) { lm = other.lm; threshold = other.threshold; state->copy(other.state.get()); return *this; } virtual ArcsIterator &operator++() { state->moveToNext(lm, threshold); return *this; } virtual WordType operator*() { return state->getWord(lm); } virtual bool isEnd() const { return state->isEnd(lm); } }; protected: /// Auxiliary result vector. AprilUtils::vector result; /// The model reference. LMModel* model; /// The protected constructor, only callable from LMModel::getInterface() /// method. LMInterface(LMModel* model) : model(model) { IncRef(model); } public: /// Destructor. virtual ~LMInterface() { DecRef(model); } /// Retrieves the LMModel where this LMInterface was obtained. virtual LMModel* getLMModel() { return model; } // /** // * @brief Returns an ArcsIterator for basic arcs outgoing from key state. // * // * This method returns an iterator to the first transition with probability // * above the given threshold. // * // * @see ArcsIterator class // */ // virtual ArcsIterator beginArcs(Key key, Score threshold) = 0; // /** // * @brief Returns an end ArcsIterator for basic arcs outgoing from key state. // * // * This method returns the first invalid iterator related with the given // * key. // * // * @see ArcsIterator class // */ // virtual ArcsIterator endArcs(Key key) = 0; // -------------- individual LM queries ------------- // get is the most basic LM query method, receives the Key and the Word, // returns 0,1 or several results by pushing back to the vector result (the // vector is not cleared, and it is not needed to be cleared as // pre-condition) /** * @brief Queries the model with a (Key,WordType,Burden) tuple. * * This method returns all the (Key,WordType) pairs of a transition in the * LMModel by using the state @c key with the given @c word * instance. Additionally a @c threshold is given to perform beam pruning. * * @param key - The context or state from where the transition starts. * * @param word - The transition word. * * @param[in,out] result - An AprilUtils::vector with all the destination * states. * * @param threshold - The threshold for the beam pruning. * * @note The result vector is not cleared, so all the resulting states will * be appended using AprilUtils::vector::push_back() method. */ virtual void get(Key key, WordType word, Burden burden, AprilUtils::vector &result, Score threshold) = 0; /** * @brief Computes only the next keys given a pair (Key,WordType). * * @note Its default implementation uses get() method and discarding Burden * and Score * * @note The result vector is not cleared, so all the resulting states will * be appended using AprilUtils::vector::push_back() method. * * @param key - The context or state from where the transition starts. * * @param[in,out] result - An AprilUtils::vector of Key's. */ virtual void getNextKeys(Key key, WordType word, AprilUtils::vector &result) { AprilUtils::vector aux_result; get(key, word, Burden(-1,-1), aux_result, Score::zero()); for (typename AprilUtils::vector::iterator it = aux_result.begin(); it != aux_result.end(); ++it) result.push_back(it->key_score.key); } // -------------- BUNCH MODE ------------- // Note: we can freely mix insertQuery and insertQueries, but // individual queries (gets) and bunch mode queries should not be // mixed. /** * @brief Removes the list of pending queries. * * @note This must be the first operation to be executed before inserting * multiple queries by calling insertQuery() method. * * @see Methods insertQuery() and getQueries(). */ virtual void clearQueries() { result.clear(); } /** * @brief Call this method for each individual query. * * @param key - The context or state from where the transition starts. * * @param word - The transition word. * * @param burden - The related burden with the current query. * * @param threshold - A threshold to be use for beam pruning. * * @note The default implementation uses the get() method within a for loop. */ virtual void insertQuery(Key key, WordType word, Burden burden, Score threshold) { get(key,word,burden,result,threshold); } /** * @brief A specialization of insertQuery() method for multiple transition * words. * * @param key - The context or state from where the transition starts. * * @param id_key - A half part of the Burden. * * @param words - An AprilUtils::vector of WordIdScoreTuple. * * @param is_sorted - Indicates if the words vector is sorted by word. * * @note The Burden is computed by the pair (id_key,id_word), where id_key * is the given parameter and id_word is different for each word in the * given words vector. * * @note The default implementation uses the insertQuery() method within a * for loop. */ virtual void insertQueries(Key key, int32_t id_key, AprilUtils::vector words, bool is_sorted=false) { UNUSED_VARIABLE(is_sorted); // default behavior for (typename AprilUtils::vector::iterator it = words.begin(); it != words.end(); ++it) insertQuery(key, it->word, Burden(id_key, it->id_word), it->score); } /** * @brief This method may perform the computation of language model queries. * * Some LM implementations can benefit of bunch mode (for instance, NNLMs * may profit this feature for grouping all queries associated to the same * Key, and can perform several forward steps in bunch or mini-batch * mode). Other LMs such as those based on automata (e.g. NgramLiraModel) * may perform the LM queries in the insert method so that here they only * have to return the result vector. * * @return An AprilUtils::vector of KeyScoreBurdenTuple with the language * model computation result for all the queries inserted with insertQuery() * or insertQueries() from the last call to clearQueries(). */ virtual const AprilUtils::vector &getQueries() { return result; } /// An upper bound on the best transition probability, usually pre-computed /// in the model. virtual Score getBestProb() const = 0; /// An upper bound on the best transition probability departing from key, /// usually pre-computed in the model. virtual Score getBestProb(Key k) = 0; /// Initial key is the initial state (initial context cue). virtual Key getInitialKey() = 0; /** * @brief Returns the Key corresponding to the zero key concept. * * The zero key is a special identifier used to represent that the lowest * possible level in the automata. In a N-gram language model it is the * 0-gram key, so the following transition is a unigram. * * @param[out] k - The zero key, only valid if the method returns @c true. * * @return A bool indicating if the model contains or not a zero key * identifier. * * @note This method returns false and does nothing on LMs without zero key, * in this case, the @c k parameter is not assigned. */ virtual bool getZeroKey(Key &k) const { UNUSED_VARIABLE(k); // default behavior return false; } /** * @brief Returns the score associated to the probability of being a * final state. * * @param k - The key of the current state. * * @param threshold - For beam prunning. * * @return A Score with the probability of @c k being a final state. * * @note This method is not const since it may depend on get which is not * const either. */ virtual Score getFinalScore(Key k, Score threshold) = 0; }; /** * @brief The LMModel is the thread-safe part of the LM. * * This class is where the model data is stored, it is thread-safe and * therefore can be shared between multiples threads. * * @note Score is usually a AprilUtils::log_float. * * @note Key is usually a WordType (uint32_t). */ template class LMModel : public Referenced { public: /// Constructor LMModel() : Referenced() {} /// Destructor virtual ~LMModel() {} /** * @brief Indicates if the model is deterministic or not. * * @note the default implementation is return false. */ virtual bool isDeterministic() const { // default behavior return false; } /** * @brief Indicates the order of the N-gram. * * @note By default it returns @c -1 indicating that the model is not an * N-gram model. */ virtual int ngramOrder() const { // default behavior return -1; } /** * @brief Indicates if the model requires a history manager. * * @note By default it is return true */ virtual bool requireHistoryManager() const { // default behavior return true; } /** * @brief Returns an instance of the interface with the model. * * All derived classes must implement this getInterface() method which must * return the proper instance of a LMInterface derived class corresponding * with a proper LMModel. Every thread which needs to query the language * model needs to get an interface using this method. */ virtual LMInterface* getInterface() = 0; }; typedef LMInterface LMInterfaceUInt32LogFloat; typedef LMModel LMModelUInt32LogFloat; }; // closes namespace #endif // LANGUAGE_MODEL_INTERFACE_H april-ann-0.4.1/packages/language_model/LM_interface/c_src/bunch_hashed_LM.cc000066400000000000000000000020641263004425400270530ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "bunch_hashed_LM.h" namespace LanguageModels { template<> class BunchHashedLMInterface; template<> class BunchHashedLM; } april-ann-0.4.1/packages/language_model/LM_interface/c_src/bunch_hashed_LM.h000066400000000000000000000124621263004425400267200ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef BUNCH_HASHED_LM_H #define BUNCH_HASHED_LM_H #include #include "hash_table.h" #include "LM_interface.h" #include "logbase.h" #include "open_addressing_hash_with_fast_iterator.h" #include "unused_variable.h" #include "vector.h" namespace LanguageModels { template class BunchHashedLM; /// BunchHashedLMInterface documentation ... template class BunchHashedLMInterface : public LMInterface { friend class BunchHashedLM; protected: BunchHashedLMInterface(BunchHashedLM* model) : LMInterface(model) { } typedef typename LMInterface::KeyScoreTuple KeyScoreTuple; typedef typename LMInterface::KeyScoreBurdenTuple KeyScoreBurdenTuple; typedef typename LMInterface::Burden Burden; public: struct KeyScoreMultipleBurdenTuple { KeyScoreTuple key_score; AprilUtils::vector burden_vector; KeyScoreMultipleBurdenTuple() {} }; virtual ~BunchHashedLMInterface() { } protected: typedef AprilUtils::hash WordResultHash; typedef AprilUtils::open_addr_hash_fast_it KeyWordHash; virtual void computeKeysAndScores(KeyWordHash &ctxt_hash, unsigned int bunch_size) = 0; private: KeyWordHash context_key_hash; public: virtual void clearQueries() { LMInterface::clearQueries(); context_key_hash.clear(); } virtual void insertQuery(Key key, WordType word, Burden burden, Score threshold) { UNUSED_VARIABLE(threshold); WordResultHash &ctxt = context_key_hash[key]; KeyScoreMultipleBurdenTuple &ctxt_word = ctxt[word]; ctxt_word.burden_vector.push_back(burden); } virtual const AprilUtils::vector &getQueries() { BunchHashedLM *mdl; mdl = static_cast*>(this->model); // compute keys and scores for queries in the hash table computeKeysAndScores(context_key_hash, mdl->getBunchSize()); // For each context key entry for (typename KeyWordHash::const_iterator it = context_key_hash.begin(); it != context_key_hash.end(); ++it) { // Key context_key = it->first; const WordResultHash &word_hash = it->second; // For each word entry for (typename WordResultHash::const_iterator it2 = word_hash.begin(); it2 != word_hash.end(); ++it2) { // WordType word = it2->first; const KeyScoreMultipleBurdenTuple &result_tuple = it2->second; // For each burden at burden vector for (unsigned int i = 0; i < result_tuple.burden_vector.size(); ++i) { KeyScoreBurdenTuple new_tuple; new_tuple.key_score.key = result_tuple.key_score.key; new_tuple.key_score.score = result_tuple.key_score.score; new_tuple.burden = result_tuple.burden_vector[i]; this->result.push_back(new_tuple); } } } return this->result; } /* virtual void get(Key key, WordType word, Burden burden, vector &result, Score threshold) = 0; */ // virtual void getNextKeys(Key key, WordType word, vector &result) = 0; // virtual bool getZeroKey(Key &k) const; // virtual Key getInitialKey(); }; template class BunchHashedLM : public LMModel { private: int ngram_order; unsigned int bunch_size; public: BunchHashedLM(int ngram_order, unsigned int bunch_size) : LMModel(), ngram_order(ngram_order), bunch_size(bunch_size) { } virtual ~BunchHashedLM() { } virtual bool isDeterministic() const { return true; } virtual bool requireHistoryManager() const { return false; } unsigned int getBunchSize() { return bunch_size; } void setBunchSize(unsigned int bunch_size) { this->bunch_size = bunch_size; } }; typedef BunchHashedLMInterface BunchHashedLMInterfaceUInt32LogFloat; typedef BunchHashedLM BunchHashedLMUInt32LogFloat; }; // closes namespace #endif // BUNCH_HASHED_LM_H april-ann-0.4.1/packages/language_model/LM_interface/c_src/feature_based_LM.cc000066400000000000000000000020671263004425400272340ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "feature_based_LM.h" namespace LanguageModels { template<> class FeatureBasedLMInterface; template<> class FeatureBasedLM; } april-ann-0.4.1/packages/language_model/LM_interface/c_src/feature_based_LM.h000066400000000000000000000302711263004425400270740ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef FEATURE_BASED_LM_H #define FEATURE_BASED_LM_H #include #include "april_assert.h" #include "bunch_hashed_LM.h" #include "error_print.h" #include "function_interface.h" #include "history_based_LM.h" #include "identity_function.h" #include "logbase.h" #include "smart_ptr.h" #include "token_vector.h" #include "trie_vector.h" #include "unused_variable.h" #include "vector.h" namespace LanguageModels { template class FeatureBasedLM; /** * @brief Interface part of FeatureBasedLM class. * @see FeatureBasedLM for more documentation. */ template class FeatureBasedLMInterface : public HistoryBasedLMInterface , public BunchHashedLMInterface { friend class FeatureBasedLM; AprilUtils::SharedPtr query_filter; AprilUtils::SharedPtr bunch_filter; protected: FeatureBasedLMInterface(FeatureBasedLM* model) : HistoryBasedLMInterface(model), BunchHashedLMInterface(model), query_filter(model->getQueryFilter()), bunch_filter(model->getBunchFilter()) { } typedef typename BunchHashedLMInterface::KeyWordHash KeyWordHash; typedef typename BunchHashedLMInterface::WordResultHash WordResultHash; typedef typename BunchHashedLMInterface::KeyScoreMultipleBurdenTuple KeyScoreMultipleBurdenTuple; /** * @brief Computes the scores for all the given queries. * * The @c queries_bunch_token is an instance of Basics::TokenBunchVector * which contains several instances of Basics::TokenBunchVector, as many * as size of the bunch. Every instance has two components: * 1. A Basics::TokenVectorUint32 for the context words. * 2. A Basics::TokenVectorUint32 for the next words. All the words in * this vector share the previous context words. * * @param queries_bunch_token - An input Token with all the queries. * @param[out] scores - A vector where computes scores will be stored. * * @note The @c scores vector is only updated by calling to * AprilUtils::vector::push_back() method, allowing to chain multiple calls * into the same @c scores vector. */ virtual void executeQueries(Basics::Token *queries_bunch_token, AprilUtils::vector &scores) = 0; /** * @brief Generates the input expected by executeQueries() method. */ virtual void computeKeysAndScores(KeyWordHash &ctxt_hash, unsigned int bunch_size) { april_assert(sizeof(WordType) == sizeof(uint32_t)); const int order = getLMModel()->ngramOrder(); april_assert(order != -1); AprilUtils::SharedPtr queries_bunch_token( new Basics::TokenBunchVector() ); AprilUtils::vector scores; // For each context key entry for (typename KeyWordHash::iterator it = ctxt_hash.begin(); it != ctxt_hash.end(); ++it) { Key context_key = it->first; WordResultHash &word_hash = it->second; // offset init'd to 0 unsigned int offset = 0; // The procedure needs to create a token where context words will be // stored. This token has a vector container which needs to resized // before call to getContextProperties(). AprilUtils::SharedPtr context_words_token( new Basics::TokenVectorUint32() ); AprilUtils::vector &context_words_vector = context_words_token->getContainer(); context_words_vector.resize( order - 1 ); // the next pointer will be given to getContextProperties() as output WordType *context_words = context_words_vector.begin(); const unsigned int context_size = this->getContextProperties(context_key, context_words, offset); AprilUtils::SharedPtr next_words_token( new Basics::TokenVectorUint32() ); // For each word entry for (typename WordResultHash::iterator it2 = word_hash.begin(); it2 != word_hash.end(); ++it2) { WordType word = it2->first; KeyScoreMultipleBurdenTuple &result_tuple = it2->second; // First pass we get the next key // collect context and word tokens result_tuple.key_score.key = this->getDestinationKey(context_words, offset, context_size, word); next_words_token->push_back(word); } // Put together context and next word tokens AprilUtils::SharedPtr query_token( new Basics::TokenBunchVector() ); query_token->getContainer().reserve(2); // 2 items query_token->push_back(context_words_token.get()); // [0] query_token->push_back(next_words_token.get()); // [1] // Apply query filter AprilUtils::SharedPtr filtered_query_token; filtered_query_token = query_filter->calculate(query_token.get()); // Put the current query into the bunch of queries queries_bunch_token->push_back(filtered_query_token.get()); // If we have a full bunch, process it if (query_token->size() % bunch_size == 0) { // Apply bunch filter AprilUtils::SharedPtr filtered_queries_bunch_token( bunch_filter->calculate(queries_bunch_token.get()) ); executeQueries(filtered_queries_bunch_token.get(), scores); queries_bunch_token->clear(); } } // If there is something left in the bunch, process it if (queries_bunch_token->size() > 0) { // Apply bunch filter AprilUtils::SharedPtr filtered_queries_bunch_token( bunch_filter->calculate(queries_bunch_token.get()) ); executeQueries(filtered_queries_bunch_token.get(), scores); queries_bunch_token->clear(); } // FIXME: find a way to store scores into hash table during the first pass // Second pass to store scores at table unsigned int k = 0; for (typename KeyWordHash::iterator it = ctxt_hash.begin(); it != ctxt_hash.end(); ++it) { Key context_key = it->first; WordResultHash &word_hash = it->second; for (typename WordResultHash::iterator it2 = word_hash.begin(); it2 != word_hash.end(); ++it2) { KeyScoreMultipleBurdenTuple &result_tuple = it2->second; result_tuple.key_score.score = scores[k++]; } } } public: virtual ~FeatureBasedLMInterface() { } void incRef() { HistoryBasedLMInterface::incRef(); //BunchHashedLMInterface::incRef(); } bool decRef() { HistoryBasedLMInterface::decRef(); //BunchHashedLMInterface::decRef(); return (HistoryBasedLMInterface::getRef() <= 0); } Basics::Token* applyQueryFilter(Basics::Token* token) { return query_filter->calculate(token); } Basics::Token* applyBunchFilter(Basics::Token* token) { return query_filter->calculate(token); } virtual LMModel* getLMModel() { return HistoryBasedLMInterface::model; } }; /** * @brief A LM base class for LMs which depend on a history of words (like * Ngrams) and can work in bunch mode. * * A FeatureBasedLM depends into two function filter instances, both * derived from Functions::FunctionInterface class. The corresponding interface * class is FeatureBasedLMInterface and it is ready to work with a bunch * of queries. Every bunch is traversed and filtered in order to extract * new features from the initial word identifiers. Two different kind of * filters has been defined: * 1. QueryFilters receive a query formed by a context words sequence * (\f$h\f$) and a list of next words (\f$w_1 w_2 \ldots\f$). This query * summarizes the computation of \f$p(w1|h), p(w2|h), \ldots\f$. * 2. BunchFilters receive a bunch of queries like such above. * The filters can modify the given information in many different ways, * allowing to produce Ngram Skips, ShortLists, FactoreBased approaches, among * others. * * @see FeatureBasedLM::query_filter and FeatureBasedLM::bunch_filter * properties for more documentation. */ template class FeatureBasedLM : public HistoryBasedLM , public BunchHashedLM { private: /** * @brief A function which will be used to filter every LM query. * * The @c query_filter expects an instance of Basics::TokenBunchVector * which contains two components: * 1. A Basics::TokenVectorUint32 for the context words. * 2. A Basics::TokenVectorUint32 for the next words. All the words in * this vector share the previous context words. * The query_filter can modify any of both components **in-place** or return * a new allocated Basics::TokenBunchVector instance. */ AprilUtils::SharedPtr query_filter; /** * @brief A function which will be used to filter a bunch of LM queries. * * @see LanguageModels::FeatureBasedLMInterface::executeQueries() method * for documentation about the expected input token format. */ AprilUtils::SharedPtr bunch_filter; public: FeatureBasedLM(int ngram_order, WordType init_word, AprilUtils::TrieVector *trie_vector, unsigned int bunch_size, Functions::FunctionInterface *query_filter, Functions::FunctionInterface *bunch_filter=0) : HistoryBasedLM(ngram_order, init_word, trie_vector), BunchHashedLM(bunch_size), query_filter(query_filter), bunch_filter(bunch_filter) { if (this->bunch_filter.empty()) { bunch_filter = new Functions::IdentityFunction(); } april_assert(!this->query_filter.empty()); april_assert(!this->bunch_filter.empty()); } virtual ~FeatureBasedLM() { } Functions::FunctionInterface* getQueryFilter() { return query_filter.get(); } Functions::FunctionInterface* getBunchFilter() { return bunch_filter.get(); } virtual void incRef() { HistoryBasedLM::incRef(); //BunchHashedLM::incRef(); } virtual bool decRef() { HistoryBasedLM::decRef(); //BunchHashedLM::decRef(); return (HistoryBasedLM::getRef() <= 0); } }; typedef FeatureBasedLMInterface FeatureBasedLMInterfaceUInt32LogFloat; typedef FeatureBasedLM FeatureBasedLMUInt32LogFloat; }; // closes namespace #endif // FEATURE_BASED_LM_H april-ann-0.4.1/packages/language_model/LM_interface/c_src/history_based_LM.cc000066400000000000000000000020671263004425400273020ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "history_based_LM.h" namespace LanguageModels { template<> class HistoryBasedLMInterface; template<> class HistoryBasedLM; } april-ann-0.4.1/packages/language_model/LM_interface/c_src/history_based_LM.h000066400000000000000000000244341263004425400271460ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef HISTORY_BASED_LM_H #define HISTORY_BASED_LM_H #include #include "april_assert.h" #include "error_print.h" #include "LM_interface.h" #include "logbase.h" #include "trie_vector.h" #include "unused_variable.h" #include "vector.h" namespace LanguageModels { template class HistoryBasedLM; /// HistoryBasedLMInterface documentation ... template class HistoryBasedLMInterface : public LMInterface { friend class HistoryBasedLM; AprilUtils::TrieVector *trie; WordType *context_words; protected: /** * Looks for the context_words related with the given key of the trie. * @param key - A value indicating a TrieVector state. * @param[out] context_words - An array of WordType with size ngramOrder()-1. * @param[out] offset - The first valid position in context_words. * * @return The valid size of context_words = ngramOrder() - 1 - offset. */ unsigned int getContextProperties(Key key, WordType *context_words, unsigned int &offset) { // Go backward to get context size and context words. Context words must // be collected from current key, which shifts context to the left unsigned int pos = this->model->ngramOrder() - 1; while (key != trie->rootNode() && pos > 0) { context_words[pos-1] = trie->getWord(key); key = trie->getParent(key); --pos; } if (key != trie->rootNode()) ERROR_EXIT(256, "Overflow filling context words from current key\n"); // return offset in context_words offset = pos; // compute context_size from position in context_words return (this->model->ngramOrder() - 1 - pos); } /** * Traverses the trie from its root using the given context_words + next * word and returns the destination trie state. The first valid position and * the valid size of context_words are given as parameters. If offset==0 * then the left-most word in context_words will be swiped out. Otherwise * all the valid context_size words will be used. In any case, the last * transition is done with the given next word. * * @param context_words - An array of WordType with ngramOrder()-1 size. * @param offset - The first valid position in context_words. * @param context_size - The valid size = ngramOrder() - 1 - offset. * @param next_word - The next word. * * @return The trie destination state. */ Key getDestinationKey(const WordType *context_words, const unsigned int offset, const unsigned int context_size, const WordType next_word) { // in case the offset==0 (context_size == order-1), we need to swipe out // one word int begin = (offset == 0) ? 1 : offset, end = offset + context_size; // Destination key is obtained traversing context_words from begin to // end-1 Key dest_key = trie->rootNode(); for (int i = begin; i < end; ++i) dest_key = trie->getChild(dest_key, context_words[i]); // last transition uses the given next_word dest_key = trie->getChild(dest_key, next_word); return dest_key; } HistoryBasedLMInterface(HistoryBasedLM* model) : LMInterface(model) { trie = model->getTrieVector(); IncRef(trie); // we put one more word to allow storing next word at end of this array context_words = new WordType[model->ngramOrder()]; } /// returns true in case the probability could be computed virtual bool privateGet(Key key, WordType word, const WordType *context_words, unsigned int context_size, Score threshold, Score &score) = 0; /// returns true in case the probability could be computed virtual bool privateGetFinalScore(Key key, const WordType *context_words, unsigned int context_size, Score threshold, Score &score) = 0; /// returns true in case the probability could be computed virtual bool privateBestProb(Key key, const WordType *context_words, unsigned int context_size, Score &score) = 0; /// Returns the best probability of the model. virtual Score privateBestProb() const = 0; typedef typename LMInterface::KeyScoreBurdenTuple KeyScoreBurdenTuple; typedef typename LMInterface::Burden Burden; public: virtual ~HistoryBasedLMInterface() { DecRef(trie); delete[] context_words; } virtual void get(Key key, WordType word, Burden burden, AprilUtils::vector &result, Score threshold) { unsigned int offset; const unsigned int context_size = getContextProperties(key, context_words, offset); // Compute score with the retrieved context. In case of success, return // them using the result vector. Else, do nothing. Score score; if (privateGet(key, word, context_words + offset, context_size, threshold, score)) { // Destination key is obtained traversing the trie Key dest_key = getDestinationKey(context_words, offset, context_size, word); // Append to the result vector result.push_back(KeyScoreBurdenTuple(dest_key, score, burden)); } } virtual void getNextKeys(Key key, WordType word, AprilUtils::vector &result) { unsigned int offset; const unsigned int context_size = getContextProperties(key, context_words, offset); Key dest_key = getDestinationKey(context_words, offset, context_size, word); // Append to the result vector result.push_back(dest_key); } virtual bool getZeroKey(Key &k) const { k = trie->rootNode(); return true; } virtual Key getInitialKey() { HistoryBasedLM *mdl; mdl = static_cast* >(this->model); WordType init_word = mdl->getInitWord(); unsigned int context_length = static_cast(this->model->ngramOrder() - 1); Key k = trie->rootNode(); for (unsigned int i = 0; i < context_length; i++) k = trie->getChild(k, init_word); return k; } virtual Score getFinalScore(Key k, Score threshold) { unsigned int offset; const unsigned int context_size = getContextProperties(k, context_words, offset); // Compute score with the retrieved context. In case of fail, return // zero probability Score score; if (!privateGetFinalScore(k, context_words+offset, context_size, threshold, score)) score = Score::zero(); return score; } virtual Score getBestProb(Key k) { unsigned int offset; const unsigned int context_size = getContextProperties(k, context_words, offset); // Compute score with the retrieved context. In case of fail, return // zero probability Score score; if (!privateBestProb(k, context_words+offset, context_size, score)) { score = Score::zero(); } return score; } virtual Score getBestProb() const { return privateBestProb(); } }; template class HistoryBasedLM : public LMModel { private: int ngram_order; WordType init_word; AprilUtils::TrieVector *trie_vector; public: HistoryBasedLM(int ngram_order, WordType init_word, AprilUtils::TrieVector *trie_vector) : LMModel(), ngram_order(ngram_order), init_word(init_word), trie_vector(trie_vector) { IncRef(trie_vector); if (ngram_order <= 0) ERROR_EXIT(128, "Impossible to build HistoryBasedLM with <= 0 order\n"); } virtual ~HistoryBasedLM() { DecRef(trie_vector); } virtual bool isDeterministic() const { return true; } virtual int ngramOrder() const { return ngram_order; } virtual bool requireHistoryManager() const { return true; } WordType getInitWord() { return init_word; } AprilUtils::TrieVector* getTrieVector() { return trie_vector; } // this class is also abstract and hence does not implement // getInterface // virtual LMInterface* getInterface() = 0; }; typedef HistoryBasedLMInterface HistoryBasedLMInterfaceUInt32LogFloat; typedef HistoryBasedLM HistoryBasedLMUInt32LogFloat; }; // closes namespace #endif // HISTORY_BASED_LM_H april-ann-0.4.1/packages/language_model/LM_interface/c_src/skip_function.cc000066400000000000000000000063351263004425400267300ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "skip_function.h" using Basics::Dice; using Basics::MTRand; using Basics::Token; using Basics::TokenBunchVector; using Basics::TokenVectorUint32; using LanguageModels::WordType; namespace LanguageModels { namespace QueryFilters { DiceSkipFunction::DiceSkipFunction(Dice *dice, MTRand *random, WordType mask_value) : FunctionInterface(), dice(dice), random(random), mask_value(mask_value) { num_ctxt_words = 0; int aux = dice->getOutcomes(); while(aux > 0) { aux >>= 1; ++num_ctxt_words; } } DiceSkipFunction::~DiceSkipFunction() { } unsigned int DiceSkipFunction::getInputSize() const { return num_ctxt_words; } unsigned int DiceSkipFunction::getOutputSize() const { return num_ctxt_words; } // Be careful, this function works **in-place** Token *DiceSkipFunction::calculate(Token *input) { if (input->getTokenCode() != Basics::table_of_token_codes::vector_Tokens) { ERROR_EXIT(128, "Input token should be a collection of tokens!\n"); } TokenBunchVector *query_token = input->convertTo(); april_assert(query_token); if (query_token->size() != 2u) { ERROR_EXIT1(128, "Expected a collection with 2 tokens, found %u\n", query_token->size()); } if ((*query_token)[0]->getTokenCode() != Basics::table_of_token_codes::vector_uint32) { ERROR_EXIT(128, "Expected a collection of uint32_t!\n"); } if ((*query_token)[1]->getTokenCode() != Basics::table_of_token_codes::vector_uint32) { ERROR_EXIT(128, "Expected a collection of uint32_t!\n"); } TokenVectorUint32 *ctxt_words_token = (*query_token)[0]->convertTo(); april_assert(ctxt_words_token); unsigned int size = ctxt_words_token->size(); if (size != num_ctxt_words) { ERROR_EXIT2(128, "Incorrect number of words, expected %d, found %d\n", num_ctxt_words, size); } // Compute a mask throwing the dice. int skip_mask = dice->thrown(random.get()); for (int j = static_cast(size)-1; j >= 0; j--) { if (skip_mask & 1) (*ctxt_words_token)[j] = mask_value; skip_mask >>= 1; } return input; } } // namespace QueryFilters } // namespace LanguageModels april-ann-0.4.1/packages/language_model/LM_interface/c_src/skip_function.h000066400000000000000000000051361263004425400265700ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SKIP_FUNCTION_H #define SKIP_FUNCTION_H #include "function_interface.h" #include "dice.h" #include "LM_interface.h" #include "smart_ptr.h" #include "token_vector.h" namespace LanguageModels { namespace QueryFilters { /** * @brief Applies a stochastic skip mask using a Basics::Dice to a query * of a feature based language model. * * @note The dice size is \f$ 2^N \f$ being \f$N\f$ the number of expected * words. * * @note This function operates **in-place** */ class DiceSkipFunction : public Functions::FunctionInterface { AprilUtils::SharedPtr dice; ///< Binomial distribution. AprilUtils::SharedPtr random; ///< For stochastic purposes. LanguageModels::WordType mask_value; ///< The value used to replace masked words. unsigned int num_ctxt_words; ///< Number of expected words. public: /// Takes all given values. DiceSkipFunction(Basics::Dice *dice, Basics::MTRand *random, LanguageModels::WordType mask_value); virtual ~DiceSkipFunction(); /// Returns the number of expected words. virtual unsigned int getInputSize() const; /// Returns the number of expected words. virtual unsigned int getOutputSize() const; /** * @brief Applies the stochastic skip mask operation given a Basics::Token * instance. * * @see LanguageModels::FeatureBasedLM::query_filter property for * a description of the expected input. * * @note This function operates **in-place** */ virtual Basics::Token *calculate(Basics::Token *input); }; } // namespace QueryFilters } // namespace LanguageModels #endif //SKIP_FUNCTION_H april-ann-0.4.1/packages/language_model/LM_interface/lua_src/000077500000000000000000000000001263004425400240765ustar00rootroot00000000000000april-ann-0.4.1/packages/language_model/LM_interface/lua_src/LM_interface.lua000066400000000000000000000036041263004425400271340ustar00rootroot00000000000000language_models = language_models or {} local lang_models_func_tbl = {} function language_models.register_by_extension(extension, func) lang_models_func_tbl[extension] = func end function language_models.load(filename, dictionary, initial_word, final_word, extra) if not extra then extra = {} end local lm_model local extension = string.get_extension(filename) return lang_models_func_tbl[extension](filename, dictionary, initial_word, final_word, extra) end --------------------------------------------------------------------------- local generic_len = function(self) return self:size() end local generic_ipairs = function(self) local i=0 return function() if i < self:size() then i=i+1 return i,self:get(i) end end end local function set_iterator_metatable(it_class) local metatable = it_class.meta_instance metatable.__len = generic_len metatable.__ipairs = generic_ipairs class.extend(it_class, "iterate", metatable.__ipairs) end --------------------------------------------------------------------------- set_iterator_metatable(language_models.__query_result__) set_iterator_metatable(language_models.__get_result__) set_iterator_metatable(language_models.__next_keys_result__) --------------------------------------------------------------------------- class.extend(language_models.__arcs_iterator__, "iterate", function(self) return function() if not self:is_end() then local w = self:get() self:next() return w end end end) -- class.extend_metamethod(language_models.__arcs_iterator__, -- "__pairs", -- class.consult(language_models.__arcs_iterator__, -- "iterate")) april-ann-0.4.1/packages/language_model/LM_interface/lua_src/test_set_ppl.lua000066400000000000000000000274041263004425400273150ustar00rootroot00000000000000language_models = language_models or {} -- Auxiliar functions local function exp10(value) return math.pow(10, value) end local function log10(value) return math.log(value) / math.log(10) end local function print_pw(log_file, lastword, previousword, ngram_value, p) fprintf (log_file, "\tp( %s | %s %s", lastword, previousword, (ngram_value > 2 and "...") or "") fprintf (log_file, ")\t= [%dgram] %g [ %f ]\n", ngram_value, exp10(p), p) end function language_models.get_sentence_prob(params) local params = get_table_fields( { lm = { mandatory = true }, words_it = { mandatory = true, isa_match = iterator }, log_file = { mandatory = false, default = io.stdout }, debug_flag = { mandatory = false, type_match = "number", default = 0 }, unk_id = { mandatory = false, type_match = "number", default = -1 }, use_unk = { mandatory = false, type_match = "string", default = "all" }, use_bcc = { mandatory = false, type_match = "boolean" }, use_ecc = { mandatory = false, type_match = "boolean" } }, params) local lm = params.lm local words_it = params.words_it local log_file = params.log_file local debug_flag = params.debug_flag local unk_id = params.unk_id local use_unk = params.use_unk local use_bcc = params.use_bcc local use_ecc = params.use_ecc local sum = 0 local numwords = 0 local numunks = 0 local lmi = lm:get_interface() local ngram_value = lm:ngram_order() or 0 -- 0 for non Ngram LMs local lastunk = -ngram_value local not_used_words = 0 local i = 1 local key local p local result local prev_word_id local prev_word assert(lm:is_deterministic(), "Error: Expected a deterministic LM") if use_bcc then key = lmi:get_initial_key() else key = lmi:get_zero_key() end local function process_prob() p = p / math.log(10) sum = sum + p end for word_id,word in words_it do -- the word which will be passed to print_pw function; a showed_word==nil -- means to show nothing local printed_word -- If word id is -1, unknown words aren't considered by the model. We must -- skip the addition, store the unknown word index, set key to zero key, and -- probability to -inf for printing purposes because it is not added up if word_id == -1 then not_used_words = not_used_words + 1 numunks = numunks + 1 lastunk = i key,p = lmi:get_zero_key(),-math.huge printed_word = "" else -- if word_id == -1 else -- The result is always computed result = lmi:get(key, word_id) -- For history based LMs (as NNLMs), it is possible that after an unknown -- word, the model can traverse to next key but it coulnd't compute probabilities, -- in this cases, show a warning and ignore the current word if #result == 0 then -- history based LMs case when no context is available result = lmi:next_keys(key, word_id) assert(#result == 1) -- sanity check key = result:get(1) not_used_words = not_used_words + 1 if use_unk ~= "none" then -- replicate the behavior of models without word in the -- vocabulary p = -math.huge printed_word = word fprintf(io.stderr, "# WARNING! LM can't compute probabilities for current ".. "context, in history-based LMs it is possible to need ".. "to fix use_unk='none'\n") else -- the same behavior as when use_unk=="none" and #result>0 printed_word = nil end else -- if #result == 0 else assert(#result == 1) -- sanity check -- In all the cases the key and probability are taken, but -- probability will be added up only when process_prob() is called key,p = result:get(1) -- If unknown words don't appear on context if i - lastunk >= ngram_value then -- If current word is unknown, we store -- the index and sum its probability if -- we consider all unknown words if word_id == unk_id then lastunk = i if use_unk == "all" then printed_word = "" process_prob() else not_used_words = not_used_words + 1 end else -- If it's known, the probability must be taken into account, the -- printed_word is the given printed_word = word process_prob() end else -- If last unknown word is on context, then -- we add its probability if we consider all -- or only context unknown words if use_unk == "none" then not_used_words = not_used_words + 1 printed_word = nil else -- use_unk == "context" or use_unk == "all" printed_word = (word_id ~= unk_id and word) or "" process_prob() end end -- if unknown word don't appear on context else end end end -- if word_id == -1 else end if debug_flag >= 2 and printed_word then print_pw(log_file, printed_word, ((prev_word_id ~= unk_id and prev_word) or prev_word_id == unk_id and "") or "", (not prev_word_id and 2) or ngram_value, p) end prev_word_id = word_id prev_word = word i = i + 1 end numwords = i - 1 if use_unk ~= "all" or unk_id == -1 then numwords = numwords - not_used_words end if use_ecc and (use_unk ~= "none" or i - lastunk >= ngram_value) then p = lmi:get_final_score(key) process_prob() if debug_flag >= 2 then print_pw(log_file, "", ((prev_word_id ~= unk_id and prev_word) or prev_word_id == unk_id and "") or "", (not prev_word_id and 2) or ngram_value, p) end end return sum,numwords,numunks end --[[ function language_models.get_prob_from_id_tbl(lm, word_ids, init_id, final_id, use_bcc, use_ecc) local lmi = lm:get_interface() local key = lmi:get_initial_key() if not use_bcc then key = lmi:get_zero_key() end local sum = 0 local result local p local numwords = #word_ids local ngram_value = lm:ngram_order() for i=1,numwords do if word ~= 0 then result = lmi:get(key, word) assert(result:size() == 1, "Error: Expected a deterministic LM") key,p = result:get(1) sum = sum + p end end if use_ecc then result = lmi:get(key, final_id) assert(result:size() == 1, "Error: Expected a deterministic LM") _,p = result:get(1) sum = sum + p end return sum end --]] function language_models.test_set_ppl(params) local params = get_table_fields ( { lm = { mandatory = true }, vocab = { mandatory = true }, testset = { mandatory = true }, log_file = { mandatory = false, default = io.stdout }, debug_flag = { mandatory = false, type_match = "number", default = 0 }, unk_word = { mandatory = false, type_match = "string", default = "" }, init_word = { mandatory = false, type_match = "string", default = "" }, final_word = { mandatory = false, type_match = "string", default = "" }, use_unk = { mandatory = false, type_match = "string", default = "all" }, use_cache = { mandatory = false, type_match = "boolean" }, train_restriction = { mandatory = false, type_match = "boolean" }, cache_stop_token = { mandatory = false, type_match = "string" }, null_token = { mandatory = false, type_match = "string" }, use_bcc = { mandatory = false, type_match = "boolean" }, use_ecc = { mandatory = false, type_match = "boolean" } }, params) local lm = params.lm local vocab = params.vocab local testset = params.testset local log_file = params.log_file local debug_flag = params.debug_flag local unk_word = params.unk_word local init_word = params.init_word local final_word = params.final_word local unk_id = -1 if vocab:getWordId(unk_word) then unk_id = vocab:getWordId(unk_word) end local init_id = vocab:getWordId(init_word) local final_id = vocab:getWordId(final_word) -- lm:restart() local use_unk = params.use_unk local use_cache = params.use_cache local train_restriction = params.train_restriction local cache_stop_token = params.cache_stop_token local null_token = params.null_token local use_bcc = params.use_bcc local use_ecc = params.use_ecc local count = 0 local totalwords = 0 local totalsentences = 0 local totalunks = 0 local totalsum = 0 local lines_it = iterator(io.lines(testset)): map( function(line) return line,iterator(line:gmatch("[^%s]+")) end ) for sentence,words_it in lines_it do words_it = words_it:map( function(w) return (vocab:getWordId(w) or unk_id),w end ) local use_sentence = true if train_restriction then if words[1] ~= "" then use_sentence = false end table.remove(words, 1) end if use_sentence then count = count + 1 --if #sentence > 0 and #words > 0 then if debug_flag >= 1 then fprintf(log_file, "%s\n", sentence) end local sum,numwords,numunks = language_models.get_sentence_prob{ lm = lm, words_it = words_it, log_file = log_file, debug_flag = debug_flag, unk_id = unk_id, use_unk = use_unk, use_bcc = use_bcc, use_ecc = use_ecc } if debug_flag >= 1 then fprintf (log_file, "%d sentences, %d words, %d OOVs\n", 1, numwords+numunks, numunks) fprintf (log_file, "0 zeroprobs, logprob= %.4f ppl= %.3f ppl1= %.3f\n", sum, exp10(-sum/(numwords + ((use_ecc and 1) or 0) )), exp10(-sum/numwords)) fprintf (log_file, "\n") end log_file:flush() totalsum = totalsum + sum totalwords = totalwords + numwords totalunks = totalunks + numunks totalsentences = totalsentences + 1 --end -- if use_cache or math.mod(count, 1000) == 0 then lm:restart() end -- if use_cache then lm:restart() end end --[[ if use_cache then local word_ids word_ids = vocab:searchWordIdSequence(words, unk_id) for i=1,#word_ids do if words[i] == cache_stop_token then lm:clearCache() elseif words[i] ~= null_token then lm:cacheWord(word_ids[i]) end end --lm:showCache() end ]]-- end -- lm:restart() local entropy = -totalsum/(totalwords + ((use_ecc and totalsentences) or 0)) local ppl = exp10(entropy) local entropy1 = -totalsum/totalwords local ppl1 = exp10(entropy1) if is_stream then ppl = ppl1 entropy = entropy1 end if debug_flag >= 0 then fprintf (log_file, "file %s: %d sentences, %d words, %d OOVs\n", testset, totalsentences, totalwords + totalunks, totalunks) log_file:flush() fprintf (log_file, "0 zeroprobs, logprob= %f ppl= %f ppl1= %f\n", totalsum, ppl, ppl1) log_file:close() end return { ppl = ppl, ppl1 = ppl1, logprob = totalsum, numwords = totalwords, numunks = totalunks, numsentences = totalsentences, } end april-ann-0.4.1/packages/language_model/LM_interface/package.lua000066400000000000000000000024001263004425400245400ustar00rootroot00000000000000 package{ name = "language_models", version = "1.0", depends = { "util", "dataset" }, --, "symbol_scores" }, keywords = { }, description = "Interface for generic language models", target{ name = "init", mkdir{ dir = "include" }, mkdir{ dir = "build" }, }, target{ name = "clean", delete{ dir = "include" }, delete{ dir = "build" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_LM_interface.lua.cc", dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp = true, -- does not need to compile because implemented methods are defined in a template object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_LM_interface.lua.cc", dest_dir = "build", }, }, target{ name = "document", document_src{ file= {"c_src/*.h", "c_src/*.c", "c_src/*.cc"}, }, document_bind{ file= {"binding/*.lua.cc"} }, }, } 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Derek unless had descended Like a Curtain by the Darkness had descended like a Clint an by the Darkness had descended like a Clerk aims by the Dusky less had descended like a Curtain by the Darkness had descended like a Clerk arms by the Darkness had descended like a Curtain lay The Darkness had descended like a Clerk aim by the Darkness had descended like a Cherian by the Derek us less had descended like a Certain by the Dave Lawless had descended like a Certain by the Darkness had descended like a Kaukau by the Darkness had descended like a Curan by the Darkness had descended like an Curtain by the ' Darkness had descended like a Curtain by the Darkness had descended like a Cecil am by the Darkness had descended like a Caetani by the Darkness had descended like a Curran by the Darkness had descended like a Certain boy the Darkness had descended like a Clint arm by the Dave caress had descended like a Curtain by the Darkness had descended like a , Curtain by the Due lawless had descended like a Curtain by the Dave kv less had descended like a Curtain by the Darkness had descended like a Curtain buy the Darkness had descended like a Court aims by the Darkness had descended like a Court arms by the Darkness , had descended like a Curtain by the Darkness had descended like a Clark an by the Darkness had descended like a Court aim by the Darkness had descended like a Curtain by She D merciless had descended like a Curtain by the Dark unless had descended like a Curtain by the " Darkness had descended like a Curtain by the Dusk unless had descended like a Curtain by the Darkness had descended like a Clerk arm lay the Darkness " had descended like a Curtain by the Derek we ss had descended like a Curtain by the Darkness had descended Like a Cecil an by the Dave kw less had descended like a Curtain by the Darkness had descended like a Certain way he Plazek unless had descended like a Certain by the Darkness had descended like a Certain May the april-ann-0.4.1/packages/language_model/LM_interface/test/best100.out000066400000000000000000000227341263004425400253440ustar00rootroot000000000000000||| Darkness had descended like a Curtain by the ||| 2542.038708 -55.259963 8 ||| 1863.131470 0||| Darkness had descended like a Certain by the ||| 2522.371668 -54.448905 8 ||| 1853.013184 0||| Darkness had descended Like a Curtain by the ||| 2579.860477 -62.873960 8 ||| 1811.312134 0||| Derek unless had descended like a Curtain by the ||| 2589.602126 -63.919438 9 ||| 1805.205078 0||| Darkness had descended Like a Certain by the ||| 2560.193315 -62.062901 8 ||| 1801.193726 0||| Darkness had descended like a Cecil an by the ||| 2525.420372 -59.189727 9 ||| 1796.707153 0||| Derek unless had descended like a Certain by the ||| 2569.935207 -63.108379 9 ||| 1795.086914 0||| Darkness had descended like a Cuban by the ||| 2444.409887 -52.965361 8 ||| 1792.517456 0||| Darkness had descended like a Curtain by he ||| 2523.460046 -59.966393 8 ||| 1789.143066 0||| Darkness had descended like a Curtain lay the ||| 2528.246243 -60.403503 8 ||| 1788.783081 0||| Darkness had descended like a Curtain by The ||| 2537.992963 -61.301343 8 ||| 1787.959351 0||| Derek was s had descended like a Curtain by the ||| 2629.158049 -68.591809 10 ||| 1786.212158 0||| Derek mess had descended like a Curtain by the ||| 2587.440190 -65.393468 9 ||| 1785.689087 0||| Darkness had descended like a Certain by he ||| 2503.793005 -59.155335 8 ||| 1779.024780 0||| Darkness had descended like a Curtain way the ||| 2503.952093 -59.187282 8 ||| 1778.807739 0||| Darkness had descended like a Certain lay the ||| 2508.579209 -59.592445 8 ||| 1778.664795 0||| Darkness had descended like a Certain by The ||| 2518.325923 -60.490285 8 ||| 1777.841064 0||| Darkness had descended like a Clurman by the ||| 2462.022572 -55.835806 8 ||| 1776.335815 0||| Derek was s had descended like a Certain by the ||| 2609.491008 -67.780751 10 ||| 1776.093872 0||| Derek mess had descended like a Certain by the ||| 2567.773150 -64.582410 9 ||| 1775.570801 0||| Darkness had descended like a Ceuta by the ||| 2419.803692 -52.420114 8 ||| 1774.330566 0||| Derek Ness had descended like a Curtain by the ||| 2595.544158 -67.142671 9 ||| 1773.199341 0||| , Darkness had descended like a Curtain by the ||| 2499.956234 -59.059953 9 ||| 1772.770874 0||| Darkness had descended like a Cecil arm by the ||| 2559.201078 -64.100634 9 ||| 1772.670776 0||| Derek is less had descended like a Curtain by the ||| 2568.014799 -64.698042 10 ||| 1770.911011 0||| Derek no less had descended like a Curtain by the ||| 2578.292662 -65.690071 10 ||| 1769.509521 0||| Dave lawless had descended like a Curtain by the ||| 2598.734693 -67.795480 9 ||| 1768.704224 0||| Darkness had descended like a Certain way the ||| 2484.285058 -58.376224 8 ||| 1768.689453 0||| Darkness had descended like a Clerk an by the ||| 2536.073096 -62.525065 9 ||| 1768.092285 0||| Darkness had descended like a Curtain by He ||| 2508.969376 -60.530578 8 ||| 1768.010132 0||| Darkness had descended like a Ceuta us by the ||| 2520.344333 -61.303480 9 ||| 1766.745483 0||| Darkness had descended like a Curtain by she ||| 2511.075109 -60.852853 8 ||| 1766.321655 0||| Dusk was s had descended like a Curtain by the ||| 2601.533469 -68.014569 10 ||| 1765.383545 0||| Darkness had descended like a Clerk arm by the ||| 2569.853718 -65.722353 9 ||| 1764.230591 0||| Darkness had descended like a Court an by the ||| 2490.715486 -59.024470 9 ||| 1763.947876 0||| Derek Ness had descended like a Certain by the ||| 2575.877117 -66.331613 9 ||| 1763.081055 0||| , Darkness had descended like a Certain by the ||| 2480.289193 -58.248895 9 ||| 1762.652588 0||| Derek us less had descended like a Curtain by the ||| 2608.032070 -68.877389 10 ||| 1761.723999 0||| Dave Lawless had descended like a Curtain by the ||| 2587.838797 -67.478628 9 ||| 1761.538696 0||| Derek is less had descended like a Certain by the ||| 2548.347759 -63.886984 10 ||| 1760.792725 0||| Darkness had descended like a Cecil aims by the ||| 2540.002381 -63.479502 9 ||| 1760.784790 0||| Darkness had descended like a Cecil arms by the ||| 2541.718528 -63.636343 9 ||| 1760.654419 0||| Darkness had descended like a Cecil aim by the ||| 2557.484783 -65.014680 9 ||| 1760.193237 0||| Darkness had descended like a Court arm by the ||| 2524.496114 -62.221759 9 ||| 1760.086182 0||| Derek no less had descended like a Certain by the ||| 2558.625744 -64.879012 10 ||| 1759.391357 0||| Darkness had descended like a Curtain boy the ||| 2506.757421 -61.089903 8 ||| 1759.213135 0||| Dave lawless had descended like a Certain by the ||| 2579.067653 -66.984422 9 ||| 1758.585938 0||| Darkness had descended like a Certain by He ||| 2489.302335 -59.719520 8 ||| 1757.891846 0||| Darkness had descended like a Curtain , by the ||| 2473.934442 -58.155214 9 ||| 1757.400757 0||| Darkness had descended like a Certain by she ||| 2491.408069 -60.041795 8 ||| 1756.203369 0||| Dusk was s had descended like a Certain by the ||| 2581.866429 -67.203511 10 ||| 1755.265259 0||| Darkness had descended like a Curtain way he ||| 2485.373377 -59.652632 8 ||| 1754.750366 0||| Plazek unless had descended like a Curtain by the ||| 2567.448472 -66.337487 9 ||| 1754.583252 0||| Darkness had descended like a Curtain May the ||| 2510.328266 -61.794653 8 ||| 1754.486816 0||| Darkness had descended like a Curtain Lay the ||| 2530.756183 -63.545803 8 ||| 1754.298096 0||| Darkness had descended like a Certainly the ||| 2346.706615 -48.221954 7 ||| 1754.199341 0||| Derek was 5 had descended like a Curtain by the ||| 2574.826421 -66.726034 10 ||| 1753.846680 0||| Darkness had descended like a Cecil arm lay the ||| 2545.408624 -64.561432 9 ||| 1753.453247 0||| Derek unless had descended Like a Curtain by the ||| 2627.423895 -71.533435 9 ||| 1753.385742 0||| Darkness had descended like a Clint an by the ||| 2487.809589 -59.716877 9 ||| 1752.890137 0||| Darkness had descended like a Clerk aims by the ||| 2550.655022 -65.101221 9 ||| 1752.344604 0||| Dusky less had descended like a Curtain by the ||| 2535.334539 -63.808474 9 ||| 1752.243896 0||| Darkness had descended like a Clerk arms by the ||| 2552.371169 -65.258062 9 ||| 1752.214233 0||| Darkness had descended like a Curtain lay The ||| 2524.200425 -63.174396 8 ||| 1752.114990 0||| Darkness had descended like a Clerk aim by the ||| 2568.137423 -66.636399 9 ||| 1751.753052 0||| Darkness had descended like a Cherian by the ||| 2440.055714 -56.062923 8 ||| 1751.695068 0||| Derek us less had descended like a Certain by the ||| 2588.365030 -68.066330 10 ||| 1751.605713 0||| Dave Lawless had descended like a Certain by the ||| 2568.171757 -66.667569 9 ||| 1751.420410 0||| Darkness had descended like a Kaukau by the ||| 2439.553499 -56.060848 8 ||| 1751.217285 0||| Darkness had descended like a Curan by the ||| 2436.740779 -55.824822 8 ||| 1751.183350 0||| Darkness had descended like an Curtain by the ||| 2455.723265 -57.461877 8 ||| 1750.892456 0||| ' Darkness had descended like a Curtain by the ||| 2502.452205 -61.171019 9 ||| 1750.412842 0||| Darkness had descended like a Cecil am by the ||| 2523.396583 -63.005261 9 ||| 1749.762329 0||| Darkness had descended like a Caetani by the ||| 2435.255706 -55.833752 8 ||| 1749.593140 0||| Darkness had descended like a Curran by the ||| 2437.663397 -56.067746 8 ||| 1749.245972 0||| Darkness had descended like a Certain boy the ||| 2487.090375 -60.278844 8 ||| 1749.094849 0||| Darkness had descended like a Clint arm by the ||| 2521.590206 -62.914165 9 ||| 1749.028442 0||| Dave caress had descended like a Curtain by the ||| 2575.610859 -67.519021 9 ||| 1748.835205 0||| Darkness had descended like a , Curtain by the ||| 2466.519179 -58.257024 9 ||| 1748.786865 0||| Due lawless had descended like a Curtain by the ||| 2601.550350 -69.745792 9 ||| 1748.558472 0||| Dave kv less had descended like a Curtain by the ||| 2675.093019 -75.698365 10 ||| 1748.480225 0||| Darkness had descended like a Curtain buy the ||| 2491.020488 -60.674863 8 ||| 1748.362549 0||| Darkness had descended like a Court aims by the ||| 2505.297418 -61.600627 9 ||| 1748.200195 0||| Darkness had descended like a Court arms by the ||| 2507.013565 -61.757468 9 ||| 1748.069824 0||| Darkness , had descended like a Curtain by the ||| 2471.174886 -58.741124 9 ||| 1747.743164 0||| Darkness had descended like a Clark an by the ||| 2497.395788 -60.979677 9 ||| 1747.609131 0||| Darkness had descended like a Court aim by the ||| 2522.779941 -63.135805 9 ||| 1747.608765 0||| Darkness had descended like a Curtain by She ||| 2497.990426 -61.334628 8 ||| 1747.564941 0||| D merciless had descended like a Curtain by the ||| 2568.628330 -67.052969 9 ||| 1747.339600 0||| Dark unless had descended like a Curtain by the ||| 2540.120352 -64.633467 9 ||| 1747.316895 0||| " Darkness had descended like a Curtain by the ||| 2493.773533 -60.758751 9 ||| 1746.587891 0||| Dusk unless had descended like a Curtain by the ||| 2561.977595 -66.664588 9 ||| 1745.261353 0||| Darkness had descended like a Clerk arm lay the ||| 2556.061265 -66.183152 9 ||| 1745.013062 0||| Darkness " had descended like a Curtain by the ||| 2460.004415 -58.029488 9 ||| 1744.950928 0||| Derek we ss had descended like a Curtain by the ||| 2666.266739 -75.252096 10 ||| 1744.907959 0||| Darkness had descended Like a Cecil an by the ||| 2563.242141 -66.803724 9 ||| 1744.887817 0||| Dave kw less had descended like a Curtain by the ||| 2673.899346 -75.909524 10 ||| 1744.800537 0||| Darkness had descended like a Certain way he ||| 2465.706343 -58.841574 8 ||| 1744.632080 0||| Plazek unless had descended like a Certain by the ||| 2547.781554 -65.526428 9 ||| 1744.465088 0||| Darkness had descended like a Certain May the ||| 2490.661220 -60.983594 8 ||| 1744.368530 april-ann-0.4.1/packages/language_model/LM_interface/test/generate_test_lira.sh000077500000000000000000000003051263004425400276220ustar00rootroot00000000000000ngram-count -order 3 -lm lm3gram.arpa -text my_text.txt -write-vocab lm3gram.voc -unk 2> /dev/null april-ann.debug /home/baha/april-ann/tools/LM/arpa2lira.lua lm3gram.voc lm3gram.arpa lm3gram.lira april-ann-0.4.1/packages/language_model/LM_interface/test/lm3gram.arpa000066400000000000000000000040361263004425400256370ustar00rootroot00000000000000 \data\ ngram 1=26 ngram 2=37 ngram 3=19 \1-grams: -0.9726142 -99 -1.229844 -2.227885 -2.227887 Cecil -0.2984526 -1.449735 Certain -0.799055 -2.227887 Clurman -0.260664 -2.227887 Cuban -0.260664 -1.273644 Curtain -0.9510902 -1.081759 Darkness -1.127182 -1.625827 Derek -0.6885672 -1.926857 Like -0.4282115 -1.926857 The -0.4282115 -0.9726142 a -1.229844 -2.227887 an -0.260664 -1.051795 by -1.15521 -0.9726142 descended -1.229844 -0.9726142 had -1.229844 -1.926857 he -0.4282115 -1.926857 lay -0.4395663 -1.023767 like -1.181539 -2.227887 mess -0.2521202 -2.227887 s -0.2521202 -1.081759 the -1.127182 -1.926857 unless -0.4282115 -2.227887 was -0.2984526 -2.227887 way -0.263475 \2-grams: -0.1326256 Darkness 0 -0.6766936 Derek -0.07918122 -0.30103 Cecil an -0.146128 Certain by 0.10721 -0.845098 Certain lay -0.30103 Clurman by -0.30103 Cuban by -0.154902 Curtain by -0.03891808 -1 Curtain lay -1 Curtain way -0.02996322 Darkness had 0.1026623 -0.69897 Derek mess -0.39794 Derek unless 0 -0.69897 Derek was -0.1760913 Like a -0.1760913 The -1.278754 a Cecil -0.5006024 a Certain -0.2340832 -1.278754 a Clurman -1.278754 a Cuban -0.3245111 a Curtain -0.1303338 -0.30103 an by -0.90309 by The 0 -0.90309 by he 0 -0.1627273 by the 0.09691012 -0.9777236 descended Like 0 -0.07463362 descended like 0 -0.0234811 had descended 0 -0.1760913 he -0.1760913 lay the 0.6989701 -0.02632894 like a -0.05030513 -0.30103 mess had -0.30103 s had -0.02996322 the -0.1760913 unless had 0.8016324 -0.30103 was s -0.30103 way the \3-grams: -0.07918125 a Certain by -0.1091445 a Curtain by -0.02996322 Darkness had -0.30103 Derek unless -0.1760913 descended Like a -0.1760913 by The -0.50515 like a Certain -0.30103 like a Curtain -0.2218488 Certain by the -0.146128 Curtain by the -0.9777236 had descended Like -0.07463362 had descended like -0.02996322 Darkness had descended -0.1760913 unless had descended -0.1760913 by he -0.02632894 descended like a -0.03778856 by the -0.1760913 lay the -0.1760913 Derek unless had \end\ april-ann-0.4.1/packages/language_model/LM_interface/test/lm3gram.lira000066400000000000000000000060771263004425400256520ustar00rootroot00000000000000# number of words and words 27 -pau- Cecil Certain Clurman Cuban Curtain Darkness Derek Like The a an by descended had he lay like mess s the unless was way # max order of n-gram 3 # number of states 43 # number of transitions 82 # bound max trans prob 1.791760 # how many different number of transitions 6 # "x y" means x states have y transitions 1 0 32 1 5 2 3 3 1 5 1 26 # initial state, final state and lowest state 34 0 42 # state backoff_st 'weight(state->backoff_st)' [max_transition_prob] # backoff_st == -1 means there is no backoff 0 42 0.000000 -2.239527 1 42 -2.595432 -0.068993 2 42 -0.687213 -0.693147 3 5 0.000000 -0.405465 4 38 -0.089612 -0.336472 5 42 -0.985993 -0.405465 6 17 1.845827 1.791760 7 42 -0.985993 -0.405465 8 1 0.000000 -0.068993 9 7 0.000000 -0.405465 10 42 -0.687213 -0.693147 11 42 -2.720594 -0.060625 12 42 -0.600201 -0.693147 13 42 -0.580528 -0.693147 14 39 -0.300105 -0.251314 15 42 -0.985993 -0.405465 16 22 0.000000 -0.405465 17 42 -2.831820 -0.054067 18 42 -0.606674 -0.693147 19 32 0.223144 0.154151 20 42 -1.012139 -0.405465 21 37 -0.538996 -0.182322 22 42 -0.985993 -0.405465 23 40 -0.182321 -0.693147 24 11 0.000000 -0.060625 25 17 0.236389 0.182321 26 42 -0.580528 -0.693147 27 42 -0.600201 -0.693147 28 38 0.246860 -0.127833 29 32 1.609438 1.540445 30 15 0.000000 -0.405465 31 42 -0.600201 -0.693147 32 42 -2.595432 -0.068993 33 42 -2.831820 -0.171850 34 42 -2.831820 -0.305382 35 33 0.000000 -0.171850 36 41 -0.115832 -0.693147 37 42 -1.839892 -0.336472 38 42 -2.659969 -0.374693 39 42 -2.189966 -0.356675 40 42 -1.585485 -0.916291 41 42 -2.831820 -0.747214 42 -1 -1 -2.239527 # transitions # orig dest word prob 1 25 18 -0.0689929 2 13 23 -0.693147 3 0 2 -0.405465 4 19 24 -0.336472 5 0 2 -0.405465 6 35 17 -0.405465 7 41 14 -0.405465 8 25 18 -0.0689929 9 41 14 -0.405465 10 27 15 -0.693147 11 36 14 -0.0606246 12 38 16 -0.693147 13 17 18 -0.693147 14 4 16 -0.251314 15 6 18 -0.405465 16 0 2 -0.405465 17 35 17 -0.0540672 18 32 24 -0.693147 19 0 2 -0.0870114 20 29 24 -0.405465 21 28 16 -0.182322 22 0 2 -0.405465 23 30 25 -0.693147 24 36 14 -0.0606246 25 35 17 -0.0689929 26 17 18 -0.693147 27 38 16 -0.693147 28 19 24 -0.510826 29 0 2 -0.405465 30 6 18 -0.405465 31 38 16 -0.693147 32 0 2 -0.0689929 33 9 12 -2.25129 33 24 21 -0.17185 34 8 10 -0.305382 34 23 11 -1.55814 35 9 12 -2.25129 35 24 21 -0.17185 36 21 6 -1.16315 36 14 9 -0.693147 37 28 16 -0.336472 37 20 20 -1.94591 38 16 13 -2.07944 38 3 19 -2.07944 38 19 24 -0.374693 39 4 16 -0.356675 39 20 20 -2.30259 39 18 27 -2.30259 40 26 22 -1.60944 40 30 25 -0.916291 40 2 26 -1.60944 41 10 5 -2.94444 41 21 6 -1.15268 41 12 7 -2.94444 41 31 8 -2.94444 41 14 9 -0.747214 42 0 2 -2.23953 42 34 3 -1e+12 42 42 4 -5.12989 42 10 5 -5.1299 42 37 6 -3.33814 42 12 7 -5.1299 42 31 8 -5.1299 42 39 9 -2.93267 42 1 10 -2.49084 42 40 11 -3.7436 42 7 12 -4.43675 42 22 13 -4.43675 42 41 14 -2.23953 42 27 15 -5.1299 42 38 16 -2.42185 42 33 17 -2.23953 42 17 18 -2.23953 42 5 19 -4.43675 42 20 20 -4.43675 42 11 21 -2.35731 42 26 22 -5.1299 42 13 23 -5.1299 42 32 24 -2.49084 42 15 25 -4.43675 42 2 26 -5.1299 42 18 27 -5.1299 april-ann-0.4.1/packages/language_model/LM_interface/test/lm3gram.voc000066400000000000000000000002151263004425400254760ustar00rootroot00000000000000-pau- Cecil Certain Clurman Cuban Curtain Darkness Derek Like The a an by descended had he lay like mess s the unless was way april-ann-0.4.1/packages/language_model/LM_interface/test/my_text.txt000066400000000000000000000015111263004425400256550ustar00rootroot00000000000000Darkness had descended like a Curtain by the Darkness had descended like a Certain by the Darkness had descended Like a Curtain by the Derek unless had descended like a Curtain by the Darkness had descended Like a Certain by the Darkness had descended like a Cecil an by the Derek unless had descended like a Certain by the Darkness had descended like a Cuban by the Darkness had descended like a Curtain by he Darkness had descended like a Curtain lay the Darkness had descended like a Curtain by The Derek was s had descended like a Curtain by the Derek mess had descended like a Curtain by the Darkness had descended like a Certain by he Darkness had descended like a Curtain way the Darkness had descended like a Certain lay the Darkness had descended like a Certain by The Darkness had descended like a Clurman by the april-ann-0.4.1/packages/language_model/LM_interface/test/rescore_bunch_test.sh000077500000000000000000000001771263004425400276510ustar00rootroot00000000000000april-ann.debug /home/baha/april-ann/tools/nbest/compute_deterministic_bunch_lm_score.lua best100.out lm3gram.lira lm3gram.voc april-ann-0.4.1/packages/language_model/LM_interface/test/rescore_test.sh000077500000000000000000000001711263004425400264640ustar00rootroot00000000000000april-ann.debug /home/baha/april-ann/tools/nbest/compute_deterministic_lm_score.lua best100.out lm3gram.lira lm3gram.voc april-ann-0.4.1/packages/language_model/LM_interface/test/rescore_test_ppl.sh000077500000000000000000000001651263004425400273420ustar00rootroot00000000000000april-ann.debug /home/baha/april-ann/tools/LM/ngram-ppl-calc.lua -t best100.filt -l lm3gram.lira -v lm3gram.voc -d 1 april-ann-0.4.1/packages/language_model/LM_interface/test/result1.txt000066400000000000000000000032301263004425400255630ustar00rootroot00000000000000-2.0437868237495 -2.6191517412663 -4.522134333849 -4.6626360714436 -5.0329623222351 -5.5841127932072 -5.2380009889603 -4.8909657895565 -4.1948205530643 -4.7826144099236 -4.1948205530643 -6.390681181103 -5.6975341774523 -4.2593594491482 -4.7338242977858 -5.1348283290863 -4.2593594491482 -4.8909657895565 -6.9660460986197 -6.272899094969 -11.636939078569 -12.34985235706 -12.190954744816 -12.436771661043 -17.479742322117 -17.479742322117 -16.98561624065 -10.109920367599 -15.038136094809 -11.739304333925 -16.766829043627 -11.739304333925 -16.132390175015 -16.766829043627 -15.038136094809 -12.925217274576 -12.766319662333 -17.479742322117 -16.98561624065 -18.055107239634 -12.436771661043 -12.436771661043 -12.436771661043 -16.766829043627 -18.055107239634 -11.548783048987 -17.560981158167 -11.803843706846 -11.87250456214 -11.803843706846 -16.707755092531 -9.4205735325813 -14.809808939695 -11.548783048987 -11.548783048987 -11.313217565417 -13.061020169407 -14.800897240639 -7.140983581543 -15.038136094809 -16.766829043627 -16.98561624065 -16.766829043627 -9.8260381817818 -16.766829043627 -11.636939078569 -18.055107239634 -17.560981158167 -11.636939078569 -11.636939078569 -12.778741359711 -12.190954744816 -12.436771661043 -11.636939078569 -11.636939078569 -11.907603308558 -16.766829043627 -16.98561624065 -12.466213226318 -16.98561624065 -22.115506205708 -11.548783048987 -16.766829043627 -16.766829043627 -11.924720082432 -15.038136094809 -16.766829043627 -11.739304333925 -16.98561624065 -14.809808939695 -12.190954744816 -14.809808939695 -19.130954623222 -11.924720082432 -17.479742322117 -7.8925611972809 -22.115506205708 -14.796669602394 -15.385173857212 -11.907603308558 april-ann-0.4.1/packages/language_model/LM_interface/test/result2.txt000066400000000000000000000320131263004425400255650ustar00rootroot00000000000000# ARG test = best100.filt # ARG langmodel_filename = lm3gram.lira # ARG vocabfilename = lm3gram.voc # ARG debug = 1 Darkness had descended like a Curtain by the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -0.8876 ppl= 1.255 ppl1= 1.291 Darkness had descended like a Certain by the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -1.1375 ppl= 1.338 ppl1= 1.387 Darkness had descended Like a Curtain by the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -1.9639 ppl= 1.653 ppl1= 1.760 Derek unless had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -2.0250 ppl= 1.594 ppl1= 1.679 Darkness had descended Like a Certain by the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -2.1858 ppl= 1.749 ppl1= 1.876 Darkness had descended like a Cecil an by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -2.4251 ppl= 1.748 ppl1= 1.860 Derek unless had descended like a Certain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -2.2748 ppl= 1.688 ppl1= 1.790 Darkness had descended like a Cuban by the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -2.1241 ppl= 1.722 ppl1= 1.843 Darkness had descended like a Curtain by he 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -1.8218 ppl= 1.594 ppl1= 1.689 Darkness had descended like a Curtain lay the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -2.0771 ppl= 1.701 ppl1= 1.818 Darkness had descended like a Curtain by The 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -1.8218 ppl= 1.594 ppl1= 1.689 Derek was s had descended like a Curtain by the 1 sentences, 10 words, 0 OOVs 0 zeroprobs, logprob= -2.7754 ppl= 1.788 ppl1= 1.895 Derek mess had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -2.4744 ppl= 1.768 ppl1= 1.883 Darkness had descended like a Certain by he 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -1.8498 ppl= 1.605 ppl1= 1.703 Darkness had descended like a Curtain way the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -2.0559 ppl= 1.692 ppl1= 1.807 Darkness had descended like a Certain lay the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -2.2300 ppl= 1.769 ppl1= 1.900 Darkness had descended like a Certain by The 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -1.8498 ppl= 1.605 ppl1= 1.703 Darkness had descended like a Clurman by the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -2.1241 ppl= 1.722 ppl1= 1.843 Derek was s had descended like a Certain by the 1 sentences, 10 words, 0 OOVs 0 zeroprobs, logprob= -3.0253 ppl= 1.884 ppl1= 2.007 Derek mess had descended like a Certain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -2.7243 ppl= 1.873 ppl1= 2.008 Darkness had descended like a Ceuta by the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.0539 ppl= 3.644 ppl1= 4.283 Derek Ness had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -5.3635 ppl= 3.438 ppl1= 3.944 , Darkness had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -5.2945 ppl= 3.384 ppl1= 3.875 Darkness had descended like a Cecil arm by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -5.4012 ppl= 3.468 ppl1= 3.982 Derek is less had descended like a Curtain by the 1 sentences, 10 words, 0 OOVs 0 zeroprobs, logprob= -7.5914 ppl= 4.899 ppl1= 5.743 Derek no less had descended like a Curtain by the 1 sentences, 10 words, 0 OOVs 0 zeroprobs, logprob= -7.5914 ppl= 4.899 ppl1= 5.743 Dave lawless had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.3768 ppl= 5.466 ppl1= 6.601 Darkness had descended like a Certain way the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -4.3907 ppl= 3.075 ppl1= 3.539 Darkness had descended like a Clerk an by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -6.5310 ppl= 4.499 ppl1= 5.317 Darkness had descended like a Curtain by He 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.0983 ppl= 3.685 ppl1= 4.338 Darkness had descended like a Ceuta us by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.2817 ppl= 5.348 ppl1= 6.443 Darkness had descended like a Curtain by she 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.0983 ppl= 3.685 ppl1= 4.338 Dusk was s had descended like a Curtain by the 1 sentences, 10 words, 0 OOVs 0 zeroprobs, logprob= -7.0062 ppl= 4.334 ppl1= 5.019 Darkness had descended like a Clerk arm by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.2817 ppl= 5.348 ppl1= 6.443 Darkness had descended like a Court an by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -6.5310 ppl= 4.499 ppl1= 5.317 Derek Ness had descended like a Certain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -5.6134 ppl= 3.642 ppl1= 4.204 , Darkness had descended like a Certain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -5.5443 ppl= 3.585 ppl1= 4.131 Derek us less had descended like a Curtain by the 1 sentences, 10 words, 0 OOVs 0 zeroprobs, logprob= -7.5914 ppl= 4.899 ppl1= 5.743 Dave Lawless had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.3768 ppl= 5.466 ppl1= 6.601 Derek is less had descended like a Certain by the 1 sentences, 10 words, 0 OOVs 0 zeroprobs, logprob= -7.8412 ppl= 5.162 ppl1= 6.083 Darkness had descended like a Cecil aims by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -5.4012 ppl= 3.468 ppl1= 3.982 Darkness had descended like a Cecil arms by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -5.4012 ppl= 3.468 ppl1= 3.982 Darkness had descended like a Cecil aim by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -5.4012 ppl= 3.468 ppl1= 3.982 Darkness had descended like a Court arm by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.2817 ppl= 5.348 ppl1= 6.443 Derek no less had descended like a Certain by the 1 sentences, 10 words, 0 OOVs 0 zeroprobs, logprob= -7.8412 ppl= 5.162 ppl1= 6.083 Darkness had descended like a Curtain boy the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.0156 ppl= 3.608 ppl1= 4.236 Dave lawless had descended like a Certain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.6266 ppl= 5.790 ppl1= 7.037 Darkness had descended like a Certain by He 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.1263 ppl= 3.712 ppl1= 4.373 Darkness had descended like a Curtain , by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -5.1562 ppl= 3.278 ppl1= 3.740 Darkness had descended like a Certain by she 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.1263 ppl= 3.712 ppl1= 4.373 Dusk was s had descended like a Certain by the 1 sentences, 10 words, 0 OOVs 0 zeroprobs, logprob= -7.2561 ppl= 4.567 ppl1= 5.316 Darkness had descended like a Curtain way he 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -4.0913 ppl= 2.848 ppl1= 3.246 Plazek unless had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -6.4318 ppl= 4.397 ppl1= 5.184 Darkness had descended like a Curtain May the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.0156 ppl= 3.608 ppl1= 4.236 Darkness had descended like a Curtain Lay the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.0156 ppl= 3.608 ppl1= 4.236 Darkness had descended like a Certainly the 1 sentences, 7 words, 0 OOVs 0 zeroprobs, logprob= -4.9133 ppl= 4.113 ppl1= 5.034 Derek was 5 had descended like a Curtain by the 1 sentences, 10 words, 0 OOVs 0 zeroprobs, logprob= -5.6723 ppl= 3.278 ppl1= 3.692 Darkness had descended like a Cecil arm lay the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -6.4279 ppl= 4.393 ppl1= 5.179 Derek unless had descended Like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -3.1013 ppl= 2.042 ppl1= 2.211 Darkness had descended like a Clint an by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -6.5310 ppl= 4.499 ppl1= 5.317 Darkness had descended like a Clerk aims by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.2817 ppl= 5.348 ppl1= 6.443 Dusky less had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.3768 ppl= 5.466 ppl1= 6.601 Darkness had descended like a Clerk arms by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.2817 ppl= 5.348 ppl1= 6.443 Darkness had descended like a Curtain lay The 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -4.2674 ppl= 2.980 ppl1= 3.415 Darkness had descended like a Clerk aim by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.2817 ppl= 5.348 ppl1= 6.443 Darkness had descended like a Cherian by the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.0539 ppl= 3.644 ppl1= 4.283 Derek us less had descended like a Certain by the 1 sentences, 10 words, 0 OOVs 0 zeroprobs, logprob= -7.8412 ppl= 5.162 ppl1= 6.083 Dave Lawless had descended like a Certain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.6266 ppl= 5.790 ppl1= 7.037 Darkness had descended like a Kaukau by the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.0539 ppl= 3.644 ppl1= 4.283 Darkness had descended like a Curan by the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.0539 ppl= 3.644 ppl1= 4.283 Darkness had descended like an Curtain by the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.5497 ppl= 4.137 ppl1= 4.940 ' Darkness had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -5.2945 ppl= 3.384 ppl1= 3.875 Darkness had descended like a Cecil am by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -5.4012 ppl= 3.468 ppl1= 3.982 Darkness had descended like a Caetani by the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.0539 ppl= 3.644 ppl1= 4.283 Darkness had descended like a Curran by the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.0539 ppl= 3.644 ppl1= 4.283 Darkness had descended like a Certain boy the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.1714 ppl= 3.755 ppl1= 4.430 Darkness had descended like a Clint arm by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.2817 ppl= 5.348 ppl1= 6.443 Dave caress had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.3768 ppl= 5.466 ppl1= 6.601 Darkness had descended like a , Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -5.4140 ppl= 3.479 ppl1= 3.995 Due lawless had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.3768 ppl= 5.466 ppl1= 6.601 Dave kv less had descended like a Curtain by the 1 sentences, 10 words, 0 OOVs 0 zeroprobs, logprob= -9.6046 ppl= 7.467 ppl1= 9.130 Darkness had descended like a Curtain buy the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.0156 ppl= 3.608 ppl1= 4.236 Darkness had descended like a Court aims by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.2817 ppl= 5.348 ppl1= 6.443 Darkness had descended like a Court arms by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.2817 ppl= 5.348 ppl1= 6.443 Darkness , had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -5.1788 ppl= 3.295 ppl1= 3.762 Darkness had descended like a Clark an by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -6.5310 ppl= 4.499 ppl1= 5.317 Darkness had descended like a Court aim by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.2817 ppl= 5.348 ppl1= 6.443 Darkness had descended like a Curtain by She 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.0983 ppl= 3.685 ppl1= 4.338 D merciless had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -7.3768 ppl= 5.466 ppl1= 6.601 Dark unless had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -6.4318 ppl= 4.397 ppl1= 5.184 " Darkness had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -5.2945 ppl= 3.384 ppl1= 3.875 Dusk unless had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -6.4318 ppl= 4.397 ppl1= 5.184 Darkness had descended like a Clerk arm lay the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -8.3085 ppl= 6.774 ppl1= 8.378 Darkness " had descended like a Curtain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -5.1788 ppl= 3.295 ppl1= 3.762 Derek we ss had descended like a Curtain by the 1 sentences, 10 words, 0 OOVs 0 zeroprobs, logprob= -7.5914 ppl= 4.899 ppl1= 5.743 Darkness had descended Like a Cecil an by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -3.4277 ppl= 2.202 ppl1= 2.404 Dave kw less had descended like a Curtain by the 1 sentences, 10 words, 0 OOVs 0 zeroprobs, logprob= -9.6046 ppl= 7.467 ppl1= 9.130 Darkness had descended like a Certain way he 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -6.4261 ppl= 5.176 ppl1= 6.357 Plazek unless had descended like a Certain by the 1 sentences, 9 words, 0 OOVs 0 zeroprobs, logprob= -6.6817 ppl= 4.658 ppl1= 5.526 Darkness had descended like a Certain May the 1 sentences, 8 words, 0 OOVs 0 zeroprobs, logprob= -5.1714 ppl= 3.755 ppl1= 4.430 file best100.filt: 100 sentences, 877 words, 0 OOVs 0 zeroprobs, logprob= -536.837259 ppl= 3.543849 ppl1= 4.093824 april-ann-0.4.1/packages/language_model/LM_interface/test/result_bunch.txt000066400000000000000000000032301263004425400266610ustar00rootroot00000000000000-2.0437868237495 -2.6191517412663 -4.522134333849 -4.6626360714436 -5.0329623222351 -5.5841127932072 -5.2380009889603 -4.8909657895565 -4.1948205530643 -4.7826144099236 -4.1948205530643 -6.390681181103 -5.6975341774523 -4.2593594491482 -4.7338242977858 -5.1348283290863 -4.2593594491482 -4.8909657895565 -6.9660460986197 -6.272899094969 -11.636939078569 -12.34985235706 -12.190954744816 -12.436771661043 -17.479742322117 -17.479742322117 -16.98561624065 -10.109920367599 -15.038136094809 -11.739304333925 -16.766829043627 -11.739304333925 -16.132390175015 -16.766829043627 -15.038136094809 -12.925217274576 -12.766319662333 -17.479742322117 -16.98561624065 -18.055107239634 -12.436771661043 -12.436771661043 -12.436771661043 -16.766829043627 -18.055107239634 -11.548783048987 -17.560981158167 -11.803843706846 -11.87250456214 -11.803843706846 -16.707755092531 -9.4205735325813 -14.809808939695 -11.548783048987 -11.548783048987 -11.313217565417 -13.061020169407 -14.800897240639 -7.140983581543 -15.038136094809 -16.766829043627 -16.98561624065 -16.766829043627 -9.8260381817818 -16.766829043627 -11.636939078569 -18.055107239634 -17.560981158167 -11.636939078569 -11.636939078569 -12.778741359711 -12.190954744816 -12.436771661043 -11.636939078569 -11.636939078569 -11.907603308558 -16.766829043627 -16.98561624065 -12.466213226318 -16.98561624065 -22.115506205708 -11.548783048987 -16.766829043627 -16.766829043627 -11.924720082432 -15.038136094809 -16.766829043627 -11.739304333925 -16.98561624065 -14.809808939695 -12.190954744816 -14.809808939695 -19.130954623222 -11.924720082432 -17.479742322117 -7.8925611972809 -22.115506205708 -14.796669602394 -15.385173857212 -11.907603308558 april-ann-0.4.1/packages/language_model/LM_interface/test/result_no_bunch.txt000066400000000000000000000032301263004425400273550ustar00rootroot00000000000000-2.0437868237495 -2.6191517412663 -4.522134333849 -4.6626360714436 -5.0329623222351 -5.5841127932072 -5.2380009889603 -4.8909657895565 -4.1948205530643 -4.7826144099236 -4.1948205530643 -6.390681181103 -5.6975341774523 -4.2593594491482 -4.7338242977858 -5.1348283290863 -4.2593594491482 -4.8909657895565 -6.9660460986197 -6.272899094969 -11.636939078569 -12.34985235706 -12.190954744816 -12.436771661043 -17.479742322117 -17.479742322117 -16.98561624065 -10.109920367599 -15.038136094809 -11.739304333925 -16.766829043627 -11.739304333925 -16.132390175015 -16.766829043627 -15.038136094809 -12.925217274576 -12.766319662333 -17.479742322117 -16.98561624065 -18.055107239634 -12.436771661043 -12.436771661043 -12.436771661043 -16.766829043627 -18.055107239634 -11.548783048987 -17.560981158167 -11.803843706846 -11.87250456214 -11.803843706846 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april-ann-0.4.1/packages/language_model/ngram_lira/000077500000000000000000000000001263004425400222315ustar00rootroot00000000000000april-ann-0.4.1/packages/language_model/ngram_lira/binding/000077500000000000000000000000001263004425400236435ustar00rootroot00000000000000april-ann-0.4.1/packages/language_model/ngram_lira/binding/bind_arpa2lira.lua.cc000066400000000000000000000075441263004425400276150ustar00rootroot00000000000000//BIND_HEADER_H #include "arpa2lira.h" using LanguageModels::arpa2lira::Transition; using LanguageModels::arpa2lira::TransitionsType; using LanguageModels::arpa2lira::TransitionsIterator; using LanguageModels::arpa2lira::State2Transitions; using LanguageModels::arpa2lira::VectorReferenced; //BIND_END //BIND_HEADER_C using AprilUtils::vector; using AprilUtils::log_float; //BIND_END //////////////////////////////////// //BIND_LUACLASSNAME VectorReferenced ngram.lira.arpa2lira.VectorReferenced //BIND_CPP_CLASS VectorReferenced //BIND_CONSTRUCTOR VectorReferenced { LUABIND_ERROR("FORBIDDEN\n"); exit(128); } //BIND_END //BIND_METHOD VectorReferenced size { LUABIND_RETURN(uint, obj->v.size()); } //BIND_END //BIND_METHOD VectorReferenced get { unsigned int idx; LUABIND_GET_PARAMETER(1, uint, idx); LUABIND_RETURN(uint, obj->v[idx-1].state); LUABIND_RETURN(uint, obj->v[idx-1].word); LUABIND_RETURN(float, obj->v[idx-1].prob.log()); } //BIND_END //BIND_METHOD VectorReferenced set { unsigned int idx; uint32_t state,word; float lprob; LUABIND_GET_PARAMETER(1, uint, idx); LUABIND_GET_PARAMETER(2, uint, state); LUABIND_GET_PARAMETER(3, uint, word); LUABIND_GET_PARAMETER(4, float, lprob); obj->v[idx-1].state = state; obj->v[idx-1].word = word; obj->v[idx-1].prob = log_float(lprob); } //BIND_END //BIND_METHOD VectorReferenced sortByWordId { obj->sortByWordId(); } //BIND_END //////////////////////////////////// //BIND_LUACLASSNAME TransitionsIterator ngram.lira.arpa2lira.TransitionsIterator //BIND_CPP_CLASS TransitionsIterator //BIND_CONSTRUCTOR TransitionsIterator { LUABIND_ERROR("FORBIDDEN\n"); exit(128); } //BIND_END //BIND_METHOD TransitionsIterator getState { LUABIND_RETURN(uint, obj->getState()); } //BIND_END //BIND_METHOD TransitionsIterator getTransitions { VectorReferenced *v = new VectorReferenced(obj->getTransitions()); LUABIND_RETURN(VectorReferenced, v); } //BIND_END //BIND_METHOD TransitionsIterator next { obj->next(); } //BIND_END //BIND_METHOD TransitionsIterator notEqual { TransitionsIterator *other; LUABIND_GET_PARAMETER(1, TransitionsIterator, other); LUABIND_RETURN(bool, obj->notEqual(other)); } //BIND_END //////////////////////////////////// //BIND_LUACLASSNAME State2Transitions ngram.lira.arpa2lira.State2Transitions //BIND_CPP_CLASS State2Transitions //BIND_CONSTRUCTOR State2Transitions { obj = new State2Transitions(); LUABIND_RETURN(State2Transitions, obj); } //BIND_END //BIND_METHOD State2Transitions exists { unsigned int st; LUABIND_GET_PARAMETER(1, uint, st); bool ret = obj->exists(st); LUABIND_RETURN(bool, ret); } //BIND_END //BIND_METHOD State2Transitions create { unsigned int st; LUABIND_GET_PARAMETER(1, uint, st); obj->create(st); } //BIND_END //BIND_METHOD State2Transitions insert { unsigned int orig_st, dest_st, word; float lprob; LUABIND_GET_PARAMETER(1, uint, orig_st); LUABIND_GET_PARAMETER(2, uint, dest_st); LUABIND_GET_PARAMETER(3, uint, word); LUABIND_GET_PARAMETER(4, float, lprob); obj->insert(orig_st, dest_st, word, log_float(lprob)); } //BIND_END //BIND_METHOD State2Transitions beginIt { TransitionsIterator it = obj->begin(); TransitionsIterator *ptr_it = new TransitionsIterator(it); LUABIND_RETURN(TransitionsIterator, ptr_it); } //BIND_END //BIND_METHOD State2Transitions endIt { TransitionsIterator it = obj->end(); TransitionsIterator *ptr_it = new TransitionsIterator(it); LUABIND_RETURN(TransitionsIterator, ptr_it); } //BIND_END //BIND_METHOD State2Transitions erase { unsigned int st; LUABIND_GET_PARAMETER(1, uint, st); obj->erase(st); } //BIND_END //BIND_METHOD State2Transitions getTransitions { unsigned int st; LUABIND_GET_PARAMETER(1, uint, st); TransitionsType &t = obj->getTransitions(st); VectorReferenced *v = new VectorReferenced(t); LUABIND_RETURN(VectorReferenced, v); } //BIND_END april-ann-0.4.1/packages/language_model/ngram_lira/binding/bind_ngram_lira.lua.cc000066400000000000000000000221341263004425400300430ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "bind_april_io.h" #include "bind_LM_interface.h" #include "bind_util.h" using namespace AprilUtils; using namespace AprilIO; //BIND_END //BIND_HEADER_H #include "bind_LM_interface.h" #include "history_based_LM.h" #include "history_based_ngram_lira.h" #include "bunch_hashed_LM.h" #include "bunch_hashed_ngram_lira.h" #include "ngram_lira.h" using namespace LanguageModels; //BIND_END //BIND_LUACLASSNAME LMModelUInt32LogFloat language_models.model //BIND_LUACLASSNAME LMInterfaceUInt32LogFloat language_models.interface //BIND_LUACLASSNAME HistoryBasedLMUInt32LogFloat language_models.history_based_model //BIND_LUACLASSNAME HistoryBasedLMInterfaceUInt32LogFloat language_models.history_based_interface //BIND_LUACLASSNAME BunchHashedLMUInt32LogFloat language_models.bunch_hashed_model //BIND_LUACLASSNAME BunchHashedLMInterfaceUInt32LogFloat language_models.bunch_hashed_interface /////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME NgramLiraModel ngram.lira.model //BIND_CPP_CLASS NgramLiraModel //BIND_SUBCLASS_OF NgramLiraModel LMModelUInt32LogFloat //BIND_LUACLASSNAME NgramLiraInterface ngram.lira.interface //BIND_CPP_CLASS NgramLiraInterface //BIND_SUBCLASS_OF NgramLiraInterface LMInterfaceUInt32LogFloat //BIND_CONSTRUCTOR NgramLiraModel { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "binary", // boolean "stream", // opens a stream "filename", "vocabulary", "final_word", "fan_out_threshold", // sirve para permitir que el diccionario que te // pasan sea mas grande que el que hay en el // modelo lira "ignore_extra_words_in_dictionary", (const char *)0); // 0 para terminar el check_table_fields // bool ignore_extra_words_in_dictionary = false; bool binary = false; const char *filename; SharedPtr stream; NgramLiraModel *obj=0; LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, binary, bool, binary, false); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, filename, string, filename, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, stream, AuxStreamInterface, stream, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, ignore_extra_words_in_dictionary, bool, ignore_extra_words_in_dictionary, false); lua_getfield(L,1,"vocabulary"); if (lua_isnil(L,-1)) { LUABIND_ERROR("error ngram.lira.model constructor requires vocabulary table"); } int vocabulary_size, final_word; LUABIND_GET_TABLE_PARAMETER(1, final_word, int, final_word); LUABIND_TABLE_GETN(-1, vocabulary_size); const char **vocabulary_vector = new const char *[vocabulary_size]; LUABIND_TABLE_TO_VECTOR(-1, string, vocabulary_vector, vocabulary_size); if (binary) { obj=new NgramLiraModel(filename, (unsigned int)vocabulary_size, vocabulary_vector, final_word, ignore_extra_words_in_dictionary); } else { int fan_out_threshold; LUABIND_GET_TABLE_PARAMETER(1, fan_out_threshold, int, fan_out_threshold); if (stream.empty()) { stream = new FileStream(filename, "r"); if (stream->hasError()) { LUABIND_FERROR1("unable to open %s\n",filename); } } obj=new NgramLiraModel(stream.get(), (unsigned int)vocabulary_size, vocabulary_vector, final_word, fan_out_threshold, ignore_extra_words_in_dictionary); } delete[] vocabulary_vector; LUABIND_RETURN(NgramLiraModel, obj); } //BIND_END //BIND_DESTRUCTOR NgramLiraModel { } //BIND_END //BIND_METHOD NgramLiraModel save_binary { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "filename", "vocabulary", (const char *)0); // 0 para terminar el check_table_fields // const char *filename; LUABIND_GET_TABLE_PARAMETER(1, filename, string, filename); lua_getfield(L,1,"vocabulary"); if (lua_isnil(L,-1)) { LUABIND_ERROR("error save_binary method requires vocabulary table"); } int vocabulary_size; LUABIND_TABLE_GETN(-1, vocabulary_size); const char **vocabulary_vector = new const char *[vocabulary_size]; LUABIND_TABLE_TO_VECTOR(-1, string, vocabulary_vector, vocabulary_size); obj->saveBinary(filename, (unsigned int)vocabulary_size, vocabulary_vector); delete[] vocabulary_vector; } //BIND_END //BIND_CLASS_METHOD NgramLiraModel loop { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "vocabulary_size", "final_word", (const char *)0); // 0 para terminar el check_table_fields // int vocabulary_size, final_word; LUABIND_GET_TABLE_PARAMETER(1, vocabulary_size, int, vocabulary_size); LUABIND_GET_TABLE_PARAMETER(1, final_word, int, final_word); NgramLiraModel *obj=new NgramLiraModel((unsigned int)vocabulary_size, (unsigned int)final_word); LUABIND_RETURN(NgramLiraModel, obj); } //BIND_END ////////////////////////////////////////////////////////////////////////// //BIND_CONSTRUCTOR NgramLiraInterface { LUABIND_ERROR("Use the model method get_interface"); } //BIND_END //BIND_METHOD NgramLiraInterface non_backoff_arcs_iterator { unsigned int key; LUABIND_GET_PARAMETER(1, uint, key); float log_threshold; LUABIND_GET_OPTIONAL_PARAMETER(2, float, log_threshold, log_float::zero().log()); log_float threshold = log_float(log_threshold); LMInterfaceUInt32LogFloat::ArcsIterator arcs_it = obj->beginNonBackoffArcs(key, threshold); LuaArcsIteratorUInt32Logfloat *lua_arcs_it = new LuaArcsIteratorUInt32Logfloat(obj, arcs_it); LUABIND_RETURN(LuaArcsIteratorUInt32Logfloat, lua_arcs_it); } //BIND_END ////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME HistoryBasedNgramLiraLM ngram.lira.history_based_model //BIND_CPP_CLASS HistoryBasedNgramLiraLM //BIND_SUBCLASS_OF HistoryBasedNgramLiraLM HistoryBasedLMUInt32LogFloat //BIND_LUACLASSNAME HistoryBasedNgramLiraLMInterface ngram.lira.history_based_interface //BIND_CPP_CLASS HistoryBasedNgramLiraLMInterface //BIND_SUBCLASS_OF HistoryBasedNgramLiraLMInterface HistoryBasedLMInterfaceUInt32LogFloat //BIND_CONSTRUCTOR HistoryBasedNgramLiraLM { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "init_word_id", "trie_vector", "lira_model", (const char *)0); unsigned int init_word_id; TrieVector *trie_vector; NgramLiraModel *lira_model; LUABIND_GET_TABLE_PARAMETER(1, init_word_id, uint, init_word_id); LUABIND_GET_TABLE_PARAMETER(1, trie_vector, TrieVector, trie_vector); LUABIND_GET_TABLE_PARAMETER(1, lira_model, NgramLiraModel, lira_model); obj = new HistoryBasedNgramLiraLM(init_word_id, trie_vector, lira_model); LUABIND_RETURN(HistoryBasedNgramLiraLM, obj); } //BIND_END ////////////////////////////////////////////////////////////////////////// //BIND_CONSTRUCTOR HistoryBasedNgramLiraLMInterface { LUABIND_ERROR("Use the model method get_interface"); } //BIND_END ////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME BunchHashedNgramLiraLM ngram.lira.bunch_hashed_model //BIND_CPP_CLASS BunchHashedNgramLiraLM //BIND_SUBCLASS_OF BunchHashedNgramLiraLM BunchHashedLMUInt32LogFloat //BIND_LUACLASSNAME BunchHashedNgramLiraLMInterface ngram.lira.bunch_hashed_interface //BIND_CPP_CLASS BunchHashedNgramLiraLMInterface //BIND_SUBCLASS_OF BunchHashedNgramLiraLMInterface BunchHashedLMInterfaceUInt32LogFloat //BIND_CONSTRUCTOR BunchHashedNgramLiraLM { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "bunch_size", "lira_model", (const char *)0); unsigned int bunch_size; NgramLiraModel *lira_model; LUABIND_GET_TABLE_PARAMETER(1, bunch_size, uint, bunch_size); LUABIND_GET_TABLE_PARAMETER(1, lira_model, NgramLiraModel, lira_model); obj = new BunchHashedNgramLiraLM(bunch_size, lira_model); LUABIND_RETURN(BunchHashedNgramLiraLM, obj); } //BIND_END ////////////////////////////////////////////////////////////////////////// //BIND_CONSTRUCTOR BunchHashedNgramLiraLMInterface { LUABIND_ERROR("Use the model method get_interface"); } //BIND_END april-ann-0.4.1/packages/language_model/ngram_lira/c_src/000077500000000000000000000000001263004425400233225ustar00rootroot00000000000000april-ann-0.4.1/packages/language_model/ngram_lira/c_src/arpa2lira.h000066400000000000000000000074241263004425400253570ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef ARPA2LIRA_H #define ARPA2LIRA_H #include #include "hash_table.h" #include "vector.h" #include "referenced.h" #include "qsort.h" namespace LanguageModels { /// Arpa2Lira implementa estructuras de datos necesarias para /// convertir los Arpa en nuestro formato interno Lira namespace arpa2lira { /// Una transicion en el automata tiene: /// - estado destino, palabra, probabilidad struct Transition { uint32_t state, word; AprilUtils::log_float prob; /// oprdena por ID de las palabras bool operator<(const Transition &other) const { return word < other.word; } }; /// tipos utiles typedef AprilUtils::vector TransitionsType; typedef AprilUtils::hash HashType; /// permite tener los vectores de transiciones en Lua struct VectorReferenced : public Referenced { TransitionsType &v; VectorReferenced(TransitionsType &v) : v(v) { } void sortByWordId() { AprilUtils::Sort(v.begin(), v.size()); } }; /// Iterador de transiciones: util para iterar sobre la tabla hash /// en Lua class TransitionsIterator : public Referenced { HashType::iterator it; public: TransitionsIterator(HashType::iterator it) : it(it) { } void next() { it++; } TransitionsType &getTransitions() { return it->second; } uint32_t getState() { return it->first; } bool notEqual(TransitionsIterator *other) const { return other->it != it; } /// OJO: idx empieza en 0 void set(uint32_t idx, uint32_t state, uint32_t word, AprilUtils::log_float prob) { it->second[idx].state = state; it->second[idx].word = word; it->second[idx].prob = prob; } }; /// Clase que permite asociar a un estado un vector de transiciones class State2Transitions : public Referenced { /// tabla Hash HashType data; public: State2Transitions() { } ~State2Transitions() { } bool exists(uint32_t st) { return data.find(st) != 0; } void create(uint32_t st) { TransitionsType &t = data[st]; t.clear(); } void insert(uint32_t orig_state, uint32_t dest_state, uint32_t word, AprilUtils::log_float prob) { Transition t; t.state = dest_state; t.word = word; t.prob = prob; data[orig_state].push_back(t); } void erase(uint32_t st) { data.erase(st); } TransitionsIterator begin() { return TransitionsIterator(data.begin()); } TransitionsIterator end() { return TransitionsIterator(data.end()); } TransitionsType &getTransitions(uint32_t st) { return data[st]; } }; } // namespace arpa2lira } // namespace LanguageModels #endif // ARPA2LIRA_H april-ann-0.4.1/packages/language_model/ngram_lira/c_src/bunch_hashed_ngram_lira.cc000066400000000000000000000075351263004425400304510ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "bunch_hashed_ngram_lira.h" #include "unused_variable.h" using namespace AprilUtils; namespace LanguageModels { typedef NgramLiraModel::Key Key; typedef NgramLiraModel::Score Score; BunchHashedNgramLiraLMInterface:: BunchHashedNgramLiraLMInterface(BunchHashedNgramLiraLM *model, NgramLiraModel *lira_model) : BunchHashedLMInterface(model) { lira_interface = static_cast(lira_model->getInterface()); IncRef(lira_interface); } BunchHashedNgramLiraLMInterface:: ~BunchHashedNgramLiraLMInterface() { DecRef(lira_interface); } Score BunchHashedNgramLiraLMInterface:: getBestProb() const { return lira_interface->getBestProb(); } Score BunchHashedNgramLiraLMInterface:: getBestProb(Key k) { return lira_interface->getBestProb(k); } Score BunchHashedNgramLiraLMInterface:: getFinalScore(Key k, Score threshold) { return lira_interface->getFinalScore(k, threshold); } bool BunchHashedNgramLiraLMInterface:: getZeroKey(Key &k) const { return lira_interface->getZeroKey(k); } Key BunchHashedNgramLiraLMInterface:: getInitialKey() { return lira_interface->getInitialKey(); } void BunchHashedNgramLiraLMInterface:: get(Key key, WordType word, Burden burden, vector &result, Score threshold) { lira_interface->get(key, word, burden, result, threshold); } void BunchHashedNgramLiraLMInterface:: computeKeysAndScores(KeyWordHash &ctxt_hash, unsigned int bunch_size) { UNUSED_VARIABLE(bunch_size); // For each context key entry for (KeyWordHash::iterator it = ctxt_hash.begin(); it != ctxt_hash.end(); ++it) { Key context_key = it->first; WordResultHash &word_hash = it->second; // For each word entry for (WordResultHash::iterator it2 = word_hash.begin(); it2 != word_hash.end(); ++it2) { vector tmp_result; WordType word = it2->first; KeyScoreMultipleBurdenTuple &result_tuple = it2->second; lira_interface->get(context_key, word, Burden(-1, -1), tmp_result, Score::zero()); if (tmp_result.size() != 1) ERROR_EXIT(127, "Multiple or zero results from lira!\n"); result_tuple.key_score.key = tmp_result[0].key_score.key; result_tuple.key_score.score = tmp_result[0].key_score.score; } } } //////////////////////////////////////////////////////////////////////////// BunchHashedNgramLiraLM:: BunchHashedNgramLiraLM(unsigned int bunch_size, NgramLiraModel *lira_model) : BunchHashedLM(lira_model->ngramOrder(), bunch_size), lira_model(lira_model) { IncRef(lira_model); } BunchHashedNgramLiraLM::~BunchHashedNgramLiraLM() { DecRef(lira_model); } LMInterface* BunchHashedNgramLiraLM::getInterface() { return new BunchHashedNgramLiraLMInterface(this, lira_model); } } // closes namespace language_models april-ann-0.4.1/packages/language_model/ngram_lira/c_src/bunch_hashed_ngram_lira.h000066400000000000000000000052151263004425400303040ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef BUNCH_HASHED_NGRAM_LIRA_H #define BUNCH_HASHED_NGRAM_LIRA_H #include "bunch_hashed_LM.h" #include "ngram_lira.h" namespace LanguageModels { class BunchHashedNgramLiraLM; class BunchHashedNgramLiraLMInterface : public BunchHashedLMInterface< NgramLiraModel::Key, NgramLiraModel::Score > { public: typedef NgramLiraModel::Key Key; typedef NgramLiraModel::Score Score; virtual ~BunchHashedNgramLiraLMInterface(); virtual Score getBestProb() const; virtual Score getBestProb(Key k); virtual Score getFinalScore(Key k, Score threshold); virtual bool getZeroKey(Key &k) const; virtual Key getInitialKey(); virtual void get(Key key, WordType word, Burden burden, AprilUtils::vector &result, Score threshold); protected: friend class BunchHashedNgramLiraLM; BunchHashedNgramLiraLMInterface(BunchHashedNgramLiraLM *model, NgramLiraModel *lira_model); virtual void computeKeysAndScores(KeyWordHash &ctxt_hash, unsigned int bunch_size); private: NgramLiraInterface *lira_interface; }; class BunchHashedNgramLiraLM : public BunchHashedLM { public: typedef NgramLiraModel::Key Key; typedef NgramLiraModel::Score Score; private: NgramLiraModel *lira_model; public: BunchHashedNgramLiraLM(unsigned int bunch_size, NgramLiraModel *lira_model); virtual ~BunchHashedNgramLiraLM(); virtual LMInterface* getInterface(); }; } // closes namespace language_models #endif // BUNCH_HASHED_NGRAM_LIRA_H april-ann-0.4.1/packages/language_model/ngram_lira/c_src/history_based_ngram_lira.cc000066400000000000000000000070701263004425400306670ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "history_based_ngram_lira.h" #include "unused_variable.h" using namespace AprilUtils; namespace LanguageModels { typedef NgramLiraModel::Key Key; typedef NgramLiraModel::Score Score; HistoryBasedNgramLiraLMInterface:: HistoryBasedNgramLiraLMInterface(HistoryBasedNgramLiraLM *model, NgramLiraModel *lira_model) : HistoryBasedLMInterface(model) { lira_interface = static_cast(lira_model->getInterface()); IncRef(lira_interface); } HistoryBasedNgramLiraLMInterface:: ~HistoryBasedNgramLiraLMInterface() { DecRef(lira_interface); } bool HistoryBasedNgramLiraLMInterface:: privateBestProb(Key k, const WordType *context_words, unsigned int context_size, Score &score) { UNUSED_VARIABLE(k); Key lira_k = lira_interface->findKeyFromNgram(context_words, context_size); score = lira_interface->getBestProb(lira_k); return true; } bool HistoryBasedNgramLiraLMInterface:: privateGetFinalScore(Key key, const WordType *context_words, unsigned int context_size, Score threshold, Score &score) { UNUSED_VARIABLE(key); UNUSED_VARIABLE(threshold); Key lira_k = lira_interface->findKeyFromNgram(context_words, context_size); score = lira_interface->getFinalScore(lira_k, Score::zero()); return true; } bool HistoryBasedNgramLiraLMInterface:: privateGet(Key key, WordType word, const WordType *context_words, unsigned int context_size, Score threshold, Score &score) { UNUSED_VARIABLE(key); UNUSED_VARIABLE(threshold); vector result; Key st = lira_interface->findKeyFromNgram(context_words, context_size); lira_interface->get(st, word, Burden(-1, -1), result, Score::zero()); score = result[0].key_score.score; return true; } Score HistoryBasedNgramLiraLMInterface:: privateBestProb() const { return lira_interface->getBestProb(); } //////////////////////////////////////////////////////////////////////////// HistoryBasedNgramLiraLM:: HistoryBasedNgramLiraLM(WordType init_word, AprilUtils::TrieVector *trie_vector, NgramLiraModel *lira_model) : HistoryBasedLM(lira_model->ngramOrder(), init_word, trie_vector), lira_model(lira_model) { IncRef(lira_model); } HistoryBasedNgramLiraLM::~HistoryBasedNgramLiraLM() { DecRef(lira_model); } LMInterface* HistoryBasedNgramLiraLM::getInterface() { return new HistoryBasedNgramLiraLMInterface(this, lira_model); } } // closes namespace language_models april-ann-0.4.1/packages/language_model/ngram_lira/c_src/history_based_ngram_lira.h000066400000000000000000000060121263004425400305240ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef HISTORY_BASED_NGRAM_LIRA_H #define HISTORY_BASED_NGRAM_LIRA_H #include "history_based_LM.h" #include "ngram_lira.h" namespace LanguageModels { class HistoryBasedNgramLiraLM; class HistoryBasedNgramLiraLMInterface : public HistoryBasedLMInterface< NgramLiraModel::Key, NgramLiraModel::Score > { public: typedef NgramLiraModel::Key Key; typedef NgramLiraModel::Score Score; virtual ~HistoryBasedNgramLiraLMInterface(); protected: friend class HistoryBasedNgramLiraLM; HistoryBasedNgramLiraLMInterface(HistoryBasedNgramLiraLM *model, NgramLiraModel *lira_model); virtual bool privateBestProb(Key k, const WordType *context_words, unsigned int context_size, Score &score); virtual Score privateBestProb() const; virtual bool privateGetFinalScore(Key key, const WordType *context_words, unsigned int context_size, Score threshold, Score &score); virtual bool privateGet(Key key, WordType word, const WordType *context_words, unsigned int context_size, Score threshold, Score &score); private: NgramLiraInterface *lira_interface; }; class HistoryBasedNgramLiraLM : public HistoryBasedLM { public: typedef NgramLiraModel::Key Key; typedef NgramLiraModel::Score Score; private: NgramLiraModel *lira_model; public: HistoryBasedNgramLiraLM(WordType init_word, AprilUtils::TrieVector *trie_vector, NgramLiraModel *lira_model); virtual ~HistoryBasedNgramLiraLM(); virtual LMInterface* getInterface(); }; } // closes namespace language_models #endif // HISTORY_BASED_NGRAM_LIRA_H april-ann-0.4.1/packages/language_model/ngram_lira/c_src/ngram_lira.cc000066400000000000000000000626621263004425400257600ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "april_assert.h" #include "c_string.h" #include "error_print.h" // print errors #include "ngram_lira.h" #include "smart_ptr.h" #include "uncommented_line.h" // read data #include #include // exit #include // strcmp extern "C" { #include #include #include // mmap() is defined in this header #include #include } using namespace AprilUtils; using namespace AprilIO; namespace LanguageModels { // format errors are NOT checked!!! NgramLiraModel::NgramLiraModel(StreamInterface *fd, unsigned int expected_vocabulary_size, const char *expected_vocabulary[], WordType final_word, int fan_out_threshold, bool ignore_extra_words_in_dictionary) : ignore_extra_words_in_dictionary(ignore_extra_words_in_dictionary), fan_out_threshold(fan_out_threshold), is_mmapped(false), final_word(final_word) { // these values will be changed later transition_words_table = 0; transition_table = 0; linear_search_table = 0; backoff_table = 0; max_out_prob = 0; first_state_binary_search = 0; AprilUtils::SharedPtr buffer( new CStringStream() ); float aux; //NgramLiraTransition emptyTransition; //---------------------------------------------------------------------- // # number of words and words extractULineFromStream(fd, buffer.get()); sscanf(buffer->c_str(),"%u",&vocabulary_size); // TODO: // if (vocabulary_size > emptyTransition.maxWordIndex()) { // ERROR_PRINT2("excessive vocabulary size %u >= %u\n", // vocabulary_size, emptyTransition.maxWordIndex()); // exit(128); // } if (!ignore_extra_words_in_dictionary && expected_vocabulary && expected_vocabulary_size != vocabulary_size) { ERROR_PRINT2("Expected vocabulary_size %u instead of %u\n", expected_vocabulary_size, vocabulary_size); exit(1); } for (unsigned int i=0;ic_str(),expected_vocabulary[i])!=0) { ERROR_PRINT3("word %u is '%s' instead of '%s'\n", i,buffer->c_str(),expected_vocabulary[i]); exit(1); } } } //---------------------------------------------------------------------- // # max order of n-gram extractULineFromStream(fd, buffer.get()); unsigned int n; sscanf(buffer->c_str(),"%u",&n); ngram_value = n; //---------------------------------------------------------------------- // # number of states extractULineFromStream(fd, buffer.get()); sscanf(buffer->c_str(),"%u",&num_states); //---------------------------------------------------------------------- // # number of transitions extractULineFromStream(fd, buffer.get()); sscanf(buffer->c_str(),"%u",&num_transitions); transition_words_table = new WordType[num_transitions]; transition_table = new NgramLiraTransition[num_transitions]; //---------------------------------------------------------------------- // # bound max trans prob extractULineFromStream(fd, buffer.get()); sscanf(buffer->c_str(),"%f",&aux); best_prob = Score(aux); //---------------------------------------------------------------------- // # how many different number of transitions extractULineFromStream(fd, buffer.get()); sscanf(buffer->c_str(),"%u",&different_number_of_trans); linear_search_table = new LinearSearchInfo[different_number_of_trans+1]; // # "x y" means x states have y transitions // sorted by transitions from lower to upper int lss = 0; // linear_search_size int aux_first_state = 0; int aux_first_trans = 0; int how_many_states; int state_fan_out; for (unsigned int i=0;ic_str(),"%u%u",&how_many_states,&state_fan_out); if (state_fan_out <= fan_out_threshold) { // anyadimos otra entrada en la tabla linear_search_table[lss].first_state = aux_first_state; linear_search_table[lss].fan_out = state_fan_out; linear_search_table[lss].first_index = aux_first_trans; aux_first_state += how_many_states; aux_first_trans += state_fan_out*how_many_states; lss++; } } linear_search_size = lss; first_state_binary_search = aux_first_state; // valores centinela: linear_search_table[lss].first_state = aux_first_state; linear_search_table[lss].fan_out = state_fan_out; linear_search_table[lss].first_index = aux_first_trans; size_first_transition = num_states-first_state_binary_search; first_transition = new unsigned int[size_first_transition + 1]; first_transition -= first_state_binary_search; //---------------------------------------------------------------------- // # initial state, final state and lowest state extractULineFromStream(fd, buffer.get()); sscanf(buffer->c_str(),"%u%u%u",&initial_state,&final_state,&lowest_state); //---------------------------------------------------------------------- // # state backoff_st 'weight(state->backoff_st)' [max_transition_prob] // # backoff_st == -1 means there is no backoff backoff_table = new NgramBackoffInfo[num_states]; max_out_prob = new Score[num_states]; // no hace falta inicializar backoff_table explicitamente, por // defecto se pone bo_dest_state a 0 y bo_prob a Score::zero() for (unsigned int i=0;ic_str(),"%u%d%f%f", &orig,&bo_dest,&dbackoff,&maxOutProb); Score backoff; if (bo_dest >= 0) { backoff_table[orig].bo_prob = Score(dbackoff); backoff_table[orig].bo_dest_state = (unsigned int)bo_dest; } if (leidos == 4) { max_out_prob[orig] = Score(maxOutProb); } } //---------------------------------------------------------------------- // # transitions // # orig dest word prob unsigned int last_state = 0; // da igual for (unsigned int i=0;ic_str(),"%u%u%u%f",&orig,&dest,&word,&prob); if ((i==0 || orig > last_state) && // new or state is changed orig >= first_state_binary_search) { first_transition[orig] = i; } transition_words_table[i] = word; transition_table[i].state = dest; transition_table[i].prob = Score(prob); last_state = orig; } first_transition[num_states] = num_transitions; } NgramLiraModel::NgramLiraModel(int vocabulary_size, WordType final_word) : is_mmapped(false), final_word(final_word) { // creates a model with 2 stes, ordered by their fan_out: // // - state 0 -> final_state has fan_out 0 // // - state 1 -> lowest_state and initial_state at the same time, // the fan_out is vocabulary_size, it loops with any word // excepting final_word which is used to go to the final state ngram_value = 1; num_states = 2; num_transitions = vocabulary_size; // the 2 states: final_state = 0; initial_state = 1; lowest_state = 1; // best probability to go from each state: best_prob = Score::one(); max_out_prob = new Score[num_states]; max_out_prob[0] = Score::zero(); max_out_prob[1] = Score::one(); // backoff information backoff_table = new NgramBackoffInfo[num_states]; backoff_table[0].bo_prob = Score::zero(); backoff_table[0].bo_dest_state = 1; backoff_table[1].bo_prob = Score::zero(); backoff_table[1].bo_dest_state = 1; // linear search info: fan_out_threshold = 0; linear_search_size = 1; different_number_of_trans = 2; linear_search_table = new LinearSearchInfo[different_number_of_trans+1]; linear_search_table[0].first_state = 0; linear_search_table[0].fan_out = 0; linear_search_table[0].first_index = 0; // sentinel values: linear_search_table[1].first_state = 1; linear_search_table[1].fan_out = 0; linear_search_table[1].first_index = 0; // information about transitions: transition_words_table = new WordType[num_transitions]; transition_table = new NgramLiraTransition[num_transitions]; first_state_binary_search = lowest_state; size_first_transition = num_states-first_state_binary_search; first_transition = new unsigned int[size_first_transition + 1]; first_transition -= first_state_binary_search; first_transition[lowest_state] = 0; first_transition[num_states] = num_transitions; // let's generate the transitions: for (unsigned int i=0;imagic != 12345u) { ERROR_PRINT("Error magic value, endianism problem?\n"); exit(1); } ngram_value = header->ngram_value; vocabulary_size = header->vocabulary_size; initial_state = header->initial_state; final_state = header->final_state; lowest_state = header->lowest_state; num_states = header->num_states; num_transitions = header->num_transitions; different_number_of_trans = header->different_number_of_trans; linear_search_size = header->linear_search_size; fan_out_threshold = header->fan_out_threshold; first_state_binary_search = header->first_state_binary_search; size_first_transition = header->size_first_transition; best_prob = header->best_prob; // checking vocabulary: if (expected_vocabulary) { if (!ignore_extra_words_in_dictionary) { if (expected_vocabulary_size != vocabulary_size) { ERROR_PRINT2("Expected vocabulary_size %u instead of %u\n", expected_vocabulary_size, vocabulary_size); exit(1); } } char *dest_voc = filemapped+header->offset_vocabulary_vector; for (unsigned int i=0;ioffset_transition_words_table); transition_table = (NgramLiraTransition *)(filemapped + header->offset_transition_table); linear_search_table = (LinearSearchInfo*)(filemapped + header->offset_linear_search_table); backoff_table = (NgramBackoffInfo*)(filemapped + header->offset_backoff_table); max_out_prob = (Score*)(filemapped + header->offset_max_out_prob); first_transition = (unsigned int*)(filemapped + header->offset_first_transition) - first_state_binary_search; // at this point, all seems to be ok :) } LMInterfaceUInt32LogFloat* NgramLiraModel::getInterface() { return new NgramLiraInterface(this); } /////////////////////////////////////////////////////////////////////////// void NgramLiraInterface::get(Key state, WordType word, Burden burden, vector &result, Score threshold) { NgramLiraModel *lira_model = static_cast(model); april_assert(word != 0); UNUSED_VARIABLE(threshold); Score accum_backoff = Score::one(); unsigned int st = state; for (;;) { if (st < lira_model->first_state_binary_search) { int linear_index = 0; while(lira_model->linear_search_table[linear_index].first_state <= st) linear_index++; // -1 because the search stopped too late ;) LinearSearchInfo *info = &(lira_model->linear_search_table[linear_index-1]); // range of transitions during the search: unsigned int first_tr_index = (st - info->first_state)*info->fan_out + info->first_index; unsigned int last_tr_index = first_tr_index + info->fan_out; // lineal search: for (unsigned int tr_index = first_tr_index; tr_index < last_tr_index; tr_index++) if (lira_model->transition_words_table[tr_index] == word) { result.push_back(KeyScoreBurdenTuple(lira_model->transition_table[tr_index].state, accum_backoff * lira_model->transition_table[tr_index].prob, burden)); return; } } else { // the dichotomic search of the transition index is not based // on the binary_search template in order to be able to return // as soon as the word is found unsigned int left = lira_model->first_transition[st]; unsigned int right = lira_model->first_transition[st+1] - 1; while (left <= right) { unsigned int tr_index = (left+right)/2; unsigned int current_word = lira_model->transition_words_table[tr_index]; if (current_word == word) { result.push_back(KeyScoreBurdenTuple(lira_model->transition_table[tr_index].state, accum_backoff * lira_model->transition_table[tr_index].prob, burden)); return; } else if (current_word < word) { left = tr_index+1; } else { right = tr_index-1; } } } // apply backoff when the transition is not found: if (st == lira_model->lowest_state) { // this is impossible, throws an error ERROR_EXIT(128, "Transition not found!!!\n"); return; } accum_backoff *= lira_model->backoff_table[st].bo_prob; st = lira_model->backoff_table[st].bo_dest_state; } ERROR_EXIT(256, "This should never happen\n"); } void NgramLiraInterface::clearQueries() { LMInterface::clearQueries(); } // void NgramLiraInterface::insertQueries(const Key &key, int32_t idKey, // vector words) { // // todo: we can take profit of the lira data structure to improve // // the efficiency of this method w.r.t. the naive implementation // } // internal method used by findKeyFromNgram NgramLiraInterface::Key NgramLiraInterface::getDestState(NgramLiraInterface::Key st, const WordType word) { NgramLiraModel *lira_model = static_cast(model); do { if (st < lira_model->first_state_binary_search) { // linear search, we look for the LinearSearchInfo of st int linear_index = 0; while(lira_model->linear_search_table[linear_index].first_state <= st) linear_index++; // -1 because the search stopped too late ;) LinearSearchInfo *info = &(lira_model->linear_search_table[linear_index-1]); // range of transitions during the search: unsigned int first_tr_index = ((st - info->first_state)*info->fan_out + info->first_index); unsigned int last_tr_index = first_tr_index + info->fan_out; // lineal search: for (unsigned int tr_index = first_tr_index; tr_index < last_tr_index; tr_index++) { if (lira_model->transition_words_table[tr_index] == word) { return lira_model->transition_table[tr_index].state; } } } else { // the dichotomic search of the transition index is not based // on the binary_search template in order to be able to return // as soon as the word is found unsigned int left = lira_model->first_transition[st]; unsigned int right = lira_model->first_transition[st+1] - 1; while (left <= right) { unsigned int tr_index = (left+right)/2; unsigned int current_word = lira_model->transition_words_table[tr_index]; if (current_word == word) { return lira_model->transition_table[tr_index].state; } else if (current_word < word) { left = tr_index+1; } else { right = tr_index-1; } } } // apply backoff when the transition is not found: st = lira_model->backoff_table[st].bo_dest_state; } while (1); return st; } NgramLiraInterface::Key NgramLiraInterface::findKeyFromNgram(const WordType *wordSequence, int len) { NgramLiraModel *lira_model = static_cast(model); Key st = lira_model->lowest_state; for (int i=0; i 0) st = getDestState(st,wordSequence[i]); return st; } } // closes namespace LanguageModels april-ann-0.4.1/packages/language_model/ngram_lira/c_src/ngram_lira.h000066400000000000000000000276641263004425400256250ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef NGRAM_LIRA_H #define NGRAM_LIRA_H #include "binary_search.h" #include "LM_interface.h" #include "stream.h" #include #include // UINT_MAX #include "logbase.h" namespace LanguageModels { struct NgramLiraTransition { unsigned int state; AprilUtils::log_float prob; }; /// lambda backoff transition: struct NgramBackoffInfo { unsigned int bo_dest_state; // estado al que se baja AprilUtils::log_float bo_prob; // probabilidad de bajar al estado bo_dest_state NgramBackoffInfo() : bo_dest_state(0), bo_prob(AprilUtils::log_float::zero()) { } }; /// states are sorted by fan_out in .lira format struct LinearSearchInfo { unsigned int first_state;// first state with a given fan_out unsigned int fan_out; // number of output transitions of states unsigned int first_index;// index of first transition of first_state }; struct NgramLiraBinaryHeader { unsigned int magic; unsigned int ngram_value; unsigned int vocabulary_size; unsigned int initial_state; unsigned int final_state; unsigned int lowest_state; unsigned int num_states; unsigned int num_transitions; unsigned int different_number_of_trans; // size del linear_search_table unsigned int linear_search_size; unsigned int fan_out_threshold; unsigned int first_state_binary_search; unsigned int size_first_transition; AprilUtils::log_float best_prob; size_t size_first_transition_vector; size_t offset_vocabulary_vector; size_t size_vocabulary_vector; size_t offset_transition_words_table; size_t size_transition_words_table; size_t offset_transition_table; size_t size_transition_table; size_t offset_linear_search_table; size_t size_linear_search_table; size_t offset_first_transition; size_t offset_backoff_table; size_t size_backoff_table; size_t offset_max_out_prob; size_t size_max_out_prob; }; class NgramLiraModel : public LMModelUInt32LogFloat { public: typedef uint32_t Key; typedef AprilUtils::log_float Score; // allows the dictionary used to check the model to be larger than // the actual list of words in the model bool ignore_extra_words_in_dictionary; unsigned int vocabulary_size; unsigned int initial_state; unsigned int final_state; unsigned int lowest_state; unsigned int num_states; unsigned int num_transitions; unsigned int ngram_value; // transitions table is divided in two parts, both of them are of // size num_transitions: WordType *transition_words_table; ///< size num_transitions NgramLiraTransition *transition_table; ///< size num_transitions NgramBackoffInfo *backoff_table; ///< size num_states // upper bound on the max probability outgoing from each state Score *max_out_prob; ///< size num_states, when fan_out==0 equals zero // number of different fan outs unsigned int different_number_of_trans; // size del linear_search_table LinearSearchInfo *linear_search_table; ///< size different_number_of_trans /// threshold where to stop searching in array linear_search_table unsigned int linear_search_size; /// fan_out_threshold the best out degree of a state whose /// transitions are linearly searched unsigned int fan_out_threshold; /// index of first state whose transitions are no longer linearly searched unsigned int first_state_binary_search; unsigned int size_first_transition; ///< num_states-first_state_binary_search unsigned int *first_transition; ///< vector shifted first_state_binary_search /// best_prob is the max of max_tr_prob_table Score best_prob; ///< loaded from .lira //---------------------------------------------------------------------- // data in case vectors are mapped: bool is_mmapped; int file_descriptor; size_t filesize; char *filemapped; //---------------------------------------------------------------------- // required by getFinalScore method: WordType final_word; virtual ~NgramLiraModel(); /// generates the binary data useful for mmaped version void saveBinary(const char *filename, unsigned int expected_vocabulary_size, const char *expected_vocabulary[]); /// constructor for binary mmaped data NgramLiraModel(const char *filename, unsigned int expected_vocabulary_size, const char *expected_vocabulary[], WordType final_word, bool ignore_extra_words_in_dictionary); /// fan_out_threshold is used to distinguish automata states when /// looking for their transitions /// expectedVocabularySize is an array of char* strings, the /// vocabulary is not checked when this argument is NULL NgramLiraModel(AprilIO::StreamInterface *fd, unsigned int expected_vocabulary_size, const char *expected_vocabulary[], WordType final_word, int fan_out_threshold, bool ignore_extra_words_in_dictionary); /// creates a simple model with two states: one which is a loop and /// a final state NgramLiraModel(int vocabulary_size, WordType final_word); virtual bool isDeterministic() const { return true; } virtual int ngramOrder() const { return ngram_value; } virtual bool requireHistoryManager() const { return false; } virtual LMInterface* getInterface(); }; // closes class NgramLiraModel class NgramLiraInterface : public LMInterface { public: friend class NgramLiraModel; typedef NgramLiraModel::Key Key; typedef NgramLiraModel::Score Score; /** * @brief For Lira Ngrams, StateControl is derived to contain an unsigned * integer property indicating the arc number in * NgramLiraModel::transition_table array, among two more integers with * first and last transitions in former table. */ class NgramLiraNoBackoffStateControl : public LMInterface::ArcsIterator::StateControl { friend class NgramLiraInterface; unsigned int current_transition, last_transition; static const NgramLiraNoBackoffStateControl *checkOther(const StateControl *other_) { const NgramLiraNoBackoffStateControl *other = dynamic_cast(other_); april_assert(other != 0); return other; } NgramLiraNoBackoffStateControl(unsigned int current_tr, unsigned int last_tr) : current_transition(current_tr), last_transition(last_tr) {} virtual bool equals(const StateControl *other_) const { const NgramLiraNoBackoffStateControl *other = checkOther(other_); return current_transition == other->current_transition && last_transition == other->last_transition; } virtual void copy(const StateControl *other_) { const NgramLiraNoBackoffStateControl *other = checkOther(other_); current_transition = other->current_transition; last_transition = other->last_transition; } virtual StateControl *clone() const { return new NgramLiraNoBackoffStateControl(this->current_transition, this->last_transition); } virtual void moveToNext(LMInterface *lm, Score threshold) { NgramLiraModel* m = static_cast(lm->getLMModel()); while (current_transition < last_transition) { ++current_transition; if (m->transition_table[current_transition].prob >= threshold) return; } return; } virtual WordType getWord(LMInterface *lm) { NgramLiraModel* lira_model = static_cast(lm->getLMModel()); WordType *twt = lira_model->transition_words_table; return twt[current_transition]; } virtual bool isEnd(LMInterface *lm) const { UNUSED_VARIABLE(lm); return current_transition>=last_transition; } }; protected: NgramLiraInterface(NgramLiraModel *lira_model) : LMInterface(lira_model) { } public: virtual ~NgramLiraInterface() { } /// Returns an ArcsIterator to non-backoff transitions. virtual ArcsIterator beginNonBackoffArcs(Key key, Score threshold) { NgramLiraModel* lira_model = static_cast(getLMModel()); // determine initial and final transition indexes unsigned int first_tr; unsigned int last_tr; if (key < lira_model->first_state_binary_search) { int linear_index = 0; while(lira_model->linear_search_table[linear_index].first_state <= key) linear_index++; // -1 because the search stopped too late ;) LinearSearchInfo *info = &(lira_model->linear_search_table[linear_index-1]); // range of transitions during the search: first_tr = (key - info->first_state)*info->fan_out + info->first_index; last_tr = first_tr + info->fan_out; } else { first_tr = lira_model->first_transition[key]; last_tr = lira_model->first_transition[key + 1] - 1; } AprilUtils::UniquePtr st; st = new NgramLiraNoBackoffStateControl(first_tr,last_tr); return ArcsIterator(this,threshold,st); } virtual void get(Key key, WordType word, Burden burden, AprilUtils::vector &result, Score threshold); virtual void clearQueries(); /* Implemented by default in parent class: virtual void insertQuery(Key key, Word word, Burden burden, Score threshold); virtual void insertQueries(Key key, int32_t id_key, vector words, bool is_sorted=false); */ virtual Score getBestProb() const { return static_cast(model)->best_prob; } virtual Score getBestProb(Key k) { return static_cast(model)->max_out_prob[k]; } virtual bool getZeroKey(Key &k) const { k = static_cast(model)->lowest_state; return true; } virtual Key getInitialKey() { return static_cast(model)->initial_state; } virtual Score getFinalScore(Key k, Score threshold) { AprilUtils::vector aux; Burden dummyBurden; get(k, static_cast(model)->final_word, dummyBurden, aux, threshold); return (aux.size() == 1) ? aux[0].key_score.score : threshold; } // useful methods to look for an state: Key getDestState(Key st, const WordType word); Key findKeyFromNgram(const WordType *word_sequence, int len); }; } // closes namespace language_models #endif // NGRAM_LIRA_H april-ann-0.4.1/packages/language_model/ngram_lira/lua_src/000077500000000000000000000000001263004425400236615ustar00rootroot00000000000000april-ann-0.4.1/packages/language_model/ngram_lira/lua_src/arpa2lira.lua000066400000000000000000000415001263004425400262410ustar00rootroot00000000000000get_table_from_dotted_string("ngram.lira.arpa2lira", true) -- Recibe una tabla con estos argumentos: -- input_filename nombre fichero de entrada -- output_filename nombre fichero de salida -- limit_vocab OPCIONAL, se usa para limitar el vocabulario -- vocabulary OPCIONAL, se asume que es un lexClass -- bccue OPCIONAL -- eccue OPCIONAL -- escribe en el fichero con formato .lira local function arpa2lira(self, tbl) -- first argument self receives the table ngram.lira.arpa2lira table -- when this local function is used in the setmetatable at the end -- of this file local tbl = get_table_fields( { input_filename = { mandatory = true, type_match = "string" }, output_filename = { mandatory = true, type_match = "string" }, limit_vocab = { mandatory = false }, vocabulary = { mandatory = false }, bccue = { mandatory = false, type_match = "string", default = "" }, eccue = { mandatory = false, type_match = "string", default = "" } }, tbl, true) local theTrie = util.trie_hash() local log10 = math.log(10) local logZero = -1e12 -- representación de log(-infinito) local logOne = 0 local limit_vocab = tbl.limit_vocab local function arpa_prob(x) if x <= -99 then return logZero end return x*log10 end local line,which_n,word,how_many_ngrams local orig_state,dest_state,dest_backoff,bow local n = 1 -- la n del n-grama, se lee del .arpa -- estas tablas contienen el automata --local state2transitions={} -- estado -> [ destino,palabra,prob ] * num_trans local state2transitions=ngram.lira.arpa2lira.State2Transitions() -- la lista de transiciones es vector de {destino,palabra,prob} local backoffs={} -- estado -> {estado,prob bajada} local max_tr_prob = {} -- estado -> mayor prob transitar desde el -- sin usar backoff local a_eliminar = {} -- estados con 0 tr salida y no finales local fanout2states = {} -- fanout -> lista de estados con dicho fanout local function consider_state(state) --if state2transitions[state] == nil then if not state2transitions:exists(state) then --state2transitions[state] = {} state2transitions:create(state) max_tr_prob[state] = logZero end end local vocabulary local check_word local line_counter = 0 -- para garbage collection local verbosity = tbl.verbosity or 0 if tbl.limit_vocab then vocabulary = tbl.limit_vocab check_word = function (word) word = string.gsub(word, "\\_", "_") if not vocabulary:getWordId(word) then return false end return true end elseif tbl.vocabulary then vocabulary = tbl.vocabulary check_word = function (word) word = string.gsub(word, "\\_", "_") if not vocabulary:getWordId(word) then error("arpa2lira found unknown word when using a fixed vocabulary: " .. word) end return true end else vocabulary = lexClass() check_word = function (word) word = string.gsub(word, "\\_", "_") if not vocabulary:getWordId(word) then vocabulary:addPair{ word = word, } end return true end end local input_file = io.open(tbl.input_filename, "r") local output_file = io.open(tbl.output_filename,"w") local bccue = tbl.bccue -- begin context cue local eccue = tbl.eccue -- end context cue -- anyadirlos al diccionario y convertirlos en su id if not check_word(bccue) then error("Not found " .. bccue .. " in vocabulary") end if not check_word(eccue) then error("Not found " .. eccue .. " in vocabulary") end bccue = vocabulary:getWordId(bccue) eccue = vocabulary:getWordId(eccue) -- saltarselo todo hasta llegar a \data\ repeat line = input_file:read('*l') until line == '\\data\\' -- leer lineas tipo 'ngram numero=numero' local ngram_counts = {} repeat line = input_file:read('*l') _,_, which_n,how_many_ngrams = string.find(line,"^ngram (%d+)=(%d+)$") which_n = tonumber(which_n) how_many_ngrams = tonumber(how_many_ngrams) if which_n ~= nil then ngram_counts[which_n] = how_many_ngrams end if which_n ~= nil and which_n>n then n = which_n end until which_n == nil -- en este punto ya sabemos la n del n-grama -- 0-grama, solamente esta el estado "_" local zeroGramState = theTrie:find({}) consider_state(zeroGramState) -- consider_state("_") -- un solo estado final: local final_state = theTrie:reserveId() -- consider_state("__final__") consider_state(final_state) local initial_state, lowest_state lowest_state = theTrie:find({}) if n>1 then initial_state = theTrie:find({bccue}) else initial_state = lowest_state end local function process_arpa_line(w, n, nmax) -------------------------------------------------------------- -- example: -0.544068 b a -0.3521825 -- -0.544068 -> probabilidad de ir de b hasta b_a -- -0.3521825 -> probabilidad de ir de b_a hasta a via backoff -------------------------------------------------------------- -- n-grama w1 w2 ... wn-1 wn -- indices 2 3 ... n n+1 line_counter = line_counter + 1 if line_counter > 100000 then line_counter = 0 collectgarbage("collect") end local num_checked_words = 0 for i=2,n+1 do if check_word(w[i]) then num_checked_words = num_checked_words + 1 end w[i] = vocabulary:getWordId(string.gsub(w[i], "\\_", "_")) end if num_checked_words < n then return end local trans_prob = arpa_prob(tonumber(w[1])) local orig_state = theTrie:find(table.slice(w,2,n)) local word = w[n+1] local function dest_state() if w[n+1] == eccue then return final_state end local from = (n with back-off weight") end --if trans_prob > logZero then -- este if hay que validarlo --table.insert(state2transitions[orig_state], dest_state) --table.insert(state2transitions[orig_state], word) --table.insert(state2transitions[orig_state], trans_prob) state2transitions:insert(orig_state, dest_state, word, trans_prob) -- para calcular getBestProb(state) y getBestProb() max_tr_prob[orig_state] = math.max(max_tr_prob[orig_state],trans_prob) --end -- transición de backoff, como procesamos valores crecientes de n -- si ya existe no la tocamos, si no existe estamos arreglando el -- problema producido por n-gramas previos inexistentes if backoffs[dest_state] == nil and backoff_weight > logZero then backoffs[dest_state] = { backoff_dest_state, backoff_weight } end ---------------------------------------------- end line = input_file:read('*l') if line then line = string.gsub(line ,"_","\\_") end if math.modf(num_proceseed_lines,10000) == 0 then printf("\r%3.0f%%", num_proceseed_lines/ngram_counts[current_n]*100) io.stdout:flush() end num_proceseed_lines = num_proceseed_lines + 1 end printf("\r100%%\n") end theTrie = nil collectgarbage("collect") -- cerrar el fichero .arpa input_file:close() -- calcular para cada estado una cota superior de la mejor forma de -- salir de el teniendo en cuenta bajadas por backoff, se utiliza en -- getBestProb() local bestProb = logZero local upperBoundBestProb = {} -- state -> bound for st,bestOutProb in pairs(max_tr_prob) do local bound = bestOutProb local backoffsum = 0 local downst = st while downst ~= zeroGramState and backoffs[downst] ~= nil do backoffsum = backoffsum + backoffs[downst][2] downst = backoffs[downst][1] bound = math.max(bound, backoffsum + max_tr_prob[downst]) end upperBoundBestProb[st] = bound bestProb = math.max(bestProb,bound) end max_tr_prob = nil -- porque ya no se vuelve a usar -- localizar estados a eliminar, aquellos con 0 transiciones de -- salida que no sean el estado final: --for st,trans in pairs(state2transitions) do local it = state2transitions:beginIt() local end_it = state2transitions:endIt() while it:notEqual(end_it) do local trans = it:getTransitions() local st = it:getState() --if #trans==0 and st ~= final_state then if trans:size() == 0 and st ~= final_state then a_eliminar[st] = true if verbosity > 0 then fprintf(output_file,"# removing state: %s\n",i) end end it:next() end -- comprobar si un estado baja a otro a eliminar --for st,trans in pairs(state2transitions) do local it = state2transitions:beginIt() local end_it = state2transitions:endIt() while it:notEqual(end_it) do local st = it:getState() while backoffs[st] and a_eliminar[backoffs[st][1]] do backoffs[st][2] = backoffs[st][2] + backoffs[backoffs[st][1]][2] backoffs[st][1] = backoffs[backoffs[st][1]][1] end it:next() end -- vamos a ordenar el vector de aristas por la palabra local incs = { 463792, 198768, 86961, 33936, 13776, 4592, 1968, 861, 336, 112, 48, 21, 7, 3, 1 } -- tbl la tabla a ordenar que contiene tripletas destino,palabra,prob -- y se ordena por palabra local function shellsort(tbl) local sz = #tbl/3 for _, gap in ipairs(incs) do for i = gap + 1, sz do local v1,v2,v3 = tbl:get(i) --tbl[i*3-2],tbl[i*3-1],tbl[i*3] for j = i - gap, 1, -gap do local w1,w2,w3 = tbl:get(j) if not (v2 < w2) then break end --tbl[j*3-1] tbl:set(i, w1, w2, w3) -- tbl[i*3-2] = tbl[j*3-2] -- tbl[i*3-1] = tbl[j*3-1] -- tbl[i*3 ] = tbl[j*3 ] i = j end tbl:set(i, v1, v2, v3) -- tbl[i*3-2] = v1 -- tbl[i*3-1] = v2 -- tbl[i*3 ] = v3 end end end -- eliminar estados cambiando las transiciones que llegan a ellos --for st,trans in pairs(state2transitions) do local it = state2transitions:beginIt() local end_it = state2transitions:endIt() while it:notEqual(end_it) do local st = it:getState() local trans = it:getTransitions() local maxprob --for i = 1,#trans,3 do for i=1,trans:size() do --local dest,prob = trans[i],trans[i+2] local dest,word,prob = trans:get(i) while a_eliminar[dest] do local info = backoffs[dest] -- info es destino,bow dest = info[1] prob = prob+info[2] end --trans[i],trans[i+2] = dest,prob trans:set(i,dest,word,prob) end -- ordenamos las transiciones por el id de la palabra --shellsort(trans) trans:sortByWordId() it:next() end -- eliminar efectivamente los "estados a eliminar" for st,trans in pairs(a_eliminar) do backoffs[st] = nil --state2transitions[st] = nil state2transitions:erase(st) end collectgarbage("collect") -- ordenar los estados por numero de transiciones que salen de ellos local fan_out_list = {} -- numero de transiciones que aparecen local num_transitions = 0 local num_states = 0 --for st,trans in pairs(state2transitions) do local it = state2transitions:beginIt() local end_it = state2transitions:endIt() while it:notEqual(end_it) do local st = it:getState() local trans = it:getTransitions() --local fanout = #trans/3 -- fan out del estado st local fanout = trans:size() num_states = num_states + 1 -- contamos estados num_transitions = num_transitions + fanout -- contamos todas las transiciones if fanout2states[fanout] == nil then -- lista de estados con un fan out dado fanout2states[fanout] = {} table.insert(fan_out_list,fanout) -- lista de fan outs aparecidos end table.insert(fanout2states[fanout],st) it:next() end ---------------------------------------------------------------------- -- empezamos a escribir el formato lira ---------------------------------------------------------------------- local tabla_vocabulario = vocabulary:getWordVocabulary() fprintf(output_file,"# number of words and words\n%d\n%s\n",#tabla_vocabulario, table.concat(tabla_vocabulario,"\n")) fprintf(output_file, "# max order of n-gram\n%d\n# number of states\n%d\n# number of transitions\n%d\n".. "# bound max trans prob\n%f\n", n,num_states,num_transitions,bestProb) ---------------------------------------------------------------------- -- darle un numero a cada estado ---------------------------------------------------------------------- local state2cod = {} -- state_name -> state_number local cod2state = {} -- state_number -> state_name local num_state = -1 fprintf(output_file,"# how many different number of transitions\n%d\n" .. "# \"x y\" means x states have y transitions\n", #fan_out_list) -- recorremos los estados ORDENADOS por numero de transiciones de -- salida table.sort(fan_out_list) for i,fan_out in ipairs(fan_out_list) do -- codificamos todos los estados con fan_out transiciones fprintf(output_file,"%d %d\n", #fanout2states[fan_out],fan_out) for k,st in ipairs(fanout2states[fan_out]) do num_state = num_state+1 state2cod[st] = num_state cod2state[num_state] = st end end fprintf(output_file,"# initial state, final state and lowest state\n%d %d %d\n", state2cod[initial_state],state2cod[final_state],state2cod[lowest_state]) -- para cada estado imprimimos su estado backoff destino, la -- probabilidad de bajar y su cota superior de transitar fprintf(output_file,"# state backoff_st 'weight(state->backoff_st)' [max_transition_prob]\n") fprintf(output_file,"# backoff_st == -1 means there is no backoff\n") -- stcod es el codigo definitivo que sale en lira, statename es el -- codigo que le asigno el trie for stcod=0,num_state do local statename = cod2state[stcod] local s = string.format("%d",stcod) local info = backoffs[statename] if info then if state2cod[info[1]] == nil then error(string.format("se intenta bajar por backoff al estado %s que no existe", info[1])) end s = s .. string.format(" %d %f",state2cod[info[1]],info[2]) else s = s .. " -1 -1" -- valores especiales para indicar que no hay backoff end if upperBoundBestProb[statename] then s = s .. string.format(" %f", upperBoundBestProb[statename]) end fprintf(output_file,"%s\n",s) if math.modf(stcod,100000) == 0 then collectgarbage("collect") end end -- las transiciones fprintf(output_file,"# transitions\n# orig dest word prob\n") for stcod=0,num_state do local statename = cod2state[stcod] --local trans = state2transitions[statename] local trans = state2transitions:getTransitions(statename) --for i = 1,#trans,3 do for i=1,trans:size() do local dest,word,prob = trans:get(i) --trans[i],trans[i+1],trans[i+2] if verbosity > 1 then fprintf(output_file,"# %s -> %s %s %g\n",statename,dest,word,prob) end fprintf(output_file,"%d %d %d %g\n", stcod,state2cod[dest],word,prob) end if math.modf(stcod,10000) == 0 then collectgarbage("collect") end end output_file:close() end setmetatable(ngram.lira.arpa2lira, { __call=arpa2lira }) april-ann-0.4.1/packages/language_model/ngram_lira/lua_src/ngram_lira.lua000066400000000000000000000030771263004425400265060ustar00rootroot00000000000000local function lira_gz_load_function(filename, dictionary, initial_ngram_word, final_ngram_word, extra) -- estadistico lm_model = ngram.lira.model{ stream=gzio.open(filename), vocabulary=dictionary:getWordVocabulary(), final_word=dictionary:getWordId(final_ngram_word), fan_out_threshold=extra.fant_out_threshold or 10, ignore_extra_words_in_dictionary = extra.ignore_extra_words_in_dictionary or false } return lm_model end local function lira_load_function(filename, dictionary, initial_ngram_word, final_ngram_word, extra) -- estadistico lm_model = ngram.lira.model{ filename=filename, vocabulary=dictionary:getWordVocabulary(), final_word=dictionary:getWordId(final_ngram_word), fan_out_threshold=extra.fant_out_threshold or 10, ignore_extra_words_in_dictionary = extra.ignore_extra_words_in_dictionary or false } return lm_model end local function blira_load_function(filename, dictionary, initial_ngram_word, final_ngram_word, extra) -- estadistico binario lm_model = ngram.lira.model{ binary=true, filename=filename, vocabulary=dictionary:getWordVocabulary(), final_word=dictionary:getWordId(final_ngram_word), ignore_extra_words_in_dictionary = extra.ignore_extra_words_in_dictionary or false } return lm_model end language_models.register_by_extension("gz", lira_gz_load_function) language_models.register_by_extension("lira", lira_load_function) language_models.register_by_extension("blira", blira_load_function) april-ann-0.4.1/packages/language_model/ngram_lira/package.lua000066400000000000000000000030121263004425400243230ustar00rootroot00000000000000package{ name = "ngram.lira", version = "1.0", depends = { "util", "language_models", "aprilio" }, keywords = { }, description = "no description available", target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test_ppl_ngramlira.lua", }, }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_ngram_lira.lua.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_arpa2lira.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp=true, object{ file = {"c_src/*.cc",}, include_dirs = "${include_dirs}", --flags = "-std=c99", not valid for c++!!! dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_ngram_lira.lua.cc", dest_dir = "build", }, build_bind{ file = "binding/bind_arpa2lira.lua.cc", dest_dir = "build", } }, target{ name = "document", document_src{ }, document_bind{ }, -- document_copy_file{ -- type="user_refman", -- file = "doc/mini_sorted.png", -- dest_dir = "ngram_lira", -- }, }, } april-ann-0.4.1/packages/language_model/ngram_lira/test/000077500000000000000000000000001263004425400232105ustar00rootroot00000000000000april-ann-0.4.1/packages/language_model/ngram_lira/test/april.out000066400000000000000000000033611263004425400250530ustar00rootroot00000000000000quer'ia un tren con destino a barcelona p( quer'ia | ) = [2gram] 0.0556274 [ -1.254712 ] p( un | quer'ia ...) = [3gram] 0.019859 [ -1.702042 ] p( tren | un ...) = [3gram] 0.11958 [ -0.922342 ] p( con | tren ...) = [3gram] 0.000764004 [ -3.116904 ] p( destino | con ...) = [3gram] 0.285036 [ -0.545100 ] p( a | destino ...) = [3gram] 0.342676 [ -0.465116 ] p( barcelona | a ...) = [3gram] 0.0691948 [ -1.159927 ] p( | barcelona ...) = [3gram] 0.222026 [ -0.653596 ] 1 sentences, 7 words, 0 OOVs 0 zeroprobs, logprob= -9.8197 ppl= 16.884 ppl1= 25.282 quer'ia un tren con destino a londres p( quer'ia | ) = [2gram] 0.0556274 [ -1.254712 ] p( un | quer'ia ...) = [3gram] 0.019859 [ -1.702042 ] p( tren | un ...) = [3gram] 0.11958 [ -0.922342 ] p( con | tren ...) = [3gram] 0.000764004 [ -3.116904 ] p( destino | con ...) = [3gram] 0.285036 [ -0.545100 ] p( a | destino ...) = [3gram] 0.342676 [ -0.465116 ] p( | a ...) = [3gram] 0 [ -inf ] p( | ...) = [3gram] 0.0901419 [ -1.045073 ] 1 sentences, 6 words, 1 OOVs 0 zeroprobs, logprob= -9.0513 ppl= 19.635 ppl1= 32.251 quer'ia un avi'on con destino a barcelona p( quer'ia | ) = [2gram] 0.0556274 [ -1.254712 ] p( un | quer'ia ...) = [3gram] 0.019859 [ -1.702042 ] p( | un ...) = [3gram] 0 [ -inf ] p( con | ...) = [3gram] 0.00286187 [ -2.543350 ] p( destino | con ...) = [3gram] 0.285036 [ -0.545100 ] p( a | destino ...) = [3gram] 0.342676 [ -0.465116 ] p( barcelona | a ...) = [3gram] 0.0691948 [ -1.159927 ] p( | barcelona ...) = [3gram] 0.222026 [ -0.653596 ] 1 sentences, 6 words, 1 OOVs 0 zeroprobs, logprob= -8.3238 ppl= 15.457 ppl1= 24.395 file frase: 3 sentences, 19 words, 2 OOVs 0 zeroprobs, logprob= -27.194871 ppl= 17.223861 ppl1= 26.996596 april-ann-0.4.1/packages/language_model/ngram_lira/test/bunch_april.out000066400000000000000000000033071263004425400262320ustar00rootroot00000000000000quer'ia un tren con destino a barcelona p( quer'ia | ) = [2gram] 0.0556274 [ -1.254712 ] p( un | quer'ia ) = [-1gram] 0.019859 [ -1.702042 ] p( tren | un ) = [-1gram] 0.11958 [ -0.922342 ] p( con | tren ) = [-1gram] 0.000764004 [ -3.116904 ] p( destino | con ) = [-1gram] 0.285036 [ -0.545100 ] p( a | destino ) = [-1gram] 0.342676 [ -0.465116 ] p( barcelona | a ) = [-1gram] 0.0691948 [ -1.159927 ] p( | barcelona ) = [-1gram] 0.222026 [ -0.653596 ] 1 sentences, 7 words, 0 OOVs 0 zeroprobs, logprob= -9.8197 ppl= 16.884 ppl1= 25.282 quer'ia un tren con destino a londres p( quer'ia | ) = [2gram] 0.0556274 [ -1.254712 ] p( un | quer'ia ) = [-1gram] 0.019859 [ -1.702042 ] p( tren | un ) = [-1gram] 0.11958 [ -0.922342 ] p( con | tren ) = [-1gram] 0.000764004 [ -3.116904 ] p( destino | con ) = [-1gram] 0.285036 [ -0.545100 ] p( a | destino ) = [-1gram] 0.342676 [ -0.465116 ] p( | a ) = [-1gram] 0 [ -inf ] p( | ) = [-1gram] 0.0901419 [ -1.045073 ] 1 sentences, 7 words, 1 OOVs 0 zeroprobs, logprob= -9.0513 ppl= 19.635 ppl1= 32.251 quer'ia un avi'on con destino a barcelona p( quer'ia | ) = [2gram] 0.0556274 [ -1.254712 ] p( un | quer'ia ) = [-1gram] 0.019859 [ -1.702042 ] p( | un ) = [-1gram] 0 [ -inf ] p( con | ) = [-1gram] 0.00286187 [ -2.543350 ] p( destino | con ) = [-1gram] 0.285036 [ -0.545100 ] p( a | destino ) = [-1gram] 0.342676 [ -0.465116 ] p( barcelona | a ) = [-1gram] 0.0691948 [ -1.159927 ] p( | barcelona ) = [-1gram] 0.222026 [ -0.653596 ] 1 sentences, 7 words, 1 OOVs 0 zeroprobs, logprob= -8.3238 ppl= 15.457 ppl1= 24.395 file frase: 3 sentences, 21 words, 2 OOVs 0 zeroprobs, logprob= -27.194871 ppl= 17.223861 ppl1= 26.996596 april-ann-0.4.1/packages/language_model/ngram_lira/test/dihana3gram.arpa000066400000000000000000002002531263004425400262350ustar00rootroot00000000000000 \data\ ngram 1=431 ngram 2=1478 ngram 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para -1.255959 tiene coche -1.054499 tiene el -0.1173241 -1.267736 tiene literas -1.263797 tiene preferente -1.152741 tiene que -0.5711361 tienen alg'un -1.125483 tipo -0.196991 tipo de -0.6954691 -0.5161824 tipos de -0.3255564 todo -1.162118 todo gracias -0.1924033 -0.7000313 toledo -0.7740162 toledo el -0.1924034 -0.5161824 total de -0.5161824 trata de -0.4776393 trayecto -0.5530602 trayectos en -1.019942 trece antes -1.047869 trece minutos -1.026762 trece o -0.9867213 treinta -0.4318269 treinta de -0.1924034 -1.237058 treinta si -0.9731681 tren -2.166524 tren ? -1.651775 tren a -1.399071 tren alaris -0.1154437 -2.18833 tren c'omodo -2.106528 tren cu'al -0.8773091 tren de -0.2565115 -2.021935 tren del -1.992229 tren es -0.1050082 -2.006828 tren euromed -2.08824 tren hay -2.18833 tren hotel -2.12562 tren intercity -2.18833 tren lanzadera -2.166524 tren llega -1.388218 tren m'as -0.6958633 -2.106528 tren madrid -2.145591 tren murcia -1.499383 tren para -1.53797 tren por -0.1924034 -2.145591 tren puede -0.9262435 tren que -0.1124973 -2.145591 tren r'apido -0.3886788 -2.166524 tren sea -0.1431911 -2.070691 tren talgo -0.812183 trenes -0.7828213 trenes a -0.1863988 -1.916209 trenes con -1.209949 trenes de -0.08022217 -1.827448 trenes es -1.954693 trenes hacia -1.954693 trenes llegan -1.892261 trenes m'as -1.3258 trenes para -0.08337863 -1.705729 trenes por -1.096524 trenes que -0.3883502 -1.944377 trenes r'apidos -1.941555 trenes salida -1.662465 trenes y -0.5657271 tres -0.6014636 tres de -0.1160294 -0.7000313 turista -0.8343544 turista en -0.7740162 u el -0.8695818 u ocho -1.264848 un alaris -0.115493 -2.048117 un ave -0.1924034 -1.546967 un billete -0.2698946 -2.016615 un coche -1.990017 un d'ia -0.1924033 -2.059716 un error -0.1924034 -1.929879 un euromed -1.062955 un horario -0.1706983 -1.537763 un intercity -0.2698946 -1.990017 un precio -2.048117 un regional -2.003113 un s'abado -1.524313 un talgo -0.1432727 -0.9223433 un tren -0.2702623 -0.8267967 un viaje -0.6561471 -0.5711361 una semana -0.5161824 uno de -0.5721126 vale pues -0.9134657 valencia -1.057053 valencia a -0.2044829 -1.652931 valencia con -1.587125 valencia desde -1.600911 valencia la -1.152998 valencia madrid -0.09874673 -1.086026 valencia para -0.2698946 -1.090328 valencia y -0.8031383 valladolid a -0.7740162 valladolid el -0.947408 van a -0.1136094 -0.8970085 van de -1.019942 van desde -0.536447 vaya a -0.5663476 veamos quiero -1.033725 veinte -0.5605534 veinte de -0.5709246 -1.413111 veinte posibilidad -1.413111 veinte vente -1.290027 veinte y -0.1924034 -0.228106 veinticinco de -0.1924034 -0.3438862 veinticuatro de -0.1452843 -1.109274 veinticuatro y -0.228106 veintid'os de -0.5161824 veintinueve de -0.5161824 veintiocho de -0.5161824 veintis'eis de -0.7664014 veintitr'es de -0.2698946 -0.8585548 veintitr'es o -0.5161824 veintiuno de -0.1924034 -0.5161824 vente de -1.024755 ver me -0.5220132 ver si -0.4776393 verdad -0.3437695 viajando en -0.9848933 viajar a -1.764369 viajar desde -1.561386 viajar el -0.2221505 viajar en -0.174241 -1.792499 viajar ma~nana -1.188627 viaje -0.3075492 viaje de -0.7440376 -1.466191 viaje en -1.563484 viaje fuera -1.545678 viaje valencia -0.3260835 viajes de -0.9563923 viene -1.345931 viene bien -1.292112 viene desde -1.240439 viene en -1.342238 viene mejor -1.240439 viene por -0.8065625 viernes -1.140866 viernes a -0.1164426 -1.790102 viernes all'i -1.67316 viernes antes -1.737551 viernes d'ia -1.322876 viernes de -1.67316 viernes desde -1.24855 viernes o -0.1924034 -1.574201 viernes por -1.781502 viernes pr'oximo -1.177506 viernes que -1.779144 viernes treinta -0.8095642 vigo -0.947408 vigo a -0.9073269 vigo el -1.063427 volver -1.315996 volver a -0.9203283 volver el -0.1177152 -0.9982214 volver en -1.50486 volver o -1.550788 volver pasado -1.415175 volver por -1.559282 volver tarde -0.4884457 volviendo el -1.044338 volviendo pasado -0.8065625 vuelta -1.445532 vuelta a -1.781502 vuelta cu'antos -1.075731 vuelta de -0.1124213 -1.67316 vuelta desde -1.088889 vuelta el -0.1924034 -1.574201 vuelta en -1.790102 vuelta huelva -1.177506 vuelta para -0.1002796 -1.522896 vuelta que -1.75785 vuelta saliendo -1.781502 vuelta volviendo -1.60414 y a -2.142725 y cinco -1.445119 y de -2.097731 y diecisiete -2.119646 y dos -1.056686 y el -0.08411729 -1.522783 y en -1.68842 y llegada -0.1924034 -1.402211 y llegar -0.09521873 -1.870124 y los -1.953573 y me -2.076869 y precio -1.712655 y que -2.019698 y quiero -2.192704 y regresar -1.624888 y salir -0.1924034 -2.142725 y se -1.369044 y si -0.09957653 -2.097731 y tambi'en -2.172538 y trece -2.1671 y tres -1.857651 y un -2.192704 y vaya -2.142725 y veinte -0.09727201 -2.192704 y veintiuno -0.1924034 -1.610733 y viajar -0.1924033 -1.211564 y volver -0.07493377 -1.68842 y volviendo -2.1671 y vuelta -0.1186894 -2.172538 y zona -1.374185 ya es -0.4120455 ya est'a -0.4617801 -1.370729 ya quer'ia -1.38118 ya salir -0.5663476 yo quiero -0.6149756 zaragoza a -1.011629 zaragoza el -1.169507 zaragoza hasta -0.8727711 zona fumador -0.8727711 zona fumadores \3-grams: -1.306749 a principios -0.7574226 a qu'e -0.413873 alicante a valencia -0.439797 castell'on a c'adiz -0.395247 granada a madrid -0.7644826 ir a barcelona -0.8722462 ir a toledo -0.4208342 llega a las -0.6165054 madrid a sevilla -0.61914 murcia a albacete -0.5927542 s'i a qu'e -0.216549 saber a qu'e -0.4397584 segovia a cuenca -0.6585314 trenes a barcelona -0.65877 trenes a sevilla -1.052185 valencia a alicante -1.157735 valencia a barcelona -1.448073 valencia a c'aceres -0.7307709 valencia a madrid -1.444942 valencia a murcia -1.400397 valencia a salamanca -1.131735 valencia a teruel -0.9037766 van a c'adiz -0.7819287 van a madrid -0.5841955 viernes a partir -0.2033561 de abril -1.068594 de abril y -0.5277403 de agosto -0.9840388 de agosto a -0.2870679 en agosto -0.5666991 tren alaris si -0.567534 un alaris o -0.2428439 a albacete -0.485768 a alicante -0.9444389 a alicante para -0.3959607 de alicante a -0.04592482 llegaban antes de -0.04592482 llegar antes de -0.02824243 llegue antes de -0.215071 s'i as'i es -0.1708606 un ave -0.2656968 m'as barato -0.6535957 a barcelona -0.7381623 a barcelona el -1.198264 a barcelona en -0.9694521 a barcelona para -0.3135481 de barcelona a -0.3548708 desde barcelona -0.4980976 del billete -0.2908846 un billete de -0.3732097 buenas quer'ia -0.6495389 hola buenas querr'ia -0.5505514 hola buenas tardes -0.153915 buenos d'ias -0.04073065 hola buenos d'ias -0.5876459 a c'adiz el -0.6158386 a c'adiz los -0.3424836 a c'ordoba para -0.06351215 coche cama -0.456362 a castell'on -0.3898313 de castell'on a -0.1163699 d'ia cinco de -0.1071129 las cinco de -0.5260111 en clase turista -0.1226184 en coche cama -0.3436274 sevilla con salida -0.2923315 quiero conocer el -0.3316627 querr'ia conseguir el -0.2606008 de cualquier tipo -0.6663721 las cuatro -0.3181017 las cuatro de -0.424005 a cuenca el -1.323169 el d'ia cinco -1.326126 el d'ia diecis'eis -1.318347 el d'ia diecisiete -1.561226 el d'ia nueve -1.315956 el d'ia siete -1.561226 el d'ia treinta -1.113922 el d'ia veinte -0.9754722 el d'ia veintitr'es -0.2980972 mismo d'ia -0.4511649 s'abado d'ia catorce -0.4375295 un d'ia laborable -0.4553667 buenos d'ias me -0.5629907 buenos d'ias quer'ia -0.6629073 los d'ias diecinueve -0.9187937 los d'ias diecis'eis -0.9174986 los d'ias veinte -0.03990236 antes de las -0.6077904 billete de ida -1.128783 cinco de diciembre -0.3128511 cinco de la -0.4181702 cu'al de los -0.1925431 cuatro de la -0.4265219 diecinueve de marzo -0.619744 diecis'eis de octubre -0.1999702 diecisiete de agosto -0.385813 diez de la -0.2231608 fin de semana -1.121241 horario de los -1.231002 horario de salida -0.7095599 horario de trenes -0.9212056 horario de un -0.6175163 horarios de los -0.4057068 horarios de trenes -1.538177 horarios de un -1.312039 horarios de vuelta -0.917634 ida de granada -0.7957813 ida de valencia -1.339315 ir de castell'on -1.225749 ir de madrid -0.3704385 ir de valencia -0.3672993 jueves de la -0.3672993 laborable de la -0.3550898 nueve de abril -1.034506 nueve de septiembre -0.4162326 ocho de abril -0.5057292 once de la -0.1327402 partir de las -1.264002 precio de ese -1.253949 precio de ida -1.044121 precio de la -1.190732 precio de los -0.3664488 precio de un -1.013393 precios de estos -0.9501287 precios de los -0.7300431 precios de trenes -0.4265219 principios de junio -0.5922362 seis de enero -0.7732636 siete de abril -0.2778634 siete de la -0.0946664 tipo de tren -0.7087018 treinta de enero -0.7087018 treinta de mayo -0.877586 tren de la -0.4136448 tren de las -1.039787 trenes de murcia -0.883374 trenes de valencia -0.5768054 tres de abril -0.1295234 veinte de abril -0.7087018 veinticinco de junio -0.7087018 veinticinco de marzo -0.8316223 veinticuatro de diciembre -0.7956706 veinticuatro de mayo -0.3284027 veintitr'es de agosto -0.4412551 veintiuno de febrero -0.1819371 viaje de ida -1.400818 viaje de valencia -0.8569664 viaje de vuelta -0.8488514 vuelta de madrid -0.7957813 vuelta de valencia -0.3726299 podr'ia decir el -1.105273 precio del billete -1.045814 precio del segundo -0.3736035 precio del tren -1.256468 precio del viaje -0.383653 salida del tren -0.335718 ir desde valencia -0.3694051 desear'ia saber -0.6618528 s'i deseo que -0.4651147 con destino a -0.2583613 me dices el -0.3349608 de diciembre -0.3016669 d'ias diecinueve y -0.4058076 las diecinueve horas -0.2749628 d'ia diecis'eis de -0.09467877 d'ia diecisiete de -0.1448665 las diez de -0.8648416 el d'ia -1.326469 el jueves -0.9246416 el pr'oximo -1.024583 el precio -1.285477 el viernes -0.6884985 barcelona el pr'oximo -0.3625041 c'adiz el d'ia -0.2812427 conocer el precio -0.3754607 conseguir el precio -0.278602 cuenca el d'ia -0.7906451 decir el horario -0.4751722 decir el precio -0.3754607 dices el precio -0.7378263 en el mismo -0.6886804 en el tren -0.2812427 es el precio -0.7876227 llegar el pr'oximo -0.9074566 llegar el viernes -0.8513082 o el nueve -0.8534971 obtener el horario -0.7383958 obtener el precio -0.8815384 obtener el tipo -0.6081933 para el d'ia -0.6314332 para el pr'oximo -1.4626 para el viaje -0.2363799 que el tren -0.3754607 quiero el precio -0.5668879 s'i el d'ia -0.8963436 s'i el tren -0.7246956 saber el horario -0.2014361 saber el precio -1.306389 saber el tipo -0.7799444 salir el d'ia -1.199419 salir el jueves -0.8266715 salir el pr'oximo -1.282915 salir el siete -0.6007406 tiene el primer -0.3804311 toledo el pr'oximo -0.6084439 volver el lunes -0.3625041 vuelta el d'ia -0.7177063 y el tipo -0.4411655 barcelona en agosto -0.4146316 ir en un -0.3010752 mayo en un -0.3010752 salir en un -1.232625 viajar en clase -0.7675173 viajar en talgo -0.5570137 viajar en un -0.2590265 de enero -0.2749746 un error no -0.2470223 as'i es -0.361793 cu'al es el -0.2437558 eso es todo -0.06526976 si es posible -0.4366513 tren es -0.7093899 de ese talgo -0.638619 de ese tren -0.3885201 llega ese tren -0.1132249 gracias eso es -0.139258 no eso es -0.8828529 ya est'a gracias -0.3807366 ya est'a muchas -0.6952813 ya est'a todo -0.1928082 del euromed -0.4694406 en euromed -0.8772492 en euromed si -0.2681483 primer euromed -0.2430125 sea euromed -0.1959814 por favor -0.47436 de febrero por -0.1427472 pr'oximo fin de -0.3666223 que fuera un -0.1593475 est'a gracias -0.02956633 m'as gracias -0.06360036 muchas gracias -1.3571 muchas gracias eso -0.06867936 no gracias -1.231412 no gracias ya -0.1986808 todo gracias -0.3661439 de granada a -1.404192 me gustar'ia conocer -1.399253 me gustar'ia ir -1.608539 me gustar'ia obtener -1.614451 me gustar'ia preguntar -0.8762224 me gustar'ia que -0.4022652 me gustar'ia saber -1.392753 me gustar'ia salir -1.200636 me gustar'ia viajar -0.3967057 s'i ha habido -0.271084 ha habido un -0.3811858 le'on hasta vigo -0.7331686 hola buenas -0.6159675 hola buenos -0.7297436 hola quer'ia -1.0505 hola quiero -1.053054 hola quisiera -0.356721 s'i hola buenos -0.486661 la hora de -0.3852798 qu'e hora llega -0.8567832 qu'e hora sale -0.3112463 el horario de -0.8517776 el horario del -0.7979512 el horario para -0.5668064 un horario de -0.547977 un horario para -0.1917167 los horarios de -1.557199 los horarios del -0.6845338 los horarios para -0.286164 obtener horarios para -0.3221012 quisiera horarios de -0.6448274 saber horarios de -0.2705895 saber horarios para -0.1259124 diecinueve horas -1.215875 de ida -0.6712669 de ida de -1.343151 de ida desde -0.3294044 de ida y -0.1534143 quer'ia informaci'on sobre -0.1116311 un intercity -0.4296744 gustar'ia ir de -0.4006912 para ir a -0.3675774 para ir de -1.424741 para ir desde -0.4630743 quiero ir a -0.5069184 quiero ir de -0.2232381 quisiera ir a -0.7544952 el jueves -0.8037138 el jueves de -0.2428439 de julio -0.0724071 de junio -0.5076362 de la ma~nana -1.532195 de la noche -1.022465 de la semana -0.4949283 de la tarde -1.163924 de la vuelta -0.4329543 por la ma~nana -1.002475 por la noche -0.4252189 por la tarde -0.2568593 d'ia laborable de -0.8262988 a las diez -0.7508149 a las siete -0.8736013 de las cinco -0.8164312 de las cuatro -1.512132 de las diecinueve -1.517545 de las doce -0.9229248 de las once -1.517545 de las seis -1.063428 de las siete -1.517545 de las tres -0.3811858 desde le'on hasta -0.7077317 hora llega -0.7546362 hora llega el -0.8045725 hora llega ese -0.3898313 que llega a -0.2728952 que llegaban antes -0.3661439 y llegada a -0.4032807 para llegar a -0.5960039 para llegar el -0.3631538 quiero llegar el -0.3631538 y llegar el -0.2656648 que llegue antes -0.3713941 c'adiz los d'ias -1.395809 de los dos -0.1427279 de los trenes -0.2847132 para los d'ias -0.1773726 saber los horarios -1.109993 saber los precios -1.641022 saber los que -0.7928009 saber los trenes -0.4131231 el lunes siguiente -0.4377618 el m'as r'apido -0.3182462 es m'as r'apido -0.2457861 nada m'as gracias -0.530295 nada m'as muchas -0.0869781 tren m'as barato -0.2280436 a madrid -1.075318 a madrid el -0.1643333 de madrid a -0.3862298 valencia madrid -0.7093486 el martes por -0.7036175 el martes que -0.3758679 de marzo -0.8106948 de marzo por -0.3758679 de mayo -0.8106948 de mayo en -0.3796574 ma~nana -0.5596885 ma~nana por -0.2706903 la ma~nana -1.425943 la ma~nana es -1.425943 la ma~nana si -1.164164 la ma~nana y -0.1871429 pasado ma~nana -0.2354275 salamanca ma~nana -0.1279119 me gustar'ia -1.206079 me podr'ia -0.1003659 d'ias me gustar'ia -1.106679 que me digas -0.1390823 s'i me gustar'ia -1.362074 s'i me podr'ia -1.362937 s'i me puedes -0.2601777 salida mi'ercoles siete -0.2162117 el mismo d'ia -0.03342111 est'a muchas gracias -0.02910009 m'as muchas gracias -0.01269329 no muchas gracias -0.3319154 de murcia a -0.06088344 nada m'as -0.08542671 no nada m'as -0.6707429 no -1.938978 no eso -0.6205967 no gracias -0.6931004 no muchas -1.205341 no nada -1.29494 no quiero -1.203622 no ya -0.4083679 error no quiero -0.6837406 la noche -0.7643894 la noche por -0.2428439 de noviembre -0.3584532 d'ia nueve -0.08172472 el nueve de -0.4237826 alaris o un -0.2421277 ocho o el -0.4278214 viernes o s'abado -0.520304 quer'ia obtener un -0.1824384 quisiera obtener el -0.5668561 el ocho o -0.2428439 de octubre -0.6482521 las once -0.5089435 las once de -0.2752352 hay otro tipo -0.3973273 barcelona para el -0.6890507 horario para un -0.822978 horarios para el -0.2521827 horarios para ir -1.3762 horarios para viajar -0.4963707 precio para ir -0.2880768 precios para el -0.2259413 s'i para el -0.5609023 trenes para ir -0.2259413 valencia para el -0.3973273 vuelta para el -0.08977847 a partir de -0.1507008 me podr'ia decir -0.3186009 por favor -0.3186009 febrero por favor -0.1448073 martes por la -0.1448073 marzo por la -0.08507676 ma~nana por la -0.3186009 noche por favor -0.1175913 s'abado por la -0.2908074 s'i por favor -0.1448073 tren por la -0.357733 es posible -0.9462603 es posible que -0.5072662 ser posible en -1.006738 el pr'oximo fin -1.436093 el pr'oximo lunes -0.4930396 el pr'oximo s'abado -0.6773143 el pr'oximo viernes -1.161876 el precio -1.81517 el precio billete -0.3789995 el precio de -0.5385861 el precio del -1.534674 el precio para -1.790492 el precio tren -1.744983 el precio y -0.3258588 qu'e precio tiene -0.3046727 saber precio -0.1814949 los precios de -0.5118219 saber precios de -0.291741 el primer euromed -0.2978785 ese primer tren -0.3961532 a primera hora -0.2124564 en primera -0.2568593 a principios de -0.3934351 se puede viajar -0.3003013 si puede ser -0.2167833 me puedes decir -0.9012976 pues el -0.9867113 pues s'i -0.5154406 qu'e precio -0.0665083 a qu'e hora -0.3879355 deseo que el -0.6057318 euromed que tenga -0.6677038 gustar'ia que fuera -0.7991256 gustar'ia que me -0.4427267 los que llegaban -0.4144495 martes que viene -0.3975289 quiero que me -0.4256832 quisiera que fuera -0.1603077 semana que viene -1.202407 tren que llega -1.062628 tren que llegue -0.925331 tren que sale -1.188624 trenes que salen -0.272466 trenes que van -1.439689 quer'ia obtener -0.1362094 quer'ia saber -1.434571 quer'ia salir -0.6615427 buenas quer'ia obtener -0.7862885 d'ias quer'ia informaci'on -0.1470442 hola quer'ia saber -0.05085469 s'i quer'ia saber -0.2799735 tardes quer'ia saber -1.260397 quiero conocer -1.153682 quiero ir -0.419867 quiero saber -0.8341553 quiero salir -0.4129388 no quiero saber -0.9558643 s'i quiero ir -1.085429 s'i quiero que -0.5640406 s'i quiero saber -1.106001 s'i quiero viajar -0.890861 quisiera horarios -1.370658 quisiera llegar -0.5091012 quisiera saber -0.211 hola quisiera ir -1.190135 s'i quisiera que -0.448401 s'i quisiera saber -1.129052 s'i quisiera salir -0.4224918 m'as r'apido -0.2360518 sea r'apido -0.178086 tren r'apido -1.062963 tren r'apido que -0.668328 el s'abado d'ia -0.8714702 el s'abado tres -0.2356717 o s'abado -0.2304445 pr'oximo s'abado -0.9722498 pr'oximo s'abado por -0.554707 s'i -1.880824 s'i a -2.307129 s'i ahora -2.085566 s'i as'i -2.271614 s'i cu'al -1.879619 s'i deseo -1.456115 s'i el -1.964887 s'i en -2.215586 s'i es -2.289045 s'i ha -2.299992 s'i hola -2.186542 s'i horarios -1.047171 s'i me -1.932405 s'i para -1.453059 s'i por -1.932405 s'i que -0.8073899 s'i quer'ia -1.170121 s'i quiero -1.205579 s'i quisiera -2.280242 s'i saliendo -2.23087 s'i salir -1.395707 gustar'ia saber cu'anto -0.350791 gustar'ia saber el -0.6905762 gustar'ia saber los -0.4541556 quer'ia saber el -1.63892 quer'ia saber horarios -0.3693191 quer'ia saber los -1.198876 quer'ia saber si -0.459645 querr'ia saber el -0.2982556 quiero saber el -0.8582407 quiero saber horarios -1.431612 quiero saber precio -1.376642 quiero saber precios -0.5850337 quisiera saber el -0.8577116 quisiera saber horarios -0.9515662 quisiera saber precios -0.3932715 a salamanca -0.6234204 a salamanca ma~nana -0.5146032 hora sale el -0.5249779 que sale a -0.5040931 que salen a -0.5612415 con salida mi'ercoles -0.5571107 de salida del -0.6057737 deseo salir hoy -0.3239425 gustar'ia salir el -0.3787248 quer'ia salir el -0.9541162 quiero salir desde -0.2804464 quiero salir el -0.2315661 s'i salir el -0.2315661 y salir el -0.3349608 a santander -0.5132752 que sea un -0.765169 tren sea euromed -0.7717795 tren sea r'apido -0.7237129 a segovia -0.8161288 a segovia desde -0.3349608 del segundo -0.2826846 el seis de -0.5153556 de semana -0.2955202 la semana que -0.9265966 la semana siguiente -0.4311359 de septiembre -0.301667 a ser posible -0.5356066 puede ser en -0.6563381 a sevilla -1.179454 a sevilla con -0.8790707 a sevilla el -0.284162 alaris si es -0.284162 euromed si es -0.284162 ma~nana si es -1.008104 saber si se -0.3921488 y si es -0.5958743 el siete u -0.1795069 las siete de -0.3929664 mi'ercoles siete de -0.1379301 lunes siguiente -0.1708606 semana siguiente -0.7014601 informaci'on sobre trenes -0.1584301 en talgo -0.1812537 ese talgo -0.2090674 un talgo -0.07921126 la tarde -0.6143055 buenas tardes quer'ia -0.4311359 que tenga -0.3224814 a teruel -0.2922432 precio tiene el -0.1812281 cualquier tipo de -0.02932455 el tipo de -0.1158519 otro tipo de -0.06900489 qu'e tipo de -0.2585571 es todo -0.7374661 es todo gracias -0.1037475 est'a todo -0.5127778 a toledo -0.542128 a toledo el -0.3157735 el treinta de -0.7525209 de tren -0.9692633 de tren de -1.125422 de tren es -1.395852 de tren hay -1.276782 de tren para -0.7367308 de tren que -0.9032685 del tren de -0.5192564 del tren m'as -0.7593295 del tren que -0.8986542 el tren de -1.113362 el tren m'as -0.5778797 el tren sea -0.1938315 ese tren -1.063984 un tren que -0.3521916 un tren r'apido -0.5832341 de trenes a -1.431001 de trenes con -0.7518775 de trenes de -0.6632975 de trenes para -0.7730983 los trenes a -1.072662 los trenes de -0.4021173 los trenes que -0.2737304 las tres -0.2851237 s'abado tres de -1.352546 de un billete -0.6846399 de un tren -0.2349943 de un viaje -1.34044 en un d'ia -1.035894 en un talgo -0.2716511 en un tren -0.732919 fuera un ave -0.4394897 habido un error -0.4242089 o un intercity -0.2930216 obtener un horario -0.2652977 para un viaje -0.4979872 sea un tren -0.7359913 a valencia -0.8041892 a valencia para -0.05291164 de valencia a -0.6698983 desde valencia -0.4834823 desde valencia a -0.3946381 el valencia madrid -0.2283721 que van a -0.4394404 d'ia veinte de -0.4080041 d'ias veinte y -0.2720277 el veinte de -0.3761918 y veinte de -0.1321481 el veinticinco de -0.2154409 el veinticuatro de -0.4238061 d'ia veintitr'es de -0.6509698 d'ia veintitr'es o -0.2568593 y veintiuno de -0.2355886 gustar'ia viajar en -0.129072 puede viajar en -0.6100611 quiero viajar a -0.7064546 quiero viajar el -0.129072 y viajar en -0.1382164 del viaje de -0.2484262 el viaje de -0.05159053 un viaje de -0.2731028 que viene -0.7066357 el viernes -0.4661517 este viernes -0.6853423 pr'oximo viernes -0.8225269 pr'oximo viernes a -0.3396498 hasta vigo -0.5857397 y volver el -0.755874 de vuelta -0.8946148 de vuelta de -0.9363329 de vuelta para -0.4881503 la vuelta -0.8687739 la vuelta en -0.8073074 y vuelta -0.5751547 y vuelta de -0.3309577 diecinueve y veinte -0.1058573 ida y vuelta -0.6142015 siete y tres -0.4412568 veinte y veintiuno -0.1733835 ya est'a -0.1231317 gracias ya est'a -0.12217 no ya est'a -0.2892666 de zaragoza a \end\ april-ann-0.4.1/packages/language_model/ngram_lira/test/dihana3gram.lira000066400000000000000000002302121263004425400262370ustar00rootroot00000000000000# number of words and words 431 'avila 'ultima 'ultimo ? a abril acerca acercara acuerdo adem'as adi'os agosto ahora al alaris albacete alg'un algo alguno alicante all'i almer'ia amable anterior antes aprovechar aproximadamente arco as'i ave ay barato baratos barcelona bien bilbao billete billetes buenas bueno buenos burgos c'aceres c'adiz c'omodo c'ordoba callado cama castell'o castell'on catorce cinco cincuenta ciudad_real claro clase coche cogi'endolo como comprar compro con concierto confirmar conocer conseguir consultar corresponde cosita costar'ia crem'a cu'al cu'ando cu'anto cu'antos cualquier cuando cuarenta cuarto cuatro cuenca cuesta d'ia d'ias d'igame dado dame de decir decirme del demasiado des desde deseaba desear'ia deseo despu'es destino dices dicho dichos diciembre diecinueve dieciocho diecis'eis diecisiete dieras diez diga digas dime disponible doce domingo dormir dos dura durmiendo efectivamente el en enero ense~nara entonces entre era error es esa ese eso esos est'a estaba estar este esto estos estrella euromed exactamente exacto existe favor febrero fin finales fuera fuese fumador fumadores gracias granada gustado gustar'ia ha hab'ia hab'ias habido habr'ia hace hacer hacerlo hacia haga hagan has hasta hay hola hora horario horarios horas hotel hoy huelva huesca ida igual informaci'on informarme intercity intercitys interesa interesado interesar'ia ir irme jueves julio junio la la_coru~na laborable laborables lanzadera las le le'on litera literas llamaba llega llegaban llegada llegan llegar llegara llegue lleida llevar lo los luego lunes m'alaga m'as m'erida madrid mare_nostrum martes marzo mayo ma~nana ma~nanas me mediod'ia mejor menos mes mi'ercoles mil minutos mira mirar mire misma mismamente mismo muchas murcia muy nada necesito negocios ninguno no noche normal noviembre nueve o obtener ocho octubre once otra otro otros oviedo palencia pamplona para partir pasado paso pedir perd'on pero poco pod'ia podr'ia podr'ias por posibilidad posibilidades posible pr'oxima pr'oximo precio precios preferente pregunta preguntar pregunto primer primera primero principios pronto puede puedes puedo pues qu'e que quedado quer'ia querr'ia quiero quince quisiera r'apido r'apidos realizar reconfirmar recorrido regional regionales regresar rep'itame repetirme repitas ruta s'abado s'e s'i saber salamanca saldr'ia sale salen salga salgan salgo salida saliendo saliera salieran salir san_sebasti'an santander se sea sean segovia segundo seis semana semana_santa septiembre ser sevilla si sido siete siguiente sobre solo son su suficiente talgo talgos tambi'en tanto tarde tardes tarragona temprano tendr'ia tener tenga tengo teruel tiene tienen tipo tipos todo todos toledo total trata trayecto trayectos trece treinta tren trenes tres turista u un una uno va vale valencia valladolid vamos van vaya veamos veinte veinticinco veinticuatro veintid'os veintinueve veintiocho veintis'eis veintitr'es veintiuno vente ver ver'a verdad vez viaja viajando viajar viaje viajes viene viernes vigo volver volver'ia volviendo vuelta vuelvo y ya yo zamora zaragoza zona # max order of n-gram 3 # number of states 783 # number of transitions 2585 # bound max trans prob -0.029227 # how many different number of transitions 29 # "x y" means x states have y transitions 1 0 447 1 132 2 67 3 34 4 28 5 16 6 8 7 9 8 7 9 4 10 2 11 3 12 2 13 3 14 5 15 1 18 2 19 1 21 2 24 1 25 1 30 1 34 1 37 1 42 1 43 1 50 1 52 1 431 # initial state, final state and lowest state 780 0 782 # state backoff_st 'weight(state->backoff_st)' [max_transition_prob] # backoff_st == -1 means there is no backoff 0 782 0.000000 -2.406370 1 648 -0.621455 -0.694614 2 708 -1.664197 -0.182391 3 671 -0.915923 -0.281307 4 782 -0.310403 -1.318776 5 782 -0.310403 -1.099805 6 170 -0.621455 -0.260710 7 476 -0.909137 -0.065031 8 782 -0.310403 -1.198371 9 628 -0.640698 -0.671758 10 770 -0.443025 -0.693251 11 782 -0.310403 -1.302238 12 703 -0.219249 -0.836193 13 432 -0.443025 -0.633152 14 659 -0.443025 -0.934407 15 779 -0.119654 -1.960210 16 782 -0.310403 -1.311400 17 759 -0.443025 -0.701535 18 782 -0.585653 -0.810863 19 782 -0.310403 -1.311400 20 782 -0.310403 -1.198371 21 583 -0.198317 -0.727095 22 750 -0.443025 -0.533201 23 782 -0.585653 -0.784930 24 782 -0.310403 -1.315089 25 719 -0.329898 -0.481395 26 777 -0.272255 -1.425623 27 782 -0.310403 -1.315089 28 768 -1.314602 -0.231101 29 750 -0.202419 -0.745905 30 781 -1.601377 -0.217977 31 141 -0.621455 -0.317596 32 782 -0.585653 -0.706347 33 781 -1.314602 -0.305646 34 782 -0.310403 -1.099805 35 744 -1.114816 -0.378391 36 717 -0.443025 -0.733606 37 676 -0.257871 -1.184918 38 702 -0.621455 -0.672915 39 782 -0.310403 -1.259388 40 770 -0.235982 -0.954725 41 779 -0.621455 -0.641505 42 782 -0.310403 -1.099805 43 781 -0.443025 -0.982103 44 601 -0.443025 -0.877713 45 782 -0.842107 -0.546150 46 779 -0.443025 -0.834697 47 715 -0.273397 -0.858012 48 782 -0.310403 -1.099805 49 776 -0.414784 -0.915344 50 765 -0.254925 -1.146658 51 773 -0.191986 -1.291525 52 777 -0.269186 -1.364867 53 782 -0.310403 -1.099805 54 782 -0.310403 -1.188554 55 717 -0.443025 -0.733606 56 756 -0.443025 -0.654307 57 782 -0.310403 -1.284160 58 18 -0.621455 -0.354402 59 666 -0.265819 -1.304873 60 782 -0.310403 -1.099805 61 779 -0.637026 -0.647585 62 782 -0.310403 -1.188554 63 616 -0.443025 -0.825369 64 765 -0.195528 -1.687608 65 782 -0.310403 -1.318776 66 777 -0.443025 -0.952978 67 717 -0.443025 -0.333431 68 580 -0.443025 -0.843077 69 782 -0.310403 -1.296780 70 776 -0.443025 -0.980172 71 719 -0.553041 -0.364799 72 772 -0.443025 -1.007449 73 782 -1.129789 -0.388224 74 782 -0.842107 -0.497529 75 701 -0.130160 -1.011849 76 782 -0.585653 -0.750835 77 782 -0.310403 -1.296780 78 781 -2.413215 -0.091879 79 18 -1.825428 -0.093786 80 777 -0.443025 -1.012670 81 782 -0.310403 -1.198371 82 712 -0.191609 -1.493835 83 750 -0.270740 -1.302556 84 782 -0.310403 -1.099805 85 782 -0.310403 -1.302238 86 782 -0.310403 -1.318776 87 782 -0.310403 -1.099805 88 779 -0.443025 -0.864530 89 497 -0.335503 -0.496071 90 590 -0.443025 -0.905918 91 773 -0.254627 -1.142936 92 782 -0.310403 -1.259388 93 697 -0.254946 -1.146912 94 663 -0.238538 -0.976308 95 747 -0.443025 -0.773019 96 760 -1.901650 -0.117097 97 756 -0.443025 -0.654307 98 782 -0.310403 -1.099805 99 735 -0.443025 -0.557520 100 452 -0.240399 -0.992727 101 691 -0.048706 -0.972823 102 725 -0.443025 -0.660998 103 691 -0.443025 -0.543529 104 773 -0.218951 -1.586598 105 526 -0.443025 -0.656522 106 514 -0.621455 -0.267952 107 781 -0.272322 -1.427013 108 782 -0.842107 -0.525233 109 476 -0.443025 -0.105746 110 782 -0.310403 -1.302238 111 742 -0.621455 -0.721971 112 782 -0.310403 -1.318776 113 714 -0.242066 -1.007984 114 763 -0.443025 -0.883394 115 782 -0.310403 -1.284160 116 782 -0.310403 -1.302238 117 781 -0.267168 -1.328144 118 782 -0.310403 -1.188554 119 774 -0.909137 -0.446314 120 498 -0.398149 -0.771276 121 781 -1.314602 -0.298239 122 767 -0.399336 -0.950827 123 620 -0.631767 -0.596431 124 782 -0.310403 -1.317338 125 660 -0.621455 -0.420080 126 782 -0.310403 -1.198371 127 141 -0.443025 -0.393421 128 718 -0.229542 -0.904839 129 782 -0.310403 -1.309561 130 782 -0.310403 -1.273468 131 455 -0.909137 -0.238887 132 514 -0.694144 -0.246637 133 782 -0.310403 -1.309561 134 739 -0.621455 -0.655576 135 782 -0.310403 -1.313243 136 606 -0.443025 -0.843077 137 521 -0.443025 -0.763682 138 782 -0.310403 -1.285953 139 501 -1.720067 -0.067522 140 770 -0.443025 -0.693251 141 782 -0.585653 -0.706347 142 591 -0.443025 -0.791231 143 772 -0.621455 -0.686394 144 782 -0.310403 -1.259388 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z l,x9Eho͍ 4n)JڪY,n伈"$rs z?: [۠_c݉ qku%p?nuٽT&+R Op/LLu;J/uv <԰"T焲{{)ܬ!#SQvWve %wΪg:]7SmuTۋro]"u9 C[&?Y,8BfHܙ{OIf=jbҌ/)mU7Ho1__t"cn0¹@o߾͵k;JtOKl.Kl='?g5-f_3:@Pɭ"NE+.Q2CJ"dg |6Pj;Pjo]̽eUE}f_2f{K\wj>闚n21ne21mӽ!r'g#ǜzxCKG:J쭭wg:%^#.ro`C ^B!3>>Z牻y.>fzW}ʄ7Spd[R5#dW|#GBuއݠ.]/lyPR~=}{6|^h'^*|[0mXYmXaכ rb<)zHKVCOvųyɭYZ!jSEtm/G<[ddģk+ŵwa쭝plL}o_DN~wQ':iߖeE"(8!yxsk6V,"$ֶ˵HXΏxw B\F_;دVд-R[QPbE|; ,QfwN.5j^ڃ.?|{brA6 G0nۮtE|&??lZ]Ƽ\|Β/Kjx5X|>"-.գ3/)QKzV̴~ɡCag߷h-ힶ-nɯ b:gvw:yM]K]jz ]1x_{+ }bs-u[xLmv;EoUaT۩PC_woYfw-fCz:^Zw!ohfu5f9u}V9tIfʻEIz=a؊]5)Nս ޑDiiL2?gaY'( 4$:Ehev) L|%MTjX^YfA^3, ,[eZ{K+n5-]V#^^՚w J|۬w+^͐YUZe]Iù~o 'j~ yTy\׸CV}Jm0april-ann-0.4.1/packages/language_model/ngram_lira/test/frase000066400000000000000000000001701263004425400242310ustar00rootroot00000000000000quer'ia un tren con destino a barcelona quer'ia un tren con destino a londres quer'ia un avi'on con destino a barcelona april-ann-0.4.1/packages/language_model/ngram_lira/test/hist_april.out000066400000000000000000000033351263004425400261030ustar00rootroot00000000000000quer'ia un tren con destino a barcelona p( quer'ia | ) = [2gram] 0.0556274 [ -1.254712 ] p( un | quer'ia ...) = [3gram] 0.019859 [ -1.702042 ] p( tren | un ...) = [3gram] 0.11958 [ -0.922342 ] p( con | tren ...) = [3gram] 0.000764004 [ -3.116904 ] p( destino | con ...) = [3gram] 0.285036 [ -0.545100 ] p( a | destino ...) = [3gram] 0.342676 [ -0.465116 ] p( barcelona | a ...) = [3gram] 0.0691948 [ -1.159927 ] p( | barcelona ...) = [3gram] 0.222026 [ -0.653596 ] 1 sentences, 7 words, 0 OOVs 0 zeroprobs, logprob= -9.8197 ppl= 16.884 ppl1= 25.282 quer'ia un tren con destino a londres p( quer'ia | ) = [2gram] 0.0556274 [ -1.254712 ] p( un | quer'ia ...) = [3gram] 0.019859 [ -1.702042 ] p( tren | un ...) = [3gram] 0.11958 [ -0.922342 ] p( con | tren ...) = [3gram] 0.000764004 [ -3.116904 ] p( destino | con ...) = [3gram] 0.285036 [ -0.545100 ] p( a | destino ...) = [3gram] 0.342676 [ -0.465116 ] p( | a ...) = [3gram] 0 [ -inf ] p( | ...) = [3gram] 0 [ -434294480124.381592 ] 1 sentences, 7 words, 1 OOVs 0 zeroprobs, logprob= -434294480132.3878 ppl= inf ppl1= inf quer'ia un avi'on con destino a barcelona p( quer'ia | ) = [2gram] 0.0556274 [ -1.254712 ] p( un | quer'ia ...) = [3gram] 0.019859 [ -1.702042 ] p( | un ...) = [3gram] 0 [ -inf ] p( con | ...) = [3gram] 0 [ -inf ] p( destino | con ...) = [3gram] 0 [ -inf ] p( a | destino ...) = [3gram] 0.342676 [ -0.465116 ] p( barcelona | a ...) = [3gram] 0.0691948 [ -1.159927 ] p( | barcelona ...) = [3gram] 0.222026 [ -0.653596 ] 1 sentences, 5 words, 1 OOVs 0 zeroprobs, logprob= -5.2354 ppl= 11.145 ppl1= 20.363 file frase: 3 sentences, 19 words, 2 OOVs 0 zeroprobs, logprob= -434294480147.442993 ppl= inf ppl1= inf april-ann-0.4.1/packages/language_model/ngram_lira/test/mini.arpa000066400000000000000000000006331263004425400250130ustar00rootroot00000000000000 \data\ ngram 1=5 ngram 2=11 ngram 3=2 \1-grams: -0.6766936 -99 -0.1983676 -0.4336556 a 0.07463366 -0.5006024 b 7.078244 -0.9777236 c -0.1014576 \2-grams: -0.2218488 a -0.1760913 -0.69897 b -0.60206 a -0.90309 a a -0.30103 a b -0.845098 b -0.544068 b a -0.3521825 -0.845098 b b -0.544068 b c -0.4771213 c -0.4771213 c a \3-grams: -0.1760913 a b -0.1760913 b a \end\ april-ann-0.4.1/packages/language_model/ngram_lira/test/mini.lira000066400000000000000000000016301263004425400250150ustar00rootroot00000000000000# number of words and words 5 a b c # max order of n-gram 3 # number of states 8 # number of transitions 18 # bound max trans prob 15.299730 # how many different number of transitions 6 # "x y" means x states have y transitions 1 0 2 1 2 2 1 3 1 4 1 5 # initial state, final state and lowest state 3 0 7 # state backoff_st 'weight(state->backoff_st)' [max_transition_prob] # backoff_st == -1 means there is no backoff 0 7 0.000000 -0.998529 1 5 -0.810930 -0.405465 2 5 -0.405465 -0.405465 3 7 -0.456758 -0.510826 4 7 -0.233615 -1.098612 5 7 0.171850 -0.693147 6 7 16.298259 15.299730 7 -1 -1 -0.998529 # transitions # orig dest word prob 1 0 2 -0.405465 2 6 4 -0.405465 3 2 3 -0.510826 3 6 4 -1.60944 4 0 2 -1.09861 4 5 3 -1.09861 5 0 2 -1.38629 5 5 3 -2.07944 5 6 4 -0.693147 6 0 2 -1.94591 6 1 3 -1.25276 6 6 4 -1.94591 6 4 5 -1.25276 7 3 1 -1e+12 7 0 2 -1.55814 7 5 3 -0.998529 7 6 4 -1.15268 7 4 5 -2.25129 april-ann-0.4.1/packages/language_model/ngram_lira/test/mini.txt000066400000000000000000000000361263004425400247040ustar00rootroot00000000000000a b c a a b a a b b a b c a b april-ann-0.4.1/packages/language_model/ngram_lira/test/srilm.out000066400000000000000000000033711263004425400250730ustar00rootroot00000000000000quer'ia un tren con destino a barcelona p( quer'ia | ) = [2gram] 0.0556273 [ -1.25471 ] p( un | quer'ia ...) = [2gram] 0.019859 [ -1.70204 ] p( tren | un ...) = [2gram] 0.119579 [ -0.922343 ] p( con | tren ...) = [1gram] 0.000764007 [ -3.1169 ] p( destino | con ...) = [2gram] 0.285037 [ -0.545098 ] p( a | destino ...) = [3gram] 0.342677 [ -0.465115 ] p( barcelona | a ...) = [2gram] 0.069195 [ -1.15992 ] p( | barcelona ...) = [3gram] 0.222026 [ -0.653596 ] 1 sentences, 7 words, 0 OOVs 0 zeroprobs, logprob= -9.81973 ppl= 16.8837 ppl1= 25.2824 quer'ia un tren con destino a londres p( quer'ia | ) = [2gram] 0.0556273 [ -1.25471 ] p( un | quer'ia ...) = [2gram] 0.019859 [ -1.70204 ] p( tren | un ...) = [2gram] 0.119579 [ -0.922343 ] p( con | tren ...) = [1gram] 0.000764007 [ -3.1169 ] p( destino | con ...) = [2gram] 0.285037 [ -0.545098 ] p( a | destino ...) = [3gram] 0.342677 [ -0.465115 ] p( | a ...) = [OOV] 0 [ -inf ] p( | ...) = [1gram] 0.090142 [ -1.04507 ] 1 sentences, 7 words, 1 OOVs 0 zeroprobs, logprob= -9.05129 ppl= 19.6355 ppl1= 32.2513 quer'ia un avi'on con destino a barcelona p( quer'ia | ) = [2gram] 0.0556273 [ -1.25471 ] p( un | quer'ia ...) = [2gram] 0.019859 [ -1.70204 ] p( | un ...) = [OOV] 0 [ -inf ] p( con | ...) = [1gram] 0.00286188 [ -2.54335 ] p( destino | con ...) = [2gram] 0.285037 [ -0.545098 ] p( a | destino ...) = [3gram] 0.342677 [ -0.465115 ] p( barcelona | a ...) = [2gram] 0.069195 [ -1.15992 ] p( | barcelona ...) = [3gram] 0.222026 [ -0.653596 ] 1 sentences, 7 words, 1 OOVs 0 zeroprobs, logprob= -8.32384 ppl= 15.4568 ppl1= 24.3953 file frase: 3 sentences, 21 words, 2 OOVs 0 zeroprobs, logprob= -27.1949 ppl= 17.2238 ppl1= 26.9965 april-ann-0.4.1/packages/language_model/ngram_lira/test/test_arpa2lira.lua000066400000000000000000000014221263004425400266260ustar00rootroot00000000000000-- Fichero de test para el metodo arpa2lira ngram.stat -- El fichero arpa no necesita estar ordenado -- No devuelve nada, escribe el resultado en un fichero function table.slice(t, ini, fin) local aux = {} for i=ini,fin do table.insert(aux, t[i]) end return aux end --dofile("../../../basics/util/lua_src/trie.lua") --dofile("../lua_src/arpa2lira.lua") -- se limita a generar un fichero .lira ngram.lira.arpa2lira{ input_filename = arg[1] or "dihana3gram.arpa", output_filename = arg[2] or "dihana3gram.lira", vocabulary = lexClass.load(io.open("vocab")) } -- se limita a generar un fichero .lira ngram.lira.arpa2lira{ input_filename = arg[1] or "mini.arpa", output_filename = arg[2] or "mini.lira", vocabulary = lexClass.load(io.open("voc")) } april-ann-0.4.1/packages/language_model/ngram_lira/test/test_bunch_hashed_lira.lua000066400000000000000000000021411263004425400303720ustar00rootroot00000000000000local check = utest.check local path = arg[0]:get_path() local vocab = lexClass.load(io.open(path .. "vocab")) local model = language_models.load(path .. "dihana3gram.lira.gz", vocab, "", "") local unk_id = -1 local result = language_models.test_set_ppl{ lm = model, vocab = vocab, testset = path .. "frase", debug_flag = -1, use_bcc = true, use_ecc = true } check.lt( math.abs(result.ppl - 17.223860768396), 1e-03 ) check.lt( math.abs(result.ppl1 - 26.996595980386), 1e-03 ) check.lt( math.abs(result.logprob + 27.194871135223), 1e-03 ) check.eq( result.numsentences, 3 ) check.eq( result.numunks, 2 ) check.eq( result.numwords, 19 ) ----------------------------------------------------------------------------- local bunch_hashed_lira_model = ngram.lira.bunch_hashed_model{ lira_model = model, bunch_size = 4, } local result2 = language_models.test_set_ppl{ lm = bunch_hashed_lira_model, vocab = vocab, testset = path .. "frase", debug_flag = 2, use_bcc = true, use_ecc = true, } for i,v in pairs(result) do check.eq( v, result2[i] ) end april-ann-0.4.1/packages/language_model/ngram_lira/test/test_ngramlira.lua000066400000000000000000000030531263004425400267270ustar00rootroot00000000000000-- FIXME: This test cannot be finished until we remember a corner case in which -- lira model simplifies arpa specification local path = arg[0]:dirname() local filename = path .. "dihana3gram" local check = utest.check local T = utest.test local IT = iterator T("NoBackoffIteratorTest", function() local function get_expected_words(...) local context = IT(table.pack(...)): map(bind(string.gsub, nil, "([<>,.-+?])", "%%%1")): select(1):concat("%s+") local words = {} for line in io.lines(filename .. ".arpa") do local word = ( line:match("^%s*%S+%s+" .. context .. "%s+(%S+)%s+%S+%s*$") or line:match("^%s*%S+%s+" .. context .. "%s+(%S+)%s*$") ) if word and not tonumber(word) then words[#words+1] = word end end return words end local vocab = lexClass.load(io.open(path .. "vocab")) local model = language_models.load(filename .. ".lira.gz", vocab, "", "") local lmi = cast.to( model:get_interface(), ngram.lira.interface ) local k = lmi:get_initial_key() local words = IT(lmi:non_backoff_arcs_iterator(k):iterate()): map(bind(vocab.getWordFromWordId, vocab)):table() local expected = get_expected_words("") print( IT.zip(IT(words),IT(expected)):concat(" ", "\n") ) table.sort(words) table.sort(expected) print(#words, #expected) check.eq(#words, #expected) check.TRUE(IT.zip(IT(words),IT(expected)):map(function(...) print(math.eq(...)) return ... end):map(math.eq):reduce(math.land,true)) end) april-ann-0.4.1/packages/language_model/ngram_lira/test/test_ppl_ngramlira.lua000066400000000000000000000022331263004425400276010ustar00rootroot00000000000000local check = utest.check local path = arg[0]:get_path() local vocab = lexClass.load(io.open(path .. "vocab")) local model = language_models.load(path .. "dihana3gram.lira.gz", vocab, "", "") local unk_id = -1 local result = language_models.test_set_ppl{ lm = model, vocab = vocab, testset = path .. "frase", debug_flag = -1, use_bcc = true, use_ecc = true } check.lt( math.abs(result.ppl - 17.223860768396), 1e-03 ) check.lt( math.abs(result.ppl1 - 26.996595980386), 1e-03 ) check.lt( math.abs(result.logprob + 27.194871135223), 1e-03 ) check.eq( result.numsentences, 3 ) check.eq( result.numunks, 2 ) check.eq( result.numwords, 19 ) ----------------------------------------------------------------------------- local hist_based_lira_model = ngram.lira.history_based_model{ lira_model = model, trie_vector = util.trie_vector(18), init_word_id = vocab:getWordId(""), } local result2 = language_models.test_set_ppl{ lm = hist_based_lira_model, vocab = vocab, testset = path .. "frase", debug_flag = -1, use_bcc = true, use_ecc = true, } for i,v in pairs(result) do check.eq( v, result2[i] ) end april-ann-0.4.1/packages/language_model/ngram_lira/test/test_sent_ngramlira.lua000066400000000000000000000052031263004425400277570ustar00rootroot00000000000000local path = arg[0]:get_path() local vocab = lexClass.load(io.open(path .. "vocab")) local model = language_models.load(path .. "dihana3gram.lira.gz", vocab, "", "") local unk_id = -1 local lines_it print("----------------------------------------------------------------------") print("-------------------------- USE_UNK = ALL -----------------------------") print("----------------------------------------------------------------------") print("\n") lines_it = iterator(io.lines(path .. "frase")): map( function(line) return line,iterator(line:gmatch("[^%s]+")) end ) for line,words_it in lines_it() do print(line) words_it = words_it:map( function(w) return (vocab:getWordId(w) or unk_id), w end ) local sum,numwords,numunks = language_models.get_sentence_prob{ lm = model, words_it = words_it, debug_flag = 2, unk_id = unk_id, use_ecc = true, use_unk = "all" } print("SUM:",sum,"Num words:", numwords, "OOVs:", numunks,"\n") end -- forcing unknown word to be "billete" we can reproduce use_unk posibilities local unk_id = vocab:getWordId("billete") print("----------------------------------------------------------------------") print("------------------------ USE_UNK = CONTEXT ---------------------------") print("----------------------------------------------------------------------") print("\n") lines_it = iterator(io.lines(path .. "frase")): map( function(line) return line,iterator(line:gmatch("[^%s]+")) end ) for line,words_it in lines_it() do print(line) words_it = words_it:map( function(w) return (vocab:getWordId(w) or unk_id), w end ) local sum,numwords,numunks = language_models.get_sentence_prob{ lm = model, words_it = words_it, debug_flag = 2, unk_id = unk_id, use_unk = "context" } print("SUM:",sum,"Num words:", numwords, "OOVs:", numunks,"\n") end print("----------------------------------------------------------------------") print("------------------------- USE_UNK = NONE -----------------------------") print("----------------------------------------------------------------------") print("\n") lines_it = iterator(io.lines(path .. "frase")): map( function(line) return line,iterator(line:gmatch("[^%s]+")) end ) for line,words_it in lines_it() do print(line) words_it = words_it:map( function(w) return (vocab:getWordId(w) or unk_id), w end ) local sum,numwords,numunks = language_models.get_sentence_prob{ lm = model, words_it = words_it, debug_flag = 2, unk_id = unk_id, use_unk = "none" } print("SUM:",sum,"Num words:", numwords, "OOVs:", numunks,"\n") end april-ann-0.4.1/packages/language_model/ngram_lira/test/test_srilm.sh000077500000000000000000000001051263004425400257300ustar00rootroot00000000000000ngram -order 3 -lm dihana3gram.arpa -ppl frase -debug 2 2> /dev/null april-ann-0.4.1/packages/language_model/ngram_lira/test/voc000066400000000000000000000000171263004425400237200ustar00rootroot00000000000000 a b c april-ann-0.4.1/packages/language_model/ngram_lira/test/vocab000066400000000000000000000060031263004425400242240ustar00rootroot00000000000000 'avila 'ultima 'ultimo ? a abril acerca acercara acuerdo adem'as adi'os agosto ahora al alaris albacete alg'un algo alguno alicante all'i almer'ia amable anterior antes aprovechar aproximadamente arco as'i ave ay barato baratos barcelona bien bilbao billete billetes buenas bueno buenos burgos c'aceres c'adiz c'omodo c'ordoba callado cama castell'o castell'on catorce cinco cincuenta ciudad_real claro clase coche cogi'endolo como comprar compro con concierto confirmar conocer conseguir consultar corresponde cosita costar'ia crem'a cu'al cu'ando cu'anto cu'antos cualquier cuando cuarenta cuarto cuatro cuenca cuesta d'ia d'ias d'igame dado dame de decir decirme del demasiado des desde deseaba desear'ia deseo despu'es destino dices dicho dichos diciembre diecinueve dieciocho diecis'eis diecisiete dieras diez diga digas dime disponible doce domingo dormir dos dura durmiendo efectivamente el en enero ense~nara entonces entre era error es esa ese eso esos est'a estaba estar este esto estos estrella euromed exactamente exacto existe favor febrero fin finales fuera fuese fumador fumadores gracias granada gustado gustar'ia ha hab'ia hab'ias habido habr'ia hace hacer hacerlo hacia haga hagan has hasta hay hola hora horario horarios horas hotel hoy huelva huesca ida igual informaci'on informarme intercity intercitys interesa interesado interesar'ia ir irme jueves julio junio la la_coru~na laborable laborables lanzadera las le le'on litera literas llamaba llega llegaban llegada llegan llegar llegara llegue lleida llevar lo los luego lunes m'alaga m'as m'erida madrid mare_nostrum martes marzo mayo ma~nana ma~nanas me mediod'ia mejor menos mes mi'ercoles mil minutos mira mirar mire misma mismamente mismo muchas murcia muy nada necesito negocios ninguno no noche normal noviembre nueve o obtener ocho octubre once otra otro otros oviedo palencia pamplona para partir pasado paso pedir perd'on pero poco pod'ia podr'ia podr'ias por posibilidad posibilidades posible pr'oxima pr'oximo precio precios preferente pregunta preguntar pregunto primer primera primero principios pronto puede puedes puedo pues qu'e que quedado quer'ia querr'ia quiero quince quisiera r'apido r'apidos realizar reconfirmar recorrido regional regionales regresar rep'itame repetirme repitas ruta s'abado s'e s'i saber salamanca saldr'ia sale salen salga salgan salgo salida saliendo saliera salieran salir san_sebasti'an santander se sea sean segovia segundo seis semana semana_santa septiembre ser sevilla si sido siete siguiente sobre solo son su suficiente talgo talgos tambi'en tanto tarde tardes tarragona temprano tendr'ia tener tenga tengo teruel tiene tienen tipo tipos todo todos toledo total trata trayecto trayectos trece treinta tren trenes tres turista u un una uno va vale valencia valladolid vamos van vaya veamos veinte veinticinco veinticuatro veintid'os veintinueve veintiocho veintis'eis veintitr'es veintiuno vente ver ver'a verdad vez viaja viajando viajar viaje viajes viene viernes vigo volver volver'ia volviendo vuelta vuelvo y ya yo zamora zaragoza zona april-ann-0.4.1/packages/metrics/000077500000000000000000000000001263004425400166215ustar00rootroot00000000000000april-ann-0.4.1/packages/metrics/rates/000077500000000000000000000000001263004425400177375ustar00rootroot00000000000000april-ann-0.4.1/packages/metrics/rates/binding/000077500000000000000000000000001263004425400213515ustar00rootroot00000000000000april-ann-0.4.1/packages/metrics/rates/binding/bind_rates.lua.cc000066400000000000000000000165261263004425400245640ustar00rootroot00000000000000//BIND_HEADER_C // FIXME MACROS ELIMINAR ESTA FUNCION DE AQUI namespace Metrics { namespace Rates { int_sequence read_int_sequence(lua_State *L) { // recibe una tabla en el tope de la pila y la consume // stack: vector-table] // meter los elementos en un vector de enteros int i,j,k; int maxlength = 1024; int *aux_seq = new int[maxlength]; // stack: j-component table k = 0; for (j=1; lua_rawgeti(L, -1, j), !lua_isnil(L,-1); j++) { // stack: j-component table if (j == maxlength) { // resize int *aux = new int[2*maxlength]; for (i=0;inext = 0; // primera entrada lua_rawgeti(L,-1,1); // stack: 1st-component i-pair-table data-table] nextpair->correct = read_int_sequence(L); // stack: i-pair-table data-table] // segunda entrada lua_rawgeti(L,-1,2); // stack: 2nd-component i-pair-table data-table] nextpair->test = read_int_sequence(L); // stack: i-pair-table data-table] // añadir nextpair en la lista "data", al final *tail_data = nextpair; tail_data = &(nextpair->next); // nos cargamos la ref. al par de tablas que acabamos de read lua_pop(L,1); // stack: data-table] } lua_pop(L,2); // delete nil value and data-table // stack: ] return data; } // FIXME posiblemente estaria mejor en otra parte: void delete_pairs_int_sequences (pairs_int_sequences *data) { pairs_int_sequences *aux; while (data != 0) { aux = data; data = data->next; delete[] aux->correct.symbol; delete[] aux->test.symbol; delete aux; } } } // namespace Rates } // namespace Metrics //BIND_END //BIND_HEADER_H #include "rates.h" using namespace Metrics::Rates; //BIND_END //BIND_FUNCTION metrics.rates.ints { // recibe como argumentos: // la tabla con los ints, // el tipo de tasa // el valor de p, <- opcional // un valor booleano "with_matrix" <- opcional // devuelve: // el valor de la tasa // la tabla con la matriz, en caso de pedirse LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); // FIXME MACROS lua_pushstring(L, "int_data"); lua_gettable(L,1); if (lua_isnil(L,-1)) { lua_pushstring(L,"rates: int_data field not found"); lua_error(L); } pairs_int_sequences *data = read_pairs_int_sequences(L); bool with_p = false,with_matrix=false; // FIXME MACROS double p=1.0; lua_pushstring(L, "p"); lua_gettable(L,1); if (!lua_isnil(L,-1)) { with_p = true; p = luaL_checknumber(L, -1); lua_pop(L,1); } lua_pushstring(L, "confusion_matrix"); lua_gettable(L,1); if (lua_isboolean(L,-1)) { with_matrix = (bool)lua_toboolean(L,-1); lua_pop(L,1); } lua_pushstring(L, "rate"); lua_gettable(L,1); if (lua_isnil(L,-1)) { lua_pushstring(L,"rates: rate field not found"); lua_error(L); } const char *typerate = lua_tostring(L,-1); // stack: typerate table] counter_edition counted; conf_matrix *m; double rrate = rates::rate(data, typerate, counted, p, with_p, (with_matrix) ? (&m) : (0)); delete_pairs_int_sequences(data); // valores devueltos lua_newtable(L); lua_pushstring(L,"rate"); lua_pushnumber(L, rrate); lua_settable(L,-3); lua_pushstring(L,"p"); lua_pushnumber(L, p); lua_settable(L,-3); lua_pushstring(L,"sust"); lua_pushnumber(L, counted.ns); lua_settable(L,-3); lua_pushstring(L,"ins"); lua_pushnumber(L, counted.ni); lua_settable(L,-3); lua_pushstring(L,"borr"); lua_pushnumber(L, counted.nb); lua_settable(L,-3); lua_pushstring(L,"ac"); lua_pushnumber(L, counted.na); lua_settable(L,-3); if (with_matrix) { lua_pushstring(L,"confusion_matrix"); lua_newtable(L); // rellenar matriz lua_pushstring(L, "confusion_matrix_dictionary"); lua_gettable(L,1); // stack: dictionary confusion_matrix] int dsize = m->columns; bool con_diccionario = !lua_isnil(L,-1); for (int i=0;inext) { counter_edition counted = rates::gp(p, r->correct, r->test); lua_newtable(L); lua_pushnumber(L,counted.na); lua_setfield(L,-2,"na"); lua_pushnumber(L,counted.ns); lua_setfield(L,-2,"ns"); lua_pushnumber(L,counted.ni); lua_setfield(L,-2,"ni"); lua_pushnumber(L,counted.nb); lua_setfield(L,-2,"nb"); // lua_rawseti(L,-2,index); index++; } delete_pairs_int_sequences(data); return 1; } //BIND_END april-ann-0.4.1/packages/metrics/rates/c_src/000077500000000000000000000000001263004425400210305ustar00rootroot00000000000000april-ann-0.4.1/packages/metrics/rates/c_src/rates.cc000066400000000000000000000376031263004425400224660ustar00rootroot00000000000000#include "rates.h" #include "constString.h" #include #include // debug using namespace AprilUtils; namespace Metrics { namespace Rates { typedef simple_matrix matrix_path; class generic_rate { double alphas, alphai, alphab, alphaa; double betas, betai, betab, betaa; public: generic_rate(double as, double ai, double ab, double aa, double bs, double bi, double bb, double ba); double operator() (counter_edition); }; generic_rate::generic_rate(double as, double ai, double ab, double aa, double bs, double bi, double bb, double ba) : alphas(as), alphai(ai), alphab(ab), alphaa(aa), betas(bs), betai(bi), betab(bb), betaa(ba) { } double generic_rate::operator() (counter_edition c) { return 100.0 * (alphas * c.ns + alphai * c.ni + alphab * c.nb + alphaa * c.na) / (betas * c.ns + betai * c.ni + betab * c.nb + betaa * c.na); } generic_rate rate_pra(0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0); generic_rate rate_pre(1.0, 1.0, 1.0, 0.0, 1.0, 1.0, 1.0, 1.0); generic_rate rate_pa (0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 1.0, 1.0); generic_rate rate_ip (0.0, -1.0, 0.0, 1.0, 1.0, 0.0, 1.0, 1.0); generic_rate rate_ie (1.0, 1.0, 1.0, 0.0, 1.0, 0.0, 1.0, 1.0); generic_rate rate_psb(1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0, 1.0); generic_rate rate_iep(1.0, 0.5, 0.5, 0.0, 1.0, 0.0, 1.0, 1.0); generic_rate rate_iap(0.0, -0.5, 0.5, 1.0, 1.0, 0.0, 1.0, 1.0); // funcion auxiliar para calcular la talla del diccionario int rates::dict_size(const pairs_int_sequences *data) { int resul = 0; for (const pairs_int_sequences *r = data; r != 0; r = r->next) { for (int i=0; i < r->correct.size; i++) if (resul < r->correct.symbol[i]) resul = r->correct.symbol[i]; for (int i=0; i < r->test.size; i++) if (resul < r->test.symbol[i]) resul = r->test.symbol[i]; } return resul; } struct dp_state { double score; counter_edition counter; }; counter_edition rates::gp(double p, int_sequence correct, int_sequence test) { const double gs = 1.0; const double gi = p; const double gb = p; const double ga = 0.0; dp_state *previous = new dp_state[test.size+1]; dp_state *current = new dp_state[test.size+1]; int itest, icorrect; current[0].score = 0.0; current[0].counter = counter_edition(0,0,0,0); for (itest = 1; itest <= test.size; itest++) { // insertion current[itest] = current[itest-1]; current[itest].score += gi; current[itest].counter.ni++; } for (icorrect = 0; icorrect < correct.size; icorrect++) { dp_state *swap = previous; previous = current; current = swap; current[0] = previous[0]; current[0].score += gb; current[0].counter.nb++; for (itest = 1; itest <= test.size; itest++) { // deletion double score_b = previous[itest].score + gb; // insertion double score_i = current[itest-1].score + gi; double score_min_ib = (score_i < score_b) ? score_i : score_b; // substitution double score_s = previous[itest-1].score + ((correct.symbol[icorrect] == test.symbol[itest-1]) ? ga : gs); // if (score_s <= score_min_ib) { current[itest].score = score_s; current[itest].counter = previous[itest-1].counter; if (correct.symbol[icorrect] == test.symbol[itest-1]) current[itest].counter.na++; else current[itest].counter.ns++; } else { if (score_i < score_b) { current[itest].score = score_i; current[itest].counter = current[itest-1].counter; current[itest].counter.ni++; } else { current[itest].score = score_b; current[itest].counter = previous[itest].counter; current[itest].counter.nb++; } } } } counter_edition result = current[test.size].counter; delete[] previous; delete[] current; return result; } counter_edition rates::Gp(double p, const pairs_int_sequences *data) { counter_edition ce(0,0,0,0); for (const pairs_int_sequences *r = data; r != 0; r = r->next) { ce += gp(p, r->correct, r->test); } return ce; } struct dpn_state { double score; int len; counter_edition counter; }; counter_edition rates::gp_normalized(int_sequence correct, int_sequence test) { const double gs = 1.0; const double gi = 1.0; const double gb = 1.0; const double ga = 0.0; dpn_state *previous = new dpn_state[test.size+1]; dpn_state *current = new dpn_state[test.size+1]; int itest, icorrect; current[0].score = 0.0; current[0].counter = counter_edition(0,0,0,0); current[0].len = 1; for (itest = 1; itest <= test.size; itest++) { // insertion current[itest].score = (current[itest-1].score+gi)/current[itest-1].len; current[itest].counter = current[itest-1].counter; current[itest].counter.ni++; current[itest].len = current[itest-1].len+1; } for (icorrect = 0; icorrect < correct.size; icorrect++) { dpn_state *swap = previous; previous = current; current = swap; current[0].score = (previous[0].score+gb)/previous[0].len; current[0].counter = previous[0].counter; current[0].counter.nb++; current[0].len = previous[0].len+1; for (itest = 1; itest <= test.size; itest++) { // deletion double score_b = (previous[itest].score + gb)/previous[itest].len; // insertion double score_i = (current[itest-1].score + gi)/current[itest-1].len; double score_min_ib = (score_i < score_b) ? score_i : score_b; // substitution double score_s = previous[itest-1].score + ((correct.symbol[icorrect] == test.symbol[itest-1]) ? ga : gs); score_s /= previous[itest-1].len; // if (score_s <= score_min_ib) { current[itest].score = score_s; current[itest].counter = previous[itest-1].counter; current[itest].len = previous[itest-1].len+1; if (correct.symbol[icorrect] == test.symbol[itest-1]) current[itest].counter.na++; else current[itest].counter.ns++; } else { if (score_i < score_b) { current[itest].score = score_i; current[itest].counter = current[itest-1].counter; current[itest].counter.ni++; current[itest].len = current[itest-1].len+1; } else { current[itest].score = score_b; current[itest].counter = previous[itest].counter; current[itest].counter.nb++; current[itest].len = previous[itest].len+1; } } } } counter_edition result = current[test.size].counter; delete[] previous; delete[] current; return result; } double rates::initialize_lambda(const pairs_int_sequences *data) { counter_edition ce(0,0,0,0); for (const pairs_int_sequences *r = data; r != 0; r = r->next) { ce += gp_normalized(r->correct, r->test); } return (ce.ns + ce.ni + ce.nb) / (double) (ce.ns + ce.ni + ce.nb + ce.na); } double rates::Fp(const pairs_int_sequences *data, counter_edition &counted) { double lambda, lambdacero; double p; counter_edition ce; // programacion fraccional lambda = initialize_lambda(data); do { lambdacero = lambda; p = 1.0 - lambdacero / 2.0; ce = Gp (p,data); lambda = (ce.ns + ce.ni + ce.nb) / (double) (ce.ni + ce.nb + ce.ns + ce.na); } while (fabs (lambda - lambdacero) > 0.000001); counted = ce; return p; } // con recuperacion del camino counter_edition rates::gp_path(double p, int_sequence correct, int_sequence test, conf_matrix &confmat) { const double gs = 1.0; const double gi = p; const double gb = p; const double ga = 0.0; matrix_path mat(correct.size+1,test.size+1); char *m = mat.m; double *previous = new double[test.size+1]; double *current = new double[test.size+1]; int itest, icorrect; current[0] = 0.0; *m = 's'; m++; for (itest = 1; itest <= test.size; itest++) { // insertion current[itest] = current[itest-1] + gi; //mat[0][itest] = 'i'; *m = 'i'; m++; } for (icorrect = 1; icorrect <= correct.size; icorrect++) { double *swap = previous; previous = current; current = swap; current[0] = previous[0] +gb; *m = 'b'; m++; for (itest = 1; itest <= test.size; itest++) { // deletion double score_b = previous[itest] + gb; // insertion double score_i = current[itest-1] + gi; double score_min_ib = (score_i < score_b) ? score_i : score_b; // substitution double score_s = previous[itest-1] + ((correct.symbol[icorrect-1] == test.symbol[itest-1]) ? ga : gs); // if (score_s <= score_min_ib) { current[itest] = score_s; if (correct.symbol[icorrect-1] == test.symbol[itest-1]) { //mat[icorrect][itest] = 'a'; *m = 'a'; m++; } else { //mat[icorrect][itest] = 's'; *m = 's'; m++; } } else { if (score_i < score_b) { current[itest] = score_i; //mat[icorrect][itest] = 'i'; *m = 'i'; m++; } else { current[itest] = score_b; //mat[icorrect][itest] = 'b'; *m = 'b'; m++; } } } } // fprintf(stderr,"----------------------------------------\n"); // printf(" correct: "); // for (int i=0;i 0 || itest > 0) { // fprintf(stderr,"icorrect=%d itest=%d %c %d %d\n", // icorrect,itest,mat[icorrect][itest], // correct.symbol[icorrect-1],test.symbol[itest-1]); switch (mat[icorrect][itest]) { case 'i': result.ni++; confmat[0][test.symbol[itest-1]]++; itest--; break; case 'b': result.nb++; confmat[correct.symbol[icorrect-1]][0]++; icorrect--; break; case 's': result.ns++; confmat[correct.symbol[icorrect-1]][test.symbol[itest-1]]++; icorrect--; itest--; break; case 'a': result.na++; confmat[correct.symbol[icorrect-1]][test.symbol[itest-1]]++; icorrect--; itest--; break; } } return result; } counter_edition rates::Gp_path(double p, const pairs_int_sequences *data, conf_matrix &confmat) { counter_edition ce(0,0,0,0); for (const pairs_int_sequences *r = data; r != 0; r = r->next) { ce += gp_path(p, r->correct, r->test,confmat); } return ce; } double rates::Fp_path (const pairs_int_sequences *data, counter_edition &counted, conf_matrix &confmat) { double lambda, lambdacero; double p; counter_edition ce; // programacion fraccional lambda = initialize_lambda(data); do { lambdacero = lambda; p = 1.0 - lambdacero / 2.0; confmat.fill(0); ce = Gp_path(p,data,confmat); lambda = (ce.ns + ce.ni + ce.nb) / (double) (ce.ni + ce.nb + ce.ns + ce.na); } while (fabs (lambda - lambdacero) > 0.000001); counted = ce; return p; } // rate devuelve un vector con los tipos de rate double rates::rate(const pairs_int_sequences *data, const char *rate_type, counter_edition &counted, double &p, bool with_p, conf_matrix **m) { constString cstipo = constString(rate_type); bool normalized = false; if (!with_p) { if (cstipo == "pra" || cstipo == "pre") { normalized = true; } else { if (cstipo == "pa" || cstipo == "psb" || cstipo == "iep" || cstipo == "iap") p = 0.5; else // ip, ie p = 1.0; } } if (m != 0) { int dsize = dict_size(data); conf_matrix *confmat = new conf_matrix(dsize+1,dsize+1); confmat->fill(0); if (normalized) { p = Fp_path(data,counted,*confmat); } else { counted = Gp_path(p,data,*confmat); } // tratar o guardar la matriz de confusion *m = confmat; } else { if (normalized) { p = Fp(data,counted); } else { counted = Gp(p,data); } } double rrate; if (cstipo == "pra") { // pra -> porcentaje real de aciertos rrate = rate_pra(counted); } else if (cstipo == "pre") { // pre -> porcentaje real de errores rrate = rate_pre(counted); } else if (cstipo == "pa") { // pa -> porcentaje de aciertos rrate = rate_pa(counted); } else if (cstipo == "ip") { // ip -> indice de precision rrate = rate_ip(counted); } else if (cstipo == "ie") { // ie -> indice de error rrate = rate_ie(counted); } else if (cstipo == "psb") { // psb -> porcentaje de sustituciones y borrados rrate = rate_psb(counted); } else if (cstipo == "iep") { // iep -> indice de error ponderado rrate = rate_iep(counted); } else if (cstipo == "iap") { // iap -> indice de acierto ponderado rrate = rate_iap(counted); } else { // TODO: REPORT ERROR??? rrate = -1; } return rrate; } // void rates::debug(const pairs_int_sequences *data) { // int ipair = 1; // for (const pairs_int_sequences *r = data; r != 0; r = r->next) { // printf("Pair %d\n",ipair); ipair++; // printf(" correct: "); // for (int i=0;icorrect.size;i++) // printf("%d ",r->correct.symbol[i]); // printf("\n test : "); // for (int i=0;itest.size;i++) // printf("%d ",r->test.symbol[i]); // printf("\n"); // } // } } // namespace Rates } // namespace Metrics april-ann-0.4.1/packages/metrics/rates/c_src/rates.h000066400000000000000000000057421263004425400223270ustar00rootroot00000000000000#ifndef RATES_H #define RATES_H namespace Metrics { /// Word Error Rate and similar dynamic programming error rate measures. namespace Rates { struct int_sequence { int size; int *symbol; }; struct pairs_int_sequences { int_sequence correct; int_sequence test; pairs_int_sequences *next; }; struct counter_edition { int na,ns,ni,nb; counter_edition(int a=0, int s=0, int i=0, int b=0) : na(a),ns(s),ni(i),nb(b) {} counter_edition& operator += (const counter_edition &otro) { na += otro.na; ns += otro.ns; ni += otro.ni; nb += otro.nb; return *this; } }; template class simple_matrix { public: T *m; int columns,rows; simple_matrix(int rows, int columns); ~simple_matrix(); T *operator[](int row); void fill(T v); }; template simple_matrix::simple_matrix(int rows, int columns) { this->columns = columns; this->rows = rows; m = new T[rows*columns]; } template simple_matrix::~simple_matrix() { delete[] m; } template T* simple_matrix::operator[](int row) { return m+(row*columns); } template void simple_matrix::fill(T v) { int s=columns*rows; for (int i=0;i conf_matrix; class rates { static int dict_size(const pairs_int_sequences *data); static counter_edition gp_path(double p, int_sequence correct, int_sequence test, conf_matrix &confmat); static counter_edition Gp(double p, const pairs_int_sequences *data); static counter_edition Gp_path(double p, const pairs_int_sequences *data, conf_matrix &confmat); static counter_edition gp_normalized(int_sequence correct, int_sequence test); static double initialize_lambda(const pairs_int_sequences *data); static double Fp(const pairs_int_sequences *data, counter_edition &resul); static double Fp_path(const pairs_int_sequences *data, counter_edition &resul, conf_matrix &confmat); public: static counter_edition gp(double p, int_sequence correct, int_sequence test); static double rate(const pairs_int_sequences *data, const char *rate_type, counter_edition &counted, double &p, bool with_p=false, conf_matrix **m = 0); }; } // namespace Rates } // namespace Metrics #endif // RATES_H april-ann-0.4.1/packages/metrics/rates/doc/000077500000000000000000000000001263004425400205045ustar00rootroot00000000000000april-ann-0.4.1/packages/metrics/rates/doc/R9407.tasas.prat.ps000066400000000000000000010142471263004425400236650ustar00rootroot00000000000000%!PS-Adobe-2.0 %%Creator: dvips 5.523 Copyright 1986, 1994 Radical Eye Software %%Title: report.dvi %%CreationDate: Wed Jul 27 20:22:21 1994 %%Pages: 27 %%PageOrder: Ascend %%BoundingBox: 0 0 596 842 %%EndComments %DVIPSCommandLine: dvips report %DVIPSParameters: dpi=300, comments removed %DVIPSSource: TeX output 1994.07.27:2021 %%BeginProcSet: tex.pro /TeXDict 250 dict def TeXDict begin /N{def}def /B{bind def}N /S{exch}N /X{S N}B 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FG(\(p)q(or)g(ejemplo,)g(\006)g(puede)h(ser)e (un)i(conjun)o(to)e(de)h(fonemas)g(o)f(palabras\).)g(Dada)h(una)-13 2690 y(cadena)c Fz(x)d Ft(2)h FG(\006)258 2674 y Fu(+)287 2690 y FG(,)h(notamos)f(su)i(talla)g(con)f Ft(j)p Fz(x)p Ft(j)g FG(y)g(nos)g(referimos)g(a)h(su)f Fz(i)p FG(-)o(\023)-21 b(esimo)15 b(s)-5 b(\023)-18 b(\020m)o(b)q(olo)18 b(p)q(or)e Fz(x)1670 2697 y Fs(i)1684 2690 y FG(.)g(Con)g(el)p -13 2743 743 2 v 8 2772 a Fr(1)36 2788 y Fx(Lo)10 b(que)h(se)g(pretende)g (ev)n(aluar)h(en)f([PS91])f(no)h(es)f(un)h(sistema)h(de)f(recono)q (cimien)o(to)i(autom\023)-19 b(atico)12 b(del)f(habla,)h(sino)f(un)g (trans-)44 2834 y(criptor)17 b(ortogr\023)-19 b(a\014co-fon)o(\023)h (etico)18 b(\(y)e(fon)o(\023)-18 b(etico-ortogr\023)f(a\014co\))17 b(de)f(palabras)i(aisladas.)g(Sin)e(em)o(bargo,)h(el)f(problema)h (formal)44 2879 y(sub)o(y)o(acen)o(te)e(es)e(el)g(mismo.)1820 3074 y FG(1)p eop %%Page: 2 8 2 7 bop 600 -33 a Fv(El)15 b(pr)n(oblema)i(de)f(la)g(evaluaci\023)-23 b(on)17 b(de)f(un)g(sistema)g(de)g(r)n(e)n(c)n(ono)n(cimiento)p Fz(:)8 b(:)g(:)p 37 -16 1857 2 v 37 110 a FG(s)-5 b(\023)-18 b(\020m)o(b)q(olo)16 b Fz(\017)g FG(represen)o(tamos)e(la)i(cadena)f(v) m(ac)-5 b(\023)-18 b(\020a.)83 167 y(Si)16 b(bien)h(se)f(ha)g(de)g(ev)m (aluar)g(el)h(sistema)e(de)h(recono)q(cimien)o(to)h(a)e(tra)o(v)o(\023) -21 b(es)14 b(de)i(un)g Fv(c)n(onjunto)f FG(de)h(pares)g(for-)37 224 y(mados)d(p)q(or)h(la)g(in)o(terpretaci\023)-23 b(on)14 b(correcta)f(y)g(la)h(prop)q(orcionada)g(p)q(or)g(el)g(sistema)f (corresp)q(ondien)o(tes)i(a)e(una)37 280 y(determinada)19 b(pron)o(unciaci\023)-23 b(on,)19 b(in)o(tro)q(ducimos)g(ahora)e (algunos)h(conceptos)f(elemen)o(tales)j(considerando)37 337 y(que)d(disp)q(onemos)g(de)f(un)i(\023)-24 b(unico)17 b(par)f(\()p Fz(c;)8 b(s)p FG(\))14 b(de)j(cadenas)f(de)h(\006)1139 320 y Fu(+)1168 337 y FG(.)f(La)g(ev)m(aluaci\023)-23 b(on)18 b(se)e(realizar\023)-23 b(a)16 b(en)o(tonces)37 393 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y(op)q(eraciones)f(de)e(edici\023)-23 b(on)17 b(de)f(cada)f(tip)q(o.)37 3074 y(2)p eop %%Page: 3 9 3 8 bop -13 -33 a Fv(El)16 b(pr)n(oblema)g(de)g(la)g(evaluaci\023)-23 b(on)17 b(de)f(un)g(sistema)g(de)g(r)n(e)n(c)n(ono)n(cimiento)p Fz(:)8 b(:)g(:)p -13 -16 1857 2 v 645 304 a(s)13 b FG(=)732 272 y Fr(1)728 304 y Fm(x)795 272 y Fr(2)790 304 y Fm(x)857 272 y Fr(3)853 304 y Fm(x)919 272 y Fr(4)915 304 y Fm(z)981 272 y Fr(5)977 304 y Fm(z)1044 272 y Fr(6)1039 304 y Fm(y)1106 272 y Fr(7)1102 304 y Fm(x)1168 272 y Fr(8)1164 304 y Fm(x)645 138 y Fz(c)f FG(=)k Fm(x)38 b(x)h(y)f(x)g(z)g(z)h(x)732 167 y Fr(1)47 b(2)h(3)f(4)g(5)h(6)f(7)p 740 250 2 79 v 802 250 V 865 250 a Fl(\034)894 214 y(\034)p 989 250 V 1051 250 V 1143 250 a(\\)1114 214 y(\\)458 367 y Fz(E)15 b FG(=)e Ft(f)p FG(\(1)p Fz(;)8 b FG(1\))p Fz(;)g FG(\(2)o Fz(;)g FG(2)o(\))p Fz(;)f FG(\(4)p Fz(;)g FG(3)o(\))p Fz(;)g FG(\(5)p Fz(;)g FG(5\))o Fz(;)h FG(\()o(6)p Fz(;)f FG(6\))p Fz(;)g FG(\()o(7)p Fz(;)g FG(8\))p Ft(g)894 450 y FJ(\(a\))p 582 1242 2 665 v 665 1242 V 748 1242 V 831 1242 V 914 1242 V 997 1242 V 1080 1242 V 1163 1242 V 583 1243 582 2 v 583 1160 V 583 1077 V 583 994 V 583 911 V 583 828 V 583 745 V 583 662 V 583 579 V 579 1263 a Fr(0)612 1284 y Fm(x)662 1263 y Fr(1)695 1284 y Fm(x)745 1263 y Fr(2)778 1284 y Fm(y)828 1263 y Fr(3)861 1284 y Fm(x)911 1263 y Fr(4)944 1284 y Fm(z)994 1263 y Fr(5)1027 1284 y Fm(z)1077 1263 y Fr(6)1110 1284 y Fm(x)1160 1263 y Fr(7)562 1251 y(0)537 1213 y Fm(x)562 1168 y Fr(1)537 1130 y Fm(x)562 1085 y Fr(2)537 1047 y Fm(x)562 1002 y Fr(3)537 964 y Fm(z)562 919 y Fr(4)537 881 y Fm(z)562 836 y Fr(5)537 798 y Fm(y)562 753 y Fr(6)537 715 y Fm(x)562 670 y Fr(7)537 632 y Fm(x)562 587 y Fr(8)583 1242 y Fk(\000)624 1201 y(\000)-42 b(\022)666 1159 y(\000)707 1118 y(\000)g(\022)p 749 1078 84 4 v 790 1076 a(-\000)873 1035 y(\000)g(\022)p 913 993 4 84 v -83 x(6)915 910 y(\000)956 869 y(\000)g(\022)998 827 y(\000)1039 786 y(\000)g(\022)p 1079 744 V -83 x(6)1081 661 y(\000)1122 620 y(\000)g(\022)857 1367 y FJ(\(b\))304 1526 y Fz(c)13 b FG(=)g Fm(xxyxzzx)559 1501 y Fj(x)p Fo(!)p Fj(x)574 1526 y Ft(\))22 b Fm(xxyxzzx)816 1501 y Fj(x)p Fo(!)p Fj(x)830 1526 y Ft(\))h Fm(xxyxzzx)1073 1496 y Fj(y)p Fo(!)p Fs(\017)1084 1526 y Ft(\))d Fm(xxxzzx)1300 1501 y Fj(x)p Fo(!)p Fj(x)1315 1526 y Ft(\))i Fm(xxxzzx)217 1610 y Fs(\017)p Fo(!)p Fj(z)229 1635 y Ft(\))e Fm(xxxzzzx)469 1610 y Fj(z)p Fo(!)p Fj(z)483 1635 y Ft(\))j Fm(xxxzzzx)725 1606 y Fj(z)p Fo(!)p Fj(y)740 1635 y Ft(\))g Fm(xxxzzyx)982 1610 y Fs(\017)p Fo(!)p Fj(x)994 1635 y Ft(\))d Fm(xxxzzyxx)1257 1610 y Fj(x)p Fo(!)p Fj(x)1272 1635 y Ft(\))i Fm(xxxzzyxx)12 b FG(=)h Fz(s)863 1719 y FG(\()p FJ(c)p FG(\))-13 1866 y(Figura)i(1:)f FJ(\(a\))f FG(T)l(raza)d(de)i(edici\023)-23 b(on)13 b(de)f Fz(c)f FG(a)g Fz(s)p FG(.)g FJ(\(b\))h FG(Camino)g(de)f(edici\023)-23 b(on.)13 b(En)f(la)f(represen)o (taci\023)-23 b(on)12 b(gr\023)-23 b(a\014ca,)11 b(las)183 1922 y(\015ec)o(has)16 b(diagonales)g(corresp)q(onden)g(a)f (sustituciones)i(y)e(aciertos,)g(mien)o(tras)g(las)g(horizon)o(tales) 183 1978 y(y)g(v)o(erticales)h(son)f(b)q(orrados)g(e)g(inserciones,)i (resp)q(ectiv)m(amen)o(te.)f FJ(\(c\))g FG(Secuencia)h(de)f(edici\023) -23 b(on.)-13 2122 y FJ(De\014nici\023)d(on)24 b(4)f(\(N)q(\023)-28 b(umero)23 b(de)g(errores)e(y)i(aciertos)g(de)g(edici\023)-26 b(on\))21 b FG(Dada)f(una)g(traza)f(de)h(edici\023)-23 b(on)-13 2178 y Fz(E)21 b FG(de)e(un)g(par)f(de)h(in)o(terpretaciones)h (\()p Fz(c;)8 b(s)p FG(\))17 b(denotaremos)h(su)g(n)q(\023)-24 b(umero)19 b(de)g(errores)f(de)h(sustituci\023)-23 b(on,)19 b(de)-13 2235 y(errores)12 b(de)h(inserci\023)-23 b(on,)14 b(de)f(errores)f(de)i(b)q(orrado)e(y)g(de)i(aciertos,)e(resp)q(ectiv)m (amen)o(te,)h(median)o(te)h Fz(n)1659 2242 y Fs(s)1677 2235 y FG(\()p Fz(E)s(;)8 b(c;)g(s)p FG(\),)-13 2291 y Fz(n)14 2298 y Fs(i)28 2291 y FG(\()p Fz(E)s(;)g(c;)g(s)p FG(\),)k Fz(n)236 2298 y Fs(b)253 2291 y FG(\()p Fz(E)s(;)c(c;)g(s)p FG(\))k(y)k Fz(n)488 2298 y Fs(a)509 2291 y FG(\()p Fz(E)s(;)8 b(c;)g(s)p FG(\):)208 2404 y Fz(n)235 2411 y Fs(s)254 2404 y FG(\()p Fz(E)s(;)g(c;)g(s)p FG(\))h(=)k(card)8 b(\()o Ft(f)p FG(\()p Fz(i;)g(j)s FG(\))i Ft(2)j Fz(E)i Ft(j)d Fz(c)843 2411 y Fs(i)870 2404 y Ft(6)p FG(=)h Fz(s)939 2411 y Fs(j)957 2404 y Ft(g)p FG(\))7 b Fz(;)744 b FG(\(1a\))212 2473 y Fz(n)239 2480 y Fs(i)254 2473 y FG(\()p Fz(E)s(;)8 b(c;)g(s)p FG(\))h(=)k(card)561 2438 y Fn(\000\010)604 2473 y Fz(j)i Ft(2)e(f)p FG(1)p Fz(;)8 b FG(2)p Fz(;)g(:)g(:)f(:)t(;)h Ft(j)p Fz(s)p Ft(jg)j(j)977 2469 y Fz(=)977 2473 y Ft(9)p Fz(i)i Ft(2)g(f)p FG(1)p Fz(;)8 b FG(2)p Fz(;)g(:)g(:)f(:)t(;)h Ft(j)p Fz(c)p Ft(jg)j FG(:)h(\()p Fz(i;)c(j)s FG(\))i Ft(2)j Fz(E)1554 2438 y Fn(\011)o(\001)1604 2473 y Fz(;)143 b FG(\(1b\))209 2542 y Fz(n)236 2549 y Fs(b)254 2542 y FG(\()p Fz(E)s(;)8 b(c;)g(s)p FG(\))h(=)k(card)561 2507 y Fn(\000\010)604 2542 y Fz(i)f Ft(2)h(f)p FG(1)p Fz(;)8 b FG(2)p Fz(;)g(:)g(:)f(:)t(;)h Ft(j)p Fz(c)p Ft(jg)j(j)970 2538 y Fz(=)970 2542 y Ft(9)p Fz(j)k Ft(2)e(f)p FG(1)p Fz(;)8 b FG(2)p Fz(;)g(:)g(:)f(:)t(;)h Ft(j)p Fz(s)p Ft(jg)k FG(:)g(\()p Fz(i;)c(j)s FG(\))i Ft(2)j Fz(E)1554 2507 y Fn(\011)o(\001)1604 2542 y Fz(;)148 b FG(\(1c\))206 2611 y Fz(n)233 2618 y Fs(a)254 2611 y FG(\()p Fz(E)s(;)8 b(c;)g(s)p FG(\))h(=)k(card)8 b(\()o Ft(f)p FG(\()p Fz(i;)g(j)s FG(\))i Ft(2)j Fz(E)i Ft(j)d Fz(c)843 2618 y Fs(i)870 2611 y FG(=)h Fz(s)939 2618 y Fs(j)957 2611 y Ft(g)p FG(\))7 b Fz(:)742 b FG(\(1d\))-13 2728 y Fp(2)32 2820 y FG(En)14 b(lo)g(sucesiv)o(o,)g(sobreen)o (tenderemos)f(el)i(par)e(\()p Fz(c;)8 b(s)p FG(\))k(en)i(las)g (funciones)h Fz(n)1309 2827 y Fs(s)1328 2820 y FG(,)e Fz(n)1381 2827 y Fs(i)1395 2820 y FG(,)g Fz(n)1448 2827 y Fs(b)1479 2820 y FG(y)h Fz(n)1544 2827 y Fs(a)1565 2820 y FG(,)f(de)h(mo)q(do)f(que)-13 2876 y(s\023)-23 b(olo)15 b(haremos)g(expl)-5 b(\023)-18 b(\020cita)17 b(su)e(dep)q(endencia)j(resp)q(ecto)d(a)g(la)h(traza)e(de)i(edici\023) -23 b(on)17 b Fz(E)s FG(.)1820 3074 y(3)p eop %%Page: 4 10 4 9 bop 600 -33 a Fv(El)15 b(pr)n(oblema)i(de)f(la)g(evaluaci\023)-23 b(on)17 b(de)f(un)g(sistema)g(de)g(r)n(e)n(c)n(ono)n(cimiento)p Fz(:)8 b(:)g(:)p 37 -16 1857 2 v 83 110 a FG(De)16 b(acuerdo)g(con)h (estas)f(de\014niciones)i(p)q(o)q(demos)f(observ)m(ar)f(que,)g(para)g (to)q(da)g(traza)f(de)i(edici\023)-23 b(on)18 b(de)f(un)37 167 y(par)e(\()p Fz(c;)8 b(s)p FG(\),)670 269 y Fz(n)697 276 y Fs(s)715 269 y FG(\()p Fz(E)s FG(\))h(+)i Fz(n)870 276 y Fs(b)887 269 y FG(\()p Fz(E)s FG(\))e(+)h Fz(n)1041 276 y Fs(a)1062 269 y FG(\()p Fz(E)s FG(\))h(=)i Ft(j)p Fz(c)p Ft(j)p Fz(;)560 b FG(\(2a\))673 338 y Fz(n)700 345 y Fs(s)719 338 y FG(\()p Fz(E)s FG(\))8 b(+)j Fz(n)873 345 y Fs(i)887 338 y FG(\()p Fz(E)s FG(\))e(+)h Fz(n)1041 345 y Fs(a)1062 338 y FG(\()p Fz(E)s FG(\))h(=)i Ft(j)p Fz(s)p Ft(j)p Fz(;)556 b FG(\(2b\))37 441 y(pues)17 b(cada)f(s)-5 b(\023)-18 b(\020m)o(b)q(olo)17 b(de)g(la)g(cadena)f Fz(c)g FG(participa)h(en)g(una)f(y)g(s\023)-23 b(olo)17 b(una)f(op)q(eraci\023)-23 b(on,)17 b(bien)g(de)g(sustituci\023)-23 b(on,)37 498 y(bien)23 b(de)e(acierto)g(o)g(bien)h(de)f(b)q(orrado.)f (Un)h(razonamien)o(to)g(an\023)-23 b(alogo)20 b(se)h(puede)h(aplicar)g (a)f(la)g(cadena)37 554 y Fz(s)p FG(,)g(cuy)o(os)f(s)-5 b(\023)-18 b(\020m)o(b)q(olos)21 b(participan)h(en)f(op)q(eraciones)g (de)g(sustituci\023)-23 b(on,)22 b(acierto)e(e)h(inserci\023)-23 b(on.)22 b(As)-5 b(\023)-18 b(\020)21 b(mismo,)37 611 y(resultar\023)-23 b(a)17 b(\023)-24 b(util)16 b(m\023)-23 b(as)14 b(adelan)o(te)i(la)f(diferencia)i(en)o(tre)e(las)h(tallas)f(de) h Fz(c)f FG(y)g Fz(s)p FG(:)401 713 y(\001)p Fz(l)e FG(=)g Ft(j)p Fz(s)p Ft(j)d(\000)g(j)p Fz(c)p Ft(j)1173 b FG(\(3\))466 782 y(=)13 b Fz(n)541 789 y Fs(s)560 782 y FG(\()p Fz(E)s FG(\))8 b(+)j Fz(n)714 789 y Fs(i)728 782 y FG(\()p Fz(E)s FG(\))e(+)h Fz(n)882 789 y Fs(a)903 782 y FG(\()p Fz(E)s FG(\))f Ft(\000)h FG(\()p Fz(n)1075 789 y Fs(s)1094 782 y FG(\()p Fz(E)s FG(\))e(+)j Fz(n)1248 789 y Fs(b)1265 782 y FG(\()p Fz(E)s FG(\))e(+)h Fz(n)1419 789 y Fs(a)1441 782 y FG(\()p Fz(E)s FG(\)\))466 851 y(=)j Fz(n)541 858 y Fs(i)555 851 y FG(\()p Fz(E)s FG(\))c Ft(\000)i Fz(n)710 858 y Fs(b)727 851 y FG(\()p Fz(E)s FG(\))p Fz(:)37 958 y FA(Ejemplo:)21 b FG(En)15 b(el)h(ejemplo)f(an)o(terior)g(se)g(tiene)h (que)f Ft(j)p Fz(c)p Ft(j)d FG(=)h(7,)h Ft(j)p Fz(s)p Ft(j)e FG(=)h(8,)h Fz(n)1286 965 y Fs(s)1317 958 y FG(=)f(1,)i Fz(n)1443 965 y Fs(i)1470 958 y FG(=)e(2,)h Fz(n)1595 965 y Fs(b)1625 958 y FG(=)f(1,)h Fz(n)1750 965 y Fs(a)1784 958 y FG(=)f(5)h(y)151 1014 y(\001)p Fz(l)f FG(=)g(1.)83 1121 y(P)o(o)q(demos)k(asumir)g(la)g(existencia)i(de)e(una)g(funci\023) -23 b(on)19 b Fz(\015)g FG(que)e(asigna)g(un)h(p)q(eso)f Fz(\015)s FG(\()p Fz(\033)r FG(\))e(a)i(cada)g(op)q(eraci\023)-23 b(on)37 1177 y(de)16 b(edici\023)-23 b(on)18 b Fz(\033)d FG(=)f Fz(a)f Ft(!)h Fz(b)p FG(.)g(Esta)h(funci\023)-23 b(on)17 b(puede)g(extenderse)f(a)f(secuencias)i(de)f(edici\023)-23 b(on)18 b Fi(\033)d FG(=)f Fz(\033)1701 1184 y Fu(1)1720 1177 y Fz(\033)1746 1184 y Fu(2)1774 1177 y Fz(:)8 b(:)g(:)d(\033)1860 1184 y Fs(m)37 1234 y FG(como)797 1310 y Fz(\015)s FG(\()p Fi(\033)q FG(\))12 b(=)966 1257 y Fs(m)952 1270 y Fn(X)954 1361 y Fs(i)p Fu(=1)1020 1310 y Fz(\015)s FG(\()p Fz(\033)1091 1317 y Fs(i)1103 1310 y FG(\))p Fz(:)83 1429 y FG(Esta)i(p)q (onderaci\023)-23 b(on)17 b(p)q(ermite)f(establecer)g(una)f(medida)h (de)g(disimilitud)i(en)o(tre)d(cadenas:)37 1511 y FJ(De\014nici\023)-26 b(on)16 b(5)d(\(Distancia)j(\(p)q(onderada\))g(de)d(edici\023)-26 b(on\))14 b FG(La)e(distancia)h(de)f(edici\023)-23 b(on)14 b(\(\\edit)e(distance")37 1567 y([WF74)o(]\),)i(p)q(onderada)i(p)q(or)f (la)g(funci\023)-23 b(on)17 b Fz(\015)s FG(,)d(en)o(tre)h(dos)g (cadenas)g Fz(c)g FG(y)g Fz(s)g FG(se)h(de\014ne)g(como:)353 1670 y Fz(\016)373 1677 y Fs(\015)396 1670 y FG(\()p Fz(c;)8 b(s)p FG(\))j(=)i(min)q Ft(f)p Fz(\015)s FG(\()p Fi(\033)p FG(\))f Ft(j)h Fi(\033)k FG(es)e(una)g(secuencia)i(de)f (edici\023)-23 b(on)17 b(de)e Fz(c)g FG(a)g Fz(s)p Ft(g)p Fz(:)257 b FG(\(4\))37 1773 y Fp(2)83 1855 y FG(W)l(agner)15 b(y)h(Fisc)o(her)g(demostraron)f(que)h(\(ba)s(jo)e(la)i(asunci\023)-23 b(on)17 b(de)f(que)g Fz(\015)s FG(\()p Fz(a)d Ft(!)h Fz(b)p FG(\))f(=)g Fz(\016)1562 1862 y Fs(\015)1585 1855 y FG(\()p Fz(a;)8 b(b)p FG(\))14 b(para)h(to)q(do)37 1912 y Fz(a)p FG(,)20 b Fz(b)f Ft(2)i FG(\006)13 b Ft([)g(f)p Fz(\017)p Ft(g)p FG(\),)19 b Fz(\016)407 1919 y Fs(\015)429 1912 y FG(\()p Fz(c;)8 b(s)p FG(\))19 b(puede)h(obtenerse)g (considerando)h(s\023)-23 b(olo)20 b(secuencias)h(de)f(edici\023)-23 b(on)21 b(aso)q(ciadas)37 1968 y(a)e(trazas)e(o)h(caminos)h(de)g (edici\023)-23 b(on)20 b([WF74)o(].)d(La)i(siguien)o(te)h(relaci\023) -23 b(on)19 b(de)g(recurrencia,)g(tam)o(bi)o(\023)-21 b(en)18 b(debida)37 2025 y(a)e(W)l(agner)g(y)g(Fisc)o(her,)g(conduce)h (directamen)o(te,)f(median)o(te)g(la)h(t)o(\023)-21 b(ecnica)16 b(algor)-5 b(\023)-18 b(\020tmica)16 b(de)g(Programaci\023)-23 b(on)37 2081 y(Din\023)g(amica,)16 b(a)f(pro)q(cedimien)o(tos)h 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Ft(!)h Fz(s)1494 2260 y Fs(j)1513 2253 y FG(\))p Fz(;)852 2322 y(\016)872 2329 y Fs(\015)894 2322 y FG(\()p Fz(c)932 2329 y Fu(1)959 2322 y Fz(:)8 b(:)g(:)d(c)1039 2329 y Fs(i)p Fo(\000)p Fu(1)1098 2322 y Fz(;)j(s)1140 2329 y Fu(1)1167 2322 y Fz(:)g(:)g(:)e(s)1249 2329 y Fs(j)r Fo(\000)p Fu(1)1312 2322 y FG(\))k(+)h Fz(\015)s FG(\()p Fz(c)1451 2329 y Fs(i)1476 2322 y Ft(!)i Fz(s)1555 2329 y Fs(j)1573 2322 y FG(\))p Ft(g)p Fz(:)37 2425 y FG(El)i(algoritmo)f(en)h(cuesti\023)-23 b(on)15 b(op)q(era)f(en)h(tiemp)q(o)f(prop)q(orcional)i(al)e(pro)q(ducto)h(de)f (las)h(tallas)f(de)h(los)g(ob)s(jetos)37 2481 y(comparados,)c Fz(\022)q FG(\()p Ft(j)p Fz(c)p Ft(j)l(\001)l(j)p Fz(s)p Ft(j)p FG(\),)e(y)j(espacio)g(prop)q(orcional)h(a)e(la)i(talla)f(de)g (uno)g(de)g(ellos,)h Fz(\022)q FG(\(min)q(\()p Ft(j)p Fz(c)p Ft(j)p Fz(;)8 b Ft(j)p Fz(s)p Ft(j)p FG(\)\))o(.)h(T)l(am)o(bi)o (\023)-21 b(en)37 2538 y(existen)16 b(t)o(\023)-21 b(ecnicas)15 b(para)g(el)h(c\023)-23 b(omputo)15 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y(siguien)o(te)h(de\014nici\023)-23 b(on:)37 3074 y(4)p eop %%Page: 5 11 5 10 bop -13 -33 a Fv(El)16 b(pr)n(oblema)g(de)g(la)g(evaluaci\023)-23 b(on)17 b(de)f(un)g(sistema)g(de)g(r)n(e)n(c)n(ono)n(cimiento)p Fz(:)8 b(:)g(:)p -13 -16 1857 2 v -13 110 a FJ(De\014nici\023)-26 b(on)14 b(6)e(\(Distancia)j(de)d(edici\023)-26 b(on)14 b(p)q(or)e(con)o(teo)h(p)q(onderado)g(de)f(op)q(eraciones)i(de)e (edici\023)-26 b(on\))259 213 y Fz(\016)279 220 y Fs(\015)297 224 y Fh(s)314 220 y Fs(;\015)342 225 y Fh(i)356 220 y Fs(;\015)384 226 y Fh(b)399 220 y Fs(;\015)427 224 y Fh(a)448 213 y FG(\()p Fz(c;)8 b(s)p FG(\))j(=)49 b(min)605 245 y Fs(E)r Fo(2)p Fs(E)r Fu(\()p Fs(c;s)p Fu(\))761 213 y Fz(\015)785 220 y Fs(s)803 213 y Fz(n)830 220 y Fs(s)848 213 y FG(\()p Fz(E)s FG(\))9 b(+)h Fz(\015)999 220 y Fs(i)1013 213 y Fz(n)1040 220 y Fs(i)1054 213 y FG(\()p Fz(E)s FG(\))f(+)h Fz(\015)1205 220 y Fs(b)1222 213 y Fz(n)1249 220 y Fs(b)1267 213 y FG(\()p Fz(E)s FG(\))e(+)j Fz(\015)1418 220 y Fs(a)1438 213 y 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b(on)21 b(tam)o(bi)o(\023)-21 b(en)18 b(puede)j(calcularse)f(p)q(or)f(Programaci\023)-23 b(on)19 b(Din\023)-23 b(amica)19 b(\(utilizando)i(la)f(re-)-13 1282 y(currencia)c(\(5\)\))e(si)i(reparamos)e(en)h(el)h(hec)o(ho)g(de)g (que)f Fz(\016)942 1290 y Fg(lcs)1015 1282 y FG(\()p Fz(c;)8 b(s)p FG(\))k(=)h Ft(\000)p Fz(\016)1228 1289 y Fu(0)p Fs(;)p Fu(0)p Fs(;)p Fu(0)p Fs(;)p Fo(\000)p Fu(1)1358 1282 y FG(\()p Fz(c;)8 b(s)p FG(\).)13 b(W)l(agner)i(y)g (Fisc)o(her,)-13 1339 y(p)q(or)h(su)h(parte,)e(sugieren)j(otro)d(m)o (\023)-21 b(eto)q(do)15 b(para)h(calcular)h Fz(\016)997 1347 y Fg(lcs)1087 1339 y FG(a)f(partir)g(del)i(c\023)-23 b(alculo)17 b(p)q(or)g(Programaci\023)-23 b(on)-13 1395 y(Din\023)g(amica)14 b(de)f(una)h(distancia)g(de)g(edici\023)-23 b(on)15 b(p)q(or)e(con)o(teo)g(p)q(onderado)g(de)h(op)q(eraciones)g(de) g(edici\023)-23 b(on:)14 b(utilizar)-13 1452 y(que)h Fz(\016)91 1459 y Fg(lcs)165 1452 y FG(\()p Fz(c;)8 b(s)p FG(\))j(=)i(\()p Ft(j)p Fz(c)p Ft(j)c FG(+)h Ft(j)p Fz(s)p Ft(j)g(\000)g Fz(\016)562 1459 y Fu(2)p Fs(;)p Fu(1)p Fs(;)p Fu(1)p Fs(;)p Fu(0)664 1452 y FG(\()p Fz(c;)e(s)p FG(\)\))p Fz(=)p FG(2)13 b([WF74)o(].)-13 1577 y Fq(2.2)53 b(Equivalencia)17 b(entre)i(criterios)e(de)h(edici\023)-27 b(on)16 b(p)r(o)n(r)h(conteo)g(p)r(onderado)f(de)i(op)r(eraciones)112 1638 y(de)g(edici\023)-27 b(on)-13 1724 y FG(La)19 b(relaci\023)-23 b(on)21 b(en)o(tre)e(las)g(distancias)i Fz(\016)657 1731 y Fu(0)p Fs(;)p Fu(0)p Fs(;)p Fu(0)p Fs(;)p Fo(\000)p Fu(1)806 1724 y FG(y)e Fz(\016)869 1731 y Fu(2)p Fs(;)p Fu(1)p Fs(;)p Fu(1)p Fs(;)p Fu(0)990 1724 y FG(puesta)h(an)o(teriormen) o(te)f(de)g(mani\014esto)h(es)f(tan)-13 1780 y(s\023)-23 b(olo)20 b(un)g(ejemplo)g(de)h(cierta)f(\\redundancia")g(sub)o(y)o (acen)o(te)g(en)g(una)g(form)o(ulaci\023)-23 b(on)21 b(como)e(\(6\).)f(En)i(esta)-13 1837 y(secci\023)-23 b(on)16 b(v)o(eremos)f(c\023)-23 b(omo)15 b(formalizar)h(esta)f (\\redundancia")h(como)f(una)h(relaci\023)-23 b(on)17 b(de)f(equiv)m(alencia)i(en)o(tre)-13 1893 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Fz(g)r FG(\()p Fz(E)s(;)g(c;)f(s)p FG(\))j(=)j(arg)8 b(min)933 2881 y Fs(E)r Fo(2)p Fs(E)r Fu(\()p Fs(c;s)p Fu(\))1088 2840 y Fz(g)1112 2821 y Fo(0)1123 2840 y FG(\()p Fz(E)s(;)g(c;)g(s)p FG(\))p Fz(:)1820 3074 y FG(5)p eop %%Page: 6 12 6 11 bop 600 -33 a Fv(El)15 b(pr)n(oblema)i(de)f(la)g(evaluaci\023)-23 b(on)17 b(de)f(un)g(sistema)g(de)g(r)n(e)n(c)n(ono)n(cimiento)p Fz(:)8 b(:)g(:)p 37 -16 1857 2 v 37 110 a Fp(2)83 191 y FG(Estudiamos)14 b(ahora)g(la)h(equiv)m(alencia)i(en)o(tre)d(diferen) o(tes)i(criterios)f(de)g(edici\023)-23 b(on)16 b(de)f(la)g(forma)e Fz(g)1725 198 y Fs(\015)1743 202 y Fh(s)1760 198 y Fs(;\015)1788 203 y Fh(i)1801 198 y Fs(;\015)1829 204 y Fh(b)1845 198 y Fs(;\015)1873 202 y Fh(a)37 247 y FG(comenzando)j(p)q(or)f (caracterizar)f(cada)h(uno)g(de)h(ellos)g(median)o(te)f(un)i(\023)-24 b(unico)16 b(par\023)-23 b(ametro.)13 b(P)o(ara)h(ello,)i(en)f(lo)37 304 y(sucesiv)o(o,)e(asumiremos)g(que)g Fz(\015)574 311 y Fs(s)598 304 y Ft(\000)5 b Fz(\015)662 311 y Fs(a)695 304 y Fz(>)13 b FG(0;)f(es)h(decir,)h(que)f(el)h(coste)e(de)h(un)h (error)e(de)h(sustituci\023)-23 b(on)14 b(es)f(ma)o(y)o(or)37 360 y(que)j(el)g(coste)f(de)h(un)f(acierto.)83 417 y(Dado)f(que)g Ft(j)p Fz(c)p Ft(j)g FG(es)g(indep)q(endie)q(n)o(te)j(de)e(la)f (edici\023)-23 b(on)17 b Fz(E)s FG(,)c(p)q(o)q(demos)i(restar)e Fz(\015)1355 424 y Fs(a)1384 417 y Ft(\001)8 b(j)p Fz(c)p Ft(j)13 b FG(a)h Fz(g)1523 424 y Fs(\015)1541 428 y Fh(s)1558 424 y Fs(;\015)1586 429 y Fh(i)1599 424 y Fs(;\015)1627 430 y Fh(b)1643 424 y Fs(;\015)1671 428 y Fh(a)1706 417 y FG(y)g(obtener)37 473 y(un)i(criterio)g(equiv)m(alen)o(te.)h(As)-5 b(\023)-18 b(\020,)15 b(utilizando)i(\(2a\),)468 574 y Fz(g)490 581 y Fs(\015)508 585 y Fh(s)524 581 y Fs(;\015)552 586 y Fh(i)565 581 y Fs(;\015)593 587 y Fh(b)609 581 y Fs(;\015)637 585 y Fh(a)671 574 y Ft(\021)c FG(\()p Fz(\015)761 581 y Fs(s)788 574 y Ft(\000)e Fz(\015)858 581 y Fs(a)878 574 y FG(\))f Ft(\001)g Fz(n)956 581 y Fs(s)984 574 y FG(+)h Fz(\015)1054 581 y Fs(i)1078 574 y Ft(\001)e Fz(n)1127 581 y Fs(i)1152 574 y FG(+)h(\()p Fz(\015)1239 581 y Fs(b)1266 574 y Ft(\000)g Fz(\015)1335 581 y Fs(a)1356 574 y FG(\))f Ft(\001)h Fz(n)1433 581 y Fs(b)1451 574 y Fz(:)37 674 y FG(As)-5 b(\023)-18 b(\020)18 b(mismo,)f(como)g(\001)p Fz(l)f FG(=)g Ft(j)p Fz(s)p Ft(j)11 b(\000)h(j)p Fz(c)p Ft(j)k FG(es)h(tam)o(bi)o(\023)-21 b(en)16 b(indep)q(endie)q(n)o(te)k(de)d Fz(E)s FG(,)f(p)q(o)q(demos)i (sumar)e(\(\()p Fz(\015)1728 681 y Fs(b)1756 674 y Ft(\000)11 b Fz(\015)1826 681 y Fs(a)1858 674 y Ft(\000)37 731 y Fz(\015)61 738 y Fs(i)75 731 y FG(\))p Fz(=)p FG(2\)\001)p Fz(l)j FG(al)i(resultado)f(an)o(terior)g(de)h(mo)q(do)f(que)g (utilizando)i(\(3\))d(obtenemos)370 847 y Fz(g)392 854 y Fs(\015)410 858 y Fh(s)426 854 y Fs(;\015)454 859 y Fh(i)468 854 y Fs(;\015)496 860 y Fh(b)511 854 y Fs(;\015)539 858 y Fh(a)573 847 y Ft(\021)f FG(\()p Fz(\015)663 854 y Fs(s)691 847 y Ft(\000)d Fz(\015)760 854 y Fs(a)780 847 y FG(\))g Ft(\001)g Fz(n)858 854 y Fs(s)887 847 y FG(+)937 817 y Fz(\015)961 824 y Fs(i)985 817 y FG(+)g Fz(\015)1054 824 y Fs(b)1081 817 y Ft(\000)h Fz(\015)1151 824 y Fs(a)p 937 837 234 2 v 1043 878 a FG(2)1176 847 y Fz(n)1203 854 y Fs(i)1227 847 y FG(+)1278 817 y Fz(\015)1302 824 y Fs(i)1325 817 y FG(+)g Fz(\015)1395 824 y Fs(b)1422 817 y Ft(\000)f Fz(\015)1491 824 y Fs(a)p 1278 837 V 1383 878 a FG(2)1517 847 y Fz(n)1544 854 y Fs(b)37 958 y FG(y)l(,)15 b(como)g(hemos)g(supuesto)h(que)f Fz(\015)639 965 y Fs(s)667 958 y Ft(\000)c Fz(\015)737 965 y Fs(a)770 958 y Fz(>)i FG(0,)h(p)q(o)q(demos)i(dividir)h(p)q(or)e(esta)g(can)o (tidad)h(y)f(obtener)469 1072 y Fz(g)491 1079 y Fs(\015)509 1083 y Fh(s)525 1079 y Fs(;\015)553 1084 y Fh(i)566 1079 y Fs(;\015)594 1085 y Fh(b)610 1079 y Fs(;\015)638 1083 y Fh(a)672 1072 y Ft(\021)e Fz(n)747 1079 y Fs(s)775 1072 y FG(+)826 1042 y Fz(\015)850 1049 y Fs(i)873 1042 y FG(+)e Fz(\015)943 1049 y Fs(b)970 1042 y Ft(\000)f Fz(\015)1039 1049 y Fs(a)p 826 1062 V 843 1104 a FG(2\()p Fz(\015)908 1111 y Fs(s)935 1104 y Ft(\000)h Fz(\015)1005 1111 y Fs(a)1025 1104 y FG(\))1065 1072 y Fz(n)1092 1079 y Fs(i)1116 1072 y FG(+)1166 1042 y Fz(\015)1190 1049 y Fs(i)1214 1042 y FG(+)g Fz(\015)1284 1049 y Fs(b)1310 1042 y Ft(\000)g Fz(\015)1380 1049 y Fs(a)p 1166 1062 V 1183 1104 a FG(2\()p Fz(\015)1248 1111 y Fs(s)1276 1104 y Ft(\000)f Fz(\015)1345 1111 y Fs(a)1366 1104 y FG(\))1405 1072 y Fz(n)1432 1079 y Fs(b)1450 1072 y Fz(:)37 1195 y FG(En)16 b(resumen,)f(denotando)g(el)h(criterio)g(de)g (edici\023)-23 b(on)17 b Fz(g)965 1202 y Fu(1)p Fs(;p;p;)p Fu(0)1082 1195 y FG(como)e Fz(g)1223 1204 y Fu(\()p Fs(p)p Fu(\))1270 1195 y FG(,)f(p)q(o)q(demos)i(a\014rmar)e(que)565 1295 y Fz(\015)589 1302 y Fs(s)617 1295 y Ft(\000)d Fz(\015)687 1302 y Fs(a)720 1295 y Fz(>)i FG(0)f Ft(\))h Fz(g)883 1302 y Fs(\015)901 1306 y Fh(s)918 1302 y Fs(;\015)946 1307 y Fh(i)959 1302 y Fs(;\015)987 1308 y Fh(b)1003 1302 y Fs(;\015)1031 1306 y Fh(a)1064 1295 y Ft(\021)g Fz(g)1134 1302 y Fu(1)p Fs(;p;p;)p Fu(0)1249 1295 y FG(=)g Fz(g)1319 1304 y Fu(\()p Fs(p)p Fu(\))37 1395 y FG(con)796 1457 y Fz(p)f FG(=)884 1426 y Fz(\015)908 1433 y Fs(i)932 1426 y FG(+)e Fz(\015)1001 1433 y Fs(b)1028 1426 y Ft(\000)g Fz(\015)1097 1433 y Fs(a)p 884 1446 V 901 1488 a FG(2\()p Fz(\015)966 1495 y Fs(s)993 1488 y Ft(\000)h Fz(\015)1063 1495 y Fs(a)1083 1488 y FG(\))1123 1457 y Fz(:)677 b FG(\(10\))83 1564 y(Seg)q(\023)-24 b(un)15 b(esta)f(equiv)m(alencia)k (p)q(o)q(demos)d(v)o(er)f(que)h(el)g(criterio)h(aso)q(ciado)e(a)h (minimizar)h(errores)e(\(distancia)37 1620 y(de)h(Lev)o(ensh)o(tein\),) g(que)g(corresp)q(onde)g(a)f Fz(g)770 1629 y Fu(\(1\))829 1620 y FG(=)f Fz(g)899 1627 y Fu(1)p Fs(;)p Fu(1)p Fs(;)p Fu(1)p Fs(;)p Fu(0)1001 1620 y FG(,)h(es)g(equiv)m(alen)o(te)i(a)e (cualquier)i(criterio)f Fz(g)1725 1627 y Fs(\015)1743 1631 y Fh(s)1760 1627 y Fs(;\015)1788 1632 y Fh(i)1801 1627 y Fs(;\015)1829 1633 y Fh(b)1845 1627 y Fs(;\015)1873 1631 y Fh(a)37 1677 y FG(con)f Fz(\015)143 1684 y Fs(s)174 1677 y Fz(>)f(\015)246 1684 y Fs(a)280 1677 y FG(en)h(el)h(que)f(los)g (v)m(alores)g Fz(\015)709 1684 y Fs(s)727 1677 y FG(,)g Fz(\015)778 1684 y Fs(i)791 1677 y FG(,)g Fz(\015)842 1684 y Fs(b)858 1677 y FG(,)g Fz(\015)909 1684 y Fs(a)943 1677 y FG(sean)g(tales)g(que)g Fz(p)e FG(=)h(1;)g(p)q(or)h(ejemplo:)g (\(0)p Fz(:)p FG(5)p Fz(;)8 b FG(2)p Fz(;)g Ft(\000)p FG(1)p Fz(;)f FG(0\),)37 1733 y(\(3)p Fz(;)h FG(2)p Fz(;)g FG(2)p Fz(;)g FG(2\))o(,)k(o)j(bien)h(\(3)p Fz(;)8 b FG(1)p Fz(;)g FG(4)p Fz(;)g FG(1\))o(.)83 1790 y(Similarmen)o(te,)24 b(el)f(criterio)h Fz(g)622 1797 y Fu(0)p Fs(;)p Fu(0)p Fs(;)p Fu(0)p Fs(;)p Fo(\000)p Fu(1)773 1790 y FG(aso)q(ciado)f(a)g(la) g(distancia)h Fz(\016)1288 1797 y Fu(0)p Fs(;)p Fu(0)p Fs(;)p Fu(0)p Fs(;)p Fo(\000)p Fu(1)1440 1790 y FG(que)f(utiliz\023)-23 b(abamos)24 b(para)37 1846 y(maximizar)c(aciertos,)f(es)h(equiv)m(alen) o(te)h(a)e Fz(g)811 1855 y Fu(\(0)p Fs(:)p Fu(5\))885 1846 y FG(,)g(pues)h(para)f Fz(\015)1157 1853 y Fs(s)1195 1846 y FG(=)h Fz(\015)1274 1853 y Fs(i)1307 1846 y FG(=)g Fz(\015)1386 1853 y Fs(b)1422 1846 y FG(=)g(0)f(y)h Fz(\015)1587 1853 y Fs(a)1627 1846 y FG(=)g Ft(\000)p FG(1)f(resulta)37 1902 y Fz(p)13 b FG(=)g(0)p Fz(:)p FG(5.)f(Obs)o(\023)-21 b(erv)o(ese)13 b(que)h(cuando)f(W)l(agner)g(y)h(Fisc)o(her)f(sugieren)i (utilizar)g Fz(\015)1366 1909 y Fs(s)1396 1902 y FG(=)e(2,)g Fz(\015)1517 1909 y Fs(i)1543 1902 y FG(=)g Fz(\015)1615 1909 y Fs(b)1644 1902 y FG(=)g(1)g(y)h Fz(\015)1790 1909 y Fs(a)1823 1902 y FG(=)f(0)37 1959 y(para)i(este)g(mismo)g(\014n,)h (no)f(hacen)h(sino)f(recurrir)h(a)f(otro)f(de)i(los)f(in\014nitos)i (criterios)e(equiv)m(alen)o(tes.)37 2082 y Fq(2.3)53 b(Edici\023)-27 b(on)17 b(de)h(un)g(conjunto)g(de)h(pa)n(res)g(de)f (cadenas)37 2168 y FG(P)o(asamos)c(ahora)h(a)g(considerar)h(el)g(caso)f (general)h(en)g(que)f(tratamos)f(de)i(ev)m(aluar)g(el)g(sistema)f(no)h (a)f(partir)37 2225 y(de)h(un)g(simple)g(par,)f(sino)h(de)f(un)h (conjun)o(to)f Ft(D)h FG(de)g Fz(M)k FG(pares)15 b(de)h(in)o (terpretaciones.)f(Sea)618 2325 y Ft(D)f FG(=)f Ft(f)p FG(\()p Fz(c)776 2306 y Fs(m)808 2325 y Fz(;)8 b(s)850 2306 y Fs(m)883 2325 y FG(\))p Ft(g)924 2306 y Fs(M)924 2336 y(m)p Fu(=1)1015 2325 y Ft(2)13 b FG(\(\006)1109 2306 y Fu(+)1148 2325 y Ft(\002)d FG(\006)1226 2306 y Fu(+)1256 2325 y FG(\))1274 2306 y Fs(M)37 2425 y FG(donde)16 b Fz(c)191 2409 y Fs(m)239 2425 y FG(y)f Fz(s)299 2409 y Fs(m)348 2425 y FG(recib)q(en,)h(resp)q(ectiv)m(amen)o(te,)g(el)g (nom)o(bre)f(de)g(in)o(terpretaciones)h Fv(c)n(orr)n(e)n(cta)f FG(y)g Fv(del)h(sistema)37 2482 y FG(para)f(la)h Fz(m)p FG(-)o(\023)-21 b(esima)14 b(pron)o(unciaci\023)-23 b(on.)37 2563 y FJ(De\014nici\023)d(on)19 b(9)f(\(Edici\023)-26 b(on)20 b(de)d Ft(D)q FJ(\))f FG(Una)f(edici\023)-23 b(on)17 b Ft(E)954 2570 y Fo(D)1000 2563 y FG(\(o)d(simplemen)o(te)j Ft(E)t FG(\))e(de)g Ft(D)i FG(es)e(un)h(conjun)o(to)811 2663 y Ft(E)835 2670 y Fo(D)878 2663 y FG(=)d Ft(f)p Fz(E)986 2644 y Fs(m)1018 2663 y Ft(g)1041 2642 y Fs(M)1041 2677 y(m)p Fu(=1)37 2764 y FG(tal)k(que,)g(para)f(to)q(do)g Fz(m)e Ft(2)i(f)p FG(1)p Fz(;)8 b FG(2)p Fz(;)g(:)f(:)h(:)t(;)g(M)d Ft(g)p FG(,)15 b Fz(E)844 2747 y Fs(m)891 2764 y Ft(2)g Fz(E)s FG(\()p Fz(c)1011 2747 y Fs(m)1043 2764 y Fz(;)8 b(s)1085 2747 y Fs(m)1118 2764 y FG(\);)16 b(es)g(decir,)i Fz(E)1382 2747 y Fs(m)1431 2764 y FG(es)e(una)h(traza)f(de)h(edici\023) -23 b(on)37 2820 y(del)17 b(par)e(\()p Fz(c)230 2804 y Fs(m)262 2820 y Fz(;)8 b(s)304 2804 y Fs(m)337 2820 y FG(\))k Ft(2)h(D)q FG(.)37 2876 y Fp(2)37 3074 y FG(6)p eop %%Page: 7 13 7 12 bop -13 -33 a Fv(El)16 b(pr)n(oblema)g(de)g(la)g(evaluaci\023)-23 b(on)17 b(de)f(un)g(sistema)g(de)g(r)n(e)n(c)n(ono)n(cimiento)p Fz(:)8 b(:)g(:)p -13 -16 1857 2 v 32 110 a FG(En)13 b(adelan)o(te,)f(y) h(mien)o(tras)f(no)g(ha)o(y)o(a)g(am)o(big)q(\177)-24 b(uedad,)12 b(nos)h(referiremos)f(con)h(el)g(t)o(\023)-21 b(ermino)11 b(\\edici\023)-23 b(on")14 b(tan)o(to)-13 167 y(a)h(una)g(\\edici\023)-23 b(on)17 b(de)e Ft(D)q FG(")h(como)e(a)h(la)h(traza)e(de)i(edici\023)-23 b(on)17 b(de)e(un)h(solo)f(par)g(de)h(in)o(terpretaciones.)32 223 y(Extendemos)g(las)g(funciones)h(de)f(c\023)-23 b(omputo)16 b(del)h(n)q(\023)-24 b(umero)16 b(de)g(sustituciones,)g(inserciones,)i (b)q(orrados)d(y)-13 280 y(aciertos)g(al)g(caso)g(de)h(ediciones)h(de)f Ft(D)q FG(.)-13 358 y FJ(De\014nici\023)-26 b(on)18 b(10)f(\(N)q(\023) -28 b(umero)17 b(de)f(errores)f(y)h(aciertos)h(de)f(una)h(edici\023)-26 b(on)18 b(de)f Ft(D)q FJ(\))e FG(Sea)f Ft(E)k FG(una)d(edici\023)-23 b(on)-13 414 y(de)16 b Ft(D)q FG(.)g(Denotaremos)f(el)i(n)q(\023)-24 b(umero)17 b(de)f(sustituciones,)h(inserciones,)h(b)q(orrados)d(y)h (aciertos)g(en)h Ft(E)t FG(,)f(resp)q(ec-)-13 470 y(tiv)m(amen)o(te,)f (median)o(te)h(las)f(funciones)i Fz(N)706 477 y Fs(s)724 470 y FG(\()p Ft(E)t Fz(;)8 b Ft(D)q FG(\),)14 b Fz(N)906 477 y Fs(i)920 470 y FG(\()p Ft(E)t Fz(;)8 b Ft(D)q FG(\),)13 b Fz(N)1101 477 y Fs(b)1118 470 y FG(\()p Ft(E)t Fz(;)8 b Ft(D)q FG(\))15 b(y)g Fz(N)1327 477 y Fs(a)1347 470 y FG(\()p Ft(E)t Fz(;)8 b Ft(D)q FG(\):)598 601 y Fz(N)632 608 y Fs(s)651 601 y FG(\()p Ft(E)t Fz(;)g Ft(D)q FG(\))j(=)851 548 y Fs(M)839 561 y Fn(X)831 652 y Fs(m)p Fu(=1)915 601 y Fz(n)942 608 y Fs(s)961 601 y FG(\()p Fz(E)1016 583 y Fs(m)1048 601 y Fz(;)d(c)1089 583 y Fs(m)1121 601 y Fz(;)g(s)1163 583 y Fs(m)1196 601 y FG(\))p Fz(;)512 b FG(\(11a\))603 752 y Fz(N)637 759 y Fs(i)651 752 y FG(\()p Ft(E)t Fz(;)8 b Ft(D)q FG(\))j(=)851 699 y Fs(M)839 712 y Fn(X)831 802 y Fs(m)p Fu(=1)915 752 y Fz(n)942 759 y Fs(i)956 752 y FG(\()p Fz(E)1011 733 y Fs(m)1044 752 y Fz(;)d(c)1085 733 y Fs(m)1117 752 y Fz(;)g(s)1159 733 y Fs(m)1192 752 y FG(\))p Fz(;)514 b FG(\(11b\))600 903 y Fz(N)634 910 y Fs(b)651 903 y FG(\()p Ft(E)t Fz(;)8 b Ft(D)q FG(\))j(=)851 850 y Fs(M)839 862 y Fn(X)831 953 y Fs(m)p Fu(=1)915 903 y Fz(n)942 910 y Fs(b)960 903 y FG(\()p Fz(E)1015 884 y Fs(m)1047 903 y Fz(;)d(c)1088 884 y Fs(m)1120 903 y Fz(;)g(s)1162 884 y Fs(m)1195 903 y FG(\))p 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y(El)17 b(\\)-5 b(\023)-18 b(\020ndice)18 b(de)f(error)f(p)q(onderado") g(\(\\w)o(eigh)o(ted)g(total)f(error")h([Hun)o(t89)o(]\))f(presen)o(ta) h(la)h(propiedad)g(de)-13 1524 y(considerar)d(de)g(igual)h(mo)q(do)f (una)g(sustituci\023)-23 b(on)15 b(que)f(un)h(par)e(formado)g(p)q(or)h (una)g(inserci\023)-23 b(on)16 b(y)d(un)i(b)q(orrado:)-13 1605 y FJ(De\014nici\023)-26 b(on)19 b(15)f(\()321 1594 y(\023)324 1605 y(Indice)g(de)f(error)f(p)q(onderado\))633 1739 y Fz(T)660 1746 y Ff(IEP)740 1739 y FG(=)d(100)862 1706 y Fz(N)896 1713 y Fs(s)923 1706 y FG(+)974 1688 y Fu(1)p 974 1695 18 2 v 974 1722 a(2)997 1706 y Fz(N)1031 1713 y Fs(i)1055 1706 y FG(+)1105 1688 y Fu(1)p 1105 1695 V 1105 1722 a(2)1128 1706 y Fz(N)1162 1713 y Fs(b)p 862 1728 318 2 v 885 1770 a Fz(N)919 1777 y Fs(s)948 1770 y FG(+)d Fz(N)1027 1777 y Fs(b)1054 1770 y FG(+)h Fz(N)1134 1777 y Fs(a)1184 1739 y Fz(:)-13 1848 y Fp(2)32 1930 y FG(Al)16 b(igual)g(que)g(suced)-5 b(\023)-18 b(\020a)16 b(con)g Fz(T)560 1937 y Ff(IE)603 1930 y FG(,)f(la)g(funci\023)-23 b(on)17 b Fz(T)869 1937 y Ff(IEP)951 1930 y FG(no)e(est\023)-23 b(a)14 b(acotada)h(sup)q(eriormen)o(te.)32 1986 y(T)l(am)o(bi)o(\023) -21 b(en)14 b(aparece)h(en)g(la)g(literatura)f(su)h(v)o(ersi\023)-23 b(on)15 b(\\grado)e(de)i(acierto",)f(que)h(denominaremos)g(\\)-5 b(\023)-18 b(\020ndice)-13 2043 y(de)15 b(acierto)h(p)q(onderado")f (\(\\w)o(eigh)o(ted)g(w)o(ord)f(accuracy")h([WPN91)o(]\):)-13 2125 y FJ(De\014nici\023)-26 b(on)19 b(16)f(\()321 2114 y(\023)324 2125 y(Indice)g(de)f(acierto)i(p)q(onderado\))613 2258 y Fz(T)640 2265 y Ff(IAP)722 2258 y FG(=)13 b(100)844 2225 y Ft(\000)884 2208 y Fu(1)p 884 2215 18 2 v 884 2241 a(2)906 2225 y Fz(N)940 2232 y Fs(i)964 2225 y FG(+)1015 2208 y Fu(1)p 1015 2215 V 1015 2241 a(2)1037 2225 y Fz(N)1071 2232 y Fs(b)1099 2225 y FG(+)d Fz(N)1178 2232 y Fs(a)p 844 2248 356 2 v 886 2290 a Fz(N)920 2297 y Fs(s)949 2290 y FG(+)g Fz(N)1028 2297 y Fs(b)1055 2290 y FG(+)h Fz(N)1135 2297 y Fs(a)1204 2258 y Fz(:)-13 2367 y Fp(2)32 2449 y FG(Con)k(esta)g(de\014nici\023)-23 b(on)17 b(se)f(v)o(eri\014ca) f(que)h Fz(T)748 2456 y Ff(IAP)830 2449 y FG(=)d(100)c Ft(\000)i Fz(T)1029 2456 y Ff(IEP)1096 2449 y FG(.)32 2506 y(La)i(funci\023)-23 b(on)13 b(de)g(tasa)e(que)i(prop)q(ondremos)f (en)h(este)f(traba)s(jo,)e(y)i(que)h(y)o(a)f(ha)g(sido)h(empleada)g(en) g(traba)s(jos)-13 2562 y(an)o(teriores)i(\(\\global)g(error)f(rate")h ([Meri88)o(]\),)f(es)h(el)h(llamado)g(\\p)q(orcen)o(ta)s(je)e(real)i (de)g(errores":)-13 2644 y FJ(De\014nici\023)-26 b(on)19 b(17)f(\(P)o(orcen)o(ta)s(je)f(real)g(de)h(errores\))599 2767 y Fz(T)626 2774 y Ff(PRE)719 2767 y FG(=)13 b(100)895 2737 y Fz(N)929 2744 y Fs(s)957 2737 y FG(+)e Fz(N)1037 2744 y Fs(i)1061 2737 y FG(+)f Fz(N)1140 2744 y Fs(b)p 841 2757 373 2 v 841 2799 a Fz(N)875 2806 y Fs(s)902 2799 y FG(+)h Fz(N)982 2806 y Fs(i)1006 2799 y FG(+)f Fz(N)1085 2806 y Fs(b)1113 2799 y FG(+)g Fz(N)1192 2806 y Fs(a)1218 2767 y Fz(:)531 b FG(\(13\))-13 2876 y Fp(2)1820 3074 y FG(9)p eop %%Page: 10 16 10 15 bop 600 -33 a Fv(El)15 b(pr)n(oblema)i(de)f(la)g(evaluaci\023)-23 b(on)17 b(de)f(un)g(sistema)g(de)g(r)n(e)n(c)n(ono)n(cimiento)p Fz(:)8 b(:)g(:)p 37 -16 1857 2 v 83 110 a FG(Ob)o(viamen)o(te,)16 b(p)q(o)q(demos)h(considerar)g(tam)o(bi)o(\023)-21 b(en)15 b(el)i(\\p)q(orcen)o(ta)s(je)e(real)i(de)f(aciertos")g(\(\\p)q(ercen)o (t)g(total")37 167 y([CA)o(CV90)o(]\))f(como)f(la)i(funci\023)-23 b(on)16 b(de)g(tasa)e(an)o(terior)h(en)g(v)o(ersi\023)-23 b(on)16 b(\\grado)e(de)h(acierto":)37 245 y FJ(De\014nici\023)-26 b(on)19 b(18)f(\(P)o(orcen)o(ta)s(je)f(real)h(de)f(aciertos\))651 360 y Fz(T)678 367 y Ff(PRA)769 360 y FG(=)c(100)1049 329 y Fz(N)1083 336 y Fs(a)p 891 349 373 2 v 891 391 a Fz(N)925 398 y Fs(s)952 391 y FG(+)e Fz(N)1032 398 y Fs(i)1056 391 y FG(+)f Fz(N)1135 398 y Fs(b)1162 391 y FG(+)h Fz(N)1242 398 y Fs(a)1268 360 y Fz(:)37 460 y Fp(2)83 538 y FG(Eviden)o(temen)o(te,)16 b Fz(T)433 545 y Ff(PRA)523 538 y FG(=)d(100)d Ft(\000)g Fz(T)722 545 y Ff(PRE)802 538 y FG(.)83 595 y(N\023)-23 b(otese)18 b(que)h(tan)o(to)e Fz(T)472 602 y Ff(PRE)570 595 y FG(como)h Fz(T)719 602 y Ff(PRA)816 595 y FG(tratan)f(sim)o(\023)-21 b(etricamen)o(te)18 b(a)g(las)h(dos)f(cadenas)h(comparadas,)37 651 y(pues)i(la)g(normalizaci\023)-23 b(on)22 b(se)e(realiza)h(con)g (resp)q(ecto)f(a)g(am)o(bas.)f(P)o(or)h(con)o(tra,)f(las)h(dem\023)-23 b(as)20 b(funciones)i(de)37 707 y(tasa)13 b(consideradas)h(efect)q (\023)-24 b(uan)14 b(la)g(normalizaci\023)-23 b(on)14 b(considerando)i(\023)-24 b(unicamen)o(te)14 b(la)g(longitud)g(de)g(la) g(cadena)37 764 y(correcta.)83 820 y(Adem\023)-23 b(as,)15 b(tan)o(to)f Fz(T)416 827 y Ff(PRE)511 820 y FG(como)g Fz(T)656 827 y Ff(PRA)750 820 y FG(presen)o(tan)h(las)g(siguien)o(tes)i (caracter)-5 b(\023)-18 b(\020sticas)15 b(deseables:)106 907 y Ft(\017)22 b FG(se)17 b(trata)d(realmen)o(te)j(de)g(p)q(orcen)o (ta)s(jes,)e(p)q(or)h(lo)h(cual)g(su)f(v)m(alor)h(puede)h(v)m(ariar)e (\()q(\023)-24 b(unicamen)o(te\))17 b(en)o(tre)151 963 y(el)f(0\045)f(y)g(el)h(100\045;)106 1053 y Ft(\017)22 b FG(no)g(ignoran)g(las)g(inserciones,)h(de)f(mo)q(do)g(que)g(el)g(v)m (alor)h(\023)-23 b(optimo)21 b(de)h(am)o(bas)f(tasas)g(\(0\045)g(de)h (er-)151 1110 y(rores/100\045)13 b(de)j(aciertos\))f(s\023)-23 b(olo)15 b(se)g(alcanza)h(en)f(ausencia)i(de)e(errores.)37 1232 y Fq(3.2)53 b(Criterios)18 b(de)h(edici\023)-27 b(on)37 1318 y FG(Como)19 b(y)o(a)g(vimos,)h(una)g(funci\023)-23 b(on)20 b(de)h(ev)m(aluaci\023)-23 b(on)21 b(resulta)f(de)g(la)g (aplicaci\023)-23 b(on)22 b(de)e(una)f(funci\023)-23 b(on)21 b(de)f(tasa)37 1374 y(determinada)14 b(a)e(una)h(edici\023)-23 b(on)15 b Ft(E)599 1358 y Fo(\003)631 1374 y FG(\023)-23 b(optima)13 b(para)f(un)h(criterio)g(de)h(edici\023)-23 b(on)14 b(determinado,)f Fz(G)p FG(.)f(P)o(or)g(lo)h(tan)o(to,)37 1431 y(diferen)o(tes)20 b(criterios)g(de)f(edici\023)-23 b(on,)21 b(aun)e(con)g(la)g(misma)g(funci\023)-23 b(on)21 b(de)e(tasa,)f(prop)q(orcionar\023)-23 b(an)19 b(diferen)o(tes)37 1487 y(v)m(alores)d(de)g(la)f(funci\023)-23 b(on)17 b(de)e(ev)m (aluaci\023)-23 b(on.)83 1544 y(Los)18 b(criterios)h(de)f(edici\023)-23 b(on,)19 b Fz(G)p FG(,)f(utilizados)h(habitualmen)o(te)g(en)g(la)f (pr\023)-23 b(actica)18 b(corresp)q(onden)h(a)f(exten-)37 1600 y(siones)e(de)g(criterios)g(de)f(edici\023)-23 b(on,)17 b Fz(g)r FG(,)d(de)i(la)f(forma)f(de\014nida)j(en)f(\(9\):)37 1679 y FJ(De\014nici\023)-26 b(on)15 b(19)e(\(Criterio)h(de)f (edici\023)-26 b(on)14 b(p)q(or)f(con)o(teo)g(p)q(onderado)h(de)f(op)q (eraciones)h(de)f(edici\023)-26 b(on\))371 1772 y Fz(G)407 1779 y Fs(\015)425 1783 y Fh(s)442 1779 y Fs(;\015)470 1784 y Fh(i)483 1779 y Fs(;\015)511 1785 y Fh(b)527 1779 y Fs(;\015)555 1783 y Fh(a)576 1772 y FG(\()p Ft(E)t Fz(;)8 b Ft(D)q FG(\))j(=)i Fz(\015)780 1779 y Fs(s)798 1772 y Fz(N)832 1779 y Fs(s)850 1772 y FG(\()p Ft(E)t FG(\))d(+)g Fz(\015)993 1779 y Fs(i)1007 1772 y Fz(N)1041 1779 y Fs(i)1055 1772 y FG(\()p Ft(E)t FG(\))f(+)i Fz(\015)1198 1779 y Fs(b)1215 1772 y Fz(N)1249 1779 y Fs(b)1266 1772 y FG(\()p Ft(E)t FG(\))e(+)i Fz(\015)1409 1779 y Fs(a)1429 1772 y Fz(N)1463 1779 y Fs(a)1484 1772 y FG(\()p Ft(E)t FG(\))p Fz(:)252 b FG(\(14\))37 1866 y Fp(2)83 1944 y FG(Ob)o(viamen)o(te,)15 b(para)g(to)q(do)g Ft(D)h FG(y)f Ft(E)20 b FG(se)15 b(observ)m(a)503 2074 y Fz(G)539 2081 y Fs(\015)557 2085 y Fh(s)574 2081 y Fs(;\015)602 2086 y Fh(i)615 2081 y Fs(;\015)643 2087 y Fh(b)659 2081 y Fs(;\015)687 2085 y Fh(a)708 2074 y FG(\()p Ft(E)t Fz(;)8 b Ft(D)q FG(\))j(=)908 2021 y Fs(M)896 2034 y Fn(X)888 2124 y Fs(m)p Fu(=1)972 2074 y Fz(g)994 2081 y Fs(\015)1012 2085 y Fh(s)1028 2081 y Fs(;\015)1056 2086 y Fh(i)1070 2081 y Fs(;\015)1098 2087 y Fh(b)1113 2081 y Fs(;\015)1141 2085 y Fh(a)1162 2074 y FG(\()p Fz(E)1217 2055 y Fs(m)1249 2074 y Fz(;)d(c)1290 2055 y Fs(m)1323 2074 y Fz(;)g(s)1365 2055 y Fs(m)1397 2074 y FG(\))p Fz(:)385 b FG(\(15\))83 2201 y(T)l(al)23 b(como)f(se)g(comen)o(t\023)-23 b(o)22 b(en)h(el)g(apartado)e(2.1,)g(en)i(una)f(form)o(ulaci\023)-23 b(on)23 b(m\023)-23 b(as)22 b(general)h(ser)-5 b(\023)-18 b(\020a)23 b(p)q(osible)37 2258 y(p)q(onderar)e(de)g(mo)q(do)f(diferen) o(te)h(cada)f(una)g(de)h(las)g(op)q(eraciones)g(de)f(edici\023)-23 b(on)23 b(concretas)c([WF74)o(]:)g(p)q(or)37 2314 y(ejemplo,)d(si)g (consideramos)f(un)h(alfab)q(eto)f(\006)h(de)f(palabras,)g(el)h(coste)f (de)h(un)g(error)e(de)i(sustituci\023)-23 b(on)16 b(puede)37 2371 y(hacerse)d(dep)q(ender)h(de)e(la)h(similitud)i(fon)o(\023)-21 b(etica)11 b(en)o(tre)h(las)h(palabras)f(implicadas)i([PFF90)n(])e(\(v) o(\023)-21 b(ease)11 b(tam)o(bi)o(\023)-21 b(en)37 2427 y([PGDF86)o(]\).)14 b(No)h(obstan)o(te,)f(lo)h(habitual)h(es)g(encon)o (trarse)e(con)i(criterios)f(de)h(la)f(forma)g Fz(G)1613 2436 y Fu(\()p Fs(p)p Fu(\))1672 2427 y FG(=)e Fz(G)1756 2434 y Fu(1)p Fs(;p;p;)p Fu(0)1858 2427 y FG(.)83 2484 y(La)18 b(minimizaci\023)-23 b(on)21 b(de)e(un)g(criterio)g(de)g(esta)f (forma)g(admite)g(soluci\023)-23 b(on)20 b(e\014cien)o(te)g(p)q(or)e (Programaci\023)-23 b(on)37 2540 y(Din\023)g(amica.)16 b(Obs)o(\023)-21 b(erv)o(ese)15 b(que)g(se)h(v)o(eri\014ca)f(la)h (siguien)o(te)g(propiedad:)37 2627 y FJ(Propiedad)i(1)23 b FG(P)o(ara)14 b(to)q(do)h Fz(\015)575 2634 y Fs(s)593 2627 y FG(,)g Fz(\015)645 2634 y Fs(i)658 2627 y FG(,)g Fz(\015)710 2634 y Fs(b)727 2627 y FG(,)g Fz(\015)779 2634 y Fs(a)812 2627 y Ft(2)e FG(I)-8 b(R)q(:)270 2760 y(arg)7 b(min)282 2801 y Fo(E)s(2E)s Fu(\()p Fo(D)q Fu(\))425 2760 y Fz(G)461 2767 y Fs(\015)479 2771 y Fh(s)495 2767 y Fs(;\015)523 2772 y Fh(i)536 2767 y Fs(;\015)564 2773 y Fh(b)580 2767 y Fs(;\015)608 2771 y Fh(a)629 2760 y FG(\()p Ft(E)t Fz(;)h Ft(D)q FG(\))j(=)809 2688 y Fn(\()887 2760 y FG(arg)d(min)843 2801 y Fs(E)871 2791 y Fh(m)900 2801 y Fo(2)p Fs(E)r Fu(\()p Fs(c)981 2791 y Fh(m)1009 2801 y Fs(;s)1035 2791 y Fh(m)1065 2801 y Fu(\))1086 2760 y Fz(g)1108 2767 y Fs(\015)1126 2771 y Fh(s)1143 2767 y Fs(;\015)1171 2772 y Fh(i)1184 2767 y Fs(;\015)1212 2773 y Fh(b)1227 2767 y Fs(;\015)1255 2771 y Fh(a)1276 2760 y FG(\()p Fz(E)1331 2741 y Fs(m)1364 2760 y Fz(;)g(c)1405 2741 y Fs(m)1437 2760 y Fz(;)g(s)1479 2741 y Fs(m)1512 2760 y FG(\))1530 2688 y Fn(\))1563 2699 y Fs(M)1563 2815 y(m)p Fu(=1)1649 2760 y Fz(:)37 2876 y Fp(2)37 3074 y FG(10)p eop %%Page: 11 17 11 16 bop -13 -33 a Fv(El)16 b(pr)n(oblema)g(de)g(la)g(evaluaci\023)-23 b(on)17 b(de)f(un)g(sistema)g(de)g(r)n(e)n(c)n(ono)n(cimiento)p Fz(:)8 b(:)g(:)p -13 -16 1857 2 v 32 110 a FG(Esta)15 b(propiedad)i(hace)g(p)q(osible)g(pro)q(ceder)g(a)f(la)g (minimizaci\023)-23 b(on)18 b(del)f(criterio)g(de)f(edici\023)-23 b(on)18 b(median)o(te)f(la)-13 167 y(minimizaci\023)-23 b(on)14 b Fv(individual)j FG(de)12 b Fz(g)551 174 y Fs(\015)569 178 y Fh(s)585 174 y Fs(;\015)613 179 y Fh(i)627 174 y Fs(;\015)655 180 y Fh(b)670 174 y Fs(;\015)698 178 y Fh(a)731 167 y FG(sobre)g(cada)f(par)h(de)g(in)o(terpretaciones)h(de) f Ft(D)h FG(\(utilizando)h(la)e(re-)-13 223 y(currencia)i(\(5\)\))d(y)i 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(coher-)-13 1917 y(en)o(tes)g(para)g(algunas)g(de)h(las)f(funciones)h (de)g(tasa)e(que)i(aparecen)f(en)h(el)g(apartado)e(3.1.)g(Una)h(p)q (osibilidad)-13 1973 y(ob)o(via)j(de)h(obtener)f(coherencia)h(en)o(tre) f Fz(G)g FG(y)g Fz(T)25 b FG(es)19 b(de\014nir)i Fz(G)e FG(=)g Fz(T)25 b FG(\(si)20 b Fz(T)25 b FG(est\023)-23 b(a)18 b(en)i(v)o(ersi\023)-23 b(on)19 b(\\grado)f(de)-13 2030 y(acierto";)e(si)h(no,)f Fz(G)f FG(=)h Ft(\000)p Fz(T)23 b FG(es)16 b(la)h(elecci\023)-23 b(on)19 b(ob)o(via\).)d (Alternativ)m(amen)o(te,)h(n\023)-23 b(otese)17 b(que,)g(para)f(la)h (ma)o(y)o(or)-5 b(\023)-18 b(\020a)-13 2086 y(de)20 b(las)g(funciones)i (de)e(tasa)f Fz(T)26 b FG(que)20 b(aparecen)g(en)g(el)h(apartado)e (3.1,)f(el)j(denominador)g(de)f Fz(T)6 b FG(\()p Ft(E)t Fz(;)i Ft(D)q FG(\))19 b(es)-13 2143 y Fz(C)25 b FG(\(12a\),)20 b(p)q(ositiv)o(o)i(e)h(indep)q(endien)o(te)i(de)d Ft(E)t FG(,)g(de)g(mo)q(do)g(que)h(no)f(in)o(terviene)h(en)g(la)f(b)q(\023)-24 b(usqueda)23 b(de)g(la)-13 2199 y(edici\023)-23 b(on)19 b(\023)-23 b(optima.)17 b(As)-5 b(\023)-18 b(\020,)18 b(un)g(criterio)h(de)f(edici\023)-23 b(on)19 b(coheren)o(te)f(con)g(el) g(\\)-5 b(\023)-18 b(\020ndice)20 b(de)e(error",)e Fz(T)1592 2206 y Ff(IE)1653 2199 y FG(\(y)l(,)h(conse-)-13 2255 y(cuen)o(temen)o(te,)c(con)h(el)g(\\)-5 b(\023)-18 b(\020ndice)15 b(de)f(precisi\023)-23 b(on",)14 b Fz(T)849 2262 y Ff(IP)892 2255 y FG(\))f(ser)-5 b(\023)-18 b(\020a)13 b(equiv)m(alen)o(te)j(a)d (la)g(minimizaci\023)-23 b(on)16 b(del)f(n)q(\023)-24 b(umero)-13 2312 y(de)20 b(errores,)f(expresable)i(como)e Fz(G)604 2321 y Fu(\(1\))651 2312 y FG(.)g(P)o(or)g(otra)g(parte,)g Fz(G)1046 2321 y Fu(\(0)p Fs(:)p Fu(5\))1140 2312 y FG(es)h(coheren)o (te)g(con)g(el)g(\\p)q(orcen)o(ta)s(je)f(de)-13 2368 y(sustituciones)g(y)e(b)q(orrados",)f Fz(T)552 2375 y Ff(PSB)644 2368 y FG(\(y)l(,)h(consecuen)o(temen)o(te,)h(con)g(el)g (\\p)q(orcen)o(ta)s(je)f(de)h(aciertos",)f Fz(T)1776 2375 y Ff(P)m(A)1825 2368 y FG(\))-13 2425 y(y)o(a)f(que)h Fz(G)171 2432 y Fu(1)p Fs(;)p Fu(0)p Fs(;)p Fu(1)p Fs(;)p Fu(0)288 2425 y Ft(\021)f Fz(G)375 2434 y Fu(\(0)p Fs(:)p Fu(5\))449 2425 y FG(,)g(y)h(tam)o(bi)o(\023)-21 b(en)16 b(con)h(el)h(\\)-5 b(\023)-18 b(\020ndice)18 b(de)f(error)f(p)q (onderado")h(\(y)l(,)f(consecuen)o(temen)o(te,)-13 2481 y(con)f(el)h(\\)-5 b(\023)-18 b(\020ndice)17 b(de)f(acierto)f(p)q (onderado"\))g(y)o(a)g(que)g Fz(G)927 2488 y Fu(1)p Fs(;)p Fu(0)p Fs(:)p Fu(5)p Fs(;)p Fu(0)p Fs(:)p Fu(5)p Fs(;)p Fu(0)1096 2481 y Ft(\021)e Fz(G)1180 2491 y Fu(\(0)p Fs(:)p Fu(5\))1255 2481 y FG(.)32 2538 y(Finalmen)o(te,)20 b(el)g(\\p)q(orcen)o(ta)s(je)e(real)h(de)h(errores",)e(que)h(como)g (vimos)g(presen)o(ta)g(propiedades)h(que)g(lo)-13 2594 y(hacen)13 b(m\023)-23 b(as)12 b(atractiv)o(o)f(que)i(las)g(dem\023)-23 b(as)13 b(funciones)h(de)f(tasa,)e(presen)o(ta)h(un)h(denominador)g (que)g Fv(s)-5 b(\023)-19 b(\020)17 b FG(dep)q(ende)-13 2651 y(de)g(la)f(edici\023)-23 b(on)19 b Ft(E)t FG(.)d(P)o(arece)g(in)o (tuitiv)o(o)h(que)g Fz(T)757 2658 y Ff(PRE)853 2651 y Fv(no)h(pue)n(de)f(ser,)g(en)g(gener)n(al,)g(c)n(oher)n(ente)f(c)n(on)g Fz(G)1695 2660 y Fu(\()p Fs(p)p Fu(\))1759 2651 y Fv(p)n(ar)n(a)-13 2707 y(ning)q(\023)-24 b(un)17 b Fz(p)c Ft(2)g FG(I)-8 b(R)16 b Fv(pr)n(e)n(determinado)p FG(.)f(Un)h(resumen)g(de)f(esta)g (discusi\023)-23 b(on)17 b(aparece)e(en)h(la)f(T)l(abla)h(2.)32 2764 y(N\023)-23 b(otese)16 b(que)g(no)f(siempre)i(en)f(la)g (literatura)f(se)h(hace)g(uso)f(de)h(criterios)h(de)f(edici\023)-23 b(on)17 b(coheren)o(tes)f(con)g(la)-13 2820 y(funci\023)-23 b(on)17 b(de)g(tasa)f(corresp)q(ondien)o(te.)h(Generalmen)o(te)g(se)f (usa)g Fz(G)1111 2829 y Fu(\(1\))1158 2820 y FG(,)g(aunque)h(tam)o(bi)o (\023)-21 b(en)16 b(es)h(frecuen)o(te)f(que)-13 2876 y(el)g(criterio)g(de)f(edici\023)-23 b(on)17 b(usado)e(no)g(aparezca)g (totalmen)o(te)g(esp)q(eci\014cado.)1797 3074 y(11)p eop %%Page: 12 18 12 17 bop 600 -33 a Fv(El)15 b(pr)n(oblema)i(de)f(la)g(evaluaci\023)-23 b(on)17 b(de)f(un)g(sistema)g(de)g(r)n(e)n(c)n(ono)n(cimiento)p Fz(:)8 b(:)g(:)p 37 -16 1857 2 v 37 142 a FG(T)l(abla)16 b(2:)e(F)l(unciones)h(de)f(ev)m(aluaci\023)-23 b(on)15 b(aparecidas)f(en)g(la)f(literatura)h(con)f(su)h(corresp)q(ondien)o(te) g(criterio)g(de)215 198 y(edici\023)-23 b(on)18 b(coheren)o(te)d(den)o (tro)g(de)g(la)h(familia)g Fz(G)1013 207 y Fu(\()p Fs(p)p Fu(\))1060 198 y FG(.)p 312 270 1308 2 v 311 320 2 50 v 473 305 a FH(F)l(unci\023)-24 b(on)13 b(de)j(tasa)p 961 320 V 185 w(Criterio)e(de)h(edici\023)-24 b(on)14 b(coheren)o(te)p 1618 320 V 312 322 1308 2 v 311 467 2 146 v 426 405 a Fe(T)450 411 y Fd(P)m(A)510 405 y FI(=)e(100)720 377 y Fe(N)751 383 y Fc(a)p 621 395 249 2 v 621 433 a Fe(N)652 439 y Fc(s)679 433 y FI(+)d Fe(N)751 439 y Fc(b)777 433 y FI(+)h Fe(N)850 439 y Fc(a)p 961 467 2 146 v 1239 405 a Fe(G)1272 412 y Fb(\(0)p Fc(:)p Fb(5\))p 1618 467 V 312 469 1308 2 v 311 614 2 146 v 429 552 a Fe(T)453 558 y Fd(IP)506 552 y FI(=)i(100)669 524 y Fe(N)700 530 y Fc(a)729 524 y FC(\000)d Fe(N)801 530 y Fc(i)p 618 542 249 2 v 618 580 a Fe(N)649 586 y Fc(s)675 580 y FI(+)h Fe(N)748 586 y Fc(b)774 580 y FI(+)f Fe(N)846 586 y Fc(a)p 961 614 2 146 v 1252 552 a Fe(G)1285 559 y Fb(\(1\))p 1618 614 V 312 616 1308 2 v 311 761 2 146 v 429 699 a Fe(T)453 705 y Fd(IE)507 699 y FI(=)i(100)621 671 y Fe(N)652 677 y Fc(i)675 671 y FI(+)e Fe(N)747 677 y Fc(s)774 671 y FI(+)h Fe(N)847 677 y Fc(b)p 618 689 249 2 v 618 727 a Fe(N)649 733 y Fc(s)676 727 y FI(+)f Fe(N)748 733 y Fc(b)774 727 y FI(+)h Fe(N)847 733 y Fc(a)p 961 761 2 146 v 1252 699 a Fe(G)1285 706 y Fb(\(1\))p 1618 761 V 312 763 1308 2 v 311 908 2 146 v 415 846 a Fe(T)439 852 y Fd(PSB)521 846 y FI(=)i(100)683 818 y Fe(N)714 824 y Fc(s)741 818 y FI(+)e Fe(N)814 824 y Fc(b)p 632 836 249 2 v 632 874 a Fe(N)663 880 y Fc(s)690 874 y FI(+)g Fe(N)763 880 y Fc(b)789 874 y FI(+)f Fe(N)861 880 y Fc(a)p 961 908 2 146 v 1239 846 a Fe(G)1272 853 y Fb(\(0)p Fc(:)p Fb(5\))p 1618 908 V 312 910 1308 2 v 311 1055 2 146 v 395 993 a Fe(T)419 999 y Fd(IEP)495 993 y FI(=)i(100)606 962 y Fe(N)637 968 y Fc(s)664 962 y FI(+)710 946 y Fb(1)p 710 953 17 2 v 710 976 a(2)732 962 y Fe(N)763 968 y Fc(i)786 962 y FI(+)832 946 y Fb(1)p 832 953 V 832 976 a(2)854 962 y Fe(N)885 968 y Fc(b)p 606 983 296 2 v 629 1021 a Fe(N)660 1027 y Fc(s)687 1021 y FI(+)e Fe(N)759 1027 y Fc(b)785 1021 y FI(+)h Fe(N)858 1027 y Fc(a)p 961 1055 2 146 v 1239 993 a Fe(G)1272 1000 y Fb(\(0)p Fc(:)p Fb(5\))p 1618 1055 V 312 1057 1308 2 v 311 1202 2 146 v 376 1140 a Fe(T)400 1146 y Fd(IAP)478 1140 y FI(=)i(100)590 1109 y FC(\000)627 1093 y Fb(1)p 627 1100 17 2 v 627 1123 a(2)648 1109 y Fe(N)679 1115 y Fc(i)702 1109 y FI(+)749 1093 y Fb(1)p 749 1100 V 749 1123 a(2)770 1109 y Fe(N)801 1115 y Fc(b)827 1109 y FI(+)e Fe(N)900 1115 y Fc(a)p 589 1130 331 2 v 630 1168 a Fe(N)661 1174 y Fc(s)688 1168 y FI(+)g Fe(N)761 1174 y Fc(b)786 1168 y FI(+)g Fe(N)859 1174 y Fc(a)p 961 1202 2 146 v 1239 1140 a Fe(G)1272 1147 y Fb(\(0)p Fc(:)p Fb(5\))p 1618 1202 V 312 1204 1308 2 v 311 1349 2 146 v 364 1287 a Fe(T)388 1293 y Fd(PRE)476 1287 y FI(=)i(100)638 1258 y Fe(N)669 1264 y Fc(s)696 1258 y FI(+)e Fe(N)769 1264 y Fc(i)792 1258 y FI(+)f Fe(N)864 1264 y Fc(b)p 587 1277 345 2 v 587 1315 a Fe(N)618 1321 y Fc(s)645 1315 y FI(+)h Fe(N)718 1321 y Fc(i)741 1315 y FI(+)f Fe(N)813 1321 y Fc(b)839 1315 y FI(+)h Fe(N)912 1321 y Fc(a)p 961 1349 2 146 v 1270 1287 a FI(|)p 1618 1349 V 312 1351 1308 2 v 311 1496 2 146 v 365 1434 a Fe(T)389 1440 y Fd(PRA)476 1434 y FI(=)h(100)733 1405 y Fe(N)764 1411 y Fc(a)p 587 1424 345 2 v 587 1462 a Fe(N)618 1468 y Fc(s)645 1462 y FI(+)e Fe(N)717 1468 y Fc(i)740 1462 y FI(+)h Fe(N)813 1468 y Fc(b)839 1462 y FI(+)f Fe(N)911 1468 y Fc(a)p 961 1496 2 146 v 1270 1434 a FI(|)p 1618 1496 V 312 1497 1308 2 v 37 1687 a FB(4.)47 b(M)o(\023)-32 b(eto)r(do)21 b(de)g (evaluaci\023)-33 b(on)22 b(p)n(ropuesto)37 1807 y Fq(4.1)53 b(F)n(unci\023)-27 b(on)18 b(de)g(evaluaci\023)-27 b(on)37 1909 y FG(Un)18 b(asp)q(ecto)e(de)h(esp)q(ecial)i(imp)q(ortancia)f(en)f (esta)f(propuesta)h(consiste)g(en)g(p)q(ostular)g(que)g(la)g(funci\023) -23 b(on)18 b(de)37 1965 y(ev)m(aluaci\023)-23 b(on)19 b(utilizada)g(ha)e(de)h(ser)f(coheren)o(te)h(\(en)f(el)h(sen)o(tido)f (de\014nido)i(en)f(el)g(apartado)e(3.3\),)f(es)j(decir,)37 2022 y(si)i(hemos)f(elegido)h(una)f(funci\023)-23 b(on)20 b(de)g(tasa)e(que)h(mide)h(satisfactoriamen)o(te)e(el)i(grado)e(de)h (semejanza)g(\(o)37 2078 y(de)h(disimilitud\))i(en)o(tre)d(las)h(in)o (terpretaciones)g(correctas)e(y)h(del)i(sistema)e(en)g(el)h(conjun)o (to)f(de)h(datos)e Ft(D)37 2135 y FG(seg)q(\023)-24 b(un)14 b(una)f(cierta)h(edici\023)-23 b(on,)14 b(esa)f(misma)h(funci\023)-23 b(on)14 b(prop)q(orcionar\023)-23 b(a)13 b(el)h(criterio)g(para,)e (\014jado)h Ft(D)q FG(,)g(ev)m(aluar)h(la)37 2191 y(\\plausibili)q (dad")h(de)e(cada)f(una)h(de)g(sus)f(p)q(osibles)j(ediciones.)f(Esto,)d (que)i(puede)g(v)o(erse)g(como)f(la)h(aplicaci\023)-23 b(on)37 2247 y(de)18 b(un)g(cierto)f(principio)i(de)f(econom)-5 b(\023)-18 b(\020a)17 b(\(a)g(menos)g(que)g(se)g(justi\014que,)h(no)f (parece)h(hab)q(er)f(necesidad)i(de)37 2304 y(de\014nir)e(dos)e (funciones)i(diferen)o(tes)f(para)f(medir)h(el)h(grado)d(de)i (compatibilidad)i(en)o(tre)d(pares)g(de)h(cadenas)37 2360 y(y)h(ediciones)i(de)e(las)g(mismas\))g(trae)f(consigo)h(otra)f (propiedad)i(deseable:)g Fv(las)f(funciones)g(de)h(evaluaci\023)-23 b(on)37 2417 y(c)n(oher)n(entes)14 b(son)g(monovaluadas)p FG(,)g(es)g(decir,)g(una)g(funci\023)-23 b(on)15 b(de)f(ev)m (aluaci\023)-23 b(on)15 b(coheren)o(te)f(prop)q(orciona,)g(para)37 2473 y(cada)f(conjun)o(to)g Ft(D)q FG(,)f(un)j(\023)-24 b(unico)13 b(v)m(alor)g(\(el)h(resultado)f(de)g(optimizar)g(su)g (funci\023)-23 b(on)14 b(de)f(tasa\).)e(Esta)h(propiedad)37 2530 y(no)17 b(siempre)g(se)f(cumple)h(para)f(funciones)i(de)e(ev)m (aluaci\023)-23 b(on)18 b(no)e(coheren)o(tes,)g(pues)h(en)o(tonces)f (puede)i(darse)37 2586 y(el)g(caso)f(de)h(que)g(exista)f(m\023)-23 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y Ff(PRE)1824 2876 y FG(que)37 3074 y(12)p eop %%Page: 13 19 13 18 bop -13 -33 a Fv(El)16 b(pr)n(oblema)g(de)g(la)g(evaluaci\023)-23 b(on)17 b(de)f(un)g(sistema)g(de)g(r)n(e)n(c)n(ono)n(cimiento)p Fz(:)8 b(:)g(:)p -13 -16 1857 2 v -13 110 a FG(p)q(o)q(demos)15 b(expresar)h(como:)558 219 y Fz(f)580 226 y Ff(PRE)660 219 y FG(\()p Ft(D)q FG(\))d(=)36 b(min)793 251 y Fo(E)s(2E)s Fu(\()p Fo(D)q Fu(\))922 219 y Fz(T)949 226 y Ff(PRE)1029 219 y FG(\()p Ft(E)t Fz(;)8 b Ft(D)q FG(\))612 b(\(16\))745 314 y(=)13 b(100)c Ft(\001)33 b FG(min)894 346 y Fo(E)s(2E)s Fu(\()p Fo(D)q Fu(\))1023 314 y Fz(G)1059 321 y Ff(PRE)1139 314 y FG(\()p Ft(E)t Fz(;)8 b Ft(D)q FG(\))p Fz(;)-13 446 y FG(donde)442 522 y Fz(G)478 529 y Ff(PRE)558 522 y FG(\()p Ft(E)t Fz(;)g Ft(D)q FG(\))k(=)830 491 y Fz(N)864 498 y Fs(s)883 491 y FG(\()p Ft(E)t FG(\))d(+)i Fz(N)1036 498 y Fs(i)1050 491 y FG(\()p Ft(E)t FG(\))e(+)i Fz(N)1203 498 y Fs(b)1220 491 y FG(\()p Ft(E)t FG(\))p 744 511 627 2 v 744 553 a Fz(N)778 560 y Fs(s)796 553 y FG(\()p Ft(E)t FG(\))e(+)i Fz(N)949 560 y Fs(i)963 553 y FG(\()p Ft(E)t FG(\))e(+)i Fz(N)1116 560 y Fs(b)1133 553 y FG(\()p Ft(E)t FG(\))e(+)i Fz(N)1286 560 y Fs(a)1307 553 y FG(\()p Ft(E)t FG(\))1375 522 y Fz(:)374 b FG(\(17\))32 637 y(Esta)14 b(funci\023)-23 b(on)16 b(de)f(ev)m(aluaci\023)-23 b(on)16 b(puede)f(v)o(erse)g(como)f(una)h(generalizaci\023)-23 b(on)16 b(de)f(la)g(\\)p Fv(distancia)g(de)g(e)n(dici\023)-23 b(on)-13 693 y(normalizada)s FG(")14 b(de\014nida)h(para)e(pares)h(de)g (cadenas)g([MV93)o(])f(a)h(secuencias)h(de)f(pares)f(de)i(cadenas)f (\(expre-)-13 749 y(sada)h(en)g(tan)o(to)f(p)q(or)h(cien)i(y)e(con)g(p) q(eso)h(1)f(para)f(los)i(errores)e(y)i(0)e(para)h(los)h(aciertos\).)-13 886 y Fq(4.2)53 b(M)o(\023)-26 b(eto)r(do)15 b(de)k(c)o(\023)-27 b(alculo)-13 976 y FG(P)o(ara)14 b(completar)g(n)o(uestra)h(propuesta)f (s\023)-23 b(olo)15 b(resta)f(presen)o(tar)h(un)g(m)o(\023)-21 b(eto)q(do)14 b(e\014cien)o(te)i(que)f(p)q(ermita,)g(dado)-13 1032 y Ft(D)q FG(,)10 b(calcular)h(el)g(v)m(alor)g(de)f Fz(f)438 1039 y Ff(PRE)519 1032 y FG(\()p Ft(D)q FG(\).)f(Obs)o(\023) -21 b(erv)o(ese)10 b(que)g(tan)o(to)f(el)i(n)o(umerador)f(como)g(el)h (denominador)f(de)h(\(17\))-13 1089 y(son)16 b(dep)q(endien)o(tes)i(de) f(la)f(edici\023)-23 b(on)18 b Ft(E)t FG(.)e(Una)g(apro)o(ximaci\023) -23 b(on)16 b(con)o(v)o(encional)h(conduce)h(a)d(un)i(algoritmo)e(de) -13 1145 y(Programaci\023)-23 b(on)15 b(Din\023)-23 b(amica)17 b(similar)h(al)f(propuesto)f(en)h([MV93)o(])f(cuy)o(o)g(coste)g(temp)q (oral)g(es)h(prop)q(orcional)-13 1202 y(al)e Fv(cuadr)n(ado)h FG(del)g(menor)f(de)g Fz(C)i FG(y)e Fz(S)i FG(p)q(or)e(el)h(ma)o(y)o (or)d(de)i(am)o(b)q(os,)f(y)h(con)g(unos)g(requerimien)o(tos)g (espaciales)-13 1258 y(prop)q(orcionales)k(al)g Fv(cuadr)n(ado)g FG(del)g(menor)f(de)h Fz(C)i FG(y)d Fz(S)i FG(\(T)l(abla)f(3\).)e(Si)i (sup)q(onemos)f(que)h(la)f(talla)h(de)g(las)-13 1314 y(in)o(terpretaciones)c(correctas)f(y)g(del)h(sistema)g(para)f(el)h (conjun)o(to)f(de)h(pron)o(unciaciones)h(son)e(comparables,)-13 1371 y(el)i(coste)f(temp)q(oral)g(del)h(algoritmo)f(es)g Fv(c)q(\023)-24 b(ubic)n(o)p FG(.)32 1430 y(Esta)21 b(situaci\023)-23 b(on)22 b(se)f(v)o(e)g(agra)o(v)m(ada)f(p)q(orque)h(en)g(el)h(caso)f (de)g Fz(G)1146 1437 y Ff(PRE)1247 1430 y FG(no)g(es)g(p)q(osible)i (pro)q(ceder)f(a)f(una)-13 1486 y(minimizaci\023)-23 b(on)23 b(individual)g(sobre)d(cada)g(uno)h(de)g(los)f(pares)g(de)h(in) o(terpretaciones)g(y)l(,)f(p)q(osteriormen)o(te,)-13 1542 y(com)o(binar)15 b(los)g(resultados)g(parciales,)g(pues)h(no)e(se) h(observ)m(a)g(una)g(propiedad)h(an\023)-23 b(aloga)14 b(a)h(la)g(Propiedad)g(1)-13 1599 y(\(apartado)c(3.2\).)g(Si)i(tenemos) g(en)g(cuen)o(ta)g(que)g(al)g(ev)m(aluar)g(un)g(sistema)g(de)g(recono)q (cimien)o(to)g(cab)q(e)h(esp)q(erar)-13 1655 y(que)22 b(se)g(presen)o(ten)g(n)o(umerosos)f(pares)g(de)h(in)o(terpretaciones,) g(p)q(o)q(demos)g(concluir)i(que)e(el)g(empleo)g(de)-13 1712 y(la)f(t)o(\023)-21 b(ecnica)22 b(de)f(Programaci\023)-23 b(on)21 b(Din\023)-23 b(amica)22 b(en)g(la)f(minimizaci\023)-23 b(on)24 b(de)e Fz(G)1288 1719 y Ff(PRE)1389 1712 y FG(conduce)h(a)e (unos)g(costes)-13 1768 y(prohibitiv)o(os.)-13 1911 y(T)l(abla)15 b(3:)g(Complejidad)25 b(resultan)o(te)e(de)h(ab)q(ordar)f(p)q(or)h (Programaci\023)-23 b(on)22 b(Din\023)-23 b(amica)24 b(la)g(ev)m(aluaci\023)-23 b(on)25 b(de)165 1967 y Fz(f)187 1974 y Ff(PRE)267 1967 y FG(.)15 b(Notaci\023)-23 b(on:)15 b Fz(\013)e FG(=)g(min)q(\()p Fz(C)q(;)8 b(S)s FG(\),)k Fz(\014)i FG(=)f(max\()p Fz(C)q(;)8 b(S)s FG(\).)p 535 2033 759 2 v 534 2179 2 146 v 543 2179 V 569 2116 a(Complejidad)16 b(temp)q(oral)p 1037 2179 V 50 w Fz(\022)q FG(\()p Fz(\014)c Ft(\001)e Fz(\013)1193 2100 y Fu(2)1213 2116 y FG(\))p 1285 2179 V 1294 2179 V 535 2180 759 2 v 534 2326 2 146 v 543 2326 V 569 2263 a(Complejidad)16 b(espacial)p 1037 2326 V 105 w Fz(\022)q FG(\()p Fz(\013)1162 2247 y Fu(2)1183 2263 y FG(\))p 1285 2326 V 1294 2326 V 535 2327 759 2 v -13 2561 a 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FG(Los)19 b(algoritmos)f(de)i (Programaci\023)-23 b(on)18 b(F)l(raccional)h(p)q(ermiten)h(resolv)o (er)f(algunos)g(problemas)h(de)f(opti-)37 167 y(mizaci\023)-23 b(on)17 b(con)e(funciones)i(ob)s(jetiv)o(o)d(racionales.)i(Si)g (deseamos)f(cono)q(cer)615 270 y(min)591 301 y Fo(E)s(2E)s Fu(\()p Fo(D)q Fu(\))721 270 y Fz(G)757 277 y Ff(PRE)837 270 y FG(\()p Ft(E)t Fz(;)8 b Ft(D)q FG(\))k(=)36 b(min)1018 301 y Fo(E)s(2E)s Fu(\()p Fo(D)q Fu(\))1152 239 y Fz(h)1178 246 y Fs(n)1202 239 y FG(\()p Ft(E)t Fz(;)8 b Ft(D)q FG(\))p 1152 259 170 2 v 1154 301 a Fz(h)1180 308 y Fs(d)1200 301 y FG(\()p Ft(E)t Fz(;)g Ft(D)q FG(\))1327 270 y Fz(;)37 375 y FG(donde)531 456 y Fz(h)557 463 y Fs(n)581 456 y FG(\()p Ft(E)t Fz(;)g Ft(D)q FG(\))j(=)i Fz(N)795 463 y Fs(s)813 456 y FG(\()p Ft(E)t FG(\))d(+)g Fz(N)966 463 y Fs(i)980 456 y FG(\()p Ft(E)t FG(\))g(+)g Fz(N)1133 463 y Fs(b)1150 456 y FG(\()p Ft(E)t FG(\))p Fz(;)534 525 y(h)560 532 y Fs(d)581 525 y FG(\()p Ft(E)t Fz(;)e Ft(D)q FG(\))j(=)i Fz(N)795 532 y Fs(s)813 525 y FG(\()p Ft(E)t FG(\))d(+)g Fz(N)966 532 y Fs(i)980 525 y FG(\()p Ft(E)t FG(\))g(+)g Fz(N)1133 532 y Fs(b)1150 525 y FG(\()p Ft(E)t FG(\))g(+)g Fz(N)1303 532 y Fs(a)1324 525 y FG(\()p Ft(E)t FG(\))p Fz(;)37 606 y FG(se)16 b(de\014ne)g(un)g(n)o(uev)o(o)f (problema)g(param)o(\023)-21 b(etrico)14 b(de)i(la)f(forma)600 688 y(\000\()p Fz(\025)p FG(\))d(=)36 b(min)751 720 y Fo(E)s(2E)s Fu(\()p Fo(D)q Fu(\))880 688 y Fz(h)906 695 y Fs(n)930 688 y FG(\()p Ft(E)t Fz(;)8 b Ft(D)q FG(\))h Ft(\000)i Fz(\025)e Ft(\001)h Fz(h)1191 695 y Fs(d)1211 688 y FG(\()p Ft(E)t Fz(;)e Ft(D)q FG(\))37 793 y(cuy)o(a)18 b(soluci\023)-23 b(on)19 b(para)e(un)h Fz(\025)f FG(particular)h (coincide)i(con)e(la)f(soluci\023)-23 b(on)19 b(al)f(problema)g (original.)g(Dic)o(ho)g Fz(\025)f FG(se)37 849 y(obtiene)d(p)q(or)e(un) h(pro)q(cedimien)o(to)h(de)f(sucesiv)m(as)h(apro)o(ximaciones)f(cuy)o (a)f(con)o(v)o(ergencia)h(est\023)-23 b(a)12 b(garan)o(tizada.)37 906 y(El)20 b(pro)q(cedimien)o(to)g(en)g(cuesti\023)-23 b(on)20 b(toma)e(como)g(primera)h(estimaci\023)-23 b(on)20 b(de)g Fz(\025)e FG(un)i(v)m(alor)f(arbitrario)g(de)g(la)37 962 y(funci\023)-23 b(on)18 b(ob)s(jetiv)o(o;)e(a)g(con)o(tin)o (uaci\023)-23 b(on)17 b(encuen)o(tra)g(una)g(edici\023)-23 b(on)18 b Ft(E)1177 946 y Fo(0)1206 962 y FG(tal)e(que)h Fz(h)1387 969 y Fs(n)1411 962 y FG(\()p Ft(E)1457 946 y Fo(0)1468 962 y Fz(;)8 b Ft(D)q FG(\))i Ft(\000)i Fz(\025)e Ft(\001)h Fz(h)1687 969 y Fs(d)1707 962 y FG(\()p Ft(E)1753 946 y Fo(0)1765 962 y Fz(;)d Ft(D)q FG(\))15 b(es)37 1019 y(m)-5 b(\023)-18 b(\020nimo)19 b(y)f(hace)g(que)h(el)f(n)o(uev)o (o)g(v)m(alor)g(de)g Fz(\025)g FG(sea)f Fz(G)960 1026 y Ff(PRE)1040 1019 y FG(\()p Ft(E)1086 1002 y Fo(0)1098 1019 y Fz(;)8 b Ft(D)q FG(\).)16 b(El)j(algoritmo)e(se)h(detiene)h (cuando)f(no)37 1075 y(se)h(exp)q(erimen)o(ta)g(cam)o(bio)f(en)h(la)g (estimaci\023)-23 b(on)19 b(de)g Fz(\025)p FG(,)e(resultando)i(el)g (propio)g(v)m(alor)f(de)h Fz(\025)f FG(la)g(soluci\023)-23 b(on)20 b(al)37 1132 y(problema)c(original.)83 1188 y(M\023)-23 b(as)14 b(concretamen)o(te,)h(ha)o(y)g(que)g(notar)g(que)213 1270 y(\000\()p Fz(\025)p FG(\))d(=)36 b(min)364 1301 y Fo(E)s(2E)s Fu(\()p Fo(D)q Fu(\))486 1270 y FG(\()p Fz(N)538 1277 y Fs(s)556 1270 y FG(\()p Ft(E)t FG(\))10 b(+)g Fz(N)709 1277 y Fs(i)723 1270 y FG(\()p Ft(E)t FG(\))g(+)g Fz(N)876 1277 y Fs(b)893 1270 y FG(\()p Ft(E)t FG(\)\))f Ft(\000)i Fz(\025)p FG(\()p Fz(N)1109 1277 y Fs(s)1126 1270 y FG(\()p Ft(E)t FG(\))f(+)g Fz(N)1279 1277 y Fs(i)1293 1270 y FG(\()p Ft(E)t FG(\))g(+)g Fz(N)1446 1277 y Fs(b)1463 1270 y FG(\()p Ft(E)t FG(\))g(+)g Fz(N)1616 1277 y Fs(a)1637 1270 y FG(\()p Ft(E)t FG(\)\))316 1365 y(=)36 b(min)364 1396 y Fo(E)s(2E)s Fu(\()p Fo(D)q Fu(\))486 1365 y FG(\(1)10 b Ft(\000)g Fz(\025)p FG(\))p Fz(N)661 1372 y Fs(s)679 1365 y FG(\()p Ft(E)t FG(\))f(+)i(\(1)e Ft(\000)h Fz(\025)p FG(\))p Fz(N)972 1372 y Fs(i)986 1365 y FG(\()p Ft(E)t FG(\))f(+)i(\(1)e Ft(\000)i Fz(\025)p FG(\))p Fz(N)1280 1372 y Fs(b)1296 1365 y FG(\()p Ft(E)t FG(\))e Ft(\000)i Fz(\025N)1476 1372 y Fs(a)1496 1365 y FG(\()p Ft(E)t FG(\))316 1460 y(=)36 b(min)364 1491 y Fo(E)s(2E)s Fu(\()p Fo(D)q Fu(\))494 1460 y Fz(G)530 1467 y Fu(1)p Fo(\000)p Fs(\025;)p Fu(1)p Fo(\000)p Fs(\025;)p Fu(1)p Fo(\000)p Fs(\025;)p Fo(\000)p Fs(\025)806 1460 y FG(\()p Ft(E)t Fz(;)8 b Ft(D)q FG(\))37 1564 y(y)16 b(que)f Fz(G)197 1571 y Fu(1)p Fo(\000)p Fs(\025;)p Fu(1)p Fo(\000)p Fs(\025;)p Fu(1)p Fo(\000)p Fs(\025;)p Fo(\000)p Fs(\025)486 1564 y Ft(\021)e Fz(G)570 1573 y Fu(\(1)p Fo(\000)p Fs(\025=)p Fu(2\))700 1564 y FG(.)83 1621 y(As)-5 b(\023)-18 b(\020)15 b(pues,)f(en)g(cada)g(iteraci\023)-23 b(on)15 b(del)g(algoritmo)f(que)g(calcula)h Fz(f)1158 1628 y Ff(PRE)1239 1621 y FG(\()p Ft(D)q FG(\),)e(se)h(busca)h(una)f (edici\023)-23 b(on)16 b(\023)-23 b(optima)37 1677 y(seg)q(\023)f(un)19 b(un)f(criterio)g Fz(G)430 1686 y Fu(\()p Fs(p)p Fu(\))495 1677 y FG(con)g Fz(p)e FG(=)i(1)11 b Ft(\000)h FG(\()p Fz(\025=)p FG(2\).)k(El)i(algoritmo)f(resultan)o(te)h(se)g(m)o(uestra)f (en)h(la)g(Figura)g(2)37 1734 y(y)e(su)g(coste)f(en)h(la)f(T)l(abla)h (4.)f(En)h(ella,)g Fz(K)i FG(es)e(el)g(n)q(\023)-24 b(umero)16 b(de)f(iteraciones)i(del)f(bucle)h(\\)p FJ(rep)q(etir)p Fz(:)8 b(:)g(:)e FJ(hasta)p FG(")37 1790 y(que)16 b(efectuamos)f(hasta) f(la)i(con)o(v)o(ergencia)f(del)i(algoritmo.)37 1921 y(T)l(abla)f(4:)e(Complejidad)24 b(resultan)o(te)e(de)g(ab)q(ordar)f(p) q(or)h(Programaci\023)-23 b(on)21 b(F)l(raccional)i(la)f(ev)m (aluaci\023)-23 b(on)24 b(de)215 1978 y Fz(f)237 1985 y Ff(PRE)318 1978 y FG(.)14 b(El)h(n)q(\023)-24 b(umero)14 b(de)h(iteraciones)h(efectuadas)e(hasta)g(alcanzar)g(la)h(con)o(v)o (ergencia)g(viene)h(indi-)215 2034 y(cado)g(p)q(or)f Fz(K)s FG(.)p 400 2098 1131 2 v 399 2243 2 146 v 408 2243 V 433 2181 a(Complejidad)i(temp)q(oral)p 902 2243 V 104 w Fz(\022)1013 2109 y Fn( )1045 2181 y Fz(K)c Ft(\001)1140 2128 y Fs(M)1128 2140 y Fn(X)1120 2231 y Fs(m)p Fu(=1)1204 2181 y Ft(j)p Fz(c)1237 2162 y Fs(m)1270 2181 y Ft(j)s(\001)s(j)p Fz(s)1336 2162 y Fs(m)1367 2181 y Ft(j)1380 2109 y Fn(!)p 1522 2243 V 1531 2243 V 400 2245 1131 2 v 399 2390 2 146 v 408 2390 V 433 2328 a FG(Complejidad)k(espacial)p 902 2390 V 75 w Fz(\022)958 2268 y Fn(\022)1017 2328 y FG(max)988 2357 y Fu(1)p Fo(\024)p Fs(m)p Fo(\024)p Fs(M)1130 2328 y FG(\(min\()p Ft(j)p Fz(c)1274 2309 y Fs(m)1306 2328 y Ft(j)p Fz(;)8 b Ft(j)p Fz(s)1374 2309 y Fs(m)1406 2328 y Ft(j)p FG(\))1437 2268 y Fn(\023)p 1522 2390 V 1531 2390 V 400 2392 1131 2 v 83 2538 a FG(Obs)o(\023)-21 b(erv)o(ese)10 b(que)i(en)f(la)i(\023)-24 b(ultima)11 b(iteraci\023)-23 b(on)12 b(del)g(algoritmo,)e(cuando)h(se)g(obtiene)h (la)f(edici\023)-23 b(on)13 b(que)f(minimiza)37 2594 y(el)20 b(\\p)q(orcen)o(ta)s(je)e(real)g(de)h(errores",)f(el)h (criterio)g(utilizado)i(es)d Fz(G)1177 2603 y Fu(\()p Fs(p)p Fu(\))1243 2594 y FG(con)g Fz(p)h FG(=)f(1)12 b Ft(\000)h FG(\()p Fz(f)1547 2601 y Ff(PRE)1627 2594 y FG(\()p Ft(D)q FG(\))p Fz(=)p FG(200\).)k(De)37 2651 y(otro)c(mo)q(do:)g(el)i(criterio)g Fz(G)507 2660 y Fu(\()p Fs(p)p Fu(\))567 2651 y FG(prop)q(orciona)g(la)f(edici\023)-23 b(on)15 b(que)g(minimiza)g(el)g(\\p)q(orcen)o(ta)s(je)e(real)h(de)g (errores")37 2707 y(cuando)i Fz(f)216 2714 y Ff(PRE)297 2707 y FG(\()p Ft(D)q FG(\))d(=)h(200\(1)9 b Ft(\000)h Fz(p)p FG(\).)15 b(En)h(particular,)g Fz(G)995 2716 y Fu(\(1\))1057 2707 y FG(\(aso)q(ciado)g(a)f(la)h(distancia)h(de)f(Lev)o (ensh)o(tein\))g(y)37 2764 y Fz(G)73 2773 y Fu(\(0)p Fs(:)p Fu(5\))162 2764 y FG(\(aso)q(ciado)e(a)f(la)i(talla)f(de)h(la)f (LCS\))g(corresp)q(onden,)h(resp)q(ectiv)m(amen)o(te,)g(a)f(las)g (situaciones)h Fz(f)1765 2771 y Ff(PRE)1858 2764 y FG(=)37 2820 y(0\045)g(y)g Fz(f)174 2827 y Ff(PRE)267 2820 y FG(=)e(100\045.)83 2876 y(En)i(el)h(Ap)o(\023)-21 b(endice)16 b(A)g(se)f(m)o(uestra)f(una)i(\\implemen)o(taci\023)-23 b(on")16 b(de)g Fz(f)1220 2883 y Ff(PRE)1315 2876 y FG(en)g Fg(ansi)h(c)e FG(\(funci\023)-23 b(on)16 b Fm(Fpre)p FG(\).)37 3074 y(14)p eop %%Page: 15 21 15 20 bop -13 -33 a Fv(El)16 b(pr)n(oblema)g(de)g(la)g(evaluaci\023)-23 b(on)17 b(de)f(un)g(sistema)g(de)g(r)n(e)n(c)n(ono)n(cimiento)p Fz(:)8 b(:)g(:)p -13 -16 1857 2 v 179 161 a FJ(Algoritmo)15 b FG(C\023)-23 b(alculo)16 b(de)g Fz(f)673 168 y Ff(PRE)270 218 y FJ(en)o(trada)8 b Ft(D)14 b FG(=)f Ft(f)p FG(\()p Fz(c)609 201 y Fs(m)642 218 y Fz(;)8 b(s)684 201 y Fs(m)717 218 y FG(\))p Ft(g)758 201 y Fs(M)758 229 y(m)p Fu(=1)270 274 y FJ(salida)53 b Fz(\025)p FG(:)15 b(I)-8 b(R)179 331 y FJ(inicio)270 387 y Ft(E)298 370 y Fo(0)322 387 y FG(:=)13 b(arbitrario)o(\()p Ft(E)t FG(\()p Ft(D)q FG(\)\))270 470 y Fz(\025)f FG(:=)467 439 y Fz(N)501 446 y Fs(s)519 439 y FG(\()p Ft(E)565 422 y Fo(0)577 439 y FG(\))d(+)i Fz(N)684 446 y Fs(i)698 439 y FG(\()p Ft(E)744 422 y Fo(0)755 439 y FG(\))f(+)h Fz(N)863 446 y Fs(b)880 439 y FG(\()p Ft(E)926 422 y Fo(0)937 439 y FG(\))p 374 459 673 2 v 374 501 a Fz(N)408 508 y Fs(s)427 501 y FG(\()p Ft(E)473 484 y Fo(0)484 501 y FG(\))f(+)g Fz(N)591 508 y Fs(i)605 501 y FG(\()p Ft(E)651 484 y Fo(0)663 501 y FG(\))f(+)i Fz(N)770 508 y Fs(b)787 501 y FG(\()p Ft(E)833 484 y Fo(0)844 501 y FG(\))f(+)h Fz(N)952 508 y Fs(a)972 501 y FG(\()p Ft(E)1018 484 y Fo(0)1030 501 y FG(\))1158 470 y Fv(//)17 b(Inicializaci\023)-23 b(on)14 b(de)j Fz(\025)e FG(//)270 552 y FJ(rep)q(etir)361 608 y Fz(\025)388 592 y Fo(0)411 608 y FG(:=)e Fz(\025)361 665 y(p)f FG(:=)h(1)c Ft(\000)i FG(\()p Fz(\025)580 648 y Fo(0)591 665 y Fz(=)p FG(2\))361 721 y Ft(E)389 702 y Fo(0)413 721 y FG(:=)h(arg)c(min)486 762 y Fo(E)s(2E)s Fu(\()p Fo(D)q Fu(\))628 721 y Fz(G)664 730 y Fu(\()p Fs(p)p Fu(\))711 721 y FG(\()p Ft(E)t Fz(;)g Ft(D)q FG(\))361 834 y Fz(\025)k FG(:=)558 809 y Fz(N)592 816 y Fs(s)610 809 y FG(\()p Ft(E)656 793 y Fo(0)668 809 y FG(\))d(+)i Fz(N)775 816 y Fs(i)789 809 y FG(\()p Ft(E)835 793 y Fo(0)846 809 y FG(\))f(+)g Fz(N)953 816 y Fs(b)971 809 y FG(\()p Ft(E)1017 793 y Fo(0)1028 809 y FG(\))p 465 824 V 465 860 a Fz(N)499 867 y Fs(s)518 860 y FG(\()p Ft(E)564 844 y Fo(0)575 860 y FG(\))g(+)g Fz(N)682 867 y Fs(i)696 860 y FG(\()p Ft(E)742 844 y Fo(0)754 860 y FG(\))f(+)i Fz(N)861 867 y Fs(b)878 860 y FG(\()p Ft(E)924 844 y Fo(0)935 860 y FG(\))f(+)g Fz(N)1042 867 y Fs(a)1063 860 y FG(\()p Ft(E)1109 844 y Fo(0)1121 860 y FG(\))270 911 y FJ(hasta)16 b Fz(\025)c FG(=)h Fz(\025)520 895 y Fo(0)270 968 y Fz(\025)f FG(:=)g(100)e Ft(\001)f Fz(\025)179 1024 y FJ(\014n)137 1215 y FG(Figura)15 b(2:)g(Algoritmo)g(para)g(la)g (ev)m(aluaci\023)-23 b(on)17 b(de)f Fz(f)1008 1222 y Ff(PRE)1103 1215 y FG(p)q(or)g(Programaci\023)-23 b(on)14 b(F)l(raccional.)-13 1350 y FA(4.2.2)50 b(Cuestiones)15 b(p)o(r)o(\023)-24 b(acticas:)16 b(la)g(inicializaci\023)-25 b(on)-13 1437 y FG(En)17 b(situaciones)i(an\023)-23 b(alogas)17 b(a)g(la)h(aqu)-5 b(\023)-18 b(\020)18 b(considerada,)g(se)f(observ)m (a)h(que)g(el)g(n)q(\023)-24 b(umero)18 b(de)g(iteraciones)g(efec-)-13 1494 y(tuadas)h(hasta)h(alcanzar)g(la)g(con)o(v)o(ergencia,)g Fz(K)s FG(,)f(dep)q(ende)j(de)f(lo)f(acertado)f(de)i(la)f(inicializaci) q(\023)-23 b(on)23 b(de)d Fz(\025)-13 1550 y FG([VMA94)o(].)9 b(Resulta)i(con)o(v)o(enien)o(te,)g(pues,)g(realizar)g(una)f(inicializ) q(aci\023)-23 b(on)13 b(tan)d(cercana)h(a)f(la)g(soluci\023)-23 b(on)12 b(\023)-23 b(optima)-13 1607 y(como)14 b(sea)g(p)q(osible)j (\(con)d(un)h(coste)f(computacional)i(razonable,)e(claro)h(est\023)-23 b(a\).)13 b(En)i([VMA94)o(])f(se)g(prop)q(one)-13 1663 y(usar)i(un)h(m)o(\023)-21 b(eto)q(do)15 b(heur)-5 b(\023)-18 b(\020stico)18 b(que,)f(en)f(un)h(elev)m(ado)h(p)q(orcen)o(ta)s(je)e (de)h(casos,)f(prop)q(orciona)g(directamen)o(te)-13 1720 y(el)e(v)m(alor)g(\014nal)h(de)f Fz(\025)p FG(,)f(con)h(lo)g(que)g(el)g (pro)q(cedimien)o(to)h(de)g(c\023)-23 b(omputo)13 b(de)h Fz(f)1236 1727 y Ff(PRE)1330 1720 y FG(s\023)-23 b(olo)14 b(necesita)g(efectuar)g(algo)-13 1776 y(m\023)-23 b(as)15 b(de)g(dos)g(iteraciones)h(en)g(promedio)g(\()p Fz(K)768 1768 y(>)768 1784 y Ft(\030)802 1776 y FG(2\).)32 1833 y(En)h(el)h(Ap)o(\023)-21 b(endice)18 b(A)e(se)h(m)o(uestra)f(una)h (\\implemen)o(taci\023)-23 b(on")18 b(de)g(este)e(heur)-5 b(\023)-18 b(\020stico)18 b(de)g(inicializaci)q(\023)-23 b(on)19 b(en)-13 1890 y(lengua)s(je)c Fg(ansi)i(c)e FG(\(funci\023)-23 b(on)16 b Fm(lambda)p 642 1890 15 2 v 16 w(init)p FG(\).)-13 2038 y FB(5.)46 b(Exp)r(erimentos)-13 2141 y FG(Con)18 b(el)h(ob)s(jeto)e(de)h(comparar)f(diferen)o(tes)i(funciones)h(de)e(ev) m(aluaci\023)-23 b(on,)20 b(hemos)e(llev)m(ado)h(a)f(cab)q(o)g(exp)q (eri-)-13 2197 y(men)o(tos)d(de)h(ev)m(aluaci\023)-23 b(on)17 b(de)f(dos)g(deco)q(di\014cadores)h(ac)q(\023)-24 b(ustico-fon)o(\023)j(eticos)16 b(para)f(el)h(castellano.)g(Se)g(trata) e(de)-13 2254 y(dos)19 b(deco)q(di\014cadores)i(basados)e(en)g(meto)q (dolog)-5 b(\023)-18 b(\020as)20 b(diferen)o(tes:)f(uno)h(de)f(ellos)i (com)o(bina)e(el)h Fv(Per)n(c)n(eptr\023)-23 b(on)-13 2310 y(Multic)n(ap)n(a)20 b FG(\(PM\))f(con)h(los)h Fv(Mo)n(delos)f(de) h(Markov)g(Ocultos)f 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y(que)j(da)f(el)h(sistema;)f(y)g(c\023)-23 b(alculo)20 b(de)f(una)g(tasa)e(de)i(semejanza)f(\(o)g(de)h (disimilitud\))i(en)o(tre)d(dic)o(has)h(in)o(ter-)-13 1105 y(pretaciones)14 b(seg)q(\023)-24 b(un)15 b(la)f(edici\023)-23 b(on)16 b(elegida.)f(Hemos)e(hec)o(ho)i(una)f(revisi\023)-23 b(on)15 b(cr)-5 b(\023)-18 b(\020tica)15 b(de)f(las)g(funciones)h(de)g (tasa)-13 1161 y(habitualmen)o(te)h(utilizadas)g(y)e(hemos)h (descubierto)h(que,)e(o)h(no)f(se)h(m)o(uev)o(en)g(en)g(un)g(rango)f (acotado)f(\(p)q(ese)-13 1217 y(a)i(su)g(apariencia)h(de)g(p)q(orcen)o (ta)s(jes\),)e(o)h(\(m)o(uc)o(ho)f(m\023)-23 b(as)15 b(gra)o(v)o(e\))f(ignoran)h(los)g(errores)g(de)h(inserci\023)-23 b(on.)32 1276 y(La)13 b(soluci\023)-23 b(on)14 b(propuesta)f(en)g(este) g(traba)s(jo)e(no)i(presen)o(ta)f(estos)h(problemas)g(y)f(man)o(tiene)i (una)f(cierta)g(co-)-13 1332 y(herencia)h(en)o(tre)f(sus)g(dos)g (etapas,)f(con)h(una)g(complejidad)i(computacional)e(comparable)h(\(en) f(la)g(pr\023)-23 b(actica\))-13 1389 y(a)15 b(la)g(propia)h(de)f(las)h (funciones)g(de)g(ev)m(aluaci\023)-23 b(on)17 b(habitualmen)o(te)f (utilizadas.)-13 1544 y FB(Referencias)-13 1649 y FG([A)o(C93])81 b(P)l(.)23 b(Aibar)g(&)g(F.)f(Casacub)q(erta:)g(\\An)g(impro)o(v)o (emen)o(t)h(of)f(the)h(Tw)o(o-Lev)o(el)g(DP)f(Matc)o(hing)206 1706 y(algorithm)d(using)h Fz(k)q FG(-NN)f(tec)o(hniques)i(for)d (acoustic-phonetic)j(deco)q(ding",)e Fv(Pr)n(o)n(c)n(e)n(e)n(dings)f (of)206 1762 y(the)f(EUR)o(OSPEECH'93)p FG(,)c(pp.)i(1735{1738,)e (1993.)-13 1863 y([BBB)96 1847 y Fu(+)126 1863 y FG(89])21 b(L.)14 b(R.)g(Bahl,)g(R.)g(Bakis,)g(J.)g(Bellegarda,)h(P)l(.)e(F.)g (Bro)o(wn,)g(D.)h(Bursh)o(tein,)g(S.)g(K.)f(Das,)g(P)l(.)h(V.)f(de)206 1920 y(Souza,)i(P)l(.)g(S.)g(Gopalakrishnan,)g(F.)f(Jelinek,)j(D.)e (Kanevsky)l(,)g(R.)g(L.)g(Mercer,)f(A.)h(N\023)-23 b(adas,)15 b(D.)206 1976 y(Nahamo)q(o)f(&)h(M.A.)f(Pic)o(hen)o(y:)h(\\Large)f(v)o (o)q(cabulary)h(natural)f(language)h(con)o(tin)o(uous)g(sp)q(eec)o(h) 206 2033 y(recognition",)h Fv(Pr)n(o)n(c)n(e)n(e)n(dings)e(of)i(the)g (ICASSP'89)p FG(,)d(pp.)j(465{467,)d(1989.)-13 2134 y([Cast94])55 b(M.)15 b(J.)g(Castro.)e(Com)o(unicaci\023)-23 b(on)17 b(priv)m(ada.)-13 2235 y([CA)o(CV90])k(M.)16 b(J.)h(Castro,)e(P)l(.)i (Aibar,)g(F.)f(Casacub)q(erta)g(&)i(E.)e(Vidal:)i(\\Automatic)e (selection)j(of)d(sub-)206 2291 y(lexic)24 b(templates)f(b)o(y)f(using) h(dynamic)g(time)f(w)o(arping)h(tec)o(hniques",)f Fv(Pr)n(o)n(c)n(e)n (e)n(dings)f(of)i(the)206 2348 y(EUSIPCO'90)p FG(,)13 b(pp.)j(1351{1353,)c(1990.)-13 2449 y([Hun)o(t89])46 b(M.J.)11 b(Hun)o(t:)g(\\Figures)h(of)f(merit)h(for)f(assessing)h (connected-w)o(ord)g(recognisers",)f Fv(Pr)n(o)n(c)n(e)n(e)n(dings)206 2505 y(of)17 b(the)f(ESCA)f(Workshop)p FG(,)h(pp.)f(4.3.1{4.3.4,)d (1989.)-13 2606 y([Lee88])79 b(K.F.)19 b(Lee:)h(\\Large-v)o(o)q (cabulary)g(sp)q(eak)o(er-indep)q(enden)o(t)j(con)o(tin)o(uous)d(sp)q (eec)o(h)g(recognition:)206 2663 y(The)h(SPHINX)g(system",)e(T)l(esis)i (Do)q(ctoral,)e(Computer)h(Science)i(Departmen)o(t,)c(Carnegie)206 2719 y(Mellon)f(Univ)o(ersit)o(y)l(,)e(Abril)i(1988.)-13 2820 y([Meri88])55 b(F.)21 b(Merialdo:)h(\\Phonetic)g(recognition)g (using)g(hidden)h(Mark)o(o)o(v)d(mo)q(dels)i(and)g(maxim)o(um)206 2876 y(m)o(utual)16 b(information)f(training",)g Fv(Pr)n(o)n(c)n(e)n(e) n(dings)f(of)i(the)h(ICASSP'88)p FG(,)c(pp.)i(111{114,)e(1988.)1797 3074 y(17)p eop %%Page: 18 24 18 23 bop 600 -33 a Fv(El)15 b(pr)n(oblema)i(de)f(la)g(evaluaci\023)-23 b(on)17 b(de)f(un)g(sistema)g(de)g(r)n(e)n(c)n(ono)n(cimiento)p Fz(:)8 b(:)g(:)p 37 -16 1857 2 v 37 110 a FG([MV93])72 b(A.)12 b(Marzal)f(&)h(E.)g(Vidal:)g(\\Computation)g(of)f(normalized)i (edit)g(distance)f(and)g(applications",)257 167 y Fv(IEEE)18 b(T)m(r)n(ansactions)f(on)h(Pattern)h(A)o(nalysis)e(and)i(Machine)g (Intel)r(ligenc)n(e)p FG(,)c(v)o(ol.)i(15,)g(no.)h(9,)257 223 y(pp.)d(926{932,)e(1993.)37 316 y([P)o(all89])71 b(D.S.)15 b(P)o(allet:)i(\\Benc)o(hmark)f(tests)g(for)f(D)o(ARP)l(A)i (resource)f(managemen)o(t)g(database)f(p)q(erfor-)257 372 y(mance)g(ev)m(aluations",)h Fv(Pr)n(o)n(c)n(e)n(e)n(dings)e(of)i (the)h(ESCA)e(Workshop)p FG(,)h(pp.)f(4.1.1{4.1.4,)c(1989.)37 465 y([PFF90])57 b(D.S.)20 b(P)o(allett,)i(W.M.)d(Fisher)j(&)g(J.G.)e (Fiscus:)i(\\T)l(o)q(ols)f(for)g(the)g(analysis)h(of)f(b)q(enc)o(hmark) 257 521 y(sp)q(eec)o(h)16 b(recognition)g(tests",)e Fv(Pr)n(o)n(c)n(e)n (e)n(dings)g(of)i(the)h(ICASSP'90)p FG(,)c(pp.)i(97{100,)e(1990.)37 614 y([PS91])92 b(S.H.)17 b(P)o(ar\014tt)e(&)j(R.A.)f(Sharman:)f(\\A)h (bi-directional)j(mo)q(del)e(of)f(English)h(pron)o(unciation",)257 670 y Fv(Pr)n(o)n(c)n(e)n(e)n(dings)c(of)i(the)h(EUR)o(OSPEECH'91)p FG(,)c(pp.)i(801{804,)e(1991.)37 763 y([PGDF86])21 b(J.)13 b(Picone,)h(K.M.)e(Goudie-Marshall,)i(G.R.)f(Do)q(ddington)h(&)f(W.)g (Fisher:)g(\\Automatic)g(text)257 820 y(alignmen)o(t)i(for)e(sp)q(eec)o (h)i(system)e(ev)m(aluation",)i Fv(IEEE)f(T)m(r)n(ansactions)f(on)i(A)n (c)n(oustics,)f(Sp)n(e)n(e)n(ch,)257 876 y(and)i(Signal)f(Pr)n(o)n(c)n (essing)p FG(,)e(v)o(ol.)i(34,)f(no.)h(4,)f(pp.)h(780{784,)e(1986.)37 969 y([SK83])88 b(D.)16 b(Sank)o(o\013)f(&)i(J.B.)f(Krusk)m(al)h (\(eds.\):)e(\\)p Fv(Time)i(warps,)h(string)e(e)n(dits,)h(and)g(macr)n (omole)n(cules:)257 1025 y(The)f(the)n(ory)h(and)f(pr)n(actic)n(e)g(of) g(se)n(quenc)n(e)f(c)n(omp)n(arison)p FG(",)f(Addison-W)l(esley)l(,)j (1983.)37 1118 y([Snie92])66 b(M.)14 b(Sniedo)o(vic)o(h:)j(\\)p Fv(Dynamic)f(Pr)n(o)n(gr)n(amming)p FG(",)e(Marcel)h(Dekk)o(er,)g (1992.)37 1211 y([VMA94])38 b(E.)15 b(Vidal,)i(A.)e(Marzal)g(&)h(P)l(.) f(Aibar:)h(\\F)l(ast)e(computation)i(of)f(normalized)i(edit)f (distances",)257 1267 y Fv(p)n(endiente)f(de)i(public)n(aci\023)-23 b(on.)37 1360 y FG([WF74])71 b(R.A.)18 b(W)l(agner)g(&)h(M.J.)f(Fisc)o (her:)g(\\The)h(string-to-string)f(correction)h(problem",)f Fv(Journal)257 1416 y(of)e(the)h(A)o(CM)p FG(,)d(v)o(ol.)g(21,)h(no.)f (1,)h(pp.)g(168{173,)e(1974.)37 1509 y([WPN91])36 b(L.C.)17 b(W)l(o)q(o)q(d,)g(D.J.B.)g(P)o(earce)g(&)h(F.)f(No)o(v)o(ello:)g (\\Impro)o(v)o(ed)h(v)o(o)q(cabulary-indep)q(enden)o(t)i(sub-)257 1565 y(w)o(ord)15 b(HMM)f(mo)q(deling",)i Fv(Pr)n(o)n(c)n(e)n(e)n (dings)e(of)i(the)h(ICASSP'91)p FG(,)c(pp.)i(181{184,)e(1991.)37 1757 y FB(Ap)o(\023)-32 b(endices)37 1945 y(A.)47 b(Implem)o(en)o (taci\023)-33 b(on)37 2050 y Fq(A.1)54 b(T)-5 b(asas.h)37 2129 y Fa(/*)22 b(Gp:)f(devuelve)f(la)i(``distancia)d(de)i (edici\\'on'')f(correspondiente)f(al)i(criterio)59 2179 y(*)109 b(de)21 b(edici\\'on)f(de)i(conteo)e(ponderado)g(de)i(errores)e (de)h(edici\\'on.)59 2229 y(*)h(Entrada:)59 2279 y(*)44 b(p:)21 b(par\\'ametro)f(de)h(equivalencia)e(de)j(criterios)e(de)h (edici\\'on)f(con)h(errores)59 2329 y(*)109 b(ponderados)20 b(como)h(sigue:)f(sustituci\\'on)f(1,)j(inserci\\'on)d(p,)j(borrado)e (p,)59 2378 y(*)109 b(acierto)20 b(0.)59 2428 y(*)44 b(c,)21 b(s:)g(vectores)g(de)g(cadenas)f(de)i(caracteres.)59 2478 y(*)44 b(M:)21 b(n\\'umero)f(de)i(pares)e(\(c,s\))h(de)g(entrada)g (\(talla)f(de)i(los)f(vectores)f(c)i(y)f(s\).)59 2528 y(*)h(Salida:)59 2578 y(*)44 b(NS,)21 b(NI,)g(NB,)g(NA:)g(n\\'umero)f (de)i(sustituciones,)d(inserciones,)g(borrados)h(y)59 2627 y(*)109 b(aciertos,)20 b(respectivamente.)59 2677 y(*/)37 2727 y(extern)37 2777 y(double)h(Gp\(double)f(p,)h(char)g(**c,) g(char)g(**s,)g(int)g(M,)h(int)f(*NS,)g(int)g(*NI,)g(int)g(*NB,)g(int)g (*NA\);)37 2876 y(/*)h(Fpre:)f(devuelve)f(el)h(valor)g(de)g(la)h (funci\\'on)e(de)h(evaluaci\\'on)e(``porcentaje)h(real)37 3074 y FG(18)p eop %%Page: 19 25 19 24 bop -13 -33 a Fv(El)16 b(pr)n(oblema)g(de)g(la)g(evaluaci\023)-23 b(on)17 b(de)f(un)g(sistema)g(de)g(r)n(e)n(c)n(ono)n(cimiento)p Fz(:)8 b(:)g(:)p -13 -16 1857 2 v 9 110 a Fa(*)108 b(de)22 b(errores''.)9 160 y(*)f(Entrada:)9 210 y(*)43 b(c,)21 b(s:)h(vectores)e(de)h(cadenas)g(de)g(caracteres.)9 260 y(*)43 b(M:)21 b(n\\'umero)g(de)g(pares)g(\(c,s\))f(de)i(entrada)e (\(talla)h(de)g(los)g(vectores)f(c)i(y)g(s\).)9 309 y(*)f(Salida:)9 359 y(*)43 b(NS,)21 b(NI,)g(NB,)h(NA:)f(n\\'umero)f(de)h (sustituciones,)e(inserciones,)g(borrados)i(y)9 409 y(*)108 b(aciertos,)20 b(respectivamente.)9 459 y(*/)-13 509 y(extern)-13 559 y(double)g(Fpre\(char)g(**c,)h(char)g(**s,)g(int)g(M,) h(int)f(*NS,)g(int)g(*NI,)g(int)g(*NB,)g(int)g(*NA\);)-13 699 y Fq(A.2)54 b(T)-5 b(asas.c)-13 784 y Fa(#include)20 b()-13 884 y(#define)g(OPS)43 b(0)-13 934 y(#define)20 b(OPI)43 b(1)-13 984 y(#define)20 b(OPB)43 b(2)-13 1033 y(#define)20 b(OPA)43 b(3)-13 1133 y(/*)g(Criterio)20 b(de)i(edici\\'on)d(por)j(conteo)e(ponderado)g(de)h(operaciones)f(de)h (edici\\'on.)f(*/)-13 1233 y(double)g(Gp\(double)g(p,)i(char)f(**c,)g (char)g(**s,)g(int)g(M,)g(int)g(*NS,)g(int)g(*NI,)g(int)h(*NB,)f(int)g (*NA\))-13 1282 y({)g(double)g(*g[2],)g(G,)g(cs,)g(ci,)g(cb,)g(va;)30 1332 y(int)87 b(*na[2],)20 b(*ns[2],)h(*ni[2],)f(*nb[2],)g(i,)i(j,)f (k,)g(op,)h(ImaxI=0,)e(*IcI,)h(int)g(*IsI,)f(I,)i(I_1;)30 1432 y(IcI=calloc\(M,)e(sizeof\(int\)\);)f(IsI=calloc\(M,)g (sizeof\(int\)\);)30 1482 y(for\(k=0;)i(k data would be a vector of lines where each", "line contains reference_sequence..separator_char..test_sequence.\n", "- 'pairs_lines' => is a vector of pairs { ref_seq, test_seq }\n", "- 'pairs_lwords' => is a vector of pairs of word lists:\n", "{ { 'he', 'is' }, { 'she', 'is' } }\n", "- 'pairs_int => is a vector of pairs of integer lists.", "NOTE that 0 integer is reserved for internal purposes.\n", }, ["words_width"] = { "When datatype is 'lines' or 'pairs_lines' this parameter", "indicates that lines would be converted in words", "taking groups of words_width characters", "(non extended ascii)." }, ["words_sep"] = { "When datatype is 'lines' or 'pairs_lines', this parameter", "indicates that lines has words separated by the given", "character. NOTE that this parameter is a Lua string used", "as pattern for string.find function, so the % character", "would be needed in some cases (see Lua reference).", }, ["rate"] = { "The type of error rate which you want to compute. It", "could be:\n", "- 'pra' => correct / total_words\n", "- 'pre' => errors / total_words\n", "- 'pa' => ACCURACY\n", "- 'ie' => WER\n", "- 'wer' => WER\n", "- 'psb' => (substitutions + deletes) / total_words\n", "- 'iep' => weighted WER\n", "- 'iap' => weighted ACCURACY\n", }, ["p"] = { "A number which indicates the insertion and delete cost", "(substitution is 1, and success is 0) [optional]. By", "default is 1", }, ["confusion_matrix"] = { "A boolean value [optional], by default", "is false. It forces to compute a confusion matrix" }, }, outputs = { ["ac"] = "Number of success", ["borr"] = "Number of deletions", ["sust"] = "Number of substitution", ["ins"] = "Number of insertions", ["rate"] = "Value of the indicated error rate", ["confusion_matrix"]="The confusion matrix, only when needed", }, }) rates.types = {'pra','pre','pa','ip','ie','psb','iep','iap'} function rates.lines2pairs_lines(lines,setsep) -- transforma una lista de cadenas en una lista de pares de cadenas local pair_lines = {} setsep = setsep or '%*' local pattern = "^(.*)["..setsep.."](.*)$" for i,line in ipairs(lines) do _,_, correct,test = string.find(line, pattern) table.insert(pair_lines,{correct,test}) end return pair_lines end function rates.pairs_lines2pairs_lwords(pairs_lines,setsep) -- transforma una lista de pares de cadenas en una lista de pares de -- secuencias de palabras local pairs_lwords = {} for i,pair_lines in ipairs(pairs_lines) do table.insert(pairs_lwords,{ string.tokenize(pair_lines[1],setsep), string.tokenize(pair_lines[2],setsep) }) end return pairs_lwords end function rates.pairs_lines2string_width(pairs_lines,width) -- transforma una lista de pares de cadenas en una lista de pares de -- secuencias de palabras local pairs_lwords = {} for i,pair_lines in ipairs(pairs_lines) do table.insert(pairs_lwords,{ string.tokenize_width(pair_lines[1],width), string.tokenize_width(pair_lines[2],width), }) end return pairs_lwords end function rates.lwords2int(lwords,dictionary) local aux = {} for _,word in ipairs(lwords) do local iword = dictionary.dir[word] if (iword == nil) then dictionary.num = dictionary.num+1 dictionary.dir[word] = dictionary.num iword = dictionary.num dictionary.inv[dictionary.num] = word end table.insert(aux,iword) end return aux end function rates.pairs_lwords2pairs_int(pairs_lwords) local dictionary = {dir={},inv={},num=0} dictionary.inv[0] = "" local pairs_int = {} for i,pair in ipairs(pairs_lwords) do table.insert(pairs_int,{ rates.lwords2int(pair[1],dictionary), rates.lwords2int(pair[2],dictionary) }) end return pairs_int,dictionary end function rates.rates(tbl) local datatype = tbl.datatype or 'lines' local data = tbl.data local dictionary if datatype == "lines" then data = rates.lines2pairs_lines(data,tbl.line_sep) datatype = "pairs_lines" end if datatype == "pairs_lines" then if tbl.words_width then data = rates.pairs_lines2string_width(data,tbl.words_width) else data = rates.pairs_lines2pairs_lwords(data,tbl.words_sep) end datatype = "pairs_lwords" end if datatype == "pairs_lwords" then data,dictionary = rates.pairs_lwords2pairs_int(data) datatype = "pairs_int" end if datatype ~= "pairs_int" then fprintf(io.stderr,"rates Error: %s is not a valid datatype", datatype) os.exit(256) end local the_rate = tbl.rate if the_rate == "wer" then the_rate = "ie" end if the_rate == "raw" then return rates.raw{ int_data = data, p = tbl.p, } else local confusion_matrix_dictionary = nil if dictionary then confusion_matrix_dictionary = dictionary.inv end return rates.ints{ int_data = data, rate = the_rate, p = tbl.p, confusion_matrix = tbl.confusion_matrix, confusion_matrix_dictionary = confusion_matrix_dictionary } end end -- hacer que la funcion rates.rates se llame rates local m = getmetatable(rates) function m.__call(x,tbl) if (tbl == nil) then april_help(rates) else return rates.rates(tbl) end end april-ann-0.4.1/packages/metrics/rates/package.lua000066400000000000000000000021111263004425400220300ustar00rootroot00000000000000 package{ name = "metrics.rates", version = "1.0", depends = { "util", }, keywords = { "rates" }, description = "alignment", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_rates.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_rates.lua.cc", dest_dir = "build" } }, target{ name = "document", document_src{ file= {"c_src/*.h", "c_src/*.c", "c_src/*.cc"}, }, document_bind{ file= {"binding/*.lua.cc"} }, }, } april-ann-0.4.1/packages/metrics/rates/test/000077500000000000000000000000001263004425400207165ustar00rootroot00000000000000april-ann-0.4.1/packages/metrics/rates/test/tasas_emulator.lua000066400000000000000000000055261263004425400244540ustar00rootroot00000000000000--[[ TODO: usar cmdOpt y tasas para emular el tasas original: Uso: ./tasas fich [-f "c"] [-s #|-s "c"] [-p #] [TASA] [-c mat|-C mat] [-w dicc] [-v] donde: fich es el fichero de datos -f "c" : hace que c separe frases en una linea -s # : hace que cada # caracteres se consideren un simbolo -s "cad" : caracts. en "cad" separan simbolos -p # : fija el parametro p a # TASA : proporciona una tasa concreta [-pra|-pre|-pa|-ip|-ie|-psb|-iep|-iap] -C mat : guarda en fichero mat la matriz de confusion -c mat : guarda en mat elementos no nulos de matriz de confusion -w dicc : toma del fichero dicc el orden de los simbolos -v : muestra el numero de ops. de cada tipo y valor de p usado Si el nombre de un fichero es "-" se toma la entrada/salida estandar POR DEFECTO: ./tasas -f "*" -s 1 -pra --]] cmdOptTest = cmdOpt{ program_name = "tasas", argument_description = "emulador del programa tasas", main_description = "", author = "", copyright = "", see_also = "", -- options can be added in the constructor: { index_name="words_sep", description = "hace que c separe frases en una linea", long = "words_sep", short = "f", argument = "yes", argument_name = '"c"', }, { index_name="words_width", description = "hace que cada # caracteres se consideren un simbolo", long = "words_width", short = "s", argument = "yes", argument_name = "#", }, { index_name="p", description = "fija el parametro p a #", short = "p", argument = "yes", }, { index_name="pra", description = "list directory entries instead of contents, and do not dereference symbolic links", short = "d", long = "directory", argument = "no", }, } -- options can also be declared outside constructor: cmdOptTest:add_option{ description = "shows this help message", short = "h", long = "help", argument = "no", action = function (argument) print(cmdOptTest:generate_help()) os.exit(1) end } cmdOptTest:add_option{ index_name = "ignore-backups", description = "do not list implied entries ending with ~", short = "B", long = "ignore-backups", argument = "no", action = function(value) print("this is a test "..tostring(value)) end, } cmdOptTest:add_option{ index_name = "ignore", description = "do not list implied entries matching shell PATTERN", short = "I", long = "ignore", argument = "yes", argument_name = "PATTERN", } ---------------------------------------------------------------------- ---------------------------- MAIN PROGRAM ---------------------------- ---------------------------------------------------------------------- result = cmdOptTest:parse_args() if type(result) == 'string' then error(result) end print("\nThis is a test, let's see the contents of result table:") for i,j in pairs(result) do print(i,j) end april-ann-0.4.1/packages/metrics/rates/test/test_rates.lua000066400000000000000000000036031263004425400236000ustar00rootroot00000000000000local rates = metrics.rates local lineas = [[ a * b b b b a a a * b a b c * b b * a b c a b c * a a b b esto es una prueba*esto es prueba de un fichero de palabras*de un fichero de muchas palabras para probar tasas*para probar el programa tasas ]] local lineas = string.tokenize(lineas,"\n") for _,line in ipairs(lineas) do print("->"..line) end local resul = rates{ datatype = "lines", -- no hace falta, es valor por defecto line_sep = "%*", -- no hace falta, es valor por defecto words_width = 1, -- words_sep = " ", -- no hace falta, por defecto es ' \t' data = lineas, -- los datos rate = "pra", -- campo obligatorio, no hay valor por defecto confusion_matrix=true, -- por defecto es false } for i,j in pairs(resul) do print(i,j) end print"\n------ matriz de confusion -------" for i,j in pairs(resul.confusion_matrix) do for k,l in pairs(j) do printf("%-8s x %-8s -> %2d ('%s' '%s')\n",i,k,l,i,k) end end print"----------------------------------\n" print"SIN MATRIZ DE CONFUSION" local resul = rates{ rate = "pra", data = lineas, } for i,j in pairs(resul) do print(i,j) end ------------------------------------------------ print"CON ENTEROS" local enteros = { {{1,1,2,3},{1,3,2,2,4}}, {{1,1,2,3},{1,1,2,3,4}} } local resul = rates{ rate = "pra", data = enteros, datatype = "pairs_int", confusion_matrix=true, } for i,j in pairs(resul) do print(i,j) end print"matriz de confusion:" for i,j in pairs(resul.confusion_matrix) do for k,l in pairs(j) do printf("%d x %d -> %d\n",i,k,l) end end ------------------------------------------------ print"\n-----------------------------------------" print"MODO RAW" local enteros = { {{1,1,2,3},{1,3,2,2,4}}, {{1,1,2,3},{1,1,2,3,4}} } local resul = rates{ rate = "raw", data = enteros, datatype = "pairs_int", } for i,j in ipairs(resul) do for k,l in pairs(j) do print(i,k,l) end end april-ann-0.4.1/packages/metrics/roc/000077500000000000000000000000001263004425400174045ustar00rootroot00000000000000april-ann-0.4.1/packages/metrics/roc/lua_src/000077500000000000000000000000001263004425400210345ustar00rootroot00000000000000april-ann-0.4.1/packages/metrics/roc/lua_src/roc.lua000066400000000000000000000214631263004425400223300ustar00rootroot00000000000000metrics = metrics or {} -- local function check_matrix(m) assert(class.is_a(m,matrix), "Needs a matrix as argument") local dim = m:dim() assert( #dim == 1 or (#dim == 2 and (dim[1] == 1 or dim[2] == 1)), "Needs a row or column vector" ) return #dim == 1 and m:contiguous():rewrap(m:size(),1) or m end -- local roc,roc_methods = class("metrics.roc") metrics.roc = roc -- global environment metrics.roc.test = nil -- implementation in next do...end block do local function compute_delong_V_vectors(normal_idx, abnormal_idx, data) local Na = abnormal_idx:size() local Nn = normal_idx:size() local V10 = matrix(Na) local V01 = matrix(Nn) local normal_data = data:index(1, normal_idx) local abnormal_data = data:index(1, abnormal_idx) for i=1,Na do local x = abnormal_data[i] local lt = normal_data:lt(x):count_ones() local gt = normal_data:gt(x):count_ones() local eq = Nn - lt - gt V10[i] = lt + 0.5 * eq end V10:scal(1.0/Nn) for i=1,Nn do local y = normal_data[i] local lt = abnormal_data:lt(y):count_ones() local gt = abnormal_data:gt(y):count_ones() local eq = Nn - lt - gt V01[i] = gt + 0.5 * eq end V01:scal(1.0/Na) -- return V10,V01 end -- Comparing the areas under two or more correlated receiver -- operating characteristic curves: a nonparametric approach. -- DeLong ER1, DeLong DM, Clarke-Pearson DL. -- http://www.ncbi.nlm.nih.gov/pubmed/3203132 local function compute_delong_covariance(params, r1, r2, t_data, p1_data, p2_data) local AUC2 = r1:compute_area() local AUC1 = r2:compute_area() local normal_idx = t_data:eq(0.0):to_index() local abnormal_idx = t_data:eq(1.0):to_index() local V10,V01 = {},{} V10[1],V01[1] = compute_delong_V_vectors(normal_idx, abnormal_idx, p1_data) V10[2],V01[2] = compute_delong_V_vectors(normal_idx, abnormal_idx, p2_data) V10[1]:scalar_add(-AUC1) V01[1]:scalar_add(-AUC1) V10[2]:scalar_add(-AUC2) V01[2]:scalar_add(-AUC2) local Na = abnormal_idx:size() local Nn = normal_idx:size() local S10 = matrix(2,2) local S01 = matrix(2,2) for i=1,2 do local row10 = S10[i] local row01 = S01[i] for j=1,2 do row10[j] = V10[i]:dot(V10[j]) / (Na-1) row01[j] = V01[i]:dot(V01[j]) / (Nn-1) end end local S = S10/Na + S01/Nn return S end local function not_stratified_bootstrap(params, t_data, p1_data, p2_data) return stats.boot{ seed = params.seed, random = params.random, size = t_data:size(), R = params.R or 1000, k = 1, ncores = params.ncores, verbose = params.verbose, statistic = function(idx) local p1_data = p1_data:index(1, idx) local p2_data = p2_data:index(1, idx) local t_data = t_data:index(1,idx) local r1 = metrics.roc(p1_data, t_data) local r2 = metrics.roc(p2_data, t_data) return r1:compute_area() - r2:compute_area() end, } end local function stratified_bootstrap(params, t_data, p1_data, p2_data) local t0_idx,t1_idx do local gt_0 = t_data:gt(0) t1_idx = gt_0:to_index() t0_idx = gt_0:complement():to_index() end return stats.boot{ seed = params.seed, random = params.random, size = { t0_idx:size(), t1_idx:size() }, R = params.R or 1000, k = 1, ncores = params.ncores, verbose = params.verbose, statistic = function(idx0,idx1) local idx = matrix.join(1, { t0_idx:index(1,idx0), t1_idx:index(1,idx1) }) local p1_data = p1_data:index(1, idx) local p2_data = p2_data:index(1, idx) local t_data = t_data:index(1,idx) local r1 = metrics.roc(p1_data, t_data) local r2 = metrics.roc(p2_data, t_data) return r1:compute_area() - r2:compute_area() end, } end local hyp_test = stats.hypothesis_test -- two-sided test, checks if both curves have a different AUC -- http://cran.r-project.org/web/packages/pROC/pROC.pdf metrics.roc.test = function(r1, r2, params) assert(r1.data:dim(1) == r2.data:dim(1), "Incompatible ROC curves") local params = params or {} local method = params.method or "bootstrap" params.method = nil local stratified = (params.stratified==nil and true) or params.stratified params.stratified = nil local r1_data = r1.data local r2_data = r2.data local t_data = r1_data:select(2,2):contiguous() local p1_data = r1_data:select(2,1):contiguous() local p2_data = r2_data:select(2,1):contiguous() assert(t_data == r2_data:select(2,2), "Different response in both curves") if method == "bootstrap" then local result if not stratified then result = not_stratified_bootstrap(params, t_data, p1_data, p2_data) else result = stratified_bootstrap(params, t_data, p1_data, p2_data) end -- normal distribution test local sd = stats.std(result) local mean = r1:compute_area() - r2:compute_area() local D = mean/sd return hyp_test(D, stats.dist.normal(), stats.dist.normal(mean,sd*sd)) elseif method == "delong" then local S = compute_delong_covariance(params, r1, r2, t_data, p1_data, p2_data) local contrast = matrix(2,2,{1,-1,-1,1}) local var = S:cmul(contrast):sum() local mean = r1:compute_area() - r2:compute_area() local z = mean/math.sqrt(var) return hyp_test(z, stats.dist.normal(), stats.dist.normal(mean,var)) else error("Unknown method " .. method) end end end april_set_doc(roc, { class="class", summary="ROC curve class, for one-class problems", }) roc.constructor = april_doc{ class = "method", summary = "Constructor without arguments", } .. april_doc{ class = "method", summary = "Constructor with matrix arguments", params = { { "A matrix with classifier output probabilities in natural scale", }, { "A matrix with target class: 0 or 1", }, }, } .. function(self,outputs,targets) self.P = 0 self.N = 0 if outputs or targets then self:add(outputs,targets) end end roc_methods.add = april_doc{ class = "method", summary = "Adds an output and target class for ROC computation", params = { { "A matrix with classifier output probabilities in natural scale", }, { "A matrix with target class: 0 or 1", }, }, } .. function(self,outputs,targets) local outputs = check_matrix(outputs) local targets = check_matrix(targets) local data,P,N = self.data,0,0 if not data then self.data = matrix.join(2, outputs, targets) else self.data = matrix.join(1, data, matrix.join(2, outputs, targets)) end local ones = targets:gt(0.5):count_ones() self.P = self.P + ones self.N = self.N + targets:size() - ones end roc_methods.compute_curve = april_doc{ class = "method", summary = "Computes the ROC curve with all added data", outputs = { {"A matrix with N rows and 4 columns, the first column is FPR, second", "is TPR, the third is the threshold, and the last is the true value"}, }, } .. function(self) local data = self.data local P = self.P local N = self.N local data = data:index(1,data:select(2,1):order()) local result = {} local TP,FP = 0,0 local prev_th,j = -math.huge,0 for i,row in matrix.ext.iterate(data, 1, -1) do if row[1] ~= prev_th then local TPR,FPR = TP/P,FP/N table.insert(result, FPR) -- 1 table.insert(result, TPR) -- 2 table.insert(result, row[1]) -- 3 table.insert(result, row[2]) -- 4 j=j+1 prev_th = row[1] end if row[2] > 0.5 then TP = TP + 1 else FP = FP + 1 end end table.insert(result, 1) table.insert(result, 1) table.insert(result, -1) table.insert(result, -1) return matrix(j+1,4,result) end roc_methods.compute_area = april_doc{ class="method", summary="Computes the Area Under the Curve", outputs={ "The area" }, } .. function(self) local cv = self:compute_curve() local area = 0 for i = 2,cv:dim(1) do area = area + (cv:get(i,1) - cv:get(i-1,1)) * (cv:get(i,2) + cv:get(i-1,2))*0.5 end return area end roc_methods.reset = april_doc{ class="method", summary="Resets all the intermediate data", } .. function(self) self.data = nil self.P = 0 self.N = 0 collectgarbage("collect") end return roc april-ann-0.4.1/packages/metrics/roc/package.lua000066400000000000000000000022611263004425400215030ustar00rootroot00000000000000 package{ name = "metrics.roc", version = "1.0", depends = { "util", "stats", }, keywords = { "roc" }, description = "alignment", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test_roc.lua", }, }, }, target{ name = "provide", depends = "init", -- copy{ file= "c_src/*.h", dest_dir = "include" }, -- provide_bind{ file = "binding/bind_rates.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, -- object{ -- file = "c_src/*.cc", -- include_dirs = "${include_dirs}", -- dest_dir = "build", -- }, luac{ orig_dir = "lua_src", dest_dir = "build", }, -- build_bind{ file = "binding/bind_rates.lua.cc", dest_dir = "build" } }, target{ name = "document", document_src{ file= { }, }, document_bind{ file= {"binding/*.lua.cc"} }, }, } april-ann-0.4.1/packages/metrics/roc/test/000077500000000000000000000000001263004425400203635ustar00rootroot00000000000000april-ann-0.4.1/packages/metrics/roc/test/test_roc.lua000066400000000000000000000036571263004425400227230ustar00rootroot00000000000000local T = utest.test local check = utest.check -- T("ROCTest", function() local roc_instance = metrics.roc() local output = matrix(100):uniformf(0,1,random(1234)) local target = matrix(100):uniform(0,1,random(4567)) roc_instance:add(output('1:50'), target('1:50')) roc_instance:add(output('51:100'), target('51:100')) check.number_eq( roc_instance:compute_area(), 0.5) check.number_eq( metrics.roc( matrix{0.2,0.3,0.4,0.5}, matrix{0,1,0,1} ):compute_area(), 0.75 ) check.eq( metrics.roc( matrix{0.2,0.3,0.4,0.5}, matrix{1,0,0,0} ):compute_area(), 0.0 ) check.number_eq( metrics.roc( matrix{0.2,0.3,0.4,0.5}, matrix{0,0,1,0} ):compute_area(), 0.66 ) check.number_eq( metrics.roc( matrix{0.2,0.3,0.4,0.5}, matrix{0,0,0,1} ):compute_area(), 1.0 ) -- local t = matrix{0,0,0,1,1,1} local d1 = matrix{0.2,0.3,0.4,0.5,0.2,0.9} local d2 = matrix{0.2,0.4,0.3,0.2,0.5,0.4} local roc1 = metrics.roc( d1, t ) local roc2 = metrics.roc( d2, t ) check.number_eq( roc1:compute_area(), 0.7222222354677) check.number_eq( roc2:compute_area(), 0.66666667660077) local h1 = metrics.roc.test(roc1,roc2,{method="bootstrap",seed=1234,verbose=true}) local h2 = metrics.roc.test(roc1,roc2,{method="delong"}) check.number_eq(h1:pvalue(), 0.89040226847281) check.number_eq(h2:pvalue(), 0.91152822827165) -- local perm_result = stats.perm{ samples = { d1, d2 }, R = 1000, seed = 11234, verbose = true, k=1, statistic = function(d1,d2) return metrics.roc(d1,t):compute_area() - metrics.roc(d2,t):compute_area() end, } local AUC_diff = roc1:compute_area() - roc2:compute_area() check.number_eq(stats.perm.pvalue(perm_result, AUC_diff), 0.86*0.5) end) april-ann-0.4.1/packages/misc/000077500000000000000000000000001263004425400161065ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/gzio/000077500000000000000000000000001263004425400170565ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/gzio/binding/000077500000000000000000000000001263004425400204705ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/gzio/binding/bind_gzio.lua.cc000066400000000000000000000025431263004425400235270ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "bind_april_io.h" #include "stream.h" using namespace AprilIO; //BIND_END //BIND_HEADER_H #include "gzfile_stream.h" using namespace GZIO; //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME StreamInterface aprilio.stream //BIND_LUACLASSNAME GZFileStream gzio.stream //BIND_CPP_CLASS GZFileStream //BIND_SUBCLASS_OF GZFileStream StreamInterface //BIND_CONSTRUCTOR GZFileStream { LUABIND_INCREASE_NUM_RETURNS(callFileStreamConstructor(L)); } //BIND_END april-ann-0.4.1/packages/misc/gzio/c_src/000077500000000000000000000000001263004425400201475ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/gzio/c_src/gzfile_stream.cc000066400000000000000000000047621263004425400233220ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include "error_print.h" #include "gzfile_stream.h" #include "maxmin.h" using AprilIO::StreamInterface; namespace GZIO { GZFileStream::GZFileStream(const char *path, const char *mode) : BufferedInputStream(), f(0) { f = gzopen(path, mode); write_flag = (mode[0] == 'w' || mode[1] == '+'); } /* GZFileStream::GZFileStream(FILE *file) : BufferedStream() { char mode[3]; f = gzdopen(dup(fileno(file)), mode); } GZFileStream::GZFileStream(int fd) : BufferedStream() { char mode[3]; f = gzdopen(dup(fd), mode); } */ GZFileStream::~GZFileStream() { close(); } bool GZFileStream::isOpened() const { return f != NULL; } void GZFileStream::close() { gzclose(f); f = NULL; } void GZFileStream::flush() { gzflush(f, Z_SYNC_FLUSH); } int GZFileStream::setvbuf(int mode, size_t size) { // TODO: UNUSED_VARIABLE(mode); UNUSED_VARIABLE(size); return 0; } bool GZFileStream::hasError() const { // TODO: return false; } const char *GZFileStream::getErrorMsg() const { // TODO: return StreamInterface::NO_ERROR_STRING; } bool GZFileStream::privateEof() const { return gzeof(f); } size_t GZFileStream::privateRead(char *buf, size_t max_size) { // TODO: check errors int nbytes = gzread(f, buf, max_size); return static_cast(nbytes); } size_t GZFileStream::privateWrite(const char *buf, size_t size) { // TODO: check error conditions gzwrite(f, buf, size); return size; } off_t GZFileStream::privateSeek(int whence, long offset) { return gzseek(f, offset, whence); } } // namespace gzio april-ann-0.4.1/packages/misc/gzio/c_src/gzfile_stream.h000066400000000000000000000034651263004425400231630ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef GZFILE_STREAM_H #define GZFILE_STREAM_H #include #include #include "buffered_stream.h" /// Input/output facilities for GZip files. namespace GZIO { class GZFileStream : public AprilIO::BufferedInputStream { public: GZFileStream(const char *path, const char *mode); /* GZFileStream(FILE *file); GZFileStream(int fd); */ virtual ~GZFileStream(); // int fileno() const { return fd; } virtual bool isOpened() const ; virtual void close(); virtual void flush(); virtual int setvbuf(int mode, size_t size); virtual bool hasError() const; virtual const char *getErrorMsg() const; protected: virtual bool privateEof() const; virtual size_t privateWrite(const char *buf, size_t size); virtual size_t privateRead(char *buf, size_t max_size); virtual off_t privateSeek(int whence, long offset); private: gzFile f; bool write_flag; }; } // namespace GZIO #endif // GZFILE_STREAM_H april-ann-0.4.1/packages/misc/gzio/lua_src/000077500000000000000000000000001263004425400205065ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/gzio/lua_src/gzio.lua000066400000000000000000000004751263004425400221670ustar00rootroot00000000000000gzio = gzio or {} gzio.open = function(...) return gzio.stream(...) end gzio.lines = function(name, ...) local f = april_assert( gzio.open(name), "cannot open file '%s'", name ) return f:lines(...) end aprilio.register_open_by_extension("gz", gzio.open) aprilio.register_open_by_extension("tgz", gzio.open) april-ann-0.4.1/packages/misc/gzio/package.lua000066400000000000000000000022351263004425400211560ustar00rootroot00000000000000 package{ name = "gzio", version = "1.0", depends = { "tar", "aprilio" }, link_libraries = { "z" }, keywords = { "gzio" }, description = "read and write gz files", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test.lua", }, }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_gzio.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_gzio.lua.cc", dest_dir = "build", } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/misc/gzio/test/000077500000000000000000000000001263004425400200355ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/gzio/test/a.tar.gz000066400000000000000000000003211263004425400214000ustar00rootroot00000000000000KԿ0}ߗ &c|7zg&_Y ?~B,]S{y(;6.cppM&X̪m|*+(april-ann-0.4.1/packages/misc/gzio/test/test.lua000066400000000000000000000024421263004425400215210ustar00rootroot00000000000000local check = utest.check local T = utest.test T("GZIPTest", function() -- gzio is used exactly the same way as standard module io local f=gzio.open("test.gz", "w") f:write("Hello, World.\n") f:close() local f=gzio.open("test.gz") check.eq(f:read("*l"), "Hello, World.") f:close() for line in gzio.lines("test.gz") do check.eq(line, "Hello, World.") end os.remove("test.gz") end) T("TARGZTest", function() -- the tar module reads tar files, can be used with gzio in order to read tgz local f = gzio.open(string.get_path(arg[0]).."a.tar.gz") local t = tar.open(f) local data = { ["dos.txt"] = { "Hola, soy dos.txt.", "Tengo mas lineas que uno.txt.", "Pero no muchas mas.", "Adios.", "", }, ["uno.txt"] = { "Hola, soy uno.txt.", "", }, } check.eq(t:number_of_files(), 2) for i in t:files() do check.TRUE(data[i], string.format("File %s is not expected",i)) local f2=t:open(i) local all = f2:read("*a") check.eq(all, table.concat(data[i],"\n"), string.format("Problem with file %s, expected\n%s\nFound\n%s\n", i, table.concat(data[i],"\n"), all)) f2:close() end end) april-ann-0.4.1/packages/misc/matlab/000077500000000000000000000000001263004425400173465ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/matlab/binding/000077500000000000000000000000001263004425400207605ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/matlab/binding/bind_matlab.lua.cc000066400000000000000000000243431263004425400243110ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013 Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "bind_matrix.h" #include "bind_matrix_complex_float.h" #include "bind_matrix_char.h" #include "bind_matrix_int32.h" #include "bind_matrix_double.h" namespace Matlab { int elements_iterator_function(lua_State *L) { MatFileReader *obj = lua_toMatFileReader(L,1); MatTaggedDataElement *element = obj->getNextDataElement(); if (element == 0) { lua_pushnil(L); return 1; } lua_pushMatTaggedDataElement(L, element); return 1; } } // namespace Matlab //BIND_END //BIND_HEADER_H #include "matlab.h" using namespace Matlab; typedef MatFileReader::DataElementInterface MatDataElementInterface; typedef MatFileReader::TaggedDataElement MatTaggedDataElement; typedef MatFileReader::CellArrayDataElement MatCellArrayDataElement; typedef MatFileReader::StructureDataElement MatStructureDataElement; //BIND_END //BIND_LUACLASSNAME MatFileReader matlab.reader //BIND_CPP_CLASS MatFileReader //BIND_LUACLASSNAME MatDataElementInterface matlab.__element_interface__ //BIND_CPP_CLASS MatDataElementInterface //BIND_LUACLASSNAME MatTaggedDataElement matlab.tagged_element //BIND_CPP_CLASS MatTaggedDataElement //BIND_SUBCLASS_OF MatTaggedDataElement MatDataElementInterface //BIND_LUACLASSNAME MatCellArrayDataElement matlab.cell_array //BIND_CPP_CLASS MatCellArrayDataElement //BIND_SUBCLASS_OF MatCellArrayDataElement MatDataElementInterface //BIND_ENUM_CONSTANT matlab.types.matrix MatFileReader::MATRIX //BIND_ENUM_CONSTANT matlab.types.int8 MatFileReader::INT8 //BIND_ENUM_CONSTANT matlab.types.int16 MatFileReader::INT16 //BIND_ENUM_CONSTANT matlab.types.int32 MatFileReader::INT32 //BIND_ENUM_CONSTANT matlab.types.int64 MatFileReader::INT64 //BIND_ENUM_CONSTANT matlab.types.uint8 MatFileReader::UINT8 //BIND_ENUM_CONSTANT matlab.types.uint16 MatFileReader::UINT16 //BIND_ENUM_CONSTANT matlab.types.uint32 MatFileReader::UINT32 //BIND_ENUM_CONSTANT matlab.types.uint64 MatFileReader::UINT64 //BIND_ENUM_CONSTANT matlab.types.single MatFileReader::SINGLE //BIND_ENUM_CONSTANT matlab.types.double MatFileReader::DOUBLE //BIND_ENUM_CONSTANT matlab.types.utf8 MatFileReader::UTF8 //BIND_ENUM_CONSTANT matlab.types.utf16 MatFileReader::UTF16 //BIND_ENUM_CONSTANT matlab.types.utf32 MatFileReader::UTF32 //BIND_ENUM_CONSTANT matlab.classes.cell_array MatFileReader::CL_CELL_ARRAY //BIND_ENUM_CONSTANT matlab.classes.structure MatFileReader::CL_STRUCTURE //BIND_ENUM_CONSTANT matlab.classes.object MatFileReader::CL_OBJECT //BIND_ENUM_CONSTANT matlab.classes.char MatFileReader::CL_CHAR //BIND_ENUM_CONSTANT matlab.classes.sparse MatFileReader::CL_SPARSE //BIND_ENUM_CONSTANT matlab.classes.double MatFileReader::CL_DOUBLE //BIND_ENUM_CONSTANT matlab.classes.single MatFileReader::CL_SINGLE //BIND_ENUM_CONSTANT matlab.classes.int8 MatFileReader::CL_INT8 //BIND_ENUM_CONSTANT matlab.classes.uint8 MatFileReader::CL_UINT8 //BIND_ENUM_CONSTANT matlab.classes.int16 MatFileReader::CL_INT16 //BIND_ENUM_CONSTANT matlab.classes.uint16 MatFileReader::CL_UINT16 //BIND_ENUM_CONSTANT matlab.classes.int32 MatFileReader::CL_INT32 //BIND_ENUM_CONSTANT matlab.classes.uint32 MatFileReader::CL_UINT32 //BIND_ENUM_CONSTANT matlab.classes.int64 MatFileReader::CL_INT64 //BIND_ENUM_CONSTANT matlab.classes.uint64 MatFileReader::CL_UINT64 ///////////////////////////////////////////////////////////////////////////// //BIND_CONSTRUCTOR MatDataElementInterface { LUABIND_ERROR("Abstract class"); } //BIND_END //BIND_METHOD MatDataElementInterface get_type { LUABIND_RETURN(uint, obj->getDataType()); } //BIND_END //BIND_METHOD MatDataElementInterface get_class { LUABIND_RETURN(uint, obj->getClass()); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_CONSTRUCTOR MatFileReader { LUABIND_CHECK_ARGN(==,1); const char *path; LUABIND_GET_PARAMETER(1, string, path); MatFileReader *reader = new MatFileReader(path); LUABIND_RETURN(MatFileReader, reader); } //BIND_END //BIND_METHOD MatFileReader reset { obj->reset(); } //BIND_END //BIND_METHOD MatFileReader get_next_element { MatTaggedDataElement *element = obj->getNextDataElement(); LUABIND_RETURN(MatTaggedDataElement, element); } //BIND_END //BIND_METHOD MatFileReader elements { LUABIND_RETURN(cfunction,elements_iterator_function); LUABIND_RETURN(MatFileReader,obj); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_CONSTRUCTOR MatTaggedDataElement { LUABIND_ERROR("abstract class"); } //BIND_END //BIND_METHOD MatTaggedDataElement get_matrix { char name[MAX_NAME_SIZE]; Basics::MatrixFloat *m = obj->getMatrix(name, MAX_NAME_SIZE); if (m != 0) { LUABIND_RETURN(MatrixFloat, m); LUABIND_RETURN(string, name); } } //BIND_END //BIND_METHOD MatTaggedDataElement get_matrix_complex { char name[MAX_NAME_SIZE]; Basics::MatrixComplexF *m = obj->getMatrixComplexF(name, MAX_NAME_SIZE); LUABIND_RETURN(MatrixComplexF, m); LUABIND_RETURN(string, name); } //BIND_END //BIND_METHOD MatTaggedDataElement get_matrix_double { char name[MAX_NAME_SIZE]; Basics::MatrixDouble *m = obj->getMatrixDouble(name, MAX_NAME_SIZE); if (m != 0) { LUABIND_RETURN(MatrixDouble, m); LUABIND_RETURN(string, name); } } //BIND_END //BIND_METHOD MatTaggedDataElement get_matrix_char { char name[MAX_NAME_SIZE]; Basics::MatrixChar *m = obj->getMatrixChar(name, MAX_NAME_SIZE); LUABIND_RETURN(MatrixChar, m); LUABIND_RETURN(string, name); } //BIND_END //BIND_METHOD MatTaggedDataElement get_matrix_int32 { char name[MAX_NAME_SIZE]; Basics::MatrixInt32 *m = obj->getMatrixInt32(name, MAX_NAME_SIZE); if (m != 0) { LUABIND_RETURN(MatrixInt32, m); LUABIND_RETURN(string, name); } } //BIND_END //BIND_METHOD MatTaggedDataElement get_cell_array { char name[MAX_NAME_SIZE]; MatCellArrayDataElement *c = obj->getCellArray(name, MAX_NAME_SIZE); LUABIND_RETURN(MatCellArrayDataElement, c); LUABIND_RETURN(string, name); } //BIND_END //BIND_METHOD MatTaggedDataElement get_structure { char name[MAX_NAME_SIZE]; MatStructureDataElement *s = obj->getStructure(name, MAX_NAME_SIZE); lua_createtable(L, 0, s->size()); for (MatStructureDataElement::HashType::iterator it=s->begin(); it != s->end(); ++it) { const char *ename = it->first.c_str(); MatTaggedDataElement *e = it->second; lua_pushstring(L, ename); lua_pushMatTaggedDataElement(L, e); lua_rawset(L, -3); } LUABIND_RETURN_FROM_STACK(-1); LUABIND_RETURN(string, name); delete s; } //BIND_END //BIND_METHOD MatTaggedDataElement reset { obj->reset(); } //BIND_END //BIND_METHOD MatTaggedDataElement get_num_bytes { LUABIND_RETURN(uint, obj->getNumberOfBytes()); } //BIND_END //BIND_METHOD MatTaggedDataElement get_next_subelement { if (obj->getNextSubElement() != 0) LUABIND_RETURN(MatTaggedDataElement, obj->getNextSubElement()); else LUABIND_RETURN_NIL(); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_CONSTRUCTOR MatCellArrayDataElement { LUABIND_ERROR("abstract class\n"); } //BIND_END //BIND_METHOD MatCellArrayDataElement compute_coords { LUABIND_CHECK_ARGN(==,1); int raw_idx; LUABIND_GET_PARAMETER(1, int, raw_idx); if (raw_idx < 0 || raw_idx >= obj->getSize()) LUABIND_FERROR3("Incorrect raw index, found %d, expected betwen [%d,%d]", raw_idx, 0, obj->getSize()); int *coords = new int[obj->getNumDim()]; obj->computeCoords(raw_idx, coords); for (int i=0; igetNumDim(); ++i) coords[i]++; LUABIND_VECTOR_TO_NEW_TABLE(int, coords, obj->getNumDim()); LUABIND_RETURN_FROM_STACK(-1); delete[] coords; } //BIND_END //BIND_METHOD MatCellArrayDataElement raw_get { LUABIND_CHECK_ARGN(==,1); int raw_idx; LUABIND_GET_PARAMETER(1, int, raw_idx); if (raw_idx < 0 || raw_idx >= obj->getSize()) LUABIND_FERROR3("Incorrect raw index, found %d, expected betwen [%d,%d]", raw_idx, 0, obj->getSize()); LUABIND_RETURN(MatTaggedDataElement, obj->getElementAt(raw_idx)); } //BIND_END //BIND_METHOD MatCellArrayDataElement size { LUABIND_RETURN(int, obj->getSize()); } //BIND_END //BIND_METHOD MatCellArrayDataElement get { int argn = lua_gettop(L); // number of arguments if (argn != obj->getNumDim()) LUABIND_FERROR2("wrong size %d instead of %d",argn,obj->getNumDim()); int *coords = new int[obj->getNumDim()]; for (int i=0; igetNumDim(); ++i) { LUABIND_GET_PARAMETER(i+1,int,coords[i]); if (coords[i]<1 || coords[i] > obj->getDimSize(i)) { LUABIND_FERROR2("wrong index parameter: 1 <= %d <= %d is incorrect", coords[i], obj->getDimSize(i)); } coords[i]--; } MatTaggedDataElement *e = obj->getElementAt(coords, argn); delete[] coords; LUABIND_RETURN(MatTaggedDataElement, e); } //BIND_END //BIND_METHOD MatCellArrayDataElement dim { int argn = lua_gettop(L); // number of arguments if (argn == 1) { int idx; LUABIND_GET_PARAMETER(1, int, idx); if (idx < 1 || idx > obj->getNumDim()) LUABIND_FERROR3("Incorrect dimension number, found %d, expected " "between [%d,%d]", idx, 1, obj->getNumDim()); LUABIND_RETURN(int, obj->getDimSize(idx-1)); } else { const int *d = obj->getDimPtr(); LUABIND_VECTOR_TO_NEW_TABLE(int, d, obj->getNumDim()); LUABIND_RETURN_FROM_STACK(-1); } } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_CONSTRUCTOR MatStructureDataElement { LUABIND_ERROR("abstract class\n"); } //BIND_END april-ann-0.4.1/packages/misc/matlab/c_src/000077500000000000000000000000001263004425400204375ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/matlab/c_src/matlab.cc000066400000000000000000001042711263004425400222130ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include #include #include #include // mmap() is defined in this header #include #include #include #include "unused_variable.h" #include "matlab.h" #include "endianism.h" #include "ignore_result.h" #include "error_print.h" #define MOD8(v) (v)&(0x07) using namespace AprilUtils; using namespace AprilMath; using namespace Basics; namespace Matlab { int inflate(const void *src, int srcLen, void *dst, int dstLen) { z_stream strm; strm.next_in = 0; strm.total_in = strm.avail_in = srcLen; strm.total_out = strm.avail_out = dstLen; strm.next_in = (Bytef *) src; strm.next_out = (Bytef *) dst; strm.zalloc = Z_NULL; strm.zfree = Z_NULL; strm.opaque = Z_NULL; int err = -1; int ret = -1; // 15 window bits, and the +32 tells zlib to to detect if using gzip or zlib err = inflateInit2(&strm, (15 + 32)); if (err == Z_OK) { err = inflate(&strm, Z_FINISH); if (err == Z_STREAM_END) { ret = strm.total_out; } else { inflateEnd(&strm); return err; } } else { inflateEnd(&strm); return err; } inflateEnd(&strm); return ret; } template inline void sanity_check_float_precision(T num) { if (num >= 16777216 || num <= -16777216) ERROR_PRINT("The integer part can't be represented " "using float precision\n"); } template<> inline void sanity_check_float_precision(int8_t num) { UNUSED_VARIABLE(num); } template<> inline void sanity_check_float_precision(uint8_t num) { UNUSED_VARIABLE(num); } template<> inline void sanity_check_float_precision(int16_t num) { UNUSED_VARIABLE(num); } template<> inline void sanity_check_float_precision(uint16_t num) { UNUSED_VARIABLE(num); } template<> inline void sanity_check_float_precision(float num) { UNUSED_VARIABLE(num); } template inline void sanity_check_int32_precision(T num) { if (llabs(num) >= 2147483648) ERROR_PRINT("The integer can't be represented using int32 precision\n"); } template<> inline void sanity_check_int32_precision(uint32_t num) { if (num >= 2147483648) ERROR_PRINT("The integer can't be represented using int32 precision\n"); } template<> inline void sanity_check_int32_precision(uint64_t num) { if (num >= 2147483648) ERROR_PRINT("The integer can't be represented using int32 precision\n"); } template<> inline void sanity_check_int32_precision(int8_t num) { UNUSED_VARIABLE(num); } template<> inline void sanity_check_int32_precision(uint8_t num) { UNUSED_VARIABLE(num); } template<> inline void sanity_check_int32_precision(int16_t num) { UNUSED_VARIABLE(num); } template<> inline void sanity_check_int32_precision(uint16_t num) { UNUSED_VARIABLE(num); } template<> inline void sanity_check_int32_precision(int32_t num) { UNUSED_VARIABLE(num); } template inline void sanity_check_double_precision(T num) { UNUSED_VARIABLE(num); } template<> inline void sanity_check_double_precision(int64_t num) { if (num >= 9007199254740991 || num <= -9007199254740991) ERROR_PRINT("The integer can't be represented using double precision\n"); } template<> inline void sanity_check_double_precision(uint64_t num) { if (num >= 9007199254740991) ERROR_PRINT("The integer can't be represented using double precision\n"); } template void readMatrixData(MatrixFloat::iterator &m_it, MatrixFloat::iterator &end, const T *ptr, const uint32_t nbytes) { UNUSED_VARIABLE(end); for (uint32_t ptr_pos=0; ptr_pos < nbytes; ptr_pos += sizeof(T), ++ptr) { april_assert(m_it != end); sanity_check_float_precision(*ptr); *m_it = static_cast(*ptr); ++m_it; } } template void readMatrixData(MatrixComplexF::iterator &m_it, MatrixComplexF::iterator &end, const T *ptr_real, const T *ptr_img, const uint32_t nbytes) { UNUSED_VARIABLE(end); if (ptr_img != 0) { for (uint32_t ptr_pos=0; ptr_pos < nbytes; ptr_pos += sizeof(T), ++ptr_real, ++ptr_img) { april_assert(m_it != end); sanity_check_float_precision(*ptr_real); sanity_check_float_precision(*ptr_img); *m_it = ComplexF(static_cast(*ptr_real), static_cast(*ptr_img)); ++m_it; } } else { for (uint32_t ptr_pos=0; ptr_pos < nbytes; ptr_pos += sizeof(T), ++ptr_real) { april_assert(m_it != end); sanity_check_float_precision(*ptr_real); *m_it = ComplexF(static_cast(*ptr_real), 0.0f); ++m_it; } } } template void readMatrixData(MatrixDouble::iterator &m_it, MatrixDouble::iterator &end, const T *ptr, const uint32_t nbytes) { UNUSED_VARIABLE(end); for (uint32_t ptr_pos=0; ptr_pos < nbytes; ptr_pos += sizeof(T), ++ptr) { april_assert(m_it != end); sanity_check_double_precision(*ptr); *m_it = static_cast(*ptr); ++m_it; } } template void readMatrixData(MatrixChar::iterator &m_it, MatrixChar::iterator &end, const T *ptr, const uint32_t nbytes) { UNUSED_VARIABLE(end); for (uint32_t ptr_pos=0; ptr_pos < nbytes; ptr_pos += sizeof(T), ++ptr) { april_assert(m_it != end); *m_it = *ptr; ++m_it; } } template void readMatrixData(MatrixInt32::iterator &m_it, MatrixInt32::iterator &end, const T *ptr, const uint32_t nbytes) { UNUSED_VARIABLE(end); for (uint32_t ptr_pos=0; ptr_pos < nbytes; ptr_pos += sizeof(T), ++ptr) { april_assert(m_it != end); sanity_check_int32_precision(*ptr); *m_it = static_cast(*ptr); ++m_it; } } ///////////////////////// TaggedDataElement ////////////////////////////////// MatFileReader::TaggedDataElement *MatFileReader::TaggedDataElement:: getNextSubElement() { if (data_pos < getSizeOf() - TAG_SIZE) { TaggedDataElement *sub_element = getDataElement(reader, data + data_pos); data_pos += sub_element->getSizeOf(); // FOR THE PADDING OF 64 BITS (8 BYTES) size_t mod8 = MOD8(data_pos); if (mod8 != 0) data_pos += (8 - mod8); april_assert(data_pos <= getSizeOf()); return sub_element; } else return 0; } uint32_t MatFileReader::TaggedDataElement::getClass() { if (getDataType() != MATRIX) { ERROR_PRINT1("Impossible to get CLASS from a non " "Matrix element (type %d)\n", getDataType()); return 0; } // ugly hack to force the extraction of array_flags from the first sub-element int old_data_pos = data_pos; data_pos = 0; // end of hack TaggedDataElement *array_flags = getNextSubElement(); // returning data_pos to its original position data_pos = old_data_pos; const char *flags = array_flags->getData(); // CHECK: [0] only for little_endian uint32_t cl = static_cast(flags[0]); delete array_flags; return cl; } MatFileReader::CellArrayDataElement *MatFileReader::TaggedDataElement:: getCellArray(char *name, size_t maxsize) { if (getDataType() != MATRIX) { ERROR_PRINT1("Impossible to get a Matrix from a non " "Matrix element (type %d)\n", getDataType()); return 0; } if (getClass() != CL_CELL_ARRAY) { ERROR_PRINT1("Impossible to get a cell array from a non cell array " "element (class %d)\n", getClass()); return 0; } TaggedDataElement *array_flags = getNextSubElement(); TaggedDataElement *dims_array = getNextSubElement(); TaggedDataElement *array_name = getNextSubElement(); if (array_flags==0 || dims_array==0 || array_name==0) ERROR_EXIT(128, "Impossible to found all ARRAY elements\n"); int num_dims = dims_array->getNumberOfBytes()/sizeof(int32_t); const int32_t *dims = dims_array->getData(); CellArrayDataElement *cell_array = new CellArrayDataElement(reader, dims, num_dims); TaggedDataElement *cell; int idx=0; while( (cell = getNextSubElement()) != 0 && idx < cell_array->getSize()) cell_array->setElementAt(idx++, cell); if (array_name->getNumberOfBytes() > maxsize-1) ERROR_EXIT2(128, "Overflow at array name, found %u, maximum %lu\n", array_name->getNumberOfBytes(), maxsize); strncpy(name, array_name->getData(), array_name->getNumberOfBytes()); name[array_name->getNumberOfBytes()] = '\0'; delete array_flags; delete dims_array; delete array_name; reset(); return cell_array; } MatFileReader::StructureDataElement *MatFileReader::TaggedDataElement:: getStructure(char *name, size_t maxsize) { if (getDataType() != MATRIX) { ERROR_PRINT1("Impossible to get a Matrix from a non " "Matrix element (type %d)\n", getDataType()); return 0; } if (getClass() != CL_STRUCTURE) { ERROR_PRINT1("Impossible to get a structure from a non structure " "element (class %d)\n", getClass()); return 0; } TaggedDataElement *array_flags = getNextSubElement(); TaggedDataElement *dims_array = getNextSubElement(); TaggedDataElement *array_name = getNextSubElement(); TaggedDataElement *fname_length = getNextSubElement(); TaggedDataElement *fnames = getNextSubElement(); if (array_flags==0 || dims_array==0 || array_name==0 || fname_length == 0 || fnames == 0) ERROR_EXIT(128, "Impossible to found all ARRAY elements\n"); StructureDataElement *structure = new StructureDataElement(reader); TaggedDataElement *field; // size of every name int32_t fname_length_value = fname_length->getData()[0]; // compute the number of fields (size) int size = fnames->getNumberOfBytes()/fname_length_value; // pointer to the current name const char *current_name=fnames->getData(); for (int i=0; isetElementByName(current_name, field); current_name += fname_length_value; } if (array_name->getNumberOfBytes() > maxsize-1) ERROR_EXIT2(128, "Overflow at array name, found %u, maximum %lu\n", array_name->getNumberOfBytes(), maxsize); strncpy(name, array_name->getData(), array_name->getNumberOfBytes()); name[array_name->getNumberOfBytes()] = '\0'; delete array_flags; delete dims_array; delete array_name; delete fname_length; delete fnames; reset(); return structure; } // ONLY IF CHAR ARRAY MatrixChar *MatFileReader::TaggedDataElement:: getMatrixChar(char *name, size_t maxsize) { if (getDataType() != MATRIX) { ERROR_PRINT1("Impossible to get a Matrix from a non " "Matrix element (type %d)\n", getDataType()); return 0; } uint32_t cl = getClass(); if (cl != CL_CHAR) { ERROR_PRINT1("Incorrect array class type: %d\n", cl); return 0; } TaggedDataElement *array_flags = getNextSubElement(); TaggedDataElement *dims_array = getNextSubElement(); TaggedDataElement *array_name = getNextSubElement(); TaggedDataElement *real_part = getNextSubElement(); if (array_flags==0 || dims_array==0 || array_name==0 || real_part==0) ERROR_EXIT(128, "Impossible to found all ARRAY elements\n"); int num_dims = dims_array->getNumberOfBytes()/sizeof(int32_t); int *dims = new int[num_dims+1]; const int32_t *const_dims = dims_array->getData(); for (int i=0; i(const_dims[i]); MatrixChar *m; m = new MatrixChar(num_dims, dims); delete[] dims; // traversing in col_major the real/img part of the matrix will be traversed // last, so it is possible add all real components in a first step, and in a // second step to add all the imaginary components AprilUtils::SharedPtr< MatrixChar > mT(m->transpose()); MatrixChar::iterator it(mT->begin()); MatrixChar::iterator end(mT->end()); // this loop traverses all the real components, and later all the imaginary // components (if any) switch(real_part->getDataType()) { case UTF8: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case UTF16: case UTF32: ERROR_EXIT(128, "UTF16 and UTF32 formats are not implemented\n"); break; default: ERROR_EXIT1(128, "Data type %d not supported, use only UTF8\n", real_part->getDataType()); } if (array_name->getNumberOfBytes() > maxsize-1) ERROR_EXIT2(128, "Overflow at array name, found %u, maximum %lu\n", array_name->getNumberOfBytes(), maxsize); strncpy(name, array_name->getData(), array_name->getNumberOfBytes()); name[array_name->getNumberOfBytes()] = '\0'; delete array_flags; delete dims_array; delete array_name; delete real_part; reset(); return m; } MatrixFloat *MatFileReader::TaggedDataElement::getMatrix(char *name, size_t maxsize) { if (getDataType() != MATRIX) { ERROR_PRINT1("Impossible to get a Matrix from a non " "Matrix element (type %d)\n", getDataType()); return 0; } uint32_t cl = getClass(); switch(cl) { case CL_CELL_ARRAY: case CL_STRUCTURE: case CL_OBJECT: case CL_CHAR: case CL_SPARSE: ERROR_PRINT1("Incorrect array class type: %d\n", cl); return 0; default: ; } TaggedDataElement *array_flags = getNextSubElement(); TaggedDataElement *dims_array = getNextSubElement(); TaggedDataElement *array_name = getNextSubElement(); TaggedDataElement *real_part = getNextSubElement(); TaggedDataElement *img_part = getNextSubElement(); if (img_part != 0) { delete array_flags; delete dims_array; delete array_name; delete real_part; delete img_part; reset(); return 0; } if (array_flags==0 || dims_array==0 || array_name==0 || real_part==0) ERROR_EXIT(128, "Impossible to found all ARRAY elements\n"); int num_dims = dims_array->getNumberOfBytes()/sizeof(int32_t); int *dims = new int[num_dims+1]; const int32_t *const_dims = dims_array->getData(); for (int i=0; i(const_dims[i]); MatrixFloat *m; m = new MatrixFloat(num_dims, dims); // traversing in col_major AprilUtils::SharedPtr< MatrixFloat > mT(m->transpose()); MatrixFloat::iterator it(mT->begin()); MatrixFloat::iterator end(mT->end()); switch(real_part->getDataType()) { case SINGLE: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case INT8: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case UINT8: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case INT16: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case UINT16: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case DOUBLE: case INT32: case UINT32: case INT64: case UINT64: default: ERROR_EXIT1(128,"Data type %d not supported\n", real_part->getDataType()); } if (array_name->getNumberOfBytes() > maxsize-1) ERROR_EXIT2(128, "Overflow at array name, found %u, maximum %lu\n", array_name->getNumberOfBytes(), maxsize); strncpy(name, array_name->getData(), array_name->getNumberOfBytes()); name[array_name->getNumberOfBytes()] = '\0'; delete array_flags; delete dims_array; delete array_name; delete real_part; delete img_part; delete[] dims; reset(); return m; } MatrixComplexF *MatFileReader::TaggedDataElement:: getMatrixComplexF(char *name, size_t maxsize) { if (getDataType() != MATRIX) { ERROR_PRINT1("Impossible to get a Matrix from a non " "Matrix element (type %d)\n", getDataType()); return 0; } uint32_t cl = getClass(); switch(cl) { case CL_CELL_ARRAY: case CL_STRUCTURE: case CL_OBJECT: case CL_CHAR: case CL_SPARSE: ERROR_PRINT1("Incorrect array class type: %d\n", cl); return 0; default: ; } TaggedDataElement *array_flags = getNextSubElement(); TaggedDataElement *dims_array = getNextSubElement(); TaggedDataElement *array_name = getNextSubElement(); TaggedDataElement *real_part = getNextSubElement(); TaggedDataElement *img_part = getNextSubElement(); if (array_flags==0 || dims_array==0 || array_name==0 || real_part==0) ERROR_EXIT(128, "Impossible to found all ARRAY elements\n"); int num_dims = dims_array->getNumberOfBytes()/sizeof(int32_t); int *dims = new int[num_dims]; const int32_t *const_dims = dims_array->getData(); for (int i=0; i(const_dims[i]); MatrixComplexF *m; m = new MatrixComplexF(num_dims, dims); // traversing in col_major AprilUtils::SharedPtr< MatrixComplexF > mT(m->transpose()); MatrixComplexF::iterator it(mT->begin()); MatrixComplexF::iterator end(mT->end()); if (real_part->getDataType() != img_part->getDataType()) ERROR_EXIT(256, "Found different data-type for real and imaginary part\n"); switch(real_part->getDataType()) { case SINGLE: readMatrixData(it, end, real_part->getData(), img_part->getData(), real_part->getNumberOfBytes()); break; case INT8: readMatrixData(it, end, real_part->getData(), img_part->getData(), real_part->getNumberOfBytes()); break; case UINT8: readMatrixData(it, end, real_part->getData(), img_part->getData(), real_part->getNumberOfBytes()); break; case INT16: readMatrixData(it, end, real_part->getData(), img_part->getData(), real_part->getNumberOfBytes()); break; case UINT16: readMatrixData(it, end, real_part->getData(), img_part->getData(), real_part->getNumberOfBytes()); break; case DOUBLE: ERROR_PRINT("Warning, casting from double to float\n"); readMatrixData(it, end, real_part->getData(), img_part->getData(), real_part->getNumberOfBytes()); break; case INT32: case UINT32: case INT64: case UINT64: default: ERROR_EXIT1(128,"Data type %d not supported\n", real_part->getDataType()); } if (array_name->getNumberOfBytes() > maxsize-1) ERROR_EXIT2(128, "Overflow at array name, found %u, maximum %lu\n", array_name->getNumberOfBytes(), maxsize); strncpy(name, array_name->getData(), array_name->getNumberOfBytes()); name[array_name->getNumberOfBytes()] = '\0'; delete array_flags; delete dims_array; delete array_name; delete real_part; delete img_part; delete[] dims; reset(); return m; } MatrixDouble *MatFileReader::TaggedDataElement::getMatrixDouble(char *name, size_t maxsize) { if (getDataType() != MATRIX) { ERROR_PRINT1("Impossible to get a Matrix from a non " "Matrix element (type %d)\n", getDataType()); return 0; } uint32_t cl = getClass(); switch(cl) { case CL_CELL_ARRAY: case CL_STRUCTURE: case CL_OBJECT: case CL_CHAR: case CL_SPARSE: ERROR_PRINT1("Incorrect array class type: %d\n", cl); return 0; default: ; } TaggedDataElement *array_flags = getNextSubElement(); TaggedDataElement *dims_array = getNextSubElement(); TaggedDataElement *array_name = getNextSubElement(); TaggedDataElement *real_part = getNextSubElement(); TaggedDataElement *img_part = getNextSubElement(); if (array_flags==0 || dims_array==0 || array_name==0 || real_part==0) ERROR_EXIT(128, "Impossible to found all ARRAY elements\n"); if (img_part != 0) { delete array_flags; delete dims_array; delete array_name; delete real_part; delete img_part; reset(); return 0; } int num_dims = dims_array->getNumberOfBytes()/sizeof(int32_t); int *dims = new int[num_dims]; const int32_t *const_dims = dims_array->getData(); for (int i=0; i(const_dims[i]); MatrixDouble *m; m = new MatrixDouble(num_dims, dims); // traversing in col_major AprilUtils::SharedPtr< MatrixDouble > mT(m->transpose()); MatrixDouble::iterator it(mT->begin()); MatrixDouble::iterator end(mT->end()); switch(real_part->getDataType()) { case INT8: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case UINT8: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case INT16: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case UINT16: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case INT32: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case UINT32: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case INT64: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case UINT64: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case DOUBLE: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case SINGLE: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; default: ERROR_EXIT1(128,"Data type %d not supported\n", real_part->getDataType()); } if (array_name->getNumberOfBytes() > maxsize-1) ERROR_EXIT2(128, "Overflow at array name, found %u, maximum %lu\n", array_name->getNumberOfBytes(), maxsize); strncpy(name, array_name->getData(), array_name->getNumberOfBytes()); name[array_name->getNumberOfBytes()] = '\0'; delete array_flags; delete dims_array; delete array_name; delete real_part; delete img_part; delete[] dims; reset(); return m; } MatrixInt32 *MatFileReader::TaggedDataElement::getMatrixInt32(char *name, size_t maxsize) { if (getDataType() != MATRIX) { ERROR_PRINT1("Impossible to get a Matrix from a non " "Matrix element (type %d)\n", getDataType()); return 0; } uint32_t cl = getClass(); switch(cl) { case CL_CELL_ARRAY: case CL_STRUCTURE: case CL_OBJECT: case CL_CHAR: case CL_SPARSE: ERROR_PRINT1("Incorrect array class type: %d\n", cl); return 0; default: ; } TaggedDataElement *array_flags = getNextSubElement(); TaggedDataElement *dims_array = getNextSubElement(); TaggedDataElement *array_name = getNextSubElement(); TaggedDataElement *real_part = getNextSubElement(); TaggedDataElement *img_part = getNextSubElement(); if (array_flags==0 || dims_array==0 || array_name==0 || real_part==0) ERROR_EXIT(128, "Impossible to found all ARRAY elements\n"); if (img_part != 0) { delete array_flags; delete dims_array; delete array_name; delete real_part; delete img_part; reset(); return 0; } int num_dims = dims_array->getNumberOfBytes()/sizeof(int32_t); int *dims = new int[num_dims]; const int32_t *const_dims = dims_array->getData(); for (int i=0; i(const_dims[i]); MatrixInt32 *m; m = new MatrixInt32(num_dims, dims); // traversing in col_major AprilUtils::SharedPtr< MatrixInt32 > mT(m->transpose()); MatrixInt32::iterator it(mT->begin()); MatrixInt32::iterator end(mT->end()); switch(real_part->getDataType()) { case INT8: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case UINT8: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case INT16: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case UINT16: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case INT32: readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case UINT32: ERROR_PRINT("Warning, casting from uint32 to int32\n"); readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case INT64: ERROR_PRINT("Warning, casting from int64 to int32\n"); readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case UINT64: ERROR_PRINT("Warning, casting from uint64 to int32\n"); readMatrixData(it, end, real_part->getData(), real_part->getNumberOfBytes()); break; case SINGLE: case DOUBLE: default: ERROR_EXIT1(128,"Data type %d not supported\n", real_part->getDataType()); } if (array_name->getNumberOfBytes() > maxsize-1) ERROR_EXIT2(128, "Overflow at array name, found %u, maximum %lu\n", array_name->getNumberOfBytes(), maxsize); strncpy(name, array_name->getData(), array_name->getNumberOfBytes()); name[array_name->getNumberOfBytes()] = '\0'; delete[] dims; delete array_flags; delete dims_array; delete array_name; delete real_part; delete img_part; reset(); return m; } //////////////////////// CellArrayDataElement ////////////////////////////////// MatFileReader::CellArrayDataElement:: CellArrayDataElement(MatFileReader *reader, const int *dims, int num_dims) : DataElementInterface(reader), dims(new int[num_dims]), stride(new int[num_dims]), num_dims(num_dims), total_size(1) { for (int i=0; idims[i] = dims[i]; this->stride[i] = total_size; total_size *= dims[i]; } elements = new TaggedDataElement*[total_size]; for (int i=0; i= 0 && raw_idx < total_size); if (elements[raw_idx] != 0) ERROR_EXIT(128, "The given position is not empty\n"); elements[raw_idx] = e; IncRef(e); } MatFileReader::TaggedDataElement *MatFileReader::CellArrayDataElement:: getElementAt(const int *coords, int n) { if (n != num_dims) ERROR_EXIT2(128, "Incorrect size of coords vector, found %d, expected %d\n", n, num_dims); return getElementAt(computeRawPos(coords)); } MatFileReader::TaggedDataElement *MatFileReader::CellArrayDataElement:: getElementAt(int raw_idx) { assert(raw_idx >= 0 && raw_idx < total_size); return elements[raw_idx]; } //////////////////////// StructureDataElement ////////////////////////////////// MatFileReader::StructureDataElement::StructureDataElement(MatFileReader *reader) : DataElementInterface(reader) { } MatFileReader::StructureDataElement:: ~StructureDataElement() { for (HashType::iterator it=elements.begin(); it!=elements.end(); ++it) DecRef(it->second); } void MatFileReader::StructureDataElement:: setElementByName(const char *name, TaggedDataElement *e) { string key(name); TaggedDataElement *&value = elements[key]; if (value != 0) ERROR_EXIT1(128, "The given name '%s' is occupied\n", name); value = e; IncRef(value); } MatFileReader::TaggedDataElement *MatFileReader::StructureDataElement:: getElementByName(const char *name) { string key(name); return elements[key]; } //////////////////////////// MatFileReader ///////////////////////////////////// MatFileReader::MatFileReader(const char *path) : Referenced(), mmapped_data_pos(0) { if ((fd = open(path, O_RDONLY)) < 0) ERROR_EXIT1(128,"Unable to open file %s\n", path); // find size of input file struct stat statbuf; if (fstat(fd, &statbuf) < 0) { ERROR_PRINT("Error guessing filesize\n"); exit(1); } // mmap the input file mmapped_data_size = statbuf.st_size; if ((mmapped_data = static_cast(mmap(0, mmapped_data_size, PROT_READ, MAP_SHARED, fd, 0))) == (caddr_t)-1) ERROR_EXIT(128, "mmap error\n"); // EXTRACT HEADER header = getCurrent(); addToCurrent(HEADER_SIZE); // union { char magic_char[2]; uint16_t magic_int; } Endianism; Endianism.magic_int = header->magic; swap_bytes = (Endianism.magic_char[0]=='M' && Endianism.magic_char[1]=='I'); if (swap_bytes) ERROR_EXIT(128, "ENDIANISM LOGIC NOT IMPLEMENTED\n"); } MatFileReader::~MatFileReader() { munmap(mmapped_data, mmapped_data_size); close(fd); while(!decompressed_buffers.empty()) { delete[] decompressed_buffers.front(); decompressed_buffers.pop_front(); } } MatFileReader::TaggedDataElement *MatFileReader::getNextDataElement() { if (mmapped_data_pos < mmapped_data_size) { TaggedDataElement *element = getDataElement(this, getCurrent()); if (element->getDataType()!=MATRIX && element->getDataType()!=COMPRESSED) ERROR_EXIT1(128, "Incorrect data type, expected MATRIX or " "COMPRESSED, found %d\n", element->getDataType()); addToCurrent(element->getSizeOf()); if (element->getDataType() == COMPRESSED) { int len = static_cast(element->getNumberOfBytes()); char *buff = 0; int err; do { len = len << 1; delete[] buff; buff = new char[len]; } while((err=inflate(element->getData(), element->getNumberOfBytes(), reinterpret_cast(buff),len)) == Z_BUF_ERROR); delete element; element = getDataElement(this, buff); decompressed_buffers.push_front(buff); } return element; } else return 0; } MatFileReader::TaggedDataElement *MatFileReader:: getDataElement(MatFileReader *reader, const char *ptr) { TaggedDataElement *ret; FullTagDataElement *full_data; full_data = new FullTagDataElement(reader, ptr); if (full_data->isSmall()) { delete full_data; ret = new SmallTagDataElement(reader, ptr); } else ret = full_data; return ret; } } // namespace Matlab april-ann-0.4.1/packages/misc/matlab/c_src/matlab.h000066400000000000000000000211451263004425400220530ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ /****************************************************************** * * Readers of MAT format of Matlab * http://www.mathworks.com/help/pdf_doc/matlab/matfile_format.pdf * ******************************************************************/ #ifndef MATLAB_H #define MATLAB_H #include #include #include "matrixFloat.h" #include "matrixComplexF.h" #include "matrixChar.h" #include "matrixInt32.h" #include "matrixDouble.h" #include "list.h" #include "hash_table.h" #include "mystring.h" #define MAX_NAME_SIZE 256 #define HEADER_SIZE 128 #define HEADER_TEXT_SIZE 124 #define TAG_SIZE 8 #define SMALL_TAG_SIZE 4 #define SMALL_DATA_SIZE 4 #define MAX_NUM_DIMS 32 #define DATA_TYPE 0 #define NUMBER_OF_BYTES 1 /** * @brief Readers of MAT format of Matlab. * @see http://www.mathworks.com/help/pdf_doc/matlab/matfile_format.pdf */ namespace Matlab { class MatFileReader : public Referenced { public: enum MatFileDataTypes { INT8=1, UINT8=2, INT16=3, UINT16=4, INT32=5, UINT32=6, SINGLE=7, RESERVED1=8, DOUBLE=9, RESERVED2=10, RESERVED3=11, INT64=12, UINT64=13, MATRIX=14, COMPRESSED=15, UTF8=16, UTF16=17, UTF32=18, NUMBER_OF_DATA_TYPES, }; enum MatFileClasses { CL_CELL_ARRAY=1, CL_STRUCTURE=2, CL_OBJECT=3, CL_CHAR=4, CL_SPARSE=5, CL_DOUBLE=6, CL_SINGLE=7, CL_INT8=8, CL_UINT8=9, CL_INT16=10, CL_UINT16=11, CL_INT32=12, CL_UINT32=13, CL_INT64=14, CL_UINT64=15, NUMBER_OF_CLASSES, }; private: struct HeaderType { char text[HEADER_TEXT_SIZE]; uint16_t version; uint16_t magic; }; struct FullDataTag { union { char hbytes[4]; uint32_t data_type; }; union { char lbytes[4]; uint32_t number_of_bytes; }; }; struct SmallDataTag { union { char hbytes[2]; uint16_t data_type; }; union { char lbytes[2]; uint16_t number_of_bytes; }; }; /************* DATA ELEMENTS ****************/ public: class DataElementInterface : public Referenced { protected: MatFileReader *reader; public: DataElementInterface(MatFileReader *reader) : Referenced(),reader(reader) { IncRef(reader); } virtual ~DataElementInterface() { DecRef(reader); } virtual uint32_t getDataType() const = 0; virtual uint32_t getClass() = 0; }; // forward declaration class CellArrayDataElement; class StructureDataElement; class TaggedDataElement : public DataElementInterface { friend class MatFileReader; protected: const char *data; size_t data_pos; TaggedDataElement(MatFileReader *reader, const char *ptr) : DataElementInterface(reader), data(ptr), data_pos(0) { } public: virtual ~TaggedDataElement() { } virtual uint32_t getDataType() const = 0; virtual uint32_t getNumberOfBytes() const = 0; virtual size_t getSizeOf() const = 0; template T getData() const { return reinterpret_cast(data); } void reset() { data_pos = 0; } // SUB-ELEMENTS TaggedDataElement *getNextSubElement(); // FOR NUMERIC TYPES (casting) Basics::MatrixFloat *getMatrix(char *name, size_t maxsize); // FOR NUMERIC TYPES (casting) Basics::MatrixComplexF *getMatrixComplexF(char *name, size_t maxsize); // FOR NUMERIC TYPES (casting) Basics::MatrixDouble *getMatrixDouble(char *name, size_t maxsize); virtual uint32_t getClass(); // ONLY IF CELL ARRAY CellArrayDataElement *getCellArray(char *name, size_t maxsize); // ONLY IF STRUCTURE StructureDataElement *getStructure(char *name, size_t maxsize); // ONLY IF CHAR ARRAY Basics::MatrixChar *getMatrixChar(char *name, size_t maxsize); // FOR NUMERIC TYPES (casting) Basics::MatrixInt32 *getMatrixInt32(char *name, size_t maxsize); }; class CellArrayDataElement : public DataElementInterface { int *dims, *stride, num_dims, total_size; TaggedDataElement **elements; int computeRawPos(const int *coords); public: CellArrayDataElement(MatFileReader *reader, const int *dims, int num_dims); ~CellArrayDataElement(); TaggedDataElement *getElementAt(const int *coords, int n); TaggedDataElement *getElementAt(int raw_idx); void setElementAt(const int *coords, int n, TaggedDataElement *e); void setElementAt(int raw_idx, TaggedDataElement *e); int getNumDim() const { return num_dims; } int getDimSize(int i) const { return dims[i]; } const int *getDimPtr() const { return dims; } int getSize() const { return total_size; } virtual uint32_t getDataType() const { return MATRIX; } virtual uint32_t getClass() { return CL_CELL_ARRAY; } void computeCoords(int raw_pos, int *coords) { for (int i=num_dims-1; i>=0; --i) { coords[i] = raw_pos / stride[i]; raw_pos = raw_pos % stride[i]; } } }; class StructureDataElement : public DataElementInterface { public: typedef AprilUtils::hash HashType; private: HashType elements; public: StructureDataElement(MatFileReader *reader); ~StructureDataElement(); TaggedDataElement *getElementByName(const char *name); void setElementByName(const char *name, TaggedDataElement *e); virtual uint32_t getDataType() const { return MATRIX; } virtual uint32_t getClass() { return CL_STRUCTURE; } HashType::iterator begin() { return elements.begin(); } HashType::iterator end() { return elements.end(); } unsigned int size() const { return elements.size(); } }; private: struct FullTagDataElement : public TaggedDataElement { const FullDataTag *tag; public: FullTagDataElement(MatFileReader *reader, const char *ptr) : TaggedDataElement(reader, ptr+TAG_SIZE), tag(reinterpret_cast(ptr)) { } virtual uint32_t getDataType() const { return tag->data_type; } virtual uint32_t getNumberOfBytes() const { return tag->number_of_bytes; } virtual size_t getSizeOf() const { return tag->number_of_bytes+TAG_SIZE; } bool isSmall() const { return (tag->hbytes[2]!=0 || tag->hbytes[3]!=0); } }; struct SmallTagDataElement : public TaggedDataElement { const SmallDataTag *tag; public: SmallTagDataElement(MatFileReader *reader, const char *ptr) : TaggedDataElement(reader, ptr+SMALL_TAG_SIZE), tag(reinterpret_cast(ptr)) { } virtual uint32_t getDataType() const { return static_cast(tag->data_type); } virtual uint32_t getNumberOfBytes() const { return static_cast(tag->number_of_bytes); } virtual size_t getSizeOf() const { return TAG_SIZE; } }; /********************************************/ /************** PROPERTIES *****************/ char *mmapped_data; size_t mmapped_data_size; size_t mmapped_data_pos; int fd; const HeaderType *header; bool swap_bytes; AprilUtils::list decompressed_buffers; /** MMAPPED DATA POINTER ACCESS **/ template T getCurrent() { return reinterpret_cast(mmapped_data+mmapped_data_pos); } void addToCurrent(size_t p) { mmapped_data_pos += p; april_assert(mmapped_data_pos <= mmapped_data_size); } /*********************************/ public: MatFileReader(const char *path); ~MatFileReader(); TaggedDataElement *getNextDataElement(); void reset() { mmapped_data_pos = 0; } static TaggedDataElement *getDataElement(MatFileReader *reader, const char *ptr); }; } // namespace Matlab #endif // MATLAB_H april-ann-0.4.1/packages/misc/matlab/lua_src/000077500000000000000000000000001263004425400207765ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/matlab/lua_src/matlab.lua000066400000000000000000000100041263004425400227340ustar00rootroot00000000000000matlab = matlab or {} local function generic_tostring(self) local out = {} for name,data in pairs(self) do local str = data.str and data:str() or "" table.insert(out,"%s : %s %s"%{name,type(data),str}) end return table.concat(out, "\n") end -- this table keeps a dictionary of functions which receives an element of a -- given class and returns an APRIL-ANN Lua object local class_tolua_table = { [0] = function(e) return e end, } -- auxiliary function to add new class builder functions local function add_wrapper(class_number, f) if not class_number then error("Incorrect class number") end class_tolua_table[class_number] = f end -- this function receives an element and returns its corresponding APRIL-ANN Lua -- object function matlab.tolua(element) if element:get_type() == matlab.types.matrix then local func = class_tolua_table[element:get_class()] if func then return func(element) else error("Not recognized class: " .. matlab.classes[element:get_class()]) end else error(string.format("Not implemented yet for type '%s'", matlab.types[element:get_type()] or tostring(element:get_type()) or "nil")) end collectgarbage("collect") end ----------------------------- -- CLASS BUILDER FUNCTIONS -- ----------------------------- local function tomatrix(e) local elem,name = e:get_matrix() if elem == nil then elem,name = e:get_matrix_complex() end return elem,name end local function tomatrixdouble(e) local elem,name = e:get_matrix_double() if elem == nil then elem,name = e:get_matrix_complex() end return elem,name end local function tomatrixint32(e) local elem,name = e:get_matrix_int32() if elem == nil then error("Not supported complex numbers for integer data types") end return elem,name end local function tomatrixchar(e) local elem,name = e:get_matrix_char() return elem,name end local function tocellarray(e) local cell_array,name = e:get_cell_array() local wrapper = class_wrapper(cell_array) wrapper = class_instance(wrapper, class.of(cell_array)) wrapper.get = function(obj, ...) return matlab.tolua(cell_array:get(...)) end wrapper.raw_get = function(obj, ...) return matlab.tolua(cell_array:raw_get(...)) end wrapper.str = function(obj) return "dims [%s]"%{table.concat(obj:dim(),",")} end return wrapper,name end local function tostructure(e) local dictionary,name = e:get_structure() for ename,elem in pairs(dictionary) do dictionary[ename] = matlab.tolua(elem) end setmetatable(dictionary, { __tostring = generic_tostring }) return dictionary,name end -- addition of all the functions to class_tolua_table -- FLOAT matrix add_wrapper(matlab.classes.single, tomatrix) -- DOUBLE matrix add_wrapper(matlab.classes.double, tomatrixdouble) -- INT matrix add_wrapper(matlab.classes.int8, tomatrixint32) add_wrapper(matlab.classes.uint8, tomatrixint32) add_wrapper(matlab.classes.int16, tomatrixint32) add_wrapper(matlab.classes.uint16, tomatrixint32) add_wrapper(matlab.classes.int32, tomatrixint32) add_wrapper(matlab.classes.uint32, tomatrixint32) add_wrapper(matlab.classes.int64, tomatrixint32) add_wrapper(matlab.classes.uint64, tomatrixint32) -- CHAR matrix add_wrapper(matlab.classes.char, tomatrixchar) -- CELL array add_wrapper(matlab.classes.cell_array, tocellarray) -- STRUCTURE array add_wrapper(matlab.classes.structure, tostructure) ----------------------------------------------------------------------------- ------------------- -- MAIN FUNCTION -- ------------------- -- reads a MAT file and returns a Lua table with all the elements, indexed by -- its names, and recursively containing matrix, cell_array or struct objects -- with all the data function matlab.read(path) assert(path and type(path)=="string", "First argument must be a path string") local reader = matlab.reader(path) local elements = {} for e in reader:elements() do local lua_element,name = matlab.tolua(e) elements[name] = lua_element end setmetatable(elements, { __tostring = generic_tostring }) return elements end april-ann-0.4.1/packages/misc/matlab/package.lua000066400000000000000000000021561263004425400214500ustar00rootroot00000000000000package{ name = "matlab", version = "1.0", depends = { "matrix", "util" }, keywords = { }, link_libraries = { "z" }, description = "", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test.lua", }, }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_matlab.lua.cc" , dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", dest_dir = "build", -- flags = "-std=c99", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_matlab.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/misc/matlab/test/000077500000000000000000000000001263004425400203255ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/matlab/test/test-output.log000066400000000000000000000045761263004425400233610ustar00rootroot00000000000000# Loading matrix double element: x # Loading cell array element: C instance 0x23e5c40 of matlab.cell_array # Loading structure element: X y instance 0x23e7460 of matlab.tagged_element # Loading matrix double element: # Loading structure element: X w instance 0x23e73f0 of matlab.tagged_element # Loading matrix double element: # Loading structure element: X z instance 0x23e74d0 of matlab.tagged_element # Loading matrix double element: # Loading matrix complex (casted from double) element: A 1.34187 -1.77726 -1.73478 -0.267141 0.67945 -0.864671 0.695942 1.12934 -1.25044 -0.710154 -0.932328 0.59467 0.332692 -0.420799 0.1242 0.361931 -0.221126 0.779788 -0.00665479 -0.327634 -0.254006 -2.86238 0.877438 0.200538 0.0397533 -0.127615 -0.429599 0.648093 -1.11046 -1.33459 1.87333 -0.572296 1.6083 -1.5067 0.707522 0.600558 0.589124 2.37575 0.0483031 -0.646724 1.3571 -1.62239 -1.25601 -0.480216 1.70552 0.00754286 -0.5679 -0.661177 -0.730054 1.2651 1.26294 -1.13459 0.799178 -0.0603598 0.967635 -1.4987 -0.419339 -1.61902 -0.597403 0.307181 0.885625 -0.303865 0.206848 0.669164 0.339318 2.30403 0.386978 -1.62213 -1.12447 -0.457475 -0.130334 0.767747 2.3219 -1.03111 -0.389085 2.80222 -0.427865 0.995131 -0.948442 -0.0218299 -0.999233 1.33908 0.968717 -0.68929 0.443295 -0.128687 0.590557 1.77715 -0.783717 -0.956102 0.564968 0.322677 -1.05338 -1.69783 1.7779 0.523945 0.810198 0.865949 -1.6916 0.827797 # MatrixDouble of size [10,10] [0x23e5310 data= 0x23b1140] # Loading matrix double element: 1 2 3 4 5 6 # MatrixDouble of size [2,3] [0x23eaed0 data= 0x23dbe20] # Loading matrix double element: 7 8 9 10 11 12 # MatrixDouble of size [2,3] [0x23eb760 data= 0x2393130] 2 # MatrixDouble of size [1,1] [0x23e76c0 data= 0x2397020] 1 # MatrixDouble of size [1,1] [0x23e7850 data= 0x23d4220] 3 # MatrixDouble of size [1,1] [0x23e79a0 data= 0x23d2fa0] 1-2i 4-4i -1+2i -4+4i # MatrixComplex of size [2,2] in row_major [0x23e7d30 data= 0x23d8850] april-ann-0.4.1/packages/misc/matlab/test/test.lua000066400000000000000000000050071263004425400220110ustar00rootroot00000000000000local check = utest.check local T = utest.test -- local dir = string.get_path(arg[0]) local test1 = matlab.read(dir.."test1.mat") local test2 = matlab.read(dir.."test2.mat") local test3 = matlab.read(dir.."test3.mat") local test4 = matlab.read(dir.."test4.mat") T("MatrixTest", function() local data=[[ 1.34187 -1.77726 -1.73478 -0.267141 0.67945 -0.864671 0.695942 1.12934 -1.25044 -0.710154 -0.932328 0.59467 0.332692 -0.420799 0.1242 0.361931 -0.221126 0.779788 -0.00665479 -0.327634 -0.254006 -2.86238 0.877438 0.200538 0.0397533 -0.127615 -0.429599 0.648093 -1.11046 -1.33459 1.87333 -0.572296 1.6083 -1.5067 0.707522 0.600558 0.589124 2.37575 0.0483031 -0.646724 1.3571 -1.62239 -1.25601 -0.480216 1.70552 0.00754286 -0.5679 -0.661177 -0.730054 1.2651 1.26294 -1.13459 0.799178 -0.0603598 0.967635 -1.4987 -0.419339 -1.61902 -0.597403 0.307181 0.885625 -0.303865 0.206848 0.669164 0.339318 2.30403 0.386978 -1.62213 -1.12447 -0.457475 -0.130334 0.767747 2.3219 -1.03111 -0.389085 2.80222 -0.427865 0.995131 -0.948442 -0.0218299 -0.999233 1.33908 0.968717 -0.68929 0.443295 -0.128687 0.590557 1.77715 -0.783717 -0.956102 0.564968 0.322677 -1.05338 -1.69783 1.7779 0.523945 0.810198 0.865949 -1.6916 0.827797]] local tgt = matrixDouble.read(aprilio.stream.input_lua_string(data), { tab=true }) check.eq(tgt:convert_to("float"), test1.x:convert_to("float")) end) T("CellArrayTest", function() local data1="1 2 3\n4 5 6" local data2="7 8 9\n10 11 12" local tgt1=matrixDouble.read(aprilio.stream.input_lua_string(data1), { tab=true }) local tgt2=matrixDouble.read(aprilio.stream.input_lua_string(data2), { tab=true }) check.eq(test2.C:get(1,1):convert_to("float"), tgt1:convert_to("float")) check.eq(test2.C:get(1,2):convert_to("float"), tgt2:convert_to("float")) end) T("StructTest", function() check.eq(test3.X.y:get(1,1), 2) check.eq(test3.X.w:get(1,1), 1) check.eq(test3.X.z:get(1,1), 3) end) T("ComplexTest", function() local data = "1-2i 4-4i\n-1+2i -4+4i" local tgt = matrixComplex.read(aprilio.stream.input_lua_string(data), { tab=true }) check.eq(test4.A, tgt) end) april-ann-0.4.1/packages/misc/matlab/test/test1.mat000066400000000000000000000017301263004425400220710ustar00rootroot00000000000000MATLAB 5.0 MAT-file, written by Octave 3.6.4, 2013-07-30 10:21:30 UTC IMP x KHx?kggAпH(w1(?;hg?%[P5? W? Y ˮ WY\ڶ7?HsoCje?gH&?%@P hQ!M8I':?@rӿ'b? Lql?C[nԼ?Z=*(J?-kr?э+?!&Nޒ?.y?}>@A}?17ѿ)_=`ڿżD>8?ךuqۻ޿+ty箿'ԯi?-6nAζeT*-[ ?-y˿?Z?ˋr?HEI?/M?\'6c?%Mؿ2^?Q[Ir?[0a뿚d)?{XUf47?&C~?ORn@/]_j@y[x6<)?"(E?RM̿P~ۿ0?Ͻ<,'0rڿ|>?:{E"bۿ*S?ʉ$?e?5 ?Z,?kd@XV)\(tC?4o?ٵ?kwTeB B{}g|qkQ0? \A㿙֪YT58 .y濭hԿ׮|ZY=?ubܨ?ZTEGݿR EZ_bCO}?april-ann-0.4.1/packages/misc/matlab/test/test2.mat000066400000000000000000000006001263004425400220650ustar00rootroot00000000000000MATLAB 5.0 MAT-file, written by Octave 3.6.4, 2013-07-30 14:25:38 UTC IMC` 0?@@@@@` 0@$@ @&@"@(@april-ann-0.4.1/packages/misc/matlab/test/test3.mat000066400000000000000000000007401263004425400220730ustar00rootroot00000000000000MATLAB 5.0 MAT-file, written by Octave 3.6.4, 2013-07-31 10:24:48 UTC IMXX `wyz8 ?8 @8 @april-ann-0.4.1/packages/misc/matlab/test/test4.mat000066400000000000000000000004001263004425400220650ustar00rootroot00000000000000MATLAB 5.0 MAT-file, written by Octave 3.6.4, 2013-08-19 12:26:08 UTC IMxA ?@ @@april-ann-0.4.1/packages/misc/rlcompleter/000077500000000000000000000000001263004425400204365ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/rlcompleter/binding/000077500000000000000000000000001263004425400220505ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/rlcompleter/binding/bind_rlcompleter.lua.cc000066400000000000000000000125211263004425400264640ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013 Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LUA_USE_READLINE #error "rlcompleter package needs READLINE support" #endif // GitHub link: https://github.com/rrthomas/lua-rlcompleter/ // // Original MIT License: // /************************************************************************ * Lua readline completion for the Lua standalone interpreter * * (c) 2013 Francisco Zamora-Martinez, adapted to APRIL-ANN * (c) 2011 Reuben Thomas * (c) 2007 Steve Donovan * (c) 2004 Jay Carlson * * Permission is hereby granted, free of charge, to any person obtaining * a copy of this software and associated documentation files (the * "Software"), to deal in the Software without restriction, including * without limitation the rights to use, copy, modify, merge, publish, * distribute, sublicense, and/or sell copies of the Software, and to * permit persons to whom the Software is furnished to do so, subject to * the following conditions * The above copyright notice and this permission notice shall be * included in all copies or substantial portions of the Software. * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY * CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, * TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE * SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ************************************************************************/ //BIND_HEADER_C #include extern "C" { #include #include #include #include #include #include } #include "unused_variable.h" char breaks[] = " \t\n\"\\'><=;:+-*%^~#{}()[].,"; char quotes[] = "\"'"; extern int rl_completion_suppress_append; #ifdef __APPLE__ #ifdef __HOMEBREW__ extern const char *rl_completer_quote_characters; #else extern char *rl_completer_quote_characters; #endif #else extern const char *rl_completer_quote_characters; #endif /* Static copy of Lua state, as readline has no per-use state */ static lua_State *storedL; /* Lua 5.2 compatibility */ #if LUA_VERSION_NUM > 501 static int luaL_typerror(lua_State *L, int narg, const char *tname) { const char *msg = lua_pushfstring(L, "%s expected, got %s", tname, luaL_typename(L, narg)); return luaL_argerror(L, narg, msg); } #endif /* This function is called repeatedly by rl_completion_matches inside do_completion, each time returning one element from the Lua table. */ static char *iterator(const char* text, int state) { UNUSED_VARIABLE(text); size_t len; const char *str; char *result; lua_rawgeti(storedL, -1, state + 1); if (lua_isnil(storedL, -1)) return NULL; str = lua_tolstring(storedL, -1, &len); result = static_cast(malloc(len + 1)); strcpy(result, str); lua_pop(storedL, 1); return result; } /* This function is called by readline() when the user wants a completion. */ static char **do_completion (const char *text, int start, int end) { int oldtop = lua_gettop(storedL); char **matches = NULL; lua_pushlightuserdata(storedL, (void *)iterator); lua_gettable(storedL, LUA_REGISTRYINDEX); rl_completion_suppress_append = 1; if (lua_isfunction(storedL, -1)) { lua_pushstring(storedL, text); lua_pushstring(storedL, rl_line_buffer); lua_pushinteger(storedL, start + 1); lua_pushinteger(storedL, end + 1); if (lua_pcall(storedL, 4, 1, 0)==LUA_OK && lua_istable(storedL, -1)) matches = rl_completion_matches (text, iterator); } lua_settop(storedL, oldtop); return matches; } //BIND_END //BIND_HEADER_H extern "C" { #include } #include "referenced.h" //BIND_END //BIND_FUNCTION rlcompleter._set { if (!lua_isfunction(L, 1)) luaL_typerror(L, 1, "function"); lua_pushlightuserdata(L, (void *)iterator); lua_pushvalue(L, 1); lua_settable(L, LUA_REGISTRYINDEX); } //BIND_END //BIND_FUNCTION rlcompleter.redisplay { rl_forced_update_display(); } //BIND_END //BIND_FUNCTION rlcompleter.readline { const char* prompt = lua_tostring(L,1); char *line = readline(prompt); LUABIND_RETURN(string, line); /* readline return value must be free'd */ free(line); } //BIND_END //BIND_STATIC_CONSTRUCTOR rlcompleter { storedL = L; // rl_basic_word_break_characters = breaks; rl_completer_word_break_characters = breaks; rl_completer_quote_characters = quotes; rl_attempted_completion_function = do_completion; } //BIND_END april-ann-0.4.1/packages/misc/rlcompleter/lua_src/000077500000000000000000000000001263004425400220665ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/rlcompleter/lua_src/rlcompleter.lua000066400000000000000000000123061263004425400251230ustar00rootroot00000000000000-- Lua side of readline completion for REPL -- By Patrick Rapin; adapted by Reuben Thomas -- Adapted to APRIL-ANN by Francisco Zamora-Martinez, 2013 -- escape all characters to avoid problems with Lua regular expressions local function escape(str) return str:gsub("(.)","%%%1") end -- Returns index_table field from a metatable, which is a copy of __index table. local function get_index(mt) return mt.index_table end -- The list of Lua keywords local keywords = { 'and', 'break', 'do', 'else', 'elseif', 'end', 'false', 'for', 'function', 'if', 'in', 'local', 'nil', 'not', 'or', 'repeat', 'return', 'then', 'true', 'until', 'while' } -- in case you want to use this software without APRIL-ANN local luatype = luatype or type -- This function is called back by C function do_completion, itself called -- back by readline library, in order to complete the current input line. rlcompleter._set( function (word, line, startpos, endpos) -- Helper function registering possible completion words, verifying matches. local matches = {} local function add(value) value = tostring(value) if value:match("^" .. word) then matches[#matches + 1] = value end end -- This function is called in a context where a keyword or a global -- variable can be inserted. Local variables cannot be listed! local function add_globals() for _, k in ipairs(keywords) do add(k) end for k in pairs(_G) do add(k) end end -- Main completion function. It evaluates the current sub-expression -- to determine its type. Currently supports tables fields, global -- variables and function prototype completion. local function contextual_list(expr, sep, str) if str then return end if expr and expr ~= "" then local v = load("return " .. expr) if v then v = v() local t = luatype(v) if sep == '.' or sep == ':' then if t == 'table' then for k, v in pairs(v) do if luatype(k) == 'string' and (sep ~= ':' or luatype(v) == "function") then add(k) end end end if getmetatable(v) then local aux = v repeat local mt = getmetatable(aux) local idx = get_index(mt) if idx and luatype(idx) == 'table' then for k,v in pairs(idx) do add(k) end end if rawequal(aux,idx) then break end -- avoid infinite loops aux = idx until not aux or not getmetatable(aux) end elseif sep == '[' then if t == 'table' then for k in pairs(v) do if luatype(k) == 'number' then add(k .. "]") end end if word ~= "" then add_globals() end end end end end if #matches == 0 then add_globals() end end -- This complex function tries to simplify the input line, by removing -- literal strings, full table constructors and balanced groups of -- parentheses. Returns the sub-expression preceding the word, the -- separator item ( '.', ':', '[', '(' ) and the current string in case -- of an unfinished string literal. local function simplify_expression(expr) -- Replace annoying sequences \' and \" inside literal strings expr = expr:gsub("\\(['\"])", function (c) return string.format("\\%03d", string.byte(c)) end) local curstring -- Remove (finished and unfinished) literal strings while true do local idx1, _, equals = expr:find("%[(=*)%[") local idx2, _, sign = expr:find("(['\"])") if idx1 == nil and idx2 == nil then break end local idx, startpat, endpat if (idx1 or math.huge) < (idx2 or math.huge) then -- equals = escape(equals) idx, startpat, endpat = idx1, "%[" .. equals .. "%[", "%]" .. equals .. "%]" else -- sign = escape(sign) idx, startpat, endpat = idx2, sign, sign end if expr:sub(idx):find("^" .. startpat .. ".-" .. endpat) then expr = expr:gsub(startpat .. "(.-)" .. endpat, " STRING ") else expr = expr:gsub(startpat .. "(.*)", function (str) curstring = str return "(CURSTRING " end) end end expr = expr:gsub("%b()"," PAREN ") -- Remove groups of parentheses expr = expr:gsub("%b{}"," TABLE ") -- Remove table constructors -- Avoid two consecutive words without operator expr = expr:gsub("(%w)%s+(%w)","%1|%2") expr = expr:gsub("%s+", "") -- Remove now useless spaces -- This main regular expression looks for table indexes and function calls. return curstring, expr:match("([%.%w%[%]_]-)([:%.%[%(])" .. word .. "$") end -- Now call the processing functions and return the list of results. local str, expr, sep = simplify_expression(line:sub(1, endpos)) contextual_list(expr, sep, str) return matches end ) april-ann-0.4.1/packages/misc/rlcompleter/package.lua000066400000000000000000000015141263004425400225350ustar00rootroot00000000000000package{ name = "rlcompleter", version = "1.0", depends = { "util" }, keywords = { "rlcompleter" }, description = "manages autocompletion", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", provide_bind{ file = "binding/bind_rlcompleter.lua.cc", dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp = true, build_bind{ file = "binding/bind_rlcompleter.lua.cc", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/misc/tar/000077500000000000000000000000001263004425400166745ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/tar/binding/000077500000000000000000000000001263004425400203065ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/tar/binding/bind_tar.lua.cc000066400000000000000000000033451263004425400231640ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "bind_april_io.h" #include "stream.h" using namespace AprilIO; //BIND_END //BIND_HEADER_H #include "tar_package.h" #include "tarfile_stream.h" using namespace TAR; //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME StreamInterface aprilio.stream //BIND_LUACLASSNAME TARFileStream tar.stream //BIND_CPP_CLASS TARFileStream //BIND_SUBCLASS_OF TARFileStream StreamInterface //BIND_CONSTRUCTOR TARFileStream { LUABIND_ERROR("Use open method of a tar.package instance"); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME ArchivePackage aprilio.package //BIND_LUACLASSNAME TARPackage tar.package //BIND_CPP_CLASS TARPackage //BIND_SUBCLASS_OF TARPackage ArchivePackage //BIND_CONSTRUCTOR TARPackage { LUABIND_INCREASE_NUM_RETURNS(callArchivePackageConstructor(L)); } //BIND_END april-ann-0.4.1/packages/misc/tar/c_src/000077500000000000000000000000001263004425400177655ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/tar/c_src/tar_package.cc000066400000000000000000000155471263004425400225510ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ extern "C" { #include #include } #include #include "april_assert.h" #include "file_stream.h" #include "tarfile_stream.h" #include "tar_package.h" #include "unused_variable.h" using AprilIO::FileStream; using AprilIO::HandledStreamInterface; using AprilIO::StreamInterface; using AprilUtils::constString; using AprilUtils::string; namespace TAR { TARPackage::TARPackage(const char *path, const char *mode) : ArchivePackage() { constString mode_cstr(mode); if (mode_cstr != "r") { ERROR_EXIT(128, "TARPackage only can open files for reading"); } tar_file = new FileStream(path, mode); init(); } TARPackage::TARPackage(int fd) : ArchivePackage() { openFileDescriptor(fd); init(); } TARPackage::TARPackage(StreamInterface *stream, bool reopen) : ArchivePackage() { if (reopen) { HandledStreamInterface *handled_stream = dynamic_cast(stream); if (handled_stream == 0) { ERROR_EXIT(128, "Impossible to reopen the given stream\n"); } else { openFileDescriptor(handled_stream->fileno()); } } else { tar_file = stream; } init(); } TARPackage::~TARPackage() { close(); } bool TARPackage::good() const { return !tar_file.empty() && !hasError(); } void TARPackage::close() { is_closed = true; tryClose(); } void TARPackage::init() { size_t BLOCK_SIZE = 512; char block[BLOCK_SIZE+1]; num_open_files = 0; is_closed = false; // reads the header from the TAR stream off_t p = tar_file->seek(SEEK_SET, 0); while(true) { size_t nbytes = tar_file->get(block, BLOCK_SIZE); constString block_str(block, BLOCK_SIZE); if (nbytes == 0 || !AprilUtils::strncchr(block, '\0', BLOCK_SIZE)) break; Header header; decode(block, BLOCK_SIZE, header); if (header.typeflag == 0) { FileInfo info(header.pathname, tar_file->seek(), header.size); name2index[string(header.pathname)] = list.size(); list.push_back(info); } p = tar_file->seek(SEEK_CUR, static_cast(BLOCK_SIZE * ceilf(static_cast(header.size)/BLOCK_SIZE))); if (p<0) { ERROR_EXIT1(128, "%s\n", tar_file->getErrorMsg()); } } } size_t TARPackage::getNumberOfFiles() { april_assert(!tar_file.empty()); return list.size(); } const char *TARPackage::getNameOf(size_t idx) { if (idx >= getNumberOfFiles()) return 0; return list[idx].pathname; } void TARPackage::openFileDescriptor(int fd) { int flags = fcntl(fd, F_GETFL); if (flags & O_WRONLY || flags & O_RDWR) { ERROR_EXIT(128, "TARPackage is only for read-only\n"); } else { tar_file = new FileStream(fd); } } bool TARPackage::hasError() const { return tar_file->hasError(); } const char *TARPackage::getErrorMsg() { return tar_file->getErrorMsg(); } StreamInterface *TARPackage::openFile(const char *name, int flags) { april_assert(!tar_file.empty()); size_t *index = name2index.find(name); // TODO make an error code if (index == 0) return 0; return openFile(*index, flags); } StreamInterface *TARPackage::openFile(size_t idx, int flags) { UNUSED_VARIABLE(flags); april_assert(!tar_file.empty()); // TODO: make an error code if (idx >= getNumberOfFiles()) return 0; FileInfo &info = list[idx]; TARFileStream *file = new TARFileStream(this, tar_file.get(), info.offset, info.size); return file; } void TARPackage::incOpenFilesCounter() { ++num_open_files; } void TARPackage::decOpenFilesCounter() { --num_open_files; if (is_closed) tryClose(); } void TARPackage::tryClose() { if (num_open_files == 0 && !tar_file.empty()) { tar_file->close(); tar_file.reset(); } } static size_t octal(char *data, size_t length) { size_t len = strnlen(data, length); size_t base = 1; size_t num = 0; for (size_t i=len; i>0; --i) { num = num + ( data[i-1] - 48 ) * base; base = base << 3; // multiply by 8 } return num; } void TARPackage::decode(const char *block, size_t block_size, Header &header) { UNUSED_VARIABLE(block_size); // sanity check april_assert(sizeof(Header) - 9*sizeof(size_t) - sizeof(header.pathname) <= block_size); size_t pos=0; // #define READ_HEADER_FIELD(field) do { \ april_assert(pos + sizeof(header.field) <= block_size); \ memcpy(header.field, block+pos, sizeof(header.field)); \ pos+=sizeof(header.field); \ } while(false) // READ_HEADER_FIELD(name); READ_HEADER_FIELD(octal_mode); READ_HEADER_FIELD(octal_uid); READ_HEADER_FIELD(octal_gid); READ_HEADER_FIELD(octal_size); READ_HEADER_FIELD(octal_mtime); READ_HEADER_FIELD(octal_chksum); READ_HEADER_FIELD(octal_typeflag); READ_HEADER_FIELD(linkname); READ_HEADER_FIELD(magic); READ_HEADER_FIELD(version); READ_HEADER_FIELD(uname); READ_HEADER_FIELD(gname); READ_HEADER_FIELD(octal_devmajor); READ_HEADER_FIELD(octal_devminor); READ_HEADER_FIELD(prefix); // #undef READ_HEADER_FIELD april_assert(pos <= block_size); // convert octal values // #define OCTAL(field) \ header.field = octal(header.octal_##field, sizeof(header.octal_##field)) // OCTAL(mode); OCTAL(uid); OCTAL(gid); OCTAL(size); OCTAL(mtime); OCTAL(chksum); OCTAL(typeflag); OCTAL(devmajor); OCTAL(devminor); // #undef OCTAL header.pathname[0] = '\0'; if (header.prefix[0] != '\0') { strncpy(header.pathname, header.prefix, sizeof(header.prefix)); header.pathname[sizeof(header.prefix)] = '\0'; strncat(header.pathname, "/", 1u); } strncat(header.pathname, header.name, sizeof(header.name)); } } // namespace TAR april-ann-0.4.1/packages/misc/tar/c_src/tar_package.h000066400000000000000000000066741263004425400224140ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef TAR_PACKAGE_H #define TAR_PACKAGE_H #include "archive_package.h" #include "handled_stream.h" #include "hash_table.h" #include "mystring.h" #include "referenced.h" #include "smart_ptr.h" #include "stream.h" #include "vector.h" /// Read of TAR files. namespace TAR { // forward declaration class TARFileStream; class TARPackage : public AprilIO::ArchivePackage { friend class TARFileStream; public: TARPackage(const char *path, const char *mode); TARPackage(int fd); TARPackage(AprilIO::StreamInterface *stream, bool reopen=false); virtual ~TARPackage(); virtual bool good() const; virtual bool hasError() const; virtual const char *getErrorMsg(); virtual void close(); virtual size_t getNumberOfFiles(); virtual const char *getNameOf(size_t idx); virtual AprilIO::StreamInterface *openFile(const char *name, int flags); virtual AprilIO::StreamInterface *openFile(size_t idx, int flags); private: /// The position and size of the file inside the package. struct FileInfo { AprilUtils::string pathname; ///< The filename. size_t offset; ///< Offset from package stream begin. size_t size; ///< Size of the file. FileInfo() { } FileInfo(const char *name, size_t off, size_t s) : pathname(name), offset(off), size(s) { } }; /// Header of each file inside the TAR package struct Header { char name[100]; char octal_mode[8]; // octal char octal_uid[8]; // octal char octal_gid[8]; // octal char octal_size[12]; // octal char octal_mtime[12]; // octal char octal_chksum[8]; // octal char octal_typeflag[1]; // octal char linkname[100]; char magic[6]; char version[2]; char uname[32]; char gname[32]; char octal_devmajor[8]; // octal char octal_devminor[8]; // octal char prefix[155]; // size_t mode, uid, gid, size, mtime, chksum, typeflag, devmajor, devminor; // derived field char pathname[260]; }; typedef AprilUtils::hash Name2IndexHash; typedef AprilUtils::vector FileInfoList; Name2IndexHash name2index; FileInfoList list; AprilUtils::SharedPtr tar_file; int num_open_files; bool is_closed; void init(); void openFileDescriptor(int fd); void incOpenFilesCounter(); void decOpenFilesCounter(); void tryClose(); void decode(const char *block, size_t block_size, Header &header); }; } // namespace TAR #endif // TAR_PACKAGE_H april-ann-0.4.1/packages/misc/tar/c_src/tarfile_stream.cc000066400000000000000000000064421263004425400233030ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "maxmin.h" #include "tarfile_stream.h" namespace TAR { TARFileStream::TARFileStream(TARPackage *cpp_tar_package, StreamInterface *tar_file, size_t offset, size_t size) : cpp_tar_package(cpp_tar_package), tar_file(tar_file), offset(offset), size(size), pos(0) { cpp_tar_package->incOpenFilesCounter(); } TARFileStream::~TARFileStream() { close(); } bool TARFileStream::isOpened() const { return !tar_file.empty(); } void TARFileStream::close() { // TODO: check errors if (!tar_file.empty()) { tar_file.reset(); cpp_tar_package->decOpenFilesCounter(); } } void TARFileStream::flush() { // nothing to do } int TARFileStream::setvbuf(int mode, size_t size) { // nothing to do UNUSED_VARIABLE(mode); UNUSED_VARIABLE(size); return 0; } bool TARFileStream::hasError() const { // TODO: check errors return false; } const char *TARFileStream::getErrorMsg() const { return StreamInterface::NO_ERROR_STRING; } bool TARFileStream::privateEof() const { return static_cast(pos) >= size; } size_t TARFileStream::privateWrite(const char *buf, size_t size) { UNUSED_VARIABLE(buf); UNUSED_VARIABLE(size); ERROR_EXIT(128, "Read only stream\n"); return 0; } size_t TARFileStream::privateRead(char *buf, size_t max_size) { if (pos >= size) return 0; tar_file->seek(SEEK_SET, offset + pos); max_size = AprilUtils::min(max_size, size - pos); size_t nbytes = tar_file->get(buf, max_size); pos += nbytes; return nbytes; } off_t TARFileStream::privateSeek(int whence, long offset) { off_t final; if (whence == SEEK_CUR && offset == 0) { return this->pos; } else { switch(whence) { case SEEK_CUR: final = tar_file->seek(SEEK_SET, this->offset + this->pos + offset) - this->offset; break; case SEEK_SET: final = tar_file->seek(SEEK_SET, this->offset + offset) - this->offset; break; case SEEK_END: final = tar_file->seek(SEEK_SET, this->offset + this->size - 1 + offset) - this->offset; break; default: final=0; // avoid compiler warnings ERROR_EXIT(128, "Unknown whence value\n"); } if (final < 0) final = 0; else if (static_cast(final) > this->size) final = this->size; this->pos = final; return final; } } } // namespace TAR april-ann-0.4.1/packages/misc/tar/c_src/tarfile_stream.h000066400000000000000000000036461263004425400231500ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef BUFFERED_TARFILE_H #define BUFFERED_TARFILE_H #include #include "buffered_stream.h" #include "error_print.h" #include "smart_ptr.h" #include "unused_variable.h" #include "tar_package.h" namespace TAR { class TARFileStream : public AprilIO::BufferedInputStream { friend class TARPackage; public: virtual ~TARFileStream(); virtual bool isOpened() const; virtual void close(); virtual void flush(); virtual int setvbuf(int mode, size_t size); virtual bool hasError() const; virtual const char *getErrorMsg() const; protected: virtual bool privateEof() const; virtual size_t privateWrite(const char *buf, size_t size); virtual size_t privateRead(char *buf, size_t max_size); virtual off_t privateSeek(int whence, long offset); private: AprilUtils::SharedPtr cpp_tar_package; AprilUtils::SharedPtr tar_file; size_t offset, size, pos; TARFileStream(TARPackage *cpp_tar_package, StreamInterface *tar_file, size_t offset, size_t size); }; } #endif // BUFFERED_TARFILE_H april-ann-0.4.1/packages/misc/tar/lua_src/000077500000000000000000000000001263004425400203245ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/tar/lua_src/tar.lua000066400000000000000000000233431263004425400216220ustar00rootroot00000000000000tar = tar or {} tar.open = function(...) return tar.package(...) end aprilio.register_open_by_extension("tar", tar.open) -- OLD VERSION OF TAR PACKAGE -- ----------------------------------------------------------------------------- -- -- tar - Lua Tape ARchive module -- -- -- -- Code for managing tar files -- -- -- -- Version 0.1 (21 AUG 2007) -- -- -- -- Author: Judge Maygarden (jmaygarden@computer.org) -- -- -- -- Copyright (c) 2007 Judge Maygarden -- ----------------------------------------------------------------------------- -- local public = {} -- local private = {} -- local TarFile = {} -- local TarInternalFile = {} -- -- tar = public -- TarFile.__index = TarFile -- TarInternalFile.__index = TarInternalFile -- ----------------------------------------------------------------------------- -- -- Closes file -- ----------------------------------------------------------------------------- -- function TarInternalFile:close() -- end -- ----------------------------------------------------------------------------- -- -- UNSUPPORTED: Saves any written data to file -- ----------------------------------------------------------------------------- -- function TarInternalFile:flush() -- error('Tar file output flushing is unsupported.') -- end -- ----------------------------------------------------------------------------- -- -- Returns an iterator function that returns a new line from the file -- -- @return String repressenting a line from the file without the newline -- ----------------------------------------------------------------------------- -- function TarInternalFile:lines() -- return function(s, var) -- return self:read("*l") -- end, self, nil -- end -- ----------------------------------------------------------------------------- -- -- Reads the file according to the given formats as follows: -- -- "*n": reads a number -- -- "*a": reads the whole file -- -- "*l" reads the next line -- -- number: reads a string with up to this number of characters -- -- @param variadic list of formats (default "*l") -- -- @return list of strings (or numbers) or nil if end of file or format error -- ----------------------------------------------------------------------------- -- function TarInternalFile:read(...) -- local eof = self.offset + self.size -- if self.pointer >= eof then return nil end -- eof -- local t = {} -- self.archive.file:seek("set", self.pointer) -- for i, v in ipairs{...} do -- local s -- if "*a" == v then -- s = self.archive.file:read(eof - self.pointer) -- elseif "*l" == v or "*n" == v or "number" == type(v) then -- s = self.archive.file:read(v) -- else -- error('bad argument %d to %s (%s)', i -- 'TarInternalFile:read', 'invalid format') -- return nil -- end -- local last = self.pointer -- self.pointer = self.archive.file:seek() -- if s and self.pointer < eof then -- table.insert(t, s) -- elseif s then -- table.insert(t, string.sub(s, 1, eof - last - 1)) -- self.pointer = self.offset + self.size -- break -- else -- break -- end -- end -- return table.unpack(t) -- end -- ----------------------------------------------------------------------------- -- -- Sets and gets the file position measured from the given base as follows: -- -- "set": base is position 0 (beginning of the file) -- -- "cur": base is current position -- -- "end": base is end of file -- -- @param base position (default "cur") -- -- @param offset in bytes (default 0) -- -- @return final position -- ----------------------------------------------------------------------------- -- function TarInternalFile:seek(whence, offset) -- local whence = whence or "cur" -- local offset = offset or 0 -- local eof = self.offset + self.size -- local final -- local err -- if "cur" == whence then -- final, err = self.archive.file:seek("set", -- offset + self.pointer) - self.offset -- elseif "set" == whence then -- final, err = self.archive.file:seek("set", -- offset + self.offset) - self.offset -- elseif "end" == whence then -- final, err = self.archive.file:seek("set", -- offset + eof - 1) - self.offset -- else -- final, err = self.archive.file:seek(whence, offset) -- end -- if not final then -- return nil, err -- elseif final < 0 then -- final = 0 -- elseif final > self.size then -- final = self.size -- end -- self.pointer = final + self.offset -- return final -- end -- ----------------------------------------------------------------------------- -- -- UNSUPPORTED: Sets the buffering mode for an output file -- -- @param "no" - no buffering, "full" - full buffering, "line" - line buffering -- -- @param size of the buffer for "full" and "line" modes -- ----------------------------------------------------------------------------- -- function TarInternalFile:setvbuf(mode, size) -- error('Tar file output buffering is unsupported.') -- end -- ----------------------------------------------------------------------------- -- -- UNSUPPORTED: Writes the value of each of its arguments to the file -- -- @param string or numbers values only -- ----------------------------------------------------------------------------- -- function TarInternalFile:write(...) -- error('Tar file writes are unsupported.') -- end -- ----------------------------------------------------------------------------- -- -- Opens a file inside the tar file archive -- -- @param pathname of a file inside the tar file -- -- @return file handle or nil if the file is not found -- ----------------------------------------------------------------------------- -- function TarFile:open(filename) -- if not self.list[filename] then return nil end -- local file = {} -- file.archive = self -- file.filename = filename -- file.offset = self.list[filename].offset -- file.pointer = file.offset -- file.size = self.list[filename].size -- setmetatable(file, TarInternalFile) -- return file -- end -- ----------------------------------------------------------------------------- -- -- Returns an iterator over all files in the tar archive -- -- @return interator function, tar file handle -- ----------------------------------------------------------------------------- -- function TarFile:files() -- return next, self.list, nil -- end -- ----------------------------------------------------------------------------- -- -- Data for parsing tar header fields -- ----------------------------------------------------------------------------- -- private.HEADER_DATA = { -- -- { field, offset, size, octal } -- { "name", 0, 100 }, -- { "mode", 100, 8, true }, -- { "uid", 108, 8, true }, -- { "gid", 116, 8, true }, -- { "size", 124, 12, true }, -- { "mtime", 136, 12, true }, -- { "chksum", 148, 8, true }, -- { "typeflag", 156, 1, true }, -- { "linkname", 157, 100 }, -- { "magic", 257, 6 }, -- { "version", 263, 2 }, -- { "uname", 265, 32 }, -- { "gname", 297, 32 }, -- { "devmajor", 329, 8, true }, -- { "devminor", 337, 8, true }, -- { "prefix", 345, 155 }, -- } -- ----------------------------------------------------------------------------- -- -- Converts an octal string into a number -- -- @param string of octal digits -- -- @return number or nil if an invalid string was passed -- ----------------------------------------------------------------------------- -- private.octal = function(s) -- if string.match(s, "[^0-7]") then return nil end -- local n, m = 0, 0 -- for i = string.len(s), 1, -1 do -- n = n + (string.byte(s, i) - 48) * 8 ^ m -- m = m + 1 -- end -- return n -- end -- ----------------------------------------------------------------------------- -- -- Decodes a tar file header -- -- @param 512-byte string containing a tar file header block -- -- @return table containg the header fields -- ----------------------------------------------------------------------------- -- private.decode = function(header) -- local t = {} -- for _, field in ipairs(private.HEADER_DATA) do -- local s = string.sub(header, field[2] + 1, field[2] + field[3]) -- local s = string.match(s, "[^%z]*") -- if field[4] then -- t[field[1]] = private.octal(s) -- else -- t[field[1]] = s -- end -- end -- if 0 < string.len(t.prefix) then -- t.pathname = t.prefix..'/'..t.name -- else -- t.pathname = t.name -- end -- return t -- end -- ----------------------------------------------------------------------------- -- -- Opens a tar archive by attaching to the provided Lua file handle. -- -- Ownership of the file handle is transferred to the returned table and -- -- should no longer be referenced by the user. -- -- @param open file handle -- -- @return tar file handle -- ----------------------------------------------------------------------------- -- public.open = function(file) -- assert(file, 'invalid file handle') -- local archive = {} -- archive.file = file -- archive.list = {} -- local p = assert( file:seek("set") ) -- while true do -- local block = file:read(512) -- if not block or not string.match(block, "[^%z]") then break end -- local header = private.decode(block) -- if 0 == header.typeflag then -- archive.list[header.pathname] = { -- ["offset"] = file:seek(), -- ["size"] = header.size -- } -- end -- local p = assert( file:seek("cur", 512 * math.ceil(header.size / 512)) ) -- end -- setmetatable(archive, TarFile) -- return archive -- end -- -- aprilio.register_open_by_extension("tar", -- -- function(name, mode) -- -- assert(not mode or mode == "r", -- -- "invalid open mode, tar only allows 'r'") -- -- return public.open(aprilio.lua_open(name, mode)) -- -- end) april-ann-0.4.1/packages/misc/tar/package.lua000066400000000000000000000022211263004425400207670ustar00rootroot00000000000000 package{ name = "tar", version = "1.0", depends = { "util", "aprilio" }, keywords = { "tar" }, description = "read tar files", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, -- target{ -- name = "test", -- lua_unit_test{ -- file={ -- "test/test.lua", -- }, -- }, -- }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_tar.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_tar.lua.cc", dest_dir = "build", } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/misc/zip/000077500000000000000000000000001263004425400167105ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/zip/binding/000077500000000000000000000000001263004425400203225ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/zip/binding/bind_zip.lua.cc000066400000000000000000000040431263004425400232100ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "bind_april_io.h" #include "stream.h" using namespace AprilIO; //BIND_END //BIND_HEADER_H #include "zip_package.h" #include "zipfile_stream.h" using namespace ZIP; //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_ENUM_CONSTANT zip.flags.NOCASE ZIP_FL_NOCASE //BIND_ENUM_CONSTANT zip.flags.NODIR ZIP_FL_NODIR //BIND_ENUM_CONSTANT zip.flags.COMPRESSED ZIP_FL_COMPRESSED //BIND_ENUM_CONSTANT zip.flags.UNCHANGED ZIP_FL_UNCHANGED ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME StreamInterface aprilio.stream //BIND_LUACLASSNAME ZIPFileStream zip.stream //BIND_CPP_CLASS ZIPFileStream //BIND_SUBCLASS_OF ZIPFileStream StreamInterface //BIND_CONSTRUCTOR ZIPFileStream { LUABIND_ERROR("Use open method of a zip.package instance"); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME ArchivePackage aprilio.package //BIND_LUACLASSNAME ZIPPackage zip.package //BIND_CPP_CLASS ZIPPackage //BIND_SUBCLASS_OF ZIPPackage ArchivePackage //BIND_CONSTRUCTOR ZIPPackage { LUABIND_INCREASE_NUM_RETURNS(callArchivePackageConstructor(L)); } //BIND_END april-ann-0.4.1/packages/misc/zip/c_src/000077500000000000000000000000001263004425400200015ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/zip/c_src/zip_package.cc000066400000000000000000000122021263004425400225620ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ extern "C" { #include #include } #include #include "april_assert.h" #include "zipfile_stream.h" #include "zip_package.h" using AprilIO::HandledStreamInterface; using AprilIO::StreamInterface; using AprilUtils::constString; namespace ZIP { const size_t ZIPPackage::ERROR_BUFFER_SIZE = 1024; ZIPPackage::ZIPPackage(const char *path, const char *mode) : ArchivePackage() { constString mode_cstr(mode); int flags; init(); if (mode_cstr.empty() || mode_cstr == "r") { flags = 0; } else if (mode_cstr == "r+") { flags = 0; } else if (mode_cstr == "w") { flags = ZIP_CREATE; // | ZIP_TRUNCATE; } else if (mode_cstr == "w+") { flags = ZIP_CREATE; // | ZIP_TRUNCATE; } else { flags = 0; ERROR_EXIT1(128, "Unknown given mode string '%s'\n", mode); } zip_package = zip_open(path, flags | ZIP_CHECKCONS, &zerr); serr = errno; } ZIPPackage::ZIPPackage(int fd) : ArchivePackage() { init(); openFileDescriptor(fd); } ZIPPackage::ZIPPackage(HandledStreamInterface *handled_stream) : ArchivePackage() { init(); openFileDescriptor(handled_stream->fileno()); } ZIPPackage::ZIPPackage(StreamInterface *stream) : ArchivePackage() { init(); HandledStreamInterface *handled_stream = dynamic_cast(stream); if (handled_stream == 0) zerr = ZIP_ER_OPEN; else openFileDescriptor(handled_stream->fileno()); } ZIPPackage::~ZIPPackage() { close(); } bool ZIPPackage::good() const { return zip_package != 0 && !hasError(); } void ZIPPackage::close() { is_closed = true; tryClose(); } void ZIPPackage::init() { zerr = 0; serr = 0; zip_package = 0; error_buffer = new char[ERROR_BUFFER_SIZE+1]; num_open_files = 0; is_closed = false; } size_t ZIPPackage::getNumberOfFiles() { april_assert(zip_package != 0); return static_cast(zip_get_num_entries(zip_package,0)); } const char *ZIPPackage::getNameOf(size_t idx) { struct zip_stat sb; ::zip_stat_index(zip_package, static_cast(idx), 0, &sb); if (sb.valid & ZIP_STAT_NAME) { return sb.name; } else { return 0; } } void ZIPPackage::openFileDescriptor(int fd) { int flags = fcntl(fd, F_GETFL); if (flags & O_WRONLY || flags & O_RDWR) { zerr = ZIP_ER_INVAL; } else { int dup_fd = dup(fd); zip_package = zip_fdopen(dup_fd, ZIP_CHECKCONS, &zerr); serr = errno; } } bool ZIPPackage::hasError() const { return zerr != 0; } const char *ZIPPackage::getErrorMsg() { zip_error_to_str(error_buffer.get(), ERROR_BUFFER_SIZE, zerr, serr); return error_buffer.get(); } StreamInterface *ZIPPackage::openFile(const char *name, int flags) { april_assert(zip_package != 0); struct zip_stat sb; ::zip_stat(zip_package, name, 0, &sb); if (sb.valid & ZIP_STAT_SIZE) { size_t size = sb.size; zip_file *file = checkReturnedValue(zip_fopen(zip_package, name, flags)); if (file == 0) return 0; return new ZIPFileStream(this, file, size); } else { return 0; } } StreamInterface *ZIPPackage::openFile(size_t idx, int flags) { april_assert(zip_package != 0); struct zip_stat sb; ::zip_stat_index(zip_package, static_cast(idx), 0, &sb); if (sb.valid & ZIP_STAT_SIZE) { size_t size = sb.size; zip_file *file = checkReturnedValue(zip_fopen_index(zip_package, static_cast(idx), flags)); if (file == 0) return 0; return new ZIPFileStream(this, file, size); } else { return 0; } } template T ZIPPackage::checkReturnedValue(T code) { april_assert(zip_package != 0); if (code != 0) { zip_error_get(zip_package, &zerr, &serr); } return code; } void ZIPPackage::incOpenFilesCounter() { ++num_open_files; } void ZIPPackage::decOpenFilesCounter() { --num_open_files; if (is_closed) tryClose(); } void ZIPPackage::tryClose() { if (num_open_files == 0 && zip_package != 0) { checkReturnedValue(zip_close(zip_package)); zip_package = 0; } } } // namespace ZIP april-ann-0.4.1/packages/misc/zip/c_src/zip_package.h000066400000000000000000000043531263004425400224340ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef ZIP_PACKAGE_H #define ZIP_PACKAGE_H extern "C" { #include } #include "archive_package.h" #include "handled_stream.h" #include "referenced.h" #include "smart_ptr.h" #include "stream.h" /// Read of ZIP files. namespace ZIP { // forward declaration class ZIPFileStream; class ZIPPackage : public AprilIO::ArchivePackage { friend class ZIPFileStream; public: ZIPPackage(const char *path, const char *mode); ZIPPackage(int fd); ZIPPackage(AprilIO::HandledStreamInterface *stream); ZIPPackage(AprilIO::StreamInterface *stream); virtual ~ZIPPackage(); virtual bool good() const; virtual bool hasError() const; virtual const char *getErrorMsg(); virtual void close(); virtual size_t getNumberOfFiles(); virtual const char *getNameOf(size_t idx); virtual AprilIO::StreamInterface *openFile(const char *name, int flags); virtual AprilIO::StreamInterface *openFile(size_t idx, int flags); private: zip *zip_package; int zerr, serr; static const size_t ERROR_BUFFER_SIZE; AprilUtils::UniquePtr error_buffer; int num_open_files; bool is_closed; void init(); void openFileDescriptor(int fd); template T checkReturnedValue(T code); void incOpenFilesCounter(); void decOpenFilesCounter(); void tryClose(); }; } // namespace ZIP #endif // ZIP_PACKAGE_H april-ann-0.4.1/packages/misc/zip/c_src/zipfile_stream.cc000066400000000000000000000050751263004425400233340ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "zipfile_stream.h" namespace ZIP { ZIPFileStream::ZIPFileStream(ZIPPackage *cpp_zip_package, zip_file *file, size_t size) : cpp_zip_package(cpp_zip_package), file(file), size(size), pos(0) { cpp_zip_package->incOpenFilesCounter(); } ZIPFileStream::~ZIPFileStream() { close(); } bool ZIPFileStream::isOpened() const { return file != 0; } void ZIPFileStream::close() { // TODO: check errors if (file != 0) { zip_fclose(file); file = 0; cpp_zip_package->decOpenFilesCounter(); } } void ZIPFileStream::flush() { // nothing to do } int ZIPFileStream::setvbuf(int mode, size_t size) { // nothing to do UNUSED_VARIABLE(mode); UNUSED_VARIABLE(size); return 0; } bool ZIPFileStream::hasError() const { // TODO: check errors return false; } const char *ZIPFileStream::getErrorMsg() const { return StreamInterface::NO_ERROR_STRING; } bool ZIPFileStream::privateEof() const { return static_cast(pos) >= size; } size_t ZIPFileStream::privateWrite(const char *buf, size_t size) { UNUSED_VARIABLE(buf); UNUSED_VARIABLE(size); ERROR_EXIT(128, "Read only stream\n"); return 0; } size_t ZIPFileStream::privateRead(char *buf, size_t max_size) { int nbytes = zip_fread(file, buf, max_size); if (nbytes < 0) { // TODO: check errors } else { pos += nbytes; } return static_cast(nbytes); } off_t ZIPFileStream::privateSeek(int whence, long offset) { if (whence == SEEK_CUR && offset == 0) { return pos; } else { ERROR_EXIT(128, "Unable to seek\n"); } return 0; } } // namespace ZIP april-ann-0.4.1/packages/misc/zip/c_src/zipfile_stream.h000066400000000000000000000035701263004425400231740ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef BUFFERED_ZIPFILE_H #define BUFFERED_ZIPFILE_H extern "C" { #include } #include #include "buffered_stream.h" #include "error_print.h" #include "smart_ptr.h" #include "unused_variable.h" #include "zip_package.h" namespace ZIP { class ZIPFileStream : public AprilIO::BufferedInputStream { friend class ZIPPackage; public: virtual ~ZIPFileStream(); virtual bool isOpened() const; virtual void close(); virtual void flush(); virtual int setvbuf(int mode, size_t size); virtual bool hasError() const; virtual const char *getErrorMsg() const; protected: virtual bool privateEof() const; virtual size_t privateWrite(const char *buf, size_t size); virtual size_t privateRead(char *buf, size_t max_size); virtual off_t privateSeek(int whence, long offset); private: AprilUtils::SharedPtr cpp_zip_package; zip_file *file; size_t size; off_t pos; ZIPFileStream(ZIPPackage *cpp_zip_package, zip_file *file, size_t size); }; } #endif // BUFFERED_ZIPFILE_H april-ann-0.4.1/packages/misc/zip/lua_src/000077500000000000000000000000001263004425400203405ustar00rootroot00000000000000april-ann-0.4.1/packages/misc/zip/lua_src/zip.lua000066400000000000000000000002611263004425400216440ustar00rootroot00000000000000zip = zip or {} zip.open = function(...) return zip.package(...) end aprilio.register_open_by_extension("zip", zip.open) aprilio.register_open_by_extension("ZIP", zip.open) april-ann-0.4.1/packages/misc/zip/package.lua000066400000000000000000000022441263004425400210100ustar00rootroot00000000000000 package{ name = "zip", version = "1.0", depends = { "util", "aprilio" }, pkgconfig_depends = { "libzip" }, keywords = { "zip" }, description = "read and write zip files", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test.lua", }, }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_zip.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_zip.lua.cc", dest_dir = "build", } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/mutual_information/000077500000000000000000000000001263004425400210675ustar00rootroot00000000000000april-ann-0.4.1/packages/mutual_information/lua_src/000077500000000000000000000000001263004425400225175ustar00rootroot00000000000000april-ann-0.4.1/packages/mutual_information/lua_src/mutual_information.lua000066400000000000000000000103361263004425400271410ustar00rootroot00000000000000stats = stats or {} stats.MI = stats.MI or {} local LEVELS = 256 local EPSILON = 1e-03 -- extracts the histogram from the matrix, using the image package local function get_histogram_from_matrix(m, levels) assert(m, "A matrix is needed") -- the matrix is adjusted to be between 0 and 1, and rewrap to fit a image of -- only one row local maux = m:clone():adjust_range(0.0, 1.0):rewrap(1, m:size()) local h = image.image_histogram.get_histogram(Image(maux), levels or LEVELS) -- sanity check assert(math.abs(h:sum() - 1) < EPSILON, "The image_histogram hasn't got bin probabilities") return h end stats.MI.entropy = april_doc{ class = "function", summary = "Computes the entropy of a given matrix or histogram", description = { "Computes the entropy of a given matrix or histogram.", "The two arguments are optional, but one of them must be", "present.", "If the matrix is given (and not the histogram),", "the entropy is computed interpreting the matrix data", "as a continuum sequence of data points, making i.i.d.", "assumptions.", }, params = { "A matrix [optional], ignored if given a histogram", "A histogram matrix [optional]", "The number of histogram bins [optional], by default 256", }, outputs = { "The entropy in base 2" }, } .. -- computes the entropy given a matrix or a histogram function(m, histogram, levels) assert(not histogram or histogram:is_contiguous(), "Histogram must be contiguous matrix") if histogram then if m ~= nil then fprintf(io.stderr,"If a histogram is given, the matrix will be ignored\n") end -- we don't know if the histogram has probabilities or raw counts local s = histogram:sum() if s~=1.0 then histogram:scal(1/s) end end local histogram = histogram or get_histogram_from_matrix(m, levels) -- the entropy is computed as -sum_i[ p_i * log_2(p_i) ] return -histogram:clone():plogp():sum()/math.log(2) end stats.MI.mutual_information = april_doc{ class = "function", summary = "Computes the Mutual Information between two matrices", description = { "Computes the Mutual Information between two matrices.", "The two matrices must have the same size. The MI is", "computed interpreting the matrix data as a continuum", "sequence of data points, making i.i.d. assumptions.", }, params = { "A matrix", "Another matrix", "The number of histogram bins [optional], by default 256", }, outputs = { "The Mutual Information between given matrices", "The Normalized Mutual Information between given matrices", }, } .. -- this function computes the mutual information between two matrices of the -- same size function(m1, m2, levels) local levels = levels or LEVELS assert(m1:size() == m2:size(), "Two matrices must be of the same size") -- the matrices are first adjusted to be between 0.0 and levels-1, and -- re-wrapped to be a vector local m1 = m1:clone():adjust_range(0.0, levels-1):rewrap(m1:size()) local m2 = m2:clone():adjust_range(0.0, levels-1):rewrap(m2:size()) -- the joint histogram is a 2-dimensional matrix local h12 = matrix(levels,levels):zeros() local sz = m1:size() -- the two matrices has the same size -- auxiliary function which computes the bin of a given matrix value function get_bin_idx(v) return math.floor(v)+1 end for i=1,sz do local i1 = get_bin_idx(m1:get(i)) -- bin row position local i2 = get_bin_idx(m2:get(i)) -- bin col position local c = h12:get(i1, i2) -- the previous count h12:set(i1, i2, c + 1) end h12:scal(1/sz) -- marginalization for m1 and m2 histograms computation local h1 = matrix(levels):zeros() local h2 = matrix(levels):zeros() for i=1,levels do h1:axpy(1.0, h12:select(2, i)) -- by columns h2:axpy(1.0, h12:select(1, i)) -- by rows end local entropy1 = stats.MI.entropy(nil, h1) local entropy2 = stats.MI.entropy(nil, h2) local entropy12 = stats.MI.entropy(nil, h12) -- returns the Mutual Information and Normalized Mutual Information return entropy1+entropy2-entropy12 , (entropy1+entropy2)/entropy12 end april-ann-0.4.1/packages/mutual_information/package.lua000066400000000000000000000022341263004425400231660ustar00rootroot00000000000000 package{ name = "stats.MI", version = "1.0", depends = { "util", "matrix", "image_cleaning" }, keywords = { "mutual_information" }, description = "Mutual information", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", -- copy{ file= "c_src/*.h", dest_dir = "include" }, -- provide_bind{ file = "binding/bind_image.lua.cc", dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp=true, -- object{ -- file = "c_src/image.cc", -- include_dirs = "${include_dirs}", -- dest_dir = "build", -- --debug = "yes", -- }, luac{ orig_dir = "lua_src", dest_dir = "build", }, -- build_bind{ file = "binding/bind_image.lua.cc", dest_dir = "build" }, -- build_bind{ file = "binding/bind_image_RGB.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{}, document_bind{}, }, } april-ann-0.4.1/packages/ocr/000077500000000000000000000000001263004425400157365ustar00rootroot00000000000000april-ann-0.4.1/packages/ocr/off_line_param/000077500000000000000000000000001263004425400206775ustar00rootroot00000000000000april-ann-0.4.1/packages/ocr/off_line_param/binding/000077500000000000000000000000001263004425400223115ustar00rootroot00000000000000april-ann-0.4.1/packages/ocr/off_line_param/binding/bind_off_line_param.lua.cc000066400000000000000000000022621263004425400273370ustar00rootroot00000000000000 //BIND_HEADER_H #include "geom_param.h" #include "bind_image.h" //BIND_END //BIND_HEADER_C using namespace Basics; using namespace Imaging; //BIND_END //BIND_FUNCTION ocr.off_line.param.geom { LUABIND_CHECK_ARGN(>=, 1); LUABIND_CHECK_ARGN(<=, 2); ImageFloat *img; const char *param_list; LUABIND_GET_PARAMETER(1, ImageFloat, img); LUABIND_GET_OPTIONAL_PARAMETER(2, string, param_list, "siepd"); MatrixFloat *result = OCR::OffLineTextPreprocessing:: GeomParam::extract(img, param_list); LUABIND_RETURN(MatrixFloat, result); } //BIND_END //BIND_FUNCTION ocr.off_line.RLSA { ImageFloat *img; int threshold; LUABIND_GET_PARAMETER(1, ImageFloat, img); LUABIND_GET_PARAMETER(2, int, threshold); OCR::OffLineTextPreprocessing::RLSA(img,threshold); // LUABIND_RETURN(ImageFloat,img); } //BIND_END //BIND_FUNCTION ocr.off_line.baselinesRLSA { ImageFloat *img; float threshold; int upper, lower; LUABIND_GET_PARAMETER(1, ImageFloat, img); LUABIND_GET_OPTIONAL_PARAMETER(2, float, threshold, 0.5f); OCR::OffLineTextPreprocessing::baseLinesRLSA(img, &lower, &upper, threshold); LUABIND_RETURN(int, lower); LUABIND_RETURN(int, upper); } //BIND_END april-ann-0.4.1/packages/ocr/off_line_param/c_src/000077500000000000000000000000001263004425400217705ustar00rootroot00000000000000april-ann-0.4.1/packages/ocr/off_line_param/c_src/geom_param.cc000066400000000000000000000250771263004425400244210ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Salvador España-Boquera, Jorge Gorbe-Moya, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "geom_param.h" #include "clamp.h" #include "derivative.h" #include #include using namespace AprilUtils; using namespace Basics; using namespace Imaging; namespace OCR { namespace OffLineTextPreprocessing { const float GeomParam::THRESHOLD = 0.7; #define SQR(x) ((x)*(x)) // val = (val - base) * scal; void GeomParam::copyNormVector(float *v, MatrixFloat *mat, int ncol, float base, float scal) { int n = mat->getDimSize(0); int nparams = mat->getDimSize(1); april_assert(ncol < nparams); for (int i=0; iheight() - 1; int inf_contour = 0; int row = 0; float val = (*img)(col, row); while ((val < THRESHOLD) && (row < img->height() - 1)) { ++row; val = (*img)(col, row); } sup_contour = row; row = img->height() - 1; val = (*img)(col, row); while ((val < THRESHOLD) && (row > 0)) { --row; val = (*img)(col, row); } inf_contour = row; // when inferior and superior contours cross, they will be placed in the // text center. if (sup_contour > inf_contour) { sup_contour = inf_contour = int(text_center); } *sup = float(sup_contour); *inf = float(inf_contour); } // OJO! Este parametrizador asume que 0 = blanco y 1 = black, al contrario que // la clase Imagen a julio de 2009 :P // // params es una cadena que puede contener las siguientes letras: // S: contour superior // I: contour inferior // E: energy // P: posicion media de la energy (momento de primer orden) // D: desv. tipica de la posicion de la energy (momento de segundo orden) // // T: numero de trazos // // Q: derivative1 del c. sup // A: derivative1 del c. inf // // Z: derivative2 del c. sup // X: derivative2 del c. inf // // H: "Altura" -> inf_contour - sup_contour // J: Derivative de H // // M: Derivative de la posicion media de la energy // // R: Density de pixels entre el contour superior y el inferior. // // Si se ponen en minusculas se normalizan respecto a las lineas base MatrixFloat* GeomParam::extract(const ImageFloat *img, const char *params) { // variance epsilon, considered as zero const float EPSILON = 0.01; // inferior and upper baselines (from a projection-based algorithm) int lower_base, upper_base; OCR::OffLineTextPreprocessing::baseLinesRLSA(img, &lower_base, &upper_base); // WARNING! because coordinates are (x,y) instead of (row,col) // the inferior line has a higher y coodinate :P float text_height = lower_base - upper_base + 1; float text_center = (lower_base + upper_base)/2.0; int matrix_size[2]; MatrixFloat *result; int NPARAM = strlen(params); // the matrix has as many rows as columns in the image, and as many // columns as parameters matrix_size[0] = img->width(); matrix_size[1] = NPARAM; result = new MatrixFloat(2, matrix_size); // temporal vectors which store all the parameters float *v_sup_contour = new float[img->width()]; float *v_inf_contour = new float[img->width()]; float *v_height = new float[img->width()]; float *v_energy = new float[img->width()]; float *v_density = new float[img->width()]; float *v_mean_energy_pos = new float[img->width()]; float *v_stddev_energy = new float[img->width()]; float *v_sup_derivative = new float[img->width()]; float *v_inf_derivative = new float[img->width()]; float *v_derivative2_sup = new float[img->width()]; float *v_derivative2_inf = new float[img->width()]; float *v_derivative_pme = new float[img->width()]; float *v_derivative_height = new float[img->width()]; float *v_orig_nstrokes = new float[img->width()]; float *v_nstrokes = new float[img->width()]; // after voting (2 of 3) // traverse all the columns for (int col = 0; col < img->width(); ++col) { float energy = 0; float mean_energy_pos = 0; float mean_pos_squared = 0; float variance = 0; // contours contours(img, col, text_center, &v_sup_contour[col], &v_inf_contour[col]); int sup_contour = int(v_sup_contour[col]); int inf_contour = int(v_inf_contour[col]); // height v_height[col] = inf_contour - sup_contour; // energy levels, mean position (weighted) and variance for (int row = sup_contour; row <= inf_contour; ++row) { float val = (*img)(col, row); energy += val; //float row_norm = (row - upper_base)/text_height; //mean_energy_pos += row_norm * val; //mean_pos_squared += SQR(row_norm) * val; mean_energy_pos += row * val; mean_pos_squared += SQR(row) * val; } if (energy > 0) { mean_energy_pos /= energy; // var(x) = E(x^2) - (E(x))^2 variance = mean_pos_squared / energy - SQR(mean_energy_pos); if (fabsf(variance) < EPSILON) variance = 0; } else { mean_energy_pos = text_center; variance = 0; } v_energy[col] = energy; v_density[col] = v_height[col] > 0 ? energy/v_height[col] : 0; v_mean_energy_pos[col] = mean_energy_pos; v_stddev_energy[col] = sqrtf(variance); // number of strokes. // starts at black and ends at black. const float THRESHOLD = 0.8; // energy threshold bool black=true; int cblack=0; int nstrokes=0; const int STROKES_THRESHOLD=1; for (int row=sup_contour; row<=inf_contour; ++row) { if ( (*img)(col,row) > THRESHOLD ) { // black pixel black=true; cblack++; } else { // white pixel if (black) { if (cblack >= STROKES_THRESHOLD) { ++nstrokes; } cblack=0; } black = false; } } if (black && cblack >= STROKES_THRESHOLD) ++nstrokes; v_orig_nstrokes[col] = nstrokes; } // derivatives derivative1(v_sup_contour, v_sup_derivative, img->width()); derivative1(v_inf_contour, v_inf_derivative, img->width()); derivative1(v_mean_energy_pos, v_derivative_pme, img->width()); derivative1(v_height, v_derivative_height, img->width()); derivative2(v_sup_contour, v_derivative2_sup, img->width()); derivative2(v_inf_contour, v_derivative2_inf, img->width()); // compute strokes by voting for (int col=0; col < img->width(); ++col) { int izq, der; // nstrokes izq = clamp(col - 1, 0, img->width() - 1); der = clamp(col + 1, 0, img->width() - 1); if (v_orig_nstrokes[izq] == v_orig_nstrokes[der]) v_nstrokes[col] = v_orig_nstrokes[izq]; else v_nstrokes[col] = v_orig_nstrokes[col]; } // put the required parameters in the result matrix int i=0; while (params[i]) { float inv_text_height = 1.0/text_height; switch(params[i]) { case 'S': result->putCol(i, v_sup_contour, img->width()); break; case 's': copyNormVector(v_sup_contour, result, i, upper_base, inv_text_height); break; case 'I': result->putCol(i, v_inf_contour, img->width()); break; case 'i': copyNormVector(v_inf_contour, result, i, upper_base, inv_text_height); break; case 'E': result->putCol(i, v_energy, img->width()); break; case 'e': copyNormVector(v_energy, result, i, 0, inv_text_height); break; case 'P': result->putCol(i, v_mean_energy_pos, img->width()); break; case 'p': copyNormVector(v_mean_energy_pos, result, i, upper_base, inv_text_height); break; case 'D': result->putCol(i, v_stddev_energy, img->width()); break; case 'd': copyNormVector(v_stddev_energy, result, i, 0, inv_text_height); break; case 'Q': result->putCol(i, v_sup_derivative, img->width()); break; case 'q': copyNormVector(v_sup_derivative, result, i, 0, inv_text_height); break; case 'A': result->putCol(i, v_inf_derivative, img->width()); break; case 'a': copyNormVector(v_inf_derivative, result, i, 0, inv_text_height); break; case 'T': result->putCol(i, v_orig_nstrokes, img->width()); break; case 't': // TODO: Normalizar? copyNormVector(v_nstrokes, result, i, 0, 0.3); break; case 'H': result->putCol(i, v_height, img->width()); break; case 'h': copyNormVector(v_height, result, i, 0, inv_text_height); break; case 'J': result->putCol(i, v_derivative_height, img->width()); break; case 'j': copyNormVector(v_derivative_height, result, i, 0, inv_text_height); break; case 'M': result->putCol(i, v_derivative_pme, img->width()); break; case 'm': copyNormVector(v_derivative_pme, result, i, 0, inv_text_height); break; case 'Z': result->putCol(i, v_derivative2_sup, img->width()); break; case 'z': copyNormVector(v_derivative2_sup, result, i, 0, inv_text_height); break; case 'X': result->putCol(i, v_derivative2_inf, img->width()); break; case 'x': copyNormVector(v_derivative2_inf, result, i, 0, inv_text_height); break; case 'R': case 'r': result->putCol(i, v_density, img->width()); break; default: ERROR_EXIT1(128, "param: invalid character '%c' in parameters string!\n", params[i]); } ++i; } delete [] v_sup_contour; delete [] v_inf_contour; delete [] v_height; delete [] v_energy; delete [] v_mean_energy_pos; delete [] v_stddev_energy; delete [] v_sup_derivative; delete [] v_inf_derivative; delete [] v_derivative2_sup; delete [] v_derivative2_inf; delete [] v_derivative_pme; delete [] v_derivative_height; delete [] v_orig_nstrokes; delete [] v_nstrokes; return result; } } } april-ann-0.4.1/packages/ocr/off_line_param/c_src/geom_param.h000066400000000000000000000064521263004425400242570ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Salvador España-Boquera, Jorge Gorbe-Moya, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef GEOM_PARAM_H #define GEOM_PARAM_H #include "matrixFloat.h" #include "utilImageFloat.h" namespace OCR { namespace OffLineTextPreprocessing { template void RLSA(Imaging::Image *img, int threshold) { const float BINARIZING_THRESHOLD = 0.5f; // for each image row, seek white pixel runs between two blacks. If the // run length is inferior to a threshold, the run will be filled with // black. for (int row=0; row < img->height(); ++row) { int left=-1; int right=0; int run_length=0; while (right < img->width()) { // a black pixel if ((*img)(right, row) > BINARIZING_THRESHOLD) { if (left != -1) { if ((run_length > 0) && (run_length < threshold)) { for(int col=left; col<=right; ++col) (*img)(col,row) = 1.0; // FIXME:CTENEGRO } } run_length=0; left=right; } else { // a white pixel ++run_length; } ++right; } } } template void baseLinesRLSA(const Imaging::Image *img, int *lower, int *upper, const float projection_th=0.5f) { // if the projection is inferior to this threshold, it won't be placed // between text baselines const int RLSA_TH=30; // work copy Imaging::Image *i2=img->clone(); RLSA(i2, RLSA_TH); T *projection = new T[img->height()]; i2->projection_h(projection); T maximum = 0; for (int i=0; i < img->height(); ++i) { if (projection[i] > maximum) maximum = projection[i]; } int u=0; while (u < img->height()) { if (projection[u] > projection_th * maximum) break; ++u; } int l = img->height() - 1; while (l >= 0) { if (projection[l] > projection_th * maximum) break; --l; } *upper = u; *lower = l; delete i2; delete[] projection; } class GeomParam { public: /// Threshold which defines when the pixel energy is considered ink static const float THRESHOLD; static Basics::MatrixFloat *extract (const Imaging::ImageFloat *i, const char *params); private: static void contours(const Imaging::ImageFloat *img, int col, float text_center, float *sup, float *inf); static void copyNormVector(float *v, Basics::MatrixFloat *mat, int ncol, float base, float scal); }; } } #endif // GEOM_PARAM_H april-ann-0.4.1/packages/ocr/off_line_param/lua_src/000077500000000000000000000000001263004425400223275ustar00rootroot00000000000000april-ann-0.4.1/packages/ocr/off_line_param/lua_src/param.lua000066400000000000000000000012441263004425400241330ustar00rootroot00000000000000function ocr.off_line.param.help() print[[ Paquete ocr.off_line.param -------------------------- Metodos (de clase): - ocr.off_line.param.geom(img, PARAMS_LIST) PARAMS_LIST es una cadena que puede contener las siguientes letras: S: contorno superior I: contorno inferior E: energia P: posicion media de la energia D: desv. tipica de la posicion media de la energia T: numero de trazos Q: derivada1 del c. sup A: derivada1 del c. inf Z: derivada2 del c. sup X: derivada2 del c. inf H: "Altura" -> contorno_inf - contorno_sup M: Derivada de la posicion media de la energía Si se ponen en minusculas se normalizan respecto a las lineas base ]] end april-ann-0.4.1/packages/ocr/off_line_param/package.lua000066400000000000000000000020611263004425400227740ustar00rootroot00000000000000 package{ name = "ocr.off_line.param", version = "1.0", depends = { "util", "matrix", "Image" }, keywords = { }, description = "Feature extraction for handwritten words", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_off_line_param.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_off_line_param.lua.cc", dest_dir = "build" } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/ocr/off_line_text_preprocessing/000077500000000000000000000000001263004425400235265ustar00rootroot00000000000000april-ann-0.4.1/packages/ocr/off_line_text_preprocessing/binding/000077500000000000000000000000001263004425400251405ustar00rootroot00000000000000bind_off_line_text_preprocessing.lua.cc000066400000000000000000000072701263004425400347420ustar00rootroot00000000000000april-ann-0.4.1/packages/ocr/off_line_text_preprocessing/binding//BIND_HEADER_H #include "off_line_text_preprocessing.h" #include "utilImageFloat.h" #include "bind_image.h" #include "vector.h" #include #include #include "geometry.h" //BIND_END //BIND_HEADER_C using namespace AprilUtils; using namespace Basics; using namespace Imaging; //BIND_END //BIND_FUNCTION ocr.off_line_text_preprocessing.normalize_image { using AprilUtils::vector; using AprilUtils::Point2D; LUABIND_CHECK_ARGN(==,2); ImageFloat *img; int dst_height; LUABIND_GET_PARAMETER(1, ImageFloat, img); LUABIND_GET_PARAMETER(2, int, dst_height); ImageFloat *result = OCR::OffLineTextPreprocessing::normalize_image(img, dst_height); LUABIND_RETURN(ImageFloat, result); } //BIND_END //BIND_FUNCTION ocr.off_line_text_preprocessing.normalize_size { using AprilUtils::vector; using AprilUtils::Point2D; LUABIND_CHECK_ARGN(>=,7); LUABIND_CHECK_ARGN(<=,9); ImageFloat *img; float ascender_ratio, descender_ratio; int dst_height; bool keep_aspect; LUABIND_GET_PARAMETER(1, ImageFloat, img); LUABIND_GET_PARAMETER(2, float, ascender_ratio); LUABIND_GET_PARAMETER(3, float, descender_ratio); LUABIND_CHECK_PARAMETER(4, table); LUABIND_CHECK_PARAMETER(5, table); LUABIND_CHECK_PARAMETER(6, table); LUABIND_CHECK_PARAMETER(7, table); LUABIND_GET_OPTIONAL_PARAMETER(8, int, dst_height, -1); LUABIND_GET_OPTIONAL_PARAMETER(9, bool, keep_aspect, false); int point_vector_length[4]; vector point_vector[4]; for (int vec=0; vec<4; vec++) { LUABIND_TABLE_GETN(vec+4, point_vector_length[vec]); point_vector[vec].resize(point_vector_length[vec]); for (int i=1; i <= point_vector_length[vec]; ++i) { lua_rawgeti(L,vec+4,i); // punto i-esimo, es una tabla, los vectores estan en pila[4-7] lua_rawgeti(L,-1,1); // x LUABIND_GET_PARAMETER(-1, float, point_vector[vec][i-1].x); lua_pop(L,1); // la quitamos de la pila lua_rawgeti(L,-1,2); // y LUABIND_GET_PARAMETER(-1, float, point_vector[vec][i-1].y); lua_pop(L,2); // la quitamos de la pila, tb la tabla } } ImageFloat *result = OCR::OffLineTextPreprocessing::normalize_size(img, ascender_ratio, descender_ratio, point_vector[0], point_vector[1], point_vector[2], point_vector[3], dst_height, keep_aspect); LUABIND_RETURN(ImageFloat, result); } //BIND_END //BIND_FUNCTION ocr.off_line_text_preprocessing.add_asc_desc { LUABIND_CHECK_ARGN(>=,2); LUABIND_CHECK_ARGN(<=,4); ImageFloat *img; MatrixFloat *mat; int v_threshold; int h_threshold; LUABIND_GET_PARAMETER(1, ImageFloat, img); LUABIND_GET_PARAMETER(2, MatrixFloat, mat); LUABIND_GET_OPTIONAL_PARAMETER(3,float,v_threshold, 5.0f); LUABIND_GET_OPTIONAL_PARAMETER(4,int,h_threshold, 20); MatrixFloat *result = OCR::OffLineTextPreprocessing::add_asc_desc(img,mat, v_threshold, h_threshold); LUABIND_RETURN(MatrixFloat, result); } //BIND_END //BIND_FUNCTION ocr.off_line_text_preprocessing.normalize_from_matrix { using AprilUtils::vector; using AprilUtils::Point2D; LUABIND_CHECK_ARGN(>=,4); LUABIND_CHECK_ARGN(<=,6); ImageFloat *img; MatrixFloat *mat; float ascender_ratio, descender_ratio; int dst_height; bool keep_aspect; LUABIND_GET_PARAMETER(1, ImageFloat, img); LUABIND_GET_PARAMETER(4, MatrixFloat, mat); LUABIND_GET_PARAMETER(2, float, ascender_ratio); LUABIND_GET_PARAMETER(3, float, descender_ratio); LUABIND_GET_OPTIONAL_PARAMETER(5, int, dst_height, -1); LUABIND_GET_OPTIONAL_PARAMETER(6, bool, keep_aspect, false); ImageFloat *result = OCR::OffLineTextPreprocessing::normalize_size(img, mat, ascender_ratio, descender_ratio, dst_height, keep_aspect); LUABIND_RETURN(ImageFloat, result); } //BIND_END april-ann-0.4.1/packages/ocr/off_line_text_preprocessing/c_src/000077500000000000000000000000001263004425400246175ustar00rootroot00000000000000april-ann-0.4.1/packages/ocr/off_line_text_preprocessing/c_src/off_line_text_preprocessing.cc000066400000000000000000000540031263004425400327200ustar00rootroot00000000000000#include "off_line_text_preprocessing.h" #include "utilImageFloat.h" #include "utilMatrixFloat.h" #include "vector.h" #include "pair.h" #include "swap.h" #include "max_min_finder.h" // para buscar_extremos_trazo #include "unused_variable.h" #include #include #include "interest_points.h" using namespace AprilUtils; using namespace Basics; using namespace Imaging; namespace OCR { namespace OffLineTextPreprocessing { static Point2D get_next_point(vector v, int index, int width, float default_y) { assert(index+1 >= 0 && "Invalid index"); if (v.size() > 0) { if (index < int(v.size())-1) { return v[index+1]; } else { return Point2D(width-1.0f, v.back().y); } } else { return Point2D(width-1.0f, default_y); } } static Point2D get_first_point(vector v, int width, float default_y, int *index) { UNUSED_VARIABLE(width); Point2D result; if (!v.empty()) { result.x = 0; result.y = v[0].y; if (v[0].x == 0) { *index = 0; // index is the last index we have used in v } else { *index = -1; } } else { result.x = 0.0f; result.y = default_y; *index = -1; } return result; } // Reduce a section of one column to one pixel static float column_reduce(ImageFloat *src, int col, float src_top, float src_bottom) { float epsilon = 1e-7; assert(src_top >= 0 && "Top source must be >= 0"); // assert(src_bottom <= src->height || // (0, printf("Bottom source must be <= src_height. (%f/%d)\n", // src_bottom, src->height))); assert(src_top <= src_bottom && "Top pixel has to be lower than bottom"); int pxl_top = floor(src_top); int pxl_bottom = floor(src_bottom); float rst_top = src_top - pxl_top; float rst_bottom = src_bottom - pxl_bottom; float total = 0.0f; //if (pxl_top == pxl_bottom) // return (float) (*src)(col, pxl_top); for(int x = pxl_top; x < pxl_bottom; ++x) { total += (*src)(col, x); } if (rst_top > epsilon) { total -= rst_top * ((*src)(col, pxl_top)); } if (rst_bottom > epsilon) { total += rst_bottom * ((*src)(col, pxl_bottom)); } return total/(src_bottom - src_top); } // Given a contour matrix (baseline, topline) and a line points // bool xComparator(Point2D &v1, Point2D &v2) { return v1.x < v2.x; } bool yComparator(Point2D &v1, Point2D &v2) { return v1.y < v2.y; } bool yComparatorReversed(Point2D &v1, Point2D &v2) { return v1.y > v2.y; } static void filter_asc(vector *points, MatrixFloat::random_access_iterator &line_it, int width, float vThreshold = 10.0f, int hThreshold = 20) { bool *valid = new bool[width]; for (int i=0; i *new_points = new vector(); AprilUtils::Sort(&(*points)[0],points->size(),yComparator); for(int i = 0; i < (int)points->size();++i) { Point2D &p = (*points)[i]; int x = int(p.x); if (line_it(x,0) > p.y+vThreshold && valid[x]) { new_points->push_back(p); int first = max(x-hThreshold,0); int last = min(x+hThreshold,width-1); for (int i=first; i<=last; ++i) valid[i]=false; } } // sort new_points by x AprilUtils::Sort(&(*new_points)[0],new_points->size(),xComparator); // delete points and change to new_points vector *aux = points; points->swap(*new_points); delete new_points; delete[] valid; } static void filter_desc(vector *points, MatrixFloat::random_access_iterator &line_it, int width, float vThreshold = 5.0f, int hThreshold = 20) { bool *valid = new bool[width]; for (int i=0; i *new_points = new vector(); AprilUtils::Sort(&(*points)[0],points->size(),yComparatorReversed); for(int i = 0; i < (int)points->size();++i) { Point2D &p = (*points)[i]; int x = int(p.x); if (line_it(x,1) < p.y-vThreshold && valid[x]) { new_points->push_back(p); int first = max(x-hThreshold,0); int last = min(x+hThreshold,width-1); for (int i=first; i<=last; ++i) valid[i]=false; } } // sort new_points by x AprilUtils::Sort(&(*new_points)[0],new_points->size(),xComparator); // delete points and change to new_points vector *aux = points; points->swap(*new_points); delete new_points; delete[] valid; } // Scales the source column to the target column // Recieve: // Two Images (Source and target) // Column to be reduced // the initial and final x of the source image // the initial and final x of the target image static void resize_index(ImageFloat *src, ImageFloat *dst, int col, float src_top, float src_bottom, float dst_top, float dst_bottom) { //We are assuming that the row of the column can be viewed //as a float between range 0 and height (inclusive) assert(src_top >= 0 && "Top source must be >= 0"); assert(dst_top >= 0 && "Top dest must be >= 0"); assert(src_bottom <= src->height() && "Bottom source must be <= src_height"); assert(dst_bottom <= dst->height() && "Bottom dest must be <= dest_height"); assert(src_top <= src_bottom && "Top src pixel has to be lower than bottom"); assert(dst_top < dst_bottom && "Top target pixel has to be lower than bottom"); //if (src_top >= src_bottom) // src_bottom = src_top+1; double epsilon = 1e-7; float ratio = (src_bottom - src_top)/(dst_bottom - dst_top); float cur_top = src_top; float cur_bottom; //Compute the first row rest int first_row = (int) ceil(dst_top); int last_row = (int) ceil(dst_bottom); float rst_top = first_row - dst_top; if (rst_top > epsilon) { cur_bottom = src_top; cur_top = (first_row-dst_top)*ratio; (*dst)(col, (int)floor(dst_top)) += column_reduce(src, col, cur_top, cur_bottom); } for (int row = first_row; row < last_row; ++row) { // fprintf(stderr, "Assert src_cur %f, src_next: %f, top: %f , bottom: %f, height: %d\n", src_cur, src_cur+ratio, src_top, src_bottom, src->height); cur_bottom = ((row +1 - dst_top)*ratio) + src_top; float dst_value = column_reduce(src, col, cur_top, cur_bottom); cur_top = cur_bottom; (*dst)(col, row) = dst_value; } //Compute the last row rest float rst_bottom = dst_bottom - last_row; if (rst_bottom > epsilon) { cur_bottom = src_bottom; (*dst)(col, (int)ceil(dst_bottom)) += column_reduce(src, col, cur_top, cur_bottom); } } ImageFloat *normalize_image(ImageFloat *source, int dst_height) { int width = source->width(); int height = source->height(); int dims[2] = {dst_height, width}; MatrixFloat *result_mat = new MatrixFloat(2, dims); ImageFloat *result = new ImageFloat(result_mat); for(int col = 0; col < width; ++col) { resize_index(source, result, col, 0, height, 0, dst_height); } return result; } ImageFloat *normalize_size (ImageFloat *source, float ascender_ratio, float descender_ratio, vector ascenders, vector upper_baseline, vector lower_baseline, vector descenders, int dst_height, bool keep_aspect ) { // Precondition: upper_baseline and lower_baseline must contain, at least, one point each assert(!upper_baseline.empty() && "Upper baseline must not be empty"); assert(!lower_baseline.empty() && "Lower baseline must not be empty"); int width = source->width(); int height = source->height(); int BASELINE_SLACK=int(0.02f*height); //printf("BASELINE_SLACK = %d\n", BASELINE_SLACK); if (dst_height < 0) dst_height = source->height(); int ascender_size = int(roundf(ascender_ratio*dst_height)); int descender_size = int(roundf(descender_ratio*dst_height)); int body_size = dst_height - ascender_size - descender_size; /* Definimos 4 alturas relevantes en las imagenes * * IMAGEN DESTINO IMAGEN ORIGEN * * - 0 --------------------------- cur_asc - * | ascenders | * - dst_upper ----------------- cur_upper - * | body | * - dst_lower ----------------- cur_lower - * | descenders | * - dst_height-1 --------------- cur_desc - */ int dst_upper = ascender_size; int dst_lower = ascender_size + body_size; int dims[2] = {dst_height, width}; MatrixFloat *result_mat = new MatrixFloat(2, dims); // FIXME: For non inverted matrix AprilMath::MatrixExt::Initializers::matFill(result_mat, 0.0f); ImageFloat *result = new ImageFloat(result_mat); int asc_idx = 0; int upper_idx = 0; int lower_idx = 0; int desc_idx = 0; Point2D next_asc, next_upper, next_lower, next_desc; Point2D prev_asc, prev_upper, prev_lower, prev_desc; prev_asc = get_first_point(ascenders, width, 0.0f, &asc_idx); next_asc = get_next_point(ascenders, asc_idx, width, 0.0f); asc_idx++; prev_desc = get_first_point(descenders, width, height-1.0f, &desc_idx); next_desc = get_next_point(descenders, desc_idx, width, height-1.0f); desc_idx++; // Default value won't be used due to precondition prev_upper = get_first_point(upper_baseline, width, -9999.9f, &upper_idx); next_upper = get_next_point(upper_baseline, upper_idx, width, -9999.9f); upper_idx++; // Default value won't be used due to precondition prev_lower = get_first_point(lower_baseline, width, -9999.9f, &lower_idx); next_lower = get_next_point(lower_baseline, lower_idx, width, -9999.9f); lower_idx++; int body_columns=0; float body_size_sum=0.0f; for (int column = 0; column < width; column++) { if (column > next_asc.x) { prev_asc = next_asc; next_asc = get_next_point(ascenders, asc_idx, width, 0.0f); asc_idx++; } if (column > next_desc.x) { prev_desc = next_desc; next_desc = get_next_point(descenders, desc_idx, width, height-1.0f); desc_idx++; } if (column > next_upper.x) { prev_upper = next_upper; next_upper = get_next_point(upper_baseline, upper_idx, width, 9999.9f); upper_idx++; } if (column > next_lower.x) { prev_lower = next_lower; next_lower = get_next_point(lower_baseline, lower_idx, width, 9999.9f); lower_idx++; } float cur_upper = max(0.0f, prev_upper.y + ((column - prev_upper.x) / (next_upper.x-prev_upper.x)) * (next_upper.y - prev_upper.y) - BASELINE_SLACK); float cur_lower = min(height - 1.0f, prev_lower.y + ((column - prev_lower.x) / (next_lower.x - prev_lower.x)) * (next_lower.y - prev_lower.y) + BASELINE_SLACK); if (cur_upper > cur_lower) { swap(cur_upper, cur_lower); } float cur_asc = min(cur_upper, prev_asc.y + ((column - prev_asc.x) / (next_asc.x - prev_asc.x) ) * (next_asc.y - prev_asc.y)); float cur_desc = max(cur_lower, prev_desc.y + ((column - prev_desc.x) / (next_desc.x - prev_desc.x)) * (next_desc.y - prev_desc.y)); // Center // // First normalize the body and calculate the normalization rasize float body_ratio = (cur_lower - cur_upper)/body_size; if (cur_lower-cur_upper >= 1.0f) { body_columns++; body_size_sum += cur_lower-cur_upper; resize_index(source, result, column, cur_upper, cur_lower, dst_upper, dst_lower); } // Ascender float expected_top = dst_upper*body_ratio; float top_cut = cur_asc; if (keep_aspect) { top_cut = cur_upper - expected_top; } //Fill the blanks float dst_asc = 0; if (top_cut < 0) { dst_asc = -top_cut/body_ratio; top_cut = 0; } if(cur_upper - top_cut >= 1.0f) resize_index(source, result, column, top_cut, cur_upper, dst_asc, dst_upper); //printf("x=%d, 1=%f, 2=%f, 4=%f, 5=%f\n", column, cur_asc, cur_upper, cur_lower, cur_desc); // Descenders float expected_bottom = (dst_height - dst_lower)*body_ratio; float dst_desc = dst_height; float bottom_cut = cur_desc; if (keep_aspect) { bottom_cut = cur_lower + expected_bottom; } if (bottom_cut > height) { dst_desc = dst_lower + (height-cur_lower)/body_ratio; bottom_cut = height; } //printf("dst_dsc :%d, dst_height: %d, bottom_cut:%d, height: %d, ratio: %f\n", dst_desc, dst_height, bottom_cut, height, body_ratio); assert(dst_desc <= dst_height && "Something went wrong"); if( bottom_cut - cur_lower >= 1.0f) resize_index(source, result, column, cur_lower, bottom_cut, dst_lower, dst_desc); } return result; } ImageFloat *normalize_size (ImageFloat *source, MatrixFloat *line_mat, float ascender_ratio, float descender_ratio, int dst_height, bool keep_aspect ) { // Precondition: upper_baseline and lower_baseline must contain, at least, one point each int width = source->width(); int height = source->height(); MatrixFloat::random_access_iterator line_it(line_mat); assert(line_mat->getDimSize(0) == width && "The number of columns does not fit"); assert(line_mat->getDimSize(1) == 4 && "There are no 3 areas on the image"); if (dst_height < 0) dst_height = source->height(); int ascender_size = int(roundf(ascender_ratio*dst_height)); int descender_size = int(roundf(descender_ratio*dst_height)); int body_size = dst_height - ascender_size - descender_size; /* Definimos 4 alturas relevantes en las imagenes * * IMAGEN DESTINO IMAGEN ORIGEN * * - 0 --------------------------- cur_asc - * | ascenders | * - dst_upper ----------------- cur_upper - * | body | * - dst_lower ----------------- cur_lower - * | descenders | * - dst_height-1 --------------- cur_desc - */ int dst_upper = ascender_size; int dst_lower = ascender_size + body_size; int dims[2] = {dst_height, width}; MatrixFloat *result_mat = new MatrixFloat(2, dims); ImageFloat *result = new ImageFloat(result_mat); for (int column = 0; column < width; column++) { float cur_upper = line_it(column, 1); float cur_lower = line_it(column, 2); float cur_asc = line_it(column, 0); float cur_desc = line_it(column, 3); // First normalize the body and calculate the normalization rasize float body_ratio = (cur_lower - cur_upper)/body_size; if (cur_lower-cur_upper >= 1.0f) { resize_index(source, result, column, cur_upper, cur_lower, dst_upper, dst_lower); } // Ascender float expected_top = dst_upper*body_ratio; float top_cut = cur_asc; if (keep_aspect) { top_cut = cur_upper - expected_top; } //Fill the blanks float dst_asc = 0; if (top_cut < 0) { dst_asc = -top_cut/body_ratio; top_cut = 0; } if (cur_upper - top_cut >= 1) resize_index(source, result, column, top_cut, cur_upper, dst_asc, dst_upper); //printf("x=%d, 1=%f, 2=%f, 4=%f, 5=%f\n", column, cur_asc, cur_upper, cur_lower, cur_desc); // Descenders float expected_bottom = (dst_height - dst_lower)*body_ratio; float dst_desc = dst_height; float bottom_cut = cur_desc; if (keep_aspect) { bottom_cut = cur_lower + expected_bottom; } if (bottom_cut > height) { dst_desc = dst_lower + (height-cur_lower)/body_ratio; bottom_cut = height; } assert(dst_desc <= dst_height && "Something went wrong"); if(bottom_cut - cur_lower >= 1.0f) resize_index(source, result, column, cur_lower, bottom_cut, dst_lower, dst_desc); } return result; } // From the points of the topline and baseline, adds the ascenderes and descenders MatrixFloat *add_asc_desc (ImageFloat *img, MatrixFloat *line_mat, float v_threshold, int h_threshold ) { // Precondition mat size must be columns //assert(line_mat->getDimSize(0) == img->width() && "Matrix points does not fit with the image"); int width = img->width(); int height = img->height(); // Generate the 4 matrix dim int dims[2] = {width, 4}; MatrixFloat *result = new MatrixFloat(2, dims); MatrixFloat::random_access_iterator line_it(line_mat); MatrixFloat::random_access_iterator result_it(result); // Compute local maxima and local minima vector *ascenders = new vector(); vector *descenders = new vector(); // The true is because the image is inverted InterestPoints::extract_points_from_image(img, descenders, ascenders, 0.6, 0.4, 6, 15, true ); // Filter the points that are over the size filter_asc(ascenders, line_it, width, v_threshold, h_threshold); filter_desc(descenders, line_it, width,v_threshold, h_threshold); // Compute the interpolated lines Point2D next_asc, next_desc; Point2D prev_asc, prev_desc; int asc_idx = 0; int desc_idx = 0; prev_asc = get_first_point(*ascenders, width, 0.0f, &asc_idx); next_asc = get_next_point(*ascenders, asc_idx, width, 0.0f); asc_idx++; prev_desc = get_first_point(*descenders, width, height-1.0f, &desc_idx); next_desc = get_next_point(*descenders, desc_idx, width, height-1.0f); desc_idx++; for (int column = 0; column < width; column++) { float cur_upper = line_it(column,0); float cur_lower = line_it(column,1); if (column >= line_mat->getDimSize(0)){ cur_upper = line_it(line_mat->getDimSize(0)-1, 0); cur_lower = line_it(line_mat->getDimSize(0)-1, 1); } if (cur_upper > cur_lower) cur_upper = cur_lower; if (column > next_asc.x) { prev_asc = next_asc; next_asc = get_next_point(*ascenders, asc_idx, width, 0.0f); asc_idx++; } if (column > next_desc.x) { prev_desc = next_desc; next_desc = get_next_point(*descenders, desc_idx, width, height-1.0f); desc_idx++; } float cur_asc = min(cur_upper-1.0f, prev_asc.y + ((column - prev_asc.x) / (next_asc.x - prev_asc.x) ) * (next_asc.y - prev_asc.y)); cur_asc = max(0.0f,cur_asc); float cur_desc = max(cur_lower+1.0f, prev_desc.y + ((column - prev_desc.x) / (next_desc.x - prev_desc.x)) * (next_desc.y - prev_desc.y)); cur_desc = min(height-1.0f, cur_desc); // Add the new lines and copy the old ones if (descenders->size() == 0) cur_desc = height; if (ascenders->size() == 0) cur_asc = 0; if (cur_upper >= cur_lower) { cur_upper = max(cur_lower-1.f, 0.0f); } //printf("Liada %d %f %f,(%f,%f) (%f,%f)\n", column, cur_asc, cur_upper, prev_asc.x, prev_asc.y, next_asc.x, next_asc.y); //printf("Liada2 %d %f %f,(%f,%f) (%f,%f)\n", column, cur_desc, cur_lower, prev_desc.x, prev_desc.y, next_desc.x, next_desc.y); result_it(column, 0) = cur_asc; result_it(column, 3) = cur_desc; result_it(column, 1) = cur_upper; result_it(column, 2) = cur_lower; } delete ascenders; delete descenders; return result; } } //namespace OffLineTextPreprocessing } // namespace OCR april-ann-0.4.1/packages/ocr/off_line_text_preprocessing/c_src/off_line_text_preprocessing.h000066400000000000000000000043101263004425400325560ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Salvador España-Boquera, Jorge Gorbe-Moya, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef OFF_LINE_TEXT_PREPROCESSING_H #define OFF_LINE_TEXT_PREPROCESSING_H #include "image.h" #include "utilImageFloat.h" #include "pair.h" #include "vector.h" #include "geometry.h" /// Optical Character Recognition stuff. namespace OCR { namespace OffLineTextPreprocessing { Basics::MatrixFloat *add_asc_desc (Imaging::ImageFloat *img, Basics::MatrixFloat *line_mat, float v_treshold = 5, int h_threshold = 22.0f); Imaging::ImageFloat *normalize_size(Imaging::ImageFloat *source, float ascender_ratio, float descender_ratio, AprilUtils::vector ascenders, AprilUtils::vector upper_baseline, AprilUtils::vector lower_baseline, AprilUtils::vector descenders, int dst_height = -1, bool keep_aspect = false); Imaging::ImageFloat *normalize_image(Imaging::ImageFloat *source, int dst_height); Imaging::ImageFloat *normalize_size (Imaging::ImageFloat *source, Basics::MatrixFloat *line_mat, float ascender_ratio, float descender_ratio, int dst_height, bool keep_aspect); AprilUtils::vector* extract_points_from_image(Imaging::ImageFloat *pimg); } } #endif april-ann-0.4.1/packages/ocr/off_line_text_preprocessing/package.lua000066400000000000000000000022231263004425400256230ustar00rootroot00000000000000 package{ name = "ocr.off_line_text_preprocessing", version = "1.0", depends = { "util", "Image", "matrix", "interest_points" }, keywords = { "off_line_text_preprocessing" }, description = "Handwritten text preprocessing utilities", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_off_line_text_preprocessing.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_off_line_text_preprocessing.lua.cc", dest_dir = "build", } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/ocr/off_line_text_preprocessing/test/000077500000000000000000000000001263004425400245055ustar00rootroot00000000000000april-ann-0.4.1/packages/ocr/off_line_text_preprocessing/test/prueba-norm.png000066400000000000000000001535601263004425400274540ustar00rootroot00000000000000PNG  IHDR(v-y IDATx=gXTgNaޤ7Ql("-؈I61ULiƸMĘ]X v `az/~? 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C !S+@1̓ *Fc0:we d 7aNgϞ_~eϞ=Z @;@0~Wb0 `[=>2 Ec1sGnn.IE Bl`$IB:6D"u: =(H.Ho4m4O.\8w\&M ZJ"lh!???''য়~?f3A@,=ޒOi0 `xӃ`0ualFX,+ Iy`0 `(0&i֭EαG^^^A\ p^)dQm,Jj7TTTzNgXh H$JCd vڷo_HD<} `0 `5 I߻vjbH$yfpp0 a0'9 tkȩW:z%%s\n", src_name, dst_name) img_dest = ocr.off_line_text_preprocessing.normalize_from_matrix(img, top_prop, base_prop,line_mat) img_dest = img_dest:invert_colors() ImageIO.write(img_dest, dst_name) collectgarbage("collect") april-ann-0.4.1/packages/ocr/off_line_text_preprocessing/test/test_smooth.lua000066400000000000000000000031441263004425400275620ustar00rootroot00000000000000local img = ImageIO.read(arg[1]) local points_file = arg[2] w, h = img:geometry() local smoothed = matrix.fromTabFilename(points_file) local bodyMat = matrix(w,2) --Fill until first point local first_col = smoothed:get(1,1) local first_up = smoothed:get(1,2) local first_low = smoothed:get(1,3) local last_col = smoothed:get(smoothed:dim(1),1) local last_up = smoothed:get(smoothed:dim(1),2) local last_low = smoothed:get(smoothed:dim(1),3) for c=1, first_col do bodyMat:set(c, 1, first_up) bodyMat:set(c, 2, first_low) end for c = last_col, smoothed:dim(1) do bodyMat:set(c, 1, last_up) bodyMat:set(c, 2, last_low) end for i=1,smoothed:dim(1) do local col = smoothed:get(i,1) local top = smoothed:get(i,2) local lower = smoothed:get(i,3) bodyMat:set(col,1,top) bodyMat:set(col,2,lower) end local finalMat = ocr.off_line_text_preprocessing.add_asc_desc(img:to_grayscale():invert_colors(), bodyMat) local img2 = img:clone() for i = 1, finalMat:dim(1) do local asc = math.max(0,math.round(finalMat:get(i,1))) local desc = math.min(h-2,math.round(finalMat:get(i,4))) local upper = math.max(0,finalMat:get(i,2)) local lower = math.min(h-2,finalMat:get(i,3)) print(i,asc, desc, w, h) img:putpixel(i,asc,1,0,0); img:putpixel(i,desc, 0,1,0); img:putpixel(i,upper,1,0,1); img:putpixel(i,lower, 0,0,1); end imgNorm = ocr.off_line_text_preprocessing.normalize_from_matrix(img2:to_grayscale():invert_colors(), 0.1,0.2,finalMat,40) finalMat:toTabFilename("prueba.mat") ImageIO.write(img, "prueba.png") ImageIO.write(imgNorm:invert_colors(), "prueba-norm.png") print (bodyMat) april-ann-0.4.1/packages/tied_model_manager/000077500000000000000000000000001263004425400207525ustar00rootroot00000000000000april-ann-0.4.1/packages/tied_model_manager/lua_src/000077500000000000000000000000001263004425400224025ustar00rootroot00000000000000april-ann-0.4.1/packages/tied_model_manager/lua_src/tied_model_manager.lua000066400000000000000000000053361263004425400267130ustar00rootroot00000000000000local tied_model_manager,tied_model_manager_methods = class("tied_model_manager") _G.tied_model_manager = tied_model_manager -- global environment ---------------------------- -- Constructor ---------------------------- function tied_model_manager:constructor(tiedlist_file) self.tiedlist = {} self.name2id = {} self.id2name = {} local id = 1 for line in tiedlist_file:lines() do local tokens = string.tokenize(line) if tokens[2] then self.name2id[tokens[1]] = self.name2id[tokens[2]] else self.name2id[tokens[1]] = id self.id2name[id] = tokens[1] id = id + 1 end self.tiedlist[tokens[1]] = tokens[2] or tokens[1] end end function tied_model_manager_methods:get_model(phone) return self.tiedlist[phone] end -- Searchs a triphone. search_triphone("a","b","c") looks for -- "a-b+c", falling back to diphones and monophones if it's not -- found function tied_model_manager_methods:search_triphone(left, phone, right) local selected if left and right then -- both contexts -- If triphone matches, OK. Else down to diphones and so on. if self.tiedlist[left.."-"..phone.."+"..right] then selected=left.."-"..phone.."+"..right elseif self.tiedlist[left.."-"..phone] then selected=left.."-"..phone elseif self.tiedlist[phone.."+"..right] then selected=phone.."+"..right elseif self.tiedlist[phone] then selected=phone else error("can't find triphone for "..left.."-"..phone.."+"..right) end elseif (not left) and right then -- Right context only if self.tiedlist[phone.."+"..right] then selected=phone.."+"..right elseif self.tiedlist[phone.."+sil"] then selected=phone.."+sil" elseif self.tiedlist[phone] then selected=phone else error("can't find triphone for (nil)-"..phone.."+"..right) end elseif left and (not right) then -- Left context only if self.tiedlist[left.."-"..phone] then selected=left.."-"..phone elseif self.tiedlist["sil-"..phone] then selected="sil-"..phone elseif self.tiedlist[phone] then selected=phone else error("can't find triphone for "..left.."-"..phone.."+(nil)") end else -- Monophone if self.tiedlist[phone] then selected=phone else error("can't find triphone for (nil)-"..phone.."+(nil)") end end return self.tiedlist[selected] end function tied_model_manager_methods:search_triphone_sequence(sequence) local result = {} for i=1,#sequence do local left = nil local right = nil if i>1 then left = sequence[i-1] end if i<#sequence then right = sequence[i+1] end table.insert(result, self:search_triphone(left, sequence[i], right)) end return result end april-ann-0.4.1/packages/tied_model_manager/package.lua000066400000000000000000000011651263004425400230530ustar00rootroot00000000000000 package{ name = "tied_model_manager", version = "1.0", depends = { "util" }, keywords = { "tied_model_manager" }, description = "", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "build", depends = "init", use_timestamp = true, luac{ orig_dir = "lua_src", dest_dir = "build", }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/trainable/000077500000000000000000000000001263004425400171145ustar00rootroot00000000000000april-ann-0.4.1/packages/trainable/lua_src/000077500000000000000000000000001263004425400205445ustar00rootroot00000000000000april-ann-0.4.1/packages/trainable/lua_src/qlearning.lua000066400000000000000000000264751263004425400232450ustar00rootroot00000000000000local trainable_qlearning_trainer,trainable_qlearning_trainer_methods = class("trainable.qlearning_trainer") trainable = trainable or {} -- global environment trainable.qlearning_trainer = trainable_qlearning_trainer -- global environment local md = matrix.dict ----------------------------- -- QLEARNING TRAINER CLASS -- ----------------------------- function trainable_qlearning_trainer:constructor(t) local params = get_table_fields( { sup_trainer = { isa_match=trainable.supervised_trainer, mandatory=true }, discount = { type_match="number", mandatory=true, default=0.6 }, lambda = { type_match="number", mandatory=true, default=0.6 }, gradients = { mandatory=false, default={} }, traces = { mandatory=false, default={} }, noise = { mandatory=false, default=ann.components.base() }, clampQ = { mandatory=false }, nactions = { mandatory=false, type_match="number" }, }, t) local tr = params.sup_trainer local thenet = tr:get_component() local weights = tr:get_weights_table() local optimizer = tr:get_optimizer() self.tr = tr self.thenet = thenet self.weights = weights self.optimizer = optimizer self.gradients = params.gradients self.traces = params.traces self.discount = params.discount self.lambda = params.lambda self.noise = params.noise self.nactions = params.nactions or thenet:get_output_size() self.clampQ = params.clampQ assert(self.nactions > 0, "nactions must be > 0") end -- PRIVATE METHOD -- updates the weights given the previous state, the action, the current state -- and the observed reward local function trainable_qlearning_trainer_train(self, prev_state, prev_action, state, reward) local noise = self.noise local weights = self.weights local thenet = self.thenet local optimizer = self.optimizer local gradients = self.gradients local traces = self.traces local nactions = self.nactions local discount = self.discount local lambda = self.lambda local clampQ = self.clampQ -- add random noise if given noise:reset(1) local prev_state = noise:forward(prev_state, true) noise:reset(0) local state = noise:forward(state, true) local error_grad = matrix(1, nactions):zeros() local needs_gradient = optimizer:needs_property("gradient") local loss,Qsp,Qs loss,gradients,Qsp,Qs,expected_Qsa = optimizer:execute(function(weights, it) assert(not it or it == 0) if weights ~= self.weights then thenet:build{ weights = weights } end thenet:reset(it) local Qsp = thenet:forward(state) local Qs = thenet:forward(prev_state,true) local Qsa = Qs:get(1, prev_action) local delta = reward + discount * Qsp:max() - Qsa local diff = delta local loss = 0.5 * diff * diff if needs_gradient then error_grad:set(1, prev_action, -diff) thenet:backprop(error_grad) gradients:zeros() gradients = thenet:compute_gradients(gradients) if traces:size() == 0 then for name,g in pairs(gradients) do traces[name] = matrix.as(g):zeros() end end md.scal( traces, lambda*discount ) md.axpy( traces, 1.0, gradients ) return loss,traces,Qsp,Qs,expected_Qsa else return loss,nil,Qsp,Qs,expected_Qsa end end, weights) self.gradients = gradients return loss,Qsp,Qs,expected_Qsa end -- takes the previos action, the current state (ANN input) and the reward, -- updates the ANN weights and returns the current output Q(state,a); -- this method updates on-line, using eligibility traces function trainable_qlearning_trainer_methods:one_step(action, state, reward) local Qsp if self.prev_state then local loss,Qs,expected_Qsa loss,Qsp,Qs,expected_Qsa = trainable_qlearning_trainer_train(self, self.prev_state, action, state, reward) self.Qprob = (self.Qprob or 0) + math.log(Qs:get(1,action)) -- printf("%8.2f Q(s): %8.2f %8.2f %8.2f E(Q(s)): %8.2f ACTION: %d REWARD: %6.2f LOSS: %8.4f MP: %.4f %.4f\n", -- -self.Qprob, -- Qs:get(1,1), Qs:get(1,2), Qs:get(1,3), -- expected_Qsa, -- action, reward, loss, -- self.tr:norm2("w."), self.tr:norm2("b.")) else self.noise:reset(0) local state = self.noise:forward(state,true) Qsp = self.thenet:forward(state) end self.prev_state = state return Qsp end -- returns an object where you can add several (state, action, next_state, -- reward) batches, and at the end, build a pair of input/output datasets for -- supervised training function trainable_qlearning_trainer_methods:get_batch_builder() return trainable.qlearning_trainer.batch_builder(self) end -- begins a new sequence of training function trainable_qlearning_trainer_methods:reset() self.prev_state = nil self.traces:zeros() self.Qprob = 0 end function trainable_qlearning_trainer_methods:calculate(...) return self.tr:calculate(...) end function trainable_qlearning_trainer_methods:randomize_weights(...) return self.tr:randomize_weights(...) end function trainable_qlearning_trainer_methods:set_option(...) return self.tr:set_option(...) end function trainable_qlearning_trainer_methods:set_layerwise_option(...) return self.tr:set_layerwise_option(...) end function trainable_qlearning_trainer_methods:get_option(...) return self.tr:get_option(...) end function trainable_qlearning_trainer_methods:has_option(...) return self.tr:has_option(...) end function trainable.qlearning_trainer.load(filename) return util.deserialize(filename) end function trainable_qlearning_trainer_methods:save(filename,format) util.serialize(self, filename, format) end function trainable_qlearning_trainer_methods:ctor_name() return "trainable.qlearning_trainer" end function trainable_qlearning_trainer_methods:ctor_params() return { sup_trainer = self.tr, noise = self.noise, discount = self.discount, lambda = self.lambda, traces = self.traces, gradients = self.gradients, clampQ = self.clampQ, } end ------------------------------------------------------------------------------ -- the batch object helps to implement NFQ algorithm: -- -- http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.72.1193&rep=rep1&type=pdf -- -- Martin Riedmiller, Neural Fitted Q Iteration - First Experiences -- with a Data Efficient Neural Reinforcement Learning Method, ECML 2005 local trainable_batch_builder,trainable_batch_builder_methods = class("trainable.qlearning_trainer.batch_builder") trainable = trainable or {} -- global environment trainable.qlearning_trainer = trainable.qlearning_trainer or {} -- global environment trainable.qlearning_trainer.batch_builder = trainable_batch_builder -- global environment function trainable_batch_builder:constructor(qlearner) self.qlearner = qlearner self.batch = {} end function trainable_batch_builder_methods:add(prev_state, output, action, reward) assert(isa(prev_state, matrix), "Needs a matrix as 1st argument") assert(isa(prev_state, matrix), "Needs a matrix as 2nd argument") assert(type(action) == "number", "Needs a number as 3rd argument") assert(type(reward) == "number", "Needs a matrix as 4th argument") table.insert(self.batch, { prev_state:clone():rewrap(prev_state:size()), action, reward, output:clone():rewrap(output:size()), }) if self.state_size then assert(self.state_size == prev_state:size(), "Found different state sizes") end self.state_size = prev_state:size() end function trainable_batch_builder_methods:compute_dataset_pair() assert(self.state_size and self.state_size>0, "Several number of adds is needed") local discount = self.qlearner.discount local inputs = matrix(#self.batch, self.state_size) local outputs = matrix(#self.batch, self.qlearner.nactions):zeros() local mask = outputs:clone() local mask_row local Qs local state local acc_reward = 0 for i=#self.batch,1,-1 do local prev_state,action,reward,output = table.unpack(self.batch[i]) -- acc_reward = reward + discount * acc_reward Qs = outputs:select(1,i,Qs):set(action,acc_reward) mask_row = mask:select(1,i,mask_row):set(action,1) -- state = inputs:select(1,i):copy(prev_state) end if self.qlearner.clampQ then outputs:map(self.qlearner.clampQ) end return dataset.matrix(inputs),dataset.matrix(outputs),dataset.matrix(mask) end function trainable_batch_builder_methods:size() return #self.batch end ------------------------------------------------------------------------------- trainable.qlearning_trainer.strategies = {} trainable.qlearning_trainer.strategies.make_epsilon_greedy = function(actions, epsilon, rnd) assert(type(actions) == "table", "Needs an actions table as 1st argument") assert(#actions > 1, "#actions must be > 1") local epsilon = epsilon or 0.1 local rnd = rnd or random() local ambiguous_rel_diff = 0.1 return function(output) local coin = rnd:rand() local max,action = output:max() local min = output:min() local diff = max - min local rel_diff = diff / max if coin < epsilon or rel_diff < ambiguous_rel_diff then action = rnd:choose(actions) end return action end end trainable.qlearning_trainer.strategies.make_epsilon_decresing = function(actions, epsilon, decay, rnd) assert(type(actions) == "table", "Needs an actions table as 1st argument") local epsilon = epsilon or 0.1 local decay = decay or 0.9 local rnd = rnd or random() return function(output) local coin = rnd:rand() local max,action = output:max() local min = output:min() local diff = max - min local rel_diff = diff / (max + min) if coin < epsilon or rel_diff < 0.01 then action = rnd:choose(actions) end epsilon = epsilon * decay return action end end trainable.qlearning_trainer.strategies.make_softmax = function(actions,rnd) assert(type(actions) == "table", "Needs an actions table as 1st argument") local rnd = rnd or random() return function(output) assert(math.abs(1-output:sum()) < 1e-03, "Softmax strategy needs normalized outputs") local dice = random.dice(output:toTable()) local action = dice:thrown(rnd) return action end end april-ann-0.4.1/packages/trainable/lua_src/supervised.lua000066400000000000000000001650711263004425400234520ustar00rootroot00000000000000------------------------------- -- LOCAL AUXILIARY FUNCTIONS -- ------------------------------- local math = math local table = table local string = string -- local ipairs = ipairs local pairs = pairs local assert = assert -- local type = type local april_assert = april_assert local is_a = class.is_a local iterator = iterator local get_table_fields = get_table_fields local md = matrix.dict local MAX_SIZE_WO_COLLECT_GARBAGE = 400*1024*1024 -- 400 MB ----------------------------------------- ------------------------------ -- SUPERVISED_TRAINER CLASS -- ------------------------------ local trainable_supervised_trainer,trainable_supervised_trainer_methods = class("trainable.supervised_trainer", aprilio.lua_serializable) trainable = trainable or {} -- global environment trainable.supervised_trainer = trainable_supervised_trainer -- global environment april_set_doc(trainable.supervised_trainer, { class = "class", summary = "Supervised machine learning trainer", description ={ "This class implements methods useful to", "train, evalute and modify contents of", "ANN components or similar supervised learning", "models.", "IMPORTANT: Any method of this class could be overwritten", "on object instances, and the overwritten methods will be", "copied by clone method. Example:", "t = trainable.supervised_trainer(ann.components.base())", "t.train_step=function() print(\"Hola\") end", }, }) ------------------------------------------------------------------------ trainable_supervised_trainer.constructor = april_doc{ class = "method", summary = "Constructor", description ={"Constructor of the supervised_trainer class.", "This class implements methods useful to", "train, evalute and modify contents of", "ANN components or similar supervised learning", "models.", "If the component is in build state, the", "constructed trainer is in build state also.", }, params = { "ANN component or similar supervised learning model", "Loss function [optional]", "Bunch size (mini batch) [optional]", "An optimizer [option], by default is ann.optimizer.sgd", { "A gradient smoothing boolean flag [optional], by default", "it is true.", "This parameter scales the gradients depending in the", "bunch_size and in the number of times the weight was used", }, { "A gradient exploding limit [optional], by default", "it is false. This parameter can be false/nil or a number indicating", "the 2-norm limit of gradients, it can be useful to avoid gradient", "exploding in optimizers like adadelta.", }, }, outputs = { "Instantiated object" }, } .. function (self, ...) if select('#',...) == 1 and type(select(1,...)) == "table" then -- Loading from a previously saved object, the first argument is a table local t = select(1,...) local model = t.model local connections = t.connections local loss = t.loss local bunch_size = t.bunch_size local optimizer = t.optimizer local smooth_gradients = (t.smooth_gradients==nil or t.smooth_gradients) local max_gradients_norm = t.max_gradients_norm trainable.supervised_trainer.constructor(self, model, loss, bunch_size, optimizer, smooth_gradients, max_gradients_norm) local weights = connections -- if not is_a(connections, matrix.dict) then -- weights = matrix.dict() -- for name,wdata in pairs(connections) do -- local m = wdata -- if not is_a(m, matrix) then -- m = wdata.w:rewrap(wdata.output,wdata.input) -- end -- weights:insert(name,m:clone()) -- end -- end self:build{ weights = weights } else -- Constructor of a new object local ann_component,loss_function,bunch_size,optimizer,smooth_gradients,max_gradients_norm = ... local optimizer = optimizer or ann.optimizer.sgd() local smooth_gradients = (smooth_gradients==nil or smooth_gradients) local max_gradients_norm = max_gradients_norm if loss_function and not is_a(loss_function, ann.loss) then error("The second parameter must be an instance of ann.loss") end if optimizer and not is_a(optimizer, ann.optimizer) then error("The fourth parameter must be an instance of ann.optimizer") end if bunch_size and not tonumber(bunch_size) then error("The third parameter must be a number") end self.ann_component = assert(ann_component,"Needs an ANN component object") self.loss_function = loss_function or false self.optimizer = optimizer self.smooth_gradients = smooth_gradients self.max_gradients_norm = max_gradients_norm self.weights_table = {} self.components_table = {} self.component2weights_dict = {} self.weights2component_dict = {} self.weights_order = {} self.components_order = {} self.bunch_size = bunch_size or false self.weight_grads = {} end end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.get_component = april_doc{ class = "method", summary = "Returns an instance of ann.components", outputs = { "An instance of ann.components" }, } .. function(self) return self.ann_component end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.set_loss_function = april_doc{ class = "method", summary = "Modifies the loss function property", params = { "Loss function" }, } .. function(self, loss_function) assert(is_a(loss_function, ann.loss), "Needs an instance of ann.loss") self.loss_function = loss_function end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.get_loss_function = april_doc{ class = "method", summary = "Modifies the loss function property", params = { "Loss function" }, } .. function(self) return self.loss_function end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.set_optimizer = april_doc{ class = "method", summary = "Modifies the optimizer property", params = { "An instance of ann.optimizer" }, } .. function(self, optimizer) assert(is_a(optimizer, ann.optimizer), "Needs an instance of ann.optimizer") self.optimizer = optimizer end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.get_optimizer = april_doc{ class = "method", summary = "Returns the optimizer property", outputs = { "An instance of ann.optimizer" }, } .. function (self) return self.optimizer end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.set_option = april_doc{ class = "method", summary = "Sets a global option of the optimizer", params = { "An string with the option name", "A number with the value", }, } .. function(self, name,value) local opt = assert(self.optimizer, "The optimizer has not been defined") opt:set_option(name,value) end trainable_supervised_trainer_methods.get_option = april_doc{ class = "method", summary = "Gets a global option of the optimizer", params = { "An string with the option name", }, outputs = { "A number with the option value", }, } .. function(self, name) local opt = assert(self.optimizer, "The optimizer has not been defined") return opt:get_option(name) end trainable_supervised_trainer_methods.has_option = april_doc{ class = "method", summary = "Returns true/false depending on the existence of a global option of the optimizer", params = { "An string with the option name", }, outputs = { "A boolean", }, } .. function(self, name) local opt = assert(self.optimizer, "The optimizer has not been defined") return opt:has_option(name) end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.set_layerwise_option = april_doc{ class = "method", summary = "Sets an specific weights layer option of the optimizer", description = { "Sets the value of an optimizer option specifying the", "layer name by a Lua regular expression, so the option is set", "for all weight layers which match the given name", }, params = { "An string with the Lua regular expression", "An string with the option name", "A number with the value", }, } .. function(self, layer_match, name, value) local N=0 local opt = assert(self.optimizer, "The optimizer has not been defined") for cnn_name,cnn in self:iterate_weights(layer_match) do opt:set_layerwise_option(cnn_name,name,value) N=N+1 end april_assert(N>0, "0 layers match the given layer_match= %s", layer_match) end trainable_supervised_trainer_methods.get_option_of = april_doc{ class = "method", summary = "Returns the optimizer option value for a given layer name", description = { "If the layer has a layer-wise option, it will be returned,", "otherwise the global option value will be returned", }, params = { "An string with the Lua regular expression", "An string with the option name", }, outputs = { "A number with the value", }, } .. function(self, layer_name, name) local opt = assert(self.optimizer, "The optimizer has not been defined") return opt:get_option_of(layer_name,name) end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.get_input_size = april_doc{ class = "method", summary = "Gets the input size of its component", outputs = { "The input size (a number)" }, } .. function(self) return self.ann_component:get_input_size() end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.get_output_size = april_doc{ class = "method", summary = "Gets the output size of its component", outputs = { "The output size (a number)" }, } .. function(self) return self.ann_component:get_output_size() end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.size = april_doc{ class = "method", summary = "Returns the model size (number of weights)", outputs = { "A number" }, } .. function(self) if not self.is_built then error("It is not build") end return md.size(self.weights_table) end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.set_max_gradients_norm = april_doc{ class = "method", summary = "Changes the max gradients norm parameter", outputs = { "The caller object" }, } .. function(self, max_gradients_norm) self.max_gradients_norm = max_gradients_norm return self end ------------------------------------------------------------------------ function trainable_supervised_trainer_methods:ctor_name() return "trainable.supervised_trainer" end function trainable_supervised_trainer_methods:ctor_params() assert(self.is_built, "The component is not built") return { model = self.ann_component, connections = self.weights_table, loss = self.loss_function, optimizer = self.optimizer, bunch_size = self.bunch_size, smooth_gradients = self.smooth_gradients, max_gradients_norm = self.max_gradients_norm, } end ------------------------------------------------------------------------ trainable.supervised_trainer.load = april_doc{ class = "function", summary = "Load the model and weights from a disk file", description = { "Load the model and connection weights stored at", "a disk file. The trainer is loaded at build state.", }, params = { "A filename string", "Loss function [optional]", "Bunch size (mini batch) [optional]", "An optimizer, instance of ann.optimizer [optional]", }, } .. function(filename, loss, bunch_size, optimizer) local obj = util.deserialize(filename) if type(obj) == "table" then fprintf(stderr, "LOADING A DEPRECATED OBJECT!!! Save it in the new format\n") -- OLD FORMAT LOADER obj = trainable.supervised_trainer(obj) end obj.bunch_size = bunch_size or obj.bunch_size obj.loss_function = loss or obj.loss_function obj.optimizer = optimizer or obj.optimizer return obj end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.count_components = april_doc{ class = "method", summary = "Count the number of components", params = { { "A match string: filter and count only components", "which match [optional], by default is '.*'" }, }, } .. function(self, match_string) local match_string = match_string or ".*" if not self.is_built then error("It is not build") end local count = 0 for i=1,#self.components_order do if self.components_order[i]:match(match_string) then count=count+1 end end return count end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.count_weights = april_doc{ class = "method", summary = "Count the number of connection weight objects", params = { { "A match string: filter and count only connections", "which match [optional], by default is '.*'" }, }, } .. function(self, match_string) local match_string = match_string or ".*" if not self.is_built then error("It is not build") end local count = 0 for i=1,#self.weights_order do if self.weights_order[i]:match(match_string) then count=count+1 end end return count end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.iterate_components = april_doc{ class = "method", summary = "Iterates over components", description = { "This method is an iterator function to be used at for", "loops: for name,component in trainer:iterate_components()", "do print(name,component) end", }, params = { { "A match string: filter and iterates only on components", "which match [optional], by default is '.*'" }, }, } .. function(self, match_string) local match_string = match_string or ".*" if not self.is_built then error("It is not build") end local pos = 0 return function() repeat pos = pos + 1 if pos > #self.components_order then return nil end until self.components_order[pos]:match(match_string) local name = self.components_order[pos] return name,self.components_table[name] end end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.iterate_weights = april_doc{ class = "method", summary = "Iterates over weight connection objects", description = { "This method is an iterator function to be used at for", "loops: for name,connections in trainer:iterate_weights()", "do print(name,component) end", }, params = { { "A match string: filter and count only connections", "which match [optional], by default is '.*'" }, }, } .. function(self, match_string) local match_string = match_string or ".*" if not self.is_built then error("It is not build") end local pos = 0 return function() repeat pos = pos + 1 if pos > #self.weights_order then return nil end until self.weights_order[pos]:match(match_string) local name = self.weights_order[pos] return name,self.weights_table[name] end end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.component = april_doc{ class = "method", summary = "Returns a component given its name", description = { "This method returns a component object", "which name is the given argument.", "This method is forbidden before build method is called.", "If an error is produced, it returns nil." }, params = { "A string with the component name" }, outputs = { "A component object" }, } .. function(self, str) if not self.is_built then error("Needs execution of build method") end return self.components_table[str] end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.weights = april_doc{ class = "method", summary = "Returns a connections object given its name", description = { "This method returns a connections object", "which name is the given argument.", "This method is forbidden before build method is called.", "If an error is produced, returns nil." }, params = { "A string with the connections name" }, outputs = { "An ann.connections object" }, } .. function(self, str) if not self.is_built then error("Needs execution of build method") end return self.weights_table[str] end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.get_weights_table = april_doc{ class = "method", summary = "Returns the table with all weights", outputs = { "A table with all the weights, indexed by names" }, } .. function(self) if not self.is_built then error("Needs execution of build method") end return self.weights_table end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.randomize_weights = april_doc{ class = "method", summary = "Initializes randomly model weights and biases", description = { "This method initialies the weights, following an uniform", "distribution, in the range [c*inf,c*sup].", "Constant c depends on fan-in and/or fan-out fields.", "If fan-in and fan-out are false, then c=1.", "If fan-in=true and fan-out=false, then c=1/sqrt(fanin).", "If fan-in=false and fan-out=true, then c=1/sqrt(fanout).", "If fan-in and fan-out are true, then c=1/sqrt(fanin + fanout).", }, params = { ["name_match"] = { "A match string [optional], if given, only the connection", "weights which match will be randomized", }, ["random"] = "A random object", ["inf"] = "Range inf value", ["sup"] = "Range sup value", ["use_fanin"] = "An [optional] boolean, by default false", ["use_fanout"] = "An [optional] boolean, by default false", }, } .. function(self, t) local params = get_table_fields( { name_match = { type_match="string", mandatory=false, default = nil }, random = { isa_match = random, mandatory = true }, inf = { type_match="number", mandatory = true }, sup = { type_match="number", mandatory = true }, use_fanin = { type_match="boolean", mandatory = false, default = false }, use_fanout = { type_match="boolean", mandatory = false, default = false }, }, t) assert(self.is_built, "Execute build method before randomize_weights") for i,wname in ipairs(self.weights_order) do if not params.name_match or wname:match(params.name_match) then local current_inf = params.inf local current_sup = params.sup local constant = 0 local connection = self.weights_table[wname] if params.use_fanin then constant = constant + ann.connections.get_input_size(connection) end if params.use_fanout then constant = constant + ann.connections.get_output_size(connection) end if constant > 0 then current_inf = current_inf / math.sqrt(constant) current_sup = current_sup / math.sqrt(constant) end ann.connections.randomize_weights(connection, { random = params.random, inf = current_inf, sup = current_sup }) end end end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.build = april_doc{ class = "method", summary = "Executes build method of the component", description = { "This method executes the build method of its", "ann_component property, and weights_order, weights_table,", "components_order and components_table properties are", "also built. The method returns two tables with the", "content of weights_table and components_table, in order", "to provide easy acces to components and connections.", }, params = { ["weights"] = "A table weights_name=>matrix [optional]", ["input"] = "The input size of the component [optional]", ["output"] = "The output size of the component [optional]", }, outputs = { "The caller object", "Weights table, associates weights_name=>matrix", "Components table, associates component_name => ann.components object", }, } .. function(self, t) local params = get_table_fields( { weights = { mandatory = false, default=nil, type_match="table" }, input = { type_match="number", mandatory = false, default=nil }, output = { type_match="number", mandatory = false, default=nil }, }, t or {}) self.weight_grads = {} self.weights_table = params.weights or {} -- BUILD CALL _, self.weights_table, self.components_table = self.ann_component:build{ input = params.input, output = params.output, weights = self.weights_table, } -- self.weights_order = iterator(table.keys(self.weights_table)):table() table.sort(self.weights_order) self.components_order = {} self.component2weights_dict = {} self.weights2component_dict = {} for name,c in pairs(self.components_table) do table.insert(self.components_order, name) if c:has_weights_name() then local wname = c:get_weights_name() self.component2weights_dict[name] = c:get_weights_name() self.weights2component_dict[wname] = self.weights2component_dict[wname] or {} table.insert(self.weights2component_dict[wname], c) end end table.sort(self.components_order) self.is_built = true return self,self.weights_table,self.components_table end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.get_weights_of = april_doc{ class = "method", summary = "Returns a the object connections related to given component name", params = { "A string with the component name" }, outputs = { "An instance of ann.connections" }, } .. function(self, name) return self.weights_table[self.component2weights_dict[name]] end trainable_supervised_trainer_methods.get_components_of = april_doc{ class = "method", summary = "Returns a table with the components related to given weights name", params = { "A string with the weights name" }, outputs = { "A table of ann.components instances" }, } .. function(self, wname) return self.weights2component_dict[wname] or {} end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.train_step = april_doc{ class = "method", summary = "Executes one training step", description = { "This method executes one training step of its component", "with the given pair input/target output.", "It returns the loss for the given pair of patterns and", "the gradient computed at component inputs.", }, params = { "A table with one input pattern or a token (with one or more patterns, usually a matrix)", "The corresponding target output pattern (table or token, usually a matrix)", "The loss function [optional]", "An optimizer [optional]", "The bunch size [optional]", "A smooth gradients boolean [optional]", "A mask token [optional] (usually a matrix)", "A max gradients norm [optional]", }, outputs = { "The mean of loss function at current batch", "A matrix with the loss of every given pattern", }, } .. function(self, input, target, loss, optimizer, bunch_size, smooth_gradients, mask, max_gradients_norm) if type(input) == "table" then input = matrix(input) end if type(target) == "table" then target = matrix(target) end if type(mask) == "table" then mask = matrix(mask) end local loss = loss or self.loss_function or error("Needs a loss object") local optimizer = optimizer or self.optimizer or error("Needs an optimizer object") local bunch_size = bunch_size or self.bunch_size or 1 local smooth_gradients = (smooth_gradients==nil or smooth_gradients) local max_gradients_norm = max_gradients_norm if mask then assert( is_a(mask, matrix) ) assert( is_a(target, matrix) ) target = target:clone():cmul(mask) end local has_average = optimizer:has_property("average") local needs_gradient = optimizer:needs_property("gradient") local tr_loss, _, tr_loss_matrix, average = optimizer:execute(function(weights, it) if weights ~= self.weights_table then self:build{ weights = weights } end local self = self local loss = loss local model = self.ann_component local grads = self.weight_grads local target = target local mask = mask model:reset(it) local output = model:forward(input, true) if mask then assert( is_a(output, matrix) ) assert( is_a(target, matrix) ) output = output:clone():cmul(mask) end local tr_loss,tr_loss_matrix tr_loss,tr_loss_matrix = loss:compute_loss(output, target) if not tr_loss_matrix then return nil end if needs_gradient then local gradient=model:backprop(loss:gradient(output,target)) -- md.zeros(grads) -- local grads = model:compute_gradients(grads) self.weight_grads = grads -- gradient smoothing if smooth_gradients then for name,mat in pairs(grads) do local N = mat:get_shared_count() N = ( N>0 and N) or 1 mat:scal( 1.0/math.sqrt(N * bunch_size) ) end end -- gradient explode control if max_gradients_norm then local gradients_norm = matrix.dict.norm2(grads) if gradients_norm > max_gradients_norm then local ratio = max_gradients_norm / gradients_norm matrix.dict.scal(grads, ratio) end end -- the loss, the gradients, and the loss matrix return tr_loss, grads, tr_loss_matrix else return tr_loss, nil, tr_loss_matrix end end, self.weights_table) if tr_loss_matrix then loss:accum_loss(tr_loss_matrix) end return tr_loss,tr_loss_matrix end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.validate_step = april_doc{ class = "method", summary = "Executes one validate step", description = { "This method performs one forward step and computes", "the loss for the given pair input/target output.", }, params = { "A table with one input pattern or a token (with one or more patterns, usually a matrix)", "The corresponding target output pattern (table or token, usually a matrix)", "The loss function [optional]", }, outputs = { "The mean of loss function at given batch", "A matrix with the loss of every pattern", }, } .. function(self, input, target, loss, mask) if type(input) == "table" then input = matrix(input) end if type(target) == "table" then target = matrix(target) end if type(mask) == "table" then mask = matrix(mask) end local model = self.ann_component local loss = loss or self.loss_function model:reset() local output = model:forward(input) if mask then assert( is_a(mask, matrix) ) assert( is_a(output, matrix) ) assert( is_a(target, matrix) ) output = output:clone():cmul(mask) target = target:clone():cmul(mask) end local tr_loss,tr_loss_matrix = loss:compute_loss(output, target) if tr_loss_matrix then loss:accum_loss(tr_loss_matrix) return tr_loss,tr_loss_matrix end end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.compute_gradients_step = april_doc{ class = "method", summary = "Executes one gradients computation step", params = { "A table with one input pattern or a token (with one or more patterns, usually a matrix)", "The corresponding target output pattern (table or token, usually a matrix)", "The loss function [optional].", "A table with matrices where to store the gradients [optional]", }, outputs = { "A table with the gradient matrices.", "The mean of loss function at given batch", "A matrix with the loss of each pattern.", }, } .. function(self, input, target, loss, weight_grads) if type(input) == "table" then input = matrix(input) end if type(target) == "table" then target = matrix(target) end local loss = loss or self.loss_function local weight_grads = weight_grads or {} local tr_loss,tr_loss_matrix,gradient self.ann_component:reset() local output = self.ann_component:forward(input, true) tr_loss,tr_loss_matrix = loss:compute_loss(output, target) if tr_loss_matrix then loss:accum_loss(tr_loss_matrix) gradient = loss:gradient(output, target) gradient = self.ann_component:backprop(gradient) -- md.zeros(weight_grads) -- weight_grads = self.ann_component:compute_gradients(weight_grads) return weight_grads,tr_loss,tr_loss_matrix end end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.grad_check_step = april_doc{ class = "method", summary = "Executes one gradients check step", params = { "A table with one input pattern or a token (with one or more patterns, usually a matrix)", "The corresponding target output pattern (table or token, usually a matrix)", "A boolean, true if you want high verbosity level [optional]", "The loss function [optional].", }, outputs = { "A boolean, true or false if the gradient is correct or not", }, } .. function(self, input, target, verbose, loss) if type(input) == "table" then input = matrix(input) end if type(target) == "table" then target = matrix(target) end local loss = loss or self.loss_function self.ann_component:reset() loss:reset() local output = self.ann_component:forward(input, true) local tr_loss,tr_loss_matrix = loss:compute_loss(output, target) if not tr_loss_matrix then return true end local gradient = loss:gradient(output, target) gradient=self.ann_component:backprop(gradient) self.weight_grads = self.ann_component:compute_gradients(self.weight_grads) local epsilond = 0.10 -- 10% relative error local epsilon = 1e-03 local ret = true local bunch_size = tr_loss_matrix:dim(1) local it = 1 -- local counts = iterator(self:iterate_weights()):map(function(name,cnn) return name,cnn:get_shared_count() end):table() for wname,cnn in self:iterate_weights() do collectgarbage("collect") local w = cnn -- The shared parameter has no effect in gradients check, only bunch_size local ratio = 1/bunch_size local ann_grads = self.weight_grads[wname] assert(w:is_contiguous(), "Unable to check grads of non-contiguous matrices") for i=1,w:size() do collectgarbage("collect") local orig_w = w:raw_get(w:offset() + i-1) w:raw_set(w:offset() + i-1, orig_w - epsilon) self.ann_component:reset(it) it=it+1 local loss_a = loss:compute_loss(self.ann_component:forward(input,true), target) w:raw_set(w:offset() + i-1, orig_w + epsilon) self.ann_component:reset(it) it=it+1 local loss_b = loss:compute_loss(self.ann_component:forward(input,true), target) w:raw_set(w:offset() + i-1, orig_w) local g = (loss_b - loss_a) / (2*epsilon) local ann_g = ann_grads:raw_get(i-1)*ratio if verbose then fprintf(io.stderr, "CHECK GRADIENT %s[%d], found %g, expected %g\n", wname, i-1, ann_g, g) end if math.abs(ann_g) > 2*epsilon or math.abs(g) > 2*epsilon then local abs_err = math.abs(ann_g - g) local err = 2*abs_err/(math.abs(ann_g) + math.abs(g)) if err > epsilond and abs_err > 2*epsilon then -- force backprop step self.ann_component:reset(it) loss:reset() local output = self.ann_component:forward(input, true) local tr_loss,tr_loss_matrix = loss:compute_loss(output, target) assert(tr_loss_matrix) local gradient = loss:gradient(output, target) self.ann_component:backprop(gradient) -- fprintf(io.stderr, "INCORRECT GRADIENT FOR %s[%d], found %g, expected %g ".. "(error %g, abs error %g)\n", wname, i-1, ann_g, g, err, abs_err) ret = false end end end end return ret end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.calculate = april_doc{ class = "method", summary = "Executes one forward", description = { "This method performs one forward step and returns", "the computed output for the given input.", }, params = { "A table with one input pattern, a matrix or a token (with one or more patterns, usually a matrix)", "A given bunch size [optional] if not given it will be setup to the number of patterns in the given input", }, outputs = { "A token with the computed output, usually a matrix", }, } .. function(self,input,bunch_size) if type(input) == "table" then input = matrix(1, input) end local bunch_size = bunch_size or input:dim(1) local N = input:dim(1) local result = matrix(N, self.ann_component:get_output_size()) local model = self.ann_component for i=1,math.ceil(N/bunch_size) do model:reset() local s = {(i-1)*bunch_size+1, math.min(i*bunch_size,N)} local current_input = input[{s,':'}] result[{s,':'}] = model:forward(current_input) end return result end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.train_dataset = april_doc{ class = "method", summary = "Executes one training epoch with a given dataset", description = { "This method performs one training epoch with a given", "dataset traversing patterns in order, and returns the", "mean loss of each training step.", "Each training step is performed with bunch_size patterns.", }, params = { ["input_dataset"] = "A dataset float or dataset token", ["output_dataset"] = "A dataset float or dataset token (target output)", ["mask_dataset"] = "A dataset float or dataset token (mask target output)", ["loss"] = "A loss function. It is [optional] if loss given at constructor", ["optimizer"] = "An optimizer. It is [optional] if optimizer is given at constructor", ["bunch_size"] = { "Bunch size (mini-batch). It is [optional] if bunch_size", "was set at constructor, otherwise it is mandatory.", }, }, outputs = { "A number with the mean loss of each training step", "A number with the sample variance of the loss", }, } .. april_doc{ class = "method", summary = "Executes one training epoch with shuffle", description = { "This method performs one training epoch with a given", "dataset traversing patterns in shuffle order, and returns the", "mean loss of each training step.", "Each training step is performed with bunch_size patterns.", }, params = { ["input_dataset"] = "A dataset float or dataset token", ["output_dataset"] = "A dataset float or dataset token (target output)", ["mask_dataset"] = "A dataset float or dataset token (mask target output)", ["shuffle"] = "A random object used to shuffle patterns before training", ["loss"] = "A loss function. It is [optional] if loss given at constructor", ["optimizer"] = "An optimizer. It is [optional] if optimizer is given at constructor", ["bunch_size"] = { "Bunch size (mini-batch). It is [optional] if bunch_size", "was set at constructor, otherwise it is mandatory.", }, }, outputs = { "A number with the mean loss of each training step", "A number with the sample variance of the loss", }, } .. april_doc{ class = "method", summary = "Executes one stochastic training epoch with replacement", description = { "This method performs one stochastic training epoch with a given", "dataset. Patterns are choosed randomly with replacement", "until a given replacement size. The", "mean loss of each training step is returned.", "Each training step is performed with bunch_size patterns.", }, params = { ["input_dataset"] = "A dataset float or dataset token", ["output_dataset"] = "A dataset float or dataset token (target output)", ["mask_dataset"] = "A dataset float or dataset token (mask target output)", ["shuffle"] = "A random object used to shuffle patterns before training", ["replacement"] = "A number with the size of replacement training", ["loss"] = "A loss function. It is [optional] if loss given at constructor", ["optimizer"] = "An optimizer. It is [optional] if optimizer is given at constructor", ["bunch_size"] = { "Bunch size (mini-batch). It is [optional] if bunch_size", "was set at constructor, otherwise it is mandatory.", }, }, outputs = { "A number with the mean loss of each training step", "A number with the sample variance of the loss", }, } .. april_doc{ class = "method", summary = "Executes one stochastic training epoch with distribution", description = { "This method performs one stochastic training epoch with a given", "set of datasets with different a-priory probabilities.", "Patterns are choosed randomly with replacement following", "given a-priori distribution, until a given replacement", "size. The mean loss of each training step is returned.", "Each training step is performed with bunch_size patterns.", }, params = { ["distibution"] = "An array of tables with input_dataset,".. " output_dataset and probability fields", ["shuffle"] = "A random object used to shuffle patterns before training", ["replacement"] = "A number with the size of replacement training", ["loss"] = "A loss function. It is [optional] if loss given at constructor", ["optimizer"] = "An optimizer. It is [optional] if optimizer is given at constructor", ["bunch_size"] = { "Bunch size (mini-batch). It is [optional] if bunch_size", "was set at constructor, otherwise it is mandatory.", }, ["smooth_gradients"] = "A smooth gradients boolean [optional]", ["max_gradients_norm"] = "A maximum gradients norm [optional]", }, outputs = { "A number with the mean loss of each training step", "A number with the sample variance of the loss", }, } .. function(self, t) local params = get_table_fields( { -- This following commented parameters will be checked by -- trainable.dataset_pair_iterator: -- -- shuffle = { isa_match = random, mandatory = false, default=nil }, -- replacement = { type_match = "number", mandatory = false, default=nil }, -- input_dataset = { mandatory = false, default=nil }, -- output_dataset = { mandatory = false, default=nil }, -- distribution = { type_match="table", mandatory = false, default=nil, -- getter = get_table_fields_ipairs{ -- input_dataset = { mandatory=true }, -- output_dataset = { mandatory=true }, -- probability = { type_match="number", -- mandatory=true }, -- }, -- }, bunch_size = { type_match = "number", mandatory = (self.bunch_size == false) }, loss = { isa_match = ann.loss, mandatory = (self.loss_function==false), default=self.loss_function }, optimizer = { isa_match = ann.optimizer, mandatory = (not self.optimizer), default=self.optimizer }, smooth_gradients = { type_match = "boolean", mandatory = false, default=self.smooth_gradients }, max_gradients_norm = { type_match = "number", mandatory = false, default=self.max_gradients_norm }, }, t, true) assert(self.is_built, "Execute build method before call this method") local loss = params.loss local optimizer = params.optimizer local smooth_gradients = params.smooth_gradients local max_gradients_norm = params.max_gradients_norm local mask_dataset = params.mask_dataset params.loss = nil params.optimizer = nil params.smooth_gradients = nil params.max_gradients_norm = nil params.mask_dataset = nil params.bunch_size = params.bunch_size or self.bunch_size local bunch_mb_size = params.bunch_size * self:size() * 4 -- set to ZERO the accumulated of loss loss:reset() if not mask_dataset then params.assert_input_size = self:get_input_size() params.assert_output_size = self:get_output_size() local k=0 for input_bunch,output_bunch,bunch_indexes in trainable.dataset_pair_iterator(params) do self:train_step(input_bunch, output_bunch, loss, optimizer, #bunch_indexes, smooth_gradients, nil, max_gradients_norm) k = k + bunch_mb_size if k > MAX_SIZE_WO_COLLECT_GARBAGE then collectgarbage("collect") k=0 end end else params.datasets = { params.input_dataset, params.output_dataset, mask_dataset } params.input_dataset = nil params.output_dataset = nil params.assert_pattern_sizes = { self:get_input_size(), self:get_output_size(), self:get_output_size() } local k=0 for input_bunch,output_bunch,mask_bunch,bunch_indexes in trainable.dataset_multiple_iterator(params) do self:train_step(input_bunch, output_bunch, loss, optimizer, #bunch_indexes, smooth_gradients, mask_bunch, max_gradients_norm) k = k + bunch_mb_size if k > MAX_SIZE_WO_COLLECT_GARBAGE then collectgarbage("collect") k=0 end end end return loss:get_accum_loss() end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.grad_check_dataset = april_doc{ class = "method", summary = "Executes gradient check with a given dataset", params = { ["input_dataset"] = "A dataset float or dataset token", ["output_dataset"] = "A dataset float or dataset token (target output)", ["loss"] = "A loss function. It is [optional] if loss given at constructor", ["bunch_size"] = { "Bunch size (mini-batch). It is [optional] if bunch_size", "was set at constructor, otherwise it is mandatory.", }, ["max_iterations"] = "Number [optional]", ["verbose"] = "A boolean, true if you want high verbosity [optiona]", }, outputs = { "A boolean", }, } .. function(self, t) local params = get_table_fields( { -- This following commented parameters will be checked by -- trainable.dataset_pair_iterator: -- -- input_dataset = { mandatory = false, default=nil }, -- output_dataset = { mandatory = false, default=nil }, bunch_size = { type_match = "number", mandatory = (self.bunch_size == false) }, loss = { isa_match = ann.loss, mandatory = (self.loss_function==false), default=self.loss_function }, verbose = { type_match = "boolean", mandatory = false, default=false }, }, t, true) assert(self.is_built, "Execute build method before call this method") local loss = params.loss local verbose = params.verbose params.loss = nil params.verbose = nil params.bunch_size = params.bunch_size or self.bunch_size params.assert_input_size = self:get_input_size() params.assert_output_size = self:get_output_size() -- set to ZERO the accumulated of loss loss:reset() local ret = true for input,output,bunch_indexes in trainable.dataset_pair_iterator(params) do if not self:grad_check_step(input, output, verbose, loss) then printf("Error processing pattern bunch: %s\n", table.concat(bunch_indexes, " ")) ret = false break end end return ret end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.validate_dataset = april_doc{ class = "method", summary = "Executes one validation epoch with a given dataset", description = { "This method performs one validation epoch with a given", "dataset traversing patterns in order, and returns the", "mean loss of each validate step.", "Each validate step is performed with bunch_size patterns.", }, params = { ["input_dataset"] = "A dataset float or dataset token", ["output_dataset"] = "A dataset float or dataset token (target output)", ["mask_dataset"] = "A dataset float or dataset token (mask target output)", ["loss"] = "A loss function. It is [optional] if loss given at constructor", ["bunch_size"] = { "Bunch size (mini-batch). It is [optional] if bunch_size", "was set at constructor, otherwise it is mandatory.", }, }, outputs = { "A number with the mean loss of each validate step", "A number with the sample variance of the loss", }, } .. april_doc{ class = "method", summary = "Executes one validation epoch with shuffle", description = { "This method performs one validation epoch with a given", "dataset traversing patterns in shuffle order, and returns the", "mean loss of each validate step.", "Each validate step is performed with bunch_size patterns.", }, params = { ["input_dataset"] = "A dataset float or dataset token", ["output_dataset"] = "A dataset float or dataset token (target output)", ["mask_dataset"] = "A dataset float or dataset token (mask target output)", ["shuffle"] = "A random object used to shuffle patterns before validate", ["loss"] = "A loss function. It is [optional] if loss given at constructor", ["bunch_size"] = { "Bunch size (mini-batch). It is [optional] if bunch_size", "was set at constructor, otherwise it is mandatory.", }, }, outputs = { "A number with the mean loss of each validate step", "A number with the sample variance of the loss", }, } .. april_doc{ class = "method", summary = "Executes one stochastic validation epoch with replacement", description = { "This method performs one stochastic validation epoch with a given", "dataset. Patterns are choosed randomly with replacement", "until a given replacement size. The", "mean loss of each validate step is returned.", "Each validate step is performed with bunch_size patterns.", }, params = { ["input_dataset"] = "A dataset float or dataset token", ["output_dataset"] = "A dataset float or dataset token (target output)", ["mask_dataset"] = "A dataset float or dataset token (mask target output)", ["shuffle"] = "A random object used to shuffle patterns before validate", ["replacement"] = "A number with the size of replacement validate", ["loss"] = "A loss function. It is [optional] if loss given at constructor", ["bunch_size"] = { "Bunch size (mini-batch). It is [optional] if bunch_size", "was set at constructor, otherwise it is mandatory.", }, }, outputs = { "A number with the mean loss of each validate step", "A number with the sample variance of the loss", }, } .. function(self, t) local params = get_table_fields( { -- In this case, we check all the given parameters, because all the -- dataset iteration schemes are not available for validate_dataset input_dataset = { mandatory = true }, output_dataset = { mandatory = true }, mask_dataset = { mandatory = false }, bunch_size = { type_match = "number", mandatory = (self.bunch_size == false) }, loss = { isa_match = ann.loss, mandatory = (self.loss_funcion==false), default=self.loss_function }, shuffle = { isa_match = random, mandatory = false, default=nil }, replacement = { type_match = "number", mandatory = false, default=nil }, }, t) assert(self.is_built, "Execute build method before call this method") -- ERROR CHECKING assert(params.input_dataset ~= not params.output_dataset, "input_dataset and output_dataset fields are mandatory together") assert(not params.input_dataset or not params.distribution, "input_dataset/output_dataset fields are forbidden with distribution") local loss = params.loss local mask_dataset = params.mask_dataset params.loss = nil params.mask_dataset = nil params.bunch_size = params.bunch_size or self.bunch_size local bunch_mb_size = params.bunch_size * self:size() * 4 -- set to ZERO the accumulated of loss loss:reset() if not mask_dataset then params.assert_input_size = self:get_input_size() params.assert_output_size = self:get_output_size() local k=0 for input_bunch,output_bunch in trainable.dataset_pair_iterator(params) do self:validate_step(input_bunch, output_bunch, loss) k = k + bunch_mb_size if k > MAX_SIZE_WO_COLLECT_GARBAGE then collectgarbage("collect") k=0 end end else params.datasets = { params.input_dataset, params.output_dataset, mask_dataset } params.input_dataset = nil params.output_dataset = nil params.assert_pattern_sizes = { self:get_input_size(), self:get_output_size(), self:get_output_size() } local k=0 for input_bunch,output_bunch in trainable.dataset_multiple_iterator(params) do self:validate_step(input_bunch, output_bunch, loss) k = k + bunch_mb_size if k > MAX_SIZE_WO_COLLECT_GARBAGE then collectgarbage("collect") k=0 end end end return loss:get_accum_loss() end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.use_dataset = april_doc{ class = "method", summary = "Computes forward with a given dataset ".. "provinding output dataset", description = { "This method performs forward with all patterns of the", "given input_dataset, storing outputs at an", "output_dataset with enough space.", "If output_dataset field is given, it must be prepared to", "store all input_dataset:numPatterns().", "If output_dataset field is nil, a new dataset will be", "constructed. The method returns the output_dataset in", "both cases.", "Each forward step is performed with bunch_size patterns.", }, params = { ["input_dataset"] = "A dataset float or dataset token", ["output_dataset"] = "A dataset float [optional].", ["bunch_size"] = { "Bunch size (mini-batch). It is [optional] if bunch_size", "was set at constructor, otherwise it is mandatory.", }, }, outputs = { "The output_dataset with input_dataset:numPatterns().", }, } .. function(self, t) local params = get_table_fields( { -- In this case, we check all the given parameters, because all the -- dataset iteration schemes are not available for use_dataset input_dataset = { mandatory = true }, output_dataset = { mandatory = false, default=nil }, bunch_size = { type_match = "number", mandatory = (self.bunch_size == false) }, }, t) assert(self.is_built, "Execute build method before call this method") local nump = params.input_dataset:numPatterns() local outsize = self.ann_component:get_output_size() if not params.output_dataset then params.output_dataset = dataset.matrix(matrix(nump, outsize)) end local result_ds = params.output_dataset if is_a(params.output_dataset, dataset) then params.output_dataset = dataset.token.wrapper(params.output_dataset) end if is_a(params.input_dataset, dataset) then params.input_dataset = dataset.token.wrapper(params.input_dataset) end local output_dataset = params.output_dataset params.bunch_size = params.bunch_size or self.bunch_size params.datasets = { params.input_dataset } params.assert_pattern_sizes = { self:get_input_size() } params.input_dataset, params.output_dataset = nil, nil local bunch_mb_size = params.bunch_size * self:size() * 4 local ann_component = self.ann_component local k=0 for input_bunch,bunch_indexes in trainable.dataset_multiple_iterator(params) do ann_component:reset() local output = ann_component:forward(input_bunch) output_dataset:putPatternBunch(bunch_indexes,output) k = k + bunch_mb_size if k > MAX_SIZE_WO_COLLECT_GARBAGE then collectgarbage("collect") k=0 end end return result_ds end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.show_weights = april_doc{ class = "method", summary = "Print connection weights (for debug purposes).", } .. function(self) for _,wname in pairs(self.weights_order) do local w = self.weights_table[wname]:toTable() print(wname, table.concat(w, " ")) end end ------------------------------------------------------------------------ trainable_supervised_trainer_methods.clone = april_doc{ class = "method", summary = "Returns a deep-copy of the object.", description = { "Returns a deep-copy of the object.", "This method copies user functions on given object instance,", "so user can overwrite any of methods in this class.", }, } .. function(self) local obj = trainable.supervised_trainer(self.ann_component:clone(), nil, self.bunch_size, nil, self.smooth_gradients, self.max_gradients_norm) if self.loss_function then obj:set_loss_function(self.loss_function:clone()) end if self.optimizer then obj:set_optimizer(self.optimizer:clone()) end if #self.weights_order > 0 then obj:build{ weights = md.clone(self.weights_table) } end -- add possible user functions for i,v in pairs(self) do if type(v) == "function" then obj[i] = v end end return obj end trainable_supervised_trainer_methods.norm2 = april_doc{ class = "method", summary = "Returns the maximum norm2 of the weights which name matches", params={ "A connection weights name Lua pattern string [optional], by default it is .*", }, outputs = { "A number with the maximum norm2", }, } .. function(self, match_string) local norm2 = 0 for _,cnn in self:iterate_weights(match_string) do norm2 = math.max(norm2, reduce(function(a,b) return math.max(a,b:norm2()) end, 0, cnn:sliding_window():iterate())) end return norm2 end function trainable_supervised_trainer_methods:train_holdout_validation(t) error("DEPRECATED: use the class trainable.train_holdout_validation") end function trainable_supervised_trainer_methods:train_wo_validation(t) error("DEPRECATED: use the class trainable.train_wo_validation") end april-ann-0.4.1/packages/trainable/lua_src/trainable.lua000066400000000000000000000674021263004425400232210ustar00rootroot00000000000000------------------------------- -- LOCAL AUXILIARY FUNCTIONS -- ------------------------------- local math = math local table = table local string = string -- local ipairs = ipairs local pairs = pairs local assert = assert -- local type = type local is_a = class.is_a local iterator = iterator local get_table_fields = get_table_fields local april_assert = april_assert ----------------------------------------- local MAX_SIZE_WO_COLLECT_GARBAGE=10*1024*1024 -- 10 MB ----------------------- -- TRAINABLE CLASSES -- ----------------------- ------------------------------------------------------------------------------- -------------------------------- -- DATASET_ITERATOR FUNCTIONS -- -------------------------------- trainable.dataset_pair_iterator = april_doc{ class = "function", summary = { "A function which returns an iterator which", "does a dataset pair loop (input_dataset and output_dataset)" }, description ={ "This class is useful to implement a loop over a dataset.", "It implements different loop schemes, in all the cases", "returning a bunch_size patterns.", "It admits the following traversals: sequential, shuffled,", "shuffled with replacement, shuffled with distribution.", }, } .. function(t) local params = get_table_fields( { input_dataset = { mandatory = false, default=nil }, output_dataset = { mandatory = false, default=nil }, distribution = { type_match="table", mandatory = false, default=nil, getter = get_table_fields_ipairs{ input_dataset = { mandatory=true }, output_dataset = { mandatory=true }, probability = { type_match="number", mandatory=true }, }, }, bunch_size = { type_match = "number", mandatory = true }, shuffle = { isa_match = random, mandatory = false, default=nil }, replacement = { type_match = "number", mandatory = false, default=nil }, assert_input_size = { type_match = "number", mandatory = false, default=0 }, assert_output_size = { type_match = "number", mandatory = false, default=0 }, }, t) -- ERROR CHECKING assert(params.input_dataset ~= not params.output_dataset, "input_dataset and output_dataset fields are mandatory together") assert(not params.input_dataset or not params.distribution, "input_dataset/output_dataset fields are forbidden with distribution") assert(params.assert_input_size ~= not params.assert_output_size, "assert_input_size and assert_output_size are mandatory together") if params.input_dataset then params.datasets = { params.input_dataset, params.output_dataset } params.input_dataset, params.output_dataset = nil end if params.distribution then iterator(ipairs(params.distribution)): apply(function(_,data) data.datasets = { data.input_dataset, data.output_dataset } data.input_dataset, data.output_dataset = nil, nil end) end if params.assert_input_size then params.assert_pattern_sizes = { params.assert_input_size, params.assert_output_size } params.assert_input_size, params.assert_output_size = nil, nil end return trainable.dataset_multiple_iterator(params) end ---------------------------- trainable.dataset_multiple_iterator = april_doc{ class = "function", summary = { "A function which returns an iterator which", "does a dataset loop through multiple datasets" }, description ={ "This function is useful to implement a loop over a dataset.", "It implements different loop schemes, in all the cases", "returning a token with bunch_size patterns.", "It admits the following traversals: sequential, shuffled,", "shuffled with replacement, shuffled with distribution.", }, } .. function(t) local cgarbage = collectgarbage cgarbage("collect") local assert = assert local table = table local iterator = iterator local april_assert = april_assert -- local TOO_LARGE_NUMPATTERNS = 1000000 local params = get_table_fields( { datasets = { mandatory = false, default=nil }, distribution = { type_match="table", mandatory = false, default=nil, getter = get_table_fields_ipairs{ datasets = { mandatory=true }, probability = { type_match="number", mandatory=true }, }, }, bunch_size = { type_match = "number", mandatory = true }, shuffle = { isa_match = random, mandatory = false, default=nil }, replacement = { type_match = "number", mandatory = false, default=nil }, assert_pattern_sizes = { type_match = "table", mandatory = false, default={ } }, }, t) -- ERROR CHECKING assert(not params.datasets or not params.distribution, "datasets field is forbidden with distribution") assert(params.datasets or params.distribution, "datasets or distribution are needed") -- local bunch_size = params.bunch_size -- local to_dataset_token = function(ds_table) local nump return iterator(ipairs(ds_table)): map(function(_,ds) if nump then april_assert(nump == ds:numPatterns(), "Incorrect number of patterns, expected %d, found %d", nump, ds:numPatterns()) else nump = ds:numPatterns() end return is_a(ds,dataset) and dataset.token.wrapper(ds) or ds end): table(), nump end -- TRAINING TABLES -- for each pattern, index in dataset local ds_idx_func if params.distribution then -- Training with distribution: given a table of datasets the patterns are -- sampled following the given apriory probability assert(params.shuffle,"shuffle is mandatory with distribution") assert(params.replacement,"replacement is mandatory with distribution") params.datasets = { } local aprioris = {} local sizes = {} local sums = { 0 } local num_ds -- params.datasets = iterator(ipairs(params.distribution.datasets)): map(function() return dataset.token.union() end):table() -- for i,v in ipairs(params.distribution) do local nump if num_ds then april_assert(num_ds == #v.datasets, "Incorrect number of datasets, expected %d, found %d", num_ds, #v.datasets) else num_ds = #v.datasets end v.datasets = to_dataset_token(v.datasets) table.insert(aprioris, v.probability) table.insert(sizes, nump) table.insert(sums, sums[#sums] + nump) -- iterator(ipairs(params.datasets)): apply(function(k,union_ds) union_ds:push_back(v.datasets[k]) end) end -- for i,v in ipairs(params.distribution) -- generate training tables local dice = random.dice(aprioris) local i = 1 ds_idx_func = function() if i <= params.replacement then i=i+1 local whichclass=dice:thrown(params.shuffle) local idx=params.shuffle:randInt(1,sizes[whichclass]) return idx+sums[whichclass] end end else -- if params.distribution then ... else -- local num_patterns params.datasets,num_patterns = to_dataset_token(params.datasets) -- generate training tables depending on training mode (replacement, -- shuffled, or sequential) if params.replacement then assert(params.shuffle,"shuffle is mandatory with replacement") local i=1 ds_idx_func = function() if i <= params.replacement then i=i+1 return params.shuffle:randInt(1,num_patterns) end end elseif params.shuffle then assert(num_patterns < TOO_LARGE_NUMPATTERNS, "The number of patterns is too large, use a shorter replacement, or non-shuffled training") local ds_idx_table = params.shuffle:shuffle(num_patterns) local i=0 ds_idx_func = function() i=i+1 if i<= #ds_idx_table then return ds_idx_table[i] end end else local i=0 ds_idx_func = function() i=i+1 if i<= num_patterns then return i end end end end -- SANITY CHECK iterator(ipairs(params.assert_pattern_sizes)): apply(function(k,psize) local ds_psize = params.datasets[k]:patternSize() april_assert(psize == 0 or psize == ds_psize, "Incorrect patternSize at dataset %d, found %d, expected %d", k, ds_psize, psize) end) -- -- ITERATOR USING ds_idx_func local k=0 local bunch_indexes = {} if #params.datasets > 2 then local pattern_size = iterator(ipairs(params.datasets)):select(2): call('patternSize'):reduce(math.add, 0) local bunch_mb_size = bunch_size * pattern_size * 4 return function() local ds_idx_func = ds_idx_func local bunch_indexes = bunch_indexes local table = table local insert = table.insert table.clear(bunch_indexes) repeat local idx = ds_idx_func() table.insert(bunch_indexes, idx) until not idx or #bunch_indexes==bunch_size -- end condition, return nil if #bunch_indexes == 0 then cgarbage("collect") return end local data = {} for i,v in ipairs(params.datasets) do data[i] = v:getPatternBunch(bunch_indexes) end insert(data, bunch_indexes) k=k+bunch_mb_size if k >= MAX_SIZE_WO_COLLECT_GARBAGE then cgarbage("collect") k=0 end return table.unpack(data) end elseif #params.datasets == 2 then local ds1,ds2 = params.datasets[1],params.datasets[2] local pattern_size = ds1:patternSize() + ds2:patternSize() local bunch_mb_size = bunch_size * pattern_size * 4 return function() local ds_idx_func = ds_idx_func local bunch_indexes = bunch_indexes local table = table local insert = table.insert -- general case table.clear(bunch_indexes) repeat local idx = ds_idx_func() insert(bunch_indexes, idx) until not idx or #bunch_indexes==bunch_size -- end condition, return nil if #bunch_indexes == 0 then cgarbage("collect") return end local bunch1 = ds1:getPatternBunch(bunch_indexes) local bunch2 = ds2:getPatternBunch(bunch_indexes) k=k+bunch_mb_size if k >= MAX_SIZE_WO_COLLECT_GARBAGE then cgarbage("collect") k=0 end return bunch1,bunch2,bunch_indexes end else -- ( #params.datasets == 1 ) local ds1 = params.datasets[1] local pattern_size = ds1:patternSize() local bunch_mb_size = bunch_size * pattern_size * 4 return function() local ds_idx_func = ds_idx_func local bunch_indexes = bunch_indexes local table = table local insert = table.insert -- general case table.clear(bunch_indexes) repeat local idx = ds_idx_func() insert(bunch_indexes, idx) until not idx or #bunch_indexes==bunch_size -- end condition, return nil if #bunch_indexes == 0 then cgarbage("collect") return end local bunch1 = ds1:getPatternBunch(bunch_indexes) k=k+bunch_mb_size if k >= MAX_SIZE_WO_COLLECT_GARBAGE then cgarbage("collect") k=0 end return bunch1,bunch_indexes end end end ------------------------------------------------------------------------------- ------------------------------------ -- TRAIN_HOLDOUT_VALIDATION CLASS -- ------------------------------------ local train_holdout, train_holdout_methods = class("trainable.train_holdout_validation", aprilio.lua_serializable) trainable = trainable or {} -- global environment trainable.train_holdout_validation = train_holdout -- global environment april_set_doc(trainable.train_holdout_validation, { class = "class", summary = "Training class using holdout validation", description ={ "This training class defines a train_func which", "follows a training schedule based on validation error or", "in number of epochs. Method execute receives a function", "which trains one epoch and returns the trainer object,", "the training loss and the validation loss. This method", "returns true in case the training continues, or false if", "the stop criterion is true.", }, }) april_set_doc(trainable.train_holdout_validation, { class = "method", summary = "Constructor", description ={ "Constructor of the train_holdout_validation class.", }, params = { epochs_wo_validation = { "Number of epochs from start where the validation is", "ignored [optional], by default it is 0", }, min_epochs = "Minimum number of epochs for training [optional]. By default it is 0", max_epochs = "Maximum number of epochs for training", stopping_criterion = { "A predicate function which", "returns true if stopping criterion, false otherwise.", "Some basic criteria are implemented at", "trainable.stopping_criteria table.", "The criterion function is called as", "stopping_criterion({ current_epoch=..., best_epoch=...,", "best_val_error=..., train_error=...,", "validation_error=... }). [optional] By default it is max_epochs criterion.", }, tolerance = { "The tolerance>=0 is the minimum relative difference to", "take the current validation loss as the best [optional],", "by default it is 0.", }, first_epoch = "The first epoch number [optional]. By default it is 0.", }, outputs = { "Instantiated object" }, }) function train_holdout:constructor(t,saved_state) local params = get_table_fields( { epochs_wo_validation = { mandatory=false, type_match="number", default=0 }, min_epochs = { mandatory=true, type_match="number", default=0 }, max_epochs = { mandatory=true, type_match="number" }, tolerance = { mandatory=true, type_match="number", default=0 }, stopping_criterion = { mandatory=true, type_match="function", default = function() return false end }, first_epoch = { mandatory=false, type_match="number", default=1 }, }, t) assert(params.tolerance >= 0, "tolerance < 0 is forbidden") local saved_state = saved_state or {} self.params = params self.state = { current_epoch = saved_state.current_epoch or 0, train_error = saved_state.train_error or math.huge, validation_error = saved_state.validation_error or math.huge, best_epoch = saved_state.best_epoch or 0, best_val_error = saved_state.best_val_error or math.huge, best = saved_state.best or nil, last = saved_state.last or nil, } end train_holdout_methods.execute = april_doc{ class = "method", summary = "Runs one training epoch", description ={ "This method executes one training epoch. It receives an", "epoch function which where the user trains the model,", "and which returns the trained model, the train loss, and the", "validation loss.", }, params = { { "A function which trains a model and returns the trained model,", "the training loss and the validation loss", }, "Variadic list of arguments for the function [optional]", }, outputs = { "True or false, indicating if the training continues or not" }, } .. function(self, epoch_function, ...) local params = self.params local state = self.state -- check max epochs if state.current_epoch >= params.max_epochs then return false end -- check stopping criterion if ( state.current_epoch > params.min_epochs and params.stopping_criterion(state) ) then return false end -- compute one training step by using epoch_function state.current_epoch = state.current_epoch + 1 state.last, state.train_error, state.validation_error = epoch_function(...) assert(state.last and state.train_error and state.validation_error, "Needs a function which returns three values: a model, training error and validation error") -- update with the best model if ( state.validation_error < state.best_val_error or state.current_epoch <= params.epochs_wo_validation ) then local abs_error = math.abs(state.best_val_error - state.validation_error) local rel_error = abs_error / math.abs(state.best_val_error) if state.best_val_error == math.huge or rel_error > params.tolerance then state.best_epoch = state.current_epoch state.best_val_error = state.validation_error state.best = util.clone( state.last ) end end return true end train_holdout_methods.set_param = april_doc{ class = "method", summary = "Modifies one parameter of which was given at construction", params = { "The parameter name", "The parameter value", }, } .. function(self,name,value) april_assert(self.params[name], "Param %s not found", name) self.params[name] = value end train_holdout_methods.get_param = april_doc{ class = "method", summary = "Returns the value of a param", params = { "The parameter name", }, outputs = { "The paremter value" }, } .. function(self,name) return self.params[name] end train_holdout_methods.get_state = april_doc{ class = "method", summary = "Returns the state of the training", outputs = { "Current epoch", "Train loss", "Validation loss", "Best epoch", "Best epoch validation loss", "Best trained model", "Last trained model", }, } .. function(self) local state = self.state return state.current_epoch, state.train_error, state.validation_error, state.best_epoch, state.best_val_error, state.best, state.last end train_holdout_methods.get_state_table = april_doc{ class = "method", summary = "Returns the state table of the training", outputs = { current_epoch = "Current epoch", train_error = "Train loss", validation_error = "Validation loss", best_epoch = "Best epoch", best_val_error = "Best epoch validation loss", best = "Best trained model", last = "Last trained model", }, } .. function(self) return self.state end train_holdout_methods.get_state_string = april_doc{ class = "method", summary = "Returns the state of the training in string format, for printing", outputs = { { "A string with the format ('%5d %.6f %.6f %5d %.6f',", "current_epoch,train_error,validation_error,best_epoch,best_val_error)" } }, } .. function(self) local state = self.state return string.format("%5d %.6f %.6f %5d %.6f", state.current_epoch, state.train_error, state.validation_error, state.best_epoch, state.best_val_error) end train_holdout_methods.is_best = april_doc{ class = "method", summary = "Returns if current epoch is the best epoch", outputs = { "A boolean" }, } .. function(self) local state = self.state return state.current_epoch == state.best_epoch end function train_holdout_methods:ctor_name() return "trainable.train_holdout_validation" end function train_holdout_methods:ctor_params() return self.params, self.state end train_holdout_methods.save = function() error("Removed, use util.serialize()") end trainable.train_holdout_validation.load = util.deserialize ------------------------------------------------------------------------------- ------------------------------------ -- TRAIN_HOLDOUT_VALIDATION CLASS -- ------------------------------------ local train_wo_validation,train_wo_validation_methods = class("trainable.train_wo_validation", aprilio.lua_serializable) trainable = trainable or {} -- global environment trainable.train_wo_validation = train_wo_validation -- global environment april_set_doc(trainable.train_wo_validation, { class = "class", summary = "Training class without validation", description ={ "This training class defines a train_func which", "follows a training schedule based on training error or", "in number of epochs. Method execute receives a function", "which trains one epoch and returns the trainer object and", "the training loss. This method", "returns true in case the training continues, or false if", "the stop criterion is true.", }, }) april_set_doc(trainable.train_wo_validation, { class = "method", summary = "Constructor", description ={ "Constructor of the train_wo_validation class.", }, params = { min_epochs = "Minimum number of epochs for training [optional]. By default it is 0,", max_epochs = "Maximum number of epochs for training", percentage_stopping_criterion = "A number [optional]. By default it is 0.01", first_epoch = "The first epoch number [optional]. By default it is 1", }, outputs = { "Instantiated object" }, }) function train_wo_validation:constructor(t,saved_state) local params = get_table_fields( { min_epochs = { mandatory=true, type_match="number", default=0 }, max_epochs = { mandatory=true, type_match="number" }, percentage_stopping_criterion = { mandatory=true, type_match="number", default = 0.01 }, first_epoch = { mandatory=false, type_match="number", default=1 }, }, t) local saved_state = saved_state or {} self.params = params self.state = { current_epoch = saved_state.current_epoch or 0, train_error = saved_state.train_error or math.huge, train_improvement = saved_state.train_improvement or math.huge, last = saved_state.last or nil, } end train_wo_validation_methods.execute = april_doc{ class = "method", summary = "Runs one training epoch", description ={ "This method executes one training epoch. It receives an", "epoch function which where the user trains the model,", "and which returns the trained model and the train loss.", }, params = { { "A function which trains a model and returns the trained model", "and the training loss", }, "Variadic list of arguments for the function [optional]", }, outputs = { "True or false, indicating if the training continues or not" }, } .. function(self, epoch_function, ...) local params = self.params local state = self.state -- stopping criterion if (state.current_epoch > params.min_epochs and state.train_improvement < params.percentage_stopping_criterion) then return false end -- check max epochs if state.current_epoch >= params.max_epochs then return false end -- compute one training step by using epoch_function state.current_epoch = state.current_epoch + 1 local model,tr_err = epoch_function(...) assert(model and tr_err, "Needs a function which returns two values: a model and training error") -- local prev_tr_err = state.train_error local tr_improvement if state.current_epoch > 1 then tr_improvement = (prev_tr_err - tr_err)/prev_tr_err else tr_improvement = math.huge end state.train_error = tr_err state.train_improvement = tr_improvement state.last = model return true end train_wo_validation_methods.set_param = april_doc{ class = "method", summary = "Modifies one parameter of which was given at construction", params = { "The parameter name", "The parameter value", }, } .. function(self,name,value) april_assert(self.params[name], "Param %s not found", name) self.params[name] = value end train_wo_validation_methods.get_param = april_doc{ class = "method", summary = "Returns the value of a param", params = { "The parameter name", }, outputs = { "The paremter value" }, } .. function(self,name) return self.params[name] end train_wo_validation_methods.get_state = april_doc{ class = "method", summary = "Returns the state of the training", outputs = { "Current epoch", "Train loss", "Train relative improvement", "Last trained model", }, } .. function(self) local state = self.state return state.current_epoch, state.train_error, state.train_improvement,state.last end train_wo_validation_methods.get_state_table = april_doc{ class = "method", summary = "Returns the state table of the training", outputs = { current_epoch = "Current epoch", train_error = "Train loss", train_improvement = "Train relative improvement", last = "Last trained model", }, } .. function(self) return self.state end train_wo_validation_methods.get_state_string = april_doc{ class = "method", summary = "Returns the state of the training in string format, for printing", outputs = { { "A string with the format ('%5d %.6f %.6f',", "current_epoch,train_error,train_improvement)" } }, } .. function(self) local state = self.state return string.format("%5d %.6f %.6f", state.current_epoch, state.train_error, state.train_improvement) end function train_wo_validation_methods:ctor_name() return "trainable.train_wo_validation" end function train_wo_validation_methods:ctor_params() return self.params, self.state end train_wo_validation_methods.save = function() error("Removed, use util.serialize()") end trainable.train_wo_validation.load = util.deserialize ------------------------------------------------------------------------------- ------------------------- -- STOPPING CRITERIA -- ------------------------- trainable.stopping_criteria = trainable.stopping_criteria or {} april_set_doc(trainable.stopping_criteria, { class = "namespace", summary = "Table with built-in stopping criteria", }) -------------------------------------------------------------------------- trainable.stopping_criteria.make_max_epochs_wo_imp_absolute = april_doc{ class = "function", summary = "Returns a stopping criterion based on absolute loss.", description = { "This function returns a stopping criterion function", "which returns is true if current_epoch - best_epoch >= abs_max." }, params = { "Absolute maximum difference (abs_max)" }, outputs = { "A stopping criterion function" }, } .. function(abs_max) local f = function(params) return (params.current_epoch - params.best_epoch) >= abs_max end return f end -------------------------------------------------------------------------- trainable.stopping_criteria.make_max_epochs_wo_imp_relative = april_doc{ class = "function", summary = "Returns a stopping criterion based on relative loss.", description = { "This function returns a stopping criterion function", "which returns is true if not", "current_epoch/best_epoch < rel_max." }, params = { "Relative maximum difference (rel_max)" }, outputs = { "A stopping criterion function" }, } .. function(rel_max) local f = function(params) return not (params.current_epoch/params.best_epoch < rel_max) end return f end april-ann-0.4.1/packages/trainable/package.lua000066400000000000000000000024151263004425400212140ustar00rootroot00000000000000 package{ name = "trainable", version = "1.0", depends = { "util", "dataset", "random", "ann", "ann.loss", "ann.optimizer" }, keywords = { "Trainable" }, description = "Define a wrapper with common methods of trainable models", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test.lua", }, }, }, target{ name = "provide", depends = "init", -- copy{ file= "c_src/*.h", dest_dir = "include" }, -- provide_bind{ file = "binding/bind_trainablesuper.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, -- object{ -- file = "c_src/*.cc", -- include_dirs = "${include_dirs}", -- dest_dir = "build", -- }, luac{ orig_dir = "lua_src", dest_dir = "build", }, -- build_bind{ -- file = "binding/bind_trainablesuper.lua.cc", -- dest_dir = "build", -- } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/trainable/test/000077500000000000000000000000001263004425400200735ustar00rootroot00000000000000april-ann-0.4.1/packages/trainable/test/.gitignore000066400000000000000000000000401263004425400220550ustar00rootroot00000000000000best_out.txt best_qlearning.net april-ann-0.4.1/packages/trainable/test/qlearning_test.lua000066400000000000000000000140511263004425400236160ustar00rootroot00000000000000-- MOUNTAIN CAR TEST (http://en.wikipedia.org/wiki/Mountain_Car) local strategies = trainable.qlearning_trainer.strategies local num_runs = 10 local num_of_episodes = 101 local max_episode_length = 1000 local epsilon = 0.5 -- probability of random action, epsilon greedy local epsilon_decay = 0.9999 local learning_rate = 0.1 local momentum = 0.4 local weight_decay = 1e-04 local L1_norm = 0.0 local max_norm_penalty = 4 local winf = -1 local wsup = 1 local bunch_size = 1024 local discount = 1.0 -- discount-rate parameter local lambda = 0.9 -- trace-decay parameter local weights_random = random(12384) local exploration_random = random(2394) local shuffle_random = random(23824) ------------------------------------------------------------------------------ -- two dimensions: velocity, position local function start_state() return matrix(1,2,{0.0, -0.5}) end local function stop_condition(state) return state:get(1,2) >= 0.6 end -- three actions: left, neutral, right local LEFT,NEUTRAL,RIGHT=1,2,3 local actions = { LEFT, NEUTRAL, RIGHT } local function update(state, action) local action_values = { -1, 0, 1 } local next_state = matrix.as(state) local p = state:get(1,2) local v = state:get(1,1) + action_values[action] * 0.001 + math.cos(3 * p) * -0.0025 local p = p + v next_state:set(1,1, math.clamp(v, -0.07, 0.07)) next_state:set(1,2, math.clamp(p, -1.2, 0.6)) local reward if stop_condition(next_state) then reward = 10 else reward = 0 end return next_state,reward end ------------------------------------------------------------------------------ local best_length = max_episode_length/2 local best_net for run=1,num_runs do ------------------------------------------------------------------------------ local take_action = strategies.make_epsilon_decresing(actions, epsilon, epsilon_decay, exploration_random) local thenet = ann.mlp.all_all.generate("2 inputs %d softmax" % { #actions }) local sup_trainer = trainable.supervised_trainer(thenet, ann.loss.mse(), bunch_size, ann.optimizer.rprop()):build() local qtrainer = trainable.qlearning_trainer{ sup_trainer = sup_trainer, discount = discount, lambda = lambda, clampQ = function(v) return math.clamp(v,0.0,1.0) end, } qtrainer:randomize_weights{ inf = winf, sup = wsup, random = weights_random, } if qtrainer:has_option("learning_rate") then qtrainer:set_option("learning_rate", learning_rate) end if qtrainer:has_option("momentum") then qtrainer:set_option("momentum", momentum) end if qtrainer:has_option("weight_decay") then qtrainer:set_option("weight_decay", weight_decay) qtrainer:set_option("L1_norm", L1_norm) qtrainer:set_option("max_norm_penalty", max_norm_penalty) for _,hyp in ipairs{ "weight_decay", "L1_norm", "max_norm_penalty" } do if qtrainer:has_option(hyp) then qtrainer:set_layerwise_option("b.*", hyp, 0) end end end local best for episode=1,num_of_episodes do collectgarbage("collect") -- RUN EPISODE qtrainer:reset() -- clear traces and other stuff local batch = qtrainer:get_batch_builder() local state,action = start_state(),NEUTRAL local output = qtrainer:calculate(state) local i = 0 local acc_reward = 0 while not stop_condition(state) and i < max_episode_length do local next_state,reward = update(state, action) acc_reward = acc_reward + reward if episode < num_of_episodes then batch:add(state, output, action, reward) end output = qtrainer:calculate(next_state) --qtrainer:one_step(action, state, reward) if episode < num_of_episodes then action = take_action(output) else _,action = output:max() end --print(i, table.concat(output:toTable(), " "), reward, action, table.concat(state:toTable(), " ")) -- i = i + 1 -- state = next_state end print(run, episode, i, acc_reward) if episode < num_of_episodes then -- BATCH TRAIN local in_ds,out_ds,mask_ds = batch:compute_dataset_pair() -- for ipat,pat in out_ds:patterns() do print(ipat, table.concat(pat, " "), table.concat(mask_ds:getPattern(ipat), " ")) end local train_func = trainable.train_wo_validation{ max_epochs = (acc_reward > 0 and 100) or 10, min_epochs = (acc_reward > 0 and 40) or 2, percentage_stopping_criterion = 0.01, } while train_func:execute(function() local tr_error = sup_trainer:train_dataset{ input_dataset = in_ds, output_dataset = out_ds, mask_dataset = mask_ds, shuffle = shuffle_random, } return sup_trainer,tr_error end) do -- print(train_func:get_state_string()) end else -- if episode < num_of_episodes then ... if i < best_length then best_length = i best_net = sup_trainer:clone() end end -- if episode < num_of_episodes then ... else ... end end -- SHOW BEST RUN if best_net then best_net:save("best_qlearning.net") local f = io.open("best_out.txt", "w") local state,action = start_state(),NEUTRAL local output = best_net:calculate(state) local i = 0 while not stop_condition(state) do local next_state,reward = update(state, action) output = best_net:calculate(next_state) _,action = output:max() fprintf(f, "BEST %d %s %s %f %d\n", i, table.concat(state:toTable(), " "), table.concat(output:toTable(), " "), reward, action) -- i = i + 1 -- state = next_state end f:close() end april-ann-0.4.1/packages/trainable/test/test.lua000066400000000000000000000076411263004425400215650ustar00rootroot00000000000000digits_image = ImageIO.read(string.get_path(arg[0]).."../../../EXAMPLES/digits.png") m1 = digits_image:to_grayscale():invert_colors():matrix() -- TRAINING -- -- a simple matrix for the desired output train_input = dataset.matrix(m1, { patternSize = {16,16}, offset = {0,0}, numSteps = {80,10}, stepSize = {16,16}, orderStep = {1,0} }) m2 = matrix(10,{1,0,0,0,0,0,0,0,0,0}) -- a circular dataset which advances with step -1 train_output = dataset.matrix(m2, { patternSize = {10}, offset = {0}, numSteps = {800}, stepSize = {-1}, circular = {true} }) -- VALIDATION -- val_input = dataset.matrix(m1, { patternSize = {16,16}, offset = {1280,0}, numSteps = {20,10}, stepSize = {16,16}, orderStep = {1,0} }) val_output = dataset.matrix(m2, { patternSize = {10}, offset = {0}, numSteps = {200}, stepSize = {-1}, circular = {true} }) bunch_size = 32 thenet = ann.mlp.all_all.generate("256 inputs 128 tanh 10 log_softmax") if util.is_cuda_available() then thenet:set_use_cuda(true) end trainer = trainable.supervised_trainer(thenet, ann.loss.multi_class_cross_entropy(), bunch_size, ann.optimizer.adadelta(), true, -- smooth parameter 15) -- max gradients norm parameter trainer:build() -- trainer:set_option("weight_decay", 1e-04) -- we avoid weight_decay in bias trainer:set_layerwise_option("b.", "weight_decay", 0) trainer:randomize_weights{ random = random(52324), use_fanin = true, use_fanout = true, inf = -1, sup = 1, } training_data = { input_dataset = train_input, output_dataset = train_output, shuffle = random(25234), } validation_data = { input_dataset = val_input, output_dataset = val_output, } clock = util.stopwatch() clock:go() --print("# Epoch Training Validation") -- print("Epoch Training Validation") train_func = trainable.train_holdout_validation{ min_epochs=10, max_epochs = 20, stopping_criterion = trainable.stopping_criteria.make_max_epochs_wo_imp_relative(1.1), tolerance = 0.1, } -- training loop tmpname = os.tmpname() while train_func:execute(function() local tr = trainer:train_dataset(training_data) local va = trainer:validate_dataset(validation_data) print(tr,va) return trainer,tr,va end) do util.serialize({ train_func, training_data.shuffle }, tmpname) train_func,training_data.shuffle = table.unpack((util.deserialize(tmpname))) end util.serialize(train_func, tmpname) train_func = util.deserialize(tmpname) os.remove(tmpname) os.remove(tmpname..".bak") clock:stop() cpu,wall = clock:read() num_epochs = train_func:get_state_table().current_epoch clock:stop() cpu,wall = clock:read() best = train_func:get_state_table().best local val_error,val_variance=best:validate_dataset{ input_dataset = val_input, output_dataset = val_output, loss = ann.loss.zero_one(10) } local out_ds = best:use_dataset{ input_dataset = val_input } best:use_dataset{ input_dataset = val_input, output_dataset = out_ds } for input,bunch_indexes in trainable.dataset_multiple_iterator{ datasets = { val_input }, bunch_size = 1 } do local out = best:calculate(input) local target = matrix(out:dim(1),out:dim(2), out_ds:getPattern(bunch_indexes[1])) assert(out:equals(target)) end --printf("# Wall total time: %.3f per epoch: %.3f\n", wall, wall/num_epochs) --printf("# CPU total time: %.3f per epoch: %.3f\n", cpu, cpu/num_epochs) --printf("# Validation error: %f +- %f\n", val_error, val_variance) local img = ann.connections.input_filters_image(best:weights("w1"), {16,16}) ImageIO.write(img, "/tmp/filters.png") util.serialize(trainer, "wop.lua") april-ann-0.4.1/profile_build_scripts/000077500000000000000000000000001263004425400177635ustar00rootroot00000000000000april-ann-0.4.1/profile_build_scripts/METADATA.lua000066400000000000000000000014221263004425400216450ustar00rootroot00000000000000return { description = "A Pattern Recognizer In Lua", version = "0.4.1", prefix = os.getenv("PREFIX") or "/usr", url = "https://github.com/pakozm/april-ann", version_flags = { '-DAPRILANN_VERSION_MAJOR=0', '-DAPRILANN_VERSION_MINOR=4', '-DAPRILANN_VERSION_RELEASE=1', }, disclaimer_strings = { '"APRIL-ANN v" TOSTRING(APRILANN_VERSION_MAJOR) "." TOSTRING(APRILANN_VERSION_MINOR) "." TOSTRING(APRILANN_VERSION_RELEASE) " Copyright (C) 2012-2015 DSIC-UPV, CEU-UCH"', string.format('"Compiled at %s, timestamp %u"', os.date(), os.time()), '"This program comes with ABSOLUTELY NO WARRANTY; for details see LICENSE.txt.\\nThis is free software, and you are welcome to redistribute it\\nunder certain conditions; see LICENSE.txt for details."', }, } april-ann-0.4.1/profile_build_scripts/build_debug_NOBLAS.lua000066400000000000000000000053651263004425400240020ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_NOBLAS_debug" local packages = dofile "profile_build_scripts/package_list.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann.debug", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="yes", use_lstrip = "no", use_readline="yes", optimization = "no", add_git_metadata = "yes", platform = "unix", extra_flags={ "-pg", "-DNO_POOL", "-DNO_BLAS", "-DNOOMP", "-fPIC", }, extra_libs={ "-fPIC", "-pg", "-rdynamic", "-Wl,-E -ldl" }, shared_extra_libs={ "-shared", "-llua5.2", "-I/usr/include/lua5.2", }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/build_debug_atlas.lua000066400000000000000000000055561263004425400241320ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_debug" local packages = dofile "profile_build_scripts/package_list.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann.debug", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="yes", use_lstrip = "no", use_readline="yes", optimization = "no", add_git_metadata = "yes", platform = "unix", extra_flags={ "-pg", "-fopenmp", "-fPIC", }, extra_libs={ "-fPIC", "-pg", "-lpthread", "-lblas", "-lcblas", "-latlas", "-L/opt/lib", -- "-lgfortran", "-rdynamic", "-llapack_atlas", "-llapacke", }, shared_extra_libs={ "-shared", "-llua5.2", "-I/usr/include/lua5.2", }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, create_shared_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/build_debug_cuda_and_mkl.lua000066400000000000000000000065161263004425400254240ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_debug_cuda_and_mkl" local packages = dofile "profile_build_scripts/package_list.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann.debug", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="yes", use_lstrip = "no", use_readline="yes", optimization = "no", add_git_metadata = "yes", platform = "unix64+cuda", ignore_cuda = false, extra_flags={ -- For Intel MKL :) "-DUSE_MKL", "-I/opt/MKL/include", -------------------- "-march=native", "-msse", "-pg", "-DNO_OMP", "-DNO_POOL", -- "-fPIC", -- For CUDA "-DUSE_CUDA", -- "-I/usr/local/cuda/include", -- "-L/usr/local/cuda/lib", }, extra_libs={ -- "-fPIC", "-pg", "-rdynamic", -- For Intel MKL :) "-L/opt/MKL/lib", "-lmkl_intel_lp64", "-Wl,--start-group", "-lmkl_intel_thread", "-lmkl_core", "-Wl,--end-group", "/opt/MKL/lib/libiomp5.a", -- For CUBLAS "-lcublas", -- For CUDA "-lcuda", "-lcudart", "-lcusparse", -- "-lpthread", }, shared_extra_libs={ "-shared", "-llua5.2", "-I/usr/include/lua5.2", }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/build_debug_homebrew.lua000066400000000000000000000066371263004425400246370ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_debug_homebrew" local packages = dofile "profile_build_scripts/package_list.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann.debug", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="yes", use_lstrip = "no", use_readline="yes", optimization = "no", add_git_metadata = "yes", platform = "unix", extra_flags={ "-D__HOMEBREW__", "-mtune=native", "-msse", "-DUSE_XCODE", "-F/System/Library/Frameworks/Accelerate.framework", "-pg", "-DNO_OMP", "-fPIC", "-I/usr/local/opt/readline/include", -- homebrew, change if necessary }, extra_libs={ "-L/usr/local/lib", -- homebrew, change if necessary "-L/usr/local/opt/readline/lib", -- homebrew, change if necessary "-lpthread", "-lpng", "/System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate", "/System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib", "/System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libLAPACK.dylib", "-pg", "-rdynamic", "-fPIC", }, shared_extra_libs={ "-flat_namespace", "-bundle", "-llua", "-I/usr/include/lua5.2", }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/build_debug_macports.lua000066400000000000000000000064071263004425400246520ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_debug_macports" local packages = dofile "profile_build_scripts/package_list.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann.debug", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="yes", use_lstrip = "no", use_readline="yes", optimization = "no", add_git_metadata = "yes", platform = "unix", extra_flags={ "-mtune=native", "-msse", "-DUSE_XCODE", "-F/System/Library/Frameworks/Accelerate.framework", "-pg", "-DNO_OMP", "-fPIC", }, extra_libs={ "-L/opt/local/lib", -- macports, change if necessary "-lpthread", "-lpng", "/System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate", "/System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib", "/System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libLAPACK.dylib", "-pg", "-rdynamic", "-fPIC", }, shared_extra_libs={ "-flat_namespace", "-bundle", assert(io.popen("pkg-config --cflags --libs 'lua >= 5.2'"):read("*l")) }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/build_debug_mkl.lua000066400000000000000000000061101263004425400235740ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_debug_mkl" local packages = dofile "profile_build_scripts/package_list.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann.debug", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="yes", use_lstrip = "no", use_readline="yes", optimization = "no", add_git_metadata = "yes", platform = "unix", extra_flags={ -- For Intel MKL :) "-DUSE_MKL", "-I/opt/MKL/include", -------------------- "-march=native", "-msse", "-pg", "-fopenmp", "-fPIC", }, extra_libs={ "-fPIC", "-pg", "-lpthread", "-rdynamic", -- For Intel MKL :) "-L/opt/MKL/lib", "-lmkl_intel_lp64", "-Wl,--start-group", "-lmkl_intel_thread", "-lmkl_def", "-lmkl_core", "-Wl,--end-group", "-liomp5" }, shared_extra_libs={ "-shared", "-llua5.2", "-I/usr/include/lua5.2", }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, create_shared_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/build_debug_no_omp.lua000066400000000000000000000055631263004425400243130ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_debug_no_omp" local packages = dofile "profile_build_scripts/package_list.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann.debug", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="yes", use_lstrip = "no", use_readline="yes", optimization = "no", add_git_metadata = "yes", platform = "unix", extra_flags={ "-pg", "-DNO_OMP", "-fPIC", }, extra_libs={ "-fPIC", "-pg", "-lpthread", "-lblas", "-lcblas", "-latlas", "-L/opt/lib", "-lgfortran", "-rdynamic", "-llapack_atlas", "-llapacke", }, shared_extra_libs={ "-shared", "-llua5.2", "-I/usr/include/lua5.2", }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, create_shared_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/build_debug_pi.lua000066400000000000000000000055031263004425400234260ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_debug_pi" local packages = dofile "profile_build_scripts/package_list.pi.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="yes", use_lstrip = "no", use_readline="yes", optimization = "no", add_git_metadata = "yes", platform = "unix", extra_flags={ "-pg", "-DNO_POOL", "-DNO_OMP", "-DNO_MM_MALLOC", "-fPIC", }, extra_libs={ "-fPIC", "-lpthread", "-lblas", "-lcblas", "-latlas", "-rdynamic", "-llapack_atlas", "-llapacke", }, shared_extra_libs={ "-shared", "-llua5.2", "-I/usr/include/lua5.2", }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/build_release_NOBLAS.lua000066400000000000000000000054341263004425400243310ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_NOBLAS_release" local packages = dofile "profile_build_scripts/package_list.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="no", use_lstrip = "yes", use_readline="yes", optimization = "yes", add_git_metadata = "yes", platform = "unix", extra_flags={ "-march=native", "-msse", "-DNDEBUG", "-DNO_BLAS", "-DNOOMP", "-fPIC", }, extra_libs={ "-fPIC", "-rdynamic", "-Wl,-E -ldl" }, shared_extra_libs={ "-shared", "-llua5.2", "-I/usr/include/lua5.2", }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, create_shared_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/build_release_atlas.lua000066400000000000000000000055611263004425400244600ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_release" local packages = dofile "profile_build_scripts/package_list.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="no", use_lstrip = "yes", use_readline="yes", optimization = "yes", add_git_metadata = "yes", platform = "unix", extra_flags={ "-march=native", "-msse", "-DNDEBUG", "-fopenmp", "-fPIC", }, extra_libs={ "-fPIC", "-lpthread", "-lblas", "-lcblas", "-latlas", "-fopenmp", "-rdynamic", "-llapack_atlas", "-llapacke", }, shared_extra_libs={ "-shared", "-llua5.2", "-I/usr/include/lua5.2", }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, create_shared_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/build_release_cuda_and_mkl.lua000066400000000000000000000065431263004425400257560ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_release_cuda_and_mkl" local packages = dofile "profile_build_scripts/package_list.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="no", use_lstrip = "yes", use_readline="yes", optimization = "yes", add_git_metadata = "yes", platform = "unix64+cuda", ignore_cuda = false, extra_flags={ -- For Intel MKL :) "-DUSE_MKL", "-I/opt/MKL/include", -------------------- "-march=native", "-msse", "-DNDEBUG", "-DNO_OMP", "-DNO_POOL", -- "-fPIC", -- For CUDA "-DUSE_CUDA", "-I/usr/local/cuda/include", "-L/usr/local/cuda/lib64", }, extra_libs={ -- "-fPIC", "-rdynamic", -- For Intel MKL :) "-L/opt/MKL/lib", "-lmkl_intel_lp64", "-Wl,--start-group", "-lmkl_intel_thread", "-lmkl_core", "-Wl,--end-group", "/opt/MKL/lib/libiomp5.a", -- For CUBLAS "-lcublas", -- For CUDA "-lcuda", "-lcudart", "-lcusparse", -- "-lpthread", }, shared_extra_libs={ "-shared", "-llua5.2", "-I/usr/include/lua5.2", }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, -- create_shared_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/build_release_homebrew.lua000066400000000000000000000066631263004425400251700ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_release_homebrew" local packages = dofile "profile_build_scripts/package_list.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="no", use_lstrip = "yes", use_readline="yes", optimization = "yes", add_git_metadata = "yes", platform = "unix", extra_flags={ "-D__HOMEBREW__", "-mtune=native", "-msse", "-DNDEBUG", "-DUSE_XCODE", "-F/System/Library/Frameworks/Accelerate.framework", "-DNO_OMP", "-fPIC", "-I/usr/local/opt/readline/include", -- homebrew, change if necessary }, extra_libs={ "-L/usr/local/lib", -- homebrew, change if necessary "-L/usr/local/opt/readline/lib", -- homebrew, change if necessary "-lpthread", "-lpng", "/System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate", "/System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib", "/System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libLAPACK.dylib", "-rdynamic", "-fPIC", }, shared_extra_libs={ "-flat_namespace", "-bundle", "-llua", "-I/usr/include/lua5.2", }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, create_shared_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/build_release_macports.lua000066400000000000000000000064331263004425400252030ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_release_macports" local packages = dofile "profile_build_scripts/package_list.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="no", use_lstrip = "yes", use_readline="yes", optimization = "yes", add_git_metadata = "yes", platform = "unix", extra_flags={ "-mtune=native", "-msse", "-DNDEBUG", "-DUSE_XCODE", "-F/System/Library/Frameworks/Accelerate.framework", "-DNO_OMP", "-fPIC", }, extra_libs={ "-L/opt/local/lib", -- macports, change if necessary "-lpthread", "-lpng", "/System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate", "/System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib", "/System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libLAPACK.dylib", "-rdynamic", "-fPIC", }, shared_extra_libs={ "-flat_namespace", "-bundle", assert(io.popen("pkg-config --cflags --libs 'lua >= 5.2'"):read("*l")) }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, create_shared_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/build_release_mkl.lua000066400000000000000000000060761263004425400241410ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_release_mkl" local packages = dofile "profile_build_scripts/package_list.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="no", use_lstrip = "yes", use_readline="yes", optimization = "yes", add_git_metadata = "yes", platform = "unix", extra_flags={ -- For Intel MKL :) "-DUSE_MKL", "-I/opt/MKL/include", -------------------- "-march=native", "-msse", "-DNDEBUG", "-fopenmp", "-fPIC", }, extra_libs={ "-fPIC", "-lpthread", "-rdynamic", -- For Intel MKL :) "-L/opt/MKL/lib", "-lmkl_intel_lp64", "-Wl,--start-group", "-lmkl_intel_thread", "-lmkl_def", "-lmkl_core", "-Wl,--end-group", "-liomp5", }, shared_extra_libs={ "-shared", "-llua5.2", "-I/usr/include/lua5.2", }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, create_shared_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/build_release_no_omp.lua000066400000000000000000000055701263004425400246430ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_release_no_omp" local packages = dofile "profile_build_scripts/package_list.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="no", use_lstrip = "yes", use_readline="yes", optimization = "yes", add_git_metadata = "yes", platform = "unix", extra_flags={ "-march=native", "-msse", "-DNDEBUG", "-DNO_OMP", "-fPIC", }, extra_libs={ "-fPIC", "-lpthread", "-lblas", "-lcblas", "-latlas", "-fopenmp", "-rdynamic", "-llapack_atlas", "-llapacke", }, shared_extra_libs={ "-shared", "-llua5.2", "-I/usr/include/lua5.2", }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, create_shared_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/build_release_pi.lua000066400000000000000000000055521263004425400237640ustar00rootroot00000000000000dofile("luapkg/formiga.lua") local postprocess = dofile("luapkg/postprocess.lua") formiga.build_dir = "build_release_pi" local packages = dofile "profile_build_scripts/package_list.pi.lua" -- table.insert(packages, "rlcompleter") -- AUTOCOMPLETION => needs READLINE local metadata = dofile "profile_build_scripts/METADATA.lua" luapkg{ program_name = "april-ann", description = metadata.description, version = metadata.version, url = metadata.url, verbosity_level = 0, -- 0 => NONE, 1 => ONLY TARGETS, 2 => ALL packages = packages, version_flags = metadata.version_flags, disclaimer_strings = metadata.disclaimer_strings, prefix = metadata.prefix, global_flags = { debug="no", use_lstrip = "yes", use_readline="yes", optimization = "yes", add_git_metadata = "yes", platform = "unix", extra_flags={ "-DNDEBUG", "-DNO_POOL", "-DNO_OMP", "-DNO_MM_MALLOC", "-fPIC", }, extra_libs={ "-fPIC", "-lpthread", "-lblas", "-lcblas", "-latlas", "-rdynamic", "-llapack_atlas", "-llapacke", }, shared_extra_libs={ "-shared", "-llua5.2", "-I/usr/include/lua5.2", }, }, main_package = package{ name = "main_package", default_target = "build", target{ name = "init", mkdir{ dir = "bin" }, mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file = formiga.os.compose_dir(formiga.os.cwd,"lua","include","*.h"), dest_dir = "include" } }, target{ name = "clean_all", exec{ command = [[find . -name "*~" -exec rm {} ';']] }, delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "clean", delete{ dir = "bin" }, delete{ dir = "build" }, delete{ dir = "build_doc" }, }, target{ name = "document_clean", delete{ dir = "build_doc" }, delete{ dir = "doxygen_doc" }, }, target{ name = "build", depends = "provide", compile_luapkg_utils{}, link_main_program{}, create_static_library{}, create_shared_library{}, copy_header_files{}, dot_graph{ file_name = "dep_graph.dot" }, use_timestamp = true, }, target{ name = "test", depends = "build", }, target{ name = "document", echo{"this is documentation"}, main_documentation{ dev_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_dev.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, }, user_documentation = { main_documentation_file = formiga.os.compose_dir("docs","april_user_ref.dox"), doxygen_options = { GENERATE_LATEX = 'NO', }, } }, }, }, } postprocess(arg, formiga) april-ann-0.4.1/profile_build_scripts/package_list.lua000066400000000000000000000020671263004425400231210ustar00rootroot00000000000000return { -- UNIT TESTING "util", "gtest", "utest", -- BASIC PACAKGES -- "plotter", "stats", "dataset", "matrix", "random", "cmdOpt", "complex", "mathcore", "matlab", "stats.MI", "autodiff", "autodiff.ann", "data_frame", "ee5_base64", -- INPUT/OUTPUT "aprilio", "gzio", "zip", "tar", -- MACHINE LEARNING "clustering.kmeans.matrix", "knn.kdtree", "trainable", -- "function_interface", -- NEURAL NETWORKS "ann", "ann.loss", "trainable", "ann.autoencoders", "ann.graph", "bayesian", -- LANGUAGE MODELS "language_models", "ngram.lira", -- IMAGE HANDLERS "Image", "ImageIO", "libpng", "median_filter", "image_metrics", -- IMAGE PREPROCESSING "binarization_filter", "image_cleaning", "interest_points", "image_connected_components", -- --"libtiff", "ocr.off_line.param", "ocr.off_line_text_preprocessing", -- HMMs "hmm_trainer", -- Metrics "metrics.rates", "metrics.roc", -- MISC "profiler", -- VERSION AND COMMIT NUMBERS "version", } april-ann-0.4.1/profile_build_scripts/package_list.pi.lua000066400000000000000000000006231263004425400235240ustar00rootroot00000000000000local packages_list = { -- BASIC PACAKGES "util", "gtest", "utest", "stats", "dataset", "matrix", "data_frame", "random", "cmdOpt", "mathcore", "gzio", "trainable", "ann", "ann.loss", "knn.kdtree", "trainable", "ann.autoencoders", "Image", "ImageIO", "libpng", "stats.MI", "autodiff", "autodiff.ann", "ee5_base64", "version", } return packages_list april-ann-0.4.1/tools/000077500000000000000000000000001263004425400145355ustar00rootroot00000000000000april-ann-0.4.1/tools/ANNs/000077500000000000000000000000001263004425400153345ustar00rootroot00000000000000april-ann-0.4.1/tools/ANNs/convert_all_all_to_new_format.lua000066400000000000000000000003701263004425400241220ustar00rootroot00000000000000input_filename = arg[1] output_filename = arg[2] bunch_size = tonumber(arg[3] or 32) thenet = ann.mlp.all_all.load(input_filename) trainer = trainable.supervised_trainer(thenet, nil, bunch_size) trainer:build() trainer:save(output_filename) april-ann-0.4.1/tools/HMM_ANN/000077500000000000000000000000001263004425400156525ustar00rootroot00000000000000april-ann-0.4.1/tools/HMM_ANN/README.md000066400000000000000000000033751263004425400171410ustar00rootroot00000000000000HMM_ANN directory ================= Here there are scripts for estimation of Hidden Markov Models hybridized with Artificial Neural Networks, as described at this primary reference: - *Improving Offline Handwritten Text Recognition with Hybrid HMM/ANN Models*. S. España-Boquera, M.J. Castro-Bleda, J. Gorbe-Moya, F. Zamora-Martinez. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2011. ## The algorithm idea BOULARD CITE DESCRIPTION OF EM ALGORITHM FOR HMM/ANNs ## Directory structure ``` HMM_ANN/ | |-- evaluation/ NOT READY YET | |-- recognition/ NOT READY YET | |-- segmentation/ Utilities to compute supervised segmentation of corpora | with trained models. | |-- nbest/ NOT READY YET | |-- training/ Utilities and scripts to train HMM/ANNs. \ -- other/ NOT READY YET ``` ## Works which uses this approach - *Improving Offline Handwritten Text Recognition with Hybrid HMM/ANN Models*. S. España-Boquera, M.J. Castro-Bleda, J. Gorbe-Moya, F. Zamora-Martinez. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2011. - *Cache Neural Network Language Models*. F. Zamora-Martinez, S. España-Boquera, M.J. Castro-Bleda and R. de-Mori. International Conference on Acoustics, Speech and Signal Processing. 2013. - *Hybrid HMM/ANN models for bimodal online and offline cursive word recognition*. S. España-Boquera, J. Gorbe-Moya, F. Zamora-Martinez and M.J. Castro-Bleda. International Conference on Pattern Recognition. 2010. - *Unconstrained Offline Handwriting Recognition using Connectionist Character N-grams*. F. Zamora-Martinez, M.J. Castro-Bleda, S. España-Boquera and J. Gorbe-Moya. IEEE International Joint Conference on Neural Networks. 2010. april-ann-0.4.1/tools/HMM_ANN/evaluation/000077500000000000000000000000001263004425400200215ustar00rootroot00000000000000april-ann-0.4.1/tools/HMM_ANN/evaluation/compute_WER.lua000066400000000000000000000023751263004425400227240ustar00rootroot00000000000000if #arg ~= 2 then printf("SINTASIS: %s REF 1BEST\n", string.basename(arg[0])) os.exit(1) end local rf = io.open(arg[1]) local target = io.open(arg[2]) SER = 0 n = 0 rates_list = {} for correcta in rf:lines() do local reconocida = target:read("*l") if not reconocida then print("Warning!!! target shorter than reference") break end if reconocida ~= correcta then SER = SER + 1 end n = n + 1 table.insert(rates_list, { correcta, reconocida }) end resul = rates{ datatype = "pairs_lines", data = rates_list, rate = "ie", } resul_cer = rates{ datatype = "pairs_lines", data = rates_list, rate = "ie", words_width = 1, confusion_matrix = true, } tot = resul.borr + resul.sust + resul.ac printf ("WER: %f %% i:%f %% d:%f %% s:%f %% a:%f %%\n", resul.rate, resul.ins/tot*100, resul.borr/tot*100, resul.sust/tot*100, resul.ac/tot*100) printf ("CER: %f %%\n", resul_cer.rate) printf ("SER: %f %%\n", SER/n*100) local f = io.open("confus.matrix", "w") fprintf(f, "------ matriz de confusion -------\n") for i,j in pairs(resul_cer.confusion_matrix) do for k,l in pairs(j) do fprintf(f, "%-8s x %-8s -> %2d (%s)\n",i,k,l, (i==k and "DIAG") or "NOT-DIAG") end end fprintf(f, "----------------------------------\n") f:close() april-ann-0.4.1/tools/HMM_ANN/evaluation/compute_tasas_for_sentences_with_unks.lua000066400000000000000000000030211263004425400303770ustar00rootroot00000000000000if #arg ~= 3 then printf ("SINTAXIS: %s DICT REFERENCE TARGET\n", string.basename(arg[0])) os.exit(1) end dict=lexClass.load(io.open(arg[1])) ref = io.open(arg[2]) tar = io.open(arg[3]) list_unks = {} list_nounks = {} local SER = 0 for correcta in ref:lines() do local w = string.tokenize(correcta) local has_unk = false for i=1,#w do if dict:getWordId(w[i]) == nil then has_unk = true break end end local out = list_nounks local recog = tar:read("*l") if has_unk then out = list_unks elseif recog ~= correcta then SER = SER + 1 end table.insert(out, { correcta, recog }) end ref:close() tar:close() local resul_val_WER = tasas{ typedata = "pairs_lines", -- words_sep valor por defecto data = list_unks, tasa = "ie", -- para calcular wer } local resul_val_CER = tasas{ typedata = "pairs_lines", -- words_sep valor por defecto data = list_unks, tasa = "ie", -- para calcular wer words_width = 1, } printf ("%7d sentences with UNKS: WER %5.2f CER %5.2f\n", #list_unks, resul_val_WER.tasa, resul_val_CER.tasa) local resul_val_WER = tasas{ typedata = "pairs_lines", -- words_sep valor por defecto data = list_nounks, tasa = "ie", -- para calcular wer } local resul_val_CER = tasas{ typedata = "pairs_lines", -- words_sep valor por defecto data = list_nounks, tasa = "ie", -- para calcular wer words_width = 1, } printf ("%7d sentences without UNKS: WER %5.2f CER %5.2f SER %5.2f\n", #list_nounks, resul_val_WER.tasa, resul_val_CER.tasa, SER/#list_nounks*100) april-ann-0.4.1/tools/HMM_ANN/evaluation/extract_WER_weights.lua000066400000000000000000000106541263004425400244530ustar00rootroot00000000000000opt = cmdOpt{ program_name = string.basename(arg[0]), argument_description = "", main_description = "WER/CER extractor", { index_name="type", description="WER or CER or SER", short="t", argument="yes", }, { index_name="nbest", description="Nbest lists.", short="n", argument="yes", }, { index_name="reference", description="Reference transcriptions.", short="r", argument="yes", }, { index_name="feats", description="Output features.", short="F", argument="yes", }, { index_name="scores", description="Output scores.", short="S", argument="yes", }, { index_name="prev_feats", description="Previous features.", short="E", argument="yes", }, { index_name="prev_scores", description="Previous scores.", short="R", argument="yes", }, { index_name="filter", description="Lua filter (post-process).", short="f", argument="yes", }, { description = "shows this help message", short = "h", long = "help", argument = "no", action = function (argument) print(opt:generate_help()) os.exit(1) end } } optargs = opt:parse_args(args) if not optargs.nbest or not optargs.reference then error("Needs a target and a reference files!!!") end local rf = io.open(optargs.reference) if optargs.filter then filter = dofile(optargs.filter) else filter = function (str) return str end end local currentn = 0 local correcta local type = optargs.type or "WER" local nbestf = io.open(optargs.nbest) lista_tasas = {} features = {} correcta=rf:read("*l") scoresf = io.open(optargs.scores, "w") featsf = io.open(optargs.feats, "w") if optargs.prev_scores then prev_scoresf = io.open(optargs.prev_scores, "r") prev_featsf = io.open(optargs.prev_feats, "r") end local kk = 0 while true do nbest_line=nbestf:read("*l") if nbest_line then n,reconocida,f,p = string.match(nbest_line, "(.*)|||(.*)|||(.*)|||(.*)") if n == nil then reconocida = nbest_line f = "0" p = "0" n = kk kk = kk + 1 end end if not nbest_line or tonumber(n) ~= currentn then fprintf(io.stderr,".") io.stdout:flush() local output_scores = {} local output_features = {} local size = 0 -- procesamos las NBEST local resul_val if type == "WER" then resul_val = tasas{ typedata = "pairs_lines", data = lista_tasas, tasa = "raw", } elseif type == "CER" then resul_val = tasas{ typedata = "pairs_lines", data = lista_tasas, tasa = "raw", words_width = 1, } elseif type == "SER" then resul_val = {} for i=1,#lista_tasas do resul_val[i] = { na=0, ns=0, ni=0, nb=0 } if lista_tasas[i][1] == lista_tasas[i][2] then resul_val[i].na = 1 else resul_val[i].ns = 1 end end else error ("Incorrect type: " .. type) end for i,j in ipairs(resul_val) do -- Aciertos Sustituciones Inserciones Borrados table.insert(output_scores, string.format("%d %d %d %d", j.na, j.ns, j.ni, j.nb)) size = size + 1 end if prev_scoresf then local line = prev_scoresf:read("*l") while true do local line = prev_scoresf:read("*l") if line ~= "SCORES_TXT_END_0" then table.insert(output_scores, line) size = size + 1 else break end end end fprintf(scoresf,"SCORES_TXT_BEGIN_0 %d %d 4 Acc Sub Ins Del\n", currentn, size) fprintf(scoresf, table.concat(output_scores, "\n").."\n") fprintf(scoresf,"SCORES_TXT_END_0\n") fprintf(featsf,"FEATURES_TXT_BEGIN_0 %d %d 3 hmm lm wip\n", currentn, size) fprintf(featsf,table.concat(features, "\n").."\n") if prev_featsf then local line = prev_featsf:read("*l") while true do local line = prev_featsf:read("*l") if line ~= "FEATURES_TXT_END_0" then fprintf(featsf, "%s\n", line) else break end end end fprintf(featsf,"FEATURES_TXT_END_0\n") if not nbest_line then break end -- reiniciamos lista_tasas = {} features = {} correcta=rf:read("*l") if not correcta then error("Incorrect number of sentences") end size = 0 currentn = tonumber(n) end table.insert(lista_tasas, {filter(correcta), filter(reconocida)}) table.insert(features, f) end fprintf(io.stderr,"\n") nbestf:close() scoresf:close() featsf:close() if prev_featsf then prev_featsf:close() end if prev_scoresf then prev_scoresf:close() end april-ann-0.4.1/tools/HMM_ANN/generate_conf.lua000066400000000000000000000016071263004425400211600ustar00rootroot00000000000000conf=arg[1] optargs = {} if io.open(conf) then local t = dofile(conf) for name,value in pairs(t) do optargs[name] = value end i=2 else i=1 end while i <= #arg do local t = {} if string.sub(arg[i], 1, 2) == "--" then local r = string.tokenize(arg[i], "=") if r[1] ~= "--defopt" then t[1] = string.gsub(r[1], "%-%-", "") t[1] = string.gsub(t[1], "%-", "_") t[2] = r[2] end else t[1] = string.sub(arg[i], 2, 2) if t[1] ~= "f" then if string.sub(arg[i+1] or "-", 1, 1) == "-" then t[2] = string.sub(arg[i], 3, #arg[i]) else i=i+1 t[2] = arg[i] end end end if #t == 2 then optargs[t[1]] = t[2] end i=i+1 end print("return {") for name,value in pairs(optargs) do printf(" %s=", name) if tonumber(value) then printf ("%g,\n", tonumber(value)) else printf ("\"%s\",\n", value) end end print("}") april-ann-0.4.1/tools/HMM_ANN/nbest/000077500000000000000000000000001263004425400167655ustar00rootroot00000000000000april-ann-0.4.1/tools/HMM_ANN/nbest/nbest-lattice-sri.lua000066400000000000000000000024451263004425400230260ustar00rootroot00000000000000scale=arg[1] nbestfilename=arg[2] local outdir=os.tmpname() os.execute("rm -f " .. outdir) os.execute("mkdir " .. outdir) nbestf = io.open(nbestfilename, "r") fprintf(io.stderr, "GSF: %f\n", scale) local i = 1 local prevn = nil local outf = nil for line in nbestf:lines() do local n,sentence,score = string.match(line, "(.*)|||(.*)|||.*|||%s*(.*)%s*") if i % 1000 == 0 then collectgarbage("collect") end i = i + 1 if tonumber(n) ~= tonumber(prevn) then fprintf(io.stderr, "Converting to SRI format nbest list %d\n", n) prevn=n if outf then outf:close() end outf = io.open(outdir .. string.format("/nbest_%06d.txt",n), "w") outf:write("NBestList1.0\n") end fprintf(outf, "(%s) %s\n", score, sentence) end outf:close() local auxlist=os.tmpname() os.execute("ls ".. outdir .. "/* > " .. auxlist) -- -no-reorder -prime-lattice local f = io.popen("/home/experimentos/HERRAMIENTAS/bin/nbest-lattice ".. " -lattice-wer -nbest-files ".. auxlist .. " -rescore-lmw 1 -posterior-scale " .. scale) fprintf(io.stderr, "Minimizing WER\n") for line in f:lines() do local t = string.tokenize(line) fprintf(io.stderr, ".") print(table.concat(t, " ", 2, #t)) io.stderr:flush() io.stdout:flush() end fprintf(io.stderr, "\n") os.execute("rm -Rf " .. auxlist .. " " .. outdir) april-ann-0.4.1/tools/HMM_ANN/nbest/rescoring-only-recog.sh000077500000000000000000000021671263004425400234010ustar00rootroot00000000000000#!/bin/bash prefix=$1 feats=$2 nbest=$3 trie_size=$4 nnlm=$5 vocab=$6 use_ccs=$7 if [ -z $use_ccs ]; then use_ccs="yes" fi if [ -e $prefix ]; then echo "ERROR, exists $prefix, sure this is PREFIX???" exit 12; fi april=~experimentos/HERRAMIENTAS/bin/april tools=~experimentos/HERRAMIENTAS april_tools="$tools/april_tools" generate_conf=$april_tools/HMM_ANN/generate_conf.lua echo "# computing NNLM feature" stdout=$prefix.NNLM_feature if [ ! -e $stdout.gz ]; then $april ~experimentos/HERRAMIENTAS/april_tools/NBEST/compute_nnlm_score.lua \ $nbest $nnlm $vocab $trie_size $use_ccs $use_ccs 2> $prefix.time.txt | gzip -c > $stdout.gz fi nnlmfeats=$prefix.`basename $feats .gz`.nnlm.gz if [ ! -e $nnlmfeats ]; then echo "# substituting LM features with " $nnlmfeats $april ~experimentos/HERRAMIENTAS/april_tools/NBEST/substitute_feature.lua 2 $feats $prefix.NNLM_feature.gz | gzip -c > $nnlmfeats fi if [ ! -e $prefix.recog.out ]; then echo "# rescoring" $april ~experimentos/HERRAMIENTAS/april_tools/NBEST/rerank.lua \ weights.txt $nbest $nnlmfeats $prefix.reranked-nbest.out.gz > $prefix.recog.out fi april-ann-0.4.1/tools/HMM_ANN/nbest/rescoring-with-cache-nnlm-only-recog.sh000077500000000000000000000037211263004425400263520ustar00rootroot00000000000000#!/bin/bash prefix=$1 feats=$2 nbest=$3 trie_size=$4 nnlm=$5 vocab=$6 extra_cache_set=$7 use_ccs=$8 scale=15 epsilon=0.0001 if [ -z $use_ccs ]; then use_ccs="yes" fi if [ -e $prefix ]; then echo "ERROR, exists $prefix, sure this is PREFIX???" exit 12; fi april=~experimentos/HERRAMIENTAS/bin/april tools=~experimentos/HERRAMIENTAS april_tools="$tools/april_tools" generate_conf=$april_tools/HMM_ANN/generate_conf.lua feats0=$prefix.reranked-feats.run0.out.gz nbest0=$prefix.reranked-nbest.run0.out.gz if [ ! -e $nbest0 ]; then ln -s $nbest $nbest0; ln -s $feats $feats0; fi nbest=$nbest0 feats=$feats0 prevrun=0 run=1 while true; do echo "# computing NNLM feature at run $run with $nbest" stdout=$prefix.NNLM_feature.run$run if [ ! -e $stdout.gz ]; then $april ~experimentos/HERRAMIENTAS/april_tools/NBEST/compute_nnlm_score.lua \ $nbest $nnlm $vocab $trie_size $use_ccs $use_ccs $extra_cache_set 2> $prefix.time.run$run.txt | gzip -c > $stdout.gz fi nnlmfeats=`basename $feats .gz`.nnlm.gz if [ ! -e $nnlmfeats ]; then echo "# substituting LM features with " $nnlmfeats $april ~experimentos/HERRAMIENTAS/april_tools/NBEST/substitute_feature.lua 2 $feats $stdout.gz | gzip -c > $nnlmfeats fi if [ ! -e $prefix.recog.run$run.out ]; then echo "# rescoring at run $run" $april ~experimentos/HERRAMIENTAS/april_tools/NBEST/rerank.lua \ weights.run`cat finished.txt`.txt $nbest $nnlmfeats \ $prefix.reranked-nbest.run$run.out.gz \ $prefix.reranked-feats.run$run.out.gz > $prefix.recog.run$run.out fi stop=0 if [ -e $prefix.recog.run$prevrun.out ]; then diff=`diff $prefix.recog.run$prevrun.out $prefix.recog.run$run.out | wc -l` if (( "$diff" == 0 )); then stop=1 fi fi if (( "$stop" == 1 )); then echo $run > $prefix.finished.txt break; fi nbest=$prefix.reranked-nbest.run$run.out.gz feats=$prefix.reranked-feats.run$run.out.gz prevrun=$run run=`expr $run + 1` done april-ann-0.4.1/tools/HMM_ANN/nbest/rescoring-with-cache-nnlm.sh000077500000000000000000000061571263004425400243040ustar00rootroot00000000000000#!/bin/bash deven=$1 nbest=$2 trie_size=$3 nnlm=$4 vocab=$5 extra_cache_set=$6 use_ccs=$7 if [ -z $use_ccs ]; then use_ccs="yes" fi scale=15 epsilon=0.0001 echo $@ > rescoring.conf if [ ! -e init.opt ]; then echo "Needs a init.opt file!!!" exit 1; fi april=~experimentos/HERRAMIENTAS/bin/april tools=~experimentos/HERRAMIENTAS april_tools="$tools/april_tools" scorer="$april $april_tools/HMM_ANN/extract_WER_weights.lua" generate_conf=$april_tools/HMM_ANN/generate_conf.lua mert="$april $april_tools/optimizer_weights.lua -s WER -t simplex -a 2 " nbest0=dev.run0.reranked-nbest.out.gz if [ ! -e $nbest0 ]; then ln -s $nbest $nbest0; fi nbest=$nbest0 prevrun=0 run=1 while true; do echo "# computing NNLM feature for run $run using $nbest" stdout=NNLM_feature.run$run if [ ! -e $stdout.gz ]; then $april ~experimentos/HERRAMIENTAS/april_tools/NBEST/compute_nnlm_score.lua \ $nbest $nnlm $vocab $trie_size $use_ccs $use_ccs $extra_cache_set 2> time.run$run.txt | gzip -c > $stdout.gz fi if [ ! -e scores.run$run.dat.gz ]; then $scorer -r $deven \ -S scores.run$run.dat \ -F feats.run$run.dat \ -n $nbest gzip scores.run$run.dat gzip feats.run$run.dat fi feats=feats.run$run.dat.gz scores=scores.run$run.dat.gz nnlmfeats=`basename $feats .gz`.nnlm.gz if [ ! -e $nnlmfeats ]; then echo "# substituting LM features with " $nnlmfeats $april ~experimentos/HERRAMIENTAS/april_tools/NBEST/substitute_feature.lua 2 $feats $stdout.gz | gzip -c > $nnlmfeats fi if [ ! -e mert.run$run.log ]; then echo "# MERT" weights=( $(tail -n 1 "init.opt") ) sizew=${#weights[@]} seed=$RANDOM if [ -e seed.run$run.txt ]; then seed=`cat seed.run$run.txt`; fi echo $seed > seed.run$run.txt $mert -n 20 -d 3 -S scores.run$run.dat.gz \ -r $seed \ -F $nnlmfeats -i init.opt >& mert.run$run.log grep -i "best point: " mert.run$run.log | cut -d':' -f 2 | cut -d'=' -f 1 > weights.run$run.txt weights=( $(tail -n 1 "weights.run$run.txt") ) new_gsf=`echo "scale=$scale; ${weights[1]}/${weights[0]}" | bc` new_wip=`echo "scale=$scale; ${weights[2]}/${weights[0]}" | bc` echo "1 $new_gsf $new_wip" > weights.run$run.txt fi if [ ! -e dev.run$run.recog.out ]; then echo "# rescoring at run $run" $april ~experimentos/HERRAMIENTAS/april_tools/NBEST/rerank.lua \ weights.run$run.txt $nbest $nnlmfeats dev.run$run.reranked-nbest.out.gz > dev.run$run.recog.out fi echo "# Evaluando el resultado at run $run" $april $april_tools/HMM_ANN/compute_WER.lua $deven dev.run$run.recog.out > results.run$run.log stop=0 if [ -e results.run$prevrun.log ]; then wer=`grep WER results.run$run.log | awk '{ print $2 }'` prevwer=`grep WER results.run$prevrun.log | awk '{print $2}'` diff=`echo "scale=$scale; $prevwer - $wer" | bc` res=`echo "scale=$scale; $diff*$diff > $epsilon*$epsilon" | bc` # echo $diff ">" $epsilon "=" $res if (( "$res" == 0 )); then stop=1 fi fi if (( "$stop" == 1 )); then echo $run > finished.txt break; fi nbest=dev.run$run.reranked-nbest.out.gz prevrun=$run run=`expr $run + 1` done april-ann-0.4.1/tools/HMM_ANN/nbest/rescoring.sh000077500000000000000000000041551263004425400213240ustar00rootroot00000000000000#!/bin/bash deven=$1 nbest=$2 trie_size=$3 nnlm=$4 vocab=$5 use_ccs=$6 if [ -z $use_ccs ]; then use_ccs="yes" fi scale=15 echo $@ > rescoring.conf if [ ! -e init.opt ]; then echo "Needs a init.opt file!!!" exit 1; fi april=~experimentos/HERRAMIENTAS/bin/april tools=~experimentos/HERRAMIENTAS april_tools="$tools/april_tools" scorer="$april $april_tools/HMM_ANN/extract_WER_weights.lua" generate_conf=$april_tools/HMM_ANN/generate_conf.lua mert="$april $april_tools/optimizer_weights.lua -s WER -t simplex -a 2 " echo "# computing NNLM feature" stdout=NNLM_feature if [ ! -e $stdout.gz ]; then $april ~experimentos/HERRAMIENTAS/april_tools/NBEST/compute_nnlm_score.lua \ $nbest $nnlm $vocab $trie_size $use_ccs $use_ccs 2> time.txt | gzip -c > $stdout.gz fi if [ ! -e scores.dat.gz ]; then $scorer -r $deven \ -S scores.dat \ -F feats.dat \ -n $nbest gzip scores.dat gzip feats.dat fi feats=feats.dat.gz scores=scores.dat.gz nnlmfeats=`basename $feats .gz`.nnlm.gz if [ ! -e $nnlmfeats ]; then echo "# substituting LM features with " $nnlmfeats $april ~experimentos/HERRAMIENTAS/april_tools/NBEST/substitute_feature.lua 2 $feats NNLM_feature.gz | gzip -c > $nnlmfeats fi if [ ! -e mert.log ]; then echo "# MERT" weights=( $(tail -n 1 "init.opt") ) sizew=${#weights[@]} seed=$RANDOM if [ -e seed.txt ]; then seed=`cat seed.txt`; fi echo $seed > seed.txt $mert -n 20 -d 3 -S scores.dat.gz \ -r $seed \ -F $nnlmfeats -i init.opt >& mert.log grep -i "best point: " mert.log | cut -d':' -f 2 | cut -d'=' -f 1 > weights.txt weights=( $(tail -n 1 "weights.txt") ) new_gsf=`echo "scale=$scale; ${weights[1]}/${weights[0]}" | bc` new_wip=`echo "scale=$scale; ${weights[2]}/${weights[0]}" | bc` echo "1 $new_gsf $new_wip" > weights.txt fi if [ ! -e dev.recog.out ]; then echo "# rescoring" $april ~experimentos/HERRAMIENTAS/april_tools/NBEST/rerank.lua \ weights.txt $nbest $nnlmfeats dev.reranked-nbest.out.gz > dev.recog.out fi echo "# Evaluando el resultado" $april $april_tools/HMM_ANN/compute_WER.lua $deven dev.recog.out > results.log april-ann-0.4.1/tools/HMM_ANN/other/000077500000000000000000000000001263004425400167735ustar00rootroot00000000000000april-ann-0.4.1/tools/HMM_ANN/other/compute_mlp_posteriors.lua000066400000000000000000000107161263004425400243200ustar00rootroot00000000000000april_print_script_header(arg) dofile(string.get_path(arg[0]) .. "../utils.lua") cmdOptTest = cmdOpt{ program_name = string.basename(arg[0]), argument_description = "", main_description = "Generate the MLP posterior matrix", { index_name="n", description = "MLP file", short = "n", argument = "yes", mode = "always", }, { index_name="p", description = "File with the corpus mfccs data", short = "p", argument = "yes", mode = "always", }, { index_name = "context", -- antes ann_context_size description = "Size of ann context", long = "context", argument = "yes", mode = "always", default_value=4, filter=tonumber, }, { index_name = "feats_format", description = "Format of features mat, mfc or png", long = "feats-format", argument = "yes", mode = "always", default_value="mat", }, { index_name = "feats_norm", description = "Table with means and devs for features", long = "feats-norm", argument = "yes", filter = dofile, }, { index_name = "step", description = "Dataset step", long = "step", argument = "yes", mode = "always", default_value="1", filter=tonumber, }, { index_name = "dir", description = "Output dir", long = "dir", argument="yes", mode="always", default_value="posteriors", }, { index_name="f", description = "Force overwritten output files", short = "f", argument = "no", }, { index_name = "cores", description = "Number of cores (processes) to use", long = "cores", argument="yes", mode="always", default_value=util.omp_get_num_threads(), filter=tonumber, }, { description = "shows this help message", short = "h", long = "help", argument = "no", action = function (argument) print(cmdOptTest:generate_help()) os.exit(1) end } } local optargs = cmdOptTest:parse_args() if type(optargs) == "string" then error(optargs) end local filenet = optargs.n local valfile = optargs.p local dir = optargs.dir local context = optargs.context local step = optargs.step local format = optargs.feats_format local cores = optargs.cores local feats_mean_and_devs = optargs.feats_norm local force_write = optargs.f os.execute("mkdir -p " .. dir) -- local trainer = trainable.supervised_trainer.load(filenet, nil, 128) local num_emissions = trainer:get_output_size() local frames_loader = nil if format == "mat" then frames_loader = load_matrix elseif format == "mfc" then frames_loader = load_mfcc elseif format == "png" then frames_loader = load_png else error("Unknown format " .. format) end ----------------------------------------------------------------------------- local feats_f = io.open(valfile) local list = {} for feats_filename in feats_f:lines() do table.insert(list, feats_filename) end local which_i_am,child_pid = util.split_process(cores) for index=which_i_am,#list,cores do collectgarbage("collect") local feats_filename = list[index] print ("# Loading frames: ", feats_filename, index .. "/" .. #list) local frames = frames_loader(feats_filename) local numFrames = math.floor(frames:dim(1)/step) local numParams = frames:dim(2) local parameters = { patternSize = {1, numParams}, stepSize = {step, 0}, numSteps = {numFrames, 1} } local current_ds = dataset.matrix(frames, parameters) if feats_mean_and_devs then current_ds:normalize_mean_deviation(feats_mean_and_devs.means, feats_mean_and_devs.devs) end current_ds = dataset.contextualizer(current_ds, context, context) local output_mat = matrix(numFrames, num_emissions) local output_ds = dataset.matrix(output_mat) trainer:use_dataset{ input_dataset = current_ds, output_dataset = output_ds, } local base_name = string.remove_extension(string.basename(feats_filename)) if string.match(feats_filename, "%.gz") then base_name = string.remove_extension(base_name) end local outfile = string.format("%s/%s.mat.gz", dir, base_name) print ("# Saving MLP output: ", outfile) if io.open(outfile) and not force_write then error(string.format("# Output file '%s' exists, use -f to force overwritten\n", outfile)) else output_mat:toFilename(outfile, "ascii") end end if child_pid then -- esperamos a los hijos util.wait() end april-ann-0.4.1/tools/HMM_ANN/other/generate_initial_hmm_from_models_nstates_table.lua000066400000000000000000000040261263004425400311420ustar00rootroot00000000000000if #arg ~= 2 then fprintf(io.stderr, "SINTAXIS: %s TIEDLIST NSTATESFILE\n", arg[0]) os.exit(128) end tiedfile = arg[1] nstates_file = arg[2] -- objeto con informacion sobre modelos ligados tied = tied_model_manager(io.open(tiedfile)) local model2nstates = {} for line in io.lines(nstates_file) do local model_name, nstates = table.unpack(string.tokenize(line)) name = tied:get_model(model_name) if model2nstates[name] and model2nstates[name] ~= tonumber(nstates) then error ("Two tied models has different number of states :S " .. model_name .. " " .. name) end model2nstates[name] = tonumber(nstates) model2nstates[model_name] = tonumber(nstates) end local num_models = 0 local hmms = {} local next_emission = 1 local trainer = HMMTrainer.trainer() for model_id,name in ipairs(tied.id2name) do m = tied.tiedlist[name] if name == m then local num_states = model2nstates[name] if not num_states then error ("Inexistent model: " .. name) end local ploops = {} for i=1,num_states do ploops[i] = 0.5 end num_models = num_models + 1 local hmm_emissions = {} -- generamos el vector de emisiones for i=1,num_states do hmm_emissions[i] = next_emission next_emission = next_emission + 1 end -- este es el representante local desc = HMMTrainer.utils.generate_lr_hmm_desc(name, hmm_emissions, ploops, {}, name) local model = trainer:model(desc) hmms[name] = { model = model, emissions = hmm_emissions, } end end print("return { {") for name,model_info in pairs(hmms) do print("['".. string.gsub(name,"'","\\'") .. "'] = {") print("\tmodel=HMMTrainer.model.from_table(") printf("%s", model_info.model:to_string()) print("),") print("\temissions={".. table.concat(model_info.emissions, ",") .."}") print("},") end print("},") print("{") num_emissions = next_emission - 1 for i=1,num_emissions do printf("%g, ", 1/num_emissions) end print("},") print("}") april-ann-0.4.1/tools/HMM_ANN/other/generate_ose_string_from_viterbi_alignment.lua000066400000000000000000000164151263004425400303400ustar00rootroot00000000000000cmd = cmdOpt{ program_name = string.basename(arg[0]), argument_description = "", main_description = "Generation of Oversegmenter strings from viterbi forced alignment", { index_name="a", description="Force viterbi alignment file indexes", short="a", argument="yes", }, { index_name="t", description="Phone transcription file indexes", short="t", argument="yes", }, { index_name="m", description="HMMs models, in LUA format", short="m", argument="yes", }, { index_name="w", description="Whitespace/silence symbol", short="w", argument="yes", }, { index_name="mark_before_w", description="Mark frontier before whitespace/silence symbol (default no)", long="mark-before-w", argument="yes", }, { index_name="mark_after_w", description="Mark frontier before whitespace/silence symbol (default yes)", long="mark-after-w", argument="yes", }, { index_name="s", description="Use sure frontier (default no)", short="s", argument="yes", }, { index_name="d", description="Dest directory", short="d", argument="yes", }, { index_name="f", description="Filter the transcription to generate phon transcription", short="f", argument="yes", }, { description = "shows this help message", short = "h", long = "help", argument = "no", action = function (argument) print(cmd:generate_help()) os.exit(1) end } } optargs = cmd:parse_args() local mark_before_w = ((optargs.mark_before_w or "no") == "yes") local mark_after_w = ((optargs.mark_after_w or "yes") == "yes") local vit_index_filename = optargs.a or error ("Needs -a option!!!") local phn_index_filename = optargs.t or error ("Needs -t option!!!") local dest_dir = optargs.d or error ("Needs -d option!!!") local hmms_filename = optargs.m or error ("Needs -m option!!!") local white_symbol = optargs.w or error ("Needs -w option!!!") local sure_frontier = ((optargs.s or "no") == "yes") local filter = optargs.f if filter then filter = dofile(filter) else filter = function(str) return str end end if not mark_after_w and not mark_before_w then error("Is mandatory to mark frontiers before or/and after silences!!!") end m = dofile(hmms_filename) models = m[1] emiss2phon = {} phon2emiss = {} for name,model_info in pairs(models) do phon2emiss[name] = {} for _,e in ipairs(model_info.emissions) do emiss2phon[e] = name phon2emiss[name][e] = true end end local vit_file = io.open(vit_index_filename) local phn_file = io.open(phn_index_filename) for orig_filename in vit_file:lines() do collectgarbage("collect") local destname = dest_dir .. "/" .. string.basename(orig_filename) destname = string.gsub(destname, "%.mat.*$", ".ose") fprintf(io.stderr,"# Generando desde \t%s\ta\t%s\n", orig_filename,destname) local orig_phn_filename = phn_file:read("*l") local phn = filter(io.open(orig_phn_filename):read("*l")) local mat = matrix.fromFilename(orig_filename) local ds = dataset.matrix(mat) phn = string.tokenize(phn) local words = { } for i=1,#phn do if phn[i] == white_symbol then if phn[i+1] and phn[i+1] ~= white_symbol then table.insert(words, {}) end else if #words == 0 then table.insert(words, {}) end table.insert(words[#words], phn[i]) end end -- words es una tabla que contiene tablas con los fonemas de cada -- palabra, eliminando los de silencio local current_frame = 1 local current_word = 1 local current_phone = 1 -- primera frontera, se marca siempre local frontiers = { util.ose.compose_frontier{ util.ose.generate_output } } local last_value = -100 if ds:patternSize() ~= 1 then error ("Incorrect segmentation file") end function add_void_frontier() table.insert(frontiers, util.ose.compose_frontier{}) end function add_frontier() if sure_frontier then table.insert(frontiers, util.ose.compose_frontier{ util.ose.mark, util.ose.generate_output, util.ose.remove_marked } ) else table.insert(frontiers, util.ose.compose_frontier{ util.ose.generate_output }) end end function skip_silence() local skipped = false -- buscamos el primer frame que no es espacio while (current_frame < ds:numPatterns() and emiss2phon[ds:getPattern(current_frame)[1]] == white_symbol) do --print(current_frame, #frontiers) -- metemos la frontera despues del frame actual add_void_frontier() -- pasamos al siguiente current_frame = current_frame + 1 skipped = true end return skipped end -- buscamos el primer frame que no es espacio skip_silence() if current_frame ~= 1 then -- current_frame apunta al primer frame diferente de silencio, -- eliminamos el ultimo y anyadimos frontera table.remove(frontiers) if mark_after_w then add_frontier() else add_void_frontier() end else current_frame = 1 end -- a partir de este momento frontiers va siempre un frame por detras while current_frame < ds:numPatterns() do local last_e = -100 while (current_frame < ds:numPatterns() and emiss2phon[ds:getPattern(current_frame)[1]] == words[current_word][current_phone] and last_e <= ds:getPattern(current_frame)[1]) do -- anyadimos la frontera vacia del frame anterior al actual add_void_frontier() last_e = ds:getPattern(current_frame)[1] -- pasamos al siguiente current_frame = current_frame + 1 --print("O", current_frame, #frontiers) end -- anyadimos porque vamos retrasados un frame, por tanto esta va -- antes del simbolo local marked_before = false if mark_before_w and emiss2phon[ds:getPattern(current_frame)[1]] == white_symbol then add_frontier() marked_before = true end -- se ha producido el cambio de fonema, evitamos el silencio local skipped_silence = skip_silence() if skipped_silence and mark_before_w then -- eliminamos la ultima, para que vuelva a ir un frame por -- detras table.remove(frontiers) end --print("O", current_frame, #frontiers) -- pasamos al siguiente fonema current_phone = current_phone + 1 if current_phone > #words[current_word] then current_word = current_word + 1 current_phone = 1 -- cambio de palabra, metemos una frontera if current_frame < ds:numPatterns() then if mark_after_w or not marked_before then add_frontier() else add_void_frontier() end else -- ultima frontera, se marca siempre if skipped_silence then table.insert(frontiers, util.ose.compose_frontier{ util.ose.generate_output }) else add_frontier() end end -- corremos un frame current_frame = current_frame + 1 end end if current_word ~= #words+1 then error ("Incorrect words number") end if #frontiers ~= ds:numPatterns() + 1 then error ("Incorrect number of frontiers: " .. #frontiers .. " instead of " .. ds:numPatterns()+1) end local f = io.open(destname, "w") if not f then error("File not found!!! " .. destname) end f:write(table.concat(frontiers, "")) f:close() end april-ann-0.4.1/tools/HMM_ANN/other/mat2htk.lua000066400000000000000000000020771263004425400210560ustar00rootroot00000000000000-- recibe un fichero indice y un directorio destino index_list = arg[1] dest_dir = arg[2] function load_matrix(MFCCfilename) local f = io.open(MFCCfilename) or error ("No se ha podido encontrar "..MFCCfilename) local aux = f:read("*a") local ad = matrix.fromString(aux) f:close() return ad end gc_count = 1 for mat_filename in io.lines(index_list) do if gc_count > 100 then collectgarbage("collect") gc_count = 1 else gc_count = gc_count+1 end -- cargamos el dataset correspondiente a la frase actual -- local basename = string.remove_extension(string.basename(mat_filename)) print ("# loading matrix", mat_filename) local mat = matrix.fromFilename(mat_filename) local basename = string.basename(mat_filename) local extension = string.get_extension(basename) basename = string.remove_extension(basename) if (extension == 'gz') then basename = string.remove_extension(basename) end local dest = dest_dir .. '/' .. basename .. '.htk' print("# writing file ",dest) htk_interface.write_matrix_as_mfc_file(mat,dest,"USER") end april-ann-0.4.1/tools/HMM_ANN/other/tree2binary.lua000066400000000000000000000007501263004425400217260ustar00rootroot00000000000000if #arg < 3 or #arg > 4 then print("Usage: tree2binary vocabulary file.tree file.btree [swap_bytes]") else vocabulary = lexClass.load(io.open(arg[1])) treemodel = parser.new_one_step.treeModel{ filename = arg[2] } swap_bytes = ((arg[4] or "no") == "yes") if swap_bytes then print("Swapping bytes, changing endianism") end treemodel:save{ filename = arg[3], vocabulary = vocabulary:getWordVocabulary(), binary = true, swap = swap_bytes, } end april-ann-0.4.1/tools/HMM_ANN/recognition/000077500000000000000000000000001263004425400201725ustar00rootroot00000000000000april-ann-0.4.1/tools/HMM_ANN/recognition/barrido-EM.sh000077500000000000000000000006471263004425400224610ustar00rootroot00000000000000#!/bin/bash conf_file=$1 outdir=$2 ini=$3 fin=$4 april=/home/experimentos/HERRAMIENTAS/bin/april recog=/home/experimentos/HERRAMIENTAS/april_tools/HMM_ANN/recog.lua mkdir -p $outdir for i in `seq $ini $fin`; do $april $recog -f $conf_file -m models/hmms/ci?_cd?_em$i.lua \ -n models/redes/ci?_cd?_em$i.net 2> $outdir/resultados.em`printf "%02d" $i`.log > $outdir/resultados.em`printf "%02d" $i`.out; done april-ann-0.4.1/tools/HMM_ANN/recognition/onepass.lua000066400000000000000000000470251263004425400223550ustar00rootroot00000000000000-------------------------------------------------- -- command line options -------------------------------------------------- opt = cmdOpt{ program_name = string.basename(arg[0]), argument_description = "", main_description = "HMM/ANN recognition with April toolkit new one pass decoder", { index_name="defopt", description="Load configuration file (a lua table)", short="f", argument="yes", }, ---------------------------------------------------------------------- { index_name = "recog", description = "Recog type: asr, htr [default=asr]", long = "recog", argument = "yes" }, ---------------------------------------------------------------------- -- relacionados con la red neuronal { index_name="n", description = "MLP file", short = "n", argument = "yes", }, { index_name="bunch_size", description="Size of bunch for MLPs [default 96]", long="bunch-size", argument="yes", }, { index_name = "context", description = "Size of ann context [default=8]", long = "context", argument = "yes" }, { index_name = "feats_norm", description = "Table with means and devs for features", long = "feats-norm", argument = "yes", }, ---------------------------------------------------------------------- -- con la carga de los modelos { index_name="m", description = "hmms file", short = "m", argument = "yes", }, { index_name="t", description = "HTK unit's tied list", short = "t", argument = "yes", }, { index_name="d", description = "HTK dictionary", short = "d", argument = "yes", }, { index_name="pt", description = "pronunciation tree model", long = "pt", argument = "yes", }, { index_name="bpt", description = "pronunciation tree model is binary [default true]", long = "bpt", argument = "yes", }, { index_name="lm", description = "Language model [default=dont use LM]", long = "lm", argument = "yes", }, { index_name = "use_context_cues", description = "Use context cues", long = "use-context-cues", argument = "yes" }, ---------------------------------------------------------------------- -- con los parametros de configuracion { index_name="beam_width", description = "Beam width [default=400]", long = "beam-width", argument = "yes", }, { index_name="histogram_size", description = "Histogram pruning size [default=5000]", long = "histogram-size", argument = "yes", }, { index_name="gsf", description = "Grammar Scale Factor [default=10]", long = "gsf", argument = "yes", }, { index_name="pt_gsf", description = "Prefix Tree Grammar Scale Factor [default=1]", long = "pt-gsf", argument = "yes", }, { index_name="wip", description = "Word Insertion Penalty [default=0]", long = "wip", argument = "yes", }, ---------------------------------------------------------------------- -- { index_name="p", description = "File with the corpus mfccs data", short = "p", argument = "yes", }, { index_name="prep", description = "File with the corpus preprocessed data", long = "prep", argument = "yes", }, { index_name="txt", description = "File with the corpus transcriptions", long = "txt", argument = "yes", }, { index_name = "filter", description = "Fiter output sentence before tasas, is a file that return a LUA function [default=nil]", long = "filter", argument = "yes", }, { index_name = "view_filter", description = "Fiter output sentence to show result, is a file that return a LUA function [default=nil]", long = "view-filter", argument = "yes", }, { index_name = "feats_format", description = "Format of features (mat, raw, mfc) [default mat]", long = "feats-format", argument = "yes", }, { index_name = "wadvance", description = "Window advance in ASR, in milliseconds [default=10] used to compute the real time factor", long = "wadvance", argument = "yes", }, { index_name = "cache_size", description = "Size of cache for NNLMs [default=20]", long = "cache-size", xargument = "yes", }, { index_name = "trie_size", description = "Size of TrieVector for NNLMs [default=24]", long = "trie-size", argument = "yes", }, { index_name="ose_file", description = "Over SEgmenter index file, with one string for each corpus file [optional]", long = "ose-file", argument = "yes", }, { description = "shows this help message", short = "h", long = "help", argument = "no", action = function (argument) print(opt:generate_help()) os.exit(1) end } } optargs = opt:parse_args() if type(optargs) == "string" then error(optargs) end if optargs.defopt then local t = dofile(optargs.defopt) for name,value in pairs(t) do if not optargs[name] then fprintf(io.stderr,"# opt %s = %s\n", name, tostring(value)) optargs[name] = value end end end dir = string.gsub(arg[0], string.basename(arg[0]), "") dir = (dir~="" and dir) or "./" loadfile(dir .. "utils.lua")() -- deprecar -------------------------------------------------- -- algunas funciones -- function load_matrix(filename) -- local f = io.open(filename) or error ("No se ha podido encontrar "..filename) -- local aux = f:read("*a") -- local ad = matrix.fromString(aux) -- f:close() -- return ad -- end guarda_frames = ASR.VectorFrameConsumer() vad = ASR.VAD{ -- beginVoiceDuration = 5, -- beginVoiceScore = 0.3, -- stopVoiceDuration = 10, -- stopVoiceScore = 0.1, frameConsumer = guarda_frames, } parametrizer = ASR.Parametrizer{ HzSamplingAD = 8000, preemphasis = 0.95, msWindowSize = 25, msWindowAdvance = 10, nparam = 12, decorrelation = "FF1", output = vad } function load_raw(filename) guarda_frames:reset() parametrizer:applyFile(filename) return guarda_frames:getMatrix() end -------------------------------------------------- -- log fprintf(io.stderr,"# HOST:\t %s\n", (io.popen("hostname", "r"):read("*l"))) fprintf(io.stderr,"# DATE:\t %s\n", (io.popen("date", "r"):read("*l"))) fprintf(io.stderr,"# CMD: \t %s %s\n",string.basename(arg[0]), table.concat(arg, " ")) -------------------------------------------------- -- Red neuronal filename_ann = optargs.n -- Fichero de HMMs filename_hmm = optargs.m -- Fichero HTK filename_hmmdefs = optargs.hmmdefs -- filename_tiedlist = optargs.t or error ("Needs a tiedlist!!!") filename_dict = optargs.d or error ("Needs a dictionary!!!") filename_prontree = optargs.pt or error ("Needs a pronunciation tree!!!") binary_prefix_tree = optargs.bpt or true filename_test = optargs.p filename_prep = optargs.prep filename_txt = optargs.txt or fprintf(io.stderr,"Warning!!! running without transcriptions --txt!!!\n") filename_lm = optargs.lm dataset_step = tonumber(optargs.step or 1) feats_format = optargs.feats_format or "mat" feats_mean_and_devs = optargs.feats_norm features_filename = optargs.features recog_type = string.lower(optargs.recog or "asr") wsize = (optargs.wsize or 25) / 1000 -- para pasar a segundos wadvance = (optargs.wadvance or 10) / 1000 -- para pasar a segundos beam_width = tonumber(optargs.beam_width or "400") hist_prun_size = tonumber(optargs.histogram_size or "5000") hist_prun_step = 1000 max_hyps = 1000000 trll_log2_hash_size = 21 trll_log2_max_nodes = 21 cache_size = tonumber(optargs.cache_size) trie_size = tonumber(optargs.trie_size) gsf = optargs.gsf or 10.0 pt_gsf = optargs.pt_gsf or 1.0 wip = optargs.wip or 0.0 ose_file = optargs.ose_file if recog_type == 'htr' then word_sil = "@" else word_sil = "." end initial_ngram_word = '' final_ngram_word = '' unk_ngram_word = '' mfcs_matrix_format = (feats_format == "mat") use_context_cues = ((optargs.use_context_cues or "yes") == "yes") ----------------------------------------------- if feats_mean_and_devs then feats_mean_and_devs = dofile(feats_mean_and_devs) end ----------------------------------------------- if optargs.filter then filter = dofile(optargs.filter) else filter = function (str) return str end end ----------------------------------------------- if optargs.view_filter then view_filter = dofile(optargs.view_filter) else view_filter = function (str) return str end end ----------------------------------------------- -- tied list ----------------------------------------------- tied_model = tied_model_manager(io.open(filename_tiedlist)) ----------------------------------------------- -- dictionary ----------------------------------------------- dictionary = lexClass.load(io.open(filename_dict)) ----------------------------------------------- -- HMMs ----------------------------------------------- local m = dofile(filename_hmm) hmm = {} hmm.models = m[1] hmm.aprioris = m[2] hmm.units = parser.lr_hmm_dictionary() hmm.unit2id = {} for id,phone in ipairs(tied_model.id2name) do local model_info = hmm.models[phone] local lprobs = {} for _,t in ipairs(model_info.model.transitions) do if t.from == t.to then lprobs[t.from-3] = math.exp(t.lprob) end end hmm.unit2id[phone] = hmm.units:insert_unit { emiss_indexes = model_info.emissions, loop_probs = lprobs, } end -- convertimos el diccionario a formato lrhmm hmm.lrhmm = parser.new_one_step.LR_HMMs(hmm.units) ----------------------------------------------- -- language model ----------------------------------------------- if filename_lm then ngram_model = ngram.load_language_model(filename_lm, dictionary, initial_ngram_word, final_ngram_word, -- EXTRA { cache_size = cache_size, trie_size = trie_size, }) else ngram_model = ngram.lira.loop{ vocabulary_size = #dictionary:getWordVocabulary(), final_word = dictionary:getWordId(""), } end ----------------------------------------------- -- pronunciation tree ----------------------------------------------- pronunciation_tree = parser.new_one_step.treeModel{ filename = filename_prontree, vocabulary = dictionary:getWordVocabulary(), is_mmaped = binary_prefix_tree, desired_gsf = pt_gsf, } ---------------------------------------------------------------------- -- construmos el lmtrellis: if getmetatable(ngram_model).id == ngram.nnlm.meta_instance.id then lmtrellis = parser.new_one_step.NNLMPBTrellis{ lm = ngram_model, trellis_log2_hash_size = trll_log2_hash_size, trellis_log2_max_nodes = trll_log2_max_nodes, initial_word = dictionary:getWordId(initial_ngram_word), final_word = dictionary:getWordId(final_ngram_word), gsf = gsf, wip = wip, } else lmtrellis = parser.new_one_step.LiraPBTrellis{ lm = ngram_model, trellis_log2_hash_size = trll_log2_hash_size, trellis_log2_max_nodes = trll_log2_max_nodes, initial_word = dictionary:getWordId(initial_ngram_word), final_word = dictionary:getWordId(final_ngram_word), gsf = gsf, wip = wip, use_context_cues = use_context_cues, } end ---------------------------------------------------------------------- -- creamos un heappruner: pruner = parser.new_one_step.HeapPruner(hist_prun_size, beam_width) ---------------------------------------------------------------------- -- construimos el lexdecoder: lexdecoder = parser.new_one_step.LexDecoder{ tree_model = pronunciation_tree, max_hyps = max_hyps, hist_prun_size = hist_prun_size, hist_prun_step = hist_prun_step, lr_hmms = hmm.lrhmm, pruner = pruner, lm_trellis = lmtrellis, silence_index = tied_model.name2id[word_sil]-1, -- FIXME hay que restar 1 :( si no se lo resto no va } ---------------------------------------------------------------------- -- crear el objeto decoder, que es un consumidor: decoder = parser.new_one_step.decoder{ lexdecoder = lexdecoder, a_prioris = hmm.aprioris } ---------------------------------------------------------------------- -- cargamos el MLP ann = {} ann.left_context = tonumber(optargs.context or 8) ann.right_context = tonumber(optargs.context or 8) ann.bunch_size = tonumber(optargs.bunch_size or 96) ann.bunched_net = mlp.load(filename_ann, ann.bunch_size) ann.emiss_func = ann.bunched_net:get_function() ---------------------------------------------------------------------- -- los datos de prueba test = field_manager() recog.generate_filenames{ corpus_data_manager = test, filename_mfc = filename_test, prepfilename = filename_prep, txtfilename = filename_txt, } -- local frames_source local frames_normalization local frames_contextualizer AUXF = io.open("aux.log", "w") local total_num_words = 0 local lista_tasas = {} local count_gc = 0 -- numero total de tramas procesadas, sirve para medir al final el -- tiempo CPU por trama: local total_processed_frames = 0 -- total de frases correctas, para calcular el SER local correct_sentences = 0 cronometro = util.stopwatch() local last_recog_lm_wids = nil local index = 0 local mfcc_filename if ose_file then ose_file = io.open(ose_file, "r") end num_sentences = #test:get_field('mfcc_filename') for index = 1,num_sentences do count_gc = count_gc+1 if count_gc >= 10 then collectgarbage("collect") count_gc = 0 end mfcc_filename = test:get_field('mfcc_filename')[index] -- cargamos el dataset correspondiente a la frase actual local tr_filename if filename_txt then tr_filename = test:get_field('transcription_filename')[index] end local prep_filename if filename_prep then prep_filename = test:get_field('prep_filename')[index] end local basenamestr = "" if mfcc_filename then basenamestr = remove_extensions(string.basename(mfcc_filename)) end local tr_string if tr_filename then fprintf(io.stderr,"# Cargando transcripcion: \t%s\n", tr_filename) tr_string = io.open(tr_filename):read("*l") end local frames local actual_ds local numFrames = 1 local numParams = 1 fprintf(io.stderr,"# Cargando frames: \t%s\n", mfcc_filename) if feats_format == 'mat' then frames = load_matrix(mfcc_filename) elseif feats_format == 'raw' then frames = load_raw(mfcc_filename) end -- if mfcs_matrix_format then -- frames = load_matrix(mfcc_filename) -- else -- frames = load_mfcc(mfcc_filename) -- end numFrames = frames:dim()[1] numParams = frames:dim()[2] local parameters = { patternSize = {dataset_step, numParams}, offset = {0,0}, -- default value stepSize = {dataset_step, 0}, -- default value, second value is not important numSteps = {numFrames/dataset_step, 1} } actual_ds = dataset.matrix(frames, parameters) if feats_mean_and_devs then actual_ds:normalize_mean_deviation(feats_mean_and_devs.means, feats_mean_and_devs.devs) end actual_ds = dataset.contextualizer(actual_ds, ann.left_context, ann.right_context) -- cargamos la transcripcion ortografica local correcta = tr_string -- RUN ONE STEP PARSER duration = wsize + numFrames*wadvance fprintf(io.stderr,"# RUN %4d/%d (%d frames %s secs)\n", index,num_sentences,numFrames,duration) t1cpu, t1wall = cronometro:read() cronometro:go() if ose_file then -- carga la sobresegmentacion de fichero local current_ose_filename = ose_file:read("*l") local current_ose = io.open(current_ose_filename) local frontiers = current_ose:read("*a") current_ose:close() -- print("frontiers has lenght",#frontiers) decoder:set_frontiers_string(frontiers) fprintf(io.stderr, "# Loading frontier %s\n", current_ose_filename) end ann.emiss_func:calculate_in_pipeline{ producer = functions.dataset_producer(actual_ds), consumer = decoder, input_size = ann.emiss_func:get_input_size(), output_size = ann.emiss_func:get_output_size(), } path,logprob=decoder:get_result() cronometro:stop() t2cpu, t2wall = cronometro:read() if path then reconocida = table.concat(dictionary:searchWordsSequenceFromWIDs(path)," ") print(reconocida) fprintf (io.stderr,"###########################################\n") fprintf (io.stderr,"# logprob N-grama: %f\n",logprob) fprintf(io.stderr,"# Correcta: %s\n",(correcta or "N/A")) fprintf(io.stderr,"# Reconocida N-grama: %s\n",view_filter(reconocida)) if correcta and filter(reconocida or "") == filter(correcta) then correct_sentences = correct_sentences + 1 end total_num_words = total_num_words + #string.tokenize(reconocida) tWall = t2wall - t1wall tCPU = t2cpu - t1cpu if tWall > 0 then framesPerSecond = numFrames/tWall else framesPerSecond = 0 end if recog_type == "asr" then RTfactor = tWall/duration fprintf(io.stderr,"# Tiempo: %.2f (cpu) %.2f (wall) %.2f frames/s (%.2f x RT)\n", tCPU, tWall, framesPerSecond, RTfactor) else fprintf(io.stderr,"# Tiempo: %.2f (cpu) %.2f (wall) %.2f frames/s\n", tCPU, tWall, framesPerSecond) end fprintf(io.stderr,"###########################################\n") total_processed_frames = total_processed_frames + numFrames + 1 ------------------------------------------------------------ -- para tasas if correcta then table.insert(lista_tasas,{filter(correcta), filter(reconocida)}) AUXF:write(filter(correcta).."="..filter(reconocida).."\n") end ------------------------------------------------ else fprintf(io.stderr,"# Correcta: %s\n",(correcta or "N/A")) fprintf(io.stderr,"# Reconocida N-grama: \n") if correcta then table.insert(lista_tasas,{filter(correcta), ""}) if filter(reconocida or "") == filter(correcta) then correct_sentences = correct_sentences + 1 end end fprintf(io.stderr,"# Error, no se ha encontrado camino!!\n") print("") end fprintf(io.stderr,"\n") io.stdout:flush() io.stderr:flush() -------------------------------------------------------- end AUXF:close() if filename_txt then local resul_val = tasas{ typedata = "pairs_lines", -- words_sep valor por defecto data = lista_tasas, tasa = "ie", -- para calcular wer } fprintf(io.stderr,"Tasa WER: %f\n", resul_val.tasa) local resul_val = tasas{ typedata = "pairs_lines", data = lista_tasas, tasa = "ie", -- para calcular wer words_width = 1, } fprintf(io.stderr,"Tasa CER: %f\n", resul_val.tasa) fprintf(io.stderr,"Tasa SER: %f\n", 100*(1 - correct_sentences/num_sentences)) end total_cpu_time, total_wall_time = cronometro:read() fprintf(io.stderr,"Total time: %.2f (cpu) %.2f (wall), cpu_time/sentence %.4f cpu_time/word %.4f\n", total_cpu_time, total_wall_time, total_cpu_time/num_sentences, total_cpu_time/total_num_words) fprintf(io.stderr,"wall_time/sentence %.4f wall_time/word %.4f", total_wall_time/num_sentences, total_wall_time/total_num_words) if recog_type == "asr" then RTfactor = total_wall_time/(total_processed_frames*wadvance) fprintf(io.stderr,", RT factor: %.2f x RT",RTfactor) end fprintf(io.stderr,"\n") april-ann-0.4.1/tools/HMM_ANN/recognition/opt.lua000066400000000000000000000235211263004425400215020ustar00rootroot00000000000000return cmdOpt{ program_name = string.basename(arg[0]), argument_description = "", main_description = "HMM/ANN recognition with April toolkit", { index_name="defopt", description="Load configuration file (a lua tabla)", short="f", argument="yes", }, { index_name="server", description="Execute in server mode, listening in the specified port. The server receives the parameters vector.", long="server", argument="yes", }, { index_name="bunch_size", description="Size of bunch for MLPs", long="bunch-size", argument="yes", }, { index_name="one_step", description="One step algorithm [default='no']", long="one-step", argument="yes", }, { index_name="n", description = "MLP file", short = "n", argument = "yes", }, { index_name="m", description = "hmms file", short = "m", argument = "yes", }, { index_name="hmmdefs", description = "hmms HTK file", long = "hmmdefs", argument = "yes", }, { index_name="t", description = "HTK unit's tied list", short = "t", argument = "yes", }, { index_name="d", description = "HTK dictionary", short = "d", argument = "yes", }, { index_name="optsil", description = "Use optional silence at begin and end of a sentence [default='no']", long = "optsil", argument = "yes", }, { index_name="beginsil", description = "Use optional silence at begin of a sentence [default='no']", long = "beginsil", argument = "yes", }, { index_name="endsil", description = "Use optional silence at end of a sentence [default='no']", long = "endsil", argument = "yes", }, { index_name="wordsil", description = "Add optional silence between words [default='no']", long = "wordsil", argument = "yes", }, { index_name="nested", description = "Parallelize emission evaluation and step viterbi when compiled with openmp [default='no']", long = "nested", argument = "yes", }, { index_name="p", description = "File with the corpus mfccs data", short = "p", argument = "yes", }, { index_name="input_lattice", description = "File with an input lattices list", long = "input-lattice", argument = "yes", }, { index_name="use_input_lat_lm_score", description = "Force to use the input lattice LM scores [default='no']", long = "use-input-lat-lm-score", argument = "yes", }, { index_name="input_lat_log_base", description="Base of the logarithms in lattices [default=exp(1)]", long="input-lat-log-base", argument="yes", }, { index_name="prep", description = "File with the corpus preprocessed data", long = "prep", argument = "yes", }, { index_name="txt", description = "File with the corpus transcriptions", long = "txt", argument = "yes", }, { index_name="ose_file", description = "Over SEgmenter index file, with one string for each corpus file [optional]", long = "ose-file", argument = "yes", }, { index_name="lm", description = "Language model [default=dont use LM]", long = "lm", argument = "yes", }, { index_name="ngram_nstates", description = "Number of max states for ngram parser pruning [default=10000]", long = "ngram-nstates", argument = "yes", }, { index_name="ngram_beam", description = "Beam for ngram parser pruning [default=2000]", long = "ngram-beam", argument = "yes", }, { index_name="ngram_size", description = "Histogram size for ngram parser pruning [default=400]", long = "ngram-size", argument = "yes", }, { index_name="viterbim_size", description = "Vector size for viterbi_m decoders", long = "viterbim-size", argument = "yes", }, { index_name="wgen_nstates", description = "Number of max states for wgen pruning [default=4000, one-step=no]", long = "wgen-nstates", argument = "yes", }, { index_name="wgen_beam", description = "Beam for wgen pruning [default=1000, one-step=no]", long = "wgen-beam", argument = "yes", }, { index_name="wgen_size", description = "Histogram size for wgen parser pruning [default=200, one-step=no]", long = "wgen-size", argument = "yes", }, { index_name="gsf", description = "Grammar Scale Factor [default=10]", long = "gsf", argument = "yes", }, { index_name="wip", description = "Word Insertion Penalty [default=0]", long = "wip", argument = "yes", }, { index_name="seg", description="Save segmentation [default=no]", long="seg", argumento="yes" }, { index_name="save_input_wg", description="Save the acoustic/optic word_graph filtered with the NBest", long="save-input-wg", argument="yes", }, { index_name="dog", description = "DOG or DAF :-) the Oversegmenter is always dummy", long = "dog", argument = "yes", }, { index_name = "use_word_probs", description = "Use probs. stored in dictionary [default='yes']", long = "use-word-probs", argument = "yes" }, { index_name = "apply_gsf_word_probs", description = "Apply GSF to word probs [default='no']", long = "apply-gsf-word-probs", argument = "yes" }, { index_name = "context", description = "Size of ann context [default=4]", long = "context", argument = "yes" }, { index_name = "filter", description = "Fiter output sentence before tasas, is a file that return a LUA function [default=nil]", long = "filter", argument = "yes", }, { index_name = "view_filter", description = "Fiter output sentence to show result, is a file that return a LUA function [default=nil]", long = "view-filter", argument = "yes", }, { index_name = "max_h_out", description = "Max HOut for NBest graph [default=0]", long = "max-h-out", argument = "yes", }, { index_name = "save_nbest_wg", description = "Word Graph of NBest filename", long = "save-nbest-wg", argument = "yes", }, { index_name = "nbest", description = "Number of nbest", long = "nbest", argument = "yes", }, { index_name = "save_nbest", description = "Filename for save Nbest list", long = "save-nbest", argument = "yes", }, { index_name = "features", description = "Filename for save Nbest list features", long = "features", argument = "yes", }, { index_name = "uniq_nbest", description = "For indicate UNIQ nbest paths [default=yes]", long = "uniq-nbest", argument = "yes", }, { index_name = "lattice_tool", description = "For indicate the use of lattice-tool for nbest [default=no]", long = "lattice-tool", argument = "yes", }, { index_name = "cache_size", description = "Size of cache for NNLMs [default=20]", long = "cache-size", argument = "yes", }, { index_name = "use_ref_annotations", description = "Use reference annotations for hte CACHE [default=no]", long = "use-ref-annotations", argument = "yes", }, { index_name = "trie_size", description = "Size of TrieVector for NNLMs [default=24]", long = "trie-size", argument = "yes", }, { index_name = "feats_format", description = "Format of features (mat or mfc)", long = "feats-format", argument = "yes", }, { index_name = "feats_norm", description = "Table with means and devs for features", long = "feats-norm", argument = "yes", }, { index_name = "recog", description = "Recog type: asr, htr, online [default=htr]", long = "recog", argument = "yes" }, { index_name = "ose", description = "Oversegmenter type: dummy, htr, maxdiff, online [default=dummy in asr recog type, htr in htr recog type, online in htr-online recog type]", long = "ose", argument = "yes", }, { index_name = "cells_per_frame", description = "Number of cells per frame in the parametrizer (default: 20)", long = "cells-per-frame", argument = "yes", }, { index_name = "wadvance", description = "Window advance in ASR, in milliseconds [default=10] used to compute the real time factor", long = "wadvance", argument = "yes", }, { index_name = "output_lm_words", description = "Output LM Words instead of OutSyms [default=no]", long = "output-lm-words", argument = "yes", }, { index_name = "use_bcc", description = "Use BCC during decoding [default=yes]", long = "use-bcc", argument = "yes", }, { index_name = "use_ecc", description = "Use ECC during decoding [default=yes]", long = "use-ecc", argument = "yes", }, { index_name = "unk", description = "Generate UNK words at the recognizer output given the difference ".. "threshold: a positive number [default NONE]", long = "unk", argument = "yes", }, { index_name = "cache_txt", description = "Transcriptions for CACHE before each recognition step (default: nil)", long = "cache-txt", argument = "yes", }, { index_name = "discriminative_smoothing", description = "Apply discriminative smoothing (linear interpolation) with given parameter (default: nil)", long = "discriminative-smoothing", argument = "yes", }, { index_name = "right_left", description = "recognise going from right to left (default: no)", long = "right-left", argument = "yes", }, { description = "shows this help message", short = "h", long = "help", argument = "no", action = function (argument) print(cmdOptTest:generate_help()) os.exit(1) end } } april-ann-0.4.1/tools/HMM_ANN/recognition/recog.lua000066400000000000000000001251051263004425400220000ustar00rootroot00000000000000dir = string.gsub(arg[0], string.basename(arg[0]), "") dir = (dir~="" and dir) or "./" loadfile(dir .. "utils.lua")() fprintf(io.stderr,"# HOST:\t %s\tload avg: %s\n", (io.popen("hostname", "r"):read("*l")), (io.open("/proc/loadavg"):read("*l"))) fprintf(io.stderr,"# DATE:\t %s\n", (io.popen("date", "r"):read("*l"))) fprintf(io.stderr,"# CMD: \t %s %s\n",string.basename(arg[0]), table.concat(arg, " ")) -------------------------------------------------- cmdOptTest = dofile(dir .. "/opt.lua") optargs = cmdOptTest:parse_args() if type(optargs) == "string" then error(optargs) end if optargs.defopt then local t = dofile(optargs.defopt) for name,value in pairs(t) do if not optargs[name] then fprintf(io.stderr,"# opt %s = %s\n", name, tostring(value)) optargs[name] = value end end end if optargs.bunch_size then error("Bunch mode not implemented!!!, we are working in it ;)") end log10 = math.log(10) -------------------------------------------------- --optargs.fast_nn_lm = true server_port = optargs.server one_step = ((optargs.one_step or "no") == "yes") -- Red neuronal filenet = optargs.n -- Fichero de HMMs filem = optargs.m -- Fichero HTK filehmmdefs = optargs.hmmdefs -- Fichero OSE ose_file = optargs.ose_file -- dictfile = optargs.d or error ("Needs a dictionary!!!") use_optional_sil = (optargs.optsil == "yes") use_word_sil = (optargs.wordsil == "yes") nested_openmp = (optargs.nested == "yes") lattice_tool = optargs.lattice_tool output_lm_words = ((optargs.output_lm_words or "no") == "yes") save_seg = (optargs.seg or "no") == "yes" testfile = optargs.p input_lat = optargs.input_lattice use_input_lat_lm_score = ((optargs.use_input_lat_lm_score or "no") == "yes") input_lat_log_base = optargs.input_lat_log_base if (input_lat_log_base or use_input_lat_lm_score) and not input_lat then error ("Needs --input-lat") end if not input_lat and not server_port and not testfile then error ("Needs a corpus testfile -p option or a --text-input option!!!") end tiedfile = optargs.t or (input_lat==nil and error ("Needs a tiedlist!!!")) prepfile = optargs.prep txtfile = optargs.txt or fprintf(io.stderr,"Warning!!! running without transcriptions --txt!!!\n") ose_type = optargs.ose recog_type = optargs.recog langmodel = optargs.lm if use_input_lat_lm_score and langmodel then error("Forbidden to use a LM when use-input-lat-lm-socre='yes'") end inputwg = optargs.save_input_wg dataset_step = tonumber(optargs.step or 1) max_h_out = tonumber(optargs.max_h_out or 0) cache_size = tonumber(optargs.cache_size) trie_size = tonumber(optargs.trie_size) feats_format = optargs.feats_format or "mfc" feats_mean_and_devs = optargs.feats_norm wg_filename = optargs.save_nbest_wg nbest_filename = optargs.save_nbest num_nbest = tonumber(optargs.nbest or 0) features_filename = optargs.features uniq_nbest = optargs.uniq_nbest or "yes" wadvance = (optargs.wadvance or 10) / 1000 -- para pasar a segundos unk_threshold = tonumber(optargs.unk or "NONE") cache_txt = optargs.cache_txt use_ref_annotations = ((optargs.use_ref_annotations or "no") == "yes") right_left = (string.lower(optargs.right_left or "no") == "yes") cells_per_frame = tonumber(optargs.cells_per_frame or 20) use_bcc = ((optargs.use_bcc or "yes") == "yes") use_ecc = ((optargs.use_ecc or "yes") == "yes") if cache_txt then cache_txt = io.open(cache_txt, "r") or error ("File not found: " .. cache_txt) end if server_port then server_port = tonumber(server_port) end if use_ref_annotations and not txtfile then error ("use_ref_annotations needs a txtfile") end viterbi_m_size = optargs.viterbim_size recog_type = string.lower(recog_type) if num_nbest > 0 and max_h_out == 0 then error("max_h_out must be > 0 when nbest > 0!!!") end if right_left and wg_filename then error ("Forbidden Output WordGraph and RightLeft feature") end if features_filename then features_file = io.open(features_filename, "w") or error("Cant create file: " .. features_filename) end if nbest_filename then nbest_file = io.open(nbest_filename, "w") or error("Cant create file: " .. nbest_filename) end read_mfcs_in_matrix_format = (feats_format == "mat") if feats_mean_and_devs then feats_mean_and_devs = dofile(feats_mean_and_devs) end if server_port then prepfile = nil txtfile = nil testfile = nil end ---------------------------------------------------------------------------------- use_word_dict_probs = ((optargs.use_word_probs or "yes") == "yes") apply_gsf_word_probs = ((optargs.apply_gsf_word_probs or "no") == "yes") ann = {} ann.left_context = tonumber(optargs.context or 4) ann.right_context = tonumber(optargs.context or 4) -- Parsing grammar_scale_factor = optargs.gsf or 10.0 word_insertion_penalty = optargs.wip or 0.0 nolm = (optargs.lm == nil) viterbi_type = "viterbi_m" -- viterbi_m" --"hash_fast_it" -- viterbi_m, array_swap, active_envelope, hash_array_swap, hash_fast_it if not one_step then if not input_lat then wgen_hist_pruning_conf = { beam_width = optargs.wgen_beam or 1000, size = optargs.wgen_size or 200, max_states = optargs.wgen_nstates or 4000, } wgen_feedback = true end else if optargs.wgen_beam or optargs.wgen_size or optargs.wgen_nstates then fprintf(io.stderr, "# Warning!!! WGEN pruning parameters are ignored when one_step=\"yes\"\n") end end hist_pruning_conf = { beam_width = optargs.ngram_beam or 2000, size = optargs.ngram_size or 400, max_states = optargs.ngram_nstates or 10000, } -- parametros de NGRAMAS initial_ngram_word = '' final_ngram_word = '' unk_ngram_word = '' -- SSE if ose_type and ose_file then error ("ose-file and ose are incompatible") end if not ose_type then if recog_type == "asr" then ose_type = "dummy" elseif recog_type == "htr" then ose_type = "htr" elseif recog_type == "online" then ose_type = "online" else error("Incorrect recognizer type: " .. recog_type) end end if ose_type == "dummy" then segmenter = nil sse_type = "dummy" elseif ose_type == "htr" then segmenter = DFS_CC_Oversegmenter() sse_type = "from_string" -- dummy, from_string, max_diff elseif ose_type == "online" then segmenter = nil sse_type = "from_string" elseif ose_type == "maxdiff" then segmenter = nil sse_type = "maxdiff" else error("Incorrect Oversegmenter type: " .. ose_type) end if ose_file then sse_type = "from_string" end if optargs.dog then segmenter=nil sse_type = "dummy" end sse_past = 5 sse_future = 5 sse_dist_max_front = 3 sse_distance = "inf-norm" -- 1-norm, 2-norm, inf-norm if optargs.filter then filter = dofile(optargs.filter) else filter = function (str) return str end end if optargs.view_filter then view_filter = dofile(optargs.view_filter) else view_filter = function (str) return str end end -- objeto con informacion sobre modelos ligados if tiedfile then tied = tied_model_manager(io.open(tiedfile) or error("File not found: " .. tiedfile)) end -- objeto con el diccionario fprintf(io.stderr,"# Loading dictionary\n") dictionary = lexClass.load(io.open(dictfile) or error ("File not found: " .. dictfile)) pairid2wordstr = {} for i=1,dictionary:pairsTblSize() do table.insert(pairid2wordstr, tostring(i)) end ---------- -- HMMs -- ---------- hmm = {} unk_pair_ids = {} if filem and filenet then -- HIBRIDOS m = dofile(filem) hmm.models = m[1] hmm.aprioris = m[2] --------------------------------------- -- cargamos la red neuronal lared = Mlp.load{ filename=filenet } emissions_func = lared --------------------------------------- -- creamos las unidades LR hmm.tree = {} hmm.tree.unit2id = {} hmm.tree.units = parser.lr_hmm_dictionary() local id = 1 for name,model_info in pairs(hmm.models) do id = id + 1 local lprobs = {} for _,t in ipairs(model_info.model.transitions) do if t.from == t.to then lprobs[t.from-3] = math.exp(t.lprob) end end if right_left then hmm.tree.unit2id[name] = hmm.tree.units:insert_unit { emiss_indexes = table.reverse(model_info.emissions), loop_probs = table.reverse(lprobs), } else hmm.tree.unit2id[name] = hmm.tree.units:insert_unit { emiss_indexes = model_info.emissions, loop_probs = lprobs, } end end -- CREAMOS EL OBJETO LEXICO EN ARBOL hmm.tree.lexicon = parser.tree_lexicon() -- ahora metemos el diccionario -- para cada par (word,outsym) for pairid=1,dictionary:pairsTblSize() do local wid,oid = dictionary:getPair(pairid) local data = dictionary:getData(pairid) local us = data.units -- la transcripcion if data.word == unk_ngram_word then table.insert(unk_pair_ids, pairid) end if #us > 0 then -- si units es mayor que 0, entonces lo metemos en el lexico local t = {} -- para cada unidad de la transcripcion for j,u in ipairs(tied:search_triphone_sequence(us)) do table.insert(t, hmm.tree.unit2id[u]) if not hmm.tree.unit2id[u] then error("ERROR incorrect hmm model in tiedlist: [ "..u.." ]") end end -- sacamos el outsym index local prob = data.prob or 0.0 if apply_gsf_word_probs then prob = prob * grammar_scale_factor end prob = math.exp(prob) if not use_word_dict_probs then prob = 1.0 end -- insertamos en el tree_lexicon if right_left then t = table.reverse(t) end if prob ~= 0 then hmm.tree.lexicon:insert_word(t, pairid, prob) end -- else print (wid, paird, prob, -- dictionary.oid2outsym[dictionary.pairs[pairid].oid]) end end end elseif filehmmdefs then -- HTK if right_left then error('right_left is not currently supported for HTK models') end hmm.tree = {} hmm.models = htk_interface.load_hmm_set(filehmmdefs) hmm.tree.units,htk_triphone_table = htk_interface.build_lr_hmm_dictionary(tied, hmm.models) hmm.tree.lexicon = htk_interface.build_tree_lexicon(dictionary, tied, htk_triphone_table, forbiden_words) emissions_func = functions.join(table.invert(hmm.models.all_mixtures)) hmm.tree.unit2id = htk_triphone_table elseif not input_lat then error ("arg's -m and -n, or --hmmdefs, are needed!!!") end -- Silencios gsub_sils = "" if not input_lat then if recog_type == "htr" then hmm.silences = { ["@"] = { prob = 1.0, output = 0 -- lambda } } begin_sil = "@" end_sil = "@" word_sil = "@" gsub_sils = "%@" elseif recog_type == "online" then hmm.silences = { } begin_sil = "" end_sil = "" word_sil = "" gsub_sils = "" else hmm.silences = { ["."] = { prob = 1.0, output = 0 -- lambda }, ["("] = { prob = 1.0, output = 0 -- lambda }, [")"] = { prob = 1.0, output = 0 -- lambda } } begin_sil = "(" end_sil = ")" word_sil = "." gsub_sils = "%.%(%)" end end -------------------------------------- -- Cargamos el modelo de ngramas... -- -------------------------------------- fprintf(io.stderr,"# Cargamos el modelo de ngramas y creamos el parser\n") if langmodel then -- estadistico ngram_model = ngram.load_language_model(langmodel, dictionary, initial_ngram_word, final_ngram_word, -- EXTRA { cache_size = cache_size, trie_size = trie_size, }) else -- NO LM fprintf(io.stderr, "# Loop LM\n") ngram_model = ngram.lira.loop{ vocabulary_size = #dictionary:getWordVocabulary(), final_word = dictionary:getWordId(final_ngram_word), } end --ngram_model:sanity_check() ----------------------- -- CREAMOS EL PARSER -- ----------------------- if not one_step then model_parser = ngram.load_parser(ngram_model, dictionary, initial_ngram_word, final_ngram_word, max_h_out) if not use_bcc then model_parser:set_use_begin_context_cue(false) end if not use_ecc then model_parser:set_use_end_context_cue(false) end end ---------------------------------------------------------------- -- GENERAMOS EL MODELO DE MARKOV HMM para el lexico en arbol -- ---------------------------------------------------------------- if not input_lat then if not one_step then hmm.tree.lexicon_model = hmm.tree.lexicon:tree_lr_hmm_model(hmm.tree.units) if viterbi_m_size then hmm.tree.lexicon_model:set_size_active_state_vector(viterbi_m_size); end hmm.tree.lexicon_factory = parser.factory[viterbi_type](hmm.tree.lexicon_model) else hmm.tree.lexicon_model = parser.one_step.treeParserModel(hmm.tree.units, hmm.tree.lexicon) end --hmm.tree.units:print() --hmm.tree.lexicon:print() -- silencios if use_word_sil then if not one_step then hmm.tree.word_sil = parser.tree_lexicon() hmm.tree.word_sil:insert_word({hmm.tree.unit2id[tied:search_triphone(nil, word_sil, nil)] }, hmm.silences[word_sil].output, hmm.silences[word_sil].prob) hmm.tree.word_sil_model = hmm.tree.word_sil:tree_lr_hmm_model(hmm.tree.units) hmm.tree.word_sil_factory = parser.factory[viterbi_type](hmm.tree.word_sil_model) end end if use_optional_sil then hmm.tree.begin_sil = parser.tree_lexicon() hmm.tree.end_sil = parser.tree_lexicon() hmm.tree.begin_sil:insert_word({hmm.tree.unit2id[tied:search_triphone(nil, begin_sil, nil)] }, hmm.silences[begin_sil].output, hmm.silences[begin_sil].prob) if not one_step then hmm.tree.begin_sil_model = hmm.tree.begin_sil:tree_lr_hmm_model(hmm.tree.units) hmm.tree.begin_sil_factory = parser.factory[viterbi_type](hmm.tree.begin_sil_model) else hmm.tree.begin_sil_model = parser.one_step.treeParserModel(hmm.tree.units, hmm.tree.begin_sil) end hmm.tree.end_sil:insert_word({hmm.tree.unit2id[tied:search_triphone(nil, end_sil, nil)] }, hmm.silences[end_sil].output, hmm.silences[end_sil].prob) if not one_step then hmm.tree.end_sil_model = hmm.tree.end_sil:tree_lr_hmm_model(hmm.tree.units) hmm.tree.end_sil_factory = parser.factory[viterbi_type](hmm.tree.end_sil_model) else hmm.tree.end_sil_model = parser.one_step.treeParserModel(hmm.tree.units, hmm.tree.end_sil) end end end ---------------------------------------------- -- CREAMOS UN PARSER_FACTORY_AUTOMATA if not input_lat then if unk_threshold then if one_step then error ("Not implemented 'unk' option for one step algorithm!!!") else if #unk_pair_ids > 1 then error ("Forbidden more than one " .. unk_ngram_word .. " pair in dictionary!!!") end local filler_parser_factory = parser.simple_filler(unk_pair_ids[1], hmm.tree.units) local lexicon_plus_oov_factory = parser.factory.lexicon_plus_oov{ lexicon_parser_factory = hmm.tree.lexicon_factory, filler_parser_factory = filler_parser_factory, } hmm.tree.lexicon_factory = lexicon_plus_oov_factory end end if not one_step then if use_optional_sil then transitions = { {from="ini",to="med",prob=1,arc=hmm.tree.begin_sil_factory}, {from="ini",to="med",prob=1,arc=hmm.tree.lexicon_factory}, {from="ini",to="fin",prob=1,arc=hmm.tree.lexicon_factory}, {from="med",to="med",prob=1,arc=hmm.tree.lexicon_factory}, {from="med",to="fin",prob=1,arc=hmm.tree.end_sil_factory}, {from="med",to="fin",prob=1,arc=hmm.tree.lexicon_factory}, } else transitions = { {from="ini",to="med",prob=1,arc=hmm.tree.lexicon_factory}, {from="ini",to="fin",prob=1,arc=hmm.tree.lexicon_factory}, {from="med",to="med",prob=1,arc=hmm.tree.lexicon_factory}, {from="med",to="fin",prob=1,arc=hmm.tree.lexicon_factory}, } end if use_word_sil then table.insert(transitions, {from="med", to="sil", prob=1, arc=hmm.tree.word_sil_factory}) table.insert(transitions, {from="sil", to="med", prob=1, arc=hmm.tree.lexicon_factory}) end hmm.tree.factory_automata = parser.factory.automata{ initials = { {"ini", 1} }, finals = { {"fin", 1}, }, transitions=transitions } end end --print(hmm.tree.lexicon_factory) --print(hmm.tree.factory_automata) --hmm.tree.factory_automata:print() -- ------------------------------------- -- -------------- -- DATAFLOW -- -------------- test = field_manager() if not server_port then -- nombres de ficheros recog.generate_filenames{ corpus_data_manager = test, filename_mfc = testfile, input_lat_filename = input_lat, prepfilename = prepfile, txtfilename = txtfile, } end -- local frames_source local frames_normalization local frames_contextualizer if not one_step then -- dataflow the_dataflow = dataflow() -- if inputwg then -- iohandler = dataflow.process.iohandler{ -- dataflow = the_dataflow, -- service_name = "iohandler" -- } -- -- df_serializer = dataflow.process.serializer{ -- dataflow = the_dataflow, -- io_service_name = "iohandler", -- filename=inputwg, -- } end -- if not server_port then if not input_lat then -- leemos de dataset frames_source = dataflow.process.dataset_source{ dataflow = the_dataflow, } end else iohandler = dataflow.process.iohandler{ dataflow = the_dataflow, service_name = "iohandler" } -- leer de socket y aplicar medias y desviaciones frames_source = dataflow.process.deserializer{ dataflow = the_dataflow, io_service_name = "iohandler", host = "0.0.0.0", port = server_port, } if feats_mean_and_devs then frames_normalization = dataflow.process.mean_and_devs_normalization{ dataflow = the_dataflow, means = feats_mean_and_devs.means, devs = feats_mean_and_devs.devs, } end local dim = emissions_func:get_input_size() / (ann.left_context + ann.right_context + 1) frames_contextualizer = dataflow.process.contextualizer{ dataflow = the_dataflow, left = ann.left_context, right = ann.right_context, input_dim = dim, } end if not input_lat then -- gausianas df_emissions = dataflow.process.function_box{ dataflow = the_dataflow, the_function = emissions_func:get_function(), } if filehmmdefs==nil then logp = dataflow.process.df_logp { dataflow = the_dataflow, prior_probs = hmm.aprioris, -- en este punto se podria poner un vector de indices para -- reordenar las emisiones que llegan a los modelos del -- seq_graph_gen } end -- sse if sse_type == "maxdiff" then sse = dataflow.process.sse_maxdiff_simple{ dataflow = the_dataflow, past = sse_past, future = sse_future, dist_max_front = sse_dist_max_front, distance = sse_distance, } elseif sse_type == "dummy" then sse = dataflow.process.sse_dummy{ dataflow = the_dataflow } elseif sse_type == "from_string" then sse = dataflow.process.sse_from_string{ dataflow = the_dataflow } end -- creamos el grafo de palabras wgen = dataflow.process.df_seq_graph_gen{ dataflow = the_dataflow, automata = hmm.tree.factory_automata, } wgen:configure_histogram_pruning(wgen_hist_pruning_conf) else -- en este caso WGEN es una fuente de grafos wgen = dataflow.process.word_graph_out{ dataflow = the_dataflow, force_topologic_order = true, } end -- -- ngram a_parser = dataflow.process.parser{ dataflow = the_dataflow, parser = model_parser, lex_table = dictionary:getCObject(), } -- -- sse_spy = dataflow.process.filter_spy{ -- dataflow=the_dataflow, -- path="sse2.log", -- name="sse_spy" -- } -- sink a_sink = dataflow.process.dummy_sink{ dataflow = the_dataflow, } if inputwg then -- WORD GRAPH IN -- -- creamos una caja para el word_graph_in wgraph_in = dataflow.process.word_graph_in(the_dataflow) ------------------- end --------------------------------------------- if not input_lat then if not frames_normalization then if not frames_contextualizer then dataflow.connect ({frames_source, "output"}, {df_emissions, "input"}) else dataflow.connect ({frames_source, "output"}, {frames_contextualizer, "input"}) dataflow.connect ({frames_contextualizer,"output"}, {df_emissions, "input"}) end else dataflow.connect ({frames_source, "output"}, {frames_normalization, "input"}) if not frames_contextualizer then dataflow.connect ({frames_normalization, "output"}, {df_emissions, "input"}) else dataflow.connect ({frames_normalization, "output"}, {frames_contextualizer, "input"}) dataflow.connect ({frames_contextualizer, "output"}, {df_emissions, "input"}) end end if filehmmdefs==nil then dataflow.connect ({df_emissions, "output"}, {logp, "input"}) dataflow.connect ({logp, "output"}, {sse, "input"}) else dataflow.connect ({df_emissions, "output"}, {sse, "input"}) end dataflow.connect ({sse, "output"}, -- {sse_spy, "input"}) -- dataflow.connect ({sse_spy, "output"}, {wgen, "input1"}) end if inputwg then dataflow.connect ({wgen, "output1"}, {wgraph_in, "input"}) dataflow.connect ({wgraph_in, "output"}, {a_parser, "input"}) else if input_lat then dataflow.connect ({wgen, "output"}, {a_parser, "input"}) else dataflow.connect ({wgen, "output1"}, {a_parser, "input"}) end end -- BESTPROB FEEDBACK -- if wgen_feedback and not input_lat then dataflow.connect ({a_parser, "output2"}, {wgen, "input2"}) end ----------------------- -- NGRAM PARSER -- dataflow.connect ({a_parser, "output1"}, {a_sink, "input"}) ------------------ else model_parser = ngram.one_step.load_parser(ngram_model, dictionary, initial_ngram_word, final_ngram_word, hmm.tree.begin_sil_model, hmm.tree.end_sil_model, hmm.tree.lexicon_model) end -- configuramos el parser model_parser:configure_histogram_pruning(hist_pruning_conf) model_parser:set_grammar_scale_factor(grammar_scale_factor) model_parser:set_word_insertion_penalty(word_insertion_penalty) --AUXF = io.open("aux.log", "w") local total_num_words = 0 local lista_tasas = {} local count_gc = 0 -- numero total de tramas procesadas, sirve para medir al final el -- tiempo CPU por trama: local total_processed_frames = 0 -- total de frases correctas, para calcular el SER local correct_sentences = 0 cronometro = util.stopwatch() local last_recog_lm_wids = nil local last_correcta = nil local index = 0 local mfcc_filename local input_lat_filename if ose_file then local name = ose_file ose_file = io.open(ose_file, "r") or error("Not found file: " .. name) end while true do index = index + 1 if not server_port then if not testfile then if index > #test:get_field('input_lat_filename') then break end input_lat_filename = test:get_field('input_lat_filename')[index] else if index > #test:get_field('mfcc_filename') then break end mfcc_filename = test:get_field('mfcc_filename')[index] end end count_gc = count_gc+1 if count_gc >= 10 or server_port then collectgarbage("collect") count_gc = 0 end -- cargamos el dataset correspondiente a la frase actual local tr_filename if txtfile then tr_filename = test:get_field('transcription_filename')[index] end local prep_filename if prepfile then prep_filename = test:get_field('prep_filename')[index] end local basenamestr = "" if mfcc_filename then basenamestr = remove_extensions(string.basename(mfcc_filename)) end local tr_string if tr_filename then fprintf(io.stderr,"# Cargando transcripcion: \t%s\n", tr_filename) local ftr = io.open(tr_filename) or error ("File not found: " .. tr_filename) tr_string = ftr:read("*l") ftr:close() end local frames local actual_ds local numFrames = 1 local numParams = 1 if not server_port then if not mfcc_filename then fprintf(io.stderr,"# Word Graph input: \t%s\n", input_lat_filename) local wg = word_graph.from_htk_lattice(input_lat_filename, dictionary, use_input_lat_lm_score, "!NULL", input_lat_log_base) wgen:set_word_graph(wg) else fprintf(io.stderr,"# Cargando frames: \t%s\n", mfcc_filename) if read_mfcs_in_matrix_format then frames = load_matrix(mfcc_filename) else frames = load_mfcc(mfcc_filename) end numFrames = frames:dim()[1] numParams = frames:dim()[2] -- nCCs+1 local parameters if right_left then parameters = { patternSize = {dataset_step, numParams}, offset = {numFrames/dataset_step-1,0}, -- default value stepSize = {-dataset_step, 0}, -- default value, second value is not important numSteps = {numFrames/dataset_step, 1} } else parameters = { patternSize = {dataset_step, numParams}, offset = {0,0}, -- default value stepSize = {dataset_step, 0}, -- default value, second value is not important numSteps = {numFrames/dataset_step, 1} } end actual_ds = dataset.matrix(frames, parameters) if feats_mean_and_devs then actual_ds:normalize_mean_deviation(feats_mean_and_devs.means, feats_mean_and_devs.devs) end if filehmmdefs==nil then actual_ds = dataset.contextualizer(actual_ds, ann.left_context, ann.right_context, right_left) end end else fprintf(io.stderr,"# Esperando frames en: \t%d\n", server_port) end -- cargamos la transcripcion ortografica local correcta = tr_string if one_step then if server_port then error("ONE STEP forbidden with server port!!!") end t1cpu, t1wall = cronometro:read() cronometro:go() local frontiers = nil if sse_type == "from_string" and not input_lat_filename then if ose_file then -- carga la sobresegmentacion de fichero local current_ose = io.open(ose_file:read("*l")) or error ("File not found!!") frontiers = current_ose:read("*a") current_ose:close() elseif recog_type == "htr" then if not prep_filename then error ("Needs a preprocessed files list --prep options!!!") end fprintf(io.stderr,"# Cargando datos prep: \t%s\n", prep_filename) -- generamos la segmentacion a partir de las imagenes preprocesadas local img = ImageIO.read(prep_filename):to_grayscale() local _,img_height = img:geometry() local max_intraword_space = 999999 -- 50 -- frames local fatFrontiers = false frontiers = segmenter:oversegment(img, cells_per_frame, max_intraword_space, fatFrontiers) elseif recog_type == "online" then -- genera las fronteras para el online. TODO: pasar a C++ este codigo frontiers = { util.ose.compose_frontier{ util.ose.generate_output } } for ipat,pat in dataset.matrix(frames):patterns() do if pat[#pat] > 0 or ipat == numFrames then table.insert(frontiers, util.ose.compose_frontier{ util.ose.generate_output }) else table.insert(frontiers, util.ose.compose_frontier{ }) end end frontiers = table.concat(frontiers, "") end if #frontiers ~= numFrames+1 then error(string.format("Generated frontiers: %d, number of frames: %d", #frontiers, numFrames)) end --print(string.byte(frontiers,1,#frontiers)) --print(#frontiers, frontiers) if right_left then frontiers = util.ose.reverse(frontiers) end end -- RUN ONE STEP PARSER fprintf(io.stderr,"# RUN\n") model_parser:reset() model_parser:do_viterbi{ input_dataset = actual_ds, emissions_func = emissions_func:get_function(), a_prioris = hmm.aprioris, sse_string = frontiers, nested_openmp = nested_openmp, } cronometro:stop() t2cpu, t2wall = cronometro:read() else -- RUN AL DATAFLOW if inputwg then cpp_lex_wg = WordGraph() lex_wg = word_graph(cpp_lex_wg, dictionary) wgraph_in:set_word_graph(cpp_lex_wg) end if not server_port then if mfcc_filename then frames_source:set_dataset(actual_ds) end end if sse_type == "from_string" and not input_lat_filename then local frontiers = nil if server_port then error("FROM STRING ose is forbidden with server port!!!") end if ose_file then -- carga la sobresegmentacion de fichero local current_ose = io.open(ose_file:read("*l")) or error("File not found!!!") frontiers = current_ose:read("*a") current_ose:close() elseif recog_type == "htr" then if not prep_filename then error ("Needs a preprocessed files list --prep options!!!") end fprintf(io.stderr,"# Cargando datos prep: \t%s\n", prep_filename) -- generamos la segmentacion a partir de las imagenes preprocesadas local img = ImageIO.read(prep_filename):to_grayscale() local _,img_height = img:geometry() local max_intraword_space = 999999 -- 50 -- frames local fatFrontiers = false frontiers = segmenter:oversegment(img, cells_per_frame, max_intraword_space, fatFrontiers) elseif recog_type == "online" then -- genera las fronteras para el online. TODO: pasar a C++ este codigo frontiers = { util.ose.compose_frontier{ util.ose.generate_output } } for ipat,pat in dataset.matrix(frames):patterns() do if pat[#pat] > 0 or ipat == numFrames then table.insert(frontiers, util.ose.compose_frontier{ util.ose.generate_output }) else table.insert(frontiers, util.ose.compose_frontier{ }) end end frontiers = table.concat(frontiers, "") end if #frontiers ~= numFrames+1 then error(string.format("Generated frontiers: %d, number of frames: %d", #frontiers, numFrames)) end --print(string.byte(frontiers,1,#frontiers)) --print(#frontiers, frontiers) if right_left then frontiers = util.ose.reverse(frontiers) end sse:set_frontiers_string(frontiers) end fprintf(io.stderr,"# RUN\n") t1cpu, t1wall = cronometro:read() if ngram_model:has_cache() then ngram_model:restart() local wids_tbl = last_recog_lm_wids if use_ref_annotations and last_correcta then local correcta_tbl = string.tokenize(last_correcta) local correcta_wids = dictionary:searchWordIdSequence(correcta_tbl) wids_tbl = correcta_wids fprintf(io.stderr,"# Processed last %d reference words\n", #correcta_wids) elseif last_recog_lm_wids then fprintf(io.stderr,"# Processed last %d recog words\n", #last_recog_lm_wids) end if wids_tbl then for i=1,#wids_tbl do ngram_model:cacheWord(wids_tbl[i]) end end if cache_txt then local cache_txt_line = cache_txt:read("*l") local cache_words = string.tokenize(cache_txt_line) for i=1,#cache_words do if cache_words[i] == "" then ngram_model:clearCache() elseif cache_words[i] ~= "" then local w = dictionary:getWordId(cache_words[i]) or dictionary:getWordId(unk_ngram_word) ngram_model:cacheWord(w) end end fprintf(io.stderr,"# Processed %d extra cache words\n", #cache_words) end --ngram_model:showCache() end cronometro:go() resul=the_dataflow:run() cronometro:stop() t2cpu, t2wall = cronometro:read() if inputwg then local dot_str = lex_wg:to_dot() local f = io.open(string.format("%s_%s_%05d.dot", inputwg, basenamestr, index), "w") f:write(dot_str.."\n") f:close() cpp_lex_wg = nil lex_wg = nil end if not resul then fprintf(io.stderr,"Error al hacer dataflow:run()\n") end end -- GET WORDGRAPH -- wgraph = wgraph_in:get_word_graph() -- local wgf = io.open("grafo.dot", "w") -- wgf:write(wgraph:to_dot(dictionary:getVocabulary())) -- wgf:close() -- -- GET BESTPATH if save_seg then path,seg,logprob = model_parser:get_best_path_and_segmentation() fprintf(io.stderr,"%s\n",table.concat(path, " ")) fprintf(io.stderr,"%s\n",table.concat(seg, " ")) else path,logprob = model_parser:get_best_path() end -- if not server_port then if mfcc_filename then fprintf(io.stderr,"# %s\t%s\n",test:get_field('mfcc_filename')[index], index .. "/" .. #test:get_field('mfcc_filename')) elseif input_lat_filename then fprintf(io.stderr,"# %s\t%s\n",test:get_field('input_lat_filename')[index], index .. "/" .. #test:get_field('input_lat_filename')) end end if path then if right_left then path = table.reverse(path) end -- print ("# DAG VERTEX:", table.concat(segmentation, ", ")) fprintf (io.stderr,"###########################################\n") fprintf (io.stderr,"# logprob N-grama: %f\n",logprob) local get_tr = function(path) local reconocida if optargs.dog then reconocida = table.concat(dictionary:searchOutSymsSequence(path), "") reconocida = string.gsub(reconocida, "[".. gsub_sils .. "]", " ") reconocida = table.concat(string.tokenize(reconocida), " ") else if output_lm_words then reconocida = table.concat(dictionary:searchWordsSequence(path), " ") else reconocida = table.concat(dictionary:searchOutSymsSequence(path), " ") end end return reconocida end local get_lm_tr = function(path) local reconocida = table.concat(dictionary:searchWordsSequence(path), " ") if optargs.dog then reconocida = table.concat(dictionary:searchWordsSequence(path), "") reconocida = string.gsub(reconocida, "[".. gsub_sils .. "]", " ") reconocida = table.concat(string.tokenize(reconocida), " ") end return reconocida end reconocida = get_tr(path) last_recog_lm_wids = dictionary:searchWordIdSequenceFromPairID(path) fprintf(io.stderr,"# Correcta: %s\n",(correcta or "N/A")) last_correcta = correcta fprintf(io.stderr,"# Reconocida N-grama: %s\n",view_filter(reconocida)) print(reconocida) if correcta and filter(reconocida or "") == filter(correcta) then correct_sentences = correct_sentences + 1 end total_num_words = total_num_words + ((correcta and #string.tokenize(correcta)) or #string.tokenize(reconocida)) if save_seg then fprintf(io.stderr,"# Segmentacion: %s\n",table.concat(seg, " ")) end tWall = t2wall-t1wall tCPU = t2cpu-t1cpu if tWall > 0 then framesPerSecond = numFrames/tWall else framesPerSecond = 0 end if recog_type == "asr" then RTfactor = tWall/((numFrames+1)*wadvance) -- sumamos 1 pq windosize es aprox 2 wadvance fprintf(io.stderr,"# Tiempo: %.2f (cpu) %.2f (wall) %.2f frames/s (%.2f x RT) %d frames\n", tCPU, tWall, framesPerSecond, RTfactor, numFrames or 0) else fprintf(io.stderr,"# Tiempo: %.2f (cpu) %.2f (wall) %.2f frames/s %d frames\n", tCPU, tWall, framesPerSecond, numFrames or 0) end fprintf(io.stderr,"###########################################\n") -- OJO: he quitado el +1 para poder medir frames/sec, en lugar de -- RT factor. Al final, para calcular el RT factor se le suma -- num_sentences para compensar total_processed_frames = total_processed_frames + numFrames -- -- para tasas -- if correcta then table.insert(lista_tasas,{filter(correcta), filter(reconocida)}) --AUXF:write(filter(correcta).."="..filter(reconocida).."\n") end -- ------------------------------------------------- -- NBEST local output_wg = nil local wg_file = nil if wg_filename then output_wg = WordGraph() end if nbest_file then local sri_filename local sri_filename2 local sri_file if lattice_tool then local wg = model_parser:get_trellis_wordgraph() local str = wg:toSLF(pairid2wordstr) sri_filename = os.tmpname() sri_file = io.open(sri_filename, "w") sri_file:write(str) sri_file:close() sri_filename2 = os.tmpname() os.execute("rm -f ".. sri_filename2) sri_filename2 = sri_filename2 .. ".out" os.execute("mkdir ".. sri_filename2) os.execute(string.format("%s %s -read-htk -in-lattice %s -nbest-decode %s ".. "-htk-lmscale 0.000000001 -htk-acscale 1 -htk-wdpenalty 0.000000001 ".. "-out-nbest-dir %s -htk-logbase 2.7182818284590451", -- -nbest-viterbi", lattice_tool, (uniq_nbest=="yes" and "-nbest-duplicates 0") or "", sri_filename, num_nbest, sri_filename2)) os.execute("rm -f " .. sri_filename) sri_filename = sri_filename2 .. "/dummy.gz" sri_file = io.open(sri_filename, "r") sri_file:read("*l") -- leemos la 1 best else if output_wg then model_parser:configure_eppstein(output_wg) else model_parser:configure_eppstein() end end local reconocida = get_tr(path) local output = {} write_features = function(path,logprob) if features_file then local wids = dictionary:searchWordIdSequenceFromPairID(path) local lm_score = ngram.get_prob_from_id_tbl(ngram_model, wids, dictionary:getWordId(initial_ngram_word), dictionary:getWordId(final_ngram_word), use_bcc, use_ecc) if apply_gsf_word_probs then for i=1,#path do lm_score = lm_score + dictionary:getData(path[i]).prob end end hmm_score = logprob - lm_score*grammar_scale_factor - #wids * word_insertion_penalty table.insert(output, string.format("%f %f %d",hmm_score,lm_score,#wids)) end end write_features(path,logprob) local uniq = {} fprintf(nbest_file, "%d||| %s ||| %s ||| %f\n", index-1, reconocida, output[#output] or "", logprob) if uniq_nbest == "yes" then uniq[reconocida] = true end --epp = model_parser:get_eppstein(nbest_wg_file ~= nil) local nbesti = 1 local num_it = 0 while nbesti < num_nbest and num_it < num_nbest*20 do num_it = num_it + 1 local path local logprob if lattice_tool then local line = sri_file:read("*l") -- leemos la siguiente if line then local t = string.tokenize(line) logprob = tonumber(t[1])*log10 path = {} for i=5,#t-1 do table.insert(path, tonumber(t[i])) end end else path,seg,logprob = model_parser:next_best_path() if right_left then path = table.reverse(path) end end if not path then break end local reconocida = get_tr(path) local do_print = true if uniq_nbest == "yes" then if not uniq[reconocida] then uniq[reconocida] = true else do_print = false end end if do_print then write_features(path,logprob) fprintf(nbest_file, "%d||| %s ||| %s ||| %f\n", index-1, reconocida, output[#output] or "", logprob) nbesti = nbesti + 1 nbest_file:flush() end end if lattice_tool then sri_file:close() end if features_file then features_file:write(string.format("FEATURES_TXT_BEGIN_0 %d %d 3 hmm lm wip\n", index-1, nbesti)) features_file:write(table.concat(output, "\n").."\n") features_file:write("FEATURES_TXT_END_0\n") features_file:flush() end if sri_filename then os.execute("rm -Rf " .. sri_filename2) end elseif wg_filename then model_parser:configure_eppstein(output_wg) model_parser:compute_nbest(num_nbest-1) end if output_wg then -- salvar word graph local wg_file = io.open(string.format("%s_%s_%05d.slf", wg_filename, basenamestr, index), "w") local wg = word_graph(output_wg, dictionary) -- TODO: usar GSF y WIP --wg_file:write(wg:to_slf(nil,grammar_scale_factor,word_insertion_penalty).."\n") wg_file:write(wg:to_slf(nil,0,0).."\n") wg_file:close() end ------------------------------------------------ else fprintf(io.stderr,"# Correcta: %s\n",(correcta or "N/A")) last_correcta = correcta fprintf(io.stderr,"# Reconocida N-grama: \n") if correcta then table.insert(lista_tasas,{filter(correcta), ""}) if filter(reconocida or "") == filter(correcta) then correct_sentences = correct_sentences + 1 end end fprintf(io.stderr,"# Error, no se ha encontrado camino!!\n") print("") last_recog_lm_wids = {} -- NBEST if nbest_file then if features_file then features_file:write("FEATURES_TXT_BEGIN_0 %d 1 3 hmm lm wip\n", index-1) end fprintf(nbest_file, "%d||| ||| %f %f %f ||| %f\n", index-1, 0, 0, 0, 0) write_features = function() if features_file then fprintf(features_file,"%f %f %f\n",0,0,0) features_file:flush() end end write_features() if features_file then features_file:write("FEATURES_TXT_END_0\n") end end if nbest_wg_file then end end --printf("%d %d\n", --hmm.tree.lexicon_model:get_num_vectors(), --hmm.tree.lexicon_model:get_num_states()) fprintf(io.stderr,"\n") io.stdout:flush() io.stderr:flush() -------------------------------------------------------- end if nbest_file then nbest_file:close() end if features_file then features_file:close() end num_sentences = index --AUXF:close() if txtfile then local resul_val = tasas{ typedata = "pairs_lines", -- words_sep valor por defecto data = lista_tasas, tasa = "ie", -- para calcular wer } fprintf(io.stderr,"Tasa WER: %f\n", resul_val.tasa) local resul_val = tasas{ typedata = "pairs_lines", data = lista_tasas, tasa = "ie", -- para calcular wer words_width = 1, } fprintf(io.stderr,"Tasa CER: %f\n", resul_val.tasa) fprintf(io.stderr,"Tasa SER: %f\n", 100*(1 - correct_sentences/num_sentences)) end total_cpu_time, total_wall_time = cronometro:read() fprintf(io.stderr,"Total time: %.2f (cpu) %.2f (wall), cpu/sentence %.4f cpu/word %.4f ", total_cpu_time, total_wall_time, total_cpu_time/num_sentences, total_cpu_time/total_num_words) fprintf(io.stderr,"wall/sentence %.4f wall/word %.4f ", total_wall_time/num_sentences, total_wall_time/total_num_words) fprintf(io.stderr,"frames/cpu %.4f frames/wall %.4f", total_processed_frames/total_cpu_time, total_processed_frames/total_wall_time) if recog_type == "asr" then -- sumamos num_sentences porque wsize es casi 2 wadvance -- (hay que sumar 1 por cada frase = num_sentences) RTfactor = total_wall_time/((total_processed_frames+num_sentences)*wadvance) fprintf(io.stderr,", RT factor: %.2f x RT",RTfactor) end fprintf(io.stderr,"\n") april-ann-0.4.1/tools/HMM_ANN/recognition/template-recog-conf.lua000066400000000000000000000013611263004425400245310ustar00rootroot00000000000000 return { recog="htr", m="BESTMODELS/hmms.lua", n="BESTMODELS/mlp.net", --hmmdefs="...", -- HTK HMMs and GMMs context=4, t="tiedlist.Graves.id", d="/home/experimentos/PAMI_MODELOS/Graves/lexicon_20000.intersected.SILOPT", lm="/home/experimentos/PAMI_MODELOS/Graves/latticeArpa_f.intersected.lira.gz", gsf=9, wip=-15, optsil="yes", feats_format="mat", feats_norm="pats/means_and_devs.PRESERVANDOX.lua", ngram_beam=2000, ngram_size=400, ngram_nstates=10000, -- one_step="no", -- nested="no", -- dog="no", -- filter="...", -- cache_size=18, -- trie_size=25, -- ose="htr" -- use_word_probs="yes", -- unk=nil, -- only valid for two steps algorithm wgen_beam=1000, wgen_size=200, wgen_nstates=4000, } april-ann-0.4.1/tools/HMM_ANN/recognition/tuning.sh000066400000000000000000000121061263004425400220320ustar00rootroot00000000000000#!/bin/bash initrun=$1 lastrun=$2 defopt=$3 lm=$4 devtarget=$5 tuningdir=${6}/ numnbest=${7} # por defecto 500 maxhout=${8} # por defecto 100 use_prev_nbest=${9} # por defecto yes initweights=${10} if [ -z $APRILANN_ROOT ]; then echo "APRILANN_ROOT environment variable is needed" exit 1 fi gsf=10 wip=0 scale=15 epsilon=0.00001 if [ -z $use_prev_nbest ]; then use_prev_nbest="yes" fi if [ ! -z $initweights ]; then waux=( $(tail -n 1 "$initweights") ) gsf=`echo "scale=$scale; ${waux[1]}/${waux[0]}" | bc` wip=`echo "scale=$scale; ${waux[2]}/${waux[0]}" | bc` fi if [ -z $maxhout ]; then maxhout=100; fi if [ -z $numnbest ]; then numnbest=500; fi optimizer=simplex; objfunc="WER"; aprilann_tools=$APRILANN_ROOT/tools aprilann=$APRILANN_ROOT/bin/april-ann recog=$aprilann_tools/HMM_ANN/recog.lua scorer="$aprilann $aprilann_tools/HMM_ANN/extract_WER_weights.lua" generate_conf=$aprilann_tools/HMM_ANN/generate_conf.lua mert="$aprilann $aprilann_tools/optimizer_weights.lua -s WER -t simplex -a 2 " if [ -z $lm ]; then tm="nil"; fi if [ $lm = "nil" ]; then lm=""; else lm="--lm=$lm" fi if [ -z $tuningdir ]; then tuningdir=tuning; fi mkdir -p $tuningdir if [ $initrun -gt 1 ]; then prevrun=`expr $initrun - 1` if [ ! -e $tuningdir/run$prevrun/weights.txt ]; then echo "ERROR!!! $tuningdir/run$prevrun/weights.txt not found" exit 128 fi weights=( $(tail -n 1 "$tuningdir/run$prevrun/weights.txt") ) gsf=`echo "scale=$scale; ${weights[1]}/${weights[0]}" | bc` wip=`echo "scale=$scale; ${weights[2]}/${weights[0]}" | bc` else cp $defopt $tuningdir/tuning-conf.lua fi if [ ! -e $tuningdir/tuning-conf.lua ]; then cp $defopt $tuningdir/tuning-conf.lua fi endrun=$initrun echo $0 $@ > $tuningdir/last_tuning_exec.sh chmod +x $tuningdir/last_tuning_exec.sh rm -f $tuningdir/finished.txt for run in `seq $initrun $lastrun`; do mkdir -p $tuningdir/run$run nbestlog=$tuningdir/run$run/run$run.best$numnbest.out tuplenbestlog=$tuningdir/run$run/run$run.tuplebest$numnbest.out featlog=$tuningdir/run$run/run$run.feats.opt stdout=$tuningdir/run$run/run$run.out stderr=$tuningdir/run$run/run$run.err # cargamos los pesos y generamos gsf y wip echo "FECHA: "`date` echo "Reconociendo... etapa $run (esto puede tarder MUCHO tiempo)" $aprilann $generate_conf $tuningdir/tuning-conf.lua $lm \ --uniq-nbest=yes --gsf=$gsf --wip=$wip > $tuningdir/run$run/conf.lua $aprilann $recog --nbest=$numnbest --save-nbest=$nbestlog --features=$featlog \ --max-h-out=$maxhout \ -f $tuningdir/run$run/conf.lua > $stdout 2> $stderr if [ $? -ne 0 ]; then echo "ERROR!!!" exit 128; fi gzip -f $nbestlog gzip -f $featlog # scorer refs=$devtarget prevsc="" prevfe="" if [ $run -gt 1 ]; then if [ $use_prev_nbest = "yes" ]; then prevsc="-R $tuningdir/prev-scores.dat.gz" prevfe="-E $tuningdir/prev-feats.dat.gz" fi fi $scorer -r $refs \ -S $tuningdir/scores.dat \ -F $tuningdir/feats.dat \ -n $nbestlog.gz $prevsc $prevfe if [ $? -ne 0 ]; then echo "ERROR!!!" exit 128; fi echo "MERT" echo "1 $gsf $wip" > $tuningdir/init.opt oldpwd=`pwd` seed=$RANDOM if [ -e $tuningdir/run$run/run$run.seed.txt ]; then seed=`cat $tuningdir/run$run/run$run.seed.txt`; fi echo $seed > $tuningdir/run$run/run$run.seed.txt cd $tuningdir/ $mert -n 20 -d 3 -S scores.dat \ -r $seed \ -F feats.dat -i init.opt >& run$run/run$run.mert.log if [ $? -ne 0 ]; then echo "ERROR!!!" exit 128; fi cd $oldpwd gzip -f $tuningdir/scores.dat gzip -f $tuningdir/feats.dat mv -f $tuningdir/scores.dat.gz $tuningdir/prev-scores.dat.gz mv -f $tuningdir/feats.dat.gz $tuningdir/prev-feats.dat.gz lastwfile=$tuningdir/run$run/weights.txt grep -i "best point: " $tuningdir/run$run/run$run.mert.log | cut -d':' -f 2 | cut -d'=' -f 1 > $lastwfile weights=( $(tail -n 1 "$tuningdir/run$run/weights.txt") ) new_gsf=`echo "scale=$scale; ${weights[1]}/${weights[0]}" | bc` new_wip=`echo "scale=$scale; ${weights[2]}/${weights[0]}" | bc` stop=1 diffs="" echo GSF= $new_gsf WIP= $new_wip aux=`echo "${gsf[$i]} - ${new_gsf[$i]}" | bc` diff=`echo "scale=$scale; sqrt($aux * $aux)" | bc` # hack FEO para valor absoluto diffs="$diffs $diff" res=`echo "$diff > $epsilon" | bc` if (( "$res" == 1 )); then stop=0 fi aux=`echo "${wip[$i]} - ${new_wip[$i]}" | bc` diff=`echo "scale=$scale; sqrt($aux * $aux)" | bc` # hack FEO para valor absoluto diffs="$diffs $diff" res=`echo "$diff > $epsilon" | bc` if (( "$res" == 1 )); then stop=0 fi echo "sizew= 3 stop= $stop dir= $tuningdir" endrun=$run if (( "$stop" == 1 )); then echo $endrun > $tuningdir/finished.txt break; fi gsf=$new_gsf wip=$new_wip done cp -f $tuningdir/run$endrun/conf.lua $tuningdir/conf.lua oldpwd=`pwd` cd $tuningdir rm -f last ln -s run$endrun last cd $oldpwd echo $endrun > $tuningdir/finished.txt echo "Stop en la etapa " $endrun echo "OK" april-ann-0.4.1/tools/HMM_ANN/segmentation/000077500000000000000000000000001263004425400203475ustar00rootroot00000000000000april-ann-0.4.1/tools/HMM_ANN/segmentation/forced_viterbi_alignment.lua000066400000000000000000000272701263004425400261060ustar00rootroot00000000000000-- FIXME: Este SCRIPT solo tiene en cuenta trifonemas dentro de las -- palabras, pero entre palabras april_print_script_header(arg) dofile(string.get_path(arg[0]) .. "../utils.lua") cmdOptTest = cmdOpt{ program_name = string.basename(arg[0]), argument_description = "", main_description = "Force Viterbi Alignment with April toolkit", { index_name="defopt", description="Load configuration file (a lua tabla)", short="f", argument="yes", filter=dofile, }, { index_name="posteriors", -- antes filenet description = "Posteriors file list", long = "posteriors", argument = "yes", }, { index_name="n", -- antes filenet description = "MLP file", short = "n", argument = "yes", }, { index_name = "m", -- antes filem description = "hmms file", short = "m", argument = "yes", }, { index_name="hmmdefs", -- antes filehmmdefs description = "hmms HTK file", long = "hmmdefs", argument = "yes", }, { index_name="t", -- antes tiedfile description = "HTK unit's tied list", short = "t", argument = "yes", mode = "always", }, { index_name="p", -- antes testfile description = "File with the corpus mfccs data", short = "p", argument = "yes", mode = "always", }, { index_name="txt", -- antes txtfile description = "File with the corpus transcriptions", long = "txt", argument = "yes", mode = "always", }, { index_name="phdict", description = "Dictionary for generate transcriptions (only if txtfile is not a phonetic transcription)", long = "phdict", argument = "yes", }, { index_name="silences", description="HMM models for silences (a blank separated list)", long="silences", argument="yes", filter=string.tokenize, }, { index_name="begin_sil", description="Add this model as Begin Silence (must be in --silences list)", long="begin-sil", argument="yes", }, { index_name="end_sil", description="Add this model as Begin Silence (must be in --silences list)", long="end-sil", argument="yes", }, { index_name="transcription_filter", description="Filter the transcriptions to generate phonetic sequences", long="transcription-filter", argument="yes", filter=dofile, }, { index_name = "context", -- antes ann_context_size description = "Size of ann context", long = "context", argument = "yes", filter = tonumber, mode = "always", default_value = 4, }, { index_name = "feats_format", description = "Format of features mat or mfc", long = "feats-format", argument = "yes", mode = "always", default_value = "mat", }, { index_name = "feats_norm", description = "Table with means and devs for features", long = "feats-norm", argument = "yes", filter = dofile, }, { index_name = "step", description = "Dataset step", long = "step", argument = "yes", mode = "always", filter = tonumber, default_value = "1", }, { index_name="force", description = "Force overwritten output files", long = "force", argument = "no", default_value = false, }, { index_name = "dir", description = "Output dir", long = "dir", argument="yes", mode = "always", }, { index_name = "phondir", description = "Output dir for phonetic transcription", long = "phondir", argument="yes", mode = "always", default_value = nil, }, { index_name = "cores", description = "Number of cores", long = "cores", argument="yes", mode = "always", default_value = "2", filter = tonumber, }, { description = "shows this help message", short = "h", long = "help", argument = "no", action = function (argument) print(cmdOptTest:generate_help()) os.exit(1) end } } local optargs = cmdOptTest:parse_without_check() if type(optargs) == "string" then error(optargs) end local initial_values if optargs.defopt then initial_values = optargs.defopt optargs.defopt=nil end optargs = cmdOptTest:check_args(optargs, initial_values) fileposteriors = optargs.posteriors filenet = optargs.n filem = optargs.m filehmmdefs = optargs.hmmdefs tiedfile = optargs.t valfile = optargs.p txtfile = optargs.txt dir = optargs.dir phondir = optargs.phondir context = optargs.context step = optargs.step format = optargs.feats_format transcription_filter = optargs.transcription_filter phdict = optargs.phdict silences = optargs.silences begin_sil = optargs.begin_sil end_sil = optargs.end_sil cores = optargs.cores feats_mean_and_devs = optargs.feats_norm force_write = optargs.force os.execute("mkdir -p " .. dir) os.execute("mkdir -p " .. phondir) if not fileposteriors and not filenet then error("Needs --posteriors or -n arguments") end if not silences then fprintf(io.stderr, "# WARNING!!! NOT SILENCES TABLE DEFINED\n") end if (not (filenet or fileposteriors) or not filem) and not fileHTK then error ("Needs a HMM/ANN or HTK file") end if fileHTK then error ("Not revised!!! probably not implemented!!!") end if filenet then ann_trainer = trainable.supervised_trainer.load(filenet, nil, 128) else posteriors_f=io.open(fileposteriors)or error("Unable to open "..fileposteriors) end -------------------- -- parametros RNA -- -------------------- ann = {} ann.left_context = context ann.right_context = context -------------------- -- Corpus -- -------------------- corpus = { } corpus.filename_val = valfile corpus.filename_txt = txtfile -- objeto con informacion sobre modelos ligados tied = tied_model_manager(io.open(tiedfile)) --------- -- HMM -- --------- -- creamos el trainer y le metemos los modelos acusticos hmm_trainer = HMMTrainer.trainer() hmm = {} hmm.silences = {} hmm.silence_tbl = {} for i=1,#silences do hmm.silences[silences[i]] = 1.0 table.insert(hmm.silence_tbl, silences[i]) end if begin_sil and (not silences or not hmm.silences[begin_sil]) then error ("Begin silence must be in --silences list") end if end_sil and (not silences or not hmm.silences[end_sil]) then error ("End silence must be in --silences list") end if ann_trainer then num_emissions = ann_trainer:get_output_size() end -- cargamos los HMMs hmm.models,num_models,num_emissions_hmm_file,emiss_to_hmm = load_models_from_hmm_lua_desc(filem, hmm_trainer) num_emissions = num_emissions or num_emissions_hmm_file if num_emissions ~= num_emissions_hmm_file then error(string.format("Incorrect number of emissions at HMMs file, ".. "expected %d and found %d", num_emissions, num_emissions_hmm_file)) end ann.output_dictionary = dataset.identity(num_emissions, 0.0, 1.0) collectgarbage("collect") -- si nos dan el diccionario fonetico, generamos modelos para las -- palabras local mangling -- sirve para el name mangling de las palabras if phdict then print("# WARNING!!! Verify that your dictionary contains optional silences ".. "as alternative pronunciations") print("# Using dictionary for generate phonetic transcriptions") _,mangling=HMMTrainer.utils.dictionary2lextree(io.open(phdict), tied, hmm.silences, hmm_trainer) collectgarbage("collect") end -------------------- -- Carga de datos -- -------------------- -- -- nombres de ficheros test = field_manager() recog.generate_filenames{ corpus_data_manager = test, filename_mfc = valfile, filename_fon = txtfile, } -- local frames_loader if format == "mat" then frames_loader = load_matrix else frames_loader = load_mfcc end collectgarbage("collect") list = test:get_field('mfcc_filename') which_i_am,child_pid = util.split_process(cores) for index=which_i_am,#list,cores do mfcc_filename = list[index] collectgarbage("collect") -- cargamos el dataset correspondiente a la frase actual local tr_filename = test:get_field('phon_filename')[index] local basenamestr = remove_extensions(string.basename(tr_filename)) print ("# Loading transcription: ", tr_filename, index.."/"..#list) local tr_string = io.open(tr_filename):read("*l") print ("# Loading frames: ", mfcc_filename) local frames = frames_loader(mfcc_filename) local numFrames = frames:dim()[1] local numParams = frames:dim()[2] -- nCCs+1 local parameters = { patternSize = {step, numParams}, offset = {0,0}, -- default value stepSize = {step, 0}, -- default value, second value is not important numSteps = {numFrames/step, 1} } local actual_ds = dataset.matrix(frames, parameters) if feats_mean_and_devs then actual_ds:normalize_mean_deviation(feats_mean_and_devs.means, feats_mean_and_devs.devs) end if filehmmdefs==nil then actual_ds = dataset.contextualizer(actual_ds, ann.left_context, ann.right_context) end local segmentation_matrix = matrix(numFrames) local mat_full if ann_trainer then print ("# Generating posteriors...") mat_full = matrix(numFrames, num_emissions) local mat_full_ds = dataset.matrix(mat_full) ann_trainer:use_dataset{ input_dataset = actual_ds, -- parametrizacion output_dataset = mat_full_ds -- matriz de emisiones } else local filename = posteriors_f:read("*l") print ("# Loading posteriors: ", filename) mat_full = frames_loader(filename) end print("# Building HMM model") -- filtramos la transcripcion if transcription_filter then tr_string = transcription_filter(tr_string) end -- anyadimos los silencios if begin_sil then tr_string = begin_sil .. " " .. tr_string end if end_sil then tr_string = tr_string .. " " .. end_sil end tr_string = string.gsub(tr_string, begin_sil.." "..begin_sil, begin_sil) tr_string = string.gsub(tr_string, end_sil.." "..end_sil, end_sil) local themodel if phdict then -- generamos el modelo a partir del diccionario fonetico, necesita -- name mangling local tbl = table.imap(string.tokenize(tr_string), function(str) assert(mangling[str] or hmm.silences[str], "Word without transcription: " .. str) return mangling[str] or str end) themodel=generate_models_from_sequences(tbl, hmm_trainer,nil,hmm.silences) else -- generamos la secuencia de esta frase themodel=generate_models_from_sequences(string.tokenize(tr_string), hmm_trainer,tied,hmm.silences) end printf ("# Segmentation... ") io.stdout:flush() -- ahora generamos la salida de Viterbi local logprob,phon_output = themodel:viterbi{ input_emission = mat_full, do_expectation = false, output_emission_seq = segmentation_matrix, emission_in_log_base = true, } printf("%12.4f score\n", logprob) -- print(segmentation_matrix) print(phon_output) local output_filename = dir .. "/" .. remove_extensions(string.basename(mfcc_filename)) .. ".mat" print ("# Saving " .. output_filename) if io.open(output_filename) and not force_write then error(string.format("# Output file '%s' exists, use --force to force overwritten\n", output_filename)) else segmentation_matrix:toFilename(output_filename, "binary") end if phondir then output_filename = phondir .. "/" .. remove_extensions(string.basename(mfcc_filename)) .. ".phon" print ("# Saving " .. output_filename) if io.open(output_filename) and not force_write then error(string.format("# Output file '%s' exists, use --force to force overwritten\n", output_filename)) else local f = io.open(output_filename, "w") f:write(phon_output .. "\n") f:close() end end end if child_pid then -- esperamos a los hijos util.wait() end april-ann-0.4.1/tools/HMM_ANN/segmentation/old/000077500000000000000000000000001263004425400211255ustar00rootroot00000000000000april-ann-0.4.1/tools/HMM_ANN/segmentation/old/convert_initial_segmentation_to_n_states_hmm.lua000066400000000000000000000060211263004425400330400ustar00rootroot00000000000000-- recibe dos numeros, el numero de estados de la segmentacion -- inicial, y el numero de estados de cada HMM que queremos que tenga orig_states = tonumber(arg[1]) orig_dir = arg[2] dest_states = tonumber(arg[3]) if not dest_states then dest_states = {} local i=0 for line in io.lines(arg[3]) do dest_states[i] = tonumber(line) i = i+1 end else local n = dest_states dest_states = {} for i=0,100 do dest_states[i] = n end end dest_dir = arg[4] if orig_dir == dest_dir then error ("NO PUEDES SOBREESCRIBIR EL ORIGEN Y EL DESTINO") end semilla = 1234 rnd = random(semilla) -- recorre cada fichero del directorio for i,file_name in ipairs(glob(orig_dir.."/*")) do local file_basename = string.basename(file_name) local m = matrix.loadfile(file_name) local msize = m:dim()[1] local t = {} local ini_pos = 1 local ant_ch = -1 local ant_emiss = -1 local ch = -1 local num_emisiones_perdidas = 0 collectgarbage("collect") -- para cada patron de la matriz original local ds = dataset.matrix(m) for j=1,msize do local pat = ds:getPattern(j) -- sacamos el indice de caracter que representa la emision ch = math.floor((pat[1]-1)/orig_states) -- si hemos cambiado de caracter o hemos llegado al final de la -- matriz -- print(j, "ant_ch: "..ant_ch, "ant_emiss: "..ant_emiss, "ch: "..ch, "emiss: "..pat[1]) if ch ~= ant_ch or pat[1] < ant_emiss or j == msize then -- si no estamos en la primera iteracion if j > 1 then local size = j - ini_pos local ini_emiss = ant_ch*dest_states[ant_ch] + 1 local fin = j-1 -- si hemos llegado al final de la matriz, entonces iremos de -- ini_emiss hasta msize, en otro caso sera de ini_emiss a j-1 if j == msize then fin = msize size = size + 1 end -- sacamos el numero de tramas por estado y las que me han sobrado local tramas_por_estado = math.floor(size / dest_states[ant_ch]) local sobran = size % dest_states[ant_ch] local aux_vec_estados = {} for k=1,dest_states[ant_ch] do aux_vec_estados[k] = tramas_por_estado end local shuffled_vector = rnd:shuffle(dest_states[ant_ch]) for k=1,sobran do local v = aux_vec_estados[shuffled_vector[k]] aux_vec_estados[shuffled_vector[k]] = v + 1 end local sum=0 for k=1,dest_states[ant_ch] do sum = sum +aux_vec_estados[k] end -- print("sum ",sum,size,j-ini_pos) for k=1,dest_states[ant_ch] do for rep=1,aux_vec_estados[k] do t[ini_pos] = ini_emiss + k - 1 --print(ds:getPattern(ini_pos)[1], t[ini_pos], size, tramas_por_estado, sobran, j) ini_pos = ini_pos + 1 end end -- print("wop",ini_pos,j) end ant_ch = ch end ant_emiss = pat[1] end -- comprobamos que no haya ERRORES if #t ~= msize then error("#t no es correcta ".. #t .. " " .. msize) end local dest_file_name = dest_dir .. "/" .. file_basename local auxm = matrix(#t, t) matrix.savefile(auxm, dest_file_name, "binary") print(i, file_basename) end april-ann-0.4.1/tools/HMM_ANN/segmentation/old/generate_initial_segmentation.py000066400000000000000000000040031263004425400275540ustar00rootroot00000000000000# lee un fichero con este formato: # 08730_533_10850:271_f2_unknown 34 uu 0 (164,0) (165,1) (166,1) (167,1) (168,0) # 08730_533_10850:271_f2_unknown 26 nn 3 (124,0) (125,1) (126,1) (127,1) (128,0) # 08730_533_10850:271_f2_unknown 4 pause 6 (16,0) (17,17) (18,15) (19,26) (20,0) # 08730_533_10850:271_f2_unknown 14 ch 64 (64,0) (65,7) (66,3) (67,6) (68,0) # 08730_533_10850:271_f2_unknown 10 an 80 (44,0) (45,4) (46,1) (47,3) (48,0) # 08730_533_10850:271_f2_unknown 12 bb 88 (54,0) (55,2) (56,1) (57,3) (58,0) # # cada linea es de la forma: # fichero indice fonema primeratrama segmentacion dentro del fonema # # la segmentacion dentro del fonema es una lista de (estadoHMM,numero # de tramas) si sumamos los numero de tramas de todos los estados # vemos que concuerda con el indice de trama del siguiente fonema # # el script genera una matriz unidimensional donde cada elemento es el # indice del tipo de emision de HMM from random import randint phone_list = open("phone_list.txt").read().split() print(phone_list) file_list = open("train.txt").read().split() for filename in file_list: print(filename) output_sequence = [] for linea in open("/labo/data/Media/SEG_CI/"+filename+".seg").readlines(): aux = linea.split() phone = phone_list.index(aux[2]) ristra = [int(x.split(',')[1].replace(")","")) for x in aux[5:-1]] numstates = len(ristra) numframes = sum(ristra) # print phone,ristra if numstates > 3: ristra[2] += sum(ristra[3:]) del ristra[3:] if numstates < 3: ristra = [0,0,0] cociente = numframes / 3 # in python3 use // resto = numframes % 3 for i in range(3): ristra[i] = cociente for i in range(resto): ristra[randint(0,2)] += 1 st = 3*phone for i in range(3): for j in range(ristra[i]): output_sequence.append(st+i) f = open("initial_segmentation/"+filename+".sgm","w") f.write("%d\nascii\n" % (len(output_sequence),)) for i in output_sequence: f.write("%d\n" % (i,)) f.close() april-ann-0.4.1/tools/HMM_ANN/segmentation/resegment.lua000066400000000000000000000101751263004425400230470ustar00rootroot00000000000000---------------------------------------------------------------------- -- argumentos file_name_frames = arg[1] origin_directory = arg[2] destiny_directory = arg[3] origin_numstates = tonumber(arg[4]) dest_numstates = tonumber(arg[5]) espace_index = 53 ---------------------------------------------------------------------- -- funciones ---------------------------------------------------------------------- segmentation = {} -- namespace function segmentation.load_hmm_seq(tbl, numstates) -- recibe un vector de tipos de emision a nivel de estado HMM, -- devuelve otro vector de pares {fin,tipo}, asume que todos los -- estados a nivel HMM son left to right con el mismo numero de -- estados local numframes,resul resul = {} local counter = 0 local prev_state_index local prev_model for i,state_index in ipairs(tbl) do state_index = state_index-1 -- pq empiezan en 1 local model = math.floor(state_index/numstates) -- print(i,state_index,model) if model ~= prev_model or state_index < prev_state_index then if prev_model then table.insert(resul,{counter,prev_model}) -- print("inserto",counter,prev_model) end end prev_model = model prev_state_index = state_index counter = counter + 1 end if prev_model then table.insert(resul,{counter,prev_model}) -- print("inserto",counter,prev_model) end return resul end function segmentation.crop(tbl, initial_space, final_space) local index_begin = 1 local index_end = #tbl local time_offset = 0 if #tbl > 0 and tbl[1][2] == initial_space then index_begin = 2 time_offset = tbl[1][1] end if tbl[#tbl] ~= nil and tbl[#tbl][2] == final_space then index_end = index_end-1 end local resul = {} for i=index_begin,index_end do table.insert(resul, {tbl[i][1]-time_offset,tbl[i][2]}) end return resul end -- tbl es una tabla con pares {instante_fin, modelo} function segmentation.save_hmm_seq(tbl, numframes, numstates) local r = random() local resul = {} local last = tbl[#tbl][1] local ratio = numframes/last local prevframe = 0 for i,pareja in ipairs(tbl) do local lastframe = math.round(pareja[1] * ratio) -- print('proceso',i,pareja[1],pareja[2],lastframe) if i==#tbl then lastframe = numframes end local model = pareja[2] local num = lastframe - prevframe prevframe = lastframe local ristra = {} local aux = {} -- lo que todos se llevan seguro local atodos = math.floor(num/numstates) for i=1,numstates do ristra[i] = atodos aux[i] = i end local sobran = num-atodos*numstates aux = r:shuffle(aux) for i=1,sobran do ristra[aux[i]] = ristra[aux[i]]+1 end local aux=0 for i=1,numstates do local st = model*numstates+i for j=1,ristra[i] do aux = aux+1 -- print(" ",aux,"inserto", st) table.insert(resul,st) end end end return resul end function mat2tab(mat) -- auxiliar resul = {} d = mat:dim() if #d ~= 1 then error("expected unidimensional matrix") end d = d[1] -- print('dimension',d) for i=1,d do table.insert(resul,mat:getElement(i)) end return resul end function tab2mat(tbl) resul = matrix(#tbl) for i,j in ipairs(tbl) do resul:setElement(i,j) end return resul end ---------------------------------------------------------------------- -- programa principal ---------------------------------------------------------------------- for line in io.lines(file_name_frames) do line = string.tokenize(line) filename = line[1] numframes = line[2] print(filename) f = io.open(origin_directory .. "/" .. filename,"r") if f == nil then print("ERROR, NO ENCUENTRA FICHERO ", filename) else m = matrix.fromString(f:read("*a")) f:close() tbl = mat2tab(m) tbl = segmentation.load_hmm_seq(tbl,origin_numstates) tbl = segmentation.crop(tbl, espace_index, espace_index) tbl = segmentation.save_hmm_seq(tbl, numframes, dest_numstates) m = tab2mat(tbl) m:toFilename(destiny_directory .. "/" .. filename,"ascii") end --os.exit() end april-ann-0.4.1/tools/HMM_ANN/training/000077500000000000000000000000001263004425400174655ustar00rootroot00000000000000april-ann-0.4.1/tools/HMM_ANN/training/README.md000066400000000000000000000144651263004425400207560ustar00rootroot00000000000000HMM_ANN/train directory: training of HMM/ANNs ============================================= The most important script here is `train.lua` script, which is prepared to train HMM/ANNs following previous described algorithm. This wiki is a mere description of the scripts. Currently non tutorial is available, but you can follow HTK tutorial in order to understand the meaning of all options presented here. Besides, ANN basic knowledge will be helpful. The script receives a lot of parameters which are shown executing `april-ann train.lua --help`: ``` USAGE: train.lua [-fVALUE] --train-m=VALUE --train-f=VALUE [--train-s=VALUE] [--train-phdict=VALUE] --val-m=VALUE --val-f=VALUE [--val-s=VALUE] [--val-phdict=VALUE] [--begin-sil=VALUE] [--end-sil=VALUE] [--count-values=VALUE] --num-states=VALUE --h1=VALUE --h2=VALUE -nVALUE [--train-r=VALUE] [--val-r=VALUE] --tiedfile=VALUE [--context=VALUE] [--feats-format=VALUE] [--feats-norm=VALUE] [--step=VALUE] [--mean=VALUE] [--var=VALUE] [--seedp=VALUE] [--firstlr=VALUE] [--epochs-firstlr=VALUE] [--lr=VALUE] [--mt=VALUE] [--wd=VALUE] [--rndw=VALUE] [--seed1=VALUE] [--seed2=VALUE] [--seed3=VALUE] [--epochs-wo-val=VALUE] [--epochs-wo-imp=VALUE] [--epochs-wo-exp=VALUE] [--epochs-max=VALUE] [--epochs-first-max=VALUE] [--em-it=VALUE] [--initial-mlp=VALUE] [--initial-hmm=VALUE] [--initial-em-epoch=VALUE] [--transcription-filter=VALUE] [--silences=VALUE] [(-h|--help)] DESCRIPTION: HMM/ANN training with APRIL-ANN toolkit -fVALUE Load configuration file (a lua tabla) (optional) --train-m=VALUE MFCC file for training set --train-f=VALUE FON file for training set --train-s=VALUE Initial segmentation file for training set (optional) --train-phdict=VALUE Phonetical dictionary for training (optional) --val-m=VALUE MFCC file for validation set --val-f=VALUE FON file for validation set --val-s=VALUE Initial segmentation file for validation set (optional) --val-phdict=VALUE Phonetical dictionary for validation (optional) --begin-sil=VALUE Initial silence (optional) --end-sil=VALUE Final silence (optional) --count-values=VALUE (optional) [DEFAULT: ] --num-states=VALUE Number of states per each HMM [DEFAULT: false] --h1=VALUE First hidden layer size --h2=VALUE Second hidden layer size -nVALUE Number of parameters per each frame --train-r=VALUE Replacement for training (0 for disable) (optional) [DEFAULT: 300000] --val-r=VALUE Replacement for validation (0 for disable) (optional) [DEFAULT: 0] --tiedfile=VALUE HTK unit's tied list --context=VALUE Size of ann context (optional) [DEFAULT: 4] --feats-format=VALUE Format of features mat or mfc or png (mat, png or mfc) (optional) [DEFAULT: mat] --feats-norm=VALUE Table with means and devs for features (optional) --step=VALUE Dataset step (optional) [DEFAULT: 1] --mean=VALUE Mean of gaussian perturbation (default 0) (optional) [DEFAULT: 0] --var=VALUE Variance of gaussian perturbation (0 for disable) (optional) [DEFAULT: 0.015] --seedp=VALUE Perturbation seed (optional) [DEFAULT: 86544] --firstlr=VALUE First learning rate (optional) [DEFAULT: 0.005] --epochs-firstlr=VALUE Num epochs for first learning rate (optional) [DEFAULT: 100] --lr=VALUE Learning rate (optional) [DEFAULT: 0.001] --mt=VALUE Momentum (optional) [DEFAULT: 0.005] --wd=VALUE Weight decay (optional) [DEFAULT: 1e-06] --rndw=VALUE Size of the random inf/sup for MLP (optional) [DEFAULT: 0.1] --seed1=VALUE Seed 1 (optional) [DEFAULT: 1234] --seed2=VALUE Seed 2 (optional) [DEFAULT: 4567] --seed3=VALUE Seed 3 (optional) [DEFAULT: 9876] --epochs-wo-val=VALUE Epochs without validation (optional) [DEFAULT: 4] --epochs-wo-imp=VALUE Epochs without improvement (optional) [DEFAULT: 20] --epochs-wo-exp=VALUE Epochs without expectation step (optional) [DEFAULT: 5] --epochs-max=VALUE Number of epochs for maximization step (optional) [DEFAULT: 100] --epochs-first-max=VALUE Number of epochs for first maximization step (optional) [DEFAULT: 500] --em-it=VALUE Number of EM iterations (default 100) (optional) [DEFAULT: 100] --initial-mlp=VALUE Initial MLP for continue an stopped training (optional) --initial-hmm=VALUE Initial HMM for continue an stopped training, or to use as a first HMM description (optional) --initial-em-epoch=VALUE Initial EM epoch for continue an stopped training (optional) --transcription-filter=VALUE Filter the transcriptions to generate phonetic sequences (optional) --silences=VALUE HMM models for silences (a blank separated list) (optional) [DEFAULT: ] -h, --help shows this help message (optional) ``` There are a lot of options to configure the training. In the following, when we talk about **files list**, they are files which contains a list of filenames, one per line (the files could be gzipped): ``` corpus/n02-000-00.mat.gz corpus/n02-000-01.mat.gz corpus/n02-000-02.mat.gz ``` The most important options are those which are not marked as `(optional)`. - `train-m`: A files list which contains the parametrization used as input. This list is used for model parameter estimation (training). - `train-f`: A files list which contains textual transcriptions of parametrized files contained in previous option. This list is used for model parameter estimation (training). If this file is not a phonetic sequence, the parameter `transcription-filter` is needed to convert the textual sequence in phonemes. Otherwise, the option `train-phdict` could replace the transcription filter. - `val-m`: Idem as `train-m` but for for early stopping (validation). - `val-f`: Idem as `train-f` but for for early stopping (validation). - `h1`: Number of neurons at the first layer. - `h2`: Number of neurons at the second layer (zero is valid, only one layer will be used). - `n`: Number of parameters on each frame. - `num-states`: Number of states per each phoneme. - `tiedfile`: A list of valid phonemes, following HTK tied-list. april-ann-0.4.1/tools/HMM_ANN/training/cmdopt.lua000066400000000000000000000240341263004425400214610ustar00rootroot00000000000000cmdOptTest = cmdOpt{ program_name = string.basename(arg[0]), argument_description = "", main_description = "HMM/ANN training with APRIL-ANN toolkit", { index_name="defopt", description="Load configuration file (a lua tabla)", short="f", argument="yes", filter=dofile, }, { index_name="bunch_size", description="Bunch size (mini-batch size)", long="bunch-size", argument="yes", mode="always", filter=tonumber, default_value=32, }, { index_name="train_m", description="MFCC file for training set", long="train-m", argument="yes", mode="always", }, { index_name="train_f", description="FON file for training set", long="train-f", argument="yes", mode="always", }, { index_name="train_s", description="Initial segmentation file for training set", long="train-s", argument="yes", }, { index_name="train_phdict", description="Phonetical dictionary for training", long="train-phdict", argument="yes", }, { index_name="val_m", description="MFCC file for validation set", long="val-m", argument="yes", mode="always", }, { index_name="val_f", description="FON file for validation set", long="val-f", argument="yes", mode="always", }, { index_name="val_s", description="Initial segmentation file for validation set", long="val-s", argument="yes", }, { index_name="val_phdict", description="Phonetical dictionary for validation", long="val-phdict", argument="yes", }, { index_name="begin_sil", description="Initial silence", long="begin-sil", argument="yes", }, { index_name="end_sil", description="Final silence", long="end-sil", argument="yes", }, { index_name="count_values", description="Blank separated list of Viterbi count values, for use with multiple corpora", long="count-values", filter=function(s) return table.imap(string.tokenize(s, " ,\t\n\r"),tonumber) end, argument="yes", mode="always", default_value="", }, { index_name="num_states", description="Number of states per each HMM", long="num-states", filter=tonumber, mode="always", argument="yes", default_value=false, }, { index_name="h1", description="First hidden layer size", long="h1", argument="yes", mode="always", filter=tonumber, }, { index_name="h2", description="Second hidden layer size", long="h2", argument="yes", mode="always", filter=tonumber, }, { index_name="n", description="Number of parameters per each frame", short="n", argument="yes", mode="always", filter=tonumber, }, { index_name="train_r", description="Replacement for training (0 for disable)", long="train-r", argument="yes", mode="always", default_value=300000, filter=tonumber, }, { index_name="val_r", description="Replacement for validation (0 for disable)", long="val-r", argument="yes", mode="always", default_value=0, filter=tonumber, }, { index_name="tiedfile", description = "HTK unit's tied list", long = "tiedfile", argument = "yes", mode="always", }, { index_name = "context", description = "Size of ann context", long = "context", argument = "yes", mode="always", default_value=4, filter=tonumber, }, { index_name = "feats_format", description = "Format of features mat or mfc or png (mat, png or mfc)", long = "feats-format", argument = "yes", mode="always", default_value="mat", }, { index_name = "feats_norm", description = "Table with means and devs for features", long = "feats-norm", argument = "yes", filter = dofile, }, { index_name = "step", description = "Dataset step", long = "step", argument = "yes", mode="always", default_value=1, filter=tonumber, }, { index_name = "mean", description = "Mean of gaussian perturbation", long = "mean", argument = "yes", mode="always", default_value=0, filter=tonumber, }, { index_name = "var", description = "Variance of gaussian perturbation (0 for disable)", long = "var", argument = "yes", mode="always", default_value=0.015, filter=tonumber, }, { index_name = "salt", description = "Salt noise percentage", long = "salt", argument = "yes", mode="always", default_value=0, filter=tonumber, }, { index_name = "seedp", description = "Perturbation seed", long = "seedp", argument = "yes", mode="always", default_value=86544, filter=tonumber, }, { index_name = "firstlr", description = "First learning rate", long ="firstlr", argument="yes", mode="always", default_value=0.005, filter=tonumber, }, { index_name = "epochs_firstlr", description = "Num epochs for first learning rate", long ="epochs-firstlr", argument="yes", mode="always", default_value=100, filter=tonumber, }, { index_name = "lr", description = "Learning rate", long ="lr", argument="yes", mode="always", default_value=0.001, filter=tonumber, }, { index_name = "mt", description = "Momentum", long ="mt", argument="yes", mode="always", default_value=0.005, filter=tonumber, }, { index_name = "wd", description = "Weight decay", long ="wd", argument="yes", mode="always", default_value=1e-06, filter=tonumber, }, { index_name = "l1", description = "L1 norm regularization", long ="l1", argument="yes", mode="always", default_value=0.0, filter=tonumber, }, { index_name = "mp", description = "Max normalization penalty, a negative value to disable it", long ="mp", argument="yes", mode="always", default_value=-1, filter=tonumber, }, { index_name="rndw", description="Size of the random inf/sup for MLP", long="rndw", argument="yes", mode="always", default_value=0.1, filter=tonumber, }, { index_name = "seed1", description = "Seed 1", long ="seed1", argument="yes", mode="always", default_value=1234, filter=tonumber, }, { index_name = "seed2", description = "Seed 2", long ="seed2", argument="yes", mode="always", default_value=4567, filter=tonumber, }, { index_name = "seed3", description = "Seed 3", long ="seed3", argument="yes", mode="always", default_value=9876, filter=tonumber, }, { index_name = "epochs_wo_val", description = "Epochs without validation", long ="epochs-wo-val", argument="yes", mode="always", default_value=4, filter=tonumber, }, { index_name = "epochs_wo_imp", description = "Epochs without improvement", long ="epochs-wo-imp", argument="yes", mode="always", default_value=20, filter=tonumber, }, { index_name = "epochs_wo_exp", description = "Epochs without expectation step", long ="epochs-wo-exp", argument="yes", mode="always", default_value=5, filter=tonumber, }, { index_name = "epochs_max", description = "Number of epochs for maximization step", long ="epochs-max", argument="yes", mode="always", default_value=100, filter=tonumber, }, { index_name = "epochs_first_max", description = "Number of epochs for first maximization step", long ="epochs-first-max", argument="yes", mode="always", default_value=500, filter=tonumber, }, { index_name = "em_it", description = "Number of EM iterations", long ="em-it", argument="yes", mode="always", default_value=100, filter=tonumber, }, { index_name = "dropped_em_iterations", description = "The number of EM iterations where the ANN is reinitialized from scratch", long ="dropped-em-iterations", argument="yes", mode="always", default_value=0, filter=tonumber, }, { index_name="pretrained_mlp", description="Initial pretrained MLP", long="pretrained-mlp", argument="yes", }, { index_name="initial_mlp", description="Initial MLP for continue an stopped training", long="initial-mlp", argument="yes", }, { index_name="initial_hmm", description="Initial HMM for continue an stopped training, or to use as a first HMM description", long="initial-hmm", argument="yes", }, { index_name="initial_em_epoch", description="Initial EM epoch for continue an stopped training", long="initial-em-epoch", argument="yes", filter=tonumber, }, { index_name="transcription_filter", description="Filter the transcriptions to generate phonetic sequences", long="transcription-filter", argument="yes", filter=dofile, }, { index_name="silences", description="HMM models for silences (a blank separated list)", long="silences", argument="yes", filter=string.tokenize, mode="always", default_value="", }, { index_name="clamp_lower", description="Indicates the lower value for input clamp (after normalization)", long="clamp-lower", argument="yes", filter=tonumber, }, { index_name="clamp_upper", description="Indicates the upper value for input clamp (after normalization)", long="clamp-upper", argument="yes", filter=tonumber, }, { description = "shows this help message", short = "h", long = "help", argument = "no", action = function (argument) print(cmdOptTest:generate_help()) os.exit(1) end } } local optargs = cmdOptTest:parse_without_check() if type(optargs) == "string" then error(optargs) end local initial_values if optargs.defopt then initial_values = optargs.defopt optargs.defopt=nil end optargs = cmdOptTest:check_args(optargs, initial_values) return optargs april-ann-0.4.1/tools/HMM_ANN/training/compute-mean-and-dev.lua000066400000000000000000000013261263004425400241000ustar00rootroot00000000000000if #arg ~= 1 then print("SINTAXIS: %s file_list\n".. "file_list must contains filenames of ".. "matrix parameters (April format)\n", arg[0]) os.exit(0) end lista = arg[1] local ds = {} for fichero in io.lines(lista) do fprintf(io.stderr, "# Loading: %s\n", fichero) local f = io.open(fichero) or error ("File not found: " .. fichero) local mat = matrix.fromFilename(fichero, "row_major") table.insert(ds, dataset.matrix(mat)) f:close() end ds = dataset.union(ds) means,devs = ds:mean_deviation() printf("-- %d patterns, %d params\n", ds:numPatterns(), ds:patternSize()) printf("return {\nmeans = {\n%s\n},\ndevs = {\n%s\n}\n}\n", table.concat(means, ", "), table.concat(devs, ", ")) april-ann-0.4.1/tools/HMM_ANN/training/extract-EM-epoch-best-entroy-values-from-log.sh000066400000000000000000000002201263004425400303460ustar00rootroot00000000000000#!/bin/bash grep -v "#" $1 | awk 'BEGIN{n=1;last=0;}{ if ($2 != n) { printf("%d %f\n", n, last); n=$2; } else last = $12; }' april-ann-0.4.1/tools/HMM_ANN/training/template-train-conf.lua000066400000000000000000000013201263004425400240350ustar00rootroot00000000000000return { -- "@" for HTR, "( ) ." for ASR silences="@", tiedlist="tiedlist_CONCOMILLADOBLE.id", train_m="pats//list.train.mat", train_s="pats//list.train.sgm", train_f="pats//list.train.txt", val_m="pats//list.val.mat", val_s="pats//list.val.sgm", val_f="pats//list.val.txt", train_r=300000, val_r=200000, num_states=7, n=60, context=4, h1=192, h2=128, rndw=0.1, lr=0.001, mt=0.005, wd=1e-6, firstlr=0.005, epochs_firstlr=100, epochs_wo_val=4, epochs_wo_imp=20, epochs_max=100, epochs_first_max=500, feats_format="mat", feats_norm="pats/means_and_devs.PRESERVANDOX.lua", mean=0, var=0.015, seedp=86544, seed1=1234, seed2=4567, seed3=9876, epochs_wo_exp=5, em_it=100, } april-ann-0.4.1/tools/HMM_ANN/training/train.lua000066400000000000000000000570601263004425400213150ustar00rootroot00000000000000-- This script is for HMM-ANN training using EM algorithm -- -- Following algorithm is a general description of how it works: -- -- Viterbi initial segmentation or use a given one -- For each em iteration or until stop criterion -- Train MLP until stop criterion -- Viterbi segmentation using previous MLP -- End -- april_print_script_header(arg) dofile(string.get_path(arg[0]) .. "../utils.lua") optargs = dofile(string.get_path(arg[0]) .. "/cmdopt.lua") table.unpack_on(optargs, _G) trainfile_mfc = optargs.train_m trainfile_fon = optargs.train_f trainfile_sgm = optargs.train_s valfile_mfc = optargs.val_m valfile_fon = optargs.val_f valfile_sgm = optargs.val_s means_and_devs = feats_norm dataset_step = optargs.step format = feats_format error_function = "multi_class_cross_entropy" if trainfile_sgm and not valfile_sgm then error ("Needed validation initial segmentation") end if initial_mlp then -- sin segmentacion inicial trainfile_sgm = nil valfile_sgm = nil end if not num_states and not initial_hmm then error ("Needs a number of states per HMM or an initial HMM file") end if not silences or #silences==0 then fprintf(io.stderr, "# WARNING!!! NOT SILENCES TABLE DEFINED\n") end if not begin_sil or not end_sil then fprintf(io.stderr, "# WARNING!!! NOT BEGIN AND END SILENCE SYMBOLS DEFINED\n") end if transcription_filter then fprintf(io.stderr, "# Using transcription filter\n") end -- pasar esto como parametro local perturbation_random = random(seedp) if var > 0 then dataset_perturbation_function = function(ds) return dataset.perturbation{ dataset = ds, random = perturbation_random, mean = mean, variance = var, } end end if salt > 0 then local old_dataset_perturbation_function = dataset_perturbation_function dataset_perturbation_function = function(ds) return dataset.salt_noise{ dataset = old_dataset_perturbation_function(ds), vd = salt, zero = 0, random = perturbation_random, } end end if initial_mlp or initial_em_epoch then if not initial_hmm or not initial_em_epoch or not initial_mlp then error("Continue a training needs: initial-em-epoch, initial-mlp, initial-hmm") end end ------------------------------------------------------------------------------ models_dir = "models" nets_dir = models_dir.."/nets" hmms_dir = models_dir.."/hmms" -------------------- -- parametros HMM -- -------------------- hmm = {} hmm.num_states = optargs.num_states hmm.num_params = optargs.n hmm.silences = {} for _,sil in ipairs(silences) do hmm.silences[sil] = 1.0 end -------------------- -- parametros RNA -- -------------------- ann_table = {} ann_table.left_context = context ann_table.right_context = context ann_table.num_hidden1 = h1 ann_table.num_hidden2 = h2 ann_table.first_learning_rate = firstlr ann_table.num_epochs_first_lr = epochs_firstlr ann_table.learning_rate = lr ann_table.momentum = mt ann_table.max_norm_penalty = mp ann_table.l1_norm = l1 ann_table.weight_decay = wd ann_table.weights_seed = seed1 ann_table.shuffle_seed = seed2 ann_table.shuffle_seed_val = seed3 ann_table.replacement = (train_r ~= 0 and train_r) or nil ann_table.replacement_val = (val_r ~= 0 and val_r ) or nil ann_table.rndw = rndw ------------------- -- parametros EM -- ------------------- em = {} --em.epoca_cambio_fb_viterbi = 0 em.num_epochs_without_validation = epochs_wo_val em.max_epochs_without_improvement = epochs_wo_imp em.num_emiterations_without_expectation = epochs_wo_exp em.num_maximization_iterations = epochs_max em.num_maximization_iterations_first_em = epochs_first_max em.em_max_iterations = em_it -------------------------------------------------------------- -------------------- -- Corpus -- -------------------- corpus = {} corpus.filename_trn_mfc = trainfile_mfc corpus.filename_val_mfc = valfile_mfc corpus.filename_trn_fon = trainfile_fon corpus.filename_val_fon = valfile_fon corpus.filename_trn_sgm = trainfile_sgm corpus.filename_val_sgm = valfile_sgm os.execute("mkdir "..models_dir) os.execute("mkdir "..nets_dir) os.execute("mkdir "..hmms_dir) -- objeto con informacion sobre modelos ligados tied = tied_model_manager(io.open(tiedfile)) --------- -- HMM -- --------- -- creamos el trainer y le metemos los modelos acusticos hmmtrainer = HMMTrainer.trainer() -- modelos HMM models = {} if initial_hmm then models,num_models,num_emissions = load_models_from_hmm_lua_desc(initial_hmm, hmmtrainer) else models,num_models = generate_hmm_models_from_tiedlist(tied, hmm.num_states, hmmtrainer) num_emissions = num_models * hmm.num_states hmmtrainer.trainer:check_cls_emission(num_emissions) -- local aprioris = iterator(range(1,num_emissions)): map(function()return 1/num_emissions end): table() -- hmmtrainer.trainer:set_a_priori_emissions(aprioris) end ann_table.output_dictionary = dataset.identity(num_emissions, 0.0, 1.0) collectgarbage("collect") -- ENTRADAS Y SALIDAS DE LA ANN ann_table.num_entradas = hmm.num_params*(ann_table.left_context+ann_table.right_context+1)*dataset_step ann_table.num_outputs = num_emissions ------------------ -- Red neuronal -- ------------------ -- -- estructura de la red local best_trainer local global_best_trainer local mlp_str local weights_random = random(ann_table.weights_seed) function initialize_neural_network() print("# INITIALIZING THE ANN") ann_table.thenet = nil mlp_str = nil if ann_table.num_hidden2 > 0 then mlp_str = string.format("%d inputs %d logistic %d logistic", ann_table.num_entradas, ann_table.num_hidden1, ann_table.num_hidden2) else mlp_str = string.format("%d inputs %d logistic", ann_table.num_entradas, ann_table.num_hidden1) end -- generamos la red if initial_mlp then print("# LOADING ANN FROM PREVIOUS HMMANN") mlp_str = initial_mlp ann_table.trainer = trainable.supervised_trainer.load(initial_mlp, ann.loss[error_function](ann_table.num_outputs), bunch_size) ann_table.thenet = ann_table.trainer:get_component() elseif pretrained_mlp then print("# LOADING PRETRAINED ANN") mlp_str = pretrained_mlp ann_table.trainer = trainable.supervised_trainer.load(pretrained_mlp, ann.loss[error_function](ann_table.num_outputs), bunch_size) ann_table.thenet = ann_table.trainer:get_component() else print("# CREATING ANN FROM SCRATCH") ann_table.thenet = ann.components.stack() mlp_str = string.format("%d inputs",ann_table.num_entradas) -- if ann_table.num_hidden1 > 0 then mlp_str = string.format("%s %d logistic", mlp_str, ann_table.num_hidden1) ann_table.thenet:push(ann.components.hyperplane{ dot_product_name="w1", bias_name="b1", dot_product_weights="w1", bias_weights="b1", input = ann_table.num_entradas, output = ann_table.num_hidden1, }): push(ann.components.actf.logistic{ name="actf1" }) end -- if ann_table.num_hidden2 > 0 then mlp_str = string.format("%s %d logistic", mlp_str, ann_table.num_hidden2) ann_table.thenet:push(ann.components.hyperplane{ dot_product_name="w2", bias_name="b2", dot_product_weights="w2", bias_weights="b2", input = ann_table.num_hidden1, output = ann_table.num_hidden2, }): push(ann.components.actf.logistic{ name="actf2" }) end -- mlp_str = string.format("%s %d log_softmax", mlp_str, ann_table.num_outputs) ann_table.thenet:push(ann.components.hyperplane{ dot_product_name="wN", bias_name="bN", dot_product_weights="wN", bias_weights="bN", output = ann_table.num_outputs, }): push(ann.components.actf.log_softmax{ name="OUPUT" }) -- ann_table.trainer = trainable.supervised_trainer(ann_table.thenet, ann.loss[error_function](ann_table.num_outputs), bunch_size) ann_table.trainer:build() ann_table.trainer:randomize_weights{ inf = ann_table.rndw, sup = -ann_table.rndw, random = weights_random } end best_trainer = ann_table.trainer global_best_trainer = ann_table.trainer end initialize_neural_network() collectgarbage("collect") -------------------- -- Carga de datos -- -------------------- -- --[[ La funcion corpus_from_audio_filename carga un field manager con estos campos: - audio_filename => Nombre de los ficheros de audio - frames => Acusticas de cada fichero - frames_size => Numero de tramas en cada fichero - hmm_emission_sequence => Tabla con la emision que corresponde a cada trama - hmm_c_models => Modelo de Markov de cada fichero - contextCCdataset => Dataset contextualizado con las tramas - segmentation_matrix => Matriz con la segmentacion inicial (la mejor) - segmentation_dataset => Dataset para la segmentation_matrix --]] -- -- TRAINING print ("# LOADING TRAINING...") training = {} if not string.match(corpus.filename_trn_mfc, "%.lua$") then if count_values[1] then error ("Count values are forbidden without distribution!!!") end table.insert(training, corpus_from_MFC_filename{ filename_mfc = corpus.filename_trn_mfc, filename_fon = corpus.filename_trn_fon, filename_sgm = corpus.filename_trn_sgm, phdict = train_phdict, begin_sil = begin_sil, end_sil = end_sil, hmmtrainer = hmmtrainer, tied = tied, left_context = ann_table.left_context, right_context = ann_table.right_context, mlp_output_dictionary = ann_table.output_dictionary, models = models, silences = hmm.silences, transcription_filter = transcription_filter, hmm_name_mangling = false, dataset_step = dataset_step, means_and_devs = means_and_devs, clamp = { clamp_lower, clamp_upper }, dataset_perturbation_function = dataset_perturbation_function, format = format, }) else local mfc = dofile(corpus.filename_trn_mfc) local fon = dofile(corpus.filename_trn_fon) local sgm = {} if #mfc ~= #fon then error ("Incorrect number of fields in Lua MFC or FON file") end if corpus.filename_trn_sgm then sgm = dofile(corpus.filename_trn_sgm) if #mfc ~= #sgm then error ("Incorrect number of fields in Lua SGM file") end end corpus.distribution = {} training = {} for i=1,#mfc do if not count_values[i] then error ("Incorrect number of count_values parameter") end sgm[i] = sgm[i] or {} if not sgm[i][1] then if not initial_mlp then print("# WARNING!!! training with equidistant initial segmentation for " .. mfc[i][1]) else print("# Ignoring initial segmentation, MLP given") end end table.insert(training, corpus_from_MFC_filename{ filename_mfc = mfc[i][1] or error("Incorrect MFC field"), filename_fon = fon[i][1] or error("Incorrect FON field"), filename_sgm = sgm[i][1], phdict = train_phdict, begin_sil = begin_sil, end_sil = end_sil, hmmtrainer = hmmtrainer, tied = tied, left_context = ann_table.left_context, right_context = ann_table.right_context, mlp_output_dictionary = ann_table.output_dictionary, models = models, silences = hmm.silences, transcription_filter = transcription_filter, hmm_name_mangling = false, dataset_step = dataset_step, means_and_devs = means_and_devs, clamp = { clamp_lower, clamp_upper }, dataset_perturbation_function = dataset_perturbation_function, format = format, }) table.insert(corpus.distribution, { -- OJO: i == #training input_dataset = dataset.union(training[i]:get_field('contextCCdataset')), output_dataset = dataset.union(training[i]:get_field('segmentation_dataset')), probability = tonumber(mfc[i][2]) }) end end -- VALIDATION print ("# LOADING VALIDATION...") validate = corpus_from_MFC_filename{ filename_mfc = corpus.filename_val_mfc, filename_fon = corpus.filename_val_fon, filename_sgm = corpus.filename_val_sgm, phdict = val_phdict, begin_sil = begin_sil, end_sil = end_sil, hmmtrainer = hmmtrainer, tied = tied, left_context = ann_table.left_context, right_context = ann_table.right_context, mlp_output_dictionary = ann_table.output_dictionary, models = models, silences = hmm.silences, transcription_filter = transcription_filter, hmm_name_mangling = false, dataset_step = dataset_step, means_and_devs = means_and_devs, clamp = { clamp_lower, clamp_upper }, format = format, } -- ESTO ERA PARA EVITAR QUE PETARA CON LOS MODELOS QUE NO APARECIESEN -- EN LAS FRASES: --aux_c_tbl = {} --for i=1,table.getn(modeloAcustico.phones_list) do -- local ph = modeloAcustico.phones_list[i].name[1] -- local desc = HMMTrainer.utils.str2model_desc(ph) -- aux = hmmtrainer:model(desc) -- table.insert(aux_c_tbl, aux:generate_C_model()) --end -- -------------------------- -- creamos los datasets -- -------------------------- -- TRAINING if not corpus.distribution then corpus.input_ds_trn = dataset.union(training[1]:get_field('contextCCdataset')) corpus.output_ds_trn = dataset.union(training[1]:get_field('segmentation_dataset')) end -- VALIDATION corpus.input_ds_val = dataset.union(validate:get_field('contextCCdataset')) corpus.output_ds_val = dataset.union(validate:get_field('segmentation_dataset')) printf ("# RANDOM: Weights: %4d Shuffle: %4d VAL RPL shuffle: %4d\n", ann_table.weights_seed, ann_table.shuffle_seed, ann_table.shuffle_seed_val) printf ("# ANN PARAMS: step:%d l%d r%d %d %d lr: %f mt: %f wd: %g mp: %g l1: %g\n", dataset_step, ann_table.left_context, ann_table.right_context, ann_table.num_hidden1, ann_table.num_hidden2, ann_table.learning_rate, ann_table.momentum, ann_table.weight_decay, ann_table.max_norm_penalty, ann_table.l1_norm) printf ("# first lr: %f epochs: %d\n", ann_table.first_learning_rate, ann_table.num_epochs_first_lr) printf ("# ANN STR: %s\n", mlp_str) printf ("# HMM PARAMS: states: %d numparams: %d\n", hmm.num_states or 0, hmm.num_params) printf ("# EM PARAMS: val: %d stop: %d expectation: %d it: %d %d em: %d\n", em.num_epochs_without_validation, em.max_epochs_without_improvement, em.num_emiterations_without_expectation, em.num_maximization_iterations_first_em, em.num_maximization_iterations, em.em_max_iterations) if not corpus.distribution then printf ("# Input pattern size: %d\n", corpus.input_ds_trn:patternSize()) printf ("# Training num patterns: %d\n", corpus.input_ds_trn:numPatterns()) else printf ("# Input pattern size: %d\n", corpus.distribution[1].input_dataset:patternSize()) printf ("# Training num patterns:") for i=1,#corpus.distribution do printf (" %d (%f)", corpus.distribution[i].input_dataset:numPatterns(), corpus.distribution[i].probability) end printf ("\n") end printf ("# Validation num patterns: %d\n", corpus.input_ds_val:numPatterns()) printf ("# Replacement: %d\n", ann_table.replacement or 0) printf ("# Replacement val: %d\n", ann_table.replacement_val or 0) -- log if not trainfile_sgm then if not initial_mlp then print("WARNING!!! training with equidistant initial segmentation") else print("# Ignoring initial segmentation") end end if initial_mlp and initial_hmm then printf ("# CONTINUE TRAINING: %s %s %d\n", initial_mlp, initial_hmm, initial_em_epoch) elseif initial_hmm then printf ("# INITIAL HMM: %s\n", initial_hmm) elseif initial_mlp then printf ("# INITIAL MLP: %s\n", initial_mlp) end ann_table.trainingdata = { shuffle = random(ann_table.shuffle_seed), replacement = ann_table.replacement, } if not corpus.distribution then ann_table.trainingdata.input_dataset = corpus.input_ds_trn ann_table.trainingdata.output_dataset = corpus.output_ds_trn else ann_table.trainingdata.distribution = corpus.distribution end ann_table.validationdata = { input_dataset = corpus.input_ds_val, output_dataset = corpus.output_ds_val, } if ann_table.replacement_val then ann_table.validationdata.replacement = ann_table.replacement_val ann_table.validationdata.shuffle = random(ann_table.shuffle_seed_val) end collectgarbage("collect") -------------------------------------------------- -------------- -- TRAINING -- -------------- totaltrain = 1 em_iteration = 1 firstbestce = 11111111111 bestce = 11111111111 bestce_em = 11111111111 bestepoch = 0 bestepoch_em = 0 if initial_em_epoch then em_iteration = initial_em_epoch -- resegmentamos validacion local va_score = generate_new_segmentation{ field_manager = validate, func = ann_table.trainer, num_emissions = num_emissions, do_expectation = false, emission_in_log_base = true, } -- reinicializamos contadores del trainer de hmm hmmtrainer.trainer:begin_expectation() -- -- EXPECTATION -- -- resegmentamos training con expectacion local tr_score = 0 for i=1,#training do local sc = generate_new_segmentation{ field_manager = training[i], func = ann_table.trainer, num_emissions = num_emissions, count_value = count_values[i], do_expectation = true, emission_in_log_base = true, } tr_score = tr_score + sc end print("# INITIAL HMM SCORE TR= ", tr_score) print("# INITIAL HMM SCORE VA= ", va_score) -- collectgarbage("collect") -- hmmtrainer.trainer:end_expectation{ update_trans_prob = (em_iteration > em.num_emiterations_without_expectation), update_a_priori_emission = true, } -- actualizamos las probabilidades de transitar de los modelos for name,model_info in pairs(models) do model_info.model:update_probs() end end while em_iteration <= em.em_max_iterations do -- -- entrenamos la red neuronal max = em.num_maximization_iterations if em_iteration == 1 then max = em.num_maximization_iterations_first_em end bestepoch = totaltrain global_best_trainer = ann_table.trainer:clone() if em_iteration > 1 then ann_table.trainer:set_option("learning_rate", ann_table.learning_rate) else ann_table.trainer:set_option("learning_rate", ann_table.first_learning_rate) end ann_table.trainer:set_option("momentum", ann_table.momentum) ann_table.trainer:set_option("weight_decay", ann_table.weight_decay) ann_table.trainer:set_option("max_norm_penalty", ann_table.max_norm_penalty) ann_table.trainer:set_option("L1_norm", ann_table.l1_norm) ann_table.trainer:set_layerwise_option("b.*", "weight_decay", 0.0) ann_table.trainer:set_layerwise_option("b.*", "max_norm_penalty", 0.0) ann_table.trainer:set_layerwise_option("b.*", "L1_norm", 0.0) -- -------------------------------------- -- ANN TRAINING (MAXIMIZATION STEP) -- -------------------------------------- local train_function = trainable.train_holdout_validation{ epochs_wo_validation = em.num_epochs_without_validation, min_epochs = em.num_epochs_without_validation, max_epochs = max, stopping_criterion = trainable.stopping_criteria.make_max_epochs_wo_imp_absolute(em.max_epochs_without_improvement), } while train_function:execute(function() local tr_loss = ann_table.trainer:train_dataset(ann_table.trainingdata) local va_loss = ann_table.trainer:validate_dataset(ann_table.validationdata) return ann_table.trainer,tr_loss,va_loss end) do local state = train_function:get_state_table() if train_function:is_best() then bestepoch = state.current_epoch end printf("em %4d epoch %4d totalepoch %4d ce_train %.7f ce_val ".. "%.7f %10d %.7f %.7f :: %.7f %.7f\n", em_iteration, state.current_epoch, totaltrain, state.train_error, state.validation_error, bestepoch, state.best_val_error, ann_table.trainer:get_option("learning_rate"), ann_table.trainer:norm2("w.*"), ann_table.trainer:norm2("b.*")) totaltrain = totaltrain + 1 if (totaltrain > ann_table.num_epochs_first_lr and em_iteration == 1 and totaltrain % 10 == 1 and ann_table.trainer:get_option("learning_rate") > ann_table.learning_rate ) then ann_table.trainer:set_option("learning_rate", ann_table.trainer:get_option("learning_rate") - 0.001) end if state.current_epoch == em.num_epochs_without_validation then firstbestce = state.validation_error printf ("# FIRST BEST CE FOR EM: %.7f\n", firstbestce) end io.stdout:flush() end local result = train_function:get_state_table() -- nos quedamos con la mejor red ;) totaltrain = bestepoch ann_table.trainer = result.best ann_table.thenet = result.best:get_component() --print("tiempo entrenar red ",os.clock() - t1) if bestepoch == em.num_epochs_without_validation then ann_table.trainer = global_best_trainer:clone() ann_table.thenet = ann_table.trainer:get_component() -- break -- BREAK DEL EM end if result.best_val_error < bestce_em then bestce_em = result.best_val_error bestepoch_em = bestepoch end collectgarbage("collect") ------------------------------------------ -- VITERBI ALIGNMENT (EXPECTATION STEP) -- ------------------------------------------ -- resegmentamos validacion local va_score = generate_new_segmentation{ field_manager = validate, func = ann_table.trainer, num_emissions = num_emissions, do_expectation = false, emission_in_log_base = true, } -- reinicializamos contadores del trainer de hmm hmmtrainer.trainer:begin_expectation() -- -- EXPECTATION -- -- resegmentamos training con expectacion local tr_score = 0 for i=1,#training do local sc = generate_new_segmentation{ field_manager = training[i], func = ann_table.trainer, num_emissions = num_emissions, count_value = count_values[i], do_expectation = true, emission_in_log_base = true, } tr_score = tr_score + sc end print("# HMM SCORE TR= ", tr_score) print("# HMM SCORE VA= ", va_score) -- collectgarbage("collect") -- hmmtrainer.trainer:end_expectation{ update_trans_prob = (em_iteration > em.num_emiterations_without_expectation), update_a_priori_emission = true, } -- actualizamos las probabilidades de transitar de los modelos for name,model_info in pairs(models) do model_info.model:update_probs() end -- salvamos a disco los modelos local filem = string.format(hmms_dir .. "/lc%d_rc%d_em%d.lua", ann_table.left_context, ann_table.right_context, em_iteration) save_models_from_hmm_lua_desc(filem, models, hmmtrainer) -- collectgarbage("collect") -- salvamos la red filenet = string.format(nets_dir .. "/lc%d_rc%d_em%d.net", ann_table.left_context, ann_table.right_context, em_iteration) print("# Saving "..filenet) ann_table.trainer:save(filenet,"binary") -- collectgarbage("collect") em_iteration = em_iteration + 1 if em_iteration <= dropped_em_iterations then initialize_neural_network() end end april-ann-0.4.1/tools/HMM_ANN/utils.lua000066400000000000000000000611171263004425400175230ustar00rootroot00000000000000recog = recog or {} local aux_local_vars = {} -- local valid_recog_parameters=table.invert{ "input_lat_filename", "corpus_data_manager", "filename_mfc", "filename_fon", "filename_sgm", "prepfilename", "txtfilename", "convert_MFCname_TRname", "convert_MFCname_FRname", "silences", "transcription_filter", "hmmtrainer", "tied", "models", "left_context", "right_context", "mlp_output_dictionary", "format", "hmm_name_mangling", "means_and_devs", "clamp", "dataset_perturbation_function", "dataset_step", "begin_sil", "end_sil", "phdict" } function check_params(args) for key,v in pairs(args) do if not valid_recog_parameters[key] then error ("The parameter '" .. key .. "' is incorrect!!") end end end function remove_extensions(path) if string.sub(path, #path-2, #path) == ".gz" then path = string.remove_extension(path) end return string.remove_extension(path) end function generate_frontiers(segmenter, mask, numFrames, a_lo_bunke) local frontiers = {} local ant_frames = 0 for i,img_name in ipairs(glob(mask.."*")) do local img_m = matrix.loadImage(img_name, "gray") local img = Image(img_m) local _,w,h = img:info() local segments = segmenter:segment(img) -- print("Segments: "..table.concat(segments," ")) -- dividimos por 20 para sacar la trama a la que corresponde este -- pixel local inc = (a_lo_bunke == "a_lo_bunke" and 1) or (h/20) local ant = 0 -- primera frontera if ant_frames == 0 then table.insert(frontiers, ant_frames) end for j,pixel_pos in ipairs(segments) do local current = math.floor(pixel_pos/inc) -- printf("divido %f entre %f y da %d\n",pixel_pos,inc,current) -- si el frame no cambia, no hacemos nada if current ~= ant then table.insert(frontiers, current + ant_frames) ant = current end end -- metemos el ultimo frame local last_frame = math.round(w/inc) if ant ~= last_frame then table.insert(frontiers, ant_frames + last_frame) end ant_frames = ant_frames + last_frame end if frontiers[#frontiers] < numFrames then table.insert(frontiers, numFrames) end return frontiers end function save_models_from_hmm_lua_desc(filem, models, hmmtrainer) print("# saving "..filem) local modelf = io.open(filem, "w") modelf:write("return { {\n") for name,model_info in pairs(models) do modelf:write("['".. string.gsub(name,"'","\\'") .. "'] = {\n") modelf:write("\tmodel=HMMTrainer.model.from_table(\n") modelf:write(model_info.model:to_string()) modelf:write("),\n") modelf:write("\temissions={".. table.concat(model_info.emissions, ",") .."}\n") modelf:write("},\n") end modelf:write("},\n") modelf:write("{".. table.concat(hmmtrainer.trainer:get_a_priori_emissions(), ",") .."}\n") modelf:write("}\n") modelf:close() end function load_models_from_hmm_lua_desc(initial_hmm, hmmtrainer) local num_models = 0 local num_emissions = 0 local m = dofile(initial_hmm) local models = m[1] local aprioris = m[2] local emiss_to_hmm = {} for name,model_info in pairs(models) do num_models = num_models + 1 num_emissions = num_emissions + #model_info.emissions model_info.model.trainer = hmmtrainer for _,t in ipairs(model_info.model.transitions) do emiss_to_hmm[t.emission] = name end hmmtrainer:add_to_dict(model_info.model, name) end if aprioris then hmmtrainer.trainer:set_a_priori_emissions(aprioris) end return models,num_models,num_emissions,emiss_to_hmm end function generate_hmm_models_from_tiedlist(tied, num_states, hmmtrainer) local emiss_to_hmm = {} local num_models = 0 local hmms = {} local next_emission = 1 local ploops = {} for i=1,num_states do ploops[i] = 0.5 end for model_id,name in ipairs(tied.id2name) do m = tied.tiedlist[name] if name == m then num_models = num_models + 1 local hmm_emissions = {} -- generamos el vector de emisiones for i=1,num_states do hmm_emissions[i] = next_emission emiss_to_hmm[next_emission] = name next_emission = next_emission + 1 end -- este es el representante local desc = HMMTrainer.utils.generate_lr_hmm_desc(name, hmm_emissions, ploops, {}, name) local model = hmmtrainer:model(desc) hmms[name] = { model = model, emissions = hmm_emissions, } -- TODO: IMPORTANTE!!! esto puede petar si palabra = name, -- PETA!!! hmmtrainer:add_to_dict(model, name) end end return hmms, num_models, emiss_to_hmm end -- -- esta funcion carga un objeto tipo field_manager -- con todos los datos que necesitamos extraer del corpus -- function recog.generate_filenames(args) check_params(args) -- local corpus_data_manager = args.corpus_data_manager local filename = args.filename_mfc local input_lat_filename = args.input_lat_filename local prepfilename = args.prepfilename local txtfilename = args.txtfilename local phonfilename = args.filename_fon local sgmfilename = args.filename_sgm -------------------- -- Carga de datos -- -------------------- -- CORPUS_DATA_MANAGER -- cargamos las listas de nombres de ficheros -- nombres de ficheros de audio if filename then corpus_data_manager:load_lines{ field = 'mfcc_filename', filename = filename, } end if input_lat_filename then corpus_data_manager:load_lines{ field = 'input_lat_filename', filename = input_lat_filename, } end if sgmfilename then corpus_data_manager:load_lines{ field = 'sgm_filename', filename = sgmfilename, } end if phonfilename then corpus_data_manager:load_lines{ field = 'phon_filename', filename = phonfilename, } end if prepfilename then corpus_data_manager:load_lines{ field = 'prep_filename', filename = prepfilename, } end if txtfilename then corpus_data_manager:load_lines{ field = 'transcription_filename', filename = txtfilename, } end end function recog.load_frames(args) check_params(args) -- local corpus_data_manager = args.corpus_data_manager local format = args.format -- CORPUS_DATA_MANAGER -- cargamos las tramas acusticas corpus_data_manager:apply{ input_fields = {'mfcc_filename'}, output_fields = { 'frames', -- campo con matrices: frames acusticos de cada frase 'frames_size' -- campo con el numero de frames de cada frase }, the_function = function (filename) printf ("# Loading MFCCs '%s'\n", filename) collectgarbage("collect") local m,size if format == "png" then m,size = load_png(filename) elseif format == "mat" then m,size = load_matrix(filename) else m,size = load_mfcc(filename) end return m,size end } end -- DEPRECATED ???? -- function recog.load_transcription_string(args) -- check_params(args) -- -- -- local corpus_data_manager = args.corpus_data_manager -- local tied = args.tied -- -- cargamos la secuencia de texto -- corpus_data_manager:apply{ -- input_fields = { -- 'transcription_filename', -- }, -- output_fields = { -- 'transcription_string' -- campo con la transcripcion de la frase -- }, -- the_function = -- function (filename) -- printf ("# Cargando '%s'\n",filename) -- local f = io.open(filename, "r") or -- error ("No se ha encontrado ".. filename) -- local tr_str = f:read("*l") -- f:close() -- -- hay que substituir el silencio por word_silence -- return (string.gsub(tr_str, " ", word_silence)) -- end -- } -- end function recog.load_fon_string(args) check_params(args) -- local corpus_data_manager = args.corpus_data_manager local tied = args.tied local phdict = args.phdict -- cargamos la secuencia fonetica corpus_data_manager:apply{ input_fields = { 'phon_filename', }, output_fields = { 'phon_table', }, the_function = function (ph_filename) printf ("# Reading '%s'\n",ph_filename) local f = io.open(ph_filename, "r") or error ("No se ha encontrado ".. ph_filename) local ph_str = f:read("*l") f:close() if transcription_filter then ph_str = transcription_filter(ph_str) end ph_tbl = string.tokenize(ph_str) if not phdict then ph_tbl = tied:search_triphone_sequence(ph_tbl) end return ph_tbl end } end function recog.generate_initial_equidistant_hmm_emission_sequence(args) check_params(args) -- local tied = args.tied local models = args.models local corpus_data_manager = args.corpus_data_manager -- -- generamos secuencia de emisiones en partes iguales a partir de -- la secuencia fonetica y del numero de frames corpus_data_manager:apply{ input_fields = { 'phon_table', -- campo con la transcripcion de la frase 'frames_size', 'phon_filename', }, output_fields = { 'hmm_emission_sequence', -- tabla con lista emisiones corresp. a cada frase }, the_function = function (tbl,numframes,name) print("# Generating equidistant segmentation " .. name) return generate_initial_hmm_emission_sequence(tbl, numframes, tied, models) end } end function recog.generate_hmm_models(args) check_params(args) -- local corpus_data_manager = args.corpus_data_manager local hmmtrainer = args.hmmtrainer local tied = args.tied local silences = args.silences local phdict = args.phdict local begin_sil = args.begin_sil local end_sil = args.end_sil local transcription_filter= args.transcription_filter --------- -- HMM -- --------- -- generamos los modelos para las frases corpus_data_manager:apply{ input_fields = {'phon_table','phon_filename'}, output_fields = { 'hmm_c_models', -- modelo hmm en c generado con el hmmtrainer }, the_function = function (tbl,name) print("# Generating HMM model for: ".. name) if not phdict then if begin_sil then tbl = string.tokenize(begin_sil .. " " .. table.concat(tbl, " ")) end if end_sil then table.insert(tbl, end_sil) end return generate_models_from_sequences(tbl, hmmtrainer, tied, silences) else return generate_models_from_words(tbl, hmmtrainer, tied, silences, begin_sil, end_sil, transcription_filter) end end } end function recog.load_initial_hmm_emission_sequence(args) check_params(args) -- local corpus_data_manager = args.corpus_data_manager -- generamos secuencia de emisiones en partes iguales a partir de -- la secuencia fonetica y del numero de frames corpus_data_manager:apply{ input_fields = { 'sgm_filename', }, output_fields = { 'hmm_emission_sequence', -- tabla con lista emisiones corresp. a cada frase }, the_function = function (sgm_filename,numframes) print("# Loading initial segmentation " .. sgm_filename) local m = matrix.fromFilename(sgm_filename) local t = m:toTable() collectgarbage("collect") return t end } end function recog.generate_datasets(args) check_params(args) -- local mlp_output_dictionary = args.mlp_output_dictionary local left_context = args.left_context local right_context = args.right_context local corpus_data_manager = args.corpus_data_manager local means_and_devs = args.means_and_devs local clamp = args.clamp local dataset_perturbation_function = args.dataset_perturbation_function local dataset_step = args.dataset_step -------------------------- -- creamos los datasets -- -------------------------- corpus_data_manager:apply{ input_fields = {'frames'}, output_fields = { 'contextCCdataset', -- campo con dataset contextualizado de frames acusticos 'nocontextDataset', -- campo con dataset de frames acusticos }, the_function = function (frames) Cds,ds = contextCCdataset(frames, left_context, right_context, means_and_devs, dataset_perturbation_function, dataset_step, clamp) return Cds,ds end } corpus_data_manager:apply{ input_fields = {'hmm_emission_sequence','frames_size', 'phon_filename'}, output_fields = { 'segmentation_matrix', -- campo con matriz de emisiones del mejor camino -- version que guarda secuencia de indices de emision 'segmentation_dataset', -- dataset para entrenar la red neuronal con la matriz anterior }, the_function = function (segmentation,numframes,filename) print("# Generating emitions matrix and dataset: ", filename) return generate_emitions_matrix_and_dataset(segmentation, numframes, mlp_output_dictionary) end } end -- -- esta funcion carga un objeto tipo field_manager -- con todos los datos que necesitamos extraer del corpus -- function corpus_from_MFC_filename(args) check_params(args) -- -------------------- -- Carga de datos -- -------------------- -- CORPUS_DATA -- cargamos las listas de nombres de ficheros corpus_data_manager = field_manager() args.corpus_data_manager = corpus_data_manager -- nombres de ficheros recog.generate_filenames(args) collectgarbage("collect") -- fonetica recog.load_fon_string(args) collectgarbage("collect") -- modelos HMM if args.phdict then recog.load_phdict(args) end recog.generate_hmm_models(args) collectgarbage("collect") -- tramas acusticas recog.load_frames(args) collectgarbage("collect") -- emisiones de los HMMs if args.filename_sgm then recog.load_initial_hmm_emission_sequence(args) else recog.generate_initial_equidistant_hmm_emission_sequence(args) end collectgarbage("collect") print("# Generating datasets") -- datasets :) recog.generate_datasets(args) collectgarbage("collect") -- return corpus_data_manager end --------------------------------------------- -- Funcion para recalcular las matrices de -- -- emisiones del modelo acustico -- --------------------------------------------- function generate_new_segmentation(args) local corpus_data = args.field_manager local func = args.func local do_expectation = args.do_expectation local num_emissions = args.num_emissions local emission_in_log_base = args.emission_in_log_base or false local without_context = args.without_context or false local current = 1 local count_value = args.count_value local total_score = 0 -- -- resegmentamos validacion corpus_data:apply{ input_fields = { 'hmm_c_models', 'segmentation_matrix', 'contextCCdataset', 'nocontextDataset', }, output_fields = { }, the_function = function (themodel,segmentation_matrix,contextCCdataset, nocontextDataset) printf ("# Segmentation... %6d ",current) io.stdout:flush() collectgarbage("collect") -- matriz de salida para la red neuronal local mat_full = matrix(segmentation_matrix:dim()[1], num_emissions) local mat_full_ds = dataset.matrix(mat_full) -- local auxm = nocontextDataset:toMatrix() -- matrix.saveImage(auxm, string.format("tmp/image_%03d.pnm", -- current)) -- generamos la matriz de emisiones dada la -- parametrizacion de la frase actual if without_context then func:use_dataset{ input_dataset = nocontextDataset, -- parametrizacion output_dataset = mat_full_ds -- matriz de emisiones } else func:use_dataset{ input_dataset = contextCCdataset, -- parametrizacion output_dataset = mat_full_ds -- matriz de emisiones } end -- DEBUG BEGIN -- first = nocontextDataset:getPattern(1) -- out = func:use(first) -- print(table.concat(out, " ")) -- print("========================") -- print(table.concat(mat_full_ds:getPattern(1), " ")) -- DEBUG END -- local aux = mat_full:clone():exp() -- aux:adjust_range(0,1) -- matrix.saveImage(aux, -- string.format("tmp-new/mlp_matrix_%03d.pnm", -- current)) -- ahora generamos la salida de Viterbi local logprob = themodel:viterbi{ input_emission = mat_full, do_expectation = do_expectation, output_emission_seq = segmentation_matrix, -- output_emission = mat_full, -- para DEBUG emission_in_log_base = emission_in_log_base, count_value = count_value, } printf("%12.4f score\n", logprob) total_score = total_score + logprob io.stdout:flush() -- mat_full:adjust_range(0,1) -- matrix.saveImage(mat_full, string.format("tmp-new/hmm_matrix_%03d.pnm", -- current)) -- print(segmentation_matrix) current = current + 1 end } -- return total_score end ------------------------------------------------- ------------------------------------------------- -- FUNCIONES PARA TRABAJAR CON UN SOLO FICHERO -- ------------------------------------------------- ------------------------------------------------- function load_frontiers(w, h, frames_size) local c = dofile(frontiers_filename) local t = {} local inc = c.height/20 local ant = 0 -- primera frontera table.insert(t, ant) for i,fr_pos in ipairs(c.frontiers) do -- dividimos por 20 para sacar la trama a la que corresponde este -- pixel local current = math.floor(fr_pos/inc) -- si el frame no cambia, no hacemos nada if current ~= ant then table.insert(t, current) ant = current end end -- metemos el ultimo frame if ant ~= frames_size then table.insert(t, frames_size) end return t end local MFCC_cache = {} -- carga la matriz de CCs a partir de un nombre de fichero function load_matrix(MFCCfilename) -- cargamos la parametrizacion de MATRIX --if MFCCfilename == 'corpus/n02-082a-s05.fea' then os.exit() end local ad = MFCC_cache[MFCCfilename] or matrix.fromFilename(MFCCfilename) MFCC_cache[MFCCfilename] = ad return ad,ad:dim(1) end -- carga la matriz de CCs a partir de un nombre de fichero function load_mfcc(MFCCfilename) -- cargamos la parametrizacion de MATRIX --if MFCCfilename == 'corpus/n02-082a-s05.fea' then os.exit() end tmpname = os.tmpname() local ad if string.sub(MFCCfilename, #MFCCfilename - 2, #MFCCfilename) == ".gz" then os.execute("gzip -d ".. MFCCfilename .." -c > ".. tmpname) ad = htk_interface.read_matrix_from_mfc_file(tmpname) os.execute("rm -f ".. tmpname) else ad = htk_interface.read_matrix_from_mfc_file(MFCCfilename) end return ad,ad:dim(1) end -- carga desde un PNG function load_png(filename) local m = ImageIO.read(filename): to_grayscale(): invert_colors(): matrix(): transpose(): clone() return m,m:dim(1) end -- genera la segmentacion a partes iguales function generate_initial_hmm_emission_sequence(tbl, numframes, tied, models) local ini local fin local m local emitions local num_emitions local seg_tbl = {} local size_tbl = #tbl local act_frame = 1 -- recorremos todos los fonemas del fichero for i=1,size_tbl do m = tied:get_model(tbl[i]) ini = act_frame fin = i*(numframes/size_tbl) if not models[m] then error ("Error, modelo no definido: "..m) end emitions = models[m].emissions num_emitions = #emitions -- dividimos el fonema en sus emisiones for k=1,num_emitions do -- metemos una entrada por cada frame emitido while act_frame < ini + k*(fin-ini)/num_emitions do table.insert (seg_tbl, emitions[k]) act_frame = act_frame + 1 end end -- rellenamos hasta el final while act_frame <= fin do table.insert(seg_tbl, emitions[num_emitions]) act_frame = act_frame + 1 end end -- while act_frame <= numframes do table.insert(seg_tbl, emitions[num_emitions]) act_frame = act_frame + 1 end -- return seg_tbl end ------------------------------- ------------ HMM -------------- ------------------------------- function recog.load_phdict(args) -- si nos dan el diccionario fonetico, generamos modelos para las -- palabras aux_local_vars.mangling = nil -- sirve para el name mangling de las palabras print("# Using dictionary for generate phonetic transcriptions") _,aux_local_vars.mangling=HMMTrainer.utils.dictionary2lextree(io.open(args.phdict), args.tied, args.silences, args.hmmtrainer) collectgarbage("collect") end function generate_models_from_words(tbl, hmmtrainer, tied, silences, begin_sil, end_sil, transcription_filter) local tr_string = table.concat(tbl, " ") -- filtramos la transcripcion if transcription_filter then tr_string = transcription_filter(tr_string) end -- anyadimos los silencios if begin_sil then tr_string = begin_sil .. " " .. tr_string end if end_sil then tr_string = tr_string .. " " .. end_sil end local themodel -- generamos el modelo a partir del diccionario fonetico, necesita -- name mangling local tbl = table.imap(string.tokenize(tr_string), function(str) assert(aux_local_vars.mangling[str] or silences[str], "Word without transcription: " .. str) return aux_local_vars.mangling[str] or str end) return generate_models_from_sequences(tbl, hmmtrainer,nil,silences) end function generate_models_from_sequences(tbl, hmmtrainer, tied, silences, output) local w local result = {} if tied then w = table.imap(tied:search_triphone_sequence(tbl), function(str) return tied:get_model(str) end) else w = tbl end local desc = HMMTrainer.utils.tbl2model_desc(w, silences, output) local aux = hmmtrainer:model(desc) -- print(aux:to_string()) collectgarbage("collect") return aux:generate_C_model() end -------------- -- datasets -- -------------- -- contextualiza la parametrizacion function contextCCdataset(m,leftcontext,rightcontext,means_and_devs,dataset_perturbation_function,dataset_step,clamp) local numFrames = m:dim()[1] local numParams = m:dim()[2] -- nCCs+1 local parameters = { patternSize = {dataset_step, numParams}, offset = {0,0}, -- default value stepSize = {dataset_step, 0}, -- default value, second value is not important numSteps = {numFrames/dataset_step, 1} } local orig_ds = dataset.matrix(m, parameters) if means_and_devs then --print(means_and_devs.means,#means_and_devs.means,means_and_devs.devs,#means_and_devs.devs) orig_ds:normalize_mean_deviation(means_and_devs.means, means_and_devs.devs) end if clamp[1] and clamp[2] then orig_ds = dataset.clamp(orig_ds, clamp[1], clamp[2]) end if dataset_perturbation_function then orig_ds = dataset_perturbation_function(orig_ds) end local ds = dataset.contextualizer (orig_ds,leftcontext,rightcontext) return ds,orig_ds end -- carga las etiquetas de salida de la red -- a partir de la tabla de segmentaciones function dslabels(mat,dictionary) local numFrames = mat:dim()[1] -- table.getn(m_tbl) local parameters = { patternSize = {1}, offset = {0}, stepSize = {1}, -- default value numSteps = {numFrames} } local ds_aux = dataset.matrix(mat,parameters) local ds = dataset.indexed(ds_aux,{dictionary}) return ds end ------------------------------------- function generate_emitions_matrix_and_dataset(seg_tbl, frames, mlp_output_dictionary) local previous = 1 local i = 0 local time,phone local emissions local num_emissions -- creamos la matriz expandiendo los valores local aux_mat = matrix(frames,seg_tbl) local aux_ds = dslabels(aux_mat, mlp_output_dictionary) return aux_mat,aux_ds end function asisted_recognition(dataflow, parser, correcta, correcta_words, dictionary, cronometro) -- RECONOCIMIENTO function corregir_reconocimiento(path, reconocida, correcta_words) local valid_prefix = {} for i=1,#reconocida do if correcta_words[i] == reconocida[i] then valid_prefix[i] = path[i] else break end end if #valid_prefix >= #correcta_words - 1 then if #valid_prefix ~= #correcta_words then return valid_prefix,1 end return valid_prefix,0 end return valid_prefix,1 end ------------------------------------------------------------ local num_corrections = 0 print ("# RUN") t1 = cronometro:read() cronometro:go() resul=the_dataflow:run() cronometro:stop() t2 = cronometro:read() print(t2-t1) if not resul then print("# Error al hacer dataflow:run()") end -- GET BESTPATH path,prob,logprob = model_parser:get_best_path() end april-ann-0.4.1/tools/LM/000077500000000000000000000000001263004425400150455ustar00rootroot00000000000000april-ann-0.4.1/tools/LM/arpa2lira.lua000066400000000000000000000004371263004425400174310ustar00rootroot00000000000000-- se limita a generar un fichero .lira ngram.lira.arpa2lira{ vocabulary = lexClass.load(io.open(arg[1])), limit_vocab = (arg[5] and lexClass.load(io.open(arg[5]))) or nil, input_filename = arg[2], output_filename = arg[3], verbosity = tonumber(arg[4] or 0), } april-ann-0.4.1/tools/LM/lira2blira.lua000066400000000000000000000012031263004425400175670ustar00rootroot00000000000000-- se limita a generar un fichero .blira a partir de un fichero .lira dictionary_filename = arg[1] lira_filename = arg[2] binary_filename = arg[3] -- cargar diccionario dictionary = lexClass.load(io.open(dictionary_filename)) -- cargar lira lira_model = language_models.load(lira_filename, dictionary, '', '') -- todo: check de que lo que lo que hemos cargado es un lira, aunque -- si no lo es el metodo siguiente petara lira_model:save_binary{ filename=binary_filename, vocabulary=dictionary:getWordVocabulary(), } april-ann-0.4.1/tools/LM/ngram-ppl-calc.lua000066400000000000000000000133041263004425400203460ustar00rootroot00000000000000-- calcula la perplejidad de un conjunto de test opt = cmdOpt{ program_name = string.basename(arg[0]), argument_description = "", main_description = "Ngram PPL computed with April toolkit", { index_name="multi_class", description = "Compute a multi class with given number of classes", long = "multi-class", argument = "no", }, { index_name="vocabfilename", description = "Vocabulary (plain or HTK dictionary)", short = "v", argument = "yes", mode = "always", }, { index_name="langmodel_filename", description = "Language model (.lua for NNLMs in Lua script, .lira.gz for lira, ".. ".DIR for NNLMs in a DIR structure)", short = "l", argument = "yes", mode = "always", }, { index_name="nnlm_conf", description = "Configuration of NNLMs training", short = "f", argument = "yes", }, { index_name="word2probs", description="Word2probs table, for compute correctly the output of NNLMs", short="w", argument="yes", }, { index_name="test", description = "Input text", short = "t", argument = "yes", mode = "always", }, { index_name="debug", description = "Debug level (0, 1, 2)", short = "d", argument = "yes", mode = "always", default_value = 0, filter = tonumber, }, { index_name="stream", description="The input text is a words stream", long="stream", argument = "no", }, { index_name = "trie_size", description = "Size of TrieVector for NNLMs", long = "trie-size", argument = "yes", mode = "always", default_value = 24, filter = tonumber, }, { index_name = "use_unk", description = "Indicate if use or not unk words in PPL computation (all, context, none)", long = "unk", argument = "yes", mode = "always", default_value = "all", }, { index_name = "train_restriction", description = "Indicate the use of for indicate which sentences must be used for compute PPL", long = "train-restriction", argument = "no", }, { index_name = "cache_data", description = "File with cache-data (use only with .DIR)", long = "cache-data", argument = "yes", }, { index_name="cache_stop_token", description="Cache stop token", long="cache-stop-token", argument="yes", mode = "always", default_value = "", }, { index_name="null_token", description="Null token", long="null-token", argument="yes", mode = "always", default_value = "", }, { index_name = "order", description = "Use this Ngram order instead of model's order", long = "order", argument = "yes", filter = tonumber, }, { index_name = "no_sos", description = "Avoid start-of-sentence", long = "no-sos", argument = "no", }, { index_name = "no_eos", description = "Avoid end-of-sentence", long = "no-eos", argument = "no", }, { index_name = "max_softmax_constants", description = "Max number of softmax constants", long="max-softmax-constants", argument="yes", mode = "always", default_value = 0, filter = tonumber, }, { index_name = "print_stats", description = "Print stats", long="print-stats", argument = "no", }, { description = "shows this help message", short = "h", long = "help", argument = "no", action = function (argument) print(opt:generate_help()) os.exit(1) end } } --------------------------------------------------- local optargs = opt:parse_args(nil,"nnlm_conf",false) table.unpack_on(optargs, _G) if word2probs then word2probs = ngram.load_word2prob_smooth_factor(word2probs) end local vocab = lexClass.load(io.open(vocabfilename)) local model = language_models.load(langmodel_filename, vocab, "", "", { cache_size = 10, -- podria ser 0 ;) trie_size = trie_size, word2probs = word2probs, cache_data = cache_data, max_trie_constants = max_softmax_constants }) --[[ if multi_class then local N = #vocab:getWordVocabulary() multi_class_table = {} for i=1,N do table.insert(multi_class_table, i) end r = random() multi_class_table = r:shuffle(multi_class_table) num_classes = math.ceil(math.sqrt(N)) end ]]-- local cronometro = util.stopwatch() cronometro:reset() cronometro:go() local resul = language_models.test_set_ppl{ lm = model, vocab = vocab, testset = test, log_file = io.stdout, debug_flag = debug, use_unk = use_unk, use_cache = false, train_restriction = train_restriction, cache_stop_token = cache_stop_token, null_token = null_token, use_bcc = not no_sos, use_ecc = not no_eos, } fprintf(io.stderr, "Time: %f\nTime/token: %f\nTime/sentence: %f\n", cronometro:read(), cronometro:read()/(resul.numwords + resul.numsentences), cronometro:read()/resul.numsentences) if print_stats then model:printStats() end april-ann-0.4.1/tools/LM/xlex_freq.lua000066400000000000000000000124351263004425400175520ustar00rootroot00000000000000opt = cmdOpt{ program_name = string.basename(arg[0]), argument_description = "", main_description = "April lexicon handler", { index_name="text", description="Text file where extract the lexicon (It could be a Lua table with pairs {text,prob} )", short="t", argument="yes", }, { index_name="vocfile", description="Take only words from this vocabulary, needs text parameter", short="v", argument="yes", }, { index_name="freqvocfile", description="Frequency vocabulary extracted from previous running", short="f", argument="yes", }, { index_name="cutsizes_tbl", description="Cut sizes table (absolute values)", short="c", argument="yes", }, { index_name="ksizes_tbl", description="K-cut sizes table (abosulte frequency values)", short="k", argument="yes", }, { index_name="addunk", description="Add word (default yes)", long="add-unk", argument="yes", }, { index_name="addnull", description="Add word (default no)", long="add-null", argument="yes", }, { index_name="addstop", description="Add word (default no)", long="add-stop", argument="yes", }, { description = "shows this help message", short = "h", long = "help", argument = "no", action = function (argument) print(opt:generate_help()) os.exit(1) end } } optargs = opt:parse_args() if type(optargs) == "string" then error(optargs) end text = optargs.text freqvocfile = optargs.freqvocfile vocfile = optargs.vocfile addunk = ((optargs.addunk or "yes") == "yes") addnull = ((optargs.addnull or "no") == "yes") addstop = ((optargs.addstop or "no") == "yes") cutsizes_tbl = string.tokenize(optargs.cutsizes_tbl or "",",") ksizes_tbl = string.tokenize(optargs.ksizes_tbl or "", ",") if (not text and not freqvocfile) or (text and freqvocfile) then error ("Needs a text or-exclusive voc!!!") end map = {} vocab = {} next = 1 counts = 0 if vocfile then if not text then error("text parameter must be active when using vocfile") end count_unks = 0 for line in io.lines(vocfile) do if line ~= "" and line ~= "" and line ~= "" and line ~= "" and line ~= "" then map[line] = next vocab[next] = { w = line, n = 0, id = next } next = next + 1 end end end min = 1000000 if text then if string.match(text, "%.lua") then textdata = dofile(text) else textdata = { { text, 1 } } end for _,d in ipairs(textdata) do local patfile=d[1] local prob=d[2] print(patfile, prob) local jaja=0 if prob < min then min = prob end for line in io.lines(patfile) do jaja = jaja + 1 if jaja % 100000 == 0 then printf(".") io.stdout:flush() end local words = string.tokenize(line) for i,w in ipairs(words) do if vocfile then if map[w] then vocab[map[w]].n = vocab[map[w]].n + prob counts = counts + prob else count_unks = count_unks + prob end elseif not vocfile then if not map[w] then map[w] = next next = next + 1 end vocab[map[w]] = vocab[map[w]] or { w = w, id = map[w], n = 0, } vocab[map[w]].n = vocab[map[w]].n+prob counts = counts + prob end end end printf("\n") end table.sort(vocab, function(a, b) if a.n == b.n then return a.id < b.id end return a.n > b.n end) local f = io.open("voc.ALL", "w") f:write("\n\n") if addunk then f:write("\n") end if addnull then f:write("\n") end if addstop then f:write("\n") end for i,data in ipairs(vocab) do fprintf(f, "%s\n", data.w) end f:close() local f = io.open("voc.freq.ALL", "w") --local g = io.open("voc.freq2.ALL", "w") if count_unks then fprintf(f, "%12f\t\n", count_unks) end for i,data in ipairs(vocab) do if vocfile and data.n == 0 then data.n = min end fprintf(f, "%12f\t%s\n", data.n, data.w) -- fprintf(g, "%s\n", data.w) end f:close() --g:close() else for line in io.lines(freqvocfile) do local t = string.tokenize(line) map[t[2]] = next vocab[next] = { w = t[2], n = tonumber(t[1]), id = next } counts = counts + vocab[next].n next = next + 1 end end for j=1,#cutsizes_tbl do local sum=0 cutsize = tonumber(cutsizes_tbl[j]) - 2 local g = io.open("voc.".. cutsize, "w") g:write("\n\n") if addunk then g:write("\n") cutsize = cutsize - 1 end if addnull then g:write("\n") cutsize = cutsize - 1 end if addstop then g:write("\n") cutsize = cutsize - 1 end for i=1,cutsize do fprintf(g, "%s\n", vocab[i].w) sum = sum + vocab[i].n end g:close() end for j=1,#ksizes_tbl do ksize = tonumber(ksizes_tbl[j]) local g = io.open("voc.K".. ksize, "w") g:write("\n\n") if addunk then g:write("\n") end if addnull then g:write("\n") end if addstop then g:write("\n") end for i=1,#vocab do if vocab[i].n <= ksize then break end fprintf(g, "%s\n", vocab[i].w) end g:close() end april-ann-0.4.1/tools/README.md000066400000000000000000000011061263004425400160120ustar00rootroot00000000000000Tools directory =============== This directory contains Lua scripts prepared to run experiments for different tasks using APRIL-ANN. Currently, you can find following directories: ``` tools/ | |-- ANNs/ With utilities to transform ANNs from different formats. | |-- HMM_ANN/ Scripts to train HMM/ANN models. | |-- statistics/ Different statistic measures for confidence computation and other stuff. | |-- april_utilities Utilities to deal with the april structure. \ -- trainable/ Utilities to do meta-training as hyper-parameter optimization. ``` april-ann-0.4.1/tools/april_utilities/000077500000000000000000000000001263004425400177375ustar00rootroot00000000000000april-ann-0.4.1/tools/april_utilities/create_package.lua000066400000000000000000000062101263004425400233570ustar00rootroot00000000000000local PACKAGE_NAME = arg[1] local GNU_LICENSE = [[ /* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco * Zamora-Martinez, Joan Pastor-Pellicer * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ ]] if not PACKAGE_NAME then error("A name as argument is required") end local root_dir = PACKAGE_NAME local PACKAGE_INFO = string.format([[ package{ name = "%s", version = "1.0", depends = { }, keywords = { }, description = "A new awesome april package!", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_%s.lua.cc", dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp=true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_%s.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{}, document_bind{}, }, } ]],PACKAGE_NAME, PACKAGE_NAME, PACKAGE_NAME) print ("Creating Root dir "..root_dir) os.execute(string.format("mkdir -p %s %s/binding %s/c_src %s/doc", root_dir, root_dir, root_dir, root_dir)) print("Creating sources") local fheader = io.open(string.format("%s/c_src/%s.h", root_dir, PACKAGE_NAME), "w") fheader:write(GNU_LICENSE) fheader:write(string.format("#ifndef %s_H\n#define %s_H\n\n\n#endif\n",string.upper(PACKAGE_NAME), string.upper(PACKAGE_NAME))) fheader:close() local fsource = io.open(string.format("%s/c_src/%s.cc", root_dir, PACKAGE_NAME), "w") fsource:write(GNU_LICENSE) fsource:write(string.format("#include \"%s.h\"",PACKAGE_NAME)) fsource:close() print("Creating Binding...") local fbinding = io.open(string.format("%s/binding/bind_%s.lua.cc", root_dir, PACKAGE_NAME), "w") fbinding:write(GNU_LICENSE) fbinding:write(string.format("//BIND_HEADER_H\n#include \n#include\n#include \"%s.h\"\n//BIND_END\n",PACKAGE_NAME)) fbinding:close() print("Setting configuration file...") local fconf = io.open(string.format("%s/package.lua", PACKAGE_NAME), "w") fconf:write(PACKAGE_INFO) fconf:close() print("Package created") april-ann-0.4.1/tools/aprilann.py000066400000000000000000000025401263004425400167140ustar00rootroot00000000000000import numpy class matrix(object): @staticmethod def fromMMap(filename): sz = 4 f = open(filename) magic_number = numpy.fromfile(f,dtype=numpy.dtype('int32'),count=1) if magic_number != 0x4321: raise RuntimeError("Incorrect magic number") commit_number = numpy.fromfile(f,dtype=numpy.dtype('int32'),count=1) size = numpy.fromfile(f,dtype=numpy.dtype('uint64'),count=1) buf = numpy.fromfile(f,dtype=numpy.dtype('float32'),count=size/sz) version = numpy.fromfile(f,dtype=numpy.dtype('uint32'),count=1) if version != 0x00000001: raise RuntimeError("Incorrect matrix version number") num_dim = numpy.fromfile(f,dtype=numpy.dtype('int32'),count=1) stride = numpy.fromfile(f,dtype=numpy.dtype('int32'),count=num_dim)*sz offset = numpy.fromfile(f,dtype=numpy.dtype('int32'),count=1)*sz matrix_size = numpy.fromfile(f,dtype=numpy.dtype('int32'),count=num_dim) total_size = numpy.fromfile(f,dtype=numpy.dtype('int32'),count=1) last_raw_pos = numpy.fromfile(f,dtype=numpy.dtype('int32'),count=1) major_order = numpy.fromfile(f,dtype=numpy.dtype('int32'),count=1) transposed = numpy.fromfile(f,dtype=numpy.dtype('int8'),count=1) return numpy.ndarray(shape = tuple(matrix_size), strides = tuple(stride), dtype = numpy.dtype('float32'), buffer = buf, offset = offset, order = 'C' if (major_order == 0) else 'F') april-ann-0.4.1/tools/gnuplot.lua000066400000000000000000000217241263004425400167360ustar00rootroot00000000000000local gnuplot = {} -- module gnuplot --------------- GNUPLOT OBJECT METHODS --------------------- local gnuplot_methods = {} ----------------------- -- PRIVATE FUNCTIONS -- ----------------------- -- Writes using format and a list of arguments local function writef(self,format, ...) if self.verbosity_level > 0 then io.write(format:format(...)) end self.in_pipe:write(string.format(format,...)) return self end -- Writes the given strings (separated by blanks) local function write(self,...) if self.verbosity_level > 0 then io.write(table.concat(table.pack(...), " ")) end self.in_pipe:write(table.concat(table.pack(...), " ")) return self end local function read(output,value,format) local format = format or "%s" if not value then return "" end return string.format("%s "..format, output, tostring(value)) end -------------------- -- PUBLIC METHODS -- -------------------- -- Writes a line using format and a list of arguments function gnuplot_methods:writeln(format, ...) writef(self,format,...) write(self,"\n") self:flush() return self end -- Sets a parameter function gnuplot_methods:set(...) write(self,"set ") write(self,table.concat(table.pack(...), " ")) write(self,"\n") self:flush() return self end -- Unsets a parameter function gnuplot_methods:unset(...) write(self,"unset ") write(self,table.concat(table.pack(...), " ")) write(self,"\n") self:flush() return self end -- Forces to write in the pipe function gnuplot_methods:flush() self.in_pipe:flush() return self end -- -- Plots (or multiplots) a given table with gnuplot parameters -- function gnuplot_methods:plot(params, range) -- -- remove previous temporal files -- for _,tmpname in pairs(self.tmpnames) do -- self:writeln(string.format("!rm -f %s", tmpname)) -- end -- self.tmpnames = {} -- local plot_str_tbl = {} -- if range then -- table.insert(plot_str_tbl, string.format("plot%s", range)) -- else -- table.insert(plot_str_tbl, "plot") -- end -- local tmpnames = self.tmpnames -- if not params[1] then params = { params } end -- for i,current in ipairs(params) do -- local data = current.data -- local func = current.func -- assert(data or func, "Field data or func is mandatory") -- local using = read("u", current.using or current.u) -- local title = read("title",current.title or current.t,"%q") -- local notitle = read("notitle",current.notitle,"") -- local with = read("w",current.with or current.w) -- local other = current.other or "" -- assert(type(other) == "string") -- if type(data) == "matrix" or type(data) == "matrixDouble" then -- local aux_tmpname = tmpnames[data] -- if not aux_tmpname then -- assert(data.toTabFilename, -- "The matrix object needs the method toTabFilename") -- aux_tmpname = os.tmpname() -- tmpnames[data] = aux_tmpname -- data:toTabFilename(aux_tmpname) -- end -- data = aux_tmpname -- end -- if data then -- if #data > 0 and string.sub(data,1,1) ~= "<" then -- local f = assert(io.open(data), "Unable to open filename " .. data) -- f:close() -- end -- data = string.format("%q", data) -- end -- table.insert(plot_str_tbl, -- string.format("%s %s %s %s %s", -- data or func, using, with, title, other)) -- if i ~= #params then table.insert(plot_str_tbl, ",") end -- end -- table.insert(plot_str_tbl, "\n") -- -- print(table.concat(plot_str_tbl, " ")) -- write(self,table.concat(plot_str_tbl, " ")) -- self:flush() -- return self -- end local function plot(self, command, line, ...) assert(type(line) == "string", "New plot needs line string as first argument and varargs in the rest") local data = table.pack(...) -- remove previous temporal files for _,tmpname in pairs(self.tmpnames) do self:writeln(string.format("!rm -f %s", tmpname)) end self.tmpnames = {} local tmpnames = self.tmpnames local dict = {} for i,m in ipairs(data) do local aux_tmpname = tmpnames[m] if not aux_tmpname then if class.is_a(m, data_frame) then aux_tmpname = os.tmpname() tmpnames[m] = aux_tmpname m:to_csv(aux_tmpname, { header=false, sep=' ', NA="NA" }) elseif type(m):find("^matrix") then assert(m.toTabFilename, "The matrix object needs the method toTabFilename") aux_tmpname = os.tmpname() tmpnames[m] = aux_tmpname m:toTabFilename(aux_tmpname) else local tt = type(m) if tt == "number" or tt == "string" then aux_tmpname = tostring(m) else error("Unexpected data type at position: " .. i) end end end dict["#"..i] = aux_tmpname end local line = line:gsub("(#%d*)",dict) -- print(line) self:writeln(command .. line) self:flush() return self end function gnuplot_methods:p(...) return plot(self, "", ...) end -- Plots (or multiplots) a given table with gnuplot parameters function gnuplot_methods:plot(line, ...) assert(not line:find("^[%s]*plot[%s]*"), "plot doesn't need 'plot' word in the given line string") return plot(self, "plot ", line, ...) end -- Plots (or multiplots) a given table with gnuplot parameters function gnuplot_methods:splot(line, ...) assert(not line:find("^[%s]*plot[%s]*"), "splot doesn't need 'plot' word in the given line string") return plot(self, "splot ", line, ...) end -- Closes the gnuplot pipe (interface) function gnuplot_methods:close() -- remove previous temporal files for _,tmpname in pairs(self.tmpnames) do self:writeln(string.format("!rm -f %s", tmpname)) end self.in_pipe:close() self.in_pipe = nil end function gnuplot_methods:verbosity(v) self.verbosity_level = v end --------------- -- METATABLE -- --------------- ------ METATABLE OF THE OBJECTS -------- local object_metatable = {} object_metatable.__index = gnuplot_methods object_metatable.__call = gnuplot_methods.p function object_metatable:__gc() self:close() end ----------------- -- CONSTRUCTOR -- ----------------- -- builds an instance for interfacing with gnuplot function gnuplot.new() local f = io.popen("which gnuplot") local command = f:read("*l") f:close() assert(command, "Impossible to find gnuplot binary executable") local in_pipe= io.popen(command, "w") local obj = { in_pipe = in_pipe, tmpnames = {}, verbosity_level=0 } setmetatable(obj, object_metatable) return obj end -- gnuplot() is equivalent to gnuplot.new() setmetatable(gnuplot, { __call = gnuplot.new }) do local singleton for k,v in pairs(gnuplot_methods) do assert(not gnuplot[k]) gnuplot[k] = function(...) singleton = singleton or gnuplot.new() return singleton[k](singleton, ...) end end end ------------------- -- HELP FUNCTION -- ------------------- function gnuplot.help() print[[ Help of module 'gnuplot'. This module is a wrap around gnuplot command, allowing to make drawings of matrix objects (not lua tables), filenames or gnuplot functions (expressions). The module allow to declare as many gnuplot objects as you need, none of them will share anything, so every object has its own gnuplot window. LOADING: load the module as usual > gp = require "gnuplot" CONSTRUCTOR: builds a gnuplot object instance > gp = gnuplot() -- the __call metamethod is defined > gp = gnuplot.new() -- both are equivalent HELP: shows this help message > gnuplot.help() METHOD __call: idem as below METHOD WRITE LINE: writes a sentence line to gnuplot arguments: format: is a string with a printf format string ... : is a variable argument list > gp(format, ...) > gp:writeln(format, ...) METHOD SET: executes the set command of gnuplot arguments: ... : a variable argument list, all of them strings > gp:set("format x '%20f'") > gp:set("xrange [-10,10]") METHOD UNSET: executes the unset command of gnuplot arguments: ... : a variable argument list, all of them strings > gp:unset("logscale y") METHOD PLOT: allows to do generic plots, it uses placeholders #n to use matrix objects as input. arguments: line string: a string with the gnuplot line (without the word 'plot') ...: vararg with matrix objects to be plotted > gp:plot("'#1' u 3:4 w l lw 3", matrix_object) -- #1 is the placeholder > gp:plot("3*x**2") > gp:plot("'tmp.log' u 1:2 w l, '#1' u 1:2 w l, '' u 1:3 w l", m) METHOD SPLOT: same as plot but using splot instead of plot command in gnuplot METHOD P: similar to plot and splot, but not giving the 'plot' command > gp:p("plot '#1' u 3:4 w l lw 3", matrix_object) -- #1 is the placeholder > gp:p("plot 3*x**2") > gp:p("plot 'tmp.log' u 1:2 w l, '#1' u 1:2 w l, '' u 1:3 w l", m) METHOD FLUSH: flushes all the pending data (normally it is not necessary) > gp:flush() METHOD CLOSE: closes the connection with gnuplot > gp:close() SINGLETON: it is possible to use gnuplot without calling the constructor, all methods are available as static functions. > gp.close() > gp.rawplot(...) > gp.set(...) > ... ]] end return gnuplot april-ann-0.4.1/tools/lgi/000077500000000000000000000000001263004425400153105ustar00rootroot00000000000000april-ann-0.4.1/tools/lgi/gtk.lua000066400000000000000000000046661263004425400166140ustar00rootroot00000000000000-- module gtk local gtk = {} local lgi = require "lgi" local Gtk = lgi.Gtk local GdkPixbuf = lgi.GdkPixbuf function gtk.show(...) local windows = {} for i=1,select('#',...) do local param = select(i,...) local gtk_image = nil local tmp_file = nil if type(param) ~= "string" then local img = nil if type(param) == "Image" or type(param) == "ImageRGB" then img = param elseif type(param) == "matrix" then if #param:dim() == 2 then img = Image(param) else img = ImageRGB(param) end else error("Not supported data type: " .. type(param)) end tmp_file = os.tmpname() ImageIO.write(img, tmp_file, 'png') param = tmp_file end local sx,sy = 1,1 local pixbuf = GdkPixbuf.Pixbuf.new_from_file(param) local window = Gtk.Window { title = 'Prueba', Gtk.Box { id = 'vbox', orientation = 'VERTICAL', spacing = 8, border_width = 8, Gtk.Box { id = 'top', orientation = 'HORIZONTAL', spacing = 8, border_width = 8, Gtk.Button { id = 'fit', label = 'fit', }, Gtk.Box { orientation = 'VERTICAL', Gtk.Button { id = 'zoomIN', label = '+', }, Gtk.Button { id = 'zoomOUT', label = '-', }, }, Gtk.Button { id = 'exit', label = 'exit', }, }, Gtk.Frame { shadow_type = 'IN', halign = 'CENTER', valign = 'CENTER', Gtk.Image { id='image', pixbuf=pixbuf }, }, }, } local function scale() local scaled_pixbuf = pixbuf:scale_simple(pixbuf.width * sx, pixbuf.height * sy, 'BILINEAR') window.child.image.pixbuf = scaled_pixbuf window.child.image:queue_draw() collectgarbage("collect") end function window.child.exit:on_pressed() for i=1,#windows do windows[i]:hide() end Gtk.main_quit() end function window.child.fit:on_pressed() local w,h = window.width-40,window.height - window.child.top.height - 50 local ratio = pixbuf.height/pixbuf.width if w*ratio > h then sy=h/pixbuf.height sx=sy else sx=w/pixbuf.width sx=sy end scale() end function window.child.zoomIN:on_pressed() sx,sy = sx*1.1,sy*1.1 scale() end function window.child.zoomOUT:on_pressed() sx,sy = sx*0.9,sy*0.9 scale() end window:show_all() table.insert(windows, window) if tmp_file then os.remove(tmp_file) end end Gtk.main() end return gtk april-ann-0.4.1/tools/nbest/000077500000000000000000000000001263004425400156505ustar00rootroot00000000000000april-ann-0.4.1/tools/nbest/add_feature.lua000066400000000000000000000015101263004425400206130ustar00rootroot00000000000000featuresfilename = arg[1] f = {} for i=2,#arg do f[i-1] = io.open(arg[i], "r") end -- leemos las features features = {} local n = 1 local fbegin = "FEATURES_TXT_BEGIN" local fend = "FEATURES_TXT_END" featsf=io.open(featuresfilename) for line in featsf:lines() do if string.sub(line, 1, #fbegin) == fbegin then features[n] = {} local t = string.tokenize(line) printf("%s %s %s %d %s", t[1], t[2], t[3], tonumber(t[4])+#arg-1, table.concat(t, " ", 5, #t)) for i=1,#f do printf(" FEAT%d", i) end printf("\n") elseif string.sub(line, 1, #fend) == fend then n = n + 1 printf("%s", line) for i=1,#f do printf(" FEAT%d", i) end printf("\n") else printf("%s", line) for i=1,#f do printf(" " .. f[i]:read("*l")) end printf("\n") end end featsf:close() for i=1,#f do f[i]:close() end april-ann-0.4.1/tools/nbest/compute_a_posterioris.lua000066400000000000000000000054021263004425400227720ustar00rootroot00000000000000opt = cmdOpt{ program_name = string.basename(arg[0]), argument_description = "", main_description = "A posterioris computation in April toolkit", { index_name="t", description="NBest target file", short="t", argument="yes", }, { index_name="l", description="L0 value (default 1, in HTR/ASR inverse of GSF)", short="l", argument="yes", }, { index_name="k", description="Use only first k-best", short="k", argument="yes", }, { index_name="e", description="Show prob instead of logprob (defauly no)", short="e", argument="yes", }, { description = "shows this help message", short = "h", long = "help", argument = "no", action = function (argument) print(opt:generate_help()) os.exit(1) end } } optargs = opt:parse_args() if type(optargs) == "string" then error(optargs) end nbest = optargs.t or error ("Needs a NBest file") lambda0 = tonumber(optargs.l or 1.0) maxk = tonumber(optargs.k or -1) doexp = optargs.e function logAdd(a, b) if a>b then return a + math.log(1 + math.exp(b-a)) else return b + math.log(1 + math.exp(a-b)) end end id2voc = {} voc2id = {} nextid = 1 f = io.open(nbest, "r") data = {} uniq = {} sum = 0 currentn = 0 next_sentence_id = 1 while true do local line = f:read("*l") local n,sentence,feats,score n = -1 if line then n,sentence,feats,score = string.match(line, "(.*)|||(.*)|||(.*)|||(.*)") n = tonumber(n) score = tonumber(score) sentence = table.concat(string.tokenize(sentence), " ") end if n ~= currentn then -- Compute posteriors for i=1,#data do data[i].posterior = data[i].score - sum end table.sort(data, function(a,b) return a.posterior > b.posterior end) -- Print sentences for j=1,#data do if doexp == "yes" then data[j].posterior=math.exp(data[j].posterior) end printf("%d ||| %s ||| %g\n", currentn, data[j].sentence, data[j].posterior) end io.stdout:flush() io.stderr:flush() -- RESET, hemos terminado con esta lista data = {} uniq = {} next_sentence_id = 1 currentn = n sum = 0 collectgarbage("collect") end if line then if maxk == -1 or #data < maxk then local id = uniq[sentence] if not id then id = next_sentence_id uniq[sentence] = next_sentence_id next_sentence_id = next_sentence_id + 1 end -- para ajustar la escala local v = score*lambda0 -- sum for posteriors sum = logAdd(sum, v) if not data[id] then data[id] = {} data[id].score = v data[id].sentence = sentence else data[id].score=logAdd(data[id].score,v) end end else break end end april-ann-0.4.1/tools/nbest/compute_deterministic_bunch_lm_score.lua000066400000000000000000000067141263004425400260240ustar00rootroot00000000000000if #arg < 3 or #arg > 6 then print("Syntax:") printf ("\t%s nbestfile lm vocab [use_bcc=yes use_ecc=yes cache_extra_set=nil]\n", string.basename(arg[0])) os.exit(128) end nbestfile = arg[1] lm_file = arg[2] voc_filename = arg[3] --trie_size = tonumber(arg[4] or 24) use_bcc = ((arg[4] or "yes") == "yes") use_ecc = ((arg[5] or "yes") == "yes") cache_extra_set = arg[6] unk_word = "" begin_word = "" end_word = "" stop_word = "" null_word = "" -------------------------------------------------- vocab = lexClass.load(io.open(voc_filename)) words = vocab:getWordVocabulary() inv_words = table.invert(words) unk_id = vocab:getWordId(unk_word) ------------------------------------------------------------------------ collectgarbage("collect") lm1 = language_models.load(lm_file, vocab, begin_word, end_word) local lm = ngram.lira.bunch_hashed_model{ lira_model = lm1, bunch_size = 4, } local lmi = lm:get_interface() collectgarbage("collect") --use_cache = lm:has_cache() ------------------------------------- GO! time=util.stopwatch() time:go() local scores = {} local j=1 local prevn = nil --lm:restart() --cachef = nil --if cache_extra_set then -- cachef = io.open(cache_extra_set, "r") --end --local last_best_line = nil assert(lm:is_deterministic(), "Error: Expected a deterministic LM") nbestf = io.open(nbestfile, "r") while true do local line = nbestf:read("*l") local n if line then n = tonumber(string.match(line, "(.*)|||.*|||.*|||")) + 1 end if not prevn then prevn = n last_best_line = line end if not line or n ~= prevn then --[[ if cachef then local line = cachef:read("*l") local words = string.tokenize(line) for i=1,#words do if words[i] == stop_word then lm:clearCache() elseif words[i] ~= null_word then local w = dictionary:getWordId(words[i]) or dictionary:getWordId(unk_word) ngram_model:cacheWord(w) end end end --]] result = lmi:get_queries() for i=1,#result do k,p,b = result:get(i) scores[b]= scores[b] + p end lmi:clear_queries() print(table.concat(scores, "\n")) scores = {} prevn = n --[[ if use_cache or n and math.mod(n, 100) == 99 then lm:restart() end if use_cache and last_best_line then local words = string.tokenize(string.match(last_best_line, "|||(.*)|||.*|||")) local wids = vocab:searchWordIdSequence(words, vocab:getWordId(unk_word)) for i=1,#wids do lm:cacheWord(wids[i]) end end --]] last_best_line = line end if not line then break end line = string.match(line, "|||(.*)|||.*|||") local words = string.tokenize(line) local wids = vocab:searchWordIdSequence(words, vocab:getWordId(unk_word)) table.insert(scores, 0) local key if use_bcc then key = lmi:get_initial_key() else key = lmi:get_zero_key() end for wpos=1,#wids do local w = wids[wpos] lmi:insert_query(key, w, { id_key = #scores}) result = lmi:next_keys(key, w) assert(#result == 1) key = result:get(1) end if use_ecc then local w = vocab:getWordId(end_word) lmi:insert_query(key, w, { id_key = #scores }) end j=j+1 if math.modf(j, 250) == 0 then collectgarbage("collect") end end nbestf:close() time:stop() a,b=time:read() fprintf(io.stderr, "TIME: cpu %f (wall %f)\n", a, b) april-ann-0.4.1/tools/nbest/compute_deterministic_lm_score.lua000066400000000000000000000067661263004425400246540ustar00rootroot00000000000000if #arg < 3 or #arg > 6 then print("Syntax:") printf ("\t%s nbestfile lm vocab [use_bcc=yes use_ecc=yes cache_extra_set=nil]\n", string.basename(arg[0])) os.exit(128) end local nbestfile = arg[1] local lm_file = arg[2] local voc_filename = arg[3] --local trie_size = tonumber(arg[4] or 24) local use_bcc = ((arg[4] or "yes") == "yes") local use_ecc = ((arg[5] or "yes") == "yes") local cache_extra_set = arg[6] local unk_word = "" local begin_word = "" local end_word = "" local stop_word = "" local null_word = "" -------------------------------------------------- local vocab = lexClass.load(io.open(voc_filename)) local words = vocab:getWordVocabulary() local inv_words = table.invert(words) local unk_id = vocab:getWordId(unk_word) ------------------------------------------------------------------------ collectgarbage("collect") local lm = language_models.load(lm_file, vocab, begin_word, end_word) local lmi = lm:get_interface() collectgarbage("collect") --use_cache = lm:has_cache() ------------------------------------- GO! local time=util.stopwatch() time:go() local scores = {} local j=1 local prevn = nil --lm:restart() --cachef = nil --if cache_extra_set then -- cachef = io.open(cache_extra_set, "r") --end local last_best_line = nil assert(lm:is_deterministic(), "Error: Expected a deterministic LM") local nbestf = io.open(nbestfile, "r") while true do local line = nbestf:read("*l") local n if line then n = tonumber(string.match(line, "(.*)|||.*|||.*|||")) + 1 end if not prevn then prevn = n last_best_line = line end if not line or n ~= prevn then --[[ if cachef then local line = cachef:read("*l") local words = string.tokenize(line) for i=1,#words do if words[i] == stop_word then lm:clearCache() elseif words[i] ~= null_word then local w = dictionary:getWordId(words[i]) or dictionary:getWordId(unk_word) ngram_model:cacheWord(w) end end end --]] local result = lmi:get_queries() for i=1,#result do local k,p,b = result:get(i) scores[b]= scores[b] + p end lmi:clear_queries() print(table.concat(scores, "\n")) scores = {} prevn = n --[[ if use_cache or n and math.mod(n, 100) == 99 then lm:restart() end if use_cache and last_best_line then local words = string.tokenize(string.match(last_best_line, "|||(.*)|||.*|||")) local wids = vocab:searchWordIdSequence(words, vocab:getWordId(unk_word)) for i=1,#wids do lm:cacheWord(wids[i]) end end --]] last_best_line = line end if not line then break end line = string.match(line, "|||(.*)|||.*|||") local words = string.tokenize(line) local wids = vocab:searchWordIdSequence(words, vocab:getWordId(unk_word)) table.insert(scores, 0) local key if use_bcc then key = lmi:get_initial_key() else key = lmi:get_zero_key() end for wpos=1,#wids do local w = wids[wpos] lmi:insert_query(key, w, { id_key = #scores}) result = lmi:next_keys(key, w) assert(#result == 1) key = result:get(1) end if use_ecc then local w = vocab:getWordId(end_word) lmi:insert_query(key, w, { id_key = #scores }) end j=j+1 if math.modf(j, 250) == 0 then collectgarbage("collect") end end nbestf:close() time:stop() local a,b=time:read() fprintf(io.stderr, "TIME: cpu %f (wall %f)\n", a, b) april-ann-0.4.1/tools/nbest/compute_errors.lua000066400000000000000000000236161263004425400214330ustar00rootroot00000000000000scores = arg[1] objfunc = arg[2] num_rep = tonumber(arg[3] or 0) baseline = arg[4] maxnbest = arg[5] confidence = tonumber(arg[6] or 0.95) if maxnbest then maxnbest = tonumber(maxnbest) end results = {} sizes = {} nscores = 0 score_func = nil if objfunc == "WER" then -- the scores order is: Acc Sub Ins Del score_func = function(data) return (data[2]+data[3]+data[4]) / (data[1]+data[2]+data[4]) end nscores = 4 elseif objfunc == "TER" then -- the scores order is: Errors / Length score_func = function(data) return data[1] / data[2] end nscores = 2 elseif objfunc == "BLEU" then -- the scores order is: 1gr TGT-1gr 2gr TGT-2gr 3gr TGT-3gr 4gr TGT-4gr 1gr-REF score_func = function(data) local logBP = 0 if data[2] <= data[9] then logBP = 1 - data[9] / data[2] end local b1 = math.log(data[1]) - math.log(data[2]) local b2 = math.log(data[3]) - math.log(data[4]) local b3 = math.log(data[5]) - math.log(data[6]) local b4 = math.log(data[7]) - math.log(data[8]) local logBLEU = (b1 + b2 + b3 + b4)/4 + logBP if data[1] == 0 or data[3] == 0 or data[5] == 0 or data[7] == 0 then return 1 end return 1 - math.exp(logBLEU) end nscores = 9 else error ("Incorrect objective function: " .. objfunc) end fprintf(io.stderr, "Loading data and errors\n") -- this function loads the scores of each sentence from Nbest lists, keeping the -- best set of scores for the given objective function function load_data(filename) local f = io.open(filename, "r") or error("File not found: " .. filename) local sentences_data = {} local results = {} local sizes = {} local n = 1 while true do local line = f:read("*l") if not line then break end local begin_line = string.tokenize(line) assert(begin_line[1] == "SCORES_TXT_BEGIN_0", "Incorrect scores file, header error: '%s'", begin_line[1]) assert(tonumber(begin_line[4]) == nscores, "Incorrect number of scores") local size = tonumber(begin_line[3]) local best = nil local bestdata = nil sentences_data[n] = sentences_data[n] or {} for i=1,size do local data = string.tokenize(f:read("*l")) if not maxnbest or i <= maxnbest then for i=1,#data do data[i] = tonumber(data[i]) end local sc = score_func(data) if not best or sc < best then best = sc bestdata = data end results[i] = results[i] or {} table.insert(results[i], bestdata) sizes[i] = (sizes[i] or 0) + 1 table.insert(sentences_data[n], bestdata) end end n = n + 1 local end_line = f:read("*l") assert(end_line == "SCORES_TXT_END_0", "Incorrect scores file, footer error: '%s'", end_line) end return results, sentences_data, sizes end -- this function receives a sorted list of points and computes the confidence -- interval function compute_confidence_interval(points, confidence) local ic,size = (1 - confidence) / 2, #points local pos = math.round(ic * size) local a,b = points[pos+1],points[size-pos+1] local median = math.median(points) return { median, (b-a)/2 } end function overlapped(a1,b1,a2,b2) if a1 < a2 and b1 < a2 then return false end if a2 < a1 and b2 < a1 then return false end return true end -- this function receives pair of sorted point lists and computes the -- confidence for which the intervals are not overlapped function compute_significance(p1, p2) local p2 = p2 or map(function() return 0 end, ipairs(p1)) assert(#p1 == #p2, "Incorrect list sizes") local median_pos = math.round(#p1/2) local sz = #p1 for i=1,median_pos-1 do local a1,b1 = p1[i],p1[sz-i+1] local a2,b2 = p2[i],p2[sz-i+1] if not overlapped(a1,b1,a2,b2) then return (sz - i*2) / sz end end return 0.0 end -- cargamos los datos del target results,sentences_data,sizes = load_data(scores) if baseline then -- y del baseline en caso de ser necesario baseline_results,baseline_sentences_data,baseline_sizes = load_data(baseline) end -- compute confidence interval fprintf(io.stderr, "Computing confidence interval\n") -- para cosas aleatorias rnd=random(os.time()) -- tendra el intervalo de confianza del target local intervals = {} -- tendra el intervalo de confianza del baseline local baseline_intervals = {} -- pairwise en forma de PUNTOS de mejora + intervalo local pairwise = {} local pairwise_significance = {} -- pairwise en forma de PROB de ser mejor a nivel de frase + intervalo local comparison_probs = {} -- pairwise en forma de PROB de ser mejor a nivel del conjunto local total_probs = {} -- este es para mostrar el tiempo que queda por pantalla local cronometro = util.stopwatch() cronometro:go() -- para cada repeticion for n=1,num_rep do -- variables auxiliares local aux = {} local baseline_aux = {} local probs = {} local nums = #sentences_data -- para el tamanyo de la muestra for i=1,nums do -- sacamos una frase al azar local rand_i = rnd:randInt(1, nums) -- para cada N de la lista de NBest for j=1,#sentences_data[rand_i] do aux[j] = aux[j] or {} -- para cada componente for k=1,#sentences_data[rand_i][j] do -- sumamos los scores de la funcion de error correspondiente a esa -- frase, y para cada N de la lista de NBest aux[j][k] = (aux[j][k] or 0) + sentences_data[rand_i][j][k] end -- calculamos la probabilidad de que sea mejor a nivel de frase if baseline and baseline_sentences_data[rand_i] and baseline_sentences_data[rand_i][j] then probs[j] = probs[j] or 0 if score_func(sentences_data[rand_i][j]) < score_func(baseline_sentences_data[rand_i][j]) then -- sumamos uno cuando es mejor probs[j] = (probs[j] or 0) + 1 end end end if baseline then -- sumamos los scores del baseline para la funcion de error y esta frase for j=1,#baseline_sentences_data[rand_i] do baseline_aux[j] = baseline_aux[j] or {} for k=1,#baseline_sentences_data[rand_i][j] do baseline_aux[j][k] = (baseline_aux[j][k] or 0) + baseline_sentences_data[rand_i][j][k] end end end end -- calculamos los intervalos y el pairwise for i=1,#aux do local r = score_func(aux[i]) intervals[i] = intervals[i] or {} table.insert(intervals[i], r) if baseline then if baseline_aux[i] then local base_r = score_func(baseline_aux[i]) -- pairwise pairwise[i] = pairwise[i] or {} table.insert(pairwise[i], base_r - r) total_probs[i] = total_probs[i] or 0 if base_r - r > 0 then -- calculamos la probabilidad de ser mejor a nivel de muestra total_probs[i] = total_probs[i] + 1 end end end end if baseline then -- calculamos los intervalos y probabilidades del baseline for i=1,#baseline_aux do -- probabilidad a nivel de frase en esta muestra probs[i] = probs[i] / math.min(sizes[i], baseline_sizes[i]) comparison_probs[i] = comparison_probs[i] or {} table.insert(comparison_probs[i], probs[i]) -- resultado en esta muestra local r = score_func(baseline_aux[i]) baseline_intervals[i] = baseline_intervals[i] or {} table.insert(baseline_intervals[i], r) end end -- tiempo estimado fprintf(io.stderr, "\rElapsed time: %6d seconds, ETA: %6d seconds", cronometro:read(), cronometro:read()/n * (num_rep-n) ) io.stderr:flush() end local ic = (1 - confidence) / 2 -- calcula los intervalos a partir de las repeticiones fprintf(io.stderr, "\nSorting intervals\n") for i=1,#intervals do table.sort(intervals[i], function(a,b) return a < b end) end if baseline then -- lo mismo para el baseline y los diferentes scores de pairwise for i=1,#total_probs do total_probs[i] = total_probs[i] / num_rep end for i=1,#baseline_intervals do table.sort(baseline_intervals[i], function(a,b) return a < b end) end fprintf(io.stderr, "\nSorting pairwise\n") for i=1,#pairwise do table.sort(pairwise[i], function(a,b) return a < b end) pairwise_significance[i] = compute_significance(pairwise[i]) pairwise[i] = compute_confidence_interval(pairwise[i], confidence) end for i=1,#comparison_probs do table.sort(comparison_probs[i], function(a,b) return a < b end) comparison_probs[i] = compute_confidence_interval(comparison_probs[i], confidence) end end -- mostramos por pantalla fprintf(io.stderr, "Computing errors\n") print("# N SCORE SCORE-MEDIAN INT BASE BASE-MEDIAN INT PAIRWISE PROBS-SENTENCE PROBS-CORPUS :: SIGNIFICANCE PWSIGNIFICANCE") for i=1,#results do -- for each Nbest local data = {} for j=1,#results[i] do -- for each repetition for k=1,#results[i][j] do -- for each score data[k] = (data[k] or 0) + results[i][j][k] end end if baseline then significance = compute_significance(intervals[i], baseline_intervals[i]) baseline_intervals[i] = compute_confidence_interval(baseline_intervals[i], confidence) end intervals[i] = compute_confidence_interval(intervals[i], confidence) local r = score_func(data) local r2 = (intervals[i] or {0,0})[1] if objfunc == "BLEU" then r = 1 - r r2 = 1 - r2 end printf("%d\t%8.4f %8.4f %8.4f", i, r*100, r2*100, (intervals[i] or {0,0})[2]*100) if baseline then local data = {} for j=1,#baseline_results[i] do for k=1,#baseline_results[i][j] do data[k] = (data[k] or 0) + baseline_results[i][j][k] end end local r = score_func(data) local r2 = (baseline_intervals[i] or {0,0})[1] local p = (pairwise[i] or {0,0})[1] if objfunc == "BLEU" then r = 1 - r r2 = 1 - r2 end printf(" bs: % -10g % -10g % -10g", r*100, r2*100, (baseline_intervals[i] or {0,0})[2]*100) printf(" pw: % -10g % -10g", p*100, (pairwise[i] or {0,0})[2]*100) printf(" p: % -10g % -10g", (comparison_probs[i] or {0,0})[1]*100, (comparison_probs[i] or {0,0})[2]*100) printf(" pW: % -10g", total_probs[i]*100) printf(" 1-p-value: % -10g", significance) printf(" 1-pw-value: % -10g", pairwise_significance[i]) end printf("\n") end april-ann-0.4.1/tools/nbest/compute_errors.sh000077500000000000000000000056321263004425400212650ustar00rootroot00000000000000#!/bin/bash refs=$1 nbest=$2 score=$3 numreps=$4 baseline=$5 maxnbest=$6 confidence=$7 # by default 0.95 april_tools=$APRIL_TOOLS_DIR april=$APRIL_EXEC refs2=`mktemp /tmp/april_XXXXXXX` refs3=`mktemp /tmp/april_XXXXXXX` cp $refs $refs2 zcat $refs2 > $refs3 || cat $refs2 > $refs3 refs=$refs3 nbest2=`mktemp /tmp/april_XXXXXXX` zcat $nbest > $nbest2 || cat $nbest > $nbest2 nbest=$nbest2 if [ ! -z $baseline ]; then baseline2=`mktemp /tmp/april_XXXXXXX` baseline3=`mktemp /tmp/april_XXXXXXX` cp $baseline $baseline2 zcat $baseline2 > $baseline3 || cat $baseline2 > $baseline3 baseline=$baseline3 fi scores=`mktemp /tmp/april_XXXXXXX` feats=`mktemp /tmp/april_XXXXXXX` scores2=`mktemp /tmp/april_XXXXXXX` feats2=`mktemp /tmp/april_XXXXXXX` if [ $score = "WER" ]; then scorer="$april $april_tools/HMM_ANN/evaluation/extract_WER_weights.lua" $scorer -r $refs -S $scores -F $feats -n $nbest || exit if [ ! -z $baseline ]; then $scorer -r $refs -S $scores2 -F $feats2 -n $baseline || exit fi elif [ $score = "CER" ]; then scorer="$april $april_tools/HMM_ANN/evaluation/extract_WER_weights.lua -t CER" $scorer -r $refs -S $scores -F $feats -n $nbest || exit if [ ! -z $baseline ]; then $scorer -r $refs -S $scores2 -F $feats2 -n $baseline || exit fi score="WER" elif [ $score = "SER" ]; then scorer="$april $april_tools/HMM_ANN/evaluation/extract_WER_weights.lua -t SER" $scorer -r $refs -S $scores -F $feats -n $nbest || exit if [ ! -z $baseline ]; then scores2=`mktemp /tmp/april_XXXXXXX` feats2=`mktemp /tmp/april_XXXXXXX` $scorer -r $refs -S $scores2 -F $feats2 -n $baseline || exit fi score="WER" elif [ $score = "TER" ]; then echo "NOT IMPLEMENTED" exit -1 scorer="$april_tools/MT/compute_TER.sh" $scorer $refs $nbest $scores || exit $april $april_tools/MT/add_head_to_scorer_from_nbest.lua $scores $nbest > $scores.2 mv -f $scores.2 $scores if [ ! -z $baseline ]; then scores2=`mktemp /tmp/april_XXXXXXX` feats2=`mktemp /tmp/april_XXXXXXX` $scorer $refs $baseline $scores2 || exit $april $april_tools/MT/add_head_to_scorer_from_nbest.lua $scores2 $baseline > $scores.2 mv -f $scores.2 $scores2 fi elif [ $score = "BLEU" ]; then echo "NOT IMPLEMENTED" exit -1 scorer="$tools/bin/extractor" $scorer -r $refs \ --scconfig "reflen:closest" \ -S $scores \ -F $feats \ -n $nbest || exit if [ ! -z $baseline ]; then scores2=`mktemp /tmp/april_XXXXXXX` feats2=`mktemp /tmp/april_XXXXXXX` $scorer -r $refs \ --scconfig "reflen:closest" \ -S $scores2 \ -F $feats2 \ -n $baseline || exit fi else echo "Invalid score type: $score" exit fi echo "# $@" ($april $april_tools/NBEST/compute_errors.lua $scores $score $numreps $scores2 $maxnbest $confidence && rm -f $scores $feats $scores2 $refs2 $nbest2 $baseline2 $baseline3 $refs3) || echo $scores $scores2 > /dev/stderr april-ann-0.4.1/tools/nbest/convert_nbest_to_sri_format.lua000066400000000000000000000015241263004425400241570ustar00rootroot00000000000000fprintf(io.stderr,"# CMD: "..table.concat(arg, " ").."\n") nbestfilename = arg[1] outdir = arg[2] os.execute("mkdir -p " .. outdir) nbestf = io.open(nbestfilename, "r") local i = 1 local prevn = nil local outf = "" log10_cte = 1.0/math.log(10) for line in nbestf:lines() do local n,sentence,probs,score = string.match(line, "(.*)|||(.*)|||(.*)|||%s*(.*)%s*") probs = string.tokenize(probs, " ") if i % 1000 == 0 then collectgarbage("collect") end i = i + 1 if tonumber(n) ~= tonumber(prevn) then printf("%d\n", n) prevn=n outf = io.open(outdir .. string.format("/nbest_%06d.score.gz",n), "w") --outf:write("NBestList1.0\n") end --fprintf(outf, "(%s) %s\n", score, sentence) for i=1,#probs do fprintf(outf, "%f ", tonumber(probs[i]) * log10_cte) end fprintf(outf, "%s\n", sentence) end outf:close() april-ann-0.4.1/tools/nbest/extract_features.lua000066400000000000000000000037151263004425400217310ustar00rootroot00000000000000opt = cmdOpt{ program_name = string.basename(arg[0]), argument_description = "", main_description = "NBest feature extractor", { index_name="nbest", description="Nbest lists.", short="n", argument="yes", }, { index_name="feats", description="Output features.", short="F", argument="yes", }, { index_name="filter", description="Lua filter (post-process).", short="f", argument="yes", }, { description = "shows this help message", short = "h", long = "help", argument = "no", action = function (argument) print(opt:generate_help()) os.exit(1) end } } optargs = opt:parse_args(args) if not optargs.nbest then error("Needs a target nbest file!!!") end if optargs.filter then filter = dofile(optargs.filter) else filter = function (str) return str end end local currentn = 0 local correcta local nbestf = io.open(optargs.nbest) features = {} featsf = io.open(optargs.feats, "w") local kk = 0 while true do nbest_line=nbestf:read("*l") if nbest_line then n,reconocida,f,p = string.match(nbest_line, "(.*)|||(.*)|||(.*)|||(.*)") if n == nil then reconocida = nbest_line f = "0" p = "0" n = kk kk = kk + 1 end end if not nbest_line or tonumber(n) ~= currentn then fprintf(io.stderr,".") io.stdout:flush() local output_features = {} local size = 0 -- procesamos las NBEST local nfeats = #string.tokenize(features[1]) fprintf(featsf,"FEATURES_TXT_BEGIN_0 %d %d %d", currentn, #features, nfeats) for i=1,nfeats do fprintf(featsf, " f%d", i) end fprintf(featsf, "\n") fprintf(featsf,table.concat(features, "\n").."\n") fprintf(featsf,"FEATURES_TXT_END_0\n") if not nbest_line then break end -- reiniciamos features = {} size = 0 currentn = tonumber(n) end table.insert(features, f) end fprintf(io.stderr,"\n") nbestf:close() featsf:close() april-ann-0.4.1/tools/nbest/extract_one_best_from_posteriors.lua000066400000000000000000000011571263004425400252230ustar00rootroot00000000000000nbest = {} local max = -11111111111111111111 function logAdd(a, b) if a>b then return a + math.log(1 + math.exp(b-a)) else return b + math.log(1 + math.exp(a-b)) end end if io.read("*l") ~= "NBestList1.0" then error ("Only allow NBestList1.0") end for line in io.lines() do local score,sentence = string.match(line, "^%(([^%(%)]*)%)%s*(.*)%s*$") score = tonumber(score) if not nbest[sentence] then nbest[sentence] = score else nbest[sentence] = logAdd(score, nbest[sentence]) end if nbest[sentence] > max then sentmax,max = sentence,nbest[sentence] end end printf("%14.6f \t %s\n", max , sentmax) april-ann-0.4.1/tools/nbest/minimum_bayes_risk_decoding.lua000066400000000000000000000220051263004425400240740ustar00rootroot00000000000000-- PAPER: "Minimum Bayes Risk Decoding for BLEU", Nicola Ehling and -- Richard Zens and Hermann Ney, in ACL 2007 -- REVISAR TAMBIEN: "Task-Specific Minimum Bayes-Risk Decoding using -- Learned Edit Distance", Izhak Shafran and William Byrne opt = cmdOpt{ program_name = string.basename(arg[0]), argument_description = "", main_description = "Minimum Bayes Risk Decoding in April toolkig", { index_name="t", description="NBest target file", short="t", argument="yes", }, { index_name="f", description="Loss function (WER, SER, CER, BLEU, PER)", short="f", argument="yes", }, { index_name="n", description="Take the first N hipothesys for compute risks (default take ALL)", short="n", argument="yes", }, { index_name="k", description="Extract the one-best from the K first hipothesis, but using the rest N for compute risks (default takes N previous parameter)", short="k", argument="yes", }, { index_name="l", description="L0 value (default 1)", short="l", argument="yes", }, { description = "shows this help message", short = "h", long = "help", argument = "no", action = function (argument) print(opt:generate_help()) os.exit(1) end } } optargs = opt:parse_args() if type(optargs) == "string" then error(optargs) end nbest = optargs.t or error ("Needs a NBest file") lossf = optargs.f or error ("Needs a Loss function") maxnbest = tonumber(optargs.n or -1) lambda0 = tonumber(optargs.l or 1.0) maxk = tonumber(optargs.k or -1) function logAdd(a, b) if a>b then return a + math.log(1 + math.exp(b-a)) else return b + math.log(1 + math.exp(a-b)) end end id2voc = {} voc2id = {} nextid = 1 f = io.open(nbest, "r") data = {} uniq = {} mem_counts = {} sum = 0 currentn = 0 next_sentence_id = 1 function normalize1(s) --s = string.lower(s) return table.concat(string.tokenize(s), " ") end function normalize2(s) s = string.gsub(s, "([^%s])([%'\"%(%)%[%]%,%.:;%-%!%?%_%%%+%-%*%$])", "%1 %2") s = string.gsub(s, "([%'\"%(%)%[%]%,%.:;%-%!%?%_%%%+%-%*%$])([^%s])", "%1 %2") --s = string.gsub(s, "[%'\"%(%)%[%]%,%.:;%-%!%?%_%%%+%-%*%$]", "") --s = string.lower(s) return table.concat(string.tokenize(s), " ") end function normalize3(s) --return string.gsub(s, "%s*", "") return table.concat(string.tokenize(s), " ") end function normalize4(s) s = string.lower(s) --s = string.gsub(s, "([^%s])([%'\"%(%)%[%]%,%.:;%-%!%?%_%%%+%-%*%$])", "%1 %2") --s = string.gsub(s, "([%'\"%(%)%[%]%,%.:;%-%!%?%_%%%+%-%*%$])([^%s])", "%1 %2") s = string.gsub(s, "[%'\"%(%)%[%]%,%.:;%-%!%?%_%%%+%-%*%$]", "") return table.concat(string.tokenize(s), " ") end function compute_none(s) return { s = s } end function compute_grams(s) s = string.tokenize(s) r = { [1] = {}, [2] = {}, [3] = {}, [4] = {}, len = #s, } local gram2 = {} local gram3 = {} local gram4 = {} for i=1,#s do if not voc2id[s[i]] then voc2id[s[i]] = nextid id2voc[nextid] = s[i] nextid = nextid + 1 end s[i] = voc2id[s[i]] local gram1 = s[i] r[1][gram1] = (r[1][gram1] or 0) + 1 if i-1 > 0 then local gram2 = table.concat(s, "#", i-1, i) r[2][gram2] = (r[2][gram2] or 0) + 1 if i-2 > 0 then local gram3 = table.concat(s, "#", i-2, i) r[3][gram3] = (r[3][gram3] or 0) + 1 if i-3 > 0 then local gram4 = table.concat(s, "#", i-3, i) r[4][gram4] = (r[4][gram4] or 0) + 1 end end end end return r end function compute_words(s) s = string.tokenize(s) r = { words = {}, len = #s, } for i=1,#s do r.words[s[i]] = (r.words[s[i]] or 0) + 1 end return r end function compute_wer(hyp, hypp) local resul = tasas{ typedata = "pairs_lines", data = { {hyp.auxdata.s, hypp.auxdata.s} }, tasa = "ie", } return resul.tasa*0.01 end function compute_cer(ref, hyp) local resul = tasas{ typedata = "pairs_lines", data = { {ref.auxdata.s, hyp.auxdata.s} }, tasa = "ie", words_width = 1, } return resul.tasa*0.01 end function compute_ser(ref, hyp) if ref == hyp then return 0 end return 1 end function compute_per(ref, hyp) local diff1=0 local diff2=0 for w,rep in pairs(ref.auxdata.words) do diff1 = diff1 + math.abs(rep - (hyp.auxdata.words[w] or 0)) end for w,rep in pairs(hyp.auxdata.words) do diff2 = diff2 + math.abs(rep - (ref.auxdata.words[w] or 0)) end return (diff1 + diff2)/ref.auxdata.len end -- hyp es la REFERENCIA y hypp es la hipotesis ??? function compute_bleu(hyp, hypp) -- hypp and hyp are tables with -- { -- id, -- score = v, -- sentence = sentence, -- grams = { -- grams1, grams2, grams3, grams4, len -- } -- } local BP = 0 if hypp.auxdata.len < hyp.auxdata.len then BP = 1 - hyp.auxdata.len/hypp.auxdata.len end local counts local prod = 0 local memid = hyp.id .. "_" .. hypp.id if hypp.id < hyp.id then memid = hypp.id .. "_" .. hyp.id end if mem_counts[memid] then counts = mem_counts[memid] else counts = {0,0,0,0} for i=1,4 do for gram,c in pairs(hyp.auxdata[i]) do if hypp.auxdata[i][gram] then counts[i] = counts[i] + math.min(c, hypp.auxdata[i][gram]) end end if i > 1 then counts[i] = math.log(counts[i] + 1) else counts[i] = math.log(counts[i]) end end mem_counts[memid] = counts end prod = prod + (counts[1] - math.log(hypp.auxdata.len)) for i=2,4 do --prod = prod + (counts[i] - math.log(hyp.auxdata.len - i + 1)) prod = prod + (counts[i] - math.log(hypp.auxdata.len - i + 2)) end prod=prod*0.25 return 1 - math.exp(prod+BP) end if lossf == "BLEU" then compute_loss = compute_bleu compute_auxdata = compute_grams normalize = normalize1 elseif lossf == "WER" then compute_loss = compute_wer compute_auxdata = compute_none normalize = normalize3 elseif lossf == "CER" then compute_loss = compute_cer compute_auxdata = compute_none normalize = normalize3 elseif lossf == "SER" then compute_loss = compute_ser compute_auxdata = compute_none normalize = normalize4 elseif lossf == "PER" then compute_loss = compute_per compute_auxdata = compute_words normalize = normalize3 else error("Incorrect loss function: " .. lossf) end while true do local line = f:read("*l") local n,sentence,feats,score n = -1 if line then n,sentence,feats,score = string.match(line, "(.*)|||(.*)|||(.*)|||(.*)") n = tonumber(n) score = tonumber(score) end if n ~= currentn then -- Compute posteriors for i=1,#data do data[i].posterior = math.exp(data[i].score - sum) end table.sort(data, function(a,b) return a.posterior > b.posterior end) -- compute MBR local min = nil local best = 1 local last = #data if maxk ~= -1 then last = math.min(maxk, #data) end for i=1,last do local score = 0 for j=1,#data do -- si son frases identicas, la funcion de perdida es 0, y por -- tanto no hay que entrar en este if if j ~= i and data[i].sentence ~= data[j].sentence then -- calculamos la funcion de perdida (1 - BLEU) local lossv = compute_loss(data[i], data[j]) --print(lossv) --print(data[i].sentence) --print(data[j].sentence) --print(j, data[j].posterior, data[j].score, lossv, score, min) --print(lossv, math.exp(data[j].score), data[j].posterior, math.exp(sum)) -- sumamos a la puntuacion de esta frase la combinacion del -- la probabilidad a posteriori y la funcion de perdida, y -- asi calculamos el riesgo score = score + data[j].posterior*lossv end -- si el score supera el mejor minimo, paramos if min and score > min then break end end --printf("%f %s\n", score, data[i].sentence) if not min or score < min then -- nos quedamos con aquella frase que tiene menor riesgo min = score best = i end end print(table.concat(string.tokenize(data[best].output), " ")) fprintf(io.stderr, "%-14g %s (%d)\n", min, data[best].sentence, data[best].id) io.stdout:flush() io.stderr:flush() -- RESET, hemos terminado con esta lista data = {} mem_counts = {} uniq = {} next_sentence_id = 1 currentn = n sum = 0 collectgarbage("collect") end if line then local realsentence = sentence sentence = normalize(sentence) if maxnbest == -1 or #data < maxnbest then local id = uniq[sentence] if not id then id = next_sentence_id uniq[sentence] = next_sentence_id next_sentence_id = next_sentence_id + 1 end -- para ajustar la escala local v = score*lambda0 -- sum for posteriors sum = logAdd(sum, v) if not data[id] then data[id] = { id = id, score = v, sentence = sentence, output = realsentence, auxdata = compute_auxdata(sentence), } else data[id].score = logAdd(data[id].score, v) end end else break end end april-ann-0.4.1/tools/nbest/rerank.lua000066400000000000000000000050131263004425400176340ustar00rootroot00000000000000weightsfilename = arg[1] nbestfilename = arg[2] features = arg[3] out_reranked = arg[4] or "reranked.nbest.out.gz" out_feats = arg[5] or nil local featsf = nil if out_feats then featsf = io.open(out_feats, "w") end local g = io.open(out_reranked, "w") -- leemos los pesos weights = string.tokenize(io.open(weightsfilename, "r"):read("*l")) for i=1,#weights do weights[i] = tonumber(weights[i]) end if features ~= nil then features = io.open(features) end -- leemos las nbest y hacemos el rescoring local currentn = 0 local best = nil local best_score = nil local f = io.open(nbestfilename) local reranked = {} if features then features:read("*l") end for line in f:lines() do local n,line,feats = string.match(line, "(.*)|||(.*)|||(.*)|||") n = tonumber(n) if features then if n ~= currentn then features:read("*l") features:read("*l") end feats = features:read("*l") end if n ~= currentn and best then print(table.concat(string.tokenize(best), " ")) table.sort(reranked, function(a,b) return a[3] > b[3] end) if featsf then fprintf(featsf, "FEATURES_TXT_BEGIN_0 %d %d %d", currentn, #reranked, #weights) for j=1,#weights do fprintf(featsf, " f_%d", j) end fprintf(featsf, "\n") for i=1,#reranked do fprintf(featsf, "%s\n", reranked[i][2]) end fprintf(featsf, "FEATURES_TXT_END_0\n") end for i=1,#reranked do fprintf(g, "%d|||%s|||%s|||%f\n", currentn, reranked[i][1], reranked[i][2], reranked[i][3]) end reranked = {} best_score = nil best = nil currentn = n end score = 0 local feats = string.tokenize(feats) for k=1,#weights do score = score + weights[k]*tonumber(feats[k]) end if not best_score or score > best_score then best_score = score best = line end table.insert(reranked, { line, table.concat(feats, " "), score }) end print(table.concat(string.tokenize(best), " ")) f:close() table.sort(reranked, function(a,b) return a[3] > b[3] end) if featsf then fprintf(featsf, "FEATURES_TXT_BEGIN_0 %d %d %d", currentn, #reranked, #weights) for j=1,#weights do fprintf(featsf, " f_%d", j) end fprintf(featsf, "\n") for i=1,#reranked do fprintf(featsf, "%s\n", reranked[i][2]) end fprintf(featsf, "FEATURES_TXT_END_0\n") end for i=1,#reranked do fprintf(g, "%d|||%s|||%s|||%f\n", currentn, reranked[i][1], reranked[i][2], reranked[i][3]) end reranked = {} g:close() if featsf then featsf:close() end april-ann-0.4.1/tools/nbest/substitute_feature.lua000066400000000000000000000020141263004425400222760ustar00rootroot00000000000000feature_pos = tonumber(arg[1]) featuresfilename = arg[2] f = io.open(arg[3], "r") -- new feature file alpha_linear_comb = tonumber(arg[4] or 0.0) -- alpha for nbest list feature, 1 - alpha for new feature -- leemos las features features = {} local n = 1 local fbegin = "FEATURES_TXT_BEGIN" local fend = "FEATURES_TXT_END" featsf=io.open(featuresfilename) for line in featsf:lines() do if string.sub(line, 1, #fbegin) == fbegin then features[n] = {} local t = string.tokenize(line) if not tonumber(t[4]) then fprintf(io.stderr, "%s\n", line) end printf("%s %s %s %d %s", t[1], t[2], t[3], t[4], table.concat(t, " ", 5, #t)) printf("\n") elseif string.sub(line, 1, #fend) == fend then n = n + 1 printf("%s", line) printf("\n") else local t = string.tokenize(line) t[feature_pos] = (t[feature_pos]*alpha_linear_comb) + ((1-alpha_linear_comb)*tonumber(f:read("*l"))) printf("%s\n", table.concat(t, " ")) end end featsf:close() f:close() april-ann-0.4.1/tools/statistics/000077500000000000000000000000001263004425400167275ustar00rootroot00000000000000april-ann-0.4.1/tools/statistics/compute-box-whiskers.lua000066400000000000000000000012501263004425400235270ustar00rootroot00000000000000-- COMPUTES BOX AND WHISKERS, PLUS MEAN AND VARIANCE datafilename = arg[1] column = tonumber(arg[2]) if datafilename == "-" then datafilename = nil end data = {} local sum = 0 local sum2 = 0 for line in io.uncommented_lines(datafilename) do local t = string.tokenize(line) local v = tonumber(t[column]) table.insert(data, v) sum = sum + v sum2 = sum2 + v*v end table.sort(data) local q0 = 1 local q1 = math.round(#data/4) local q2 = math.round(#data/2) local q3 = math.round(#data*3/4) local q4 = #data local mean = sum/#data local stddev = math.sqrt( (sum2 - sum*sum/#data)/(#data - 1) ) print(data[q0], data[q1], data[q2], data[q3], data[q4], mean, stddev) april-ann-0.4.1/tools/statistics/time-series-autocorrelation.lua000066400000000000000000000020161263004425400250670ustar00rootroot00000000000000if #arg < 3 then print("Syntax error!") printf("\t%s FILENAME|- NUMCOL LAG1 [LAG2 [LAG3 [...]]]\n", arg[0]) os.exit(1) end filename = arg[1] col = tonumber(arg[2]) lags = {} for i=3,#arg do table.insert(lags, tonumber(arg[i])) end if filename == "-" then filename = nil end function zero_if_null(v) if v == "None" or v == "Undefined" or v == "Unintialized" or v == "Null" then v = 0 end return v end local data = {} local sum = 0 local sum2 = 0 for line in io.uncommented_lines(filename) do local t = string.tokenize(line) local v = zero_if_null(t[col]) table.insert(data, v) sum = sum + v sum2 = sum2 + v*v end local mean = sum/#data local var = (sum2 - sum*sum/#data)/(#data - 1) printf("mean: %g\nvariance: %g\n\n", mean, var) for _,lag in ipairs(lags) do local i = 1 local j = 1 + lag local sum = 0 while j <= #data do local x,y = data[i],data[j] sum = sum + (x - mean) * (y - mean) i, j = i + 1, j + 1 end printf("LAG %d %g\n", lag, (sum/#data)/var) end april-ann-0.4.1/tools/trainable/000077500000000000000000000000001263004425400164765ustar00rootroot00000000000000april-ann-0.4.1/tools/trainable/compute-generalization-statistics.lua000066400000000000000000000113461263004425400260630ustar00rootroot00000000000000if #arg < 5 then print("Syntax error!") printf("\t%s FILENAME VAL_MEAN_COL VAL_VAR_COL TEST_MEAN_COL TEST_VAR_COL [W_REPS [EXP_REPS [EXP1_SIZE [EXP2_SIZE ...] ] ] ]\n", arg[0]) printf("\nThis script computes the generalization ability given a set of experiments\n") printf("using different hyperparameters.\n\n") printf("\tuse - as FILENAME for stdin\n") printf("\tVAL_MEAN_COL is the column with the MEAN for your loss-function\n") printf("\t over all validation samples\n") printf("\tVAL_VAR_COL is the column with the VARIANCE of the MEAN for your\n") printf("\t loss-function over all validation samples\n") printf("\tTEST_MEAN_COL idem but with TEST\n") printf("\tTEST_VAR_COL idem but with TEST\n") printf("\tW_REPS is the number of simulation repetitions to compute\n") printf("\t generalization weights (by default 1000)\n") printf("\tEXP_REPS is the number of simulation repetitions to compute\n") printf("\t box-whiskers plots for each size (by default 1)\n") printf("\tThe following arguments are as many experiment sizes as you need\n") printf("\t(taken as subset of all your data), by default num_lines_of(FILENAME)\n") printf("\n\tSee 2012, Bergstra and Bengio, 'Random Search for Hyper-Parameter Optimization'\n") printf("\tfor more details: http://jmlr.csail.mit.edu/papers/volume13/bergstra12a/bergstra12a.pdf\n") os.exit(1) end datafilename = arg[1] val_mean_column = tonumber(arg[2]) val_var_column = tonumber(arg[3]) test_mean_column = tonumber(arg[4]) test_var_column = tonumber(arg[5]) repetitions = tonumber(arg[6] or 1000) expsize_reps = tonumber(arg[7] or 1) expsizes = {} for i=8,#arg do table.insert(expsizes, tonumber(arg[i])) end if datafilename == "-" then datafilename = nil end function sample_random_from_bash() return tonumber(io.popen("od -N2 -An -i /dev/urandom"):read("*l")) end -- read data data = {} for line in io.uncommented_lines(datafilename) do local t = string.tokenize(line) local val_mean = tonumber(t[val_mean_column]) local val_var = tonumber(t[val_var_column]) local test_mean = tonumber(t[test_mean_column]) local test_var = tonumber(t[test_var_column]) table.insert(data, { val_mean = val_mean, val_var = val_var, test_mean = test_mean, test_var = test_var, sum_mean2_var2 = (test_mean*test_mean + test_var*test_var), distribution = random(sample_random_from_bash()) }) end if #expsizes == 0 then table.insert(expsizes, #data) end ----------------------------------------- rnd = random(sample_random_from_bash()) -- for each random experiment size for _,expsize in ipairs(expsizes) do -- table to keep computed test means local test_means_tbl = {} for rep=1,expsize_reps do -- populate expsize-sized random experiment local wins = {} local population = {} for i=1,expsize do local idx = rnd:randInt(1,#data) if #expsizes == 1 and expsize_reps == 1 then idx = i end table.insert(population, data[idx]) table.insert(wins, 0) end -- sampling loop for estimation of random experiment weights for i=1,repetitions do local min = nil local argmin = 0 -- sample from each hyperparameter set distribution for j,one_exp in ipairs(population) do local sampled_error = one_exp.distribution:randNorm(one_exp.val_mean, one_exp.val_var) if argmin == 0 or sampled_error < min then argmin,min = j,sampled_error end end -- wins measures how many times a given set of hyperparameters was the -- best, so at the end is possible to compute weights normalizing this -- table wins[argmin] = wins[argmin] + 1 end ----------------------------------------- -- compute test mean and test variance local test_mean = 0 local test_var = 0 for i,one_exp in ipairs(population) do local weight = wins[i]/repetitions test_mean = test_mean + weight * one_exp.test_mean test_var = test_var + weight * one_exp.sum_mean2_var2 end test_var = test_var - test_mean*test_mean ----------------------------------------- if #expsizes == 1 and expsize_reps == 1 then print(expsize, test_mean, test_var) end table.insert(test_means_tbl, test_mean) end if #test_means_tbl > 1 then -- sort test_means_tbl table.sort(test_means_tbl) -- compute box-whisker data local q0 = 1 local q1 = math.max(1,math.round(#test_means_tbl/4)) local q2 = math.max(1,math.round(#test_means_tbl/2)) local q3 = math.max(1,math.round(#test_means_tbl*3/4)) local q4 = #test_means_tbl print(expsize, test_means_tbl[q0], test_means_tbl[q1],test_means_tbl[q2],test_means_tbl[q3], test_means_tbl[q4]) end end april-ann-0.4.1/tools/trainable/random-search-hyperparemeter-optimization.lua000066400000000000000000000277651263004425400275230ustar00rootroot00000000000000help_string = [[ Command line args must be: april-ann random-search.....lua conf.lua ["all_hyperparams.TAG.option='blah'" "global_vars.working_dir='blah'" "global_vars.n=blah" "global_vars.seed=blah"... ] This script executes a random search optimization of hyperparameters of any executable (not only april scripts). It receives one mandatory argument, a configuration file which must fullfil following template: return { hyperparams = { { option="--o1=", value=10, tag="o1", sampling="fixed", hidden=true }, { option="--o2=", value=20, tag="o2", sampling="fixed" }, { option="--r1=", tag="r1", sampling = "log-uniform", type="integer", values= { { min=1, max=10 }, { min=20, max=100 } }, filter = function(hyperparams) hyperparams["r1"] = "200" return true end }, { option="--r2=", tag="r2", sampling = "uniform", values= { 1, 2, 3, 4, 5 } }, { option="--r3=", tag="r3", prec=3, sampling = "gaussian", values= { mean=0, variance=0.1 } }, { option="--r4=", tag="r4", sampling = "random", filter = function(hyperparams) if hyperparams["r2"] == "1" then hyperparams["r4"] = "0" end return true end }, { option=nil, tag="r5", sampling="random" } }, filter = function(hyperparams) hyperparams['r5'] = '0.4' return true end, script = "", exec = "echo", working_dir = "/tmp/", -- seed = ANY_SEED_VALUE (if not given, take random from bash) n = 50, arguments_maker = function(args_list) return iterator(ipairs(args_list)): map(function(_,t) return "%s%q"%{t.option,t.value} end): concat(""," ") end } and any number of arguments which modify configuration file values. This arguments could access to: - all_hyperparams table which could be indexed by TAGs => all_hyperparams.TAG.option='blah' - global_vars table which could be indexed by any global var => global_vars.seed=blah ]] if #arg < 1 then printf("%s\n", help_string) error("Syntax error") end april_print_script_header(arg) ------------------------ Auxiliar functions --------------------------------- -- This sample random numbers from urandom device function sample_random_from_bash() return tonumber(io.popen("od -N2 -An -i /dev/urandom"):read("*l")) end -- This function check the correction of random_hyperparams local fixed_hyperparam_valid_options = table.invert{"option", "tag", "value", "hidden", "sampling" } local random_hyperparam_valid_options = table.invert{"option", "tag", "values", "sampling", "prec", "filter", "type", "size", "hidden" } local random_hyperparam_values_table_valid_options = table.invert{"min","max","step", "mean", "variance", "size" } function check_hyperparam(hyperparam) if not hyperparam.sampling then error("Each hyperhyperparameter needs a sampling") end if not hyperparam.tag then error("Each hyperparameter needs a tag") end if hyperparam.sampling == "fixed" then for name,v in pairs(hyperparam) do if not fixed_hyperparam_valid_options[name] then error("Incorrect fixed hyperparam option name: " .. name) end end hyperparam.filter = function(hyperparams) return true end else if not hyperparam.prec then hyperparam.prec = 10 end if not hyperparam.filter then hyperparam.filter = function(hyperparams) return true end end for name,v in pairs(hyperparam) do if not random_hyperparam_valid_options[name] then error("Incorrect random hyperparam option name: " .. name) end end if hyperparam.sampling == "gaussian" then if not hyperparam.values then error("Each random hyperparameter needs values") end if not hyperparam.values.mean or not hyperparam.values.variance then error("Gaussian sampling needs mean and variance") end elseif hyperparam.sampling == "uniform" or hyperparam.sampling == "log-uniform" then if not hyperparam.values then error("Each random hyperparameter needs values") end if type(hyperparam.values) ~= "table" then error("Uniform sampling needs values table") end if type(hyperparam.values[1]) == "table" then if hyperparam.type ~= "integer" and hyperparam.type ~= "real" then error("Needs integer or real type field for TAG "..hyperparam.tag) end local size = 0 for _,p in ipairs(hyperparam.values) do for name,v in pairs(p) do if not random_hyperparam_values_table_valid_options[name] then error("Incorrect random values table option name: " .. name) end end if not p.step then p.step = 1 end if not p.min or not p.max then error("Values need min and max (optionally step) hyperparameters") end p.size = (p.max - p.min)/p.step if hyperparam.type == "integer" then p.size = math.floor(p.size) end size = size + p.size end hyperparam.size = size end elseif hyperparam.sampling == "random" then -- NOTHING TO DO else error("Incorrect sampling type") end end end -- This function sample one value from the given hyperparam distribution and random -- number generator function sample(hyperparam, rnd) local v if hyperparam.sampling == "fixed" then v = tostring(hyperparam.value) elseif hyperparam.sampling == "gaussian" then v = string.format("%."..hyperparam.prec.."f", rnd:randNorm(hyperparam.values.mean, hyperparam.values.variance)) elseif hyperparam.sampling == "random" then v = tostring(sample_random_from_bash()) else -- uniform and log-uniform if type(hyperparam.values[1]) == "table" then local pos = rnd:rand(hyperparam.size) for k,p in ipairs(hyperparam.values) do pos = pos - p.size if pos <= 0 or k==#hyperparam.values then if hyperparam.type == "integer" then local r if hyperparam.sampling == "uniform" then r = rnd:randInt(0, p.size)*p.step + p.min else if p.step ~= 1 then error("Step must be one for log-uniform integers") end r = rnd:rand(math.log(p.max)-math.log(p.min)) + math.log(p.min) r = math.round(math.exp(r)) end v = tostring(r) else -- if hyperparam.type == "integer" ... local r if hyperparam.sampling == "uniform" then r = rnd:rand(p.max-p.min) + p.min else r = rnd:rand(math.log(p.max)-math.log(p.min)) + math.log(p.min) r = math.exp(r) end v = string.format("%.".. hyperparam.prec .."f", r) end -- if hyperparam.type == "integer" else ... break end -- if pos <= 0 or k == #hyperparam.values ... end -- for k,p in ipairs(hyperparam.values) else -- if type(hyperparam.values[1]) == "table" ... if hyperparam.sampling == "log-uniform" then error("log-uniform sampling don't works with a finite table") end v = tostring(rnd:choose(hyperparam.values)) end end return v end ------------------------------------------------------------------------------ local conf_table = (dofile(arg[1] or error("Needs a configuration file")) or error("Impossible to load configuration file")) local global_vars = {} global_vars.n = conf_table.n or error ("The configuration file needs ".. "a n option") global_vars.seed = tonumber(conf_table.seed or sample_random_from_bash()) global_vars.working_dir = conf_table.working_dir or error("Needs a working_dir option") global_vars.exec = conf_table.exec or error("Needs an exec option") global_vars.script = conf_table.script or error("Needs a script option") global_vars.filter = conf_table.filter or (function(hyperparams) return true end) local hyperparams_conf_tbl = conf_table.hyperparams or {} all_hyperparams = {} -- ERROR CHECK -- for _,hyperparam in ipairs(hyperparams_conf_tbl) do check_hyperparam(hyperparam) if all_hyperparams[hyperparam.tag] then error("The following tag is repeated: " .. hyperparam.tag) end all_hyperparams[hyperparam.tag] = hyperparam end -- Modify hyperparams by command line local valid_cmd_options = table.invert{ "seed", "working_dir", "exec", "script", "filter", "n" } for i=2,#arg do -- load the chunk local chunk_func=loadstring(arg[i]) or error("Impossible to load string: ".. arg[i]) -- execute the chunk chunk_func() -- printf("# Executed chunk string: %s\n", arg[i]) end local n = global_vars.n local seed = global_vars.seed local working_dir = global_vars.working_dir local exec = global_vars.exec local script = global_vars.script local filter = global_vars.filter local rnd = random(seed) local arguments_maker = conf_table.arguments_maker or function(hyperparams_list) return iterator(ipairs(hyperparams_list)): map(function(_,t) return "%s%q"%{t.option,t.value} end): concat("", " ") end printf("# Seed %d\n", global_vars.seed) printf("# Sampling over %d hyperparameters\n", #hyperparams_conf_tbl) -- N random iterations for i=1,n do collectgarbage("collect") local hyperparam_values = nil local args_table = nil local filename_tags = nil local filename = nil local skip = false local max_iters = 1000 local iter1_count = 0 -- First loop, until the combination of hyperparams were unique repeat iter1_count = iter1_count + 1 if iter1_count > max_iters then error("Possible infinite loop, all possible hyperparam values ".. "are sampled yet") end -- Second loop, until hyperparam filter function returns true local iter2_count = 0 repeat iter2_count = iter2_count + 1 if iter2_count > max_iters then error("Possible infinite loop due to global filter function\n".. "Check that it is not always returning false or nil") end hyperparam_values = {} args_table = {} filename_tags = {} -- auxiliar function function put_value(option, tag, value, hidden) local value = tostring(value) if option then local v = value table.insert(args_table, { tag=tag, option=option, value=v }) end if not hidden then table.insert(filename_tags, string.format("%s:%s", tag, string.gsub(value, "/", "_"))) end end for _,hyperparam in ipairs(hyperparams_conf_tbl) do -- Third loop, until current filter function returns true local v local iter3_count = 0 repeat iter3_count = iter3_count + 1 if iter3_count > max_iters then error("Possible infinite loop due to filter function of: ".. hyperparam.tag .."\n".. "Check that it is not always returning false or nil") end v = sample(hyperparam, rnd) hyperparam_values[hyperparam.tag] = v until hyperparam.filter(hyperparam_values) end until filter(hyperparam_values) for _,hyperparam in ipairs(hyperparams_conf_tbl) do local tag = hyperparam.tag if type(hyperparam_values[tag]) ~= "string" then print("WARNING!!! Please, check that all filter functions set".. " hyperparams to string type values, at least this ".. "one: " .. tag) end put_value(hyperparam.option, tag, tostring(hyperparam_values[tag]), hyperparam.hidden) end filename=string.format("%s/output-%s.log", working_dir, table.concat(filename_tags, "_")) skip = (io.open(filename, "r") ~= nil) if skip then printf ("# Skipping file %s\n", filename) end until not skip printf("# ITERATION %d :: %s\n", i, table.concat(filename_tags, " ")) printf("# \t output file: %s\n", filename) local args_str = arguments_maker(args_table) assert(type(args_str) == "string", "arguments_maker must return a string") local cmd = string.format("%s %s %s", exec, script, args_str) printf("# \t executed string: %s\n", cmd) printf("# \t hyperparam values:\n") for _,hyperparam in ipairs(hyperparams_conf_tbl) do printf("# \t \t %s = %s\n", hyperparam.tag, hyperparam_values[hyperparam.tag]) end local f = io.popen(cmd) local g = io.open(filename, "w") or error(string.format("Impossible to open logfile '%s'", filename)) for line in f:lines() do g:write(line.."\n") g:flush() end f:close() g:close() end april-ann-0.4.1/update_doc.sh000077500000000000000000000003061263004425400160420ustar00rootroot00000000000000#!/bin/bash user=$(grep user /etc/pakozm.hol.es | cut -d' ' -f 2) host=$(grep host /etc/pakozm.hol.es | cut -d' ' -f 2) cmd="mirror -R doxygen_doc /public_html/STUFF/" lftp -e "$cmd" -u $user $host

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april-ann-0.4.1/packages/basics/iterator/000077500000000000000000000000001263004425400202505ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/iterator/lua_src/000077500000000000000000000000001263004425400217005ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/iterator/lua_src/iterator.lua000066400000000000000000000416101263004425400242360ustar00rootroot00000000000000--[[ Copyright (c) 2014 Francisco Zamora-Martinez (pakozm@gmail.com) Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ]] -- Detect if APRIL-ANN is available. local type = type local aprilann_available = (aprilann ~= nil) if aprilann_available then type = luatype or type end -- local class = class or require "oop-iter.class" -------------------------------- -- iterator module definition -- -------------------------------- local iterator,iterator_methods = class("iterator") iterator._NAME = "iterator" iterator._VERSION = "0.1" local concat = table.concat local insert = table.insert local pack = table.pack local remove = table.remove local unpack = table.unpack local wrap = coroutine.wrap local yield = coroutine.yield -- Clones the function and its upvalues local function clone_function(func) -- clone by using a string dump local ok,func_dump = pcall(string.dump, func) local func_clone = (ok and loadstring(func_dump)) or func if func_clone ~= func then -- copy upvalues local i = 1 while true do local name,value = debug.getupvalue(func,i) if not name then break end -- TODO: implement cone (deep copy) of tables if type(value) == "function" then value = clone_function(value) end debug.setupvalue(func_clone, i, value) i = i + 1 end end return func_clone end -- Filters a Lua iterator function output using a given predicate function. The -- predicate returns true when a value must be taken, false when it must be -- removed. The predicate function is called as f(...) where ... are the values -- returned by the iterator function. local function filter(predicate_func, f, s, v) return function(s, v) local tmp = pack(f(s, v)) while tmp[1] ~= nil and not predicate_func(unpack(tmp)) do v = tmp[1] tmp = pack(f(s, v)) end return unpack(tmp) end, s, v end -- Iterable map function, receives a map function and a Lua iterator and returns -- another Lua iterator function. The map function is called as f(...) where -- ... are the values returned by the iterator function. Multiple results are -- possible from one map call using coroutine.yield function. -- -- @note FROM: http://www.corsix.org/content/mapping-and-lua-iterators local function map(map_func, f, s, v) local done local function maybeyield(...) if ... ~= nil then yield(...) end end local function domap(...) v = ... if v ~= nil then return maybeyield(map_func(...)) else done = true end end return wrap(function() repeat local tmp = pack(f(s,v)) v = tmp[1] domap(unpack(tmp)) until done end), s, v end -- Reduce function, receives a reduce function, a reduce initial value, and a -- Lua iterator, and returns the computation result of the reduction. The -- reduce function is call as f(acc,...) where acc is the reduced (accumulated) -- computation, and ... are the values returned by the iterator function. local function reduce(reduce_func, initial_value, f, s, v) assert(initial_value ~= nil, "reduce: needs an initial_value as second argument") local accum = initial_value local tmp = pack(f(s, v)) while tmp[1] ~= nil do accum = reduce_func(accum, unpack(tmp)) tmp = pack(f(s, tmp[1])) end return accum end -- Apply function, receives a function and a Lua iterator, and calls the apply -- function with every element of the iterator. The apply function is called as -- f(...) where ... are the values returned by the iterator function. local function apply(apply_func, f, s, v) if not apply_func then apply_func = function() end end local tmp = pack(f(s,v)) while tmp[1] ~= nil do apply_func(unpack(tmp)) tmp = pack(f(s,tmp[1])) end end local function iscallable(obj) local t = type(obj) if t == "function" then return true end if t == "table" or t == "userdata" then return (getmetatable(obj) or {}).__call end return false end -------------------------------------------------------------------- -------------------------------------------------------------------- -------------------------------------------------------------------- -- Function generators -- Range iterator, receives start,stop,step function iterator.range(...) local arg = pack(...) local start,stop,step = arg[1],arg[2],arg[3] or 1 if not stop then start,stop=1,start end local i = start - step if step > 0 then return iterator(function(step, i) if step and i then i = i + step if i <= stop then return i end end end, step, i) else return iterator(function(step, i) if step and i then i = i + step if i >= stop then return i end end end, step, i) end end -- Duplicates its arguments in an infinite iterator. function iterator.duplicate(...) return iterator(function(arg) return unpack(arg) end, pack(...)) end -- Returns an inifite iterator which calls the given function with: f(0), f(1), -- ..., f(i), ... function iterator.tabulate(func) local x=-1 return iterator(function() x=x+1 return func(x) end) end -- Returns a zero indefinitely. function iterator.zeros() return iterator(function() return 0 end) end -- Returns a one indefinitely. function iterator.ones() return iterator(function() return 1 end) end -- Returns an iterator over multiple iterators at the same time. The iteration -- ends if any of the given iterators end. function iterator.zip(...) local arg = { ... } for i=1,#arg do assert(class.is_a(arg[i], iterator), "Needs instances of iterator class") end local finished = false return iterator(function() if finished then return nil end local result = {} for i=1,#arg do local partial = table.pack( arg[i]() ) if not partial[1] then finished=true return nil end for k,v in ipairs(partial) do table.insert(result,v) end end return table.unpack(result) end) end -------------------------------------------------------------------- -------------------------------------------------------------------- -------------------------------------------------------------------- -- Constructor of class iterator. It is a wrapper around a Lua iterator -- function, which allow to keep the iterator state, allowing to write easy -- functional operations (map, reduce, filter, ...). function iterator:constructor(f, s, v) if class.is_a(f, iterator) then assert(not s and not v, "Given s and v parameters with an iterator object") f,s,v = f:get() elseif not iscallable(f) and type(f) == "table" then if #f == 0 then f,s,v = iterator(pairs(f)):select(2):get() else f,s,v = iterator(ipairs(f)):select(2):get() end end assert(iscallable(f), "Needs a Lua iterator tripplete, a table, a function or a callable table") self.f,self.s,self.v = f,s,v end -- Returns the underlying Lua iterator. function iterator_methods:get() return self.f,self.s,self.v end -- Performs one iterator step, and returns its result. function iterator_methods:step() local tmp = pack( self.f(self.s, self.v) ) self.v = tmp[1] return unpack(tmp) end -- Equivalent to step() method, allowing to use iterator objects as Lua -- iterators in generic for loops. function iterator.meta_instance:__call() return self:step() end -- Map method, a wrapper around map function. Multiple results are possible -- from one map call using coroutine.yield function. function iterator_methods:map(func) return iterator(map(func, self:get())) end -- Filter method, a wrapper around filter function. function iterator_methods:filter(func) return iterator(filter(func, self:get())) end -- Apply method, a wrapper around apply function. function iterator_methods:apply(func) apply(func, self:get()) end -- Reduce method, a wrapper around reduce function. function iterator_methods:reduce(func, initial_value) return reduce(func, initial_value, self:get()) end -- Enumerate method, returns another iterator object which appends as a first -- element of every iteration a enumeration number. function iterator_methods:enumerate() local id = 0 return self:map(function(...) id = id + 1 return id, ... end) end -- Calls a function for every iteration value. The function is a name, and this -- name must be declared in every iteration value (as table keys, or in its -- metatable). function iterator_methods:call(funcname, ...) local func_args = pack(...) return self:map(function(...) local arg = pack(...) local result = {} for i=1,#arg do local t = pack(arg[i][funcname](arg[i],unpack(func_args))) for j=1,#t do insert(result, t[j]) end end return unpack(result) end) end -- Performs a nested iteration over every result. It receives a Lua function -- which returns an iterator (as ipairs, pairs, ...) function iterator_methods:iterate(iterator_func) return self:map(function(...) local f,s,v = iterator_func(...) local tmp = pack(f(s,v)) while tmp[1] ~= nil do yield(unpack(tmp)) tmp = pack(f(s,tmp[1])) end end) end -- Concats the iterator results using sep1 for inter-iteration elements, and -- sep2 for intra-iteration calls. function iterator_methods:concat(sep1,sep2) local sep1,sep2 = sep1 or "",sep2 or sep1 or "" local t = {} self:apply(function(...) local arg = pack(...) insert(t, string.format("%s", concat(arg, sep1))) end) return concat(t, sep2) end -- Indexes iteration result by a given set of indices. It assumes that all -- the elements in the iterator result are tables. function iterator_methods:field(...) local f,s,v = self:get() local arg = pack(...) return iterator(function(s) local tmp = pack(f(s,v)) if tmp[1] == nil then return nil end v = tmp[1] local ret = { } for i=1,#tmp do for j=1,#arg do insert(ret, tmp[i][arg[j]]) end end return unpack(ret) end, s,v) end -- Selects an iteration result by a given set of number indices. function iterator_methods:select(...) local f,s,v = self:get() local arg = pack(...) for i=1,#arg do arg[i]=tonumber(arg[i]) assert(arg[i],"select: expected a number") end return iterator(function(s) local tmp = pack(f(s,v)) if tmp[1] == nil then return nil end v = tmp[1] local selected = {} for i=1,#arg do selected[i] = tmp[arg[i]] end return unpack(selected) end, s,v) end -- Stores the iteration into a table. If every iteration has more than one -- result, the first element will be used as key, otherwise, an enumerated -- key will be used. function iterator_methods:table() local t = {} local idx = 1 self:apply(function(...) local v = pack(...) local k = remove(v, 1) if #v == 0 then k,v = idx,k elseif #v == 1 then v = v[1] end t[k] = v idx = idx + 1 end) return t end -- Converts to table and then unpack the resulting table. function iterator_methods:unpack(...) return table.unpack(self:table(), ...) end -- Returns the iterator result at nth position. function iterator_methods:nth(nth) for i=1,nth-1 do if not self() then break end end return self() end -- Returns the head of the iterator. function iterator_methods:head() return self:nth(1) end -- Returns the tail of the iterator. function iterator_methods:tail() self() -- skip first value return self end -- Returns the first n elements of the iterator, or the first which satisfy a -- given predicate function iterator_methods:take(n) if type(n) == "number" then local i=0 return iterator(function() if i < n then i=i+1 return self() end end) else local satisfied = true return iterator(function() if satisfied then local result = pack( self() ) if not n( unpack(result) ) then satisfied = false else return unpack( result ) end end end) end end -- Skips the first n elements of the iterator, or the first which satisfy a -- given predicate function iterator_methods:drop(n) if type(n) == "number" then for i=1,n do if not self() then break end end return self else local result repeat result = pack(self()) until not n( unpack(result) ) return iterator(function() local aux aux,result = result,pack( self() ) return unpack(aux) end) end end -- Splits an iterator into two iterators, only works with pure functional -- iterators. function iterator_methods:split(n) return self:clone():take(n),self:clone():drop(n) end -- Only works properly with pure functional iterators. function iterator_methods:clone() local f,s,v = self:get() local f = clone_function(f) return iterator(f,s,v) end -- Returns the position of the first iterator index which is equals to the given -- arguments. function iterator_methods:index(...) local arg = pack(...) local idx=0 while true do idx=idx+1 local current = pack(self()) if not current[1] then break end assert(#current == #arg, "Incorrect number of arguments") local eq = true for j=1,#current do if current[j] ~= arg[j] then eq = false break end end if eq then return idx end end return nil end -- Returns an iterator to positions which are equal to the given arguments. function iterator_methods:indices(...) local arg = pack(...) return iterator(function(self, idx) while true do idx = idx+1 local current = pack(self()) if not current[1] then break end local eq = true for j=1,#current do if current[j] ~= arg[j] then eq = false break end end if eq then return idx end end end, self, 0) end -- Filters by using a regular expression. function iterator_methods:grep(regexp_string) assert(type(regexp_string) == "string", "Only valid with string values") return self:filter(function(str,...) assert(not ..., "Only valid for unary iterators") assert(type(str) == "string", "Only valid with string values") return str:find(regexp_string) ~= nil end) end -- Returns two iterators where elements do and not do satisfy the given -- predicate. function iterator_methods:partition(pred) return self:clone():filter(pred), self:clone():filter(function(...) return not pred(...) end) end -- Returns two iterators where elements do and not do satisfy the given -- predicate. function iterator_methods:size() return self:reduce(function(acc,x) return acc + 1 end, 0) end -- Returns true if all return values satisfy the predicate. function iterator_methods:all(pred) return self:reduce(function(acc,...) return acc and pred(...) end, true) end -- Returns true if at least one return value satisfies the predicate. function iterator_methods:any(pred) return self:reduce(function(acc,...) return acc or pred(...) end, false) end -- Returns the sum. function iterator_methods:sum() return self:reduce(function(a,b) return a+b end, 0) end -- Returns the product. function iterator_methods:prod() return self:reduce(function(a,b) return a*b end, 1) end -- Returns the max. function iterator_methods:max() return self:reduce(math.max, -math.huge) end -- Returns the min. function iterator_methods:min() return self:reduce(math.min, math.huge) end -- In APRIL-ANN this module is defined at global environment if aprilann_available then _G.apply = apply _G.iscallable = iscallable _G.iterator = iterator _G.iterable_filter = filter _G.iterable_map = map _G.range = iterator.range _G.reduce = reduce end -- UNIT TEST function iterator.test() for k,v in filter(function(k,v) return v % 2 == 0 end, ipairs{1,2,3,4}) do assert(v % 2 == 0) end for k,v in map(function(k,v) return k,k+v end, ipairs{1,2,3,4}) do assert(v == 2*k) end local r = reduce(function(acc,a,b,c) return acc+a+b+c end, 0, map(function(k,v) return k,v,v end, ipairs{1,2,3,4})) assert(r == 3 + 6 + 9 + 12) apply(function(a,b,c) assert(a==b and b==c) end, map(function(k,v) return k,v,v end, ipairs{1,2,3,4})) end return iterator april-ann-0.4.1/packages/basics/iterator/package.lua000066400000000000000000000021541263004425400223500ustar00rootroot00000000000000package{ name = "iterator", version = "1.0", depends = { "base", "class" }, keywords = { }, description = "", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", --copy{ file= "c_src/*.h", dest_dir = "include" }, --provide_bind{ file = "binding/bind_util.lua.cc" , dest_dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test-iterator.lua", }, }, }, target{ name = "build", depends = "provide", use_timestamp = true, -- object{ -- file = "c_src/*.cc", -- dest_dir = "build", -- -- flags = "-std=c99", -- }, luac{ orig_dir = "lua_src", dest_dir = "build", }, --build_bind{ file = "binding/bind_util.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/iterator/test/000077500000000000000000000000001263004425400212275ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/iterator/test/test-iterator.lua000066400000000000000000000035151263004425400245440ustar00rootroot00000000000000local check = utest.check local T = utest.test -- reduce T("ReduceTest", function() check.eq(iterator(ipairs({4,2,1,10})):reduce(math.min, math.huge), 1) check.eq(iterator(string.gmatch("01101",".")):reduce(function(acc,v)return acc*2+v end, 0), 13) end) -- map T("MapTest", function() check.eq(iterator(ipairs({1,2,3,4})):map(function(i,v) return v*2 end):concat(" "), "2 4 6 8") end) -- filter T("FilterTest", function() check.eq(iterator(ipairs{1,2,3,4,5,6,7}):filter(function(i,v) return v%2==0 end):map(function(i,v)return v end):concat(" "), "2 4 6") end) T("IterableMapTest", function() local t = { Lemon = "sour", Cake = "nice", } local expected = { ["lemon is slightly SOUR"]=0, ["cake is slightly NICE"]=0, } for ingredient, modifier, taste in iterator(pairs(t)):map(function(a, b) return a:lower(),"slightly",b:upper() end) do local str = ingredient .." is ".. modifier .. " " .. taste check.eq(expected[str], 0) expected[str] = expected[str] + 1 end local t = { Lemon = "sour", Cake = "nice", } local expected = { ["cake is very NICE"]=0, ["Cake is slightly nice"]=0, ["lemon is very SOUR"]=0, ["Lemon is slightly sour"]=0, } for ingredient, modifier, taste in iterator(pairs(t)):map(function(a, b) coroutine.yield(a:lower(),"very",b:upper()) return a, "slightly", b end) do local str = ingredient .." is ".. modifier .. " " .. taste check.eq(expected[str], 0) expected[str] = expected[str] + 1 end local idx=1 local expected={2,4,6} for v in iterator(ipairs{1,2,3,4,5,6,7}):filter(function(key,value) return value%2==0 end) do check.eq(v, expected[idx]) idx=idx+1 end for k,v in iterator(ipairs{1,2,3}) do check.eq(k, v) end end) april-ann-0.4.1/packages/basics/lexClass/000077500000000000000000000000001263004425400201755ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/lexClass/binding/000077500000000000000000000000001263004425400216075ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/lexClass/binding/bind_lexclass.lua.cc000066400000000000000000000057271263004425400255230ustar00rootroot00000000000000//BIND_HEADER_C #include "lua_table.h" using namespace AprilUtils; IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(LexClass); //BIND_END //BIND_HEADER_H #include #include "lexclass.h" using namespace AprilUtils; //BIND_END //BIND_LUACLASSNAME LexClass _internal_lexclass_ //BIND_CPP_CLASS LexClass //BIND_CONSTRUCTOR LexClass { LexClass *obj = new LexClass(); LUABIND_RETURN(LexClass, obj); } //BIND_END //BIND_DESTRUCTOR LexClass { } //BIND_END //BIND_METHOD LexClass addPair { const char *lua_word, *lua_outsym; char *word, *outsym; log_float lprob; float prob; check_table_fields(L, 1, "word", "outsym", "prob", 0); LUABIND_GET_TABLE_PARAMETER(1, word, string, lua_word); LUABIND_GET_TABLE_PARAMETER(1, outsym, string, lua_outsym); LUABIND_GET_TABLE_PARAMETER(1, prob, float, prob); lprob = log_float(prob); word = new char[strlen(lua_word)+1]; strcpy(word, lua_word); outsym = new char[strlen(lua_outsym)+1]; strcpy(outsym, lua_outsym); uint32_t ret = obj->addPair(word, outsym, prob); LUABIND_RETURN(uint, ret); } //BIND_END //BIND_METHOD LexClass size { LUABIND_RETURN(uint, obj->size()); } //BIND_END //BIND_METHOD LexClass getWordFromWordId { uint32_t wid; LUABIND_GET_PARAMETER(1, uint, wid); const char *w = obj->getWordFromWordId(wid); LUABIND_RETURN(string, w); } //BIND_END //BIND_METHOD LexClass getWordFromPairId { uint32_t pid; LUABIND_GET_PARAMETER(1, uint, pid); const char *w = obj->getWordFromPairId(pid); LUABIND_RETURN(string, w); } //BIND_END //BIND_METHOD LexClass getOutSymFromOutSymId { uint32_t oid; LUABIND_GET_PARAMETER(1, uint, oid); const char *o = obj->getOutSymFromOutSymId(oid); LUABIND_RETURN(string, o); } //BIND_END //BIND_METHOD LexClass getOutSymFromPairId { uint32_t pid; LUABIND_GET_PARAMETER(1, uint, pid); const char *o = obj->getOutSymFromPairId(pid); LUABIND_RETURN(string, o); } //BIND_END //BIND_METHOD LexClass getWordId { uint32_t wid; const char *w; LUABIND_GET_PARAMETER(1, string, w); if (obj->getWordId(w, wid)) LUABIND_RETURN(uint, wid); else LUABIND_RETURN_NIL(); } //BIND_END //BIND_METHOD LexClass getOutSymId { uint32_t oid; const char *o; LUABIND_GET_PARAMETER(1, string, o); if (obj->getOutSymId(o, oid)) LUABIND_RETURN(uint, oid); else LUABIND_RETURN_NIL(); } //BIND_END //BIND_METHOD LexClass getPairData { uint32_t pair_id; LUABIND_GET_PARAMETER(1, uint, pair_id); LexClass::data_t d = obj->getPairData(pair_id); lua_newtable(L); LUABIND_RETURN_FROM_STACK(-1); lua_pushstring(L, "word"); lua_pushnumber(L, d.word); lua_settable(L, -3); lua_pushstring(L, "outsym"); lua_pushnumber(L, d.outsym); lua_settable(L, -3); lua_pushstring(L, "prob"); lua_pushnumber(L, d.prob.log()); lua_settable(L, -3); } //BIND_END //BIND_METHOD LexClass wordTblSize { LUABIND_RETURN(uint, obj->wordTblSize()); } //BIND_END //BIND_METHOD LexClass outsymTblSize { LUABIND_RETURN(uint, obj->outsymTblSize()); } //BIND_END april-ann-0.4.1/packages/basics/lexClass/c_src/000077500000000000000000000000001263004425400212665ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/lexClass/c_src/lexclass.h000066400000000000000000000105161263004425400232600ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Francisco Zamora-Martinez, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LEXCLASS_H #define LEXCLASS_H #include #include "aux_hash_table.h" #include "hash_table.h" #include "lua_table.h" #include "referenced.h" #include "vector.h" namespace AprilUtils { // OJO! esta tabla empieza en 1. el 0 esta reservado class LexClass : public Referenced { public: struct data_t { uint32_t word, outsym; log_float prob; }; vector data; vector strings; vector string2wid_oid; vector wid2string; vector oid2string; hash string2id; LexClass() { char *aux1 = new char[2]; aux1[0] = '_'; aux1[1] = '\0'; char *aux2 = new char[2]; aux2[0] = '_'; aux2[1] = '\0'; // el 0 esta reservado para palabra vacia addPair(aux1, aux2, log_float::one()); } ~LexClass() { for (unsigned int i=0; i 0) { uint32_t &string_id = string2id[word]; if (string_id == 0) { // no estaba en la tabla string_id = strings.size(); strings.push_back(word); string2wid_oid.push_back(int_pair(0,0)); } else delete[] word; if ((wid=string2wid_oid[string_id].first) == 0) { string2wid_oid[string_id].first = wid2string.size(); wid = wid2string.size(); wid2string.push_back(string_id); } } else wid = 0; if (outsym != 0 && strlen(outsym) > 0) { uint32_t &string_id = string2id[outsym]; if (string_id == 0) { // no estaba en la tabla string_id = strings.size(); strings.push_back(outsym); string2wid_oid.push_back(int_pair(0,0)); } else delete[] outsym; if ((oid=string2wid_oid[string_id].second) == 0) { string2wid_oid[string_id].second = oid2string.size(); oid = oid2string.size(); oid2string.push_back(string_id); } } else oid = 0; data_t d; d.word = wid; d.outsym = oid; d.prob = prob; data.push_back(d); //printf("%u: %s %s (%u %u)\n", //data.size()-1, strings[wid2string[wid]], strings[oid2string[oid]], //wid, oid); return data.size()-1; } unsigned int size() { return data.size() - 1; } const char *getWordFromWordId(uint32_t wid) { return strings[ wid2string[wid]]; } const char *getWordFromPairId(uint32_t pairid) { return getWordFromWordId(data[pairid].word); } const char *getOutSymFromOutSymId(uint32_t oid) { return strings[ oid2string[oid]]; } const char *getOutSymFromPairId(uint32_t pairid) { return getOutSymFromOutSymId(data[pairid].outsym); } bool getWordId(const char *word, uint32_t &wid) { uint32_t *string_id; string_id = string2id.find((char*)word); if (string_id == 0) return false; wid = string2wid_oid[*string_id].first; return true; } bool getOutSymId(const char *outsym, uint32_t &oid) { uint32_t *string_id; string_id = string2id.find((char*)outsym); if (string_id == 0) return false; oid = string2wid_oid[*string_id].second; return true; } data_t getPairData(uint32_t pair_id) { return data[pair_id]; } unsigned int wordTblSize() { return wid2string.size()-1; } unsigned int outsymTblSize() { return oid2string.size()-1; } }; } DECLARE_LUA_TABLE_BIND_SPECIALIZATION(AprilUtils::LexClass); #endif april-ann-0.4.1/packages/basics/lexClass/lua_src/000077500000000000000000000000001263004425400216255ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/lexClass/lua_src/lexClass.lua000066400000000000000000000124171263004425400241130ustar00rootroot00000000000000local lexClass,lexClass_methods = class("lexClass") _G.lexClass = lexClass function lexClass:constructor(voc_id2word) self.cobj = _internal_lexclass_() self.units = {} if voc_id2word then for _,word in ipairs(voc_id2word) do self:addPair{ word = word, } end end end function lexClass_methods:addPair(t) local word = t.word or error ("Falta definir word") local outsym = t.outsym or word local prob = t.prob or 1.0 local units = t.units or {} local rid = self.cobj:addPair{ word=word, outsym=outsym, prob=math.log(prob) } if #units > 0 then self.units[rid] = units end return rid end function lexClass_methods:getWordFromPairId(pairid) return self.cobj:getWordFromPairId(pairid) end function lexClass_methods:getWordFromWordId(wid) return self.cobj:getWordFromWordId(wid) end function lexClass_methods:getOutSymFromPairId(pairid) return self.cobj:getOutSymFromPairId(pairid) end function lexClass_methods:getOutSymFromOutSymId(oid) return self.cobj:getOutSymFromOutSymId(oid) end function lexClass_methods:getWordId(word) return self.cobj:getWordId(word) end function lexClass_methods:getOutSymId(outsym) return self.cobj:getOutSymId(outsym) end -- Outsym [Word] prob t1 t2 t3 ... function lexClass.load(dict_file) local lex = lexClass() for line in dict_file:lines() do local l = string.tokenize(line) local outsym = l[1] local begin_units = 2 local prob = 1 local w = outsym if #l>1 and string.sub(l[2],1,1)=="[" and string.sub(l[2],#l[2],#l[2])=="]" then w = string.sub(l[2], 2, #l[2]-1) begin_units = begin_units + 1 end local units = {} if tonumber(l[begin_units]) ~= nil then prob = tonumber(l[begin_units]) begin_units = begin_units + 1 end for i=begin_units,#l do table.insert(units, l[i]) end -- anyadimos la palabra y toda su informacion local rid = lex:addPair{ word = w, outsym = outsym, prob = prob, units = units, } end return lex end -- para guardar en disco function lexClass_methods:save(f) -- for pairid=1,self.cobj:size() do -- local info = self.cobj:getInfo(pairid) -- -- -- f:write(self.oid2outsym[info.oid] .. " ") -- f:write("[".. self.wid2word[info.wid] .."] ") -- f:write(math.exp(info.prob) .." ") -- f:write(table.concat(info.units, " ")) -- f:write("\n") -- f:flush() -- end -- collectgarbage("collect") error("Deprecated!!! :'( hay que actualizar esta funcion") end function lexClass_methods:getWordVocabulary() local t = {} for i=1,self.cobj:wordTblSize() do table.insert(t, self.cobj:getWordFromWordId(i)) end return t end function lexClass_methods:getOutSymVocabulary() local t = {} for i=1,self.cobj:outsymTblSize() do table.insert(t, self.cobj:getOutSymFromOutSymId(i)) end return t end function lexClass_methods:searchWordsSequenceFromWIDs(wordid_seq) local words={} for i,id in ipairs(wordid_seq) do if id ~= 0 then table.insert(words, self.cobj:getWordFromWordId(id)) end end return words end function lexClass_methods:searchWordsSequence(pairid_seq) local words={} for i,id in ipairs(pairid_seq) do local word = self.cobj:getWordFromPairId(id) if word then if #word ~= 0 then table.insert(words, word) end else table.insert(words,"") end end return words end function lexClass_methods:searchOutSymsSequenceFromOIDs(outsym_seq) error ("Deprecated!!!!") -- local outsyms={} -- for i,id in ipairs(outsym_seq) do -- if id ~= 0 then table.insert(outsyms, self.oid2outsym[id]) end -- end -- return outsyms end function lexClass_methods:searchOutSymsSequence(pairid_seq) local outsyms={} for i,id in ipairs(pairid_seq) do local word = self.cobj:getOutSymFromPairId(id) if word then if #word ~= 0 then table.insert(outsyms,word) end else table.insert(outsyms, "") end end return outsyms end function lexClass_methods:searchWordIdSequence(words, unk_id) local ids={} for i,w in ipairs(words) do local wid = self.cobj:getWordId(w) or unk_id if wid ~= 0 then table.insert(ids, wid) end end return ids end function lexClass_methods:searchWordIdSequenceFromPairID(pairid_seq) local ids={} for i,pid in ipairs(pairid_seq) do local wid = self.cobj:getPairData(pid).word if wid ~= 0 then table.insert(ids, wid) end end return ids end function lexClass_methods:searchOutSymIdSequenceFromPairID(pairid_seq) local ids={} for i,pid in ipairs(pairid_seq) do local oid = self.cobj:getPairData(pid).outsym if oid ~= 0 then table.insert(ids, oid) end end return ids end function lexClass_methods:wordTblSize() return self.cobj:wordTblSize() end function lexClass_methods:outsymTblSize() return self.cobj:outsymTblSize() end function lexClass_methods:pairsTblSize() return self.cobj:size() end function lexClass_methods:getCObject() return self.cobj end function lexClass_methods:getData(pair_id) local t = self.cobj:getPairData(pair_id) t.units = self.units[pair_id] or {} return t end function lexClass_methods:getPair(pair_id) local wid,oid local t = self.cobj:getPairData(pair_id) wid,oid = t.word,t.outsym return wid,oid end april-ann-0.4.1/packages/basics/lexClass/package.lua000066400000000000000000000020771263004425400223010ustar00rootroot00000000000000 package{ name = "lexClass", version = "1.0", depends = { "util" }, keywords = { "lexClass" }, description = "no description available", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_lexclass.lua.cc", dest_dir = "include" } }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", --flags = "-std=c99", not valid for c++!!! dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_lexclass.lua.cc", dest_dir = "build", } }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/mathcore/000077500000000000000000000000001263004425400202215ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/mathcore/binding/000077500000000000000000000000001263004425400216335ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/mathcore/binding/bind_mathcore.lua.cc000066400000000000000000000423501263004425400255240ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_H #include "gpu_mirrored_memory_block.h" using namespace AprilMath; //BIND_END //BIND_HEADER_C #include "bind_april_io.h" #include "bind_complex.h" #include "bind_mathcore.h" #include "cmath_overloads.h" #include "error_print.h" #include "luabindutil.h" #include "luabindmacros.h" #include "maxmin.h" using namespace AprilMath; typedef bool boolean; IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(CharGPUMirroredMemoryBlock); IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(FloatGPUMirroredMemoryBlock); IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(DoubleGPUMirroredMemoryBlock); IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(Int32GPUMirroredMemoryBlock); IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(ComplexFGPUMirroredMemoryBlock); IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(BoolGPUMirroredMemoryBlock); #define MAKE_READ_BLOCK_LUA_METHOD(BlockType, Type) do { \ BlockType *obj = readBlockLuaMethod(L); \ if (obj == 0) { \ luaL_error(L, "Error happens reading from file stream"); \ } \ else { \ lua_push##BlockType(L, obj); \ } \ } while(false) template GPUMirroredMemoryBlock *readBlockLuaMethod(lua_State *L) { AprilUtils::SharedPtr stream; if (lua_isstring(L, 1)) { stream = new InputLuaStringStream(L, 1); } else { stream = lua_toAuxStreamInterface(L,1); if (!stream) luaL_error(L, "Needs a stream as first argument"); } AprilUtils::LuaTable options(L,2); return GPUMirroredMemoryBlock::read(stream.get(), options); } namespace MathCoreBinding { template T luaToFunc(lua_State *L, int n) { return AprilUtils::LuaTable::convertTo(L,n); } } namespace AprilMath { #define FUNCTION_NAME "Constructor" template void GPUMirroredMemoryBlockConstructor(lua_State *L, GPUMirroredMemoryBlock *&obj) { unsigned int N; if (lua_istable(L,1)) N = lua_rawlen(L,1); else LUABIND_GET_PARAMETER(1,uint,N); obj = new GPUMirroredMemoryBlock(N); if (lua_istable(L,1)) { T *ptr = obj->getPPALForWrite(); for (unsigned int i=0; i(L, -1); lua_pop(L,1); } } } #undef FUNCTION_NAME #define FUNCTION_NAME "raw_set" template void GPUMirroredMemoryBlockSet(lua_State *L, GPUMirroredMemoryBlock *obj) { T value; unsigned int i; LUABIND_GET_PARAMETER(1,uint,i); value = MathCoreBinding::luaToFunc(L, 2); if (i >= obj->getSize()) ERROR_EXIT(128, "Index out of bounds\n"); T *ptr = obj->getPPALForWrite(); ptr[i] = value; } #undef FUNCTION_NAME #define FUNCTION_NAME "raw_get" template T GPUMirroredMemoryBlockGet(lua_State *L, GPUMirroredMemoryBlock *obj) { unsigned int i; LUABIND_GET_PARAMETER(1,uint,i); if (i >= obj->getSize()) ERROR_EXIT(128, "Index out of bounds\n"); const T *ptr = obj->getPPALForRead(); return ptr[i]; } #undef FUNCTION_NAME } // namespace AprilMath //BIND_END //BIND_FUNCTION mathcore.set_mmap_allocation { bool v; LUABIND_CHECK_ARGN(==,1); LUABIND_GET_PARAMETER(1, bool, v); GPUMirroredMemoryBlockBase::setUseMMapAllocation(v); } //BIND_END //BIND_FUNCTION mathcore.get_mmap_allocation { LUABIND_RETURN(bool, GPUMirroredMemoryBlockBase::getUseMMapAllocation()); } //BIND_END //BIND_FUNCTION mathcore.set_max_pool_size { int max_pool_size; LUABIND_CHECK_ARGN(==,1); LUABIND_GET_PARAMETER(1, int, max_pool_size); #ifndef NO_POOL GPUMirroredMemoryBlockBase:: changeMaxPoolSize(static_cast(max_pool_size)); #endif } //BIND_END //BIND_FUNCTION mathcore.set_use_cuda_default { bool v; LUABIND_CHECK_ARGN(==,1); LUABIND_GET_PARAMETER(1, bool, v); GPUMirroredMemoryBlockBase::USE_CUDA_DEFAULT = v; } //BIND_END //BIND_FUNCTION mathcore.get_use_cuda_default { LUABIND_RETURN(bool, GPUMirroredMemoryBlockBase::USE_CUDA_DEFAULT); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME Serializable aprilio.serializable //////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME FloatGPUMirroredMemoryBlock mathcore.block.float //BIND_CPP_CLASS FloatGPUMirroredMemoryBlock //BIND_SUBCLASS_OF FloatGPUMirroredMemoryBlock Serializable //BIND_CONSTRUCTOR FloatGPUMirroredMemoryBlock { LUABIND_CHECK_ARGN(==,1); GPUMirroredMemoryBlockConstructor(L,obj); LUABIND_RETURN(FloatGPUMirroredMemoryBlock,obj); } //BIND_END //BIND_CLASS_METHOD FloatGPUMirroredMemoryBlock read { MAKE_READ_BLOCK_LUA_METHOD(FloatGPUMirroredMemoryBlock, float); LUABIND_INCREASE_NUM_RETURNS(1); } //BIND_END //BIND_METHOD FloatGPUMirroredMemoryBlock size { LUABIND_RETURN(uint,obj->getSize()); } //BIND_END //BIND_METHOD FloatGPUMirroredMemoryBlock raw_set { LUABIND_CHECK_ARGN(==,2); GPUMirroredMemoryBlockSet(L,obj); LUABIND_RETURN(FloatGPUMirroredMemoryBlock,obj); } //BIND_END //BIND_METHOD FloatGPUMirroredMemoryBlock raw_get { LUABIND_RETURN(float,GPUMirroredMemoryBlockGet(L,obj)); } //BIND_END //BIND_METHOD FloatGPUMirroredMemoryBlock get_reference_string { char buff[128]; sprintf(buff,"data= %p", (void*)obj); LUABIND_RETURN(string, buff); } //BIND_END //BIND_METHOD FloatGPUMirroredMemoryBlock copy { FloatGPUMirroredMemoryBlock *other; LUABIND_GET_PARAMETER(1, FloatGPUMirroredMemoryBlock, other); obj->copyFromBlock(0, other, 0, AprilUtils::min(obj->getSize(),other->getSize())); LUABIND_RETURN(FloatGPUMirroredMemoryBlock, obj); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME DoubleGPUMirroredMemoryBlock mathcore.block.double //BIND_CPP_CLASS DoubleGPUMirroredMemoryBlock //BIND_SUBCLASS_OF DoubleGPUMirroredMemoryBlock Serializable //BIND_CONSTRUCTOR DoubleGPUMirroredMemoryBlock { LUABIND_CHECK_ARGN(==,1); GPUMirroredMemoryBlockConstructor(L,obj); LUABIND_RETURN(DoubleGPUMirroredMemoryBlock,obj); } //BIND_END //BIND_CLASS_METHOD DoubleGPUMirroredMemoryBlock read { MAKE_READ_BLOCK_LUA_METHOD(DoubleGPUMirroredMemoryBlock, double); LUABIND_INCREASE_NUM_RETURNS(1); } //BIND_END //BIND_METHOD DoubleGPUMirroredMemoryBlock size { LUABIND_RETURN(uint,obj->getSize()); } //BIND_END //BIND_METHOD DoubleGPUMirroredMemoryBlock raw_set { LUABIND_CHECK_ARGN(==,2); GPUMirroredMemoryBlockSet(L,obj); LUABIND_RETURN(DoubleGPUMirroredMemoryBlock,obj); } //BIND_END //BIND_METHOD DoubleGPUMirroredMemoryBlock raw_get { LUABIND_RETURN(double,GPUMirroredMemoryBlockGet(L,obj)); } //BIND_END //BIND_METHOD DoubleGPUMirroredMemoryBlock get_reference_string { char buff[128]; sprintf(buff,"data= %p", (void*)obj); LUABIND_RETURN(string, buff); } //BIND_END //BIND_METHOD DoubleGPUMirroredMemoryBlock copy { DoubleGPUMirroredMemoryBlock *other; LUABIND_GET_PARAMETER(1, DoubleGPUMirroredMemoryBlock, other); obj->copyFromBlock(0, other, 0, AprilUtils::min(obj->getSize(),other->getSize())); LUABIND_RETURN(DoubleGPUMirroredMemoryBlock, obj); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME Int32GPUMirroredMemoryBlock mathcore.block.int32 //BIND_CPP_CLASS Int32GPUMirroredMemoryBlock //BIND_SUBCLASS_OF Int32GPUMirroredMemoryBlock Serializable //BIND_CONSTRUCTOR Int32GPUMirroredMemoryBlock { LUABIND_CHECK_ARGN(==,1); GPUMirroredMemoryBlockConstructor(L,obj); LUABIND_RETURN(Int32GPUMirroredMemoryBlock,obj); } //BIND_END //BIND_CLASS_METHOD Int32GPUMirroredMemoryBlock read { MAKE_READ_BLOCK_LUA_METHOD(Int32GPUMirroredMemoryBlock, int); LUABIND_INCREASE_NUM_RETURNS(1); } //BIND_END //BIND_METHOD Int32GPUMirroredMemoryBlock size { LUABIND_RETURN(uint,obj->getSize()); } //BIND_END //BIND_METHOD Int32GPUMirroredMemoryBlock raw_set { LUABIND_CHECK_ARGN(==,2); GPUMirroredMemoryBlockSet(L,obj); LUABIND_RETURN(Int32GPUMirroredMemoryBlock,obj); } //BIND_END //BIND_METHOD Int32GPUMirroredMemoryBlock raw_get { LUABIND_RETURN(int,GPUMirroredMemoryBlockGet(L,obj)); } //BIND_END //BIND_METHOD Int32GPUMirroredMemoryBlock get_reference_string { char buff[128]; sprintf(buff,"data= %p", (void*)obj); LUABIND_RETURN(string, buff); } //BIND_END //BIND_METHOD Int32GPUMirroredMemoryBlock copy { Int32GPUMirroredMemoryBlock *other; LUABIND_GET_PARAMETER(1, Int32GPUMirroredMemoryBlock, other); obj->copyFromBlock(0, other, 0, AprilUtils::min(obj->getSize(),other->getSize())); LUABIND_RETURN(Int32GPUMirroredMemoryBlock, obj); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME BoolGPUMirroredMemoryBlock mathcore.block.bool //BIND_CPP_CLASS BoolGPUMirroredMemoryBlock //BIND_SUBCLASS_OF BoolGPUMirroredMemoryBlock Serializable //BIND_CONSTRUCTOR BoolGPUMirroredMemoryBlock { LUABIND_CHECK_ARGN(==,1); GPUMirroredMemoryBlockConstructor(L,obj); LUABIND_RETURN(BoolGPUMirroredMemoryBlock,obj); } //BIND_END //BIND_CLASS_METHOD BoolGPUMirroredMemoryBlock read { MAKE_READ_BLOCK_LUA_METHOD(BoolGPUMirroredMemoryBlock, boolean); LUABIND_INCREASE_NUM_RETURNS(1); } //BIND_END //BIND_METHOD BoolGPUMirroredMemoryBlock size { LUABIND_RETURN(uint,obj->getSize()); } //BIND_END //BIND_METHOD BoolGPUMirroredMemoryBlock raw_set { LUABIND_CHECK_ARGN(==,2); GPUMirroredMemoryBlockSet(L,obj); LUABIND_RETURN(BoolGPUMirroredMemoryBlock,obj); } //BIND_END //BIND_METHOD BoolGPUMirroredMemoryBlock raw_get { LUABIND_RETURN(boolean,GPUMirroredMemoryBlockGet(L,obj)); } //BIND_END //BIND_METHOD BoolGPUMirroredMemoryBlock get_reference_string { char buff[128]; sprintf(buff,"data= %p", (void*)obj); LUABIND_RETURN(string, buff); } //BIND_END //BIND_METHOD BoolGPUMirroredMemoryBlock copy { BoolGPUMirroredMemoryBlock *other; LUABIND_GET_PARAMETER(1, BoolGPUMirroredMemoryBlock, other); obj->copyFromBlock(0, other, 0, AprilUtils::min(obj->getSize(),other->getSize())); LUABIND_RETURN(BoolGPUMirroredMemoryBlock, obj); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME CharGPUMirroredMemoryBlock mathcore.block.char //BIND_CPP_CLASS CharGPUMirroredMemoryBlock //BIND_SUBCLASS_OF CharGPUMirroredMemoryBlock Serializable //BIND_CONSTRUCTOR CharGPUMirroredMemoryBlock { LUABIND_CHECK_ARGN(==,1); GPUMirroredMemoryBlockConstructor(L,obj); LUABIND_RETURN(CharGPUMirroredMemoryBlock,obj); } //BIND_END //BIND_CLASS_METHOD CharGPUMirroredMemoryBlock read { MAKE_READ_BLOCK_LUA_METHOD(CharGPUMirroredMemoryBlock, char); LUABIND_INCREASE_NUM_RETURNS(1); } //BIND_END //BIND_METHOD CharGPUMirroredMemoryBlock size { LUABIND_RETURN(uint,obj->getSize()); } //BIND_END //BIND_METHOD CharGPUMirroredMemoryBlock raw_set { LUABIND_CHECK_ARGN(==,2); GPUMirroredMemoryBlockSet(L,obj); LUABIND_RETURN(CharGPUMirroredMemoryBlock,obj); } //BIND_END //BIND_METHOD CharGPUMirroredMemoryBlock raw_get { char c = GPUMirroredMemoryBlockGet(L,obj); lua_pushlstring(L, &c, 1); LUABIND_INCREASE_NUM_RETURNS(1); } //BIND_END //BIND_METHOD CharGPUMirroredMemoryBlock get_reference_string { char buff[128]; sprintf(buff,"data= %p", (void*)obj); LUABIND_RETURN(string, buff); } //BIND_END //BIND_METHOD CharGPUMirroredMemoryBlock copy { CharGPUMirroredMemoryBlock *other; LUABIND_GET_PARAMETER(1, CharGPUMirroredMemoryBlock, other); obj->copyFromBlock(0, other, 0, AprilUtils::min(obj->getSize(),other->getSize())); LUABIND_RETURN(CharGPUMirroredMemoryBlock, obj); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME ComplexFGPUMirroredMemoryBlock mathcore.block.complex //BIND_CPP_CLASS ComplexFGPUMirroredMemoryBlock //BIND_SUBCLASS_OF ComplexFGPUMirroredMemoryBlock Serializable //BIND_CONSTRUCTOR ComplexFGPUMirroredMemoryBlock { LUABIND_CHECK_ARGN(==,1); GPUMirroredMemoryBlockConstructor(L,obj); LUABIND_RETURN(ComplexFGPUMirroredMemoryBlock,obj); } //BIND_END //BIND_CLASS_METHOD ComplexFGPUMirroredMemoryBlock read { MAKE_READ_BLOCK_LUA_METHOD(ComplexFGPUMirroredMemoryBlock, ComplexF); LUABIND_INCREASE_NUM_RETURNS(1); } //BIND_END //BIND_METHOD ComplexFGPUMirroredMemoryBlock size { LUABIND_RETURN(uint,obj->getSize()); } //BIND_END //BIND_METHOD ComplexFGPUMirroredMemoryBlock raw_set { LUABIND_CHECK_ARGN(==,2); GPUMirroredMemoryBlockSet(L,obj); LUABIND_RETURN(ComplexFGPUMirroredMemoryBlock,obj); } //BIND_END //BIND_METHOD ComplexFGPUMirroredMemoryBlock raw_get { LUABIND_RETURN(ComplexF,GPUMirroredMemoryBlockGet(L,obj)); } //BIND_END //BIND_METHOD ComplexFGPUMirroredMemoryBlock get_reference_string { char buff[128]; sprintf(buff,"data= %p", (void*)obj); LUABIND_RETURN(string, buff); } //BIND_END //BIND_METHOD ComplexFGPUMirroredMemoryBlock copy { ComplexFGPUMirroredMemoryBlock *other; LUABIND_GET_PARAMETER(1, ComplexFGPUMirroredMemoryBlock, other); obj->copyFromBlock(0, other, 0, AprilUtils::min(obj->getSize(),other->getSize())); LUABIND_RETURN(ComplexFGPUMirroredMemoryBlock, obj); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_FUNCTION mathcore.limits.float.max { LUABIND_RETURN(float,Limits::max()); } //BIND_END //BIND_FUNCTION mathcore.limits.float.min { LUABIND_RETURN(float,Limits::min()); } //BIND_END //BIND_FUNCTION mathcore.limits.float.lowest { LUABIND_RETURN(float,Limits::lowest()); } //BIND_END //BIND_FUNCTION mathcore.limits.float.epsilon { LUABIND_RETURN(float,Limits::epsilon()); } //BIND_END //BIND_FUNCTION mathcore.limits.float.infinity { LUABIND_RETURN(float,Limits::infinity()); } //BIND_END //BIND_FUNCTION mathcore.limits.float.quiet_NaN { LUABIND_RETURN(float,Limits::quiet_NaN()); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_FUNCTION mathcore.limits.double.max { LUABIND_RETURN(double,Limits::max()); } //BIND_END //BIND_FUNCTION mathcore.limits.double.min { LUABIND_RETURN(double,Limits::min()); } //BIND_END //BIND_FUNCTION mathcore.limits.double.lowest { LUABIND_RETURN(double,Limits::lowest()); } //BIND_END //BIND_FUNCTION mathcore.limits.double.epsilon { LUABIND_RETURN(double,Limits::epsilon()); } //BIND_END //BIND_FUNCTION mathcore.limits.double.infinity { LUABIND_RETURN(double,Limits::infinity()); } //BIND_END //BIND_FUNCTION mathcore.limits.double.quiet_NaN { LUABIND_RETURN(double,Limits::quiet_NaN()); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_FUNCTION mathcore.limits.int32.max { LUABIND_RETURN(int,Limits::max()); } //BIND_END //BIND_FUNCTION mathcore.limits.int32.min { LUABIND_RETURN(int,Limits::min()); } //BIND_END //BIND_FUNCTION mathcore.limits.int32.lowest { LUABIND_RETURN(int,Limits::lowest()); } //BIND_END //BIND_FUNCTION mathcore.limits.int32.epsilon { LUABIND_RETURN(int,Limits::epsilon()); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_FUNCTION mathcore.limits.char.max { LUABIND_RETURN(char,Limits::max()); } //BIND_END //BIND_FUNCTION mathcore.limits.char.min { LUABIND_RETURN(char,Limits::min()); } //BIND_END //BIND_FUNCTION mathcore.limits.char.lowest { LUABIND_RETURN(char,Limits::lowest()); } //BIND_END //BIND_FUNCTION mathcore.limits.char.epsilon { LUABIND_RETURN(char,Limits::epsilon()); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_FUNCTION mathcore.limits.complex.max { LUABIND_RETURN(ComplexF,Limits::max()); } //BIND_END //BIND_FUNCTION mathcore.limits.complex.min { LUABIND_RETURN(ComplexF,Limits::min()); } //BIND_END //BIND_FUNCTION mathcore.limits.complex.lowest { LUABIND_RETURN(ComplexF,Limits::lowest()); } //BIND_END //BIND_FUNCTION mathcore.limits.complex.epsilon { LUABIND_RETURN(ComplexF,Limits::epsilon()); } //BIND_END //BIND_FUNCTION mathcore.limits.complex.infinity { LUABIND_RETURN(ComplexF,Limits::infinity()); } //BIND_END //BIND_FUNCTION mathcore.limits.complex.quiet_NaN { LUABIND_RETURN(ComplexF,Limits::quiet_NaN()); } //BIND_END april-ann-0.4.1/packages/basics/mathcore/c_src/000077500000000000000000000000001263004425400213125ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/mathcore/c_src/axpy.cu000066400000000000000000000424001263004425400226240ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "cblas_headers.h" #include "cuda_utils.h" #include "unused_variable.h" namespace AprilMath { #ifdef USE_CUDA namespace CUDA { /*************************************** ************** CUDA SECTION *********** ***************************************/ cublasStatus_t wrapperCublasAxpy(cublasHandle_t &handle, int N, float *alpha, const float *x_mem, unsigned int x_inc, float *y_mem, unsigned int y_inc) { return cublasSaxpy(handle, N, alpha, x_mem, x_inc, y_mem, y_inc); } cublasStatus_t wrapperCublasAxpy(cublasHandle_t &handle, int N, double *alpha, const double *x_mem, unsigned int x_inc, double *y_mem, unsigned int y_inc) { return cublasDaxpy(handle, N, alpha, x_mem, x_inc, y_mem, y_inc); } cublasStatus_t wrapperCublasAxpy(cublasHandle_t &handle, int N, ComplexF *alpha, const ComplexF *x_mem, unsigned int x_inc, ComplexF *y_mem, unsigned int y_inc) { return cublasCaxpy(handle, N, reinterpret_cast(alpha), reinterpret_cast(x_mem), x_inc, reinterpret_cast(y_mem), y_inc); } // Cusparse wrappers cusparseStatus_t wrapperCusparseAxpy(cusparseHandle_t &handle, int NNZ, float *alpha, const float *x_values_mem, const int *x_indices_mem, float *y_mem) { return cusparseSaxpyi(handle, NNZ, alpha, x_values_mem, x_indices_mem, y_mem, CUSPARSE_INDEX_BASE_ZERO); } cusparseStatus_t wrapperCusparseAxpy(cusparseHandle_t &handle, int NNZ, double *alpha, const double *x_values_mem, const int *x_indices_mem, double *y_mem) { return cusparseDaxpyi(handle, NNZ, alpha, x_values_mem, x_indices_mem, y_mem, CUSPARSE_INDEX_BASE_ZERO); } cusparseStatus_t wrapperCusparseAxpy(cusparseHandle_t &handle, int NNZ, ComplexF *alpha, const ComplexF *x_values_mem, const int *x_indices_mem, ComplexF *y_mem) { return cusparseCaxpyi(handle, NNZ, reinterpret_cast(alpha), reinterpret_cast(x_values_mem), x_indices_mem, reinterpret_cast(y_mem), CUSPARSE_INDEX_BASE_ZERO); } //////////////////////////////////////////////////////////////////////////// template __global__ void axpyLoopKernel(unsigned int N, T alpha, const T *x_mem, unsigned int x_inc, T *y_mem, unsigned int y_inc, unsigned int times, unsigned int x_ld, unsigned int y_ld) { unsigned int matrix_x_pos, matrix_y_pos; matrix_x_pos = blockIdx.x*blockDim.x + threadIdx.x; matrix_y_pos = blockIdx.y*blockDim.y + threadIdx.y; if (matrix_x_pos < times && matrix_y_pos < N) { unsigned int index_x = matrix_x_pos*x_ld + matrix_y_pos*x_inc; unsigned int index_y = matrix_x_pos*y_ld + matrix_y_pos*y_inc; T val = alpha * x_mem[index_x]; if (y_ld == 0) { // This loop is used to synchronize the threads for accessing // the global memory where they write the results. The loop // gets all the values from the threads at the index X in // the current block, synchronizing the access to Y. for (unsigned int i=0; i void wrapperCblasAxpyi(int NNZ, T alpha, const T *x_mem, const int *x_ind, T *y_mem, unsigned int y_inc) { if (alpha != AprilMath::Limits::one()) { for (int i=0; i void doAxpy(int N, T alpha, const GPUMirroredMemoryBlock* x, unsigned int x_inc, unsigned int x_shift, GPUMirroredMemoryBlock* y, unsigned int y_inc, unsigned int y_shift, bool use_gpu) { const T *x_mem; T *y_mem; #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { cublasStatus_t status; cublasHandle_t handle = CUDA::GPUHelper::getHandler(); //printf("Doing a saxpy with comp=1 & cuda=1\n"); x_mem = x->getGPUForRead() + x_shift; y_mem = y->getGPUForReadAndWrite() + y_shift; status = cublasSetStream(handle, CUDA::GPUHelper::getCurrentStream()); checkCublasError(status); status = CUDA::wrapperCublasAxpy(handle, N, &alpha, x_mem, x_inc, y_mem, y_inc); checkCublasError(status); } else { //printf("Doing a saxpy with comp=1 & cuda=0\n"); #endif #ifndef USE_CUDA //printf("Doing a saxpy with comp=0 & cuda=0\n"); #endif x_mem = x->getPPALForRead() + x_shift; y_mem = y->getPPALForReadAndWrite() + y_shift; wrapperCblasAxpy(N, alpha, x_mem, x_inc, y_mem, y_inc); #ifdef USE_CUDA } #endif } template void doAxpyLoop(int N, T alpha, GPUMirroredMemoryBlock* x, unsigned int x_inc, unsigned int x_shift, GPUMirroredMemoryBlock* y, unsigned int y_inc, unsigned int y_shift, unsigned int times, const unsigned int x_stride, const unsigned int y_stride, bool use_gpu) { const T *x_mem; T *y_mem; #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { x_mem = x->getGPUForRead() + x_shift; y_mem = y->getGPUForReadAndWrite() + y_shift; const unsigned int MAX_THREADS = CUDA::GPUHelper::getMaxThreadsPerBlock(); dim3 block, grid; // Number of threads on each block dimension block.x = min(MAX_THREADS, times); block.y = min(MAX_THREADS/block.x, N); block.z = 1; grid.x = (times/block.x + (times % block.x ? 1 : 0)); grid.y = (N/block.y + (N % block.y ? 1 : 0)); grid.z = 1; CUDA::axpyLoopKernel<<>> (N, alpha, x_mem, x_inc, y_mem, y_inc, times, x_stride, y_stride); } else { //printf("Doing a saxpy loop with comp=1 & cuda=0\n"); #endif #ifndef USE_CUDA //printf("Doing a saxpy loop with comp=0 & cuda=0\n"); #endif x_mem = x->getPPALForRead() + x_shift; y_mem = y->getPPALForReadAndWrite() + y_shift; for (unsigned int i = 0; i < times; i++) wrapperCblasAxpy(N, alpha, x_mem + i * x_stride, x_inc, y_mem + i * y_stride, y_inc); #ifdef USE_CUDA } #endif } template void doSparseAxpy(int NNZ, T alpha, const GPUMirroredMemoryBlock *x_values, const Int32GPUMirroredMemoryBlock *x_indices, GPUMirroredMemoryBlock* y, unsigned int x_shift, unsigned int y_shift, unsigned int y_inc, bool use_gpu) { const T *x_values_mem; const int *x_indices_mem; T *y_mem; #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { if (y_inc != 1) { ERROR_EXIT(128, "sparse AXPY not implemented for stride != 1\n"); } cusparseStatus_t status; cusparseHandle_t handle = CUDA::GPUHelper::getSparseHandler(); //printf("Doing a saxpy with comp=1 & cuda=1\n"); x_values_mem = x_values->getGPUForRead() + x_shift; x_indices_mem = x_indices->getGPUForRead() + x_shift; y_mem = y->getGPUForReadAndWrite() + y_shift; status = cusparseSetStream(handle, CUDA::GPUHelper::getCurrentStream()); checkCusparseError(status); status = CUDA::wrapperCusparseAxpy(handle, NNZ, &alpha, x_values_mem, x_indices_mem, y_mem); checkCusparseError(status); } else { #endif x_values_mem = x_values->getPPALForRead() + x_shift; x_indices_mem = x_indices->getPPALForRead() + x_shift; y_mem = y->getPPALForReadAndWrite() + y_shift; wrapperCblasAxpyi(NNZ, alpha, x_values_mem, x_indices_mem, y_mem, y_inc); #ifdef USE_CUDA } #endif } template void doAxpy(int N, float alpha, const GPUMirroredMemoryBlock* x, unsigned int x_shift, unsigned int x_inc, GPUMirroredMemoryBlock* y, unsigned int y_shift, unsigned int y_inc, bool use_gpu); template void doAxpy(int N, double alpha, const GPUMirroredMemoryBlock* x, unsigned int x_shift, unsigned int x_inc, GPUMirroredMemoryBlock* y, unsigned int y_shift, unsigned int y_inc, bool use_gpu); template void doAxpy(int N, ComplexF alpha, const GPUMirroredMemoryBlock* x, unsigned int x_shift, unsigned int x_inc, GPUMirroredMemoryBlock* y, unsigned int y_shift, unsigned int y_inc, bool use_gpu); template void doSparseAxpy(int NNZ, float alpha, const GPUMirroredMemoryBlock *x_values, const Int32GPUMirroredMemoryBlock *x_indices, GPUMirroredMemoryBlock* y, unsigned int x_shift, unsigned int y_shift, unsigned int y_inc, bool use_gpu); template void doSparseAxpy(int NNZ, double alpha, const GPUMirroredMemoryBlock *x_values, const Int32GPUMirroredMemoryBlock *x_indices, GPUMirroredMemoryBlock* y, unsigned int x_shift, unsigned int y_shift, unsigned int y_inc, bool use_gpu); template void doSparseAxpy(int NNZ, ComplexF alpha, const GPUMirroredMemoryBlock *x_values, const Int32GPUMirroredMemoryBlock *x_indices, GPUMirroredMemoryBlock* y, unsigned int x_shift, unsigned int y_shift, unsigned int y_inc, bool use_gpu); template void doAxpyLoop(int N, float alpha, GPUMirroredMemoryBlock* x, unsigned int x_inc, unsigned int x_shift, GPUMirroredMemoryBlock* y, unsigned int y_inc, unsigned int y_shift, unsigned int times, const unsigned int x_stride, const unsigned int y_stride, bool use_gpu); template void doAxpyLoop(int N, double alpha, GPUMirroredMemoryBlock* x, unsigned int x_inc, unsigned int x_shift, GPUMirroredMemoryBlock* y, unsigned int y_inc, unsigned int y_shift, unsigned int times, const unsigned int x_stride, const unsigned int y_stride, bool use_gpu); template void doAxpyLoop(int N, ComplexF alpha, GPUMirroredMemoryBlock* x, unsigned int x_inc, unsigned int x_shift, GPUMirroredMemoryBlock* y, unsigned int y_inc, unsigned int y_shift, unsigned int times, const unsigned int x_stride, const unsigned int y_stride, bool use_gpu); } // namespace AprilMath april-ann-0.4.1/packages/basics/mathcore/c_src/cblas_headers.cc000066400000000000000000000611471263004425400244110ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "swap.h" #include "april_assert.h" #include "unused_variable.h" #include "cblas_headers.h" #include "error_print.h" using AprilUtils::swap; using AprilMath::ComplexF; #ifdef ADHOC_BLAS void cblas_sgemv(CBLAS_ORDER order, CBLAS_TRANSPOSE a_transpose, int m, int n, float alpha, const float *a, unsigned int a_inc, const float *x, unsigned int x_inc, float beta, float *y, unsigned int y_inc) { if (m == 0 || n == 0) return; if (alpha == 0.0f && beta == 1.0f) return; int cols, rows; if (a_transpose == CblasNoTrans) { cols = n; rows = m; } else { cols = m; rows = n; } // y = beta * y if (beta == 0.0f) { unsigned int y_pos = 0; for (int i=0; i void generic_cblas_axpyi(int NNZ, T alpha, const T *x_values_mem, const int *x_indices_mem, T *y_mem) { for (int i=0; i void generic_cblas_sparse_mm(CBLAS_ORDER major_order, SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, CBLAS_TRANSPOSE c_transpose, int m, int n, int k, T alpha, const T *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const T *b_mem, int b_inc, T beta, T *c_mem, int c_inc) { UNUSED_VARIABLE(k); if (a_transpose == CblasTrans) { if (sparse_format == CSR_FORMAT) sparse_format = CSC_FORMAT; else sparse_format = CSR_FORMAT; } int b_stride[2] = { b_inc, 1 }; int c_stride[2] = { c_inc, 1 }; if ( (b_transpose == CblasTrans && major_order == CblasRowMajor) || (b_transpose == CblasNoTrans && major_order == CblasColMajor) ) swap(b_stride[0], b_stride[1]); if ( (c_transpose == CblasTrans && major_order == CblasRowMajor) || (c_transpose == CblasNoTrans && major_order == CblasColMajor) ) swap(c_stride[0], c_stride[1]); if (sparse_format == CSR_FORMAT) { // C = beta C + alpha A*B for (int dest_row=0; dest_row void generic_cblas_sparse_mv(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, T alpha, const T *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const T *x_mem, int x_inc, T beta, T *y_mem, int y_inc) { if (a_transpose == CblasTrans) { if (sparse_format == CSR_FORMAT) sparse_format = CSC_FORMAT; else sparse_format = CSR_FORMAT; } int y_size = (a_transpose==CblasNoTrans)?(m):(n); int x_size = (a_transpose==CblasNoTrans)?(n):(m); if (sparse_format == CSR_FORMAT) { for (int dest=0; dest #error "MKL spblas mm operation is not implemented" // FIXME: finish it using a more general multiplication function void cblas_sparse_mm(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, int k, float alpha, const float *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const float *b_mem, int b_inc, float beta, float *c_mem, int c_inc) { char descrA[6]; descrA[0] = 'g'; descrA[3]='c'; char trans = (a_transpose == CblasTrans) ? 't' : 'n'; switch(sparse_format) { case CSR_FORMAT: mkl_scsrmm(&trans, &m, &n, &k, &alpha, descrA, const_cast(a_values_mem), const_cast(a_indices_mem), const_cast(a_first_index_mem), const_cast(a_first_index_mem+1), const_cast(b_mem), &b_inc, &beta, const_cast(c_mem), &c_inc); break; case CSC_FORMAT: mkl_scscmm(&trans, &m, &n, &k, &alpha, descrA, const_cast(a_values_mem), const_cast(a_indices_mem), const_cast(a_first_index_mem), const_cast(a_first_index_mem+1), const_cast(b_mem), &b_inc, &beta, const_cast(c_mem), &c_inc); break; default: ERROR_EXIT(128, "Incorrect sparse format\n"); } } void cblas_sparse_mm(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, int k, double alpha, const double *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const double *b_mem, int b_inc, double beta, double *c_mem, int c_inc) { char descrA[6]; descrA[0] = 'g'; descrA[3]='c'; char trans = (a_transpose == CblasTrans) ? 't' : 'n'; switch(sparse_format) { case CSR_FORMAT: mkl_dcsrmm(&trans, &m, &n, &k, &alpha, descrA, const_cast(a_values_mem), const_cast(a_indices_mem), const_cast(a_first_index_mem), const_cast(a_first_index_mem+1), const_cast(b_mem), &b_inc, &beta, const_cast(c_mem), &c_inc); break; case CSC_FORMAT: mkl_dcscmm(&trans, &m, &n, &k, &alpha, descrA, const_cast(a_values_mem), const_cast(a_indices_mem), const_cast(a_first_index_mem), const_cast(a_first_index_mem+1), const_cast(b_mem), &b_inc, &beta, const_cast(c_mem), &c_inc); break; default: ERROR_EXIT(128, "Incorrect sparse format\n"); } } void cblas_sparse_mm(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, int k, ComplexF alpha, const ComplexF *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const ComplexF *b_mem, int b_inc, ComplexF beta, ComplexF *c_mem, int c_inc) { char descrA[6]; descrA[0] = 'g'; descrA[3]='c'; char trans = (a_transpose == CblasTrans) ? 't' : 'n'; switch(sparse_format) { case CSR_FORMAT: mkl_ccsrmm(&trans, &m, &n, &k, reinterpret_cast(&alpha), descrA, reinterpret_cast(const_cast(a_values_mem)), const_cast(a_indices_mem), const_cast(a_first_index_mem), const_cast(a_first_index_mem+1), reinterpret_cast(const_cast(b_mem)), &b_inc, reinterpret_cast(&beta), reinterpret_cast(const_cast(c_mem)), &c_inc); break; case CSC_FORMAT: mkl_ccscmm(&trans, &m, &n, &k, reinterpret_cast(&alpha), descrA, reinterpret_cast(const_cast(a_values_mem)), const_cast(a_indices_mem), const_cast(a_first_index_mem), const_cast(a_first_index_mem+1), reinterpret_cast(const_cast(b_mem)), &b_inc, reinterpret_cast(&beta), reinterpret_cast(const_cast(c_mem)), &c_inc); break; default: ERROR_EXIT(128, "Incorrect sparse format\n"); } } void cblas_sparse_mv(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, float alpha, const float *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const float *x_mem, int x_inc, float beta, float *y_mem, int y_inc) { if ((x_inc!=1) || (y_inc!=1)) ERROR_EXIT(128, "Impossible to execute sparse gemv with MKL and " "non-contiguous vectors\n"); char descrA[6]; descrA[0] = 'g'; descrA[3]='c'; char trans = (a_transpose == CblasTrans) ? 't' : 'n'; switch(sparse_format) { case CSR_FORMAT: mkl_scsrmv(&trans, &m, &n, &alpha, descrA, const_cast(a_values_mem), const_cast(a_indices_mem), const_cast(a_first_index_mem), const_cast(a_first_index_mem+1), const_cast(x_mem), &beta, const_cast(y_mem)); break; case CSC_FORMAT: mkl_scscmv(&trans, &m, &n, &alpha, descrA, const_cast(a_values_mem), const_cast(a_indices_mem), const_cast(a_first_index_mem), const_cast(a_first_index_mem+1), const_cast(x_mem), &beta, const_cast(y_mem)); break; default: ERROR_EXIT(128, "Incorrect sparse format\n"); } } void cblas_sparse_mv(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, double alpha, const double *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const double *x_mem, int x_inc, double beta, double *y_mem, int y_inc) { if ((x_inc!=1) || (y_inc!=1)) ERROR_EXIT(128, "Impossible to execute sparse gemv with MKL and " "non-contiguous vectors\n"); char descrA[6]; descrA[0] = 'g'; descrA[3]='c'; char trans = (a_transpose == CblasTrans) ? 't' : 'n'; switch(sparse_format) { case CSR_FORMAT: mkl_dcsrmv(&trans, &m, &n, &alpha, descrA, const_cast(a_values_mem), const_cast(a_indices_mem), const_cast(a_first_index_mem), const_cast(a_first_index_mem+1), const_cast(x_mem), &beta, const_cast(y_mem)); break; case CSC_FORMAT: mkl_dcscmv(&trans, &m, &n, &alpha, descrA, const_cast(a_values_mem), const_cast(a_indices_mem), const_cast(a_first_index_mem), const_cast(a_first_index_mem+1), const_cast(x_mem), &beta, const_cast(y_mem)); break; default: ERROR_EXIT(128, "Incorrect sparse format\n"); } } void cblas_sparse_mv(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, ComplexF alpha, const ComplexF *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const ComplexF *x_mem, int x_inc, ComplexF beta, ComplexF *y_mem, int y_inc) { if ((x_inc!=1) || (y_inc!=1)) ERROR_EXIT(128, "Impossible to execute sparse gemv with MKL and " "non-contiguous vectors\n"); char descrA[6]; descrA[0] = 'g'; descrA[3]='c'; char trans = (a_transpose == CblasTrans) ? 't' : 'n'; switch(sparse_format) { case CSR_FORMAT: mkl_ccsrmv(&trans, &m, &n, reinterpret_cast(&alpha), descrA, reinterpret_cast(const_cast(a_values_mem)), const_cast(a_indices_mem), const_cast(a_first_index_mem), const_cast(a_first_index_mem+1), reinterpret_cast(const_cast(x_mem)), reinterpret_cast(&beta), reinterpret_cast(const_cast(y_mem))); break; case CSC_FORMAT: mkl_ccscmv(&trans, &m, &n, reinterpret_cast(&alpha), descrA, reinterpret_cast(const_cast(a_values_mem)), const_cast(a_indices_mem), const_cast(a_first_index_mem), const_cast(a_first_index_mem+1), reinterpret_cast(const_cast(x_mem)), reinterpret_cast(&beta), reinterpret_cast(const_cast(y_mem))); break; default: ERROR_EXIT(128, "Incorrect sparse format\n"); } } template float cblas_sparse_dot(int NNZ, const float *x_values_mem, const int *x_indices_mem, const float *y_mem, int y_inc); template double cblas_sparse_dot(int NNZ, const double *x_values_mem, const int *x_indices_mem, const double *y_mem, int y_inc); template ComplexF cblas_sparse_dot(int NNZ, const ComplexF *x_values_mem, const int *x_indices_mem, const ComplexF *y_mem, int y_inc); #endif april-ann-0.4.1/packages/basics/mathcore/c_src/cblas_headers.h000066400000000000000000000567331263004425400242600ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef CBLAS_HEADERS_H #define CBLAS_HEADERS_H #include "aligned_memory.h" #include "complex_number.h" #include "gpu_mirrored_memory_block.h" enum SPARSE_FORMAT { CSR_FORMAT=0, CSC_FORMAT=1, NONE_FORMAT=255 }; #ifdef USE_MKL #ifdef USE_XCODE #error "USE ONLY ONE OF: USE_MKL, USE_XCODE, NO_BLAS, or none of this" #endif #ifdef NO_BLAS #error "USE ONLY ONE OF: USE_MKL, USE_XCODE, NO_BLAS, or none of this" #endif /////////////////////////////////// MKL /////////////////////////////////////// extern "C" { #include #include #include #include } // if you compile with MKL you do not need atlas #define VECTOR_SSET(n, value, vec, step) for(unsigned int _i_=0,_j_=0;_j_<(n);++_j_,_i_+=(step))(vec)[_i_]=(value) #define VECTOR_DSET(n, value, vec, step) for(unsigned int _i_=0,_j_=0;_j_<(n);++_j_,_i_+=(step))(vec)[_i_]=(value) /*****************************************************************************/ #elif USE_XCODE #ifdef NO_BLAS #error "USE ONLY ONE OF: USE_MKL, USE_XCODE, NO_BLAS, or none of this" #endif ////////////////////////////////// XCODE ////////////////////////////////////// #include #define VECTOR_SSET(n, value, vec, step) for(unsigned int _i_=0,_j_=0;_j_<(n);++_j_,_i_+=(step))(vec)[_i_]=(value) #define VECTOR_DSET(n, value, vec, step) for(unsigned int _i_=0,_j_=0;_j_<(n);++_j_,_i_+=(step))(vec)[_i_]=(value) /*****************************************************************************/ #else #ifndef NO_BLAS ////////////////////////////////// ATLAS ////////////////////////////////////// extern "C" { #include } #define VECTOR_SSET(n, value, vec, step) catlas_sset((n), (value), (vec), (step)) #define VECTOR_DSET(n, value, vec, step) catlas_dset((n), (value), (vec), (step)) /*****************************************************************************/ #else ///////////////////////////////// AD-HOC ////////////////////////////////////// #define ADHOC_BLAS #define VECTOR_SSET(n, value, vec, step) for(unsigned int _i_=0,_j_=0;_j_<(n);++_j_,_i_+=(step))(vec)[_i_]=(value) #define VECTOR_DSET(n, value, vec, step) for(unsigned int _i_=0,_j_=0;_j_<(n);++_j_,_i_+=(step))(vec)[_i_]=(value) enum CBLAS_ORDER { CblasRowMajor = 0, CblasColMajor = 1 }; enum CBLAS_TRANSPOSE { CblasNoTrans = 0, CblasTrans = 1 }; enum CBLAS_UPLO { CblasLower = 0, CblasUpper = 1 }; void cblas_sgemv(CBLAS_ORDER order, CBLAS_TRANSPOSE a_transpose, int m, int n, float alpha, const float *a, unsigned int a_inc, const float *x, unsigned int x_inc, float beta, float *y, unsigned int y_inc); void cblas_scopy(int N, const float *x, unsigned int x_inc, float *y, unsigned int y_inc); void cblas_axpy(int N, float alpha, const float *x, unsigned int x_inc, float *y, unsigned int y_inc); void cblas_sgemm(CBLAS_ORDER order, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, int m, int n, int k, float alpha, const float *a, unsigned int a_inc, const float *b, unsigned int b_inc, float beta, float *c, unsigned int c_inc); void cblas_sscal(unsigned int N, float alpha, float *x, unsigned int inc); void cblas_sger(CBLAS_ORDER order, int m, int n, float alpha, const float *x, unsigned int x_inc, const float *y, unsigned int y_inc, float *a, unsigned int a_inc); float cblas_sdot(unsigned int N, const float *x, unsigned int x_inc, const float *y, unsigned int y_inc); float cblas_snrm2(unsigned int N, const float *x, unsigned int inc); /*****************************************************************************/ #endif #endif #define NEGATE_CBLAS_TRANSPOSE(trans) ((trans) == CblasNoTrans)?CblasTrans:CblasNoTrans // FIXME: MKL version is not working properly //#ifndef USE_MKL #if 1 // sparse BLAS is only available with CUDA or MKL void cblas_saxpyi(int NNZ, float alpha, const float *x_values_mem, const int *x_indices_mem, float *y_mem); void cblas_daxpyi(int NNZ, double alpha, const double *x_values_mem, const int *x_indices_mem, double *y_mem); void cblas_caxpyi(int NNZ, const AprilMath::ComplexF *alpha, const AprilMath::ComplexF *x_values_mem, const int *x_indices_mem, AprilMath::ComplexF *y_mem); #endif void cblas_sparse_mm(CBLAS_ORDER major_order, SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, CBLAS_TRANSPOSE c_transpose, int m, int n, int k, float alpha, const float *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const float *b_mem, int b_inc, float beta, float *c_mem, int c_inc); void cblas_sparse_mm(CBLAS_ORDER major_order, SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, CBLAS_TRANSPOSE c_transpose, int m, int n, int k, double alpha, const double *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const double *b_mem, int b_inc, double beta, double *c_mem, int c_inc); void cblas_sparse_mm(CBLAS_ORDER major_order, SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, CBLAS_TRANSPOSE c_transpose, int m, int n, int k, AprilMath::ComplexF alpha, const AprilMath::ComplexF *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const AprilMath::ComplexF *b_mem, int b_inc, AprilMath::ComplexF beta, AprilMath::ComplexF *c_mem, int c_inc); void cblas_sparse_mv(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, float alpha, const float *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const float *x_mem, int x_inc, float beta, float *y_mem, int y_inc); void cblas_sparse_mv(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, double alpha, const double *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const double *x_mem, int x_inc, double beta, double *y_mem, int y_inc); void cblas_sparse_mv(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, AprilMath::ComplexF alpha, const AprilMath::ComplexF *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const AprilMath::ComplexF *x_mem, int x_inc, AprilMath::ComplexF beta, AprilMath::ComplexF *y_mem, int y_inc); template T cblas_sparse_dot(int NNZ, const T *x_values_mem, const int *x_indices_mem, const T *y_mem, int y_inc) { T result = T(); for (int i=0; i void doAxpy(int N, T alpha, const GPUMirroredMemoryBlock* x, unsigned int x_inc, unsigned int x_shift, GPUMirroredMemoryBlock* y, unsigned int y_inc, unsigned int y_shift, bool use_gpu); template void doAxpyLoop(int N, T alpha, GPUMirroredMemoryBlock* x, unsigned int x_inc, unsigned int x_shift, GPUMirroredMemoryBlock* y, unsigned int y_inc, unsigned int y_shift, unsigned int times, const unsigned int stride_x, const unsigned int stride_y, bool use_gpu); /** * @brief Template wrapper for sparse ºqAXPY CBLAS operation. * * It computes y = y + alpha * x, where y is a dense vector and x is a sparse * vector with NNZ number of non-zero elements, and y length is at least NNZ. * * @tparam T - The data type. In APRIL-ANN it is available for float, double, * Basics::ComplexF. * * @param NNZ - The number of non-zero elements in y sparse vector. * @param alpha - The alpha value of the sparse AXPY operation. * @param x_values - A pointer to GPUMirroredMemoryBlock with values of x * sparse vector. * @param x_indices - A pointer to a Int32GPUMirroredMemoryBlock with the indices * of the values in x_value parameter. * @param[in,out] y - The vector y in AXPY operation. It is given as a * GPUMirroredMemoryBlock pointer. * @param x_shift - The first valid position at x pointers (both of them). * @param y_shift - The first valid position at y pointer. * @param y_inc - The stride between two consecutive elements in y vector. * @param use_gpu - Indicates if to use GPU computation or not. * * @note The sparse vector is given by x_values and x_indices memory blocks, * using a stride of 1 and an offset of 0. */ template void doSparseAxpy(int NNZ, T alpha, const GPUMirroredMemoryBlock *x_values, const Int32GPUMirroredMemoryBlock *x_indices, GPUMirroredMemoryBlock* y, unsigned int x_shift, unsigned int y_shift, unsigned int y_inc, bool use_gpu); /** * @brief Template wrapper for sparse copy CBLAS operation. * * It computes y = x, where y and x are vectors with size N. * * @tparam T - The data type. In APRIL-ANN it is available for float, double, * Basics::ComplexF. * * @param NNZ - The number of non-zero elements in y sparse vector. * @param x - A pointer to GPUMirroredMemoryBlock with values of x vector. * @param x_inc - The stride between consecutive elements in x. * @param x_shift - The position of the first valid element in x pointer. * @param[in,out] y - The vector y in copy operation. It is given as a * GPUMirroredMemoryBlock pointer. * @param y_inc - The stride between two consecutive elements in y vector. * @param y_shift - The first valid position at y pointer. * @param use_gpu - Indicates if to use GPU computation or not. */ template void doCopy(int N, const GPUMirroredMemoryBlock* x, unsigned int x_inc, unsigned int x_shift, GPUMirroredMemoryBlock* y, unsigned int y_inc, unsigned int y_shift, bool use_gpu); template void doCopyBroadcast(int N, GPUMirroredMemoryBlock* x, unsigned int x_inc, GPUMirroredMemoryBlock* A, unsigned int A_inc, unsigned int times, const unsigned int A_stride, bool use_gpu); /** * @brief Template wrapper for GEMM operation using CBLAS interface. * * GEMM computes C = alpha * op(A) * op(B) + beta * C where A, B and C are * matrices, op is tranposition operator, and alpha and beta are scalars. C is * a matrix with MxN size. op(A) will be MxK and op(B) will be KxN. * * @tparam T - The data type. In APRIl-ANN it could be float, double, * ComplexF. * * @param major_type - The expected major_order in the matrices. * @param a_transpose - Indicates if A matrix must be transposed. * @param b_transpose - Indicates if B matrix must be transposed. * @param m - The number of rows in C. * @param n - The number of columns in C. * @param k - The common dimension for A and B. * @param alpha - The alpha scalar of GEMM operation. * @param a - The A matrix given as a GPUMirroredMemoryBlock pointer. * @param a_inc - The stride of the leading dimension of A. * @param b - The B matrix given as a GPUMirroredMemoryBlock pointer. * @param b_inc - The stride of the leading dimension of B. * @param beta - The beta scalar of GEMM operation. * @param[in,out] c - The matrix C given as a GPUMirroredMemoryBlock pointer. * @param c_inc - The stride of the leading dimension of C. * @param a_shift - The first valid position of matrix A pointer. * @param b_shift - The first valid position of matrix B pointer. * @param c_shift - The first valid position of matrix C pointer. * @param use_gpu - Indicates if use GPU or not for the computation. */ template void doGemm(CBLAS_ORDER major_type, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, int m, int n, int k, T alpha, const GPUMirroredMemoryBlock* a, unsigned int a_inc, const GPUMirroredMemoryBlock* b, unsigned int b_inc, T beta, GPUMirroredMemoryBlock* c, unsigned int c_inc, unsigned int a_shift, unsigned int b_shift, unsigned int c_shift, bool use_gpu); /** * @brief Template wrapper for sparse MM operation. * * SparseMM computes C = alpha * op(A) * op(B) + beta * C where A is a * sparse matrix given in CSR or CSC formats, B and C are dense matrices, op * is tranposition operator, and alpha and beta are scalars. C is a matrix * with MxN size. op(A) will be MxK and op(B) will be KxN. * * @see Basics::SparseMatrix class documentation. * * @tparam T - The data type. In APRIl-ANN it could be float, double, * ComplexF. * * @param major_type - The expected major_order in the dense matrices. * @param sparse_format - The format can be CSR_FORMAT or CSC_FORMAT. * @param a_transpose - Indicates if A matrix must be transposed. * @param b_transpose - Indicates if B matrix must be transposed. * @param m - The number of rows in C. * @param n - The number of columns in C. * @param k - The common dimension for A and B. * @param alpha - The alpha scalar of GEMM operation. * @param a_values - The A matrix values given as a GPUMirroredMemoryBlock pointer. * @param a_indices - The A matrix indices given as a Int32GPUMirroredMemoryBlock pointer. * @param a_first_index - The A matrix first indices given as a Int32GPUMirroredMemoryBlock pointer. * @param b - The B matrix given as a GPUMirroredMemoryBlock pointer. * @param b_inc - The stride of the leading dimension of B. * @param beta - The beta scalar of GEMM operation. * @param[in,out] c - The matrix C given as a GPUMirroredMemoryBlock pointer. * @param c_inc - The stride of the leading dimension of C. * @param b_shift - The first valid position of matrix B pointer. * @param c_shift - The first valid position of matrix C pointer. * @param use_gpu - Indicates if use GPU or not for the computation. */ template void doSparseMM(CBLAS_ORDER major_order, SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, int m, int n, int k, T alpha, const GPUMirroredMemoryBlock* a_values, const Int32GPUMirroredMemoryBlock* a_indices, const Int32GPUMirroredMemoryBlock* a_first_index, const GPUMirroredMemoryBlock* b, int b_inc, T beta, GPUMirroredMemoryBlock* c, int c_inc, int b_shift, int c_shift, bool use_gpu); // BLAS FUNCTIONS /** * @brief Template wrapper for GEMV CBLAS operation. * * GEMV computex Y = alpha * op(A)*X + beta*Y, where X and Y are vectors and A * is a matrix, op is tranposition operator, and alpha and beta are scalars. A * is of MxN size, Y is a N vector and X is a M vector. * * @tparam T - The data type. In APRIl-ANN it could be float, double, * ComplexF. * * @param major_type - The expected major_order in the dense matrices. * @param a_transpose - Indicates if A matrix must be transposed. * @param m - The number of rows in A. * @param n - The number of columns in A. * @param alpha - The alpha scalar of GEMV operation. * @param a - The A matrix given as a GPUMirroredMemoryBlock pointer. * @param a_inc - The stride for the leading dimension of A matrix. * @param x - The X vector given as a GPUMirroredMemoryBlock pointer. * @param x_inc - The stride between consecutive elements of X. * @param beta - The beta scalar of GEMV operation. * @param y[in,out] - The Y vector given as a GPUMirroredMemoryBlock pointer. * @param y_inc - The stride between consecutive elements of Y. * @param a_shift - The first valid position of matrix A pointer. * @param x_shift - The first valid position of matrix X pointer. * @param y_shift - The first valid position of matrix Y pointer. * @param use_gpu - Indicates if use GPU or not for the computation. */ template void doGemv(CBLAS_ORDER major_type, CBLAS_TRANSPOSE a_transpose, int m, int n, T alpha, const GPUMirroredMemoryBlock *a, unsigned int a_inc, const GPUMirroredMemoryBlock *x, unsigned int x_inc, T beta, GPUMirroredMemoryBlock *y, unsigned int y_inc, unsigned int a_shift, unsigned int x_shift, unsigned int y_shift, bool use_gpu); /** * @brief Template wrapper for sparse GEMV CBLAS operation. * * GEMV computex Y = alpha * op(A)*X + Y, where X and Y are vectors and A is a * sparse matrix, op is tranposition operator, and alpha and beta are * scalars. A is of MxN size, Y is a N vector and X is a M vector. * * @tparam T - The data type. In APRIl-ANN it could be float, double, * ComplexF. * * @param sparse_format - The sparse format for A matrix, CSR_FORMAT or CSC_FORMAT. * @param a_transpose - Indicates if A matrix must be transposed. * @param m - The number of rows in A. * @param n - The number of columns in A. * @param alpha - The alpha scalar of GEMV operation. * @param a_values - The A matrix values given as a GPUMirroredMemoryBlock pointer. * @param a_indices - The A matrix indices given as a Int32GPUMirroredMemoryBlock pointer. * @param a_first_index - The A matrix first indices given as a Int32GPUMirroredMemoryBlock pointer. * @param x - The X vector given as a GPUMirroredMemoryBlock pointer. * @param x_inc - The stride between consecutive elements of X. * @param beta - The beta scalar of sparse GEMV operation. * @param y[in,out] - The Y vector given as a GPUMirroredMemoryBlock pointer. * @param y_inc - The stride between consecutive elements of Y. * @param x_shift - The first valid position of matrix X pointer. * @param y_shift - The first valid position of matrix Y pointer. * @param use_gpu - Indicates if use GPU or not for the computation. */ template void doSparseGemv(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, T alpha, const GPUMirroredMemoryBlock *a_values, const Int32GPUMirroredMemoryBlock *a_indices, const Int32GPUMirroredMemoryBlock *a_first_index, const GPUMirroredMemoryBlock *x, unsigned int x_inc, T beta, GPUMirroredMemoryBlock *y, unsigned int y_inc, unsigned int x_shift, unsigned int y_shift, bool use_gpu); template void doGer(CBLAS_ORDER major_type, unsigned int m, unsigned int n, T alpha, const GPUMirroredMemoryBlock *x, unsigned int x_shift, unsigned int x_inc, const GPUMirroredMemoryBlock *y, unsigned int y_shift, unsigned int y_inc, GPUMirroredMemoryBlock *a, unsigned int a_shift, unsigned int a_inc, bool use_gpu); template void doScal(unsigned int size, GPUMirroredMemoryBlock *x, unsigned int inc, unsigned int shift, T alpha, bool use_gpu); //////// CURRIED VERSIONS ///////// template struct CurriedAxpy { const T alpha; CurriedAxpy(const T &alpha) : alpha(alpha) { } void operator()(unsigned int N, const GPUMirroredMemoryBlock *input, unsigned int input_stride, unsigned int input_shift, GPUMirroredMemoryBlock *output, unsigned int output_stride, unsigned int output_shift, bool use_cuda) const { doAxpy(static_cast(N), alpha, input, input_stride, input_shift, output, output_stride, output_shift, use_cuda); } }; template struct CurriedScal { const T alpha; CurriedScal(const T &alpha) : alpha(alpha) { } void operator()(unsigned int N, const GPUMirroredMemoryBlock *input, unsigned int input_stride, unsigned int input_shift, GPUMirroredMemoryBlock *output, unsigned int output_stride, unsigned int output_shift, bool use_cuda) const { if (input != output) { ERROR_EXIT(128, "Scal is always an in-place operation\n"); } april_assert(input_stride == output_stride); april_assert(input_shift == output_shift); UNUSED_VARIABLE(input); UNUSED_VARIABLE(input_stride); UNUSED_VARIABLE(input_shift); doScal(N, output, output_stride, output_shift, alpha, use_cuda); } }; } // namespace AprilMath #include "dot.h" #include "nrm2.h" #endif // CBLAS_HEADERS_H april-ann-0.4.1/packages/basics/mathcore/c_src/cmath_overloads.cu000066400000000000000000000123521263004425400250200ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include "cmath_overloads.h" #ifndef INT8_MAX #define INT8_MAX 0x7f #endif #ifndef INT8_MIN #define INT8_MIN (-INT8_MAX - 1) #endif #ifndef UINT8_MAX #define UINT8_MAX 0xffU #endif #ifndef INT16_MAX #define INT16_MAX 0x7fff #endif #ifndef INT16_MIN #define INT16_MIN (-INT16_MAX - 1) #endif #ifndef UINT16_MAX #define UINT16_MAX 0xffffU #endif #ifndef INT32_MAX #define INT32_MAX 0x7fffffffL #endif #ifndef INT32_MIN #define INT32_MIN (-INT32_MAX - 1L) #endif #ifndef UINT32_MAX #define UINT32_MAX 0xffffffffUL #endif #ifndef INT64_MAX #define INT64_MAX 0x7fffffffffffffffLL #endif #ifndef INT64_MIN #define INT64_MIN (-INT64_MAX - 1LL) #endif #ifndef UINT64_MAX #define UINT64_MAX 0xffffffffffffffffULL #endif namespace AprilMath { template<> char Limits::lowest() { return CHAR_MIN; } template<> char Limits::min() { return CHAR_MIN; } template<> char Limits::max() { return CHAR_MAX; } template<> int8_t Limits::lowest() { return INT8_MIN; } template<> int8_t Limits::min() { return INT8_MIN; } template<> int8_t Limits::max() { return INT8_MAX; } template<> uint8_t Limits::lowest() { return 0u; } template<> uint8_t Limits::min() { return 0u; } template<> uint8_t Limits::max() { return UINT8_MAX; } template<> int16_t Limits::lowest() { return INT16_MIN; } template<> int16_t Limits::min() { return INT16_MIN; } template<> int16_t Limits::max() { return INT16_MAX; } template<> uint16_t Limits::lowest() { return 0u; } template<> uint16_t Limits::min() { return 0u; } template<> uint16_t Limits::max() { return UINT16_MAX; } template<> int32_t Limits::lowest() { return INT32_MIN; } template<> int32_t Limits::min() { return INT32_MIN; } template<> int32_t Limits::max() { return INT32_MAX; } template<> uint32_t Limits::lowest() { return 0u; } template<> uint32_t Limits::min() { return 0u; } template<> uint32_t Limits::max() { return UINT32_MAX; } template<> int64_t Limits::lowest() { return INT64_MIN; } template<> int64_t Limits::min() { return INT64_MIN; } template<> int64_t Limits::max() { return INT64_MAX; } template<> uint64_t Limits::lowest() { return 0u; } template<> uint64_t Limits::min() { return 0u; } template<> uint64_t Limits::max() { return UINT64_MAX; } template<> float Limits::lowest() { return -FLT_MAX; } template<> float Limits::min() { return FLT_MIN; } template<> float Limits::max() { return FLT_MAX; } template<> float Limits::epsilon() { return FLT_EPSILON; } template<> bool Limits::hasInfinity() { return true; } template<> float Limits::infinity() { return HUGE_VALF; } template<> float Limits::quiet_NaN() { return float(NAN); } template<> double Limits::lowest() { return -DBL_MAX; } template<> double Limits::min() { return DBL_MIN; } template<> double Limits::max() { return DBL_MAX; } template<> double Limits::epsilon() { return DBL_EPSILON; } template<> bool Limits::hasInfinity() { return true; } template<> double Limits::infinity() { return HUGE_VAL; } template<> double Limits::quiet_NaN() { return double(NAN); } template<> ComplexF Limits::lowest() { return ComplexF(Limits::lowest(),Limits::lowest()); } template<> ComplexF Limits::min() { return ComplexF(Limits::min(),Limits::min()); } template<> ComplexF Limits::max() { return ComplexF(Limits::max(),Limits::max()); } template<> ComplexF Limits::epsilon() { return ComplexF(Limits::epsilon(),Limits::epsilon()); } template<> bool Limits::hasInfinity() { return true; } template<> ComplexF Limits::infinity() { return ComplexF(Limits::infinity(),Limits::infinity()); } template<> ComplexF Limits::quiet_NaN() { return ComplexF(Limits::quiet_NaN(), Limits::quiet_NaN()); } #ifndef USE_CUDA template<> ComplexF Limits::zero() { return ComplexF::zero_zero(); } template<> ComplexF Limits::one() { return ComplexF::one_zero(); } #endif } // namespace AprilMath april-ann-0.4.1/packages/basics/mathcore/c_src/cmath_overloads.h000066400000000000000000001410041263004425400246350ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef CMATH_OVERLOADS_H #define CMATH_OVERLOADS_H #include #include #include #include "complex_number.h" #include "cuda_headers.h" #include "error_print.h" #include "unused_variable.h" #ifndef NAN #define NAN 0.0/0.0 #endif /// Constant for values close to zero. #define NEAR_ZERO 1e-6f /** * @brief A derivative is considered saturated when its abs is greater than this * constant. */ #define DERIVATIVE_SATURATION 17.0f // Documentation of AprilMath namespace is in mathcore.h namespace AprilMath { /// Logarithm of NEAR_ZERO for float numbers. const float logf_NZ = logf(NEAR_ZERO); /// Logarithm of NEAR_ZERO for double numbers. const double log_NZ = log(NEAR_ZERO); ///////////////// NUMERIC LIMITS ///////////////// /** * @brief A replacement of std::limits implemented to avoid dependencies in * C++ std namespace. */ template class Limits { public: /// Indicates if infinity() method can be used. APRIL_CUDA_EXPORT static bool hasInfinity() { return false; } /// Returns the positive infinity representation, if hasInfinity() == true. APRIL_CUDA_EXPORT static T infinity() { return T(); } /** * @brief Machine the difference between 1 and the least value greater * than 1 that is representable for typename T. */ APRIL_CUDA_EXPORT static T epsilon() { return T(); } /// Returns the lowest finite value of a typename T. APRIL_CUDA_EXPORT static T lowest() { return T(); } /// Returns the minimum finite value of a typename T. APRIL_CUDA_EXPORT static T min() { return T(); } /// Returns the maximum finite value of a typename T. APRIL_CUDA_EXPORT static T max() { return T(); } /// Returns a NaN value. APRIL_CUDA_EXPORT static T quiet_NaN() { return T(); } /// Zero value. APRIL_CUDA_EXPORT static T zero() { return T(0.0f); } /// One value. APRIL_CUDA_EXPORT static T one() { return T(1.0f); } }; template<> char Limits::lowest(); template<> char Limits::min(); template<> char Limits::max(); template<> int8_t Limits::lowest(); template<> int8_t Limits::min(); template<> int8_t Limits::max(); template<> uint8_t Limits::lowest(); template<> uint8_t Limits::min(); template<> uint8_t Limits::max(); template<> int16_t Limits::lowest(); template<> int16_t Limits::min(); template<> int16_t Limits::max(); template<> uint16_t Limits::lowest(); template<> uint16_t Limits::min(); template<> uint16_t Limits::max(); template<> int32_t Limits::lowest(); template<> int32_t Limits::min(); template<> int32_t Limits::max(); template<> uint32_t Limits::lowest(); template<> uint32_t Limits::min(); template<> uint32_t Limits::max(); template<> int64_t Limits::lowest(); template<> int64_t Limits::min(); template<> int64_t Limits::max(); template<> uint64_t Limits::lowest(); template<> uint64_t Limits::min(); template<> uint64_t Limits::max(); template<> float Limits::lowest(); template<> float Limits::min(); template<> float Limits::max(); template<> float Limits::epsilon(); template<> bool Limits::hasInfinity(); template<> float Limits::infinity(); template<> float Limits::quiet_NaN(); template<> double Limits::lowest(); template<> double Limits::min(); template<> double Limits::max(); template<> double Limits::epsilon(); template<> bool Limits::hasInfinity(); template<> double Limits::infinity(); template<> double Limits::quiet_NaN(); template<> ComplexF Limits::lowest(); template<> ComplexF Limits::min(); template<> ComplexF Limits::max(); template<> ComplexF Limits::epsilon(); template<> bool Limits::hasInfinity(); template<> ComplexF Limits::infinity(); template<> ComplexF Limits::quiet_NaN(); #ifndef USE_CUDA template<> ComplexF Limits::zero(); template<> ComplexF Limits::one(); #endif ///////////////// NAN CHECK ///////////////// /** * @brief Operations over scalar types are defined as C++ functors in this * namespace. * * This functors allow to implement map or reduce operations defined in * AprilMath. */ namespace Functors { /// Functor for comparison with a NaN value. template struct m_isnan { /** * @brief The operator returns @c true/false if @c v is NaN or not. * * @note By definition, a NaN is always different of any other value, even * another NaN, so this operator identifies it using return v != v */ APRIL_CUDA_EXPORT bool operator()(const T &v) const { return v != v; } }; } /** * @brief Function for instantiation and call of Functors::m_isnan::operator() * @see Functors::m_isnan */ template APRIL_CUDA_EXPORT bool m_isnan(const T &v) { return Functors::m_isnan()(v); } //////////////// MATH SCALAR MAP FUNCTIONS //////////////// #define SCALAR_MAP_TEMPLATE(NAME, T_IN, T_OUT) \ namespace Functors { \ template \ struct NAME { \ APRIL_CUDA_EXPORT T_OUT operator()(const T_IN &v) const { \ UNUSED_VARIABLE(v); \ APRIL_CUDA_ERROR_EXIT(128, "NOT IMPLEMENTED\n"); \ return T_OUT(); \ } \ }; \ } \ template \ APRIL_CUDA_EXPORT T_OUT NAME(const T_IN &v) { return Functors::NAME()(v); } #define SCALAR_STD_CMATH_MAP_TEMPLATE(NAME,CFUNC) \ SCALAR_MAP_TEMPLATE(NAME, T, T); \ namespace Functors { \ template<> struct NAME { \ APRIL_CUDA_EXPORT float operator()(const float &v) const { return CFUNC##f(v); } \ }; \ template<> struct NAME { \ APRIL_CUDA_EXPORT double operator()(const double &v) const { return CFUNC(v); } \ }; \ } /** * @struct Functors::m_floor * * @brief Overloaded floor operation, currently defined for float, double and * ComplexF types. */ /** * @fn m_floor * * @brief Function for instantiation and call of Functors::m_floor::operator() * @see Functors::m_floor */ // abs overload SCALAR_MAP_TEMPLATE(m_floor, T, T); namespace Functors { template<> struct m_floor { APRIL_CUDA_EXPORT float operator()(const float &v) const { return floorf(v); } }; template<> struct m_floor { APRIL_CUDA_EXPORT double operator()(const double &v) const { return floor(v); } }; template<> struct m_floor { APRIL_CUDA_EXPORT ComplexF operator()(const ComplexF &v) const { return ComplexF(floorf(v.real()), floorf(v.img())); } }; } /** * @struct Functors::m_ceil * * @brief Overloaded ceil operation, currently defined for float, double and * ComplexF types. */ /** * @fn m_ceil * * @brief Function for instantiation and call of Functors::m_ceil::operator() * @see Functors::m_ceil */ // abs overload SCALAR_MAP_TEMPLATE(m_ceil, T, T); namespace Functors { template<> struct m_ceil { APRIL_CUDA_EXPORT float operator()(const float &v) const { return ceilf(v); } }; template<> struct m_ceil { APRIL_CUDA_EXPORT double operator()(const double &v) const { return ceil(v); } }; template<> struct m_ceil { APRIL_CUDA_EXPORT ComplexF operator()(const ComplexF &v) const { return ComplexF(ceilf(v.real()), ceilf(v.img())); } }; } /** * @struct Functors::m_round * * @brief Overloaded round operation, currently defined for float, double and * ComplexF types. */ /** * @fn m_round * * @brief Function for instantiation and call of Functors::m_round::operator() * @see Functors::m_round */ // abs overload SCALAR_MAP_TEMPLATE(m_round, T, T); namespace Functors { template<> struct m_round { APRIL_CUDA_EXPORT float operator()(const float &v) const { return roundf(v); } }; template<> struct m_round { APRIL_CUDA_EXPORT double operator()(const double &v) const { return round(v); } }; template<> struct m_round { APRIL_CUDA_EXPORT ComplexF operator()(const ComplexF &v) const { return ComplexF(roundf(v.real()), roundf(v.img())); } }; } /** * @struct Functors::m_abs * * @brief Overloaded abs operation, currently defined for float, double and * ComplexF types. * * @note Its @c operator() returns a float always. */ /** * @fn m_abs * * @brief Function for instantiation and call of Functors::m_abs::operator() * @see Functors::m_abs */ // abs overload SCALAR_MAP_TEMPLATE(m_abs, T, float); namespace Functors { template<> struct m_abs { APRIL_CUDA_EXPORT float operator()(const float &v) const { return fabsf(v); } }; template<> struct m_abs { APRIL_CUDA_EXPORT float operator()(const double &v) const { return fabs(v); } }; template<> struct m_abs { APRIL_CUDA_EXPORT float operator()(const ComplexF &v) const { return v.abs(); } }; template<> struct m_abs { APRIL_CUDA_EXPORT char operator()(const char &v) const { return v; } }; template<> struct m_abs { APRIL_CUDA_EXPORT int32_t operator()(const int32_t &v) const { return ::abs(v); } }; template<> struct m_abs { APRIL_CUDA_EXPORT bool operator()(const bool &v) const { return v; } }; } /** * @struct Functors::m_sqrt * * @brief Overloaded sqrt operation, currently defined for float, double and * ComplexF types. * * @note Its @c operator() returns a float always. */ /** * @fn m_sqrt * * @brief Function for instantiation and call of Functors::m_sqrt::operator() * @see Functors::m_sqrt */ // sqrt overload SCALAR_MAP_TEMPLATE(m_sqrt, T, float); namespace Functors { template<> struct m_sqrt { APRIL_CUDA_EXPORT float operator()(const float &v) const { return sqrtf(v); } }; template<> struct m_sqrt { APRIL_CUDA_EXPORT float operator()(const double &v) const { return sqrt(v); } }; template<> struct m_sqrt { APRIL_CUDA_EXPORT float operator()(const ComplexF &v) const { return v.sqrtc(); } }; } /** * @struct Functors::m_log * * @brief Overloaded log operation, currently defined for float and double */ /** * @fn m_log * * @brief Function for instantiation and call of Functors::m_log::operator() * @see Functors::m_log */ // log overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_log, log); // SCALAR_MAP_TEMPLATE(m_log, T, T); // APRIL_CUDA_EXPORT template<> float m_log(const float &v) { // if (m_abs(v) < NEAR_ZERO) return logf_NZ; // else return logf(v); // } // APRIL_CUDA_EXPORT template<> double m_log(const double &v) { // if (m_abs(v) < NEAR_ZERO) return log_NZ; // else return log(v); // } /** * @struct Functors::m_log1p * * @brief Overloaded log1p operation, currently defined for float and double. */ /** * @fn m_log1p * * @brief Function for instantiation and call of Functors::m_log1p::operator() * @see Functors::m_log1p */ // log1p overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_log1p, log1p); /** * @struct Functors::m_exp * * @brief Overloaded exp operation, currently defined for float and double. */ /** * @fn m_exp * * @brief Function for instantiation and call of Functors::m_exp::operator() * @see Functors::m_exp */ // exp overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_exp, exp); /** * @struct Functors::m_expm1 * * @brief Overloaded expm1 operation, currently defined for float and double. */ /** * @fn m_expm1 * * @brief Function for instantiation and call of Functors::m_expm1::operator() * @see Functors::m_expm1 */ // expm1 overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_expm1, expm1); /** * @struct Functors::m_pow * * @brief Overloaded pow operation, currently defined for float and double. */ /** * @fn m_pow * * @brief Function for instantiation and call of Functors::m_pow::operator() * @see Functors::m_pow */ // pow overload namespace Functors { template struct m_pow { APRIL_CUDA_EXPORT T operator()(const T &v, const T &p) const { UNUSED_VARIABLE(v); UNUSED_VARIABLE(p); APRIL_CUDA_ERROR_EXIT(128, "NOT IMPLEMENTED\n"); return T(); } }; template<> struct m_pow { APRIL_CUDA_EXPORT float operator()(const float &v, const float &p) const { return powf(v, p); } }; template<> struct m_pow { APRIL_CUDA_EXPORT double operator()(const double &v, const double &p) const { return pow(v, p); } }; } template APRIL_CUDA_EXPORT T m_pow(const T &a, const T &b) { return Functors::m_pow()(a,b); } /** * @struct Functors::m_cos * * @brief Overloaded cos operation, currently defined for float and double. */ /** * @fn m_cos * * @brief Function for instantiation and call of Functors::m_cos::operator() * @see Functors::m_cos */ // cos overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_cos, cos); /** * @struct Functors::m_acos * * @brief Overloaded acos operation, currently defined for float and double. */ /** * @fn m_acos * * @brief Function for instantiation and call of Functors::m_acos::operator() * @see Functors::m_acos */ // acos overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_acos, acos); /** * @struct Functors::m_cosh * * @brief Overloaded cosh operation, currently defined for float and double. */ /** * @fn m_cosh * * @brief Function for instantiation and call of Functors::m_cosh::operator() * @see Functors::m_cosh */ // cosh overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_cosh, cosh); /** * @struct Functors::m_acosh * * @brief Overloaded acosh operation, currently defined for float and double. */ /** * @fn m_acosh * * @brief Function for instantiation and call of Functors::m_acosh::operator() * @see Functors::m_acosh */ // acosh overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_acosh, acosh); /** * @struct Functors::m_sin * * @brief Overloaded sin operation, currently defined for float and double. */ /** * @fn m_sin * * @brief Function for instantiation and call of Functors::m_sin::operator() * @see Functors::m_sin */ // sin overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_sin, sin); /** * @struct Functors::m_asin * * @brief Overloaded asin operation, currently defined for float and double. */ /** * @fn m_asin * * @brief Function for instantiation and call of Functors::m_asin::operator() * @see Functors::m_asin */ // asin overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_asin, asin); /** * @struct Functors::m_sinh * * @brief Overloaded sinh operation, currently defined for float and double. */ /** * @fn m_sinh * * @brief Function for instantiation and call of Functors::m_sinh::operator() * @see Functors::m_sinh */ // sinh overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_sinh, sinh); /** * @struct Functors::m_asinh * * @brief Overloaded asinh operation, currently defined for float and double. */ /** * @fn m_asinh * * @brief Function for instantiation and call of Functors::m_asinh::operator() * @see Functors::m_asinh */ // asinh overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_asinh, asinh); /** * @struct Functors::m_tan * * @brief Overloaded tan operation, currently defined for float and double. */ /** * @fn m_tan * * @brief Function for instantiation and call of Functors::m_tan::operator() * @see Functors::m_tan */ // tan overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_tan, tan); /** * @struct Functors::m_atan * * @brief Overloaded atan operation, currently defined for float and double. */ /** * @fn m_atan * * @brief Function for insatantiation and call of Functors::m_atan::operator() * @see Functors::m_atan */ // atan overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_atan, atan); /** * @struct Functors::m_tanh * * @brief Overloaded tanh operation, currently defined for float and double. */ /** * @fn m_tanh * * @brief Function for instantiation and call of Functors::m_tanh::operator() * @see Functors::m_tanh */ // tanh overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_tanh, tanh); /** * @struct Functors::m_atanh * * @brief Overloaded atanh operation, currently defined for float and double. */ /** * @fn m_atanh * * @brief Function for instantiation and call of Functors::m_atanh::operator() * @see Functors::m_atanh */ // atanh overload SCALAR_STD_CMATH_MAP_TEMPLATE(m_atanh, atanh); // namespace Functors { /// Identity functor, it can be used to copy vectors using map. template struct m_identity { /// Returns by value its given parameter. APRIL_CUDA_EXPORT T operator()(const T &a) const { return a; } }; /// Cast functor, it can be used to cast vectors using map. template struct m_cast { /// Returns by value its given parameter. APRIL_CUDA_EXPORT O operator()(const T &a) const { return static_cast(a); } }; /// Implementation of p log(p) . template struct m_plogp { /** * @brief p log(p) is simplified to take into account the case * 0 log(0) = 0 */ APRIL_CUDA_EXPORT T operator()(const T &x) const { return ((x) > T(0.0f) || (x) < T(0.0f)) ? (x) * AprilMath::m_log(x) : (x); } }; /// Sign functor. template struct m_sign { /** * @brief Returns the sign of the given parameter. * * It uses a comparison with T(0.0f) to decide the sign, and returns * T(-1.0f) or T(1.0f) depending in the result of previous comparison. */ APRIL_CUDA_EXPORT T operator()(const T &x) const { return ((x)T(0.0f)) ? T(1.0f) : T(0.0f) ); } }; /// Complement functor. template struct m_complement { /// Returns T(1.0f) - x APRIL_CUDA_EXPORT T operator()(const T &x) const { return (T(1.0f) - (x)); } }; /// Clamp functor. template struct m_clamp { /// Returns the clamp of @c x using the range [min,max] APRIL_CUDA_EXPORT T operator()(const T &x, const T &min, const T &max) const { return ((x)max?max:x)); } }; /// Sigmoid function. template struct m_sigmoid { /// Returns \f$ \displaystyle{ \frac{n}{e^{-v} + 1.0} } \f$ where @c n is numerator param. APRIL_CUDA_EXPORT T operator()(const T &numerator, const T &value) const { return (numerator) / (AprilMath::m_exp(-(value))+T(1.0f)); } }; /// Rectified Linear Unit (ReLU) function. template struct m_relu { /// Returns max(0, value) APRIL_CUDA_EXPORT T operator()(const T &value) const { return (value > T(0.0f)) ? (value) : T(0.0f); } }; /// Leaky Rectified Linear Unit (Leaky ReLU) function. template struct m_leaky_relu { T leak; m_leaky_relu(T leak) : leak(leak) { } /// Returns value if x>0, leak * x otherwise APRIL_CUDA_EXPORT T operator()(const T &value) const { return (value > T(0.0f)) ? (value) : leak*value; } }; /// Less than comparison. template struct m_lt { /// Returns @c true or @c false depending in @c a struct m_gt { /// Returns @c true or @c false depending in @c b struct m_eq { /// Returns @c true or @c false depending in @c b==a APRIL_CUDA_EXPORT T operator()(const T &a, const T &b) const { if (AprilMath::m_isnan(a)) { return AprilMath::m_isnan(b); } else { return (a == b); } } }; /// Equals comparison using a percentage threshold. template struct m_relative_equals { /** * @brief Compares @c a=b using @c TH as percentage of relative error. * @returns True or false. * * @note This function checks NaN equality, exact equality (==) and * finally computes relative difference between both numbers. */ APRIL_CUDA_EXPORT bool operator()(const T &a, const T &b, const float &TH) const { // NaN equality if (AprilMath::m_isnan(a) && AprilMath::m_isnan(b)) { return true; } // Exact equality else if (a == b) { return true; } else { const float ZERO = 1e-03; float a_abs = AprilMath::m_abs(a); float b_abs = AprilMath::m_abs(b); if (a_abs < ZERO || b_abs < ZERO) { // In case any of both numbers is less than ZERO... if (a_abs < ZERO && b_abs < ZERO) { // both are < ZERO return true; } // check relative error between any of the numbers and ZERO else if (AprilMath::m_abs(a_abs-ZERO)/(a_abs+ZERO) > TH || AprilMath::m_abs(b_abs-ZERO)/(b_abs+ZERO) > TH) { return false; } else { return true; } } else { // Relative difference. float diff = 2.0f * ( AprilMath::m_abs(a - b) / (a_abs + b_abs) ); if (diff < TH) { return true; } else { return false; } } } } }; /// Multiplication map operation. template struct m_mul { /// Returns \f$ a*b \f$ APRIL_CUDA_EXPORT T operator()(const T &a, const T &b) const { return a*b; } }; /// Addition map operation. template struct m_add { /// Returns \f$ a+b \f$ APRIL_CUDA_EXPORT T operator()(const T &a, const T &b) const { return a+b; } }; /// is_finite map operation. template struct m_is_finite { /// Returns \f$ (a-a) == 0.0 \f$ APRIL_CUDA_EXPORT bool operator()(const T &a) const { return (a-a) == Limits::zero(); } }; /// Division map operation. template struct m_div { /// Returns \f$ a/b \f$ APRIL_CUDA_EXPORT T operator()(const T &a, const T &b) const { return a/b; } }; /// Modulus map operation. template struct m_mod { /// Returns \f$ a/b \f$ APRIL_CUDA_EXPORT T operator()(const T &a, const T &b) const { return a%b; } }; /// Maximum map operation. template struct m_max { /// Returns \f$ max(a,b) \f$ APRIL_CUDA_EXPORT T operator()(const T &a, const T &b) const { return (a struct m_min { /// Returns \f$ min(a,b) \f$ APRIL_CUDA_EXPORT T operator()(const T &a, const T &b) const { return (a APRIL_CUDA_EXPORT T m_identity(const T &a) { return Functors::m_identity()(a); } /// @see Functors::m_cast template APRIL_CUDA_EXPORT O m_cast(const T &a) { return Functors::m_cast()(a); } /// @see Functors::m_plogp template APRIL_CUDA_EXPORT T m_plogp(const T &a) { return Functors::m_plogp()(a); } /// @see Functors::m_sign template APRIL_CUDA_EXPORT T m_sign(const T &a) { return Functors::m_sign()(a); } /// @see Functors::m_complement template APRIL_CUDA_EXPORT T m_complement(const T &a) { return Functors::m_complement()(a); } /// @see Functors::m_clamp template APRIL_CUDA_EXPORT T m_clamp(const T &a, const T &b, const T &c) { return Functors::m_clamp()(a,b,c); } /// @see Functors::m_sigmoid template APRIL_CUDA_EXPORT T m_sigmoid(const T &a, const T &b) { return Functors::m_sigmoid()(a,b); } /// @see Functors::m_relu template APRIL_CUDA_EXPORT T m_relu(const T &a) { return Functors::m_relu()(a); } /// @see Functors::m_leaky_relu template APRIL_CUDA_EXPORT T m_leaky_relu(const T &a, T leak) { return Functors::m_relu(leak)(a); } /// @see Functors::m_lt template APRIL_CUDA_EXPORT bool m_lt(const T &a, const T &b) { return Functors::m_lt()(a,b); } /// @see Functors::m_gt template APRIL_CUDA_EXPORT bool m_gt(const T &a, const T &b) { return Functors::m_gt()(a,b); } /// @see Functors::m_eq template APRIL_CUDA_EXPORT bool m_eq(const T &a, const T &b) { return Functors::m_eq()(a,b); } /// @see Functors::m_relative_equals template APRIL_CUDA_EXPORT bool m_relative_equals(const T &a, const T &b, const float &c) { return Functors::m_relative_equals()(a,b,c); } /// @see Functors::m_mul template APRIL_CUDA_EXPORT T m_mul(const T &a, const T &b) { return Functors::m_mul()(a,b); } /// @see Functors::m_add template APRIL_CUDA_EXPORT T m_add(const T &a, const T &b) { return Functors::m_add()(a,b); } /// @see Functors::m_is_finite template APRIL_CUDA_EXPORT bool m_is_finite(const T &a) { return Functors::m_is_finite()(a); } /// @see Functors::m_div template APRIL_CUDA_EXPORT T m_div(const T &a, const T &b) { return Functors::m_div()(a,b); } /// @see Functors::m_mod template APRIL_CUDA_EXPORT T m_mod(const T &a, const T &b) { return Functors::m_mod()(a,b); } /// @see Functors::m_min template APRIL_CUDA_EXPORT T m_min(const T &a, const T &b) { return Functors::m_min()(a,b); } /// @see Functors::m_max template APRIL_CUDA_EXPORT T m_max(const T &a, const T &b) { return Functors::m_max()(a,b); } namespace Functors { /// Not equals functor. template struct m_neq { /// It uses AprilMath::m_eq function. APRIL_CUDA_EXPORT bool operator()(const T &a, const T &b) const { return !(AprilMath::m_eq(a,b)); } }; /// Logistic functor. template struct m_logistic { /** * @brief Computes AprilMath::m_sigmoid(T(1.0f),value) * @see AprilMath::m_sigmoid */ APRIL_CUDA_EXPORT T operator()(const T &value) const { return AprilMath::m_sigmoid(T(1.0f), value); } }; /// Anti-symmetric logistic functor. template struct m_antisym_logistic { /** * @brief Computes AprilMath::m_sigmoid(T(2.0f),value) - T(1.0f) * @see AprilMath::m_sigmoid */ APRIL_CUDA_EXPORT T operator()(const T &value) const { return AprilMath::m_sigmoid(T(2.0f), value) - T(1.0f); } }; /// Log-logistic functor. template struct m_log_logistic { /** * @brief Computes \f$ -log1p(exp(-x)) \f$ * @note Checks the case when @c value is a negative value large than * @c T(-10.0f) which is approximated by @c value */ APRIL_CUDA_EXPORT T operator()(const T &value) const { // The value of -log1p(exp(x)) when X is negative and large, is // approximately X return ( (value) struct m_softsign { /// Computes \f$ \displaystyle{\frac{x}{1.0 + abs(x)}} \f$ APRIL_CUDA_EXPORT T operator()(const T &value) const { return value / (T(1.0f) + AprilMath::m_abs(value)); } }; /// Softplus functor. template struct m_softplus { /** * @brief Computes \f$ log1p(exp(x)) \f$ * @note Checks the case when @c value is a positive value large than * @c T(10.0f) which is approximated by @c value */ APRIL_CUDA_EXPORT T operator()(const T &value) const { return ( (value)>T(10.0f) ) ? (value) : (AprilMath::m_log1p(AprilMath::m_exp(value))); } }; } // namespace Functors /// @see Functors::m_neq template APRIL_CUDA_EXPORT bool m_neq(const T &a, const T &b) { return Functors::m_neq()(a,b); } /// @see Functors::m_logistic template APRIL_CUDA_EXPORT T m_logistic(const T &a) { return Functors::m_logistic()(a); } /// @see Functors::m_log_logistic template APRIL_CUDA_EXPORT T m_log_logistic(const T &a) { return Functors::m_log_logistic()(a); } /// @see Functors::m_antisym_logistic template APRIL_CUDA_EXPORT T m_antisym_logistic(const T &a) { return Functors::m_antisym_logistic()(a); } /// @see Functors::m_softsign template APRIL_CUDA_EXPORT T m_softsign(const T &a) { return Functors::m_softsign()(a); } /// @see Functors::m_softplus template APRIL_CUDA_EXPORT T m_softplus(const T &a) { return Functors::m_softplus()(a); } // DERIVATIVES namespace Functors { /// Logistic derivative functor. template struct m_logistic_der { /** * @brief Computes \f$ x * (1.0 - x) \f$ * @note It receives the activation value, it is, the output * of AprilMath::m_logistic function. * @note The value is clamped between [ NEAR_ZERO, 1.0 - NEAR_ZERO] */ APRIL_CUDA_EXPORT T operator()(const T &after_actf) const { float value = AprilMath::m_clamp(after_actf, NEAR_ZERO, T(1.0f) - NEAR_ZERO); return value * (T(1.0f) - value); } }; /// Logistic derivative functor. template struct m_antisym_logistic_der { /** * @brief Computes \f$ 0.5 * (1.0 - x * x) \f$ * @note It receives the activation value, it is, the output * of AprilMath::m_antisym_logistic function. * @note The value is clamped between [ -1.0 + NEAR_ZERO, 1.0 - NEAR_ZERO] * before the transformation. */ APRIL_CUDA_EXPORT T operator()(const T &after_actf) const { T value = AprilMath::m_clamp(after_actf, T(-1.0f) + NEAR_ZERO, T(1.0f) - NEAR_ZERO); return T(0.5f) * (T(1.0f) - (value*value)); } }; /// Softsign derivative functor. template struct m_softsign_der { /** * @brief Computes \f$ \displaystyle{ \frac{1.0}{ (1.0 + abs(x))^2 } } \f$ * @note It receives the activation value, it is, the output * of AprilMath::m_softsign function. * @note The value is clamped between [ -1.0 + NEAR_ZERO, 1.0 - NEAR_ZERO] * before the transformation. */ APRIL_CUDA_EXPORT T operator()(const T &after_actf) const { T value = AprilMath::m_clamp(after_actf, T(-1.0f) + NEAR_ZERO, T(1.0f) - NEAR_ZERO); T aux = T(1.0f) + AprilMath::m_abs(value); return T(1.0f) / (aux * aux); } }; /// Softplus derivative functor. template struct m_softplus_der { /** * @brief Computes AprilMath::m_logistic(x) * @note It receives the value before the activation, the input of * AprilMath::m_softplus function. */ APRIL_CUDA_EXPORT T operator()(const T &before_actf) const { T value = AprilMath::m_logistic(before_actf); return value; } }; /// ReLU derivative functor. template struct m_relu_der { /** * @brief Computes x > T(0.0f) ? T(1.0f) : T(0.0f) * @note It receives the value before the activation, the input of * AprilMath::m_relu function. */ APRIL_CUDA_EXPORT T operator()(const T &before_actf) const { return (before_actf > T(0.0f)) ? T(1.0f) : T(0.0f); } }; /// Leaky ReLU derivative functor. template struct m_leaky_relu_der { T leak; m_leaky_relu_der(T leak) : leak(leak) { } /** * @brief Computes x > T(0.0f) ? T(1.0f) : leak * @note It receives the value before the activation, the input of * AprilMath::m_relu function. */ APRIL_CUDA_EXPORT T operator()(const T &before_actf) const { return (before_actf > T(0.0f)) ? T(1.0f) : T(leak); } }; /// Clamp derivative functor. template struct m_clamp_der { /** * @brief Computes ( x < inf || x > sup ) ? T(0.0f) : T(1.0f) * @note It receives the value before the activation, the input of * AprilMath::m_clamp function. */ APRIL_CUDA_EXPORT T operator()(const T &before_actf, const T &inf, const T &sup) const { return (before_actf < inf || before_actf > sup) ? T(0.0f) : T(1.0f); } }; } // namespace Functors /// @see Functors::m_logistic_der template APRIL_CUDA_EXPORT T m_logistic_der(const T &a) { return Functors::m_logistic_der()(a); } /// @see Functors::m_antisym_logistic_der template APRIL_CUDA_EXPORT T m_antisym_logistic_der(const T &a) { return Functors::m_antisym_logistic_der()(a); } /// @see Functors::m_softsign_der template APRIL_CUDA_EXPORT T m_softsign_der(const T &a) { return Functors::m_softsign_der()(a); } /// @see Functors::m_softplus_der template APRIL_CUDA_EXPORT T m_softplus_der(const T &a) { return Functors::m_softplus_der()(a); } /// @see Functors::m_relu_der template APRIL_CUDA_EXPORT T m_relu_der(const T &a) { return Functors::m_relu_der()(a); } /// @see Functors::m_leaky_relu_der template APRIL_CUDA_EXPORT T m_leaky_relu_der(const T &a, T leak) { return Functors::m_relu_der(leak)(a); } /// @see Functors::m_clamp_der template APRIL_CUDA_EXPORT T m_clamp_der(const T &a, const T &b, const T &c) { return Functors::m_clamp_der()(a,b,c); } //////////////// MATH SCALAR REDUCE FUNCTIONS //////////////// namespace Functors { /** * @brief Unary map and reduce functor. * * It allows to incorporate a unary map operation before another reduce * operation. * * @tparam T - The map input typename. * @tparam O - The reduce output typename. * @tparam MAP_OP - The map operation functor typename. * @tparam RED_OP - The reduce operation functor typename. */ template struct r_map1 { MAP_OP map_functor; ///< The instance of MAP_OP typename. RED_OP red_functor; ///< The instance of RED_OP typename. /// The constructor stores the functor instances. r_map1(const MAP_OP &map_functor, const RED_OP &red_functor) : map_functor(map_functor), red_functor(red_functor) { } /// Computes red_functor(acc, map_functor(b)) APRIL_CUDA_EXPORT void operator()(O &acc, const T &b) const { red_functor(acc, map_functor(b)); } }; /** * @brief Binray map and reduce functor. * * It allows to incorporate a binary map operation before another reduce * operation. * * @tparam T1 - The map input1 typename. * @tparam T2 - The map input2 typename. * @tparam O - The reduce output typename. * @tparam MAP_OP - The map operation functor typename. * @tparam RED_OP - The reduce operation functor typename. */ template struct r_map2 { MAP_OP map_functor; ///< The instance of MAP_OP typename. RED_OP red_functor; ///< The instance of RED_OP typename. /// The constructor stores the functor instances. r_map2(const MAP_OP &map_functor, const RED_OP &red_functor) : map_functor(map_functor), red_functor(red_functor) { } /// Computes red_functor(acc, map_functor(b,c)) APRIL_CUDA_EXPORT void operator()(O &acc, const T1 &b, const T2 &c) const { red_functor(acc, map_functor(b,c)); } }; /// Max reduce functor. template struct r_max { /// Computes \f$ acc = \max(acc,b) \f$ APRIL_CUDA_EXPORT void operator()(T &acc, const T &b) const { if (acc struct r_min { /// Computes \f$ acc = \min(acc,b) \f$ APRIL_CUDA_EXPORT void operator()(T &acc, const T &b) const { if (!(acc < b)) acc = b; } }; /// Max reduce with argmax computation functor. template struct r_max2 { /** * @brief Computes \f$ acc = \max(acc,b) \f$ and if @c acc which_acc = b_idx */ APRIL_CUDA_EXPORT void operator()(T &acc, const T &b, int32_t &which_acc, const int32_t b_idx) const { if (acc struct r_min2 { /** * @brief Computes \f$ acc = \min(acc,b) \f$ and if @c acc>b also * computes which_acc = b_idx */ APRIL_CUDA_EXPORT void operator()(T & acc, const T &b, int32_t &which_acc, const int32_t b_idx) const { if (!(acc struct r_add { /// Copmputes @c acc+=v using the C++ @c operator+= APRIL_CUDA_EXPORT void operator()(O &acc, const T &v) const { acc += v; } }; /// @brief Reduction for @c acc*=v template struct r_mul { /// Copmputes @c acc*=v using the C++ @c operator*= APRIL_CUDA_EXPORT void operator()(O &acc, const T &v) const { acc *= v; } }; /// @brief Reduction for @c acc/=v template struct r_div { /// Copmputes @c acc/=v using the C++ @c operator/= APRIL_CUDA_EXPORT void operator()(T &acc, const T &v) const { acc /= v; } }; /// @brief Reduction for @c acc=acc&&v template struct r_and { /// Computes acc = acc && v APRIL_CUDA_EXPORT void operator()(T &acc, const T &b) const { acc = acc && b; } }; /// @brief Reduction for @c acc=acc||v template struct r_or { /// Computes acc = acc || v APRIL_CUDA_EXPORT void operator()(T &acc, const T &b) const { acc = acc || b; } }; } // namespace Functors /// @see Functors::r_map1 template Functors::r_map1 make_r_map1(const MAP_OP &map_functor, const RED_OP &red_functor) { return Functors::r_map1(map_functor, red_functor); } /// @see Functors::r_map2 template Functors::r_map2 make_r_map2(const MAP_OP &map_functor, const RED_OP &red_functor) { return Functors::r_map2(map_functor, red_functor); } /// @see Functors::r_max template APRIL_CUDA_EXPORT void r_max(T &acc, const T &b) { Functors::r_max()(acc,b); } /// @see Functors::r_min template APRIL_CUDA_EXPORT void r_min(T &acc, const T &b) { Functors::r_min()(acc,b); } /// @see Functors::r_max2 template APRIL_CUDA_EXPORT void r_max2(T &acc, const T &b, int32_t &c, const int32_t d) { Functors::r_max2()(acc,b,c,d); } /// @see Functors::r_min2 template APRIL_CUDA_EXPORT void r_min2(T &acc, const T b, int32_t &c, const int32_t d) { Functors::r_min2()(acc,b,c,d); } /// @see Functors::r_add template APRIL_CUDA_EXPORT void r_add(O &a, const T &b) { Functors::r_add()(a,b); } /// @see Functors::r_mul template APRIL_CUDA_EXPORT void r_mul(O &a, const T &b) { Functors::r_mul()(a,b); } /// @see Functors::r_div template APRIL_CUDA_EXPORT void r_div(O &a, const T &b) { return Functors::r_div()(a,b); } /// @see Functors::r_and template APRIL_CUDA_EXPORT void r_and(T &a, const T &b) { Functors::r_and()(a,b); } /// @see Functors::r_or template APRIL_CUDA_EXPORT void r_or(T &a, const T &b) { Functors::r_or()(a,b); } /////////////////////// // Curried functions // /////////////////////// /// Curried version of AprilMath::m_clamp function. template struct m_curried_clamp { const T inf, ///< Inferior bound. sup; ///< superior bound. /// The constructor stores inf and sup values. m_curried_clamp(const T &inf, const T &sup) : inf(inf), sup(sup) { } /** * @brief Returns AprilMath::m_clamp(u, inf, sup) * @see AprilMath::m_clamp */ APRIL_CUDA_EXPORT T operator()(const T &u) const { return AprilMath::m_clamp(u, inf, sup); } }; /// Curried version of AprilMath::m_pow function. template struct m_curried_pow { const T power; ///< The power curried parameter. /// The constructor stores power value. m_curried_pow(const T &power) : power(power) { } /** * @brief Returns AprilMath::m_pow(a, power) * @see AprilMath::m_pow */ APRIL_CUDA_EXPORT T operator()(const T &a) const { return AprilMath::m_pow(a, power); } }; /// Curried version of a mask function. template struct m_curried_mask { const T masked_value; ///< The value result of application of mask. /// The constructor stores the masked_value instance. m_curried_mask(const T &masked_value) : masked_value(masked_value) { } /// Returns (mask < T(0.5f)) ? masked_value : unit APRIL_CUDA_EXPORT T operator()(const T &unit, const T &mask) const { return (mask < T(0.5f)) ? masked_value : unit; } }; /// Curried version of AprilMath::m_fill function. template struct m_curried_fill { const T value; ///< The fill value. /// The constructor stores the fill value. m_curried_fill(const T &value) : value(value) { } /// Returns value , ignores the given @c u parameter. APRIL_CUDA_EXPORT T operator()(const T &u) const { UNUSED_VARIABLE(u); return value; } }; /// Curried version of AprilMath::m_clamp_der function. template struct m_curried_clamp_der { const T inf, sup; m_curried_clamp_der(const T &inf, const T &sup) : inf(inf), sup(sup) { } /// Returns AprilMath::m_clamp_der(before_actf, inf, sup) APRIL_CUDA_EXPORT T operator()(const T &before_actf) const { return AprilMath::m_clamp_der(before_actf, inf, sup); } }; template struct m_curried_lt { const T value; m_curried_lt(const T &value) : value(value) { } APRIL_CUDA_EXPORT bool operator()(const T &a) const { return AprilMath::m_lt(a, value); } }; template struct m_curried_gt { const T value; m_curried_gt(const T &value) : value(value) { } APRIL_CUDA_EXPORT bool operator()(const T &a) const { return AprilMath::m_gt(a, value); } }; template struct m_curried_eq { const T value; m_curried_eq(const T &value) : value(value) { if (AprilMath::m_isnan(value)) { ERROR_EXIT(128, "For NaN comparison use m_curried_eq_nan\n"); } } APRIL_CUDA_EXPORT bool operator()(const T &a) const { return (a == value); } }; template struct m_curried_eq_nan { APRIL_CUDA_EXPORT bool operator()(const T &a) const { return AprilMath::m_isnan(a); } }; template struct m_curried_neq { const T value; m_curried_neq(const T &value) : value(value) { if (AprilMath::m_isnan(value)) { ERROR_EXIT(128, "For NaN comparison use m_curried_eq_nan\n"); } } APRIL_CUDA_EXPORT bool operator()(const T &a) const { return !(a == value); } }; template struct m_curried_neq_nan { APRIL_CUDA_EXPORT bool operator()(const T &a) const { return !(AprilMath::m_isnan(a)); } }; template struct m_curried_add { const T value; m_curried_add(const T &value) : value(value) { } APRIL_CUDA_EXPORT T operator()(const T &a) const { return a + value; } }; template struct m_curried_mul { const T value; m_curried_mul(const T &value) : value(value) { } APRIL_CUDA_EXPORT T operator()(const T &a) const { return a*value; } }; template struct m_curried_div { const T value; m_curried_div(const T &value) : value(value) { } APRIL_CUDA_EXPORT T operator()(const T &a) const { return value/a; } }; template struct m_curried_idiv { const T value; m_curried_idiv(const T &value) : value(value) { } APRIL_CUDA_EXPORT T operator()(const T &a) const { return a/value; } }; template struct m_curried_mod { const T value; m_curried_mod(const T &value) : value(value) { } APRIL_CUDA_EXPORT T operator()(const T &a) const { return a%value; } }; template struct m_curried_relative_equals { const float epsilon; m_curried_relative_equals(const float &epsilon) : epsilon(epsilon) { } APRIL_CUDA_EXPORT bool operator()(const T &a, const T &b) const { return AprilMath::m_relative_equals(a, b, epsilon); } }; #undef SCALAR_MAP_TEMPLATE #undef SCALAR_STD_CMATH_MAP_TEMPLATE } // namespace AprilMath #endif // CMATH_OVERLOADS_H april-ann-0.4.1/packages/basics/mathcore/c_src/copy.cu000066400000000000000000000225501263004425400226210ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "cblas_headers.h" #include "copy.impl.h" #include "cuda_utils.h" #include "unused_variable.h" namespace AprilMath { #ifdef USE_CUDA namespace CUDA { /*************************************** ************** CUDA SECTION *********** ***************************************/ template<> cublasStatus_t wrapperCublasCopy(cublasHandle_t &handle, int N, const float *x_mem, unsigned int x_inc, float *y_mem, unsigned int y_inc) { return cublasScopy(handle, N, x_mem, x_inc, y_mem, y_inc); } template<> cublasStatus_t wrapperCublasCopy(cublasHandle_t &handle, int N, const double *x_mem, unsigned int x_inc, double *y_mem, unsigned int y_inc) { return cublasDcopy(handle, N, x_mem, x_inc, y_mem, y_inc); } template<> cublasStatus_t wrapperCublasCopy(cublasHandle_t &handle, int N, const ComplexF *x_mem, unsigned int x_inc, ComplexF *y_mem, unsigned int y_inc) { return cublasCcopy(handle, N, reinterpret_cast(x_mem), x_inc, reinterpret_cast(y_mem), y_inc); } template __global__ void copyLoopKernel(unsigned int N, const T *x_mem, unsigned int x_inc, T *y_mem, unsigned int y_inc, unsigned int times, unsigned int y_ld) { unsigned int matrix_x_pos, matrix_y_pos; matrix_x_pos = blockIdx.x*blockDim.x + threadIdx.x; matrix_y_pos = blockIdx.y*blockDim.y + threadIdx.y; if (matrix_x_pos < times && matrix_y_pos < N) { unsigned int index_x = matrix_y_pos*x_inc; unsigned int index_y = matrix_x_pos*y_ld + matrix_y_pos*y_inc; y_mem[index_y] = x_mem[index_x]; } } } // namespace CUDA #endif /*************************************** ************* CBLAS SECTION *********** ***************************************/ template<> void wrapperCblasCopy(int N, const float *x_mem, unsigned int x_inc, float *y_mem, unsigned int y_inc) { cblas_scopy(N, x_mem, x_inc, y_mem, y_inc); } template<> void wrapperCblasCopy(int N, const double *x_mem, unsigned int x_inc, double *y_mem, unsigned int y_inc) { cblas_dcopy(N, x_mem, x_inc, y_mem, y_inc); } template<> void wrapperCblasCopy(int N, const ComplexF *x_mem, unsigned int x_inc, ComplexF *y_mem, unsigned int y_inc) { cblas_ccopy(N, x_mem, x_inc, y_mem, y_inc); } /*************************************** *********** TEMPLATE SECTION ********** ***************************************/ template void doCopyBroadcast(int N, GPUMirroredMemoryBlock* x, unsigned int x_inc, GPUMirroredMemoryBlock* A, unsigned int A_inc, unsigned int times, const unsigned int A_stride, bool use_gpu) { const T *x_mem; T *A_mem; #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { //printf("Doing a scopy with comp=1 & cuda=1\n"); x_mem = x->getGPUForRead(); A_mem = A->getGPUForWrite(); const unsigned int MAX_THREADS = CUDA::GPUHelper::getMaxThreadsPerBlock(); dim3 block, grid; // Number of threads on each block dimension block.x = min(MAX_THREADS, times); block.y = min(MAX_THREADS/block.x, N); block.z = 1; grid.x = (times/block.x + (times % block.x ? 1 : 0)); grid.y = (N/block.y + (N % block.y ? 1 : 0)); grid.z = 1; CUDA::copyLoopKernel<<>> (N, x_mem, x_inc, A_mem, A_inc, times, A_stride); } else { //printf("Doing a scopy with comp=1 & cuda=0\n"); #endif #ifndef USE_CUDA //printf("Doing a scopy with comp=0 & cuda=0\n"); #endif x_mem = x->getPPALForRead(); A_mem = A->getPPALForWrite(); for (unsigned int i = 0; i < times; i++) wrapperCblasCopy(N, x_mem, x_inc, A_mem + i * A_stride , A_inc); #ifdef USE_CUDA } #endif } template void doCopy(int, const GPUMirroredMemoryBlock*, unsigned int, unsigned int, GPUMirroredMemoryBlock*, unsigned int, unsigned int, bool); template void doCopy(int, const GPUMirroredMemoryBlock*, unsigned int, unsigned int, GPUMirroredMemoryBlock*, unsigned int, unsigned int, bool); template void doCopy(int, const GPUMirroredMemoryBlock*, unsigned int, unsigned int, GPUMirroredMemoryBlock*, unsigned int, unsigned int, bool); template void doCopy(int, const GPUMirroredMemoryBlock*, unsigned int, unsigned int, GPUMirroredMemoryBlock*, unsigned int, unsigned int, bool); template void doCopy(int, const GPUMirroredMemoryBlock*, unsigned int, unsigned int, GPUMirroredMemoryBlock*, unsigned int, unsigned int, bool); template void doCopy(int, const GPUMirroredMemoryBlock*, unsigned int, unsigned int, GPUMirroredMemoryBlock*, unsigned int, unsigned int, bool); template void doCopyBroadcast(int, GPUMirroredMemoryBlock*, unsigned int, GPUMirroredMemoryBlock*, unsigned int, unsigned int, const unsigned int, bool); template void doCopyBroadcast(int, GPUMirroredMemoryBlock*, unsigned int, GPUMirroredMemoryBlock*, unsigned int, unsigned int, const unsigned int, bool); template void doCopyBroadcast(int, GPUMirroredMemoryBlock*, unsigned int, GPUMirroredMemoryBlock*, unsigned int, unsigned int, const unsigned int, bool); } // namespace AprilMath april-ann-0.4.1/packages/basics/mathcore/c_src/copy.impl.h000066400000000000000000000123111263004425400233730ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef COPY_IMPL_H #define COPY_IMPL_H #include "cblas_headers.h" #include "cuda_utils.h" #include "unused_variable.h" namespace AprilMath { #ifdef USE_CUDA namespace CUDA { /*************************************** ************** CUDA SECTION *********** ***************************************/ template cublasStatus_t wrapperCublasCopy(cublasHandle_t &handle, int N, const T *x_mem, unsigned int x_inc, T *y_mem, unsigned int y_inc) { UNUSED_VARIABLE(handle); UNUSED_VARIABLE(N); UNUSED_VARIABLE(x_mem); UNUSED_VARIABLE(x_inc); UNUSED_VARIABLE(y_mem); UNUSED_VARIABLE(y_inc); ERROR_EXIT(128, "CUDA VERSION NOT IMPLEMENTED\n"); return CUBLAS_STATUS_INTERNAL_ERROR; } template<> cublasStatus_t wrapperCublasCopy(cublasHandle_t &handle, int N, const float *x_mem, unsigned int x_inc, float *y_mem, unsigned int y_inc); template<> cublasStatus_t wrapperCublasCopy(cublasHandle_t &handle, int N, const double *x_mem, unsigned int x_inc, double *y_mem, unsigned int y_inc); template<> cublasStatus_t wrapperCublasCopy(cublasHandle_t &handle, int N, const ComplexF *x_mem, unsigned int x_inc, ComplexF *y_mem, unsigned int y_inc); } // namespace CUDA #endif /*************************************** ************* CBLAS SECTION *********** ***************************************/ template void wrapperCblasCopy(int N, const T *x_mem, unsigned int x_inc, T *y_mem, unsigned int y_inc) { for (int i=0; i void wrapperCblasCopy(int N, const float *x_mem, unsigned int x_inc, float *y_mem, unsigned int y_inc); template<> void wrapperCblasCopy(int N, const double *x_mem, unsigned int x_inc, double *y_mem, unsigned int y_inc); template<> void wrapperCblasCopy(int N, const ComplexF *x_mem, unsigned int x_inc, ComplexF *y_mem, unsigned int y_inc); /*************************************** *********** TEMPLATE SECTION ********** ***************************************/ template void doCopy(int N, const GPUMirroredMemoryBlock* x, unsigned int x_inc, unsigned int x_shift, GPUMirroredMemoryBlock* y, unsigned int y_inc, unsigned int y_shift, bool use_gpu) { const T *x_mem; T *y_mem; #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { cublasStatus_t status; cublasHandle_t handle = CUDA::GPUHelper::getHandler(); //printf("Doing a scopy with comp=1 & cuda=1\n"); x_mem = x->getGPUForRead() + x_shift; y_mem = y->getGPUForWrite() + y_shift; status = cublasSetStream(handle, CUDA::GPUHelper::getCurrentStream()); checkCublasError(status); status = CUDA::wrapperCublasCopy(handle, N, x_mem, x_inc, y_mem, y_inc); checkCublasError(status); } else { //printf("Doing a scopy with comp=1 & cuda=0\n"); #endif #ifndef USE_CUDA //printf("Doing a scopy with comp=0 & cuda=0\n"); #endif x_mem = x->getPPALForRead() + x_shift; y_mem = y->getPPALForWrite() + y_shift; wrapperCblasCopy(N, x_mem, x_inc, y_mem, y_inc); #ifdef USE_CUDA } #endif } } // namespace AprilMath #endif // COPY_IMPL_H april-ann-0.4.1/packages/basics/mathcore/c_src/cublas_error.cc000066400000000000000000000036651263004425400243150ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "cublas_error.h" #include "error_print.h" #ifdef USE_CUDA void checkCublasError(cublasStatus_t status) { if (status == CUBLAS_STATUS_SUCCESS) { return; } else if (status == CUBLAS_STATUS_NOT_INITIALIZED) { ERROR_EXIT(152, "Cublas is not initialized!\n"); } else if (status == CUBLAS_STATUS_ALLOC_FAILED) { ERROR_EXIT(153, "Cublas resource allocation failed!\n"); } else if (status == CUBLAS_STATUS_INVALID_VALUE) { ERROR_EXIT(154, "Cublas detected an unsupported parameter.\n"); } else if (status == CUBLAS_STATUS_ARCH_MISMATCH) { ERROR_EXIT(155, "Cublas and architecture not compatible.\n"); } else if (status == CUBLAS_STATUS_MAPPING_ERROR) { ERROR_EXIT(156, "Cublas accessed to a wrong GPU memory space!\n"); } else if (status == CUBLAS_STATUS_EXECUTION_FAILED) { ERROR_EXIT(157, "Cublas failed to execute the operation\n"); } else if (status == CUBLAS_STATUS_INTERNAL_ERROR) { ERROR_EXIT(158, "Cublas failed to execute an internal operation!\n"); } else { ERROR_EXIT(128, "Uknown Cublas error\n"); } } #endif april-ann-0.4.1/packages/basics/mathcore/c_src/cublas_error.h000066400000000000000000000020311263004425400241410ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef _CUBLAS_ERROR_H_ #define _CUBLAS_ERROR_H_ #ifdef USE_CUDA #include void checkCublasError(cublasStatus_t status); #endif #endif // _CUBLAS_ERROR_H_ april-ann-0.4.1/packages/basics/mathcore/c_src/cuda_headers.h000066400000000000000000000034411263004425400240740ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2015, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef CUDA_HEADERS_H #define CUDA_HEADERS_H // AUXILIAR INLINE FUNCTIONS // #ifdef USE_CUDA #include #include #include #include #define MAX_CUDA_REDUCE_THREAD_SIZE 1024 #define MIN_CUDA_REDUCE_THREAD_SIZE 8 #define MAX_CUDA_REDUCE_NUM_THREADS 1024 // must be multiple of 2 (wrap size=32) #define APRIL_CUDA_EXPORT __host__ __device__ #define APRIL_CUDA_ERROR_EXIT(code,msg) aprilCudaErrorExit((code),(msg)) // FIXME: implement properly this feature to control errors in CUDA kernels and // CPU equivalent code. static APRIL_CUDA_EXPORT void aprilCudaErrorExit(int code, const char *msg) { UNUSED_VARIABLE(code); UNUSED_VARIABLE(msg); // do nothing } // static void aprilCudaErrorExit(int code, const char *msg) { // ERROR_EXIT(code,msg); // } #else #define APRIL_CUDA_EXPORT #define APRIL_CUDA_ERROR_EXIT(code,msg) ERROR_EXIT(code,msg) #endif #endif // CUDA_UTILS_H april-ann-0.4.1/packages/basics/mathcore/c_src/cuda_kernel_templates.h000066400000000000000000001202211263004425400260130ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef CUDA_KERNEL_TEMPLATES_H #define CUDA_KERNEL_TEMPLATES_H #ifdef USE_CUDA #include "ceiling_power_of_two.h" #include "complex_number.h" #include "cublas_error.h" #include "cuda_utils.h" #include "cusparse_error.h" #include "gpu_mirrored_memory_block.h" #include "gpu_helper.h" #include "smart_ptr.h" #include "unused_variable.h" namespace AprilMath { namespace CUDA { /////////////////////////////// REDUCE //////////////////////////////////// /** * @brief Two pass CUDA reduce kernel. * * Performs a reduction with @c T input type and @c O output type, by using * @c F functor to reduce input data into output data, and @c P functor to * reduce intermediate output data. * * @tparam T - The type for input vectors. * @tparam O - The type for output vectors. * @tparam F - An operator implemented as a functor. * @tparam P - An operator implemented as a functor. * @tparam overwrite_output - A boolean indicating if output data has to be * ignored (overwritten) or reduced with the result of this computation. * * @param input - The input vector. * @param input_stride - The stride between consecutive values at input. * @param output - The output vector. * @param N - Size of the input vector. * @param reduce_op - The functor operator with the reduction over two * values. * @param partials_reduce_op - The functor operator with the reduction over * two partial values. * @param zero - The initial value for the reduction. * * @note Adapted from CUDA Handbook: * - http://www.cudahandbook.com/ * - https://github.com/ArchaeaSoftware/cudahandbook * * @code * // First pass call. * genericCudaReduce1Kernel * <<>> * (input_ptr, input_stride, blocks_ptr, 1u, N, reduce_op, * partials_reduce_op, zero); * // Second pass call. * genericCudaReduce1Kernel * <<<1, num_threads, num_threads*sizeof(O), GPUHelper::getCurrentStream()>>> * (blocks_ptr, 1u, dest_ptr, 1u, * static_cast(num_blocks), partials_reduce_op, * partials_reduce_op, zero); * @endcode */ template __global__ void genericCudaReduce1Kernel(const T *input, unsigned int input_stride, O *output, unsigned int output_stride, unsigned int N, F reduce_op, P partials_reduce_op, O zero) { SharedMemory partials; O result = zero; const int tid = threadIdx.x; for ( size_t i = blockIdx.x*blockDim.x + tid; i < N; i += blockDim.x*gridDim.x ) { reduce_op(result, input[i * input_stride]); } partials[tid] = result; __syncthreads(); for ( int activeThreads = blockDim.x>>1; activeThreads; activeThreads >>= 1 ) { if ( tid < activeThreads ) { partials_reduce_op(partials[tid], partials[tid+activeThreads]); } __syncthreads(); } if ( tid == 0 ) { if (overwrite_output) { output[blockIdx.x * output_stride] = zero; } partials_reduce_op(output[blockIdx.x * output_stride], partials[0]); } } /** * @brief Two pass CUDA reduce kernel for two input vectors. * * Performs a reduction with @c T1 and @c T2 input types and @c O output * type, by using @c F functor to reduce input data into output data, and @c * P functor to reduce intermediate output data. * * @tparam T1 - The type for input1 vectors. * @tparam T2 - The type for input2 vectors. * @tparam O - The type for output vectors. * @tparam F - An operator implemented as a functor. * @tparam P - An operator implemented as a functor. * @tparam overwrite_output - A boolean indicating if output data has to be * ignored (overwritten) or reduced with the result of this computation. * * @param input1 - The input1 vector. * @param input1_stride - The stride between consecutive values at input1. * @param input2 - The input2 vector. * @param input2_stride - The stride between consecutive values at input2. * @param output - The output vector. * @param N - Size of the input vector. * @param reduce_op - The functor operator with the reduction over two * values. * @param partials_reduce_op - The functor operator with the reduction over * two partial values. * @param zero - The initial value for the reduction. * * @note Adapted from CUDA Handbook: * - http://www.cudahandbook.com/ * - https://github.com/ArchaeaSoftware/cudahandbook * * @code * // First pass call. * genericCudaReduce2Kernel * <<>> * (input1_ptr, input1_stride, input2_ptr, input2_stride, blocks_ptr, 1u, N, reduce_op, * partials_reduce_op, zero); * // Second pass call. * genericCudaReduce1Kernel * <<<1, num_threads, num_threads*sizeof(O), GPUHelper::getCurrentStream()>>> * (blocks_ptr, 1u, dest_ptr, 1u, * static_cast(num_blocks), partials_reduce_op, * partials_reduce_op, zero); * @endcode */ template __global__ void genericCudaReduce2Kernel(const T1 *input1, unsigned int input1_stride, const T2 *input2, unsigned int input2_stride, O *output, unsigned int output_stride, unsigned int N, F reduce_op, P partials_reduce_op, O zero) { SharedMemory partials; O result = zero; const int tid = threadIdx.x; for ( size_t i = blockIdx.x*blockDim.x + tid; i < N; i += blockDim.x*gridDim.x ) { reduce_op(result, input1[i * input1_stride], input2[i * input2_stride]); } partials[tid] = result; __syncthreads(); for ( int activeThreads = blockDim.x>>1; activeThreads; activeThreads >>= 1 ) { if ( tid < activeThreads ) { partials_reduce_op(partials[tid], partials[tid+activeThreads]); } __syncthreads(); } if ( tid == 0 ) { if (overwrite_output) { output[blockIdx.x * output_stride] = zero; } partials_reduce_op(output[blockIdx.x * output_stride], partials[0]); } } /** * @brief First pass of CUDA reduce kernel for Min/Max reduction. * * The Min/Max reduction allows to retrieve ArgMin/ArgMax value. Performs a * reduction with @c T input/output type, by using @c F functor to reduce * input data into intermediate output data vector. * * @tparam T - The type for input/output vectors. * @tparam F - An operator implemented as a functor for reduce_op param. * * @param input - The input vector. * @param input_stride - The stride between consecutive values at input. * @param which - The output vector for ArgMax/ArgMin result. * @param which_stride - The stride between consecutive values at which. * @param output - The output vector. * @param output_stride - The stride between consecutive values at output. * @param N - Size of the input vector. * @param reduce_op - The functor operator with the reduction over two * values. * @param zero - The initial value for the reduction. * * @note Adapted from CUDA Handbook: * - http://www.cudahandbook.com/ * - https://github.com/ArchaeaSoftware/cudahandbook * * @note This kernel overwrites the content of @c which and @c output * vectors. */ template __global__ void genericCudaReduceMinMaxKernel(const T *input, unsigned int input_stride, int32_t *which, unsigned int which_stride, T *output, unsigned int output_stride, unsigned int N, F reduce_op, T zero) { SharedMemory partials; int32_t *which_partials = (int32_t*)(&partials[blockDim.x]); int32_t which_result=0; T result = zero; const int tid = threadIdx.x; for ( size_t i = blockIdx.x*blockDim.x + tid; i < N; i += blockDim.x*gridDim.x ) { reduce_op(result, input[i * input_stride], // i+1 because Lua startas at 1. which_result, static_cast(i+1)); } partials[tid] = result; which_partials[tid] = which_result; __syncthreads(); for ( int activeThreads = blockDim.x>>1; activeThreads; activeThreads >>= 1 ) { if ( tid < activeThreads ) { reduce_op(partials[tid], partials[tid+activeThreads], which_partials[tid], which_partials[tid+activeThreads]); } __syncthreads(); } if ( tid == 0 ) { // Overwrites the output output[blockIdx.x * output_stride] = partials[0]; which[blockIdx.x * which_stride] = which_partials[0]; } } /** * @brief First pass of CUDA reduce kernel for Min/Max reduction. * * The Min/Max reduction allows to retrieve ArgMin/ArgMax value. Performs a * reduction with @c T input/output type, by using @c F functor to reduce * input data into intermediate output data vector. * * @tparam T - The type for input/output vectors. * @tparam F - An operator implemented as a functor for reduce_op param. * @tparam overwrite_output - A boolean indicating if output data has to be * ignored (overwritten) or reduced with the result of this computation. * * @param which_input - The input vector with intermediate ArgMin/ArgMax values. * @param which_input_stride - The stride between consecutive values at input. * @param input - The input vector. * @param input_stride - The stride between consecutive values at input. * @param which - The output for ArgMax/ArgMin result. * @param which_stride - The stride between consecutive values at which. * @param output - The output vector. * @param output_stride - The stride between consecutive values at output. * @param N - Size of the input vector. * @param reduce_op - The functor operator with the reduction over two * values. * @param zero - The initial value for the reduction. * * @note Adapted from CUDA Handbook: * - http://www.cudahandbook.com/ * - https://github.com/ArchaeaSoftware/cudahandbook */ template __global__ void genericCudaReduceMinMaxKernel2(const int32_t *which_input, unsigned int which_input_stride, const T *input, unsigned int input_stride, int32_t *which, unsigned int which_stride, T *output, unsigned int output_stride, unsigned int N, F reduce_op, T zero) { SharedMemory partials; int32_t *which_partials = (int32_t*)(&partials[blockDim.x]); int32_t which_result=0; T result = zero; const int tid = threadIdx.x; for ( size_t i = blockIdx.x*blockDim.x + tid; i < N; i += blockDim.x*gridDim.x ) { reduce_op(result, input[i * input_stride], which_result, which_input[i * which_input_stride]); } partials[tid] = result; which_partials[tid] = which_result; __syncthreads(); for ( int activeThreads = blockDim.x>>1; activeThreads; activeThreads >>= 1 ) { if ( tid < activeThreads ) { reduce_op(partials[tid], partials[tid+activeThreads], which_partials[tid], which_partials[tid+activeThreads]); } __syncthreads(); } if ( tid == 0 ) { if (overwrite_output) { output[blockIdx.x * output_stride] = zero; which[blockIdx.x * which_stride] = 0; } reduce_op(output[blockIdx.x * output_stride], partials[0], which[blockIdx.x * which_stride], which_partials[0]); } } /** * @brief Performs a CUDA reduce over a vector and stores its result at * a given position into another vector. * * The reduce operations are performed in a two-pass fashion. First * reducing the input vector into an intermediate memory as large as * the number executed blocks. Second pass reduces the intermediate memory * into the given position of the output vector. * * @tparam T - The type for input vector. * @tparam O - The type for output vector. * @tparam F - An operator implemented as a functor for reduce_op param. * @tparam P - An operator implemented as a functor for partials_reduce_op param. * * @param input - The input vector. * @param input_stride - The stride between consecutive values at input. * @param input_shift - The first valid position at input vector. * @param zero - The value of reduce over zero elements. * @param dest - The output vector. * @param dest_shift - The first valid position at dest vector. * @param set_dest_to_zero - A boolean indicating if dest memory has to be * initialized to zero, otherwise its content will be reduced allowing to * perform chains of multiple reductions over the same dest pointer. * @param reduce_op - The functor operator with the reduce one input values * into an output accumulator. * @param partials_reduce_op - The functor operator with the reduce over two * output values. */ template void genericCudaReduce1Call(unsigned int N, const GPUMirroredMemoryBlock *input, unsigned int input_stride, unsigned int input_shift, O zero, GPUMirroredMemoryBlock *dest, unsigned int dest_shift, bool set_dest_to_zero, F reduce_op, P partials_reduce_op) { if (N == 0u) { if (set_dest_to_zero) dest->putValue(dest_shift, zero); return; } int num_threads, thread_size, num_blocks; computeReductionSize(static_cast(N), num_threads, thread_size, num_blocks); const T *input_ptr = input->getGPUForRead() + input_shift; if (num_blocks > 1) { AprilUtils::SharedPtr< GPUMirroredMemoryBlock > blocks(new GPUMirroredMemoryBlock(static_cast(num_blocks))); O *blocks_ptr = blocks->getGPUForWrite(); // first pass genericCudaReduce1Kernel <<>> (input_ptr, input_stride, blocks_ptr, 1u, N, reduce_op, partials_reduce_op, zero); computeSecondReductionSize(num_blocks, num_threads); // second pass if (set_dest_to_zero) { O *dest_ptr = dest->getGPUForWrite() + dest_shift; genericCudaReduce1Kernel <<<1, num_threads, num_threads*sizeof(O), GPUHelper::getCurrentStream()>>> (blocks_ptr, 1u, dest_ptr, 1u, static_cast(num_blocks), partials_reduce_op, partials_reduce_op, zero); } else { O *dest_ptr = dest->getGPUForReadAndWrite() + dest_shift; genericCudaReduce1Kernel <<<1, num_threads, num_threads*sizeof(O), GPUHelper::getCurrentStream()>>> (blocks_ptr, 1u, dest_ptr, 1u, static_cast(num_blocks), partials_reduce_op, partials_reduce_op, zero); } } // num_blocks > 1 else { // num_blocks == 1 // only one pass if (set_dest_to_zero) { O *dest_ptr = dest->getGPUForWrite() + dest_shift; genericCudaReduce1Kernel <<<1, num_threads, num_threads*sizeof(O), GPUHelper::getCurrentStream()>>> (input_ptr, input_stride, dest_ptr, 1u, N, reduce_op, partials_reduce_op, zero); } else { O *dest_ptr = dest->getGPUForReadAndWrite() + dest_shift; genericCudaReduce1Kernel <<<1, num_threads, num_threads*sizeof(O), GPUHelper::getCurrentStream()>>> (input_ptr, input_stride, dest_ptr, 1u, N, reduce_op, partials_reduce_op, zero); } } // TODO: check return value (cudaError_t) // cudaDeviceSynchronize(); } // function genericCudaReduce1Call /** * @brief Performs a CUDA reduce over a two vectors and stores its result at * a given position into another vector. * * The reduce operations are performed in a two-pass fashion. First * reducing the input vectors into an intermediate memory as large as * the number executed blocks. Second pass reduces the intermediate memory * into the given position of the output vector. * * @tparam T1 - The type for input1 vector. * @tparam T2 - The type for input2 vector. * @tparam O - The type for output vector. * @tparam F - An operator implemented as a functor for reduce_op param. * @tparam P - An operator implemented as a functor for partials_reduce_op param. * * @param input1 - The input1 vector. * @param input1_stride - The stride between consecutive values at input1. * @param input1_shift - The first valid position at input1 vector. * @param input2 - The input2 vector. * @param input2_stride - The stride between consecutive values at input2. * @param input2_shift - The first valid position at input2 vector. * @param zero - The value of reduce over zero elements. * @param dest - The output vector. * @param dest_shift - The first valid position at dest vector. * @param set_dest_to_zero - A boolean indicating if dest memory has to be * initialized to zero, otherwise its content will be reduced allowing to * perform chains of multiple reductions over the same dest pointer. * @param reduce_op - The functor operator with the reduce one input values * into an output accumulator. * @param partials_reduce_op - The functor operator with the reduce over two * output values. */ template void genericCudaReduce2Call(unsigned int N, const GPUMirroredMemoryBlock *input1, unsigned int input1_stride, unsigned int input1_shift, const GPUMirroredMemoryBlock *input2, unsigned int input2_stride, unsigned int input2_shift, O zero, GPUMirroredMemoryBlock *dest, unsigned int dest_shift, bool set_dest_to_zero, F reduce_op, P partials_reduce_op) { if (N == 0u) { if (set_dest_to_zero) dest->putValue(dest_shift, zero); return; } int num_threads, thread_size, num_blocks; computeReductionSize(static_cast(N), num_threads, thread_size, num_blocks); const T1 *input1_ptr = input1->getGPUForRead() + input1_shift; const T2 *input2_ptr = input2->getGPUForRead() + input2_shift; if (num_blocks > 1) { AprilUtils::SharedPtr< GPUMirroredMemoryBlock > blocks(new GPUMirroredMemoryBlock(static_cast(num_blocks))); O *blocks_ptr = blocks->getGPUForWrite(); // first pass genericCudaReduce2Kernel <<>> (input1_ptr, input1_stride, input2_ptr, input2_stride, blocks_ptr, 1u, N, reduce_op, partials_reduce_op, zero); computeSecondReductionSize(num_blocks, num_threads); // second pass if (set_dest_to_zero) { O *dest_ptr = dest->getGPUForWrite() + dest_shift; genericCudaReduce1Kernel <<<1, num_threads, num_threads*sizeof(O), GPUHelper::getCurrentStream()>>> (blocks_ptr, 1u, dest_ptr, 1u, static_cast(num_blocks), partials_reduce_op, partials_reduce_op, zero); } else { O *dest_ptr = dest->getGPUForReadAndWrite() + dest_shift; genericCudaReduce1Kernel <<<1, num_threads, num_threads*sizeof(O), GPUHelper::getCurrentStream()>>> (blocks_ptr, 1u, dest_ptr, 1u, static_cast(num_blocks), partials_reduce_op, partials_reduce_op, zero); } } // num_blocks > 1 else { // num_blocks == 1 // only one pass if (set_dest_to_zero) { O *dest_ptr = dest->getGPUForWrite() + dest_shift; genericCudaReduce2Kernel <<<1, num_threads, num_threads*sizeof(O), GPUHelper::getCurrentStream()>>> (input1_ptr, input1_stride, input2_ptr, input2_stride, dest_ptr, 1u, N, reduce_op, partials_reduce_op, zero); } else { O *dest_ptr = dest->getGPUForReadAndWrite() + dest_shift; genericCudaReduce2Kernel <<<1, num_threads, num_threads*sizeof(O), GPUHelper::getCurrentStream()>>> (input1_ptr, input1_stride, input2_ptr, input2_stride, dest_ptr, 1u, N, reduce_op, partials_reduce_op, zero); } } // TODO: check return value (cudaError_t) // cudaDeviceSynchronize(); } // function genericCudaReduce2Call /** * @brief Performs a CUDA Min/Max reduce over a vector and stores its result * at a given position into another vector. * * The reduce operations are performed in a two-pass fashion. First * reducing the input vector into an intermediate memory as large as * the number executed blocks. Second pass reduces the intermediate memory * into the given position of the output vector. * * @tparam T - The type for input/output vectors. * @tparam F - An operator implemented as a functor for reduce_op param. * * @param input - The input vector. * @param input_stride - The stride between consecutive values at input. * @param input_shift - The first valid position at input vector. * @param zero - The value of reduce over zero elements. * @param which - The output vector where to store ArgMin/ArgMax result. * @param which_shift - The first valid position at which vector. * @param dest - The output vector. * @param dest_shift - The first valid position at dest vector. * @param set_dest_to_zero - A boolean indicating if dest memory has to be * initialized to zero, otherwise its content will be reduced allowing to * perform chains of multiple reductions over the same dest pointer. * @param reduce_op - The functor operator with the reduce one input values * into an output accumulator. */ template void genericCudaReduceMinMaxCall(unsigned int N, const GPUMirroredMemoryBlock *input, unsigned int input_stride, unsigned int input_shift, T zero, GPUMirroredMemoryBlock *which, unsigned int which_shift, GPUMirroredMemoryBlock *dest, unsigned int dest_shift, bool set_dest_to_zero, F reduce_op) { if (N == 0u) { if (set_dest_to_zero) { dest->putValue(dest_shift, zero); which->putValue(which_shift, 0); } return; } int num_threads, thread_size, num_blocks; computeReductionSize(static_cast(N), num_threads, thread_size, num_blocks); const T *input_ptr = input->getGPUForRead() + input_shift; AprilUtils::SharedPtr< GPUMirroredMemoryBlock > blocks(new GPUMirroredMemoryBlock(static_cast(num_blocks))); AprilUtils::SharedPtr< GPUMirroredMemoryBlock > which_blocks(new GPUMirroredMemoryBlock(static_cast(num_blocks))); T *blocks_ptr = blocks->getGPUForWrite(); int32_t *which_blocks_ptr = which_blocks->getGPUForWrite(); // First pass genericCudaReduceMinMaxKernel<<>> (input_ptr, input_stride, which_blocks_ptr, 1u, blocks_ptr, 1u, N, reduce_op, zero); computeSecondReductionSize(num_blocks, num_threads); if (set_dest_to_zero) { int32_t *which_ptr = which->getGPUForWrite() + which_shift; T *dest_ptr = dest->getGPUForWrite() + dest_shift; // Second pass genericCudaReduceMinMaxKernel2<<>> (which_blocks_ptr, 1u, blocks_ptr, 1u, which_ptr, 1u, dest_ptr, 1u, static_cast(num_blocks), reduce_op, zero); } else { int32_t *which_ptr = which->getGPUForReadAndWrite() + which_shift; T *dest_ptr = dest->getGPUForReadAndWrite() + dest_shift; // Second pass genericCudaReduceMinMaxKernel2<<>> (which_blocks_ptr, 1u, blocks_ptr, 1u, which_ptr, 1u, dest_ptr, 1u, static_cast(num_blocks), reduce_op, zero); } // TODO: check return value (cudaError_t) // cudaDeviceSynchronize(); } // function genericCudaReduceMinMaxCall /////////////////////////////// MAP //////////////////////////////////// /** * @brief Executes the CUDA map kernel over a vector position. * * @tparam T - The type for input vector. * @tparam O - The type for output vector. * @tparam F - An operator implemented as a functor. * * @param input - The input vector. * @param input_stride - The stride between consecutive values at input. * @param output - The output vector. * @param output_stride - The stride between consecutive values at output. * @param size - Size of the input and output vectors. * @param map_op - The functor operator with the unary map function. */ template __global__ void genericCudaMap1Kernel(const T *input, unsigned int input_stride, O *output, unsigned int output_stride, unsigned int size, F map_op) { for ( size_t i = blockIdx.x*blockDim.x + threadIdx.x; i < size; i += blockDim.x*gridDim.x ) { output[i*output_stride] = map_op(input[i*input_stride]); } } /** * @brief Executes the CUDA map kernel over two vectors. * * @tparam T1 - The type for input1 vector. * @tparam T2 - The type for input2 vector. * @tparam O - The type for output vector. * @tparam F - An operator implemented as a functor. * * @param input1 - The first input vector. * @param input1_stride - The stride between consecutive values at input1. * @param input2 - The second input vector. * @param input2_stride - The stride between consecutive values at input2. * @param output - The output vector. * @param output_stride - The stride between consecutive values at output. * @param size - Size of the input and output vectors. * @param map_op - The functor operator with the binary map function. */ template __global__ void genericCudaMap2Kernel(const T1 *input1, unsigned int input1_stride, const T2 *input2, unsigned int input2_stride, O *output, unsigned int output_stride, unsigned int size, F map_op) { for ( size_t i = blockIdx.x*blockDim.x + threadIdx.x; i < size; i += blockDim.x*gridDim.x ) { output[i*output_stride] = map_op(input1[i*input1_stride], input2[i*input2_stride]); } } /** * @brief Executes the CUDA map kernel over three vectors. * * @tparam T1 - The type for input1 vector. * @tparam T2 - The type for input2 vector. * @tparam T3 - The type for input3 vector. * @tparam O - The type for output vector. * @tparam F - An operator implemented as a functor. * * @param input1 - The first input vector. * @param input1_stride - The stride between consecutive values at input1. * @param input2 - The second input vector. * @param input2_stride - The stride between consecutive values at input2. * @param input3 - The second input vector. * @param input3_stride - The stride between consecutive values at input3. * @param output - The output vector. * @param output_stride - The stride between consecutive values at output. * @param size - Size of the input and output vectors. * @param map_op - The functor operator with the binary map function. */ template __global__ void genericCudaMap3Kernel(const T1 *input1, unsigned int input1_stride, const T2 *input2, unsigned int input2_stride, const T3 *input3, unsigned int input3_stride, O *output, unsigned int output_stride, unsigned int size, F map_op) { for ( size_t i = blockIdx.x*blockDim.x + threadIdx.x; i < size; i += blockDim.x*gridDim.x ) { output[i*output_stride] = map_op(input1[i*input1_stride], input2[i*input2_stride], input3[i*input3_stride]); } } /** * @brief Performs a CUDA map over a vector and stores its result at * another vector. * * @note Input and output vectors can be the same. * * @tparam T - The type for input vector. * @tparam O - The type for output vector. * @tparam F - An operator implemented as a functor. * * @param input - The input vector. * @param input_stride - The stride between consecutive values at input. * @param input_shift - The first valid position at input vector. * @param output - The output vector. * @param output_stride - The stride between consecutive values at output. * @param output_shift - The first valid position at output vector. * @param map_op - The functor operator with the unary map. */ template void genericCudaMap1Call(unsigned int N, const GPUMirroredMemoryBlock *input, unsigned int input_stride, unsigned int input_shift, GPUMirroredMemoryBlock *output, unsigned int output_stride, unsigned int output_shift, F map_op) { if (N == 0u) return; // Nothing to do! const T *input_ptr = input->getGPUForRead() + input_shift; O *output_ptr = output->getGPUForWrite() + output_shift; int num_threads, num_blocks; computeBlockAndGridSizesForArray(N, num_threads, num_blocks); genericCudaMap1Kernel<<>> (input_ptr, input_stride, output_ptr, output_stride, N, map_op); } // function genericCudaMap1Call /** * @brief Performs a CUDA map over two vectors and stores its result at * another vector. * * @note Input1, input2 and output vectors can be the same. * * @tparam T1 - The type for input1 vector. * @tparam T2 - The type for input2 vector. * @tparam F - An operator implemented as a functor. * * @param input1 - The first input vector. * @param input1_stride - The stride between consecutive values at input1. * @param input1_shift - The first valid position at input1. * @param input2 - The second input vector. * @param input2_stride - The stride between consecutive values at input2. * @param input2_shift - The first valid position at input2. * @param output - The output vector. * @param output_stride - The stride between consecutive values at output. * @param output_shift - The first valid position at output vector. * @param map_op - The functor operator with the binary map. */ template void genericCudaMap2Call(unsigned int N, const GPUMirroredMemoryBlock *input1, unsigned int input1_stride, unsigned int input1_shift, const GPUMirroredMemoryBlock *input2, unsigned int input2_stride, unsigned int input2_shift, GPUMirroredMemoryBlock *output, unsigned int output_stride, unsigned int output_shift, F map_op) { if (N == 0u) return; // Nothing to do! const T1 *input1_ptr = input1->getGPUForRead() + input1_shift; const T2 *input2_ptr = input2->getGPUForRead() + input2_shift; O *output_ptr = output->getGPUForWrite() + output_shift; dim3 block, grid; int num_threads, num_blocks; computeBlockAndGridSizesForArray(N, num_threads, num_blocks); genericCudaMap2Kernel<<>> (input1_ptr, input1_stride, input2_ptr, input2_stride, output_ptr, output_stride, N, map_op); } // function genericCudaMap1Call /** * @brief Performs a CUDA map over three vectors and stores its result at * another vector. * * @note Input1, input2, input3, and output vectors can be the same. * * @tparam T1 - The type for input1 vector. * @tparam T2 - The type for input2 vector. * @tparam T3 - The type for input3 vector. * @tparam F - An operator implemented as a functor. * * @param input1 - The first input vector. * @param input1_stride - The stride between consecutive values at input1. * @param input1_shift - The first valid position at input1. * @param input2 - The second input vector. * @param input2_stride - The stride between consecutive values at input2. * @param input2_shift - The first valid position at input2. * @param input3 - The second input vector. * @param input3_stride - The stride between consecutive values at input3. * @param input3_shift - The first valid position at input3. * @param output - The output vector. * @param output_stride - The stride between consecutive values at output. * @param output_shift - The first valid position at output vector. * @param map_op - The functor operator with the binary map. */ template void genericCudaMap3Call(unsigned int N, const GPUMirroredMemoryBlock *input1, unsigned int input1_stride, unsigned int input1_shift, const GPUMirroredMemoryBlock *input2, unsigned int input2_stride, unsigned int input2_shift, const GPUMirroredMemoryBlock *input3, unsigned int input3_stride, unsigned int input3_shift, GPUMirroredMemoryBlock *output, unsigned int output_stride, unsigned int output_shift, F map_op) { if (N == 0u) return; // Nothing to do! const T1 *input1_ptr = input1->getGPUForRead() + input1_shift; const T2 *input2_ptr = input2->getGPUForRead() + input2_shift; const T3 *input3_ptr = input3->getGPUForRead() + input3_shift; O *output_ptr = output->getGPUForWrite() + output_shift; dim3 block, grid; int num_threads, num_blocks; computeBlockAndGridSizesForArray(N, num_threads, num_blocks); genericCudaMap3Kernel<<>> (input1_ptr, input1_stride, input2_ptr, input2_stride, input3_ptr, input3_stride, output_ptr, output_stride, N, map_op); } // function genericCudaMap3Call } // namespace CUDA } // namespace AprilMath #endif // USE_CUDA #endif // CUDA_KERNEL_TEMPLATES_H april-ann-0.4.1/packages/basics/mathcore/c_src/cuda_utils.h000066400000000000000000000165311263004425400236250ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef CUDA_UTILS_H #define CUDA_UTILS_H #include "error_print.h" // AUXILIAR INLINE FUNCTIONS // #ifdef USE_CUDA #include #include #include #include #include "cblas_headers.h" #include "ceiling_power_of_two.h" #include "complex_number.h" #include "cuda_headers.h" #include "maxmin.h" #include "gpu_helper.h" namespace AprilMath { /// Contains CUDA kernels, helper classes and functions. namespace CUDA { // // From Reduction SDK sample: // // Utility class used to avoid linker errors with extern // unsized shared memory arrays with templated type // template struct SharedMemory { __device__ inline operator T*() { extern __shared__ int __smem[]; return (T*) (void *) __smem; } __device__ inline operator const T*() const { extern __shared__ int __smem[]; return (T*) (void *) __smem; } }; // // from Reduction SDK sample: // specialize to avoid unaligned memory // access compile errors // #define SPECIALIZE_CUDA_SHARED_MEMORY(FULLTYPE,TYPE) \ namespace AprilMath { \ namespace CUDA { \ template<> \ struct SharedMemory \ { \ __device__ inline operator FULLTYPE*() \ { \ extern __shared__ FULLTYPE \ __smem_##TYPE[]; \ return (FULLTYPE*)__smem_##TYPE; \ } \ __device__ inline operator const FULLTYPE*() const \ { \ extern __shared__ FULLTYPE \ __smem_##TYPE[]; \ return (FULLTYPE*)__smem_##TYPE; \ } \ }; \ } \ } static __device__ unsigned int getArrayIndex(const dim3 &blockIdx, const dim3 &blockDim, const dim3 &threadIdx) { return blockIdx.x * blockDim.x + threadIdx.x; } static __device__ void getMatrixIndices(const dim3 &blockIdx, const dim3 &blockDim, const dim3 &threadIdx, unsigned int &matrix_row_pos, unsigned int &matrix_col_pos) { matrix_row_pos = blockIdx.x*blockDim.x + threadIdx.x; matrix_col_pos = blockIdx.y*blockDim.y + threadIdx.y; } static void computeReductionSize(int N, int &num_threads, int &thread_size, int &num_blocks) { int N2 = AprilUtils::ceilingPowerOfTwo(N); num_threads = AprilUtils::max(1, AprilUtils::min(N2/MIN_CUDA_REDUCE_THREAD_SIZE, AprilUtils::min(MAX_CUDA_REDUCE_NUM_THREADS, static_cast(GPUHelper::getMaxThreadsPerBlock())))); thread_size = AprilUtils::max(1, AprilUtils::min(MAX_CUDA_REDUCE_THREAD_SIZE, N/num_threads + ((N%num_threads)?1:0))); int num_threads_by_thread_size = num_threads*thread_size; num_blocks = AprilUtils::max(1, N/num_threads_by_thread_size + ((N%num_threads_by_thread_size)?1:0)); april_assert(num_threads * thread_size * num_blocks >= N); } static void computeSecondReductionSize(int N, int &num_threads) { int N2 = AprilUtils::ceilingPowerOfTwo(N); num_threads = AprilUtils::max(1, AprilUtils::min(N2/MIN_CUDA_REDUCE_THREAD_SIZE, AprilUtils::min(MAX_CUDA_REDUCE_NUM_THREADS, static_cast(GPUHelper::getMaxThreadsPerBlock())))); } static void computeBlockAndGridSizesFor2DMatrix(unsigned int N, unsigned int M, dim3 &block, dim3 &grid) { const unsigned int MAX_THREADS = GPUHelper::getMaxThreadsPerBlock(); // Number of threads on each block dimension block.x = AprilUtils::min(MAX_THREADS, N); block.y = AprilUtils::min(MAX_THREADS/block.x, M); block.z = 1; grid.x = (N/block.x + (N % block.x ? 1 : 0)); grid.y = (M/block.y + (M % block.y ? 1 : 0)); grid.z = 1; // TODO: FIXME: Check that the grid size does not exceed the limits of the GPU } static void computeBlockAndGridSizesForArray(int N, int &num_threads, int &num_blocks) { int thread_size; computeReductionSize(N, num_threads, thread_size, num_blocks); } static cublasOperation_t getCublasOperation(CBLAS_TRANSPOSE operation) { if (operation == CblasNoTrans) { return CUBLAS_OP_N; } else if (operation == CblasTrans) { return CUBLAS_OP_T; } else { // operation == CblasConjTrans return CUBLAS_OP_C; } } static cusparseOperation_t getCusparseOperation(CBLAS_TRANSPOSE operation) { if (operation == CblasNoTrans) { return CUSPARSE_OPERATION_NON_TRANSPOSE; } else if (operation == CblasTrans) { return CUSPARSE_OPERATION_TRANSPOSE; } else { // operation == CblasConjTrans return CUSPARSE_OPERATION_CONJUGATE_TRANSPOSE; } } } // namespace CUDA } // namespace AprilMath #else #define SPECIALIZE_CUDA_SHARED_MEMORY(FULLTYPE,TYPE) #endif SPECIALIZE_CUDA_SHARED_MEMORY(int32_t,int32_t); SPECIALIZE_CUDA_SHARED_MEMORY(float,float); SPECIALIZE_CUDA_SHARED_MEMORY(double,double); SPECIALIZE_CUDA_SHARED_MEMORY(AprilMath::ComplexF,ComplexF); #endif // CUDA_UTILS_H april-ann-0.4.1/packages/basics/mathcore/c_src/cusparse_error.cc000066400000000000000000000036461263004425400246700ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "cusparse_error.h" #include "error_print.h" #ifdef USE_CUDA void checkCusparseError(cusparseStatus_t status) { if (status == CUSPARSE_STATUS_SUCCESS) { return; } else if (status == CUSPARSE_STATUS_NOT_INITIALIZED) { ERROR_EXIT(152, "Cusparse is not initialized!\n"); } else if (status == CUSPARSE_STATUS_ALLOC_FAILED) { ERROR_EXIT(153, "Cusparse resource allocation failed!\n"); } else if (status == CUSPARSE_STATUS_INVALID_VALUE) { ERROR_EXIT(154, "Cusparse detected an unsupported parameter.\n"); } else if (status == CUSPARSE_STATUS_ARCH_MISMATCH) { ERROR_EXIT(155, "Cusparse and architecture not compatible.\n"); } else if (status == CUSPARSE_STATUS_MAPPING_ERROR) { ERROR_EXIT(156, "Cusparse accessed to a wrong GPU memory space!\n"); } else if (status == CUSPARSE_STATUS_EXECUTION_FAILED) { ERROR_EXIT(157, "Cusparse failed to execute the operation\n"); } else if (status == CUSPARSE_STATUS_INTERNAL_ERROR) { ERROR_EXIT(158, "Cusparse failed to execute an internal operation!\n"); } else { ERROR_EXIT(128, "Unknown Cusparse error\n"); } } #endif april-ann-0.4.1/packages/basics/mathcore/c_src/cusparse_error.h000066400000000000000000000017551263004425400245310ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef _CUSPARSE_ERROR_H_ #define _CUSPARSE_ERROR_H_ #ifdef USE_CUDA #include void checkCusparseError(cusparseStatus_t status); #endif #endif // _CUBLAS_ERROR_H_ april-ann-0.4.1/packages/basics/mathcore/c_src/dot.cu000066400000000000000000000071131263004425400224330ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "cblas_headers.h" #include "cuda_utils.h" #include "dot.h" #include "unused_variable.h" namespace AprilMath { #ifdef USE_CUDA namespace CUDA { /*************************************** ************** CUDA SECTION *********** ***************************************/ template<> cublasStatus_t wrapperCublasDot(cublasHandle_t &handle, unsigned int size, const float *x_mem, unsigned int x_inc, const float *y_mem, unsigned int y_inc, float *ret) { return cublasSdot(handle, size, x_mem, x_inc, y_mem, y_inc, ret); } template<> cublasStatus_t wrapperCublasDot(cublasHandle_t &handle, unsigned int size, const double *x_mem, unsigned int x_inc, const double *y_mem, unsigned int y_inc, double *ret) { return cublasDdot(handle, size, x_mem, x_inc, y_mem, y_inc, ret); } } // namespace CUDA #endif /*************************************** ************* CBLAS SECTION *********** ***************************************/ template<> float wrapperCblasDot(unsigned int size, const float *x_mem, unsigned int x_inc, const float *y_mem, unsigned int y_inc) { return cblas_sdot(size, x_mem, x_inc, y_mem, y_inc); } template<> double wrapperCblasDot(unsigned int size, const double *x_mem, unsigned int x_inc, const double *y_mem, unsigned int y_inc) { return cblas_ddot(size, x_mem, x_inc, y_mem, y_inc); } template<> ComplexF wrapperCblasDot(unsigned int size, const ComplexF *x_mem, unsigned int x_inc, const ComplexF *y_mem, unsigned int y_inc) { ComplexF ret; cblas_zdotu_sub(size, x_mem, x_inc, y_mem, y_inc, &ret); return ret; } } // namespace AprilMath april-ann-0.4.1/packages/basics/mathcore/c_src/dot.h000066400000000000000000000214411263004425400222530ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef DOT_H #define DOT_H #include "cblas_headers.h" #include "cuda_utils.h" #include "unused_variable.h" namespace AprilMath { #ifdef USE_CUDA namespace CUDA { /*************************************** ************** CUDA SECTION *********** ***************************************/ template cublasStatus_t wrapperCublasDot(cublasHandle_t &handle, unsigned int size, const T *x_mem, unsigned int x_inc, const T *y_mem, unsigned int y_inc, T *ret) { UNUSED_VARIABLE(handle); UNUSED_VARIABLE(size); UNUSED_VARIABLE(x_mem); UNUSED_VARIABLE(x_inc); UNUSED_VARIABLE(y_mem); UNUSED_VARIABLE(y_inc); UNUSED_VARIABLE(ret); ERROR_EXIT(128, "NOT IMPLEMENTED\n"); return CUBLAS_STATUS_INTERNAL_ERROR; } template<> cublasStatus_t wrapperCublasDot(cublasHandle_t &handle, unsigned int size, const float *x_mem, unsigned int x_inc, const float *y_mem, unsigned int y_inc, float *ret); template<> cublasStatus_t wrapperCublasDot(cublasHandle_t &handle, unsigned int size, const double *x_mem, unsigned int x_inc, const double *y_mem, unsigned int y_inc, double *ret); } // namespace CUDA #endif /*************************************** ************* CBLAS SECTION *********** ***************************************/ template T wrapperCblasDot(unsigned int size, const T *x_mem, unsigned int x_inc, const T *y_mem, unsigned int y_inc) { UNUSED_VARIABLE(size); UNUSED_VARIABLE(x_mem); UNUSED_VARIABLE(x_inc); UNUSED_VARIABLE(y_mem); UNUSED_VARIABLE(y_inc); ERROR_EXIT(128, "NOT IMPLEMENTED\n"); return T(0.0f); } template<> float wrapperCblasDot(unsigned int size, const float *x_mem, unsigned int x_inc, const float *y_mem, unsigned int y_inc); template<> double wrapperCblasDot(unsigned int size, const double *x_mem, unsigned int x_inc, const double *y_mem, unsigned int y_inc); template<> ComplexF wrapperCblasDot(unsigned int size, const ComplexF *x_mem, unsigned int x_inc, const ComplexF *y_mem, unsigned int y_inc); /*************************************** *********** TEMPLATE SECTION ********** ***************************************/ /** * @brief Template wrapper for dot product operation using CBLAS interface. * * @tparam T - The data type. In APRIl-ANN it could be float, double, * ComplexF. * * @tparam OP - Functor type. * * @param size - The number of elements in both vectors. * @param x - The GPUMirroredMemoryBlock pointer with x vector. * @param x_inc - The stride between consecutive elements in x vector. * @param x_shift - The position of the first valid element in x pointer. * @param[in,out] y - The GPUMirroredMemoryBlock pointer with y vector. * @param y_inc - The stride between consecutive elements in y vector. * @param y_shift - The position of the first valid element in y pointer. * @param use_gpu - Indicates if use GPU or not for the computation. * @param zero - Zero value (unused, needed for API compliant). * @param functor - A functor reduction to write the result into dest pointer. * @param dest - Destination of the computation. * @param dest_raw_pos - Position in dest where to store the result. */ template void doDot(unsigned int size, const GPUMirroredMemoryBlock *x, unsigned int x_inc, unsigned int x_shift, const GPUMirroredMemoryBlock *y, unsigned int y_inc, unsigned int y_shift, bool use_gpu, T zero, OP functor, GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos, bool set_dest_to_zero=true) { UNUSED_VARIABLE(zero); const T *x_mem; const T *y_mem; #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { cublasStatus_t status; cublasHandle_t handle = CUDA::GPUHelper::getHandler(); x_mem = x->getGPUForRead() + x_shift; y_mem = y->getGPUForRead() + y_shift; status = cublasSetStream(handle, CUDA::GPUHelper::getCurrentStream()); checkCublasError(status); if (set_dest_to_zero) { status = CUDA::wrapperCublasDot(handle, size, x_mem, x_inc, y_mem, y_inc, dest->getPPALForWrite() + dest_raw_pos); } else { GPUMirroredMemoryBlock result(1); status = CUDA::wrapperCublasDot(handle, size, x_mem, x_inc, y_mem, y_inc, result.getPPALForWrite()); T *dest_ptr = dest->getPPALForReadAndWrite() + dest_raw_pos; functor(*dest_ptr, *(result.getPPALForRead())); } checkCublasError(status); } else { #endif x_mem = x->getPPALForRead() + x_shift; y_mem = y->getPPALForRead() + y_shift; if (set_dest_to_zero) { T *dest_ptr = dest->getPPALForWrite() + dest_raw_pos; *dest_ptr = wrapperCblasDot(size, x_mem, x_inc, y_mem, y_inc); } else { T *dest_ptr = dest->getPPALForReadAndWrite() + dest_raw_pos; functor(*dest_ptr, wrapperCblasDot(size, x_mem, x_inc, y_mem, y_inc)); } #ifdef USE_CUDA } #endif } /** * @brief Template wrapper for sparse dot product operation using CBLAS * interface. * * It computes dot(x,y) where x is a sparse vector and y is a dense vector. * * @tparam T - The data type. In APRIl-ANN it could be float, double, * ComplexF. * * @param NNZ - The number of non-zero elements in x vector. * @param x_values - The GPUMirroredMemoryBlock pointer with x values. * @param x_indices - The Int32GPUMirroredMemoryBlock pointer with x indices. * @param[in,out] y - The GPUMirroredMemoryBlock pointer with y vector. * @param y_inc - The stride between consecutive elements in y vector. * @param y_shift - The position of the first valid element in y pointer. * @param use_gpu - Indicates if use GPU or not for the computation. */ template T doSparseDot(int NNZ, const GPUMirroredMemoryBlock *x_values, const Int32GPUMirroredMemoryBlock *x_indices, const GPUMirroredMemoryBlock *y, int y_shift, int y_inc, bool use_gpu) { const T *x_values_mem; const int *x_indices_mem; const T *y_mem; T ret; #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { ERROR_PRINT("CUDA sparse DOT not implemented\n"); } #endif x_values_mem = x_values->getPPALForRead(); x_indices_mem = x_indices->getPPALForRead(); y_mem = y->getPPALForRead() + y_shift; ret = cblas_sparse_dot(NNZ, x_values_mem, x_indices_mem, y_mem, y_inc); return ret; } } // namespace AprilMath #endif // DOT_H april-ann-0.4.1/packages/basics/mathcore/c_src/gemm.cu000066400000000000000000000615121263004425400225750ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "april_assert.h" #include "mathcore.h" #include "smart_ptr.h" #include "transpose.h" #include "unused_variable.h" namespace AprilMath { #ifdef USE_CUDA namespace CUDA { /*************************************** ************** CUDA SECTION *********** ***************************************/ cublasStatus_t wrapperCublasGemm(cublasHandle_t &handle, cublasOperation_t &cublas_a_transpose, cublasOperation_t &cublas_b_transpose, int m, int n, int k, float *alpha, const float *a_mem, unsigned int a_inc, const float *b_mem, unsigned int b_inc, float *beta, float *c_mem, unsigned int c_inc) { return cublasSgemm(handle, cublas_a_transpose, cublas_b_transpose, m, n, k, alpha, a_mem, a_inc, b_mem, b_inc, beta, c_mem, c_inc); } cublasStatus_t wrapperCublasGemm(cublasHandle_t &handle, cublasOperation_t &cublas_a_transpose, cublasOperation_t &cublas_b_transpose, int m, int n, int k, double *alpha, const double *a_mem, unsigned int a_inc, const double *b_mem, unsigned int b_inc, double *beta, double *c_mem, unsigned int c_inc) { return cublasDgemm(handle, cublas_a_transpose, cublas_b_transpose, m, n, k, alpha, a_mem, a_inc, b_mem, b_inc, beta, c_mem, c_inc); } cublasStatus_t wrapperCublasGemm(cublasHandle_t &handle, cublasOperation_t &cublas_a_transpose, cublasOperation_t &cublas_b_transpose, int m, int n, int k, ComplexF *alpha, const ComplexF *a_mem, unsigned int a_inc, const ComplexF *b_mem, unsigned int b_inc, ComplexF *beta, ComplexF *c_mem, unsigned int c_inc) { return cublasCgemm(handle, cublas_a_transpose, cublas_b_transpose, m, n, k, reinterpret_cast(alpha), reinterpret_cast(a_mem), a_inc, reinterpret_cast(b_mem), b_inc, reinterpret_cast(beta), reinterpret_cast(c_mem), c_inc); } cusparseStatus_t wrapperCusparseCSRMM(cusparseHandle_t &handle, cusparseOperation_t &cusparse_a_transpose, int m, int n, int k, int NNZ, float *alpha, const cusparseMatDescr_t descrA, const float *a_values_mem, const int *a_first_index_mem, const int *a_indices_mem, const float *b_mem, unsigned int b_inc, float *beta, float *c_mem, unsigned int c_inc) { return cusparseScsrmm(handle, cusparse_a_transpose, m, n, k, NNZ, alpha, descrA, a_values_mem, a_first_index_mem, a_indices_mem, b_mem, b_inc, beta, c_mem, c_inc); } cusparseStatus_t wrapperCusparseCSRMM(cusparseHandle_t &handle, cusparseOperation_t &cusparse_a_transpose, int m, int n, int k, int NNZ, double *alpha, const cusparseMatDescr_t descrA, const double *a_values_mem, const int *a_first_index_mem, const int *a_indices_mem, const double *b_mem, unsigned int b_inc, double *beta, double *c_mem, unsigned int c_inc) { return cusparseDcsrmm(handle, cusparse_a_transpose, m, n, k, NNZ, alpha, descrA, a_values_mem, a_first_index_mem, a_indices_mem, b_mem, b_inc, beta, c_mem, c_inc); } cusparseStatus_t wrapperCusparseCSRMM(cusparseHandle_t &handle, cusparseOperation_t &cusparse_a_transpose, int m, int n, int k, int NNZ, ComplexF *alpha, const cusparseMatDescr_t descrA, const ComplexF *a_values_mem, const int *a_first_index_mem, const int *a_indices_mem, const ComplexF *b_mem, unsigned int b_inc, ComplexF *beta, ComplexF *c_mem, unsigned int c_inc) { return cusparseCcsrmm(handle, cusparse_a_transpose, m, n, k, NNZ, reinterpret_cast(alpha), descrA, reinterpret_cast(a_values_mem), a_first_index_mem, a_indices_mem, reinterpret_cast(b_mem), b_inc, reinterpret_cast(beta), reinterpret_cast(c_mem), c_inc); } } // namespace CUDA #endif /*************************************** ************* CBLAS SECTION *********** ***************************************/ void wrapperCblasGemm(CBLAS_ORDER &major_order, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, int m, int n, int k, float alpha, const float *a_mem, unsigned int a_inc, const float *b_mem, unsigned int b_inc, float beta, float *c_mem, unsigned int c_inc) { cblas_sgemm(major_order, a_transpose, b_transpose, m, n, k, alpha, a_mem, a_inc, b_mem, b_inc, beta, c_mem, c_inc); } void wrapperCblasGemm(CBLAS_ORDER &major_order, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, int m, int n, int k, double alpha, const double *a_mem, unsigned int a_inc, const double *b_mem, unsigned int b_inc, double beta, double *c_mem, unsigned int c_inc) { cblas_dgemm(major_order, a_transpose, b_transpose, m, n, k, alpha, a_mem, a_inc, b_mem, b_inc, beta, c_mem, c_inc); } void wrapperCblasGemm(CBLAS_ORDER &major_order, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, int m, int n, int k, ComplexF alpha, const ComplexF *a_mem, unsigned int a_inc, const ComplexF *b_mem, unsigned int b_inc, ComplexF beta, ComplexF *c_mem, unsigned int c_inc) { cblas_cgemm(major_order, a_transpose, b_transpose, m, n, k, &alpha, a_mem, a_inc, b_mem, b_inc, &beta, c_mem, c_inc); } template void wrapperCblasSparseMM(CBLAS_ORDER major_order, SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, CBLAS_TRANSPOSE c_transpose, int m, int n, int k, T alpha, const T *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const T *b_mem, unsigned int b_inc, T beta, T *c_mem, unsigned int c_inc) { cblas_sparse_mm(major_order, sparse_format, a_transpose, b_transpose, c_transpose, m, n, k, alpha, a_values_mem, a_indices_mem, a_first_index_mem, b_mem, static_cast(b_inc), beta, c_mem, static_cast(c_inc)); } /*************************************** *********** TEMPLATE SECTION ********** ***************************************/ template void doGemm(CBLAS_ORDER major_order, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, int m, int n, int k, T alpha, const GPUMirroredMemoryBlock* a, unsigned int a_inc, const GPUMirroredMemoryBlock* b, unsigned int b_inc, T beta, GPUMirroredMemoryBlock* c, unsigned int c_inc, unsigned int a_shift, unsigned int b_shift, unsigned int c_shift, bool use_gpu) { const T *a_mem, *b_mem; T *c_mem; #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { if (major_order != CblasColMajor) { AprilUtils::swap(m,n); AprilUtils::swap(a,b); AprilUtils::swap(a_inc,b_inc); AprilUtils::swap(a_transpose, b_transpose); } cublasStatus_t status; cublasHandle_t handle = CUDA::GPUHelper::getHandler(); //printf("Doing a sgemm with comp=1 & cuda=1\n"); a_mem = a->getGPUForRead() + a_shift; b_mem = b->getGPUForRead() + b_shift; c_mem = c->getGPUForReadAndWrite() + c_shift; cublasOperation_t cublas_a_transpose = CUDA::getCublasOperation(a_transpose); cublasOperation_t cublas_b_transpose = CUDA::getCublasOperation(b_transpose); status = cublasSetStream(handle, CUDA::GPUHelper::getCurrentStream()); checkCublasError(status); status = CUDA::wrapperCublasGemm(handle, cublas_a_transpose, cublas_b_transpose, m, n, k, &alpha, a_mem, a_inc, b_mem, b_inc, &beta, c_mem, c_inc); checkCublasError(status); } else { //printf("Doing a sgemm with comp=1 & cuda=0\n"); #endif //printf("Doing a sgemm with comp=0 & cuda=0\n"); a_mem = a->getPPALForRead() + a_shift; b_mem = b->getPPALForRead() + b_shift; c_mem = c->getPPALForReadAndWrite() + c_shift; // matrix matrix product: C = \alpha op(A) op(B) + \beta C wrapperCblasGemm(major_order, // Row or Col Major a_transpose, // Transpose or not A b_transpose, // Transpose or not B m, // num rows of A (before transpose) n, // num rows at B (before transpose) k, // Common dimension between A and B alpha, // Alpha value a_mem, // A matrix a_inc, // A matrix stride b_mem, // B matrix b_inc, // B matrix stride beta, // Beta value c_mem, // C matrix c_inc); // C matrix stride #ifdef USE_CUDA } #endif } template void doSparseMM(CBLAS_ORDER major_order, SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, int m, int n, int k, T alpha, const GPUMirroredMemoryBlock* a_values, const Int32GPUMirroredMemoryBlock* a_indices, const Int32GPUMirroredMemoryBlock* a_first_index, const GPUMirroredMemoryBlock* b, int b_inc, T beta, GPUMirroredMemoryBlock* c, int c_inc, int b_shift, int c_shift, bool use_gpu) { const T *a_values_mem, *b_mem; const int *a_indices_mem, *a_first_index_mem; T *c_mem; const int NNZ = static_cast(a_values->getSize()); UNUSED_VARIABLE(NNZ); #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { cusparseStatus_t status; cusparseHandle_t handle = CUDA::GPUHelper::getSparseHandler(); if (major_order != CblasColMajor) ERROR_EXIT(128, "Column major matrices are expected\n"); if (b_transpose == CblasTrans) ERROR_EXIT(128, "Impossible to transpose B matrix " "when using CUDA\n"); if (sparse_format != CSR_FORMAT) a_transpose = NEGATE_CBLAS_TRANSPOSE(a_transpose); //printf("Doing a sgemm with comp=1 & cuda=1\n"); a_values_mem = a_values->getGPUForRead(); a_indices_mem = a_indices->getGPUForRead(); a_first_index_mem = a_first_index->getGPUForRead(); b_mem = b->getGPUForRead() + b_shift; c_mem = c->getGPUForReadAndWrite() + c_shift; cusparseOperation_t cusparse_a_transpose = CUDA::getCusparseOperation(a_transpose); status = cusparseSetStream(handle, CUDA::GPUHelper::getCurrentStream()); checkCusparseError(status); cusparseMatDescr_t descrA; status = cusparseCreateMatDescr(&descrA); checkCusparseError(status); /* by default, it is initialized like this: descrA->MatrixType = CUSPARSE_MATRIX_TYPE_GENERAL; descrA->FillMode = 0; descrA->DiagType = 0; descrA->IndexBase = CUSPARSE_INDEX_BASE_ZERO; */ // status = CUDA::wrapperCusparseCSRMM(handle, cusparse_a_transpose, m, n, k, NNZ, &alpha, descrA, a_values_mem, a_first_index_mem, a_indices_mem, b_mem, b_inc, &beta, c_mem, c_inc); checkCusparseError(status); status = cusparseDestroyMatDescr(descrA); checkCusparseError(status); } else { //printf("Doing a sgemm with comp=1 & cuda=0\n"); #endif //printf("Doing a sgemm with comp=0 & cuda=0\n"); a_values_mem = a_values->getPPALForRead(); a_indices_mem = a_indices->getPPALForRead(); a_first_index_mem = a_first_index->getPPALForRead(); b_mem = b->getPPALForRead() + b_shift; c_mem = c->getPPALForReadAndWrite() + c_shift; // matrix matrix product: C = \alpha op(A) op(B) + \beta C wrapperCblasSparseMM(major_order, sparse_format, a_transpose, b_transpose, CblasNoTrans, m, // num rows of A (before transpose) n, // num rows at B (before transpose) k, // Common dimension between A and B alpha, // Alpha value a_values_mem, a_indices_mem, a_first_index_mem, b_mem, // B matrix b_inc, // B matrix stride beta, // Beta value c_mem, // C matrix c_inc); // C matrix stride #ifdef USE_CUDA } #endif } template void doGemm(CBLAS_ORDER major_order, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, int m, int n, int k, float alpha, const GPUMirroredMemoryBlock* a, unsigned int a_inc, const GPUMirroredMemoryBlock* b, unsigned int b_inc, float beta, GPUMirroredMemoryBlock* c, unsigned int c_inc, unsigned int a_shift, unsigned int b_shift, unsigned int c_shift, bool use_gpu); template void doGemm(CBLAS_ORDER major_order, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, int m, int n, int k, double alpha, const GPUMirroredMemoryBlock* a, unsigned int a_inc, const GPUMirroredMemoryBlock* b, unsigned int b_inc, double beta, GPUMirroredMemoryBlock* c, unsigned int c_inc, unsigned int a_shift, unsigned int b_shift, unsigned int c_shift, bool use_gpu); template void doGemm(CBLAS_ORDER major_order, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, int m, int n, int k, ComplexF alpha, const GPUMirroredMemoryBlock* a, unsigned int a_inc, const GPUMirroredMemoryBlock* b, unsigned int b_inc, ComplexF beta, GPUMirroredMemoryBlock* c, unsigned int c_inc, unsigned int a_shift, unsigned int b_shift, unsigned int c_shift, bool use_gpu); template void doSparseMM(CBLAS_ORDER major_order, SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, int m, int n, int k, float alpha, const GPUMirroredMemoryBlock* a_values, const Int32GPUMirroredMemoryBlock* a_indices, const Int32GPUMirroredMemoryBlock* a_first_index, const GPUMirroredMemoryBlock* b, int b_inc, float beta, GPUMirroredMemoryBlock* c, int c_inc, int b_shift, int c_shift, bool use_gpu); template void doSparseMM(CBLAS_ORDER major_order, SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, int m, int n, int k, double alpha, const GPUMirroredMemoryBlock* a_values, const Int32GPUMirroredMemoryBlock* a_indices, const Int32GPUMirroredMemoryBlock* a_first_index, const GPUMirroredMemoryBlock* b, int b_inc, double beta, GPUMirroredMemoryBlock* c, int c_inc, int b_shift, int c_shift, bool use_gpu); template void doSparseMM(CBLAS_ORDER major_order, SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, CBLAS_TRANSPOSE b_transpose, int m, int n, int k, ComplexF alpha, const GPUMirroredMemoryBlock* a_values, const Int32GPUMirroredMemoryBlock* a_indices, const Int32GPUMirroredMemoryBlock* a_first_index, const GPUMirroredMemoryBlock* b, int b_inc, ComplexF beta, GPUMirroredMemoryBlock* c, int c_inc, int b_shift, int c_shift, bool use_gpu); } // namespace AprilMath april-ann-0.4.1/packages/basics/mathcore/c_src/gemv.cu000066400000000000000000000474201263004425400226100ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "mathcore.h" #include "unused_variable.h" namespace AprilMath { #ifdef USE_CUDA namespace CUDA { /*************************************** ************** CUDA SECTION *********** ***************************************/ cublasStatus_t wrapperCublasGemv(cublasHandle_t &handle, cublasOperation_t &cublas_a_transpose, int m, int n, const float *alpha, const float *a_mem, unsigned int a_inc, const float *x_mem, unsigned int x_inc, const float *beta, float *y_mem, unsigned int y_inc) { return cublasSgemv(handle, cublas_a_transpose, m, n, alpha, a_mem, a_inc, x_mem, x_inc, beta, y_mem, y_inc); } cublasStatus_t wrapperCublasGemv(cublasHandle_t &handle, cublasOperation_t &cublas_a_transpose, int m, int n, const double *alpha, const double *a_mem, unsigned int a_inc, const double *x_mem, unsigned int x_inc, const double *beta, double *y_mem, unsigned int y_inc) { return cublasDgemv(handle, cublas_a_transpose, m, n, alpha, a_mem, a_inc, x_mem, x_inc, beta, y_mem, y_inc); } cublasStatus_t wrapperCublasGemv(cublasHandle_t &handle, cublasOperation_t &cublas_a_transpose, int m, int n, const ComplexF *alpha, const ComplexF *a_mem, unsigned int a_inc, const ComplexF *x_mem, unsigned int x_inc, const ComplexF *beta, ComplexF *y_mem, unsigned int y_inc) { return cublasCgemv(handle, cublas_a_transpose, m, n, reinterpret_cast(alpha), reinterpret_cast(a_mem), a_inc, reinterpret_cast(x_mem), x_inc, reinterpret_cast(beta), reinterpret_cast(y_mem), y_inc); } cusparseStatus_t wrapperCusparseCSRGemv(cusparseHandle_t &handle, cusparseOperation_t &cusparse_a_transpose, int m, int n, int NNZ, const float *alpha, cusparseMatDescr_t descrA, const float *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const float *x_mem, unsigned int x_inc, const float *beta, float *y_mem, unsigned int y_inc) { if (x_inc != 1 || y_inc != 1) ERROR_EXIT(128, "Not implemented for non contiguous vectors\n"); return cusparseScsrmv(handle, cusparse_a_transpose, m, n, NNZ, alpha, descrA, a_values_mem, a_first_index_mem, a_indices_mem, x_mem, beta, y_mem); } cusparseStatus_t wrapperCusparseCSRGemv(cusparseHandle_t &handle, cusparseOperation_t &cusparse_a_transpose, int m, int n, int NNZ, const double *alpha, cusparseMatDescr_t descrA, const double *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const double *x_mem, unsigned int x_inc, const double *beta, double *y_mem, unsigned int y_inc) { if (x_inc != 1 || y_inc != 1) ERROR_EXIT(128, "Not implemented for non contiguous vectors\n"); return cusparseDcsrmv(handle, cusparse_a_transpose, m, n, NNZ, alpha, descrA, a_values_mem, a_first_index_mem, a_indices_mem, x_mem, beta, y_mem); } cusparseStatus_t wrapperCusparseCSRGemv(cusparseHandle_t &handle, cusparseOperation_t &cusparse_a_transpose, int m, int n, int NNZ, const ComplexF *alpha, cusparseMatDescr_t descrA, const ComplexF *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const ComplexF *x_mem, unsigned int x_inc, const ComplexF *beta, ComplexF *y_mem, unsigned int y_inc) { if (x_inc != 1 || y_inc != 1) ERROR_EXIT(128, "Not implemented for non contiguous vectors\n"); return cusparseCcsrmv(handle, cusparse_a_transpose, m, n, NNZ, reinterpret_cast(alpha), descrA, reinterpret_cast(a_values_mem), a_first_index_mem, a_indices_mem, reinterpret_cast(x_mem), reinterpret_cast(beta), reinterpret_cast(y_mem)); } } // namespace CUDA #endif /*************************************** ************* CBLAS SECTION *********** ***************************************/ void wrapperCblasGemv(CBLAS_ORDER &major_order, CBLAS_TRANSPOSE a_transpose, int m, int n, float alpha, const float *a_mem, unsigned int a_inc, const float *x_mem, unsigned int x_inc, float beta, float *y_mem, unsigned int y_inc) { cblas_sgemv(major_order, a_transpose, m, n, alpha, a_mem, a_inc, x_mem, x_inc, beta, y_mem, y_inc); } void wrapperCblasGemv(CBLAS_ORDER &major_order, CBLAS_TRANSPOSE a_transpose, int m, int n, double alpha, const double *a_mem, unsigned int a_inc, const double *x_mem, unsigned int x_inc, double beta, double *y_mem, unsigned int y_inc) { cblas_dgemv(major_order, a_transpose, m, n, alpha, a_mem, a_inc, x_mem, x_inc, beta, y_mem, y_inc); } void wrapperCblasGemv(CBLAS_ORDER &major_order, CBLAS_TRANSPOSE a_transpose, int m, int n, ComplexF alpha, const ComplexF *a_mem, unsigned int a_inc, const ComplexF *x_mem, unsigned int x_inc, ComplexF beta, ComplexF *y_mem, unsigned int y_inc) { cblas_cgemv(major_order, a_transpose, m, n, &alpha, a_mem, a_inc, x_mem, x_inc, &beta, y_mem, y_inc); } template void wrapperCblasSparseGemv(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, T alpha, const T *a_values_mem, const int *a_indices_mem, const int *a_first_index_mem, const T *x_mem, unsigned int x_inc, T beta, T *y_mem, unsigned int y_inc) { cblas_sparse_mv(sparse_format, a_transpose, m, n, alpha, a_values_mem, a_indices_mem, a_first_index_mem, x_mem, static_cast(x_inc), beta, y_mem, static_cast(y_inc)); } /*************************************** *********** TEMPLATE SECTION ********** ***************************************/ template void doGemv(CBLAS_ORDER major_order, CBLAS_TRANSPOSE a_transpose, int m, int n, T alpha, const GPUMirroredMemoryBlock *a, unsigned int a_inc, const GPUMirroredMemoryBlock *x, unsigned int x_inc, T beta, GPUMirroredMemoryBlock *y, unsigned int y_inc, unsigned int a_shift, unsigned int x_shift, unsigned int y_shift, bool use_gpu) { const T *a_mem, *x_mem; T *y_mem; #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { cublasStatus_t status; cublasHandle_t handle = CUDA::GPUHelper::getHandler(); if (major_order != CblasColMajor) { a_transpose = NEGATE_CBLAS_TRANSPOSE(a_transpose); AprilUtils::swap(m, n); } cublasOperation_t cublas_a_transpose = CUDA::getCublasOperation(a_transpose); a_mem = a->getGPUForRead() + a_shift; x_mem = x->getGPUForRead() + x_shift; y_mem = y->getGPUForReadAndWrite() + y_shift; status = cublasSetStream(handle, CUDA::GPUHelper::getCurrentStream()); checkCublasError(status); status = CUDA::wrapperCublasGemv(handle, cublas_a_transpose, m, n, &alpha, a_mem, a_inc, x_mem, x_inc, &beta, y_mem, y_inc); checkCublasError(status); } else { #endif a_mem = a->getPPALForRead() + a_shift; x_mem = x->getPPALForRead() + x_shift; y_mem = y->getPPALForReadAndWrite() + y_shift; wrapperCblasGemv(major_order, a_transpose, m, n, alpha, a_mem, a_inc, x_mem, x_inc, beta, y_mem, y_inc); #ifdef USE_CUDA } #endif } template void doSparseGemv(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, T alpha, const GPUMirroredMemoryBlock *a_values, const Int32GPUMirroredMemoryBlock *a_indices, const Int32GPUMirroredMemoryBlock *a_first_index, const GPUMirroredMemoryBlock *x, unsigned int x_inc, T beta, GPUMirroredMemoryBlock *y, unsigned int y_inc, unsigned int x_shift, unsigned int y_shift, bool use_gpu) { const T *a_values_mem, *x_mem; const int *a_indices_mem, *a_first_index_mem; T *y_mem; const int NNZ = static_cast(a_values->getSize()); UNUSED_VARIABLE(NNZ); #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { cusparseStatus_t status; cusparseHandle_t handle = CUDA::GPUHelper::getSparseHandler(); if (sparse_format != CSR_FORMAT) a_transpose = NEGATE_CBLAS_TRANSPOSE(a_transpose); a_values_mem = a_values->getGPUForRead(); a_indices_mem = a_indices->getGPUForRead(); a_first_index_mem = a_first_index->getGPUForRead(); x_mem = x->getGPUForRead() + x_shift; y_mem = y->getGPUForReadAndWrite() + y_shift; cusparseOperation_t cusparse_a_transpose = CUDA::getCusparseOperation(a_transpose); status = cusparseSetStream(handle, CUDA::GPUHelper::getCurrentStream()); checkCusparseError(status); cusparseMatDescr_t descrA; status = cusparseCreateMatDescr(&descrA); checkCusparseError(status); /* by default, it is initialized like this: descrA->MatrixType = CUSPARSE_MATRIX_TYPE_GENERAL; descrA->FillMode = 0; descrA->DiagType = 0; descrA->IndexBase = CUSPARSE_INDEX_BASE_ZERO; */ status = CUDA::wrapperCusparseCSRGemv(handle, cusparse_a_transpose, m, n, NNZ, &alpha, descrA, a_values_mem, a_first_index_mem, a_indices_mem, x_mem, x_inc, &beta, y_mem, y_inc); checkCusparseError(status); status = cusparseDestroyMatDescr(descrA); checkCusparseError(status); } else { #endif a_values_mem = a_values->getPPALForRead(); a_indices_mem = a_indices->getPPALForRead(); a_first_index_mem = a_first_index->getPPALForRead(); x_mem = x->getPPALForRead() + x_shift; y_mem = y->getPPALForReadAndWrite() + y_shift; wrapperCblasSparseGemv(sparse_format, a_transpose, m, n, alpha, a_values_mem, a_indices_mem, a_first_index_mem, x_mem, x_inc, beta, y_mem, y_inc); #ifdef USE_CUDA } #endif } template void doGemv(CBLAS_ORDER major_order, CBLAS_TRANSPOSE a_transpose, int m, int n, float alpha, const GPUMirroredMemoryBlock *a, unsigned int a_inc, const GPUMirroredMemoryBlock *x, unsigned int x_inc, float beta, GPUMirroredMemoryBlock *y, unsigned int y_inc, unsigned int a_shift, unsigned int x_shift, unsigned int y_shift, bool use_gpu); template void doGemv(CBLAS_ORDER major_order, CBLAS_TRANSPOSE a_transpose, int m, int n, double alpha, const GPUMirroredMemoryBlock *a, unsigned int a_inc, const GPUMirroredMemoryBlock *x, unsigned int x_inc, double beta, GPUMirroredMemoryBlock *y, unsigned int y_inc, unsigned int a_shift, unsigned int x_shift, unsigned int y_shift, bool use_gpu); template void doGemv(CBLAS_ORDER major_order, CBLAS_TRANSPOSE a_transpose, int m, int n, ComplexF alpha, const GPUMirroredMemoryBlock *a, unsigned int a_inc, const GPUMirroredMemoryBlock *x, unsigned int x_inc, ComplexF beta, GPUMirroredMemoryBlock *y, unsigned int y_inc, unsigned int a_shift, unsigned int x_shift, unsigned int y_shift, bool use_gpu); template void doSparseGemv(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, float alpha, const GPUMirroredMemoryBlock *a_values, const Int32GPUMirroredMemoryBlock *a_indices, const Int32GPUMirroredMemoryBlock *a_first_index, const GPUMirroredMemoryBlock *x, unsigned int x_inc, float beta, GPUMirroredMemoryBlock *y, unsigned int y_inc, unsigned int x_shift, unsigned int y_shift, bool use_gpu); template void doSparseGemv(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, double alpha, const GPUMirroredMemoryBlock *a_values, const Int32GPUMirroredMemoryBlock *a_indices, const Int32GPUMirroredMemoryBlock *a_first_index, const GPUMirroredMemoryBlock *x, unsigned int x_inc, double beta, GPUMirroredMemoryBlock *y, unsigned int y_inc, unsigned int x_shift, unsigned int y_shift, bool use_gpu); template void doSparseGemv(SPARSE_FORMAT sparse_format, CBLAS_TRANSPOSE a_transpose, int m, int n, ComplexF alpha, const GPUMirroredMemoryBlock *a_values, const Int32GPUMirroredMemoryBlock *a_indices, const Int32GPUMirroredMemoryBlock *a_first_index, const GPUMirroredMemoryBlock *x, unsigned int x_inc, ComplexF beta, GPUMirroredMemoryBlock *y, unsigned int y_inc, unsigned int x_shift, unsigned int y_shift, bool use_gpu); } // namespace AprilMath april-ann-0.4.1/packages/basics/mathcore/c_src/ger.cu000066400000000000000000000212721263004425400224240ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "mathcore.h" #include "unused_variable.h" namespace AprilMath { #ifdef USE_CUDA namespace CUDA { /*************************************** ************** CUDA SECTION *********** ***************************************/ cublasStatus_t wrapperCublasGer(cublasHandle_t &handle, unsigned int m, unsigned int n, float *alpha, const float *x_mem, unsigned int x_inc, const float *y_mem, unsigned int y_inc, float *a_mem, unsigned int a_inc) { return cublasSger(handle, m, n, alpha, x_mem, x_inc, y_mem, y_inc, a_mem, a_inc); } cublasStatus_t wrapperCublasGer(cublasHandle_t &handle, unsigned int m, unsigned int n, double *alpha, const double *x_mem, unsigned int x_inc, const double *y_mem, unsigned int y_inc, double *a_mem, unsigned int a_inc) { return cublasDger(handle, m, n, alpha, x_mem, x_inc, y_mem, y_inc, a_mem, a_inc); } cublasStatus_t wrapperCublasGer(cublasHandle_t &handle, unsigned int m, unsigned int n, ComplexF *alpha, const ComplexF *x_mem, unsigned int x_inc, const ComplexF *y_mem, unsigned int y_inc, ComplexF *a_mem, unsigned int a_inc) { ERROR_EXIT(256, "Ger operation not implemented in CUDA\n"); return CUBLAS_STATUS_INTERNAL_ERROR; } } // namespace CUDA #endif /*************************************** ************* CBLAS SECTION *********** ***************************************/ void wrapperCblasGer(CBLAS_ORDER major_type, int m, int n, float alpha, const float *x_mem, unsigned int x_inc, const float *y_mem, unsigned int y_inc, float *a_mem, unsigned int a_inc) { cblas_sger(major_type, m, n, alpha, x_mem, x_inc, y_mem, y_inc, a_mem, a_inc); } void wrapperCblasGer(CBLAS_ORDER major_type, int m, int n, double alpha, const double *x_mem, unsigned int x_inc, const double *y_mem, unsigned int y_inc, double *a_mem, unsigned int a_inc) { cblas_dger(major_type, m, n, alpha, x_mem, x_inc, y_mem, y_inc, a_mem, a_inc); } void wrapperCblasGer(CBLAS_ORDER major_type, int m, int n, ComplexF alpha, const ComplexF *x_mem, unsigned int x_inc, const ComplexF *y_mem, unsigned int y_inc, ComplexF *a_mem, unsigned int a_inc) { cblas_cgeru(major_type, m, n, &alpha, x_mem, x_inc, y_mem, y_inc, a_mem, a_inc); } /*************************************** *********** TEMPLATE SECTION ********** ***************************************/ template void doGer(CBLAS_ORDER major_type, unsigned int m, unsigned int n, T alpha, const GPUMirroredMemoryBlock *x, unsigned int x_shift, unsigned int x_inc, const GPUMirroredMemoryBlock *y, unsigned int y_shift, unsigned int y_inc, GPUMirroredMemoryBlock *a, unsigned int a_shift, unsigned int a_inc, bool use_gpu) { const T *x_mem; const T *y_mem; T *a_mem; #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { cublasStatus_t status; cublasHandle_t handle = CUDA::GPUHelper::getHandler(); if (major_type != CblasColMajor) { AprilUtils::swap(m, n); AprilUtils::swap(x, y); AprilUtils::swap(x_inc, y_inc); } x_mem = x->getGPUForRead() + x_shift; y_mem = y->getGPUForRead() + y_shift; a_mem = a->getGPUForReadAndWrite() + a_shift; status = cublasSetStream(handle, CUDA::GPUHelper::getCurrentStream()); checkCublasError(status); status = CUDA::wrapperCublasGer(handle, m, n, &alpha, x_mem, x_inc, y_mem, y_inc, a_mem, a_inc); checkCublasError(status); } else { #endif x_mem = x->getPPALForRead() + x_shift; y_mem = y->getPPALForRead() + y_shift; a_mem = a->getPPALForReadAndWrite() + a_shift; wrapperCblasGer(major_type, m, n, alpha, x_mem, x_inc, y_mem, y_inc, a_mem, a_inc); #ifdef USE_CUDA } #endif } template void doGer(CBLAS_ORDER major_type, unsigned int m, unsigned int n, float alpha, const GPUMirroredMemoryBlock *x, unsigned int x_shift, unsigned int x_inc, const GPUMirroredMemoryBlock *y, unsigned int y_shift, unsigned int y_inc, GPUMirroredMemoryBlock *a, unsigned int a_shift, unsigned int a_inc, bool use_gpu); template void doGer(CBLAS_ORDER major_type, unsigned int m, unsigned int n, double alpha, const GPUMirroredMemoryBlock *x, unsigned int x_shift, unsigned int x_inc, const GPUMirroredMemoryBlock *y, unsigned int y_shift, unsigned int y_inc, GPUMirroredMemoryBlock *a, unsigned int a_shift, unsigned int a_inc, bool use_gpu); template void doGer(CBLAS_ORDER major_type, unsigned int m, unsigned int n, ComplexF alpha, const GPUMirroredMemoryBlock *x, unsigned int x_shift, unsigned int x_inc, const GPUMirroredMemoryBlock *y, unsigned int y_shift, unsigned int y_inc, GPUMirroredMemoryBlock *a, unsigned int a_shift, unsigned int a_inc, bool use_gpu); } // namespace AprilMath april-ann-0.4.1/packages/basics/mathcore/c_src/gpu_helper.cu000066400000000000000000000025051263004425400237770ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "gpu_helper.h" #ifdef USE_CUDA namespace AprilMath { namespace CUDA { bool GPUHelper::initialized = false; cublasHandle_t GPUHelper::handler; cusparseHandle_t GPUHelper::sparse_handler; cudaDeviceProp GPUHelper::properties; CUdevice GPUHelper::device; CUcontext GPUHelper::context; AprilUtils::vector GPUHelper::streams; unsigned int GPUHelper::current_stream = 0; } // namespace CUDA } // namespace AprilMath #endif april-ann-0.4.1/packages/basics/mathcore/c_src/gpu_helper.h000066400000000000000000000115141263004425400236170ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef _CUBLAS_HANDLER_H_ #define _CUBLAS_HANDLER_H_ #ifdef USE_CUDA #include #include #include #include #include "april_assert.h" #include "cublas_error.h" #include "cusparse_error.h" #include "vector.h" namespace AprilMath { namespace CUDA { /** * @brief A class to deal with CUDA initialization, streams and handlers. */ class GPUHelper { static cublasHandle_t handler; static cusparseHandle_t sparse_handler; static bool initialized; static cudaDeviceProp properties; static CUdevice device; static CUcontext context; static AprilUtils::vector streams; static unsigned int current_stream; public: /// If not initialized before, this method initializes CUDA. static void initHelper() { if (!initialized) { cublasStatus_t state; state = cublasCreate(&handler); if (state != CUBLAS_STATUS_SUCCESS) ERROR_EXIT(150, "Cublas couldn't be initialized\n"); cusparseStatus_t sparse_state = cusparseCreate(&sparse_handler); if (sparse_state != CUSPARSE_STATUS_SUCCESS) ERROR_EXIT(150, "Cusparse couldn't be initialized\n"); // initialized = true; if (cuDeviceGet (&device, 0) != CUDA_SUCCESS) ERROR_EXIT(152, "Failed to get device\n"); if (cudaGetDeviceProperties(&properties, 0) != cudaSuccess) ERROR_EXIT(153, "Failed to get properties\n"); streams.push_back(0); current_stream = 0; #ifndef NDEBUG fprintf(stderr, "# Initialized CUDA, CUBLAS and CUSPARSE for GPU capabilitites " "of version %d.%d\n", properties.major, properties.minor); #endif } } /// Destroy a previously initialized CUDA environment. static void destroyHandler() { destroyStreams(); if (initialized != true) ERROR_EXIT(151, "Destroying CUBLAS handler, that it's not initialized\n"); // Need to free all the allocated memory in GPU cublasDestroy(handler); cusparseDestroy(sparse_handler); initialized = false; } /// Returns the cublas handler. static cublasHandle_t &getHandler() { initHelper(); return handler; } /// Returns the cusparse handler. static cusparseHandle_t &getSparseHandler() { initHelper(); return sparse_handler; } /// Returns the CUDA device handler. static CUdevice &getCUdevice() { initHelper(); return device; } /// Returns the maximum number of threads per block in the active device. static unsigned int getMaxThreadsPerBlock() { initHelper(); return properties.maxThreadsPerBlock; } /// Push @c n streams into the collection GPUHelper::streams . static void createNStreams(unsigned int n) { initHelper(); cuStreamSynchronize(0); for (unsigned int i=0; i1; --i) { cuStreamSynchronize(streams[i-1]); cuStreamDestroy(streams[i-1]); streams.pop_back(); } current_stream = 0; april_assert(streams.size() == 1); } /// Changes current stream number. static void setCurrentStream(unsigned int i) { april_assert(i < streams.size()); current_stream = i; } /// Returns current stream handler. static CUstream getCurrentStream() { initHelper(); return streams[current_stream]; } }; } // namespace CUDA } // namespace AprilMath #endif #endif // _CUBLAS_HANDLER_H_ april-ann-0.4.1/packages/basics/mathcore/c_src/gpu_mirrored_memory_block.cu000066400000000000000000000050051263004425400271030ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "gpu_mirrored_memory_block.h" namespace AprilMath { bool GPUMirroredMemoryBlockBase::use_mmap_allocation = false; bool GPUMirroredMemoryBlockBase::USE_CUDA_DEFAULT = false; #ifndef NO_POOL size_t GPUMirroredMemoryBlockBase::MAX_POOL_LIST_SIZE = 200*1024*1024; // 200 Megabytes size_t GPUMirroredMemoryBlockBase::MIN_MEMORY_TH_IN_POOL = 20; // 20 bytes GPUMirroredMemoryBlockBase::PoolFreeBeforeExit GPUMirroredMemoryBlockBase::pool_free_before_exit; size_t GPUMirroredMemoryBlockBase::pool_size = 0; GPUMirroredMemoryBlockBase::PoolType *GPUMirroredMemoryBlockBase::pool_lists = new GPUMirroredMemoryBlockBase::PoolType(1024); #endif template<> const char *GPUMirroredMemoryBlock::luaCtorName() const { return "mathcore.block.char.read"; } template<> const char *GPUMirroredMemoryBlock::luaCtorName() const { return "mathcore.block.float.read"; } template<> const char *GPUMirroredMemoryBlock::luaCtorName() const { return "mathcore.block.double.read"; } template<> const char *GPUMirroredMemoryBlock::luaCtorName() const { return "mathcore.block.int32.read"; } template<> const char *GPUMirroredMemoryBlock::luaCtorName() const { return "mathcore.block.complex.read"; } template<> const char *GPUMirroredMemoryBlock::luaCtorName() const { return "mathcore.block.bool.read"; } template class GPUMirroredMemoryBlock; template class GPUMirroredMemoryBlock; template class GPUMirroredMemoryBlock; template class GPUMirroredMemoryBlock; template class GPUMirroredMemoryBlock; } // namespace AprilMath april-ann-0.4.1/packages/basics/mathcore/c_src/gpu_mirrored_memory_block.h000066400000000000000000000626271263004425400267400ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef GPU_MIRRORED_MEMORY_BLOCK_H #define GPU_MIRRORED_MEMORY_BLOCK_H // Define NO_POOL to avoid the use of a pool of pointers // #define NO_POOL // Define POOL_DEBUG for verbose debug printf's // #define POOL_DEBUG #include #include extern "C" { #include #include } #include "april_assert.h" #include "binarizer.h" #include "c_string.h" #include "cmath_overloads.h" #include "lua_string.h" #include "lua_table.h" #include "referenced.h" #include "complex_number.h" #include "unused_variable.h" #include #include "gpu_helper.h" #include "error_print.h" #include "aligned_memory.h" #include "mmapped_data.h" #include "smart_ptr.h" #ifndef NO_POOL #include "hash_table.h" #include "aux_hash_table.h" #include "list.h" #endif #define PPAL_MASK 0x01 // bit 0 = 1 #define GPU_MASK 0x02 // bit 1 = 2 #define CONST_MASK 0x04 // bit 2 = 4 #define ALLOC_MASK 0x08 // bit 3 = 8 #define MMAP_MASK 0x10 // bit 4 = 16 namespace AprilMath { /** * @brief Class base for memory blocks mirrored between host (mem ppal) and * device (GPU). * * This base defines a generic which keeps a pool of memory pointers, stores the * mem ppal pointer and the device pointer, and updates the status of this * pointers. This class does not know pointers type, it works with generic void* * or char* pointers. Therefore, the size property stores the number of * bytes. Doing this way, it is possible to reinterpret the same memory pointer * as different types, allowing a complex number block to be interpreted as a * float block with twice number of floats (but the same size). */ class GPUMirroredMemoryBlockBase : public Referenced { public: #ifndef NO_POOL typedef AprilUtils::list PoolListType; typedef AprilUtils::hash PoolType; #endif static bool USE_CUDA_DEFAULT; private: static bool use_mmap_allocation; protected: #ifndef NO_POOL static size_t MAX_POOL_LIST_SIZE; static size_t MIN_MEMORY_TH_IN_POOL; static size_t pool_size; static PoolType *pool_lists; /// Auxiliary class for free of memory pool class PoolFreeBeforeExit { public: PoolFreeBeforeExit() { } ~PoolFreeBeforeExit() { for (PoolType::iterator it = pool_lists->begin(); it != pool_lists->end(); ++it) { for (PoolListType::iterator lit = it->second.begin(); lit != it->second.end(); ++lit) { AprilUtils::aligned_free(*lit); } } delete pool_lists; } }; static PoolFreeBeforeExit pool_free_before_exit; #endif const size_t size; union { char *char_mem; mutable void *mem_ppal; const void *const_mem_ppal; }; #ifdef USE_CUDA mutable CUdeviceptr mem_gpu; bool pinned; #endif mutable unsigned char status; // bit 0 CPU, bit 1 GPU, bit 2 CONST, bit 3 ALLOCATED AprilUtils::SharedPtr mmapped_data; void setConst() { status = status | CONST_MASK; } bool isConst() const { return status & CONST_MASK; } void setAllocated() { status = status | ALLOC_MASK; } bool isAllocated() const { return status & ALLOC_MASK; } void setMMapped() { status = status | MMAP_MASK; } bool isMMapped() const { return status & MMAP_MASK; } #ifdef USE_CUDA bool getUpdatedPPAL() const { return status & PPAL_MASK; } bool getUpdatedGPU() const { return status & GPU_MASK; } void unsetUpdatedPPAL() { status = status & (~PPAL_MASK); } void unsetUpdatedGPU() { status = status & (~GPU_MASK); } void setUpdatedPPAL() { status = status | PPAL_MASK; } void setUpdatedPPAL() const { status = status | PPAL_MASK; } void setUpdatedGPU() { status = status | GPU_MASK; } void setUpdatedGPU() const { status = status | GPU_MASK; } void updateMemPPAL() const { if (!getUpdatedPPAL()) { CUresult result; setUpdatedPPAL(); april_assert(mem_gpu != 0); if (!pinned) { result = cuMemcpyDtoH(mem_ppal, mem_gpu, size); if (result != CUDA_SUCCESS) ERROR_EXIT1(160, "Could not copy memory from device to host: %s\n", cudaGetErrorString(cudaGetLastError())); } else { if (cudaMemcpyAsync(mem_ppal, reinterpret_cast(mem_gpu), size, cudaMemcpyDeviceToHost, 0) != cudaSuccess) ERROR_EXIT1(162, "Could not copy memory from device to host: %s\n", cudaGetErrorString(cudaGetLastError())); cudaThreadSynchronize(); } } } void updateMemPPAL() { if (!getUpdatedPPAL()) { CUresult result; setUpdatedPPAL(); april_assert(mem_gpu != 0); if (!pinned) { result = cuMemcpyDtoH(mem_ppal, mem_gpu, size); if (result != CUDA_SUCCESS) ERROR_EXIT1(160, "Could not copy memory from device to host: %s\n", cudaGetErrorString(cudaGetLastError())); } else { if (cudaMemcpyAsync(mem_ppal, reinterpret_cast(mem_gpu), size, cudaMemcpyDeviceToHost, 0) != cudaSuccess) ERROR_EXIT1(162, "Could not copy memory from device to host: %s\n", cudaGetErrorString(cudaGetLastError())); cudaThreadSynchronize(); } } } void copyPPALtoGPU() const { /* ERROR_EXIT(128, "You need first to update the " "memory in a non const pointer\n"); */ CUresult result; if (!pinned) { result = cuMemcpyHtoD(mem_gpu, mem_ppal, size); if (result != CUDA_SUCCESS) ERROR_EXIT1(162, "Could not copy memory from host to device: %s\n", cudaGetErrorString(cudaGetLastError())); } else { cudaThreadSynchronize(); if (cudaMemcpyAsync(reinterpret_cast(mem_gpu), mem_ppal, size, cudaMemcpyHostToDevice, 0) != cudaSuccess) ERROR_EXIT1(162, "Could not copy memory from host to device: %s\n", cudaGetErrorString(cudaGetLastError())); } } void copyPPALtoGPU() { CUresult result; if (!pinned) { result = cuMemcpyHtoD(mem_gpu, mem_ppal, size); if (result != CUDA_SUCCESS) ERROR_EXIT1(162, "Could not copy memory from host to device: %s\n", cudaGetErrorString(cudaGetLastError())); } else { cudaThreadSynchronize(); if (cudaMemcpyAsync(reinterpret_cast(mem_gpu), mem_ppal, size, cudaMemcpyHostToDevice, 0) != cudaSuccess) ERROR_EXIT1(162, "Could not copy memory from host to device: %s\n", cudaGetErrorString(cudaGetLastError())); } } bool allocMemGPU() const { /* ERROR_EXIT(128, "You need first to update the " "memory in a non const pointer\n"); return false; */ if (mem_gpu == 0) { CUDA::GPUHelper::initHelper(); CUresult result; result = cuMemAlloc(&mem_gpu, size); if (result != CUDA_SUCCESS) { ERROR_EXIT2(161, "Could not allocate %lu memory bytes in device, error %d\n", size, result); } return true; } return false; } bool allocMemGPU() { if (mem_gpu == 0) { CUDA::GPUHelper::initHelper(); CUresult result; result = cuMemAlloc(&mem_gpu, size); if (result != CUDA_SUCCESS) { ERROR_EXIT2(161, "Could not allocate %lu memory bytes in device, error %d\n", size, result); } return true; } return false; } #endif public: #ifdef USE_CUDA void updateMemGPU() const { allocMemGPU(); if (!getUpdatedGPU()) { /* ERROR_EXIT(128, "You need first to update the " "memory in a non const pointer\n"); */ setUpdatedGPU(); copyPPALtoGPU(); } } void updateMemGPU() { allocMemGPU(); if (!getUpdatedGPU()) { setUpdatedGPU(); copyPPALtoGPU(); } } #endif void toMMappedDataWriter(AprilUtils::MMappedDataWriter *mmapped_data) const { #ifdef USE_CUDA if (!getUpdatedPPAL()) ERROR_EXIT(128, "Impossible to update memory from a const pointer\n"); #endif mmapped_data->put(&size); mmapped_data->put(char_mem, size); } void toMMappedDataWriter(AprilUtils::MMappedDataWriter *mmapped_data) { #ifdef USE_CUDA updateMemPPAL(); #endif mmapped_data->put(&size); mmapped_data->put(char_mem, size); } GPUMirroredMemoryBlockBase(AprilUtils::MMappedDataReader *mmapped_data) : Referenced(), size(*(mmapped_data->get())), mmapped_data(mmapped_data) { this->char_mem = mmapped_data->get(this->size); this->status = 0; this->setMMapped(); #ifdef USE_CUDA this->unsetUpdatedGPU(); this->setUpdatedPPAL(); this->mem_gpu = 0; this->pinned = false; #endif } GPUMirroredMemoryBlockBase(size_t sz, void *mem) : Referenced(), size(sz), mem_ppal(mem) { status = 0; #ifdef USE_CUDA unsetUpdatedGPU(); setUpdatedPPAL(); mem_gpu = 0; pinned = false; #endif } GPUMirroredMemoryBlockBase(size_t sz, const void *mem) : Referenced(), size(sz), const_mem_ppal(mem) { status = 0; setConst(); #ifdef USE_CUDA unsetUpdatedGPU(); setUpdatedPPAL(); mem_gpu = 0; pinned = false; #endif } // WARNING!!! the memory zone is not initialized by default GPUMirroredMemoryBlockBase(size_t sz) : Referenced(), size(sz) { status = 0; setAllocated(); #ifdef USE_CUDA setUpdatedGPU(); setUpdatedPPAL(); mem_gpu = 0; pinned = false; #endif #ifndef NO_POOL PoolListType &l = (*pool_lists)[size]; if (l.empty() || use_mmap_allocation) { if (!use_mmap_allocation) { char_mem = AprilUtils::aligned_malloc(size); #ifdef POOL_DEBUG printf("ALLOC %lu :: %p\n", size, char_mem); #endif } else { setMMapped(); mem_ppal = (void*)mmap(NULL, sz, PROT_READ | PROT_WRITE, MAP_ANON | MAP_SHARED, -1, 0); if (mem_ppal == MAP_FAILED) ERROR_EXIT1(128, "Impossible to open required mmap memory: %s\n", strerror(errno)); } } else { mem_ppal = *(l.begin()); l.pop_front(); pool_size -= size; #ifdef POOL_DEBUG printf("POP %lu :: %p\n", size, mem_ppal); #endif } #else if (!use_mmap_allocation) { char_mem = AprilUtils::aligned_malloc(size); } else { setMMapped(); mem_ppal = (void*)mmap(NULL, sz, PROT_READ | PROT_WRITE, MAP_ANON | MAP_SHARED, -1, 0); if (mem_ppal == MAP_FAILED) ERROR_EXIT1(128, "Impossible to open required mmap memory: %s\n", strerror(errno)); } #endif } virtual ~GPUMirroredMemoryBlockBase() { // for (unsigned int i=0; i= MIN_MEMORY_TH_IN_POOL) { pool_size += size; l.push_front(char_mem); #ifdef POOL_DEBUG printf("PUSH %lu :: %p\n", size, char_mem); #endif } else { #ifdef POOL_DEBUG printf("FREE %lu :: %p\n", size, char_mem); #endif AprilUtils::aligned_free(char_mem); } #else AprilUtils::aligned_free(char_mem); #endif } else { munmap(mem_ppal, size); } } } if (mem_gpu != 0) { CUresult result; result = cuMemFree(mem_gpu); if (result != CUDA_SUCCESS) ERROR_EXIT(163, "Could not free memory from device.\n"); } #else if (isAllocated()) { if (!isMMapped()) { #ifndef NO_POOL PoolListType &l = (*pool_lists)[size]; if (pool_size+size <= MAX_POOL_LIST_SIZE && size >= MIN_MEMORY_TH_IN_POOL) { pool_size += size; l.push_front(char_mem); #ifdef POOL_DEBUG printf("PUSH %lu :: %p\n", size, char_mem); #endif } else { #ifdef POOL_DEBUG printf("FREE %lu :: %p\n", size, char_mem); #endif AprilUtils::aligned_free(char_mem); } #else AprilUtils::aligned_free(char_mem); #endif } else munmap(mem_ppal, size); } #endif } #ifdef USE_CUDA void pinnedMemoryPageLock() const { ERROR_EXIT(128, "Execute it from a non const pointer\n"); } void pinnedMemoryPageLock() { if (isConst() || isMMapped()) { ERROR_EXIT(128, "Impossible to set as pinned a const or mmapped memory block\n"); } if (mem_ppal) AprilUtils::aligned_free(char_mem); void *ptr; if (cudaHostAlloc(&ptr, size, 0) != cudaSuccess) ERROR_EXIT1(162, "Could not copy memory from host to device: %s\n", cudaGetErrorString(cudaGetLastError())); mem_ppal = ptr; pinned = true; } #endif bool getInCuda() const { #ifdef USE_CUDA return getUpdatedGPU(); #else return false; #endif } static void setUseMMapAllocation(bool v) { use_mmap_allocation = v; } static bool getUseMMapAllocation() { return use_mmap_allocation; } void forceSync(bool use_cuda) { #ifdef USE_CUDA if (isConst()) { ERROR_EXIT(128, "Impossible to write in a const memory block\n"); } if (use_cuda) { updateMemGPU(); } else { updateMemPPAL(); } #else UNUSED_VARIABLE(use_cuda); #endif } void forceSync(bool use_cuda) const { #ifdef USE_CUDA if (isConst()) { ERROR_EXIT(128, "Impossible to write in a const memory block\n"); } if (use_cuda) { updateMemGPU(); } else { updateMemPPAL(); } #else UNUSED_VARIABLE(use_cuda); #endif } #ifndef NO_POOL static void changeMaxPoolSize(size_t max_pool_size) { MAX_POOL_LIST_SIZE = max_pool_size; // TODO: free pool memory if necessary } #endif }; //////////////////////////////////////////////////////////////////////////// /** * @brief Class template for instantiation of GPUMirroredMemoryBlockBase for different * data types. */ template class GPUMirroredMemoryBlock : public GPUMirroredMemoryBlockBase { protected: GPUMirroredMemoryBlock(AprilUtils::MMappedDataReader *mmapped_data) : GPUMirroredMemoryBlockBase(mmapped_data) { } T *getPointer() { union { void *void_ptr; T *T_ptr; }; void_ptr = mem_ppal; return T_ptr; } const T *getPointer() const { union { const void *void_ptr; const T *T_ptr; }; void_ptr = const_mem_ppal; return T_ptr; } static AprilUtils::constString readULine(AprilIO::StreamInterface *stream, AprilIO::CStringStream *dest) { // Not needed, it is done in extractULineFromStream: dest->clear(); extractULineFromStream(stream, dest); return dest->getConstString(); } public: static GPUMirroredMemoryBlock * fromMMappedDataReader(AprilUtils::MMappedDataReader *mmapped_data) { return new GPUMirroredMemoryBlock(mmapped_data); } /// Constructor from non-allocated memory, does not free mem pointer. GPUMirroredMemoryBlock(unsigned int sz, T *mem) : GPUMirroredMemoryBlockBase(sz*sizeof(T), mem) { } /// Constructor from non-allocated const memory, does not free mem pointer, /// and writes are not allowed GPUMirroredMemoryBlock(unsigned int sz, const T *mem) : GPUMirroredMemoryBlockBase(sz*sizeof(T), mem) { } /// Constructor with allocation of memory, the memory pointer will be properly /// allocated and freed at destruction. GPUMirroredMemoryBlock(unsigned int sz) : GPUMirroredMemoryBlockBase(sz*sizeof(T)) { #ifndef NDEBUG T nan = AprilMath::Limits::quiet_NaN(); // Initialization to NaN allows to find not initialized memory blocks. T *mem = getPPALForWrite(); unsigned int len = getSize(); for (unsigned int i=0; i *clone() const { GPUMirroredMemoryBlock *result = new GPUMirroredMemoryBlock(getSize()); result->copyFromBlock(0, this, 0, getSize()); return result; } void copyFromBlock(size_t where, const GPUMirroredMemoryBlock *other, size_t from, size_t sz) { #ifdef USE_CUDA if (other->getUpdatedGPU()) { const T *other_ptr = other->getGPUForRead() + from; T *this_ptr = this->getGPUForWrite() + where; cudaMemcpy(this_ptr, other_ptr, sz * sizeof(T), cudaMemcpyDeviceToDevice); } else { #endif const T *other_ptr = other->getPPALForRead() + from; T *this_ptr = this->getPPALForWrite() + where; memcpy(this_ptr, other_ptr, sz * sizeof(T)); #ifdef USE_CUDA } #endif } void putValue(size_t where, const T &value) { #ifdef USE_CUDA if (this->getUpdatedGPU()) { cudaMemcpy(this->getGPUForWrite() + where, &value, sizeof(T), cudaMemcpyHostToDevice); } else { #endif T *ptr = this->getPPALForWrite(); ptr[where] = value; #ifdef USE_CUDA } #endif } void getValue(size_t from, T &result) const { #ifdef USE_CUDA if (this->getUpdatedGPU()) { cudaMemcpy(&result, this->getGPUForRead() + from, sizeof(T), cudaMemcpyDeviceToHost); } else { #endif const T *ptr = this->getPPALForRead(); result = ptr[from]; #ifdef USE_CUDA } #endif } unsigned int getSize() const { return size/sizeof(T); } const T *getPPALForRead() const { /* #ifdef USE_CUDA if (!getUpdatedPPAL()) ERROR_EXIT(128, "Update the memory from a non const pointer\n"); #endif */ #ifdef USE_CUDA updateMemPPAL(); #endif return getPointer(); } const T *getPPALForRead() { #ifdef USE_CUDA updateMemPPAL(); #endif return getPointer(); } #ifdef USE_CUDA const T *getGPUForRead() const { /* if (!getUpdatedGPU()) ERROR_EXIT(128, "Update the memory from a non const pointer\n"); */ updateMemGPU(); return reinterpret_cast(mem_gpu); } const T *getGPUForRead() { updateMemGPU(); return reinterpret_cast(mem_gpu); } #endif T *getPPALForWrite() { if (isConst()) ERROR_EXIT(128, "Impossible to write in a const memory block\n"); #ifdef USE_CUDA setUpdatedPPAL(); unsetUpdatedGPU(); #endif return getPointer(); } #ifdef USE_CUDA T *getGPUForWrite() { if (isConst()) ERROR_EXIT(128, "Impossible to write in a const memory block\n"); allocMemGPU(); setUpdatedGPU(); unsetUpdatedPPAL(); return reinterpret_cast(mem_gpu); } #endif T *getPPALForReadAndWrite() { if (isConst()) ERROR_EXIT(128, "Impossible to write in a const memory block\n"); #ifdef USE_CUDA updateMemPPAL(); unsetUpdatedGPU(); #endif return getPointer(); } #ifdef USE_CUDA T *getGPUForReadAndWrite() { if (isConst()) ERROR_EXIT(128, "Impossible to write in a const memory block\n"); updateMemGPU(); unsetUpdatedPPAL(); return reinterpret_cast(mem_gpu); } #endif T &get(unsigned int pos) { #ifdef USE_CUDA updateMemPPAL(); unsetUpdatedGPU(); #endif return getPointer()[pos]; } T &operator[](unsigned int pos) { return get(pos); } const T &get(unsigned int pos) const { #ifdef USE_CUDA updateMemPPAL(); #endif return getPointer()[pos]; } const T &operator[](unsigned int pos) const { return get(pos); } template GPUMirroredMemoryBlock *reinterpretAs() { union { GPUMirroredMemoryBlock *other; GPUMirroredMemoryBlock *ptr; }; ptr = this; return other; } static GPUMirroredMemoryBlock * read(AprilIO::StreamInterface *source, const AprilUtils::LuaTable &options) { UNUSED_VARIABLE(options); AprilUtils::SharedPtr c_str(new AprilIO::CStringStream());; AprilUtils::constString line; line = readULine(source, c_str.get()); if (!line) { ERROR_EXIT(128, "Incorrect line!!!\n"); } const unsigned int len = AprilUtils::binarizer::binary_size(); unsigned int sz; if (!line.extract_unsigned_int(&sz)) { ERROR_EXIT(128, "Incorrect line!!!\n"); } GPUMirroredMemoryBlock *obj = new GPUMirroredMemoryBlock(sz); T *ptr = obj->getPPALForWrite(); for (unsigned int i=0; i((const char *)line); line.skip(len); } return obj; } virtual void write(AprilIO::StreamInterface *destination, const AprilUtils::LuaTable &options) { UNUSED_VARIABLE(options); destination->printf("%u\n", getSize()); const int columns = 16; const unsigned int len = AprilUtils::binarizer::binary_size(); AprilUtils::UniquePtr b = new char[len]; const T *ptr = getPPALForRead(); unsigned int i; for (i=0; iput(b.get(), len); if ((i+1) % columns == 0) destination->printf("\n"); } if ((i % columns) != 0) destination->printf("\n"); } virtual const char *luaCtorName() const { ERROR_EXIT(128, "Serialization not implemented\n"); return 0; } virtual int exportParamsToLua(lua_State *L) { AprilIO::OutputLuaStringStream destination(L); AprilUtils::LuaTable options(L); write(&destination, options); destination.push(L); return 1; } }; template<> const char *GPUMirroredMemoryBlock::luaCtorName() const; template<> const char *GPUMirroredMemoryBlock::luaCtorName() const; template<> const char *GPUMirroredMemoryBlock::luaCtorName() const; template<> const char *GPUMirroredMemoryBlock::luaCtorName() const; template<> const char *GPUMirroredMemoryBlock::luaCtorName() const; template<> const char *GPUMirroredMemoryBlock::luaCtorName() const; // typedef for referring to float memory blocks typedef GPUMirroredMemoryBlock CharGPUMirroredMemoryBlock; typedef GPUMirroredMemoryBlock FloatGPUMirroredMemoryBlock; typedef GPUMirroredMemoryBlock DoubleGPUMirroredMemoryBlock; typedef GPUMirroredMemoryBlock Int32GPUMirroredMemoryBlock; typedef GPUMirroredMemoryBlock ComplexFGPUMirroredMemoryBlock; typedef GPUMirroredMemoryBlock BoolGPUMirroredMemoryBlock; } // namespace AprilMath DECLARE_LUA_TABLE_BIND_SPECIALIZATION(AprilMath::CharGPUMirroredMemoryBlock); DECLARE_LUA_TABLE_BIND_SPECIALIZATION(AprilMath::FloatGPUMirroredMemoryBlock); DECLARE_LUA_TABLE_BIND_SPECIALIZATION(AprilMath::DoubleGPUMirroredMemoryBlock); DECLARE_LUA_TABLE_BIND_SPECIALIZATION(AprilMath::Int32GPUMirroredMemoryBlock); DECLARE_LUA_TABLE_BIND_SPECIALIZATION(AprilMath::ComplexFGPUMirroredMemoryBlock); DECLARE_LUA_TABLE_BIND_SPECIALIZATION(AprilMath::BoolGPUMirroredMemoryBlock); #endif // GPU_MIRRORED_MEMORY_BLOCK_H april-ann-0.4.1/packages/basics/mathcore/c_src/lapack_headers.cc000066400000000000000000000113251263004425400245510ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "unused_variable.h" #include "lapack_headers.h" #include "error_print.h" #if defined(USE_MKL) #include "cblas_headers.h" int clapack_sgetrf(const int Order, const int M, const int N, float *A, const int lda, int *ipiv) { UNUSED_VARIABLE(Order); int INFO; sgetrf_(&M,&N,A,&lda,ipiv,&INFO); return INFO; } int clapack_sgetri(const int Order, const int N, float *A, const int lda, int *ipiv) { UNUSED_VARIABLE(Order); int INFO; int LWORK = N*N; float *WORK = new float[LWORK]; sgetri_(&N,A,&lda,ipiv,WORK,&LWORK,&INFO); delete[] WORK; return INFO; } int clapack_sgesdd(const int Order, const int M, const int N, const int LDA, float *A, float *U, float *S, float *VT) { if (Order != CblasColMajor) { ERROR_EXIT(256, "Only col_major order is allowed\n"); } const int numSV = (M 0) ERROR_EXIT(128, "The matrix is singular, computation can't be done\n"); } april-ann-0.4.1/packages/basics/mathcore/c_src/lapack_headers.h000066400000000000000000000050061263004425400244120ustar00rootroot00000000000000 /* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef LAPACK_HEADERS_H #define LAPACK_HEADERS_H #ifdef USE_MKL /////////////////////////////////// MKL /////////////////////////////////////// extern "C" { #include } /*****************************************************************************/ #elif USE_XCODE ////////////////////////////////// XCODE ////////////////////////////////////// #include /*****************************************************************************/ #else ////////////////////////////////// ATLAS ////////////////////////////////////// extern "C" { #include } /*****************************************************************************/ #endif #if defined(USE_MKL) int clapack_sgetrf(const int Order, const int M, const int N, float *A, const int lda, int *ipiv); int clapack_sgetri(const int Order, const int N, float *A, const int lda, int *ipiv); int clapack_sgesdd(const int Order, const int M, const int N, const int LDA, float *A, float *U, float *S, float *VT); int clapack_spotrf(const int Order, const int Uplo, const int N, float *A, const int LDA); #elif defined(USE_XCODE) int clapack_sgetrf(int Order, int M, int N, float *A, int lda, int *ipiv); int clapack_sgetri(int Order, int N, float *A, int lda, int *ipiv); int clapack_sgesdd(int Order, int M, int N, int LDA, float *A, float *U, float *S, float *VT); int clapack_spotrf(int Order, int Uplo, int N, float *A, int LDA); #else int clapack_sgesdd(const int Order, const int M, const int N, const int LDA, float *A, float *U, float *S, float *VT); #endif void checkLapackInfo(int info); #endif // LAPACK_HEADERS_H april-ann-0.4.1/packages/basics/mathcore/c_src/map_template.h000066400000000000000000000272621263004425400241440ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2014, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MAP_TEMPLATE_H #define MAP_TEMPLATE_H #include "cuda_kernel_templates.h" #include "cuda_utils.h" #include "gpu_mirrored_memory_block.h" namespace AprilMath { template void genericMap1Call(unsigned int N, const GPUMirroredMemoryBlock *input, unsigned int input_stride, unsigned int input_shift, GPUMirroredMemoryBlock *output, unsigned int output_stride, unsigned int output_shift, bool use_gpu, F map_op) { #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { CUDA::genericCudaMap1Call(N, input, input_stride, input_shift, output, output_stride, output_shift, map_op); } else { #endif const T *input_mem = input->getPPALForRead() + input_shift; O *output_mem = output->getPPALForWrite() + output_shift; for (unsigned int i=0; i void genericMap2Call(unsigned int N, const GPUMirroredMemoryBlock *input1, unsigned int input1_stride, unsigned int input1_shift, const GPUMirroredMemoryBlock *input2, unsigned int input2_stride, unsigned int input2_shift, GPUMirroredMemoryBlock *output, unsigned int output_stride, unsigned int output_shift, bool use_gpu, F map_op) { #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { CUDA::genericCudaMap2Call(N, input1, input1_stride, input1_shift, input2, input2_stride, input2_shift, output, output_stride, output_shift, map_op); } else { #endif const T1 *input1_mem = input1->getPPALForRead() + input1_shift; const T2 *input2_mem = input2->getPPALForRead() + input2_shift; O *output_mem = output->getPPALForWrite() + output_shift; for (unsigned int i=0; i void genericMap3Call(unsigned int N, const GPUMirroredMemoryBlock *input1, unsigned int input1_stride, unsigned int input1_shift, const GPUMirroredMemoryBlock *input2, unsigned int input2_stride, unsigned int input2_shift, const GPUMirroredMemoryBlock *input3, unsigned int input3_stride, unsigned int input3_shift, GPUMirroredMemoryBlock *output, unsigned int output_stride, unsigned int output_shift, bool use_gpu, F map_op) { #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif // FIXME: Review why this code is not compiling with nvcc (CUDA) :S /* /home/pako/programas/april-ann/build_release_cuda_and_mkl/packages/basics/mathcore/include/map_template.h(126): error: no instance of function template "AprilMath::CUDA::genericCudaMap3Call" matches the argument list argument types are: (unsigned int, const AprilMath::GPUMirroredMemoryBlock *, unsigned int, unsigned int, const AprilMath::GPUMirroredMemoryBlock<__nv_bool> *, unsigned int, unsigned int, const AprilMath::GPUMirroredMemoryBlock *, unsigned int, unsigned int, AprilMath::GPUMirroredMemoryBlock *, unsigned int, unsigned int, AprilMath::MatrixExt::Operations::maskedCopyOp) detected during: instantiation of "void AprilMath::genericMap3Call(unsigned int, const AprilMath::GPUMirroredMemoryBlock *, unsigned int, unsigned int, const AprilMath::GPUMirroredMemoryBlock *, unsigned int, unsigned int, const AprilMath::GPUMirroredMemoryBlock *, unsigned int, unsigned int, AprilMath::GPUMirroredMemoryBlock *, unsigned int, unsigned int, __nv_bool, F) [with T1=AprilMath::ComplexF, T2=__nv_bool, T3=AprilMath::ComplexF, O=AprilMath::ComplexF, F=AprilMath::MatrixExt::Operations::maskedCopyOp]" (214): here instantiation of "void AprilMath::ScalarToSpanMap3::operator()(unsigned int, const AprilMath::GPUMirroredMemoryBlock *, unsigned int, unsigned int, const AprilMath::GPUMirroredMemoryBlock *, unsigned int, unsigned int, const AprilMath::GPUMirroredMemoryBlock *, unsigned int, unsigned int, AprilMath::GPUMirroredMemoryBlock *, unsigned int, unsigned int, __nv_bool) const [with T1=AprilMath::ComplexF, T2=__nv_bool, T3=AprilMath::ComplexF, O=AprilMath::ComplexF, OP=AprilMath::MatrixExt::Operations::maskedCopyOp]" c_src/map_matrix.impl.h(371): here instantiation of "Basics::Matrix *AprilMath::MatrixExt::MatrixSpanMap3(const Basics::Matrix *, const Basics::Matrix *, const Basics::Matrix *, const OP &, Basics::Matrix *, int, unsigned int) [with T1=AprilMath::ComplexF, T2=__nv_bool, T3=AprilMath::ComplexF, O=AprilMath::ComplexF, OP=AprilMath::ScalarToSpanMap3>]" c_src/map_matrix.impl.h(114): here instantiation of "Basics::Matrix *AprilMath::MatrixExt::MatrixScalarMap3(const Basics::Matrix *, const Basics::Matrix *, const Basics::Matrix *, const OP &, Basics::Matrix *, int, unsigned int) [with T1=AprilMath::ComplexF, T2=__nv_bool, T3=AprilMath::ComplexF, O=AprilMath::ComplexF, OP=AprilMath::MatrixExt::Operations::maskedCopyOp]" c_src/matrix_ext_operations.cu(406): here instantiation of "Basics::Matrix *AprilMath::MatrixExt::Operations::matMaskedCopy(Basics::Matrix *, const Basics::Matrix<__nv_bool> *, const Basics::Matrix *, Basics::Matrix *) [with T=AprilMath::ComplexF]" c_src/matrix_ext_operations.cu(515): here */ // #ifdef USE_CUDA // if (use_gpu) { // CUDA::genericCudaMap3Call(N, // input1, input1_stride, input1_shift, // input2, input2_stride, input2_shift, // input3, input3_stride, input3_shift, // output, output_stride, output_shift, // map_op); // } // else { // #endif const T1 *input1_mem = input1->getPPALForRead() + input1_shift; const T2 *input2_mem = input2->getPPALForRead() + input2_shift; const T3 *input3_mem = input3->getPPALForRead() + input3_shift; O *output_mem = output->getPPALForWrite() + output_shift; for (unsigned int i=0; i struct ScalarToSpanMap1 { const OP functor; ScalarToSpanMap1(const OP &functor) : functor(functor) { } void operator()(unsigned int N, const GPUMirroredMemoryBlock *input, unsigned int input_stride, unsigned int input_shift, GPUMirroredMemoryBlock *output, unsigned int output_stride, unsigned int output_shift, bool use_cuda) const { genericMap1Call(N, input, input_stride, input_shift, output, output_stride, output_shift, use_cuda, functor); } }; template struct ScalarToSpanMap2 { const OP functor; ScalarToSpanMap2(const OP &functor) : functor(functor) { } void operator()(unsigned int N, const GPUMirroredMemoryBlock *input1, unsigned int input1_stride, unsigned int input1_shift, const GPUMirroredMemoryBlock *input2, unsigned int input2_stride, unsigned int input2_shift, GPUMirroredMemoryBlock *output, unsigned int output_stride, unsigned int output_shift, bool use_cuda) const { genericMap2Call(N, input1, input1_stride, input1_shift, input2, input2_stride, input2_shift, output, output_stride, output_shift, use_cuda, functor); } }; template struct ScalarToSpanMap3 { const OP functor; ScalarToSpanMap3(const OP &functor) : functor(functor) { } void operator()(unsigned int N, const GPUMirroredMemoryBlock *input1, unsigned int input1_stride, unsigned int input1_shift, const GPUMirroredMemoryBlock *input2, unsigned int input2_stride, unsigned int input2_shift, const GPUMirroredMemoryBlock *input3, unsigned int input3_stride, unsigned int input3_shift, GPUMirroredMemoryBlock *output, unsigned int output_stride, unsigned int output_shift, bool use_cuda) const { genericMap3Call(N, input1, input1_stride, input1_shift, input2, input2_stride, input2_shift, input3, input3_stride, input3_shift, output, output_stride, output_shift, use_cuda, functor); } }; } // namespace AprilMath #endif // MAP_TEMPLATE_H april-ann-0.4.1/packages/basics/mathcore/c_src/mathcore.h000066400000000000000000000075311263004425400232730ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATHCORE_H #define MATHCORE_H #include #ifdef USE_CUDA #include #include #include #include #include "cublas_error.h" #include "cusparse_error.h" #endif #include "cblas_headers.h" #include "lapack_headers.h" #include "cublas_error.h" #include "cusparse_error.h" #include "cuda_utils.h" #include "gpu_helper.h" #include "gpu_mirrored_memory_block.h" /** * @brief The namespace AprilMath contains operations over different scalar types by * using templatized functions and C++ functors. * * - **Reduce operations**: they are defined over vector spans, taking two * functors which allow the reduce computation. The first functor computes the * reduce from the input typename into the output typename. The second functor * allows to reduce output typename scalars and is needed because it is possible * to need intermediate partial results in the output space before the reduction * is computed: * - AprilMath::genericReduce1Call * - AprilMath::genericReduce2Call * - AprilMath::genericReduceMinMAxCall * * - **Map operations**: they are defined over vector spans, taking a functor * which implement the map operation over a vector span. * - AprilMath::genericMap1Call * - AprilMath::genericMap2Call * * Previous functions take mathematicals functors like ones declared in * AprilMath::Functors namespace. For simplicity, some of this functors has a * function which allows to call @c operator() without an explicit instantiation * of the functor object. This functions are in AprilMath namespace under the * same name as their equivalent AprilMath::Functors object declaration. * * @note All of this operations are exported to CUDA and can be used safely in * functions implemented to run in GPU device or CPU host. * * @note Some of the math operations defined in AprilMath has a curried version * that allow to call the function with a fixed parameter. */ namespace AprilMath { ////////////////////////////////////////////////////////////////////// int doSearchCSCSparseIndexOf(const Int32GPUMirroredMemoryBlock *indices, const Int32GPUMirroredMemoryBlock *first_index, const int c1, const int c2, bool use_gpu); int doSearchCSRSparseIndexOf(const Int32GPUMirroredMemoryBlock *indices, const Int32GPUMirroredMemoryBlock *first_index, const int c1, const int c2, bool use_gpu); int doSearchCSCSparseIndexOfFirst(const Int32GPUMirroredMemoryBlock *indices, const Int32GPUMirroredMemoryBlock *first_index, const int c1, const int c2, bool use_gpu); int doSearchCSRSparseIndexOfFirst(const Int32GPUMirroredMemoryBlock *indices, const Int32GPUMirroredMemoryBlock *first_index, const int c1, const int c2, bool use_gpu); } #endif // MATHCORE_H april-ann-0.4.1/packages/basics/mathcore/c_src/nrm2.cu000066400000000000000000000046471263004425400225340ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "mathcore.h" #include "nrm2.h" #include "unused_variable.h" namespace AprilMath { #ifdef USE_CUDA namespace CUDA { /*************************************** ************** CUDA SECTION *********** ***************************************/ template<> cublasStatus_t wrapperCublasNrm2(cublasHandle_t &handle, unsigned int n, const float *x_mem, unsigned int x_inc, float *result) { return cublasSnrm2(handle, n, x_mem, x_inc, result); } } // namespace CUDA #endif /*************************************** ************* CBLAS SECTION *********** ***************************************/ template<> float wrapperCblasNrm2(unsigned int size, const float *x_mem, unsigned int x_inc) { return cblas_snrm2(size, x_mem, x_inc); } template<> float wrapperCblasNrm2(unsigned int size, const double *x_mem, unsigned int x_inc) { return cblas_dnrm2(size, x_mem, x_inc); } template<> float wrapperCblasNrm2(unsigned int size, const ComplexF *x_mem, unsigned int x_inc) { return cblas_scnrm2(size, x_mem, x_inc); } } // namespace AprilMath april-ann-0.4.1/packages/basics/mathcore/c_src/nrm2.h000066400000000000000000000136121263004425400223440ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef NRM2_H #define NRM2_H #include "mathcore.h" #include "unused_variable.h" namespace AprilMath { #ifdef USE_CUDA namespace CUDA { /*************************************** ************** CUDA SECTION *********** ***************************************/ template cublasStatus_t wrapperCublasNrm2(cublasHandle_t &handle, unsigned int size, const T *x_mem, unsigned int x_inc, float *result) { UNUSED_VARIABLE(handle); UNUSED_VARIABLE(size); UNUSED_VARIABLE(x_mem); UNUSED_VARIABLE(x_inc); UNUSED_VARIABLE(result); ERROR_EXIT(256, "NOT IMPLEMENTED\n"); return CUBLAS_STATUS_INTERNAL_ERROR; } template<> cublasStatus_t wrapperCublasNrm2(cublasHandle_t &handle, unsigned int size, const float *x_mem, unsigned int x_inc, float *result); } // namespace CUDA #endif /*************************************** ************* CBLAS SECTION *********** ***************************************/ template float wrapperCblasNrm2(unsigned int size, const T *x_mem, unsigned int x_inc) { UNUSED_VARIABLE(size); UNUSED_VARIABLE(x_mem); UNUSED_VARIABLE(x_inc); ERROR_EXIT(128, "NOT IMPLEMENTED\n"); return 0.0f; } template<> float wrapperCblasNrm2(unsigned int, const float *, unsigned int); template<> float wrapperCblasNrm2(unsigned int, const double *, unsigned int); template<> float wrapperCblasNrm2(unsigned int, const ComplexF *, unsigned int); /*************************************** *********** TEMPLATE SECTION ********** ***************************************/ /** * @brief doNrm2 reduction, it is applied over a vector span, and follows the * CBLAS wrapper API. * * @tparam T - The type of the input/output data. * @tparam OP - A functor typename, needed to reduce the partial result of * dest pointer in case @c set_dest_to_zero=false * * @param n - The size of the vector. * @param x - The input vector. * @param inc - The stride between consecutive elements. * @param shift - The position of the first valid element. * @param use_gpu - Indicates if do computation using GPU or not. * @param zero - The initial value of the reduction. * @param functor - The functor for partial results reduction, used to reduce * dest content. * @param dest - A pointer to result memory. * @param dest_raw_pos - The position in previous memory block where result * will be stored. * @param set_dest_to_zero - Indicates if @c dest memory needs to be initialized * to zero or if its content will be taken as partial value of the reduction. * * @note functor implements void operator()(T &acc, const T &other) const; * * @see AprilMath::MatrixExt for more information about API of CBLAS and * user-defined reductions. */ template void doNrm2(unsigned int n, const GPUMirroredMemoryBlock *x, unsigned int inc, unsigned int shift, bool use_gpu, float zero, OP functor, GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos, bool set_dest_to_zero) { UNUSED_VARIABLE(zero); const T *x_mem; #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { cublasStatus_t status; cublasHandle_t handle = CUDA::GPUHelper::getHandler(); x_mem = x->getGPUForRead() + shift; status = cublasSetStream(handle, CUDA::GPUHelper::getCurrentStream()); checkCublasError(status); if (set_dest_to_zero) { status = CUDA::wrapperCublasNrm2(handle, n, x_mem, inc, dest->getPPALForWrite() + dest_raw_pos); } else { GPUMirroredMemoryBlock result(1); status = CUDA::wrapperCublasNrm2(handle, n, x_mem, inc, result.getPPALForWrite()); float *dest_ptr = dest->getPPALForReadAndWrite() + dest_raw_pos; functor(*dest_ptr, *(result.getPPALForRead())); } checkCublasError(status); } else { #endif x_mem = x->getPPALForRead() + shift; if (set_dest_to_zero) { float *dest_ptr = dest->getPPALForWrite() + dest_raw_pos; *dest_ptr = wrapperCblasNrm2(n, x_mem, inc); } else { float *dest_ptr = dest->getPPALForReadAndWrite() + dest_raw_pos; functor(*dest_ptr, wrapperCblasNrm2(n, x_mem, inc)); } #ifdef USE_CUDA } #endif } } // namespace AprilMath #endif // NRM2_H april-ann-0.4.1/packages/basics/mathcore/c_src/realfftwithhamming.cc000066400000000000000000000123251263004425400255040ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2010, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include #include "realfftwithhamming.h" namespace AprilMath { RealFFTwithHamming::RealFFTwithHamming(int vSize) { this->vSize = vSize; // obtain first power of 2 >= vSize bitsnFFT = 1; nFFT = 2; while (nFFT < vSize) { nFFT *= 2; bitsnFFT++; } // invsqrt2 = 1.0/sqrt(2.0); vec = new double[nFFT]; tmp = new double[nFFT]; tbl = new nodtblfft[nFFT>>3]; double aux = M_PI/(nFFT>>1); for (int i=0;i<(nFFT>>3);i++) { tbl[i].c = cos(aux*i); tbl[i].s = sin(aux*i); tbl[i].c3 = cos(aux*i*3); tbl[i].s3 = sin(aux*i*3); } hamming_window = new double[vSize]; double factor = 2.0 * M_PI / (vSize - 1.0); for(int i=0; i < vSize; i++ ) hamming_window[i] = 0.54 - 0.46 * cos( factor * i ); } RealFFTwithHamming::~RealFFTwithHamming() { delete[] tmp; delete[] vec; delete[] tbl; delete[] hamming_window; } ///////////////////////////////////////////////////////// // Sorensen in-place split-radix FFT for real values // Sorensen et al: Real-Valued Fast Fourier Transform Algorithms, // IEEE Trans. ASSP, ASSP-35, No. 6, June 1987 // // input vector data is an array of doubles: // re(0),re(1),re(2),...,re(vSize-1) // // output vector data is // s(0), s(1), s(nFFT/2-1) // where s = abs(fft(data)) void RealFFTwithHamming::operator() (const double input[], double output[]) { int i; // copy data to vec applying the Hamming window: for (i=0; i> 1; double t1,t2,t3,t4,t5,t6,ss1,ss3,cc1,cc3; n4=nFFT-1; //data shuffling for (i=0,j=0,n2=halfnFFT; i>= 1; } j += k; } /*----------------------*/ //length two butterflies i0=0; id=4; do{ for (; i02;k>>=1){ n2<<=1; n4=n2>>2; n8=n2>>3; ie = je = nFFT/n2; i1=0; id=n2<<1; do{ for (; i1(tmp[0])); double *aux; for (i=1,aux=tmp+2;ivoid operator()(O &acc, const T &other) const * * @note partials_reduce_op implements void operator()(O &acc, const O &other) const */ template void genericReduce1Call(unsigned int N, const GPUMirroredMemoryBlock *input, unsigned int input_stride, unsigned int input_shift, bool use_gpu, const O &zero, F reduce_op, P partials_reduce_op, GPUMirroredMemoryBlock *dest, unsigned int dest_shift, bool set_dest_to_zero) { #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); UNUSED_VARIABLE(partials_reduce_op); #endif #ifdef USE_CUDA if (use_gpu) { CUDA::genericCudaReduce1Call(N, input, input_stride, input_shift, zero, dest, dest_shift, set_dest_to_zero, reduce_op, partials_reduce_op); } else { #endif const T *v_mem = input->getPPALForRead() + input_shift; O *dest_ptr; if (set_dest_to_zero) { dest_ptr = dest->getPPALForWrite() + dest_shift; *dest_ptr = zero; } else { dest_ptr = dest->getPPALForReadAndWrite() + dest_shift; } for (unsigned int i=0; ivoid operator()(O &acc, const T1 &other1, const T2 &other2) const * * @note partials_reduce_op implements void operator()(O &acc, const O &other) const */ template void genericReduce2Call(unsigned int N, const GPUMirroredMemoryBlock *input1, unsigned int input1_stride, unsigned int input1_shift, const GPUMirroredMemoryBlock *input2, unsigned int input2_stride, unsigned int input2_shift, bool use_gpu, const O &zero, F reduce_op, P partials_reduce_op, GPUMirroredMemoryBlock *dest, unsigned int dest_shift, bool set_dest_to_zero) { #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); UNUSED_VARIABLE(partials_reduce_op); #endif #ifdef USE_CUDA if (use_gpu) { CUDA::genericCudaReduce2Call(N, input1, input1_stride, input1_shift, input2, input2_stride, input2_shift, zero, dest, dest_shift, set_dest_to_zero, reduce_op, partials_reduce_op); } else { #endif const T1 *v1_mem = input1->getPPALForRead() + input1_shift; const T2 *v2_mem = input2->getPPALForRead() + input2_shift; O *dest_ptr; if (set_dest_to_zero) { dest_ptr = dest->getPPALForWrite() + dest_shift; *dest_ptr = zero; } else { dest_ptr = dest->getPPALForReadAndWrite() + dest_shift; } for (unsigned int i=0; ivoid operator()(T &, const T &, int32_t &, const int32_t &) const */ template void genericReduceMinMaxCall(unsigned int N, const GPUMirroredMemoryBlock *input, unsigned int input_stride, unsigned int input_shift, bool use_gpu, const T &zero, F reduce_op, GPUMirroredMemoryBlock *which, unsigned int which_shift, GPUMirroredMemoryBlock *dest, unsigned int dest_shift, bool set_dest_to_zero) { #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); UNUSED_VARIABLE(zero); #endif #ifdef USE_CUDA if (use_gpu) { CUDA::genericCudaReduceMinMaxCall(N, input, input_stride, input_shift, zero, which, which_shift, dest, dest_shift, set_dest_to_zero, reduce_op); } else { #endif const T *v_mem = input->getPPALForRead() + input_shift; T *dest_ptr; int32_t *which_ptr; if (set_dest_to_zero) { dest_ptr = dest->getPPALForWrite() + dest_shift; which_ptr = which->getPPALForWrite() + which_shift; *dest_ptr = zero; *which_ptr = 0; } else { dest_ptr = dest->getPPALForReadAndWrite() + dest_shift; which_ptr = which->getPPALForReadAndWrite() + which_shift; } for (unsigned int i=0; i(i+1)); } #ifdef USE_CUDA } #endif } /** * @brief A functor which transforms a unary reduction functor into a * unary span reduction functor. * * @tparam T - The input type. * @tparam O - The output type. * @tparam OP1 - The type of the unary functor. * * @note OP1 implements void operator()(O &acc, const T &other) const * * @note The unary span is the concept of unary reduction applied over a vector * span. * * @note This struct is used by AprilMath::MatrixExt reduce functions to * force user-defined reductions to follow CBLAS wrappers API. * * @see AprilMath::MatrixExt for more information about API of CBLAS and * user-defined reductions. */ template struct ScalarToSpanReduce1 { /// An instance of the unary functor. const OP1 functor; /// The constructor stores the functor. ScalarToSpanReduce1(const OP1 &functor) : functor(functor) { } template /** * @brief The unary span functor implements an operator() which receives the * vector (pointer, size, stride and shift/offset) where @c functor will be * applied. * * Additionally, it needs another @c functor2 for reduction of partial * results. * * @param N - The size of the vector. * @param input - A pointer to the vector. * @param input_stride - The stride between consecutive elements. * @param input_shift - The position of the first valid element. * @param use_cuda - A boolean indicating if use or not CUDA. * @param zero - The initial value of the reduction. * @param functor2 - The functor for partial results reduction. * @param dest - A pointer to a destination memory block. * @param dest_raw_pos - The position in dest where result will be stored. * @param set_dest_to_zero - Indicates if dest will be set to zero or its * content will be reused in the reduction. * * @note functor2 implements void operator(O &acc, const O &other) const */ void operator()(unsigned int N, const GPUMirroredMemoryBlock *input, unsigned int input_stride, unsigned int input_shift, bool use_cuda, const O &zero, const OP2 &functor2, GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos, bool set_dest_to_zero) const { genericReduce1Call(N, input, input_stride, input_shift, use_cuda, zero, functor, functor2, dest, dest_raw_pos, set_dest_to_zero); } }; /** * @brief A functor which transforms a binary reduction functor into a * binary span reduction functor. * * @tparam T1 - The input1 type. * @tparam T2 - The input2 type. * @tparam O - The output type. * @tparam OP1 - The type of the unary functor. * * @note OP1 implements void operator()(O &acc, const T1 &other, const T2 &other) const * * @note The binary span is the concept of binary reduction applied over a vector * span. * * @note This struct is used by AprilMath::MatrixExt reduce functions to * force user-defined reductions to follow CBLAS wrappers API. * * @see AprilMath::MatrixExt for more information about API of CBLAS and * user-defined reductions. */ template struct ScalarToSpanReduce2 { /// An instance of the given functor typename. const OP1 functor; /// The constructor stores the given functor. ScalarToSpanReduce2(const OP1 &functor) : functor(functor) { } /** * @brief The binary span functor implements an operator() which receives * the input vectors (pointer, size, stride and shift/offset) where @c * functor will be applied. * * Additionally, it needs another @c functor2 for reduction of partial * results. * * @param N - The size of the vector. * @param input1 - A pointer to the vector. * @param input1_stride - The stride between consecutive elements. * @param input1_shift - The position of the first valid element. * @param input2 - A pointer to the vector. * @param input2_stride - The stride between consecutive elements. * @param input2_shift - The position of the first valid element. * @param use_cuda - A boolean indicating if use or not CUDA. * @param zero - The initial value of the reduction. * @param functor2 - The functor for partial results reduction. * @param dest - A pointer to a destination memory block. * @param dest_raw_pos - The position in dest where result will be stored. * @param set_dest_to_zero - Indicates if dest will be set to zero or its * content will be reused in the reduction. * * @note functor2 implements void operator(O &acc, const O &other) const */ template void operator()(unsigned int N, const GPUMirroredMemoryBlock *input1, unsigned int input1_stride, unsigned int input1_shift, const GPUMirroredMemoryBlock *input2, unsigned int input2_stride, unsigned int input2_shift, bool use_cuda, const O &zero, const OP2 &functor2, GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos, bool set_dest_to_zero) const { genericReduce2Call(N, input1, input1_stride, input1_shift, input2, input2_stride, input2_shift, use_cuda, zero, functor, functor2, dest, dest_raw_pos, set_dest_to_zero); } }; template struct ScalarToSpanReduceMinMax { const OP functor; ScalarToSpanReduceMinMax(const OP &functor) : functor(functor) { } template void operator()(unsigned int N, const GPUMirroredMemoryBlock *input, unsigned int input_stride, unsigned int input_shift, bool use_cuda, const T &zero, const OP2 &functor2, // ignored here GPUMirroredMemoryBlock *which, unsigned int which_raw_pos, GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos, bool set_dest_to_zero) const { UNUSED_VARIABLE(functor2); genericReduceMinMaxCall(N, input, input_stride, input_shift, use_cuda, zero, functor, which, which_raw_pos, dest, dest_raw_pos, set_dest_to_zero); } }; } // namespace AprilMath #endif // REDUCE_TEMPLATE_H april-ann-0.4.1/packages/basics/mathcore/c_src/scal.cu000066400000000000000000000111211263004425400225610ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "mathcore.h" #include "unused_variable.h" namespace AprilMath { #ifdef USE_CUDA namespace CUDA { /*************************************** ************** CUDA SECTION *********** ***************************************/ cublasStatus_t wrapperCublasScal(cublasHandle_t &handle, int N, float *alpha, float *x_mem, unsigned int x_inc) { return cublasSscal(handle, N, alpha, x_mem, x_inc); } cublasStatus_t wrapperCublasScal(cublasHandle_t &handle, int N, double *alpha, double *x_mem, unsigned int x_inc) { return cublasDscal(handle, N, alpha, x_mem, x_inc); } cublasStatus_t wrapperCublasScal(cublasHandle_t &handle, int N, ComplexF *alpha, ComplexF *x_mem, unsigned int x_inc) { return cublasCscal(handle, N, reinterpret_cast(alpha), reinterpret_cast(x_mem), x_inc); } } #endif /*************************************** ************* CBLAS SECTION *********** ***************************************/ void wrapperCblasScal(int N, float alpha, float *x_mem, unsigned int x_inc) { cblas_sscal(N, alpha, x_mem, x_inc); } void wrapperCblasScal(int N, double alpha, double *x_mem, unsigned int x_inc) { cblas_dscal(N, alpha, x_mem, x_inc); } void wrapperCblasScal(int N, ComplexF alpha, ComplexF *x_mem, unsigned int x_inc) { cblas_cscal(N, &alpha, x_mem, x_inc); } /*************************************** *********** TEMPLATE SECTION ********** ***************************************/ template void doScal(unsigned int size, GPUMirroredMemoryBlock *x, unsigned int inc, unsigned int shift, T alpha, bool use_gpu) { T *x_mem; #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { cublasStatus_t status; cublasHandle_t handle = CUDA::GPUHelper::getHandler(); x_mem = x->getGPUForReadAndWrite() + shift; status = cublasSetStream(handle, CUDA::GPUHelper::getCurrentStream()); checkCublasError(status); status = CUDA::wrapperCublasScal(handle, size, &alpha, x_mem, inc); checkCublasError(status); } else { #endif x_mem = x->getPPALForReadAndWrite() + shift; wrapperCblasScal(size, alpha, x_mem, inc); #ifdef USE_CUDA } #endif } template void doScal(unsigned int size, GPUMirroredMemoryBlock *x, unsigned int inc, unsigned int shift, float alpha, bool use_gpu); template void doScal(unsigned int size, GPUMirroredMemoryBlock *x, unsigned int inc, unsigned int shift, double alpha, bool use_gpu); template void doScal(unsigned int size, GPUMirroredMemoryBlock *x, unsigned int inc, unsigned int shift, ComplexF alpha, bool use_gpu); } // namespace AprilMath april-ann-0.4.1/packages/basics/mathcore/c_src/search_index_of.cu000066400000000000000000000121271263004425400247660ustar00rootroot00000000000000/* * This file is part of the Neural Network modules of the APRIL toolkit (A * Pattern Recognizer In Lua). * * Copyright 2012, Salvador España-Boquera, Adrian Palacios Corella, Francisco * Zamora-Martinez * * The APRIL-MLP toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "binary_search.h" #include "mathcore.h" #include "unused_variable.h" using namespace AprilUtils; namespace AprilMath { /// searchs the index where the given coordinate (c1,c2) will is stored, or -1 /// in case it isn't there int doSearchCSCSparseIndexOf(const Int32GPUMirroredMemoryBlock *indices, const Int32GPUMirroredMemoryBlock *first_index, const int c1, const int c2, bool use_gpu) { #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { ERROR_PRINT("CUDA VERSION NOT IMPLEMENTED\n"); } // else { #endif const int *indices_ptr = indices->getPPALForRead(); const int *first_index_ptr = first_index->getPPALForRead(); if (c1 == 0) return first_index_ptr[c2]; else { int idx = binary_search(indices_ptr + first_index_ptr[c2], first_index_ptr[c2+1] - first_index_ptr[c2], c1); return (idx >= 0) ? (idx + first_index_ptr[c2]) : idx; } #ifdef USE_CUDA // } #endif } /// searchs the index where the given coordinate (c1,c2) will is stored, or -1 /// in case it isn't there int doSearchCSRSparseIndexOf(const Int32GPUMirroredMemoryBlock *indices, const Int32GPUMirroredMemoryBlock *first_index, const int c1, const int c2, bool use_gpu) { #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { ERROR_PRINT("CUDA VERSION NOT IMPLEMENTED\n"); } // else { #endif const int *indices_ptr = indices->getPPALForRead(); const int *first_index_ptr = first_index->getPPALForRead(); if (c2 == 0) return first_index_ptr[c1]; else { int idx = binary_search(indices_ptr + first_index_ptr[c1], first_index_ptr[c1+1] - first_index_ptr[c1], c2); return (idx >= 0) ? (idx + first_index_ptr[c1]) : idx; } #ifdef USE_CUDA // } #endif } ///////////////////////////////////////////////////////////////////// /// searchs the index where the given coordinate (c1,c2) will is stored, or -1 /// in case it isn't there int doSearchCSCSparseIndexOfFirst(const Int32GPUMirroredMemoryBlock *indices, const Int32GPUMirroredMemoryBlock *first_index, const int c1, const int c2, bool use_gpu) { #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { ERROR_PRINT("CUDA VERSION NOT IMPLEMENTED\n"); } // else { #endif const int *indices_ptr = indices->getPPALForRead(); const int *first_index_ptr = first_index->getPPALForRead(); if (c1 == 0) return first_index_ptr[c2]; else { const int *aux = binary_search_first(indices_ptr + first_index_ptr[c2], first_index_ptr[c2+1] - first_index_ptr[c2], c1); if (aux == 0) ERROR_EXIT(128, "Incorrect given coordinates\n"); return (*aux > 0) ? (*aux + first_index_ptr[c2]) : *aux; } #ifdef USE_CUDA // } #endif } /// searchs the index where the given coordinate (c1,c2) will is stored, or -1 /// in case it isn't there int doSearchCSRSparseIndexOfFirst(const Int32GPUMirroredMemoryBlock *indices, const Int32GPUMirroredMemoryBlock *first_index, const int c1, const int c2, bool use_gpu) { #ifndef USE_CUDA UNUSED_VARIABLE(use_gpu); #endif #ifdef USE_CUDA if (use_gpu) { ERROR_PRINT("CUDA VERSION NOT IMPLEMENTED\n"); } // else { #endif const int *indices_ptr = indices->getPPALForRead(); const int *first_index_ptr = first_index->getPPALForRead(); if (c2 == 0) return first_index_ptr[c1]; else { const int *aux = binary_search_first(indices_ptr + first_index_ptr[c1], first_index_ptr[c1+1] - first_index_ptr[c1], c2); if (aux == 0) ERROR_EXIT(128, "Incorrect given coordinates\n"); return (*aux > 0) ? (*aux + first_index_ptr[c1]) : *aux; } #ifdef USE_CUDA // } #endif } } // namespace AprilMath april-ann-0.4.1/packages/basics/mathcore/c_src/transpose.cu000066400000000000000000000052471263004425400236710ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "transpose.h" #ifdef USE_CUDA namespace AprilMath { namespace CUDA { cublasStatus_t wrapperTranspose(cublasHandle_t &handle, int m, int n, const float *orig, int orig_inc, float *dest, int dest_inc) { float alpha=1.0f, beta=0.0f; return cublasSgeam(handle, CUBLAS_OP_T, CUBLAS_OP_T, m, n, &alpha, orig, orig_inc, &beta, orig, orig_inc, dest, dest_inc); } cublasStatus_t wrapperTranspose(cublasHandle_t &handle, int m, int n, const double *orig, int orig_inc, double *dest, int dest_inc) { double alpha=1.0, beta=0.0; return cublasDgeam(handle, CUBLAS_OP_T, CUBLAS_OP_T, m, n, &alpha, orig, orig_inc, &beta, orig, orig_inc, dest, dest_inc); } cublasStatus_t wrapperTranspose(cublasHandle_t &handle, int m, int n, const ComplexF *orig, int orig_inc, ComplexF *dest, int dest_inc) { ComplexF alpha=ComplexF(1.0,1.0), beta=ComplexF(0.0,0.0); return cublasCgeam(handle, CUBLAS_OP_T, CUBLAS_OP_T, m, n, reinterpret_cast(&alpha), reinterpret_cast(orig), orig_inc, reinterpret_cast(&beta), reinterpret_cast(orig), orig_inc, reinterpret_cast(dest), dest_inc); } } } #endif // USE_CUDA april-ann-0.4.1/packages/basics/mathcore/c_src/transpose.h000066400000000000000000000034711263004425400235060ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef TRANSPOSE_H #define TRANSPOSE_H #include "complex_number.h" #include "mathcore.h" #ifdef USE_CUDA namespace AprilMath { namespace CUDA { cublasStatus_t wrapperTranspose(cublasHandle_t &handle, int m, int n, const float *orig, int orig_inc, float *dest, int dest_inc); cublasStatus_t wrapperTranspose(cublasHandle_t &handle, int m, int n, const double *orig, int orig_inc, double *dest, int dest_inc); cublasStatus_t wrapperTranspose(cublasHandle_t &handle, int m, int n, const AprilMath::ComplexF *orig, int orig_inc, AprilMath::ComplexF *dest, int dest_inc); } } #endif // USE_CUDA #endif // TRANSPOSE_H april-ann-0.4.1/packages/basics/mathcore/lua_src/000077500000000000000000000000001263004425400216515ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/mathcore/lua_src/mathcore.lua000066400000000000000000000171121263004425400241600ustar00rootroot00000000000000local MAX = 4 local DEFAULT_SIZE = 8 -- global NaN and inf definition nan = mathcore.limits.double.quiet_NaN() inf = mathcore.limits.double.infinity() local function make_block_tostring(name, str) return function(b) local result = {} local data = {} for i=1,math.min(MAX, b:size()) do data[i] = str(b:raw_get(i-1)) end if b:size() > MAX then data[#data+1] = "..." data[#data+1] = str(b:raw_get(b:size()-1)) end result[1] = table.concat(data, " ") result[2] = "# %s size %d [%s]"%{name, b:size(), b:get_reference_string()} return table.concat(result, "\n") end end local function make_serialize(cls) cls.meta_instance.serialize = function(self,stream) if not stream then local result = self:write() return table.concat{ self:ctor_name(), "[[", result, "]]" } else stream:write(self:ctor_name()) stream:write("[[") self:write(stream) stream:write("]]") end end end local function make_index_function(cls) class.declare_functional_index(cls, function(obj,key) if type(key) == "number" then return obj(key) end end) end local function new_index_function(obj, key, value) obj:raw_set(key, value) end local function call_function(obj, ...) return obj:raw_get(...) end local function len_function(obj) return obj:size() end mathcore.block.float.meta_instance.__tostring = make_block_tostring("Float block", function(value) return string.format("% -13.6g", value) end) mathcore.block.double.meta_instance.__tostring = make_block_tostring("Double block", function(value) return string.format("% -15.6g", value) end) mathcore.block.int32.meta_instance.__tostring = make_block_tostring("Int32 block", function(value) return string.format("% 11d", value) end) mathcore.block.complex.meta_instance.__tostring = make_block_tostring("Complex block", function(value) return string.format("%26s", tostring(value)) end) mathcore.block.bool.meta_instance.__tostring = make_block_tostring("Bool block", function(value) return string.format("%s", value and "T" or "F") end) make_serialize(mathcore.block.float) make_serialize(mathcore.block.double) make_serialize(mathcore.block.int32) make_serialize(mathcore.block.complex) make_serialize(mathcore.block.bool) make_index_function(mathcore.block.float) make_index_function(mathcore.block.double) make_index_function(mathcore.block.int32) make_index_function(mathcore.block.complex) make_index_function(mathcore.block.bool) mathcore.block.float.meta_instance.__newindex = new_index_function mathcore.block.double.meta_instance.__newindex = new_index_function mathcore.block.int32.meta_instance.__newindex = new_index_function mathcore.block.complex.meta_instance.__newindex = new_index_function mathcore.block.bool.meta_instance.__newindex = new_index_function mathcore.block.float.meta_instance.__call = call_function mathcore.block.double.meta_instance.__call = call_function mathcore.block.int32.meta_instance.__call = call_function mathcore.block.complex.meta_instance.__call = call_function mathcore.block.bool.meta_instance.__call = call_function mathcore.block.float.meta_instance.__len = len_function mathcore.block.double.meta_instance.__len = len_function mathcore.block.int32.meta_instance.__len = len_function mathcore.block.complex.meta_instance.__len = len_function mathcore.block.bool.meta_instance.__len = len_function ------------------------------------------------------------------------------ local vector,vector_methods = class("mathcore.vector") mathcore.vector = vector -- global definition local block_to_dtype ={ [mathcore.block.float] = "float", [mathcore.block.double] = "double", [mathcore.block.complex] = "complex", [mathcore.block.int32] = "int32", [mathcore.block.bool] = "bool", [mathcore.block.char] = "char", } vector.constructor = april_doc{ class="method", summary="Constructor of dynamic vector using underlying mathcore.block data", params={ "A mathcore.block instance", }, outputs={ "A dynamic vector instance", }, } .. april_doc{ class="method", summary="Constructor of dynamic vector using underlying mathcore.block data", params={ dtype="Data type: float, double, complex, int32, bool [optional], by default it is float", reserve="Size reserved in the underlying memory block [optional]", size="Initial size of the vector [optional], by default it is 0", }, outputs={ "A dynamic vector instance", }, } .. function(self, params) params = params or {} if type(params) ~= "table" then local block = params self.dtype = block_to_dtype[class.of(block)] self.ctor = class.of(block) self.len = #block self.block = block else local params = get_table_fields({ dtype = { type_match="string", default="float" }, reserve = { type_match="number", default=DEFAULT_SIZE }, size = { type_match="number", default=0 }, }, params) local dtype = params.dtype local reserve = params.reserve local size = params.size self.dtype = dtype self.ctor = assert(mathcore.block[dtype], "Incorrect block type") self.len = size self.block = self.ctor(math.max(reserve, size)) end end vector_methods.resize = function(self, size) self.block = self.ctor(size):copy(self.block) collectgarbage("collect") return self end vector_methods.reserve = function(self, size) if #self.block < size then self:resize(size) end return self end vector_methods.push_back = function(self, value) if self.len == #self.block then self:resize(#self.block * 2) end self.block[self.len] = value self.len = self.len + 1 end -- not guaranteed to return the underlying block, it can be a copy vector_methods.to_block = april_doc{ class="method", summary="Returns a mathcore.block with the data", description="Be careful, this function doesn't guarantee to return a new allocated block", outputs={ "A mathcore.block instance", }, } .. function(self) local block = self.block if self.len < #block then block = self.ctor(self.len):copy(block) end return block end class.declare_functional_index(vector, function(self, key) if type(key) == "number" then return self.block[key-1] end end) class.extend_metamethod(vector, "__newindex", function(self, key, value) if type(key) == "number" then self.block[key-1] = value else rawset(self, key, value) end end) class.extend_metamethod(vector, "__len", function(self) return self.len end) class.extend_metamethod(vector, "__ipairs", function(self) return function(self,i) if i < #self then i=i+1 return i,self[i] end end,self,0 end) class.extend_metamethod(vector, "__tostring", function(self) return tostring(self:to_block()) end) april-ann-0.4.1/packages/basics/mathcore/package.lua000066400000000000000000000020541263004425400223200ustar00rootroot00000000000000package{ name = "mathcore", version = "1.0", depends = { "util", "complex", "aprilio" }, keywords = { }, description = "Math library", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_mathcore.lua.cc" , dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", dest_dir = "build", }, object{ file = "c_src/*.cu", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_mathcore.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/matrix/000077500000000000000000000000001263004425400177235ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/matrix/binding/000077500000000000000000000000001263004425400213355ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/matrix/binding/.gitignore000066400000000000000000000002271263004425400233260ustar00rootroot00000000000000bind_matrix.lua.cc bind_matrix_bool.lua.cc bind_matrix_char.lua.cc bind_matrix_complex_float.lua.cc bind_matrix_double.lua.cc bind_matrix_int32.lua.cc april-ann-0.4.1/packages/basics/matrix/binding/bind_matrix_ext.lua.cc000066400000000000000000000174341263004425400256150ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C extern "C" { #include } #include "ignore_result.h" #include "luabindutil.h" #include "luabindmacros.h" #include "matrix_ext.h" #include "smart_ptr.h" #include "utilMatrixChar.h" #include "utilMatrixComplexF.h" #include "utilMatrixFloat.h" #include "utilMatrixInt32.h" //BIND_END //BIND_HEADER_H #include "bind_matrix.h" #include "bind_matrix_bool.h" #include "bind_matrix_char.h" #include "bind_matrix_complex_float.h" #include "bind_matrix_double.h" #include "bind_matrix_int32.h" //BIND_END //BIND_LUACLASSNAME MatrixFloat matrix //BIND_LUACLASSNAME MatrixBool matrixBool //BIND_LUACLASSNAME MatrixInt32 matrixInt32 //BIND_LUACLASSNAME MatrixComplexF matrixComplex //BIND_LUACLASSNAME MatrixChar matrixChar ////////////////////////////////////////////////////////////////////////////// //BIND_FUNCTION matrix.ext.convolution { MatrixFloat *obj, *kernel, *result; //, *unrolled_kernel, *unrolled_self; AprilUtils::UniquePtr step; int D; LUABIND_CHECK_ARGN(>=, 2); LUABIND_CHECK_ARGN(<=, 3); LUABIND_GET_PARAMETER(1, MatrixFloat, obj); LUABIND_CHECK_PARAMETER(2, table); LUABIND_GET_TABLE_PARAMETER(2, D, int, D); LUABIND_GET_TABLE_PARAMETER(2, kernel, MatrixFloat, kernel); /* LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, unrolled_kernel, MatrixFloat, unrolled_kernel, 0); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, unrolled_self, MatrixFloat, unrolled_self, 0); */ LUABIND_GET_OPTIONAL_PARAMETER(3, MatrixFloat, result, 0); lua_getfield(L, 2, "step"); if (!lua_isnil(L, -1)) { step = new int[D]; int len; LUABIND_TABLE_GETN(-1, len); if (len != D) { LUABIND_FERROR2("Incorrect length of step table, found %d, expected %d", len, D); } LUABIND_TABLE_TO_VECTOR(-1, int, step.get(), D); } lua_pop(L, 1); LUABIND_RETURN(MatrixFloat, AprilMath::MatrixExt::Misc:: matConvolution(obj, D, step.get(), kernel, result)); //&unrolled_kernel, &unrolled_self); /*LUABIND_RETURN(MatrixFloat, unrolled_kernel); LUABIND_RETURN(MatrixFloat, unrolled_self);*/ } //BIND_END //BIND_FUNCTION matrix.ext.real_fftwh { MatrixFloat *obj, *dest; int wsize, wadvance; LUABIND_GET_PARAMETER(1, MatrixFloat, obj); LUABIND_GET_OPTIONAL_PARAMETER(2, int, wsize, obj->size()); LUABIND_GET_OPTIONAL_PARAMETER(3, int, wadvance, wsize); LUABIND_GET_OPTIONAL_PARAMETER(4, MatrixFloat, dest, 0); LUABIND_RETURN(MatrixFloat, AprilMath::MatrixExt::Misc:: matRealFFTwithHamming(obj, wsize, wadvance, dest)); } //BIND_END ////////////////////////////////////////////////////////////////////////////// //BIND_CLASS_METHOD MatrixFloat fromPNM //DOC_BEGIN // matrix *fromPNM(string pnm_image) /// constructor con un argumento que es una cadena con una imagen en /// formato de netpbm P5 o P6 (binario PGM o PNM) ///@param pnm_image String que contiene la imagen. //DOC_END // TODO: poder forzar niveles de gris o color, poder leer PBM { LUABIND_CHECK_ARGN(>=, 1); LUABIND_CHECK_ARGN(<=, 2); LUABIND_CHECK_PARAMETER(1, string); bool forcecolor=false,forcegray=false; AprilUtils::constString cs,csopt; LUABIND_GET_PARAMETER(1,constString,cs); LUABIND_GET_OPTIONAL_PARAMETER(2,constString,csopt, AprilUtils::constString()); if (csopt == "color") forcecolor = true; if (csopt == "gray") forcegray = true; MatrixFloat *obj; if ((obj = readMatrixFloatPNM(cs,forcecolor,forcegray))== 0) LUABIND_ERROR("bad format"); else LUABIND_RETURN(MatrixFloat,obj); } //BIND_END //BIND_CLASS_METHOD MatrixFloat fromHEX //DOC_BEGIN // matrix *fromHEX(width, height, string hex_image) /// constructor con 3 argumentos que es una cadena con una imagen en /// escala de grises, 2 caracteres hexadecimales por pixel ///@param width ///@param height ///@param hex_image //DOC_END { LUABIND_CHECK_ARGN(==, 3); LUABIND_CHECK_PARAMETER(1, int); LUABIND_CHECK_PARAMETER(1, int); LUABIND_CHECK_PARAMETER(1, string); int width,height; AprilUtils::constString cs; LUABIND_GET_PARAMETER(1,int,width); LUABIND_GET_PARAMETER(2,int,height); LUABIND_GET_PARAMETER(3,constString,cs); MatrixFloat *obj; obj = readMatrixFloatHEX(width,height,cs); LUABIND_RETURN(MatrixFloat,obj); } //BIND_END //BIND_METHOD MatrixFloat toHEX //DOC_BEGIN // string toHEX() //DOC_END { char *buffer; int width, height; int longitud = saveMatrixFloatHEX(obj,&buffer, &width, &height); if (!buffer) { LUABIND_ERROR("bad format"); } LUABIND_RETURN(int, width); LUABIND_RETURN(int, height); lua_pushlstring(L,buffer,longitud); delete[] buffer; LUABIND_RETURN_FROM_STACK(-1); } //BIND_END //BIND_METHOD MatrixFloat toPNM //DOC_BEGIN // string toPNM() /// Devuelve una cadena correspondiente a un fichero PNM (P5 o P6). La /// matriz debe ser de dimension 2 o, si es de dimension 3, la tercera /// dimension debe tener 3 componentes correspondientes respectivamente /// a los colores RGB. El 0 se interpreta como negro, el 1 como blanco /// y saturan (es decir, un -1 es como 0 y un 5 es como 1). //DOC_END { LUABIND_CHECK_ARGN(==, 0); char *buffer; int longitud = saveMatrixFloatPNM(obj,&buffer); if (!buffer) LUABIND_ERROR("bad format"); lua_pushlstring(L,buffer,longitud); delete[] buffer; LUABIND_RETURN_FROM_STACK(-1); } //BIND_END ////////////////////////////////////////////////////////////////////////////// //BIND_METHOD MatrixBool count_ones { int count=AprilMath::MatrixExt::Misc::matCountEq(obj, true); LUABIND_RETURN(int, count); } //BIND_END //BIND_METHOD MatrixBool count_zeros { int count=AprilMath::MatrixExt::Misc::matCountEq(obj, false); LUABIND_RETURN(int, count); } //BIND_END //BIND_METHOD MatrixBool any { int count=AprilMath::MatrixExt::Misc::matCountEq(obj, true); bool result=(count != 0); LUABIND_RETURN(boolean, result); } //BIND_END //BIND_METHOD MatrixBool all { int count=AprilMath::MatrixExt::Misc::matCountEq(obj, false); bool result=(count == 0); LUABIND_RETURN(boolean, result); } //BIND_END //BIND_METHOD MatrixBool complement { for (MatrixBool::iterator it(obj->begin()); it != obj->end(); ++it) { if (*it) *it = false; else *it = true; } LUABIND_RETURN(MatrixBool, obj); } //BIND_END ////////////////////////////////////////////////////////////////////////////// //BIND_METHOD MatrixComplexF to_float { LUABIND_RETURN(MatrixFloat, convertFromMatrixComplexFToMatrixFloat(obj)); } //BIND_END //BIND_METHOD MatrixComplexF conj { applyConjugateInPlace(obj); LUABIND_RETURN(MatrixComplexF, obj); } //BIND_END //BIND_METHOD MatrixComplexF real { LUABIND_RETURN(MatrixFloat, realPartFromMatrixComplexFToMatrixFloat(obj)); } //BIND_END //BIND_METHOD MatrixComplexF img { LUABIND_RETURN(MatrixFloat, imgPartFromMatrixComplexFToMatrixFloat(obj)); } //BIND_END //BIND_METHOD MatrixComplexF abs { LUABIND_RETURN(MatrixFloat, absFromMatrixComplexFToMatrixFloat(obj)); } //BIND_END //BIND_METHOD MatrixComplexF angle { LUABIND_RETURN(MatrixFloat, angleFromMatrixComplexFToMatrixFloat(obj)); } //BIND_END april-ann-0.4.1/packages/basics/matrix/binding/bind_matrix_options.lua.cc000066400000000000000000000026711263004425400265050ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "matrix.h" //BIND_END //BIND_STRING_CONSTANT matrix.options.tab Basics::MatrixIO::TAB_OPTION //BIND_STRING_CONSTANT matrix.options.ascii Basics::MatrixIO::ASCII_OPTION //BIND_STRING_CONSTANT matrix.options.delim Basics::MatrixIO::DELIM_OPTION //BIND_STRING_CONSTANT matrix.options.empty Basics::MatrixIO::EMPTY_OPTION //BIND_STRING_CONSTANT matrix.options.default Basics::MatrixIO::DEFAULT_OPTION //BIND_STRING_CONSTANT matrix.options.ncols Basics::MatrixIO::NCOLS_OPTION //BIND_STRING_CONSTANT matrix.options.nrows Basics::MatrixIO::NROWS_OPTION //BIND_STRING_CONSTANT matrix.options.map Basics::MatrixIO::MAP_OPTION april-ann-0.4.1/packages/basics/matrix/binding/bind_referenced_vector.lua.cc000066400000000000000000000114101263004425400271010ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_H #include "referenced_vector.h" #include "matrixFloat.h" #include "utilLua.h" #include "bind_matrix.h" using AprilUtils::ReferencedVectorFloat; using AprilUtils::ReferencedVectorUint; //BIND_END //BIND_LUACLASSNAME ReferencedVectorFloat util.vector_float //BIND_CPP_CLASS ReferencedVectorFloat //BIND_CONSTRUCTOR ReferencedVectorFloat { int initial_size; LUABIND_CHECK_ARGN(<=, 1); LUABIND_GET_OPTIONAL_PARAMETER(1,int,initial_size,1024); ReferencedVectorFloat *obj = new ReferencedVectorFloat(); obj->reserve(initial_size); LUABIND_RETURN(ReferencedVectorFloat, obj); } //BIND_END //BIND_METHOD ReferencedVectorFloat size { LUABIND_CHECK_ARGN(==, 0); LUABIND_RETURN(int, (int)obj->size()); } //BIND_END //BIND_METHOD ReferencedVectorFloat get { LUABIND_CHECK_ARGN(==, 1); uint idx; LUABIND_GET_PARAMETER(1, uint, idx); if (idx > obj->size()) LUABIND_FERROR2("Incorrect index, found %d, maximum size %d\n", idx, obj->size()); LUABIND_RETURN(float, (*obj)[idx-1]); } //BIND_END //BIND_METHOD ReferencedVectorFloat set { LUABIND_CHECK_ARGN(==, 2); uint idx; float value; LUABIND_GET_PARAMETER(1, uint, idx); LUABIND_GET_PARAMETER(2, float, value); if (idx > obj->size()) LUABIND_FERROR2("Incorrect index, found %d, maximum size %d\n", idx, obj->size()); (*obj)[idx-1] = value; } //BIND_END //BIND_METHOD ReferencedVectorFloat push_back { LUABIND_CHECK_ARGN(==, 1); float value; LUABIND_GET_PARAMETER(1, float, value); obj->push_back(value); } //BIND_END //BIND_METHOD ReferencedVectorFloat toMatrix { // LUABIND_CHECK_ARGN(<=, 1); // bool reuse_vector; // LUABIND_GET_OPTIONAL_PARAMETER(1,bool,reuse_vector,true); int dim = (int)obj->size(); MatrixFloat *mat; // if (reuse_vector) { // float *internal_data = obj->release_internal_vector(); // mat = new MatrixFloat(1,&dim,internal_data); // } else { mat = new MatrixFloat(1,&dim); MatrixFloat::iterator it(mat->begin()); for (int i=0; ireserve(initial_size); LUABIND_RETURN(ReferencedVectorUint, obj); } //BIND_END //BIND_METHOD ReferencedVectorUint size { LUABIND_CHECK_ARGN(==, 0); LUABIND_RETURN(int, (int)obj->size()); } //BIND_END //BIND_METHOD ReferencedVectorUint get { LUABIND_CHECK_ARGN(==, 1); uint idx; LUABIND_GET_PARAMETER(1, uint, idx); if (idx > obj->size()) LUABIND_FERROR2("Incorrect index, found %d, maximum size %d\n", idx, obj->size()); LUABIND_RETURN(uint, (*obj)[idx-1]); } //BIND_END //BIND_METHOD ReferencedVectorUint set { LUABIND_CHECK_ARGN(==, 2); uint idx, value; LUABIND_GET_PARAMETER(1, uint, idx); LUABIND_GET_PARAMETER(2, uint, value); if (idx > obj->size()) LUABIND_FERROR2("Incorrect index, found %d, maximum size %d\n", idx, obj->size()); (*obj)[idx-1] = value; } //BIND_END //BIND_METHOD ReferencedVectorUint push_back { LUABIND_CHECK_ARGN(==, 1); double value; LUABIND_GET_PARAMETER(1, double, value); obj->push_back(value); } //BIND_END //BIND_METHOD ReferencedVectorUint toMatrix { // este metodo no hace falta, lo pongo para testear LUABIND_CHECK_ARGN(==, 0); int dim = (int)obj->size(); MatrixFloat *mat = new MatrixFloat(1,&dim); MatrixFloat::iterator it(mat->begin()); for (int i=0; i // para isfinite #include "april_assert.h" #include "bind_april_io.h" #include "bind_matrix.h" #include "bind_matrix_int32.h" #include "bind_mathcore.h" #include "cmath_overloads.h" #include "luabindmacros.h" // for lua_pushfloat and lua_pushint #include "luabindutil.h" // for lua_pushfloat and lua_pushint #include "matrix_ext.h" using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Boolean; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilMath::MatrixExt::Misc; using namespace AprilMath::MatrixExt::LAPACK; using namespace AprilMath::MatrixExt::Operations; using namespace AprilMath::MatrixExt::Reductions; IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(SparseMatrixFloat); namespace Basics { int sparseMatrixFloatIteratorFunction(lua_State *L) { SparseMatrixFloatIterator *obj = lua_toSparseMatrixFloatIterator(L,1); if (obj->it == obj->m->end()) { lua_pushnil(L); return 1; } int c0=0,c1=0; obj->it.getCoords(c0,c1); lua_pushfloat(L,*(obj->it)); lua_pushint(L,c0+1); lua_pushint(L,c1+1); ++(obj->it); return 3; } } //BIND_END //BIND_HEADER_H #include // para isfinite #include "bind_april_io.h" #include "referenced.h" #include "sparse_matrixFloat.h" #include "utilLua.h" namespace Basics { class SparseMatrixFloatIterator : public Referenced { public: SparseMatrixFloat *m; SparseMatrixFloat::iterator it; // SparseMatrixFloatIterator(SparseMatrixFloat *m) : m(m), it(m->begin()) { IncRef(m); } virtual ~SparseMatrixFloatIterator() { DecRef(m); } }; #define MAKE_READ_SPARSE_MATRIX_LUA_METHOD(MatrixType, Type) do { \ MatrixType *obj = readSparse(L); \ if (obj == 0) { \ luaL_error(L, "Error happens reading from file stream"); \ } \ else { \ lua_push##MatrixType(L, obj); \ } \ } while(false) template SparseMatrix *readSparse(lua_State *L) { AprilIO::StreamInterface *stream = lua_toAuxStreamInterface(L,1); AprilUtils::SharedPtr ptr(stream); if (stream == 0) { luaL_error(L, "Needs a stream as 1st argument"); return 0; } AprilUtils::LuaTable options(L,2); return SparseMatrix::read(ptr.get(), options); } } // namespace Basics using namespace Basics; //BIND_END //BIND_LUACLASSNAME SparseMatrixFloatIterator matrix.sparse.iterator //BIND_CPP_CLASS SparseMatrixFloatIterator //BIND_CONSTRUCTOR SparseMatrixFloatIterator { LUABIND_ERROR("Use iterate() method in matrix.sparse object"); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME SparseMatrixFloat matrix.sparse //BIND_CPP_CLASS SparseMatrixFloat //BIND_LUACLASSNAME Serializable aprilio.serializable //BIND_SUBCLASS_OF SparseMatrixFloat Serializable //BIND_CONSTRUCTOR SparseMatrixFloat { if (lua_isMatrixFloat(L,1)) { float near_zero; MatrixFloat *m; LUABIND_GET_PARAMETER(1, MatrixFloat, m); LUABIND_GET_OPTIONAL_PARAMETER(2, float, near_zero, NEAR_ZERO); obj = SparseMatrixFloat::fromDenseMatrix(m, CSR_FORMAT, near_zero); } else { int rows,cols; FloatGPUMirroredMemoryBlock *values; Int32GPUMirroredMemoryBlock *indices; Int32GPUMirroredMemoryBlock *first_index; bool sort; LUABIND_GET_PARAMETER(1, int, rows); if (lua_isFloatGPUMirroredMemoryBlock(L,2)) { cols = rows; rows = 1; LUABIND_GET_PARAMETER(2, FloatGPUMirroredMemoryBlock, values); LUABIND_GET_PARAMETER(3, Int32GPUMirroredMemoryBlock, indices); LUABIND_GET_OPTIONAL_PARAMETER(4, Int32GPUMirroredMemoryBlock, first_index, 0); LUABIND_GET_OPTIONAL_PARAMETER(5, boolean, sort, false); } else { LUABIND_GET_PARAMETER(2, int, cols); LUABIND_GET_PARAMETER(3, FloatGPUMirroredMemoryBlock, values); LUABIND_GET_PARAMETER(4, Int32GPUMirroredMemoryBlock, indices); LUABIND_GET_OPTIONAL_PARAMETER(5, Int32GPUMirroredMemoryBlock, first_index, 0); LUABIND_GET_OPTIONAL_PARAMETER(6, boolean, sort, false); } obj = new SparseMatrixFloat(rows, cols, values, indices, first_index, CSR_FORMAT, sort); } LUABIND_RETURN(SparseMatrixFloat,obj); } //BIND_END //BIND_CLASS_METHOD SparseMatrixFloat csc { SparseMatrixFloat *obj; if (lua_isMatrixFloat(L,1)) { MatrixFloat *m; float near_zero; LUABIND_GET_PARAMETER(1, MatrixFloat, m); LUABIND_GET_OPTIONAL_PARAMETER(2, float, near_zero, NEAR_ZERO); obj = SparseMatrixFloat::fromDenseMatrix(m, CSC_FORMAT, near_zero); } else { int rows,cols; FloatGPUMirroredMemoryBlock *values; Int32GPUMirroredMemoryBlock *indices; Int32GPUMirroredMemoryBlock *first_index; bool sort; LUABIND_GET_PARAMETER(1, int, rows); if (lua_isFloatGPUMirroredMemoryBlock(L,2)) { cols = 1; LUABIND_GET_PARAMETER(2, FloatGPUMirroredMemoryBlock, values); LUABIND_GET_PARAMETER(3, Int32GPUMirroredMemoryBlock, indices); LUABIND_GET_OPTIONAL_PARAMETER(4, Int32GPUMirroredMemoryBlock, first_index, 0); LUABIND_GET_OPTIONAL_PARAMETER(5, boolean, sort, false); } else { LUABIND_GET_PARAMETER(2, int, cols); LUABIND_GET_PARAMETER(3, FloatGPUMirroredMemoryBlock, values); LUABIND_GET_PARAMETER(4, Int32GPUMirroredMemoryBlock, indices); LUABIND_GET_OPTIONAL_PARAMETER(5, Int32GPUMirroredMemoryBlock, first_index, 0); LUABIND_GET_OPTIONAL_PARAMETER(6, boolean, sort, false); } obj = new SparseMatrixFloat(rows, cols, values, indices, first_index, CSC_FORMAT, sort); } LUABIND_RETURN(SparseMatrixFloat,obj); } //BIND_END //BIND_METHOD SparseMatrixFloat size { LUABIND_RETURN(int, obj->size()); } //BIND_END //BIND_METHOD SparseMatrixFloat non_zero_size { LUABIND_RETURN(int, obj->nonZeroSize()); } //BIND_END //BIND_METHOD SparseMatrixFloat get_reference_string { char buff[128]; sprintf(buff,"%p data= %p %p %p", (void*)obj, (void*)obj->getRawValuesAccess(), (void*)obj->getRawIndicesAccess(), (void*)obj->getRawFirstIndexAccess()); LUABIND_RETURN(string, buff); } //BIND_END //BIND_CLASS_METHOD SparseMatrixFloat fromMMap { LUABIND_CHECK_ARGN(>=, 1); LUABIND_CHECK_ARGN(<=, 3); LUABIND_CHECK_PARAMETER(1, string); const char *filename; bool write, shared; LUABIND_GET_PARAMETER(1,string,filename); LUABIND_GET_OPTIONAL_PARAMETER(2,bool,write,true); LUABIND_GET_OPTIONAL_PARAMETER(3,bool,shared,true); AprilUtils::MMappedDataReader *mmapped_data; mmapped_data = new AprilUtils::MMappedDataReader(filename,write,shared); IncRef(mmapped_data); SparseMatrixFloat *obj = SparseMatrixFloat::fromMMappedDataReader(mmapped_data); DecRef(mmapped_data); LUABIND_RETURN(SparseMatrixFloat,obj); } //BIND_END //BIND_METHOD SparseMatrixFloat toMMap { LUABIND_CHECK_ARGN(==, 1); const char *filename; LUABIND_GET_PARAMETER(1, string, filename); AprilUtils::MMappedDataWriter *mmapped_data; mmapped_data = new AprilUtils::MMappedDataWriter(filename); IncRef(mmapped_data); obj->toMMappedDataWriter(mmapped_data); DecRef(mmapped_data); } //BIND_END //BIND_METHOD SparseMatrixFloat get { int row,col; LUABIND_GET_PARAMETER(1, int, row); LUABIND_GET_PARAMETER(2, int, col); float v = (*obj)(row-1,col-1); LUABIND_RETURN(float, v); } //BIND_END //BIND_METHOD SparseMatrixFloat raw_get { int idx; LUABIND_GET_PARAMETER(1, int, idx); if (idx < 1 || idx > obj->nonZeroSize()) LUABIND_FERROR2("Index out-of-bounds [%d,%d]", 1, obj->nonZeroSize()); SparseMatrixFloat::const_iterator it(obj->iteratorAtRawIndex(idx-1)); LUABIND_RETURN(float, *it); int c0=0,c1=0; it.getCoords(c0,c1); LUABIND_RETURN(float, *it); LUABIND_RETURN(int, c0+1); LUABIND_RETURN(int, c1+1); } //BIND_END //BIND_METHOD SparseMatrixFloat raw_set { float value; int idx; LUABIND_GET_PARAMETER(1, int, idx); LUABIND_GET_PARAMETER(2, float, value); if (idx < 1 || idx > obj->nonZeroSize()) LUABIND_FERROR2("Index out-of-bounds [%d,%d]", 1, obj->nonZeroSize()); (*obj)[idx] = value; LUABIND_RETURN(SparseMatrixFloat, obj); } //BIND_END //BIND_METHOD SparseMatrixFloat iterate { LUABIND_CHECK_ARGN(==, 0); LUABIND_RETURN(cfunction,sparseMatrixFloatIteratorFunction); LUABIND_RETURN(SparseMatrixFloatIterator,new SparseMatrixFloatIterator(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat fill { LUABIND_CHECK_ARGN(==, 1); float value; if (lua_isSparseMatrixFloat(L, 1)) { SparseMatrixFloat *aux; LUABIND_GET_PARAMETER(1,SparseMatrixFloat,aux); for (int i=0; igetNumDim(); ++i) if (aux->getDimSize(i) != 1) LUABIND_ERROR("Needs a float or a matrix with only one element\n"); value = *(aux->begin()); } else { LUABIND_CHECK_PARAMETER(1, float); LUABIND_GET_PARAMETER(1,float,value); } LUABIND_RETURN(SparseMatrixFloat, matFill(obj,value)); } //BIND_END //BIND_METHOD SparseMatrixFloat zeros //DOC_BEGIN // void zeros(float value) /// Permite poner todos los valores de la matriz a un mismo valor. //DOC_END { LUABIND_RETURN(SparseMatrixFloat, matZeros(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat ones //DOC_BEGIN // void onex(float value) /// Permite poner todos los valores de la matriz a un mismo valor. //DOC_END { LUABIND_RETURN(SparseMatrixFloat, matOnes(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat get_use_cuda { LUABIND_RETURN(bool, obj->getCudaFlag()); } //BIND_END //BIND_METHOD SparseMatrixFloat to_dense { LUABIND_RETURN(MatrixFloat, obj->toDense()); } //BIND_END //BIND_METHOD SparseMatrixFloat set_use_cuda { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, bool); bool v; LUABIND_GET_PARAMETER(1,bool, v); obj->setUseCuda(v); LUABIND_RETURN(SparseMatrixFloat, obj); } //BIND_END //BIND_METHOD SparseMatrixFloat get_sparse_format { if (obj->getSparseFormat() == CSR_FORMAT) LUABIND_RETURN(string, "csr"); else LUABIND_RETURN(string, "csc"); } //BIND_END //BIND_METHOD SparseMatrixFloat dim { LUABIND_CHECK_ARGN(>=, 0); LUABIND_CHECK_ARGN(<=, 1); int pos; const int *d=obj->getDimPtr(); LUABIND_GET_OPTIONAL_PARAMETER(1, int, pos, -1); if (pos < 1) { LUABIND_VECTOR_TO_NEW_TABLE(int, d, obj->getNumDim()); LUABIND_RETURN_FROM_STACK(-1); } else LUABIND_RETURN(int, d[pos-1]); } //BIND_END //BIND_METHOD SparseMatrixFloat slice { LUABIND_CHECK_ARGN(>=,2); LUABIND_CHECK_ARGN(<=,3); LUABIND_CHECK_PARAMETER(1, table); LUABIND_CHECK_PARAMETER(2, table); int *coords, *sizes, coords_len, sizes_len; bool clone; LUABIND_TABLE_GETN(1, coords_len); LUABIND_TABLE_GETN(2, sizes_len); if (coords_len != sizes_len || coords_len != obj->getNumDim()) LUABIND_FERROR3("Incorrect number of dimensions, expected %d, " "found %d and %d\n", obj->getNumDim(), coords_len, sizes_len); coords = new int[coords_len]; sizes = new int[sizes_len]; LUABIND_TABLE_TO_VECTOR_SUB1(1, int, coords, coords_len); LUABIND_TABLE_TO_VECTOR(2, int, sizes, sizes_len); LUABIND_GET_OPTIONAL_PARAMETER(3, bool, clone, false); for (int i=0; i obj->getDimSize(i)) LUABIND_FERROR1("Incorrect size or coord at position %d\n", i+1); SparseMatrixFloat *obj2 = new SparseMatrixFloat(obj, coords, sizes, clone); LUABIND_RETURN(SparseMatrixFloat, obj2); delete[] coords; delete[] sizes; } //BIND_END //BIND_METHOD SparseMatrixFloat clone { LUABIND_CHECK_ARGN(>=, 0); LUABIND_CHECK_ARGN(<=, 1); int argn; argn = lua_gettop(L); // number of arguments SparseMatrixFloat *obj2; if (argn == 0) obj2 = obj->clone(); else { const char *sparse; LUABIND_GET_PARAMETER(1, string, sparse); SPARSE_FORMAT format = CSC_FORMAT; if (strcmp(sparse, "csr") == 0) format = CSR_FORMAT; else if (strcmp(sparse, "csc") != 0) LUABIND_FERROR1("Incorrect sparse format string %s", sparse); obj2 = obj->clone(format); } LUABIND_RETURN(SparseMatrixFloat,obj2); } //BIND_END //BIND_METHOD SparseMatrixFloat transpose { LUABIND_RETURN(SparseMatrixFloat, obj->transpose()); } //BIND_END //BIND_METHOD SparseMatrixFloat isfinite { LUABIND_CHECK_ARGN(==, 0); bool resul=true; for (SparseMatrixFloat::iterator it(obj->begin()); resul && it!=obj->end(); ++it) //if (!isfinite(obj->data[i])) resul = 0; if ((*it) - (*it) != 0.0f) resul = false; LUABIND_RETURN(boolean,resul); } //BIND_END //BIND_CLASS_METHOD SparseMatrixFloat diag { SparseMatrixFloat *obj; int argn = lua_gettop(L); // number of arguments if (lua_isMatrixFloat(L,1)) { MatrixFloat *m; LUABIND_GET_PARAMETER(1, MatrixFloat, m); const char *sparse; LUABIND_GET_OPTIONAL_PARAMETER(2, string, sparse, "csr"); SPARSE_FORMAT format = CSR_FORMAT; if (strcmp(sparse, "csc") == 0) format = CSC_FORMAT; else if (strcmp(sparse, "csr") != 0) LUABIND_FERROR1("Incorrect sparse format string %s", sparse); obj = SparseMatrixFloat::diag(m,format); } else if (lua_isFloatGPUMirroredMemoryBlock(L,1)) { FloatGPUMirroredMemoryBlock *block; LUABIND_GET_PARAMETER(1, FloatGPUMirroredMemoryBlock, block); const char *sparse; LUABIND_GET_OPTIONAL_PARAMETER(2, string, sparse, "csr"); SPARSE_FORMAT format = CSR_FORMAT; if (strcmp(sparse, "csc") == 0) format = CSC_FORMAT; else if (strcmp(sparse, "csr") != 0) LUABIND_FERROR1("Incorrect sparse format string %s", sparse); obj = SparseMatrixFloat::diag(block,format); } else if (lua_istable(L,1)) { int N; LUABIND_TABLE_GETN(1, N); FloatGPUMirroredMemoryBlock *block = new FloatGPUMirroredMemoryBlock(N); const char *sparse; LUABIND_GET_OPTIONAL_PARAMETER(2, string, sparse, "csr"); SPARSE_FORMAT format = CSR_FORMAT; if (strcmp(sparse, "csc") == 0) format = CSC_FORMAT; else if (strcmp(sparse, "csr") != 0) LUABIND_FERROR1("Incorrect sparse format string %s", sparse); float *mem = block->getPPALForWrite(); lua_pushnil(L); int i=0; while(lua_next(L, 1) != 0) { mem[i++] = lua_tofloat(L, -1); lua_pop(L, 1); } obj = SparseMatrixFloat::diag(block,format); } else { int N; float v; LUABIND_GET_PARAMETER(1, int, N); LUABIND_GET_PARAMETER(2, float, v); const char *sparse; LUABIND_GET_OPTIONAL_PARAMETER(3, string, sparse, "csr"); SPARSE_FORMAT format = CSR_FORMAT; if (strcmp(sparse, "csc") == 0) format = CSC_FORMAT; else if (strcmp(sparse, "csr") != 0) LUABIND_FERROR1("Incorrect sparse format string %s", sparse); obj = SparseMatrixFloat::diag(N,v,format); } LUABIND_RETURN(SparseMatrixFloat, obj); } //BIND_END //BIND_METHOD SparseMatrixFloat min { LUABIND_CHECK_ARGN(>=,0); LUABIND_CHECK_ARGN(<=,3); int argn = lua_gettop(L); if (argn > 0) { int dim; MatrixFloat *dest; MatrixInt32 *argmin; LUABIND_GET_PARAMETER(1, int, dim); LUABIND_GET_OPTIONAL_PARAMETER(2, MatrixFloat, dest, 0); LUABIND_GET_OPTIONAL_PARAMETER(3, MatrixInt32, argmin, 0); int *aux = 0; if (argmin == 0) { aux = new int[obj->getNumDim()]; for (int i=0; igetNumDim(); ++i) aux[i] = obj->getDimSize(i); aux[dim-1] = 1; argmin = new MatrixInt32(obj->getNumDim(), aux); } IncRef(argmin); if (dim < 1 || dim > obj->getNumDim()) LUABIND_FERROR2("Incorrect dimension, found %d, expect in [1,%d]", dim, obj->getNumDim()); LUABIND_RETURN(MatrixFloat, matMin(obj, dim-1, dest, argmin)); LUABIND_RETURN(MatrixInt32, argmin); DecRef(argmin); delete[] aux; } else { int c0, c1; LUABIND_RETURN(float, matMin(obj, c0, c1)); LUABIND_RETURN(int, c0+1); LUABIND_RETURN(int, c1+1); } } //BIND_END //BIND_METHOD SparseMatrixFloat max { LUABIND_CHECK_ARGN(>=,0); LUABIND_CHECK_ARGN(<=,3); int argn = lua_gettop(L); if (argn > 0) { int dim; MatrixFloat *dest; MatrixInt32 *argmax; LUABIND_GET_PARAMETER(1, int, dim); LUABIND_GET_OPTIONAL_PARAMETER(2, MatrixFloat, dest, 0); LUABIND_GET_OPTIONAL_PARAMETER(3, MatrixInt32, argmax, 0); int *aux = 0; if (argmax == 0) { aux = new int[obj->getNumDim()]; for (int i=0; igetNumDim(); ++i) aux[i] = obj->getDimSize(i); aux[dim-1] = 1; argmax = new MatrixInt32(obj->getNumDim(), aux); } IncRef(argmax); if (dim < 1 || dim > obj->getNumDim()) LUABIND_FERROR2("Incorrect dimension, found %d, expect in [1,%d]", dim, obj->getNumDim()); LUABIND_RETURN(MatrixFloat, matMax(obj, dim-1, dest, argmax)); LUABIND_RETURN(MatrixInt32, argmax); DecRef(argmax); delete[] aux; } else { int c0, c1; LUABIND_RETURN(float, matMax(obj, c0, c1)); LUABIND_RETURN(int, c0+1); LUABIND_RETURN(int, c1+1); } } //BIND_END //BIND_METHOD SparseMatrixFloat equals { SparseMatrixFloat *other; float epsilon; LUABIND_GET_PARAMETER(1, SparseMatrixFloat, other); LUABIND_GET_OPTIONAL_PARAMETER(2, float, epsilon, 1e-04f); LUABIND_RETURN(boolean, matEquals(obj, other, epsilon)); } //BIND_END //BIND_METHOD SparseMatrixFloat sqrt { LUABIND_RETURN(SparseMatrixFloat, matSqrt(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat pow { float value; LUABIND_CHECK_ARGN(==,1); LUABIND_GET_PARAMETER(1, float, value); LUABIND_RETURN(SparseMatrixFloat, matPow(obj,value)); } //BIND_END //BIND_METHOD SparseMatrixFloat tan { LUABIND_RETURN(SparseMatrixFloat, matTan(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat tanh { LUABIND_RETURN(SparseMatrixFloat, matTanh(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat atan { LUABIND_RETURN(SparseMatrixFloat, matAtan(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat atanh { LUABIND_RETURN(SparseMatrixFloat, matAtanh(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat sin { LUABIND_RETURN(SparseMatrixFloat, matSin(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat sinh { LUABIND_RETURN(SparseMatrixFloat, matSinh(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat asin { LUABIND_RETURN(SparseMatrixFloat, matAsin(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat asinh { LUABIND_RETURN(SparseMatrixFloat, matAsinh(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat abs { LUABIND_RETURN(SparseMatrixFloat, matAbs(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat sign { LUABIND_RETURN(SparseMatrixFloat, matSign(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat sum { LUABIND_CHECK_ARGN(>=, 0); LUABIND_CHECK_ARGN(<=, 2); int argn = lua_gettop(L); // number of arguments if (argn >= 1 && !lua_isnil(L,1)) { int dim; MatrixFloat *dest; LUABIND_GET_PARAMETER(1, int, dim); LUABIND_GET_OPTIONAL_PARAMETER(2, MatrixFloat, dest, 0); if (dim < 1 || dim > obj->getNumDim()) LUABIND_FERROR2("Incorrect dimension, found %d, expect in [1,%d]", dim, obj->getNumDim()); LUABIND_RETURN(MatrixFloat, matSum(obj, dim-1, dest)); } else LUABIND_RETURN(float, matSum(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat copy { int argn; LUABIND_CHECK_ARGN(==, 1); SparseMatrixFloat *mat; LUABIND_GET_PARAMETER(1, SparseMatrixFloat, mat); LUABIND_RETURN(SparseMatrixFloat, matCopy(obj, mat)); } //BIND_END //BIND_METHOD SparseMatrixFloat scal { LUABIND_CHECK_ARGN(==, 1); float value; LUABIND_GET_PARAMETER(1, float, value); LUABIND_RETURN(SparseMatrixFloat, matScal(obj, value)); } //BIND_END //BIND_METHOD SparseMatrixFloat div { LUABIND_CHECK_ARGN(==, 1); float value; LUABIND_GET_PARAMETER(1, float, value); LUABIND_RETURN(SparseMatrixFloat, matDiv(obj, value)); } //BIND_END //BIND_METHOD SparseMatrixFloat norm2 { LUABIND_RETURN(float, matNorm2(obj)); } //BIND_END //BIND_METHOD SparseMatrixFloat get_shared_count { LUABIND_RETURN(uint, obj->getSharedCount()); } //BIND_END //BIND_METHOD SparseMatrixFloat reset_shared_count { obj->resetSharedCount(); LUABIND_RETURN(SparseMatrixFloat, obj); } //BIND_END //BIND_METHOD SparseMatrixFloat add_to_shared_count { unsigned int count; LUABIND_GET_PARAMETER(1,uint,count); obj->addToSharedCount(count); } //BIND_END //BIND_METHOD SparseMatrixFloat prune_subnormal_and_check_normal { obj->pruneSubnormalAndCheckNormal(); } //BIND_END //BIND_METHOD SparseMatrixFloat as_vector { LUABIND_RETURN(SparseMatrixFloat, obj->asVector()); } //BIND_END //BIND_METHOD SparseMatrixFloat is_diagonal { LUABIND_RETURN(bool, obj->isDiagonal()); } //BIND_END //// MATRIX SERIALIZATION //// //BIND_CLASS_METHOD SparseMatrixFloat read { MAKE_READ_SPARSE_MATRIX_LUA_METHOD(SparseMatrixFloat, float); LUABIND_INCREASE_NUM_RETURNS(1); } //BIND_END //BIND_METHOD SparseMatrixFloat num_dim { LUABIND_RETURN(int, 2); } //BIND_END //BIND_METHOD SparseMatrixFloat select { LUABIND_ERROR("Not implemented method in sparse matrix instances"); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_METHOD SparseMatrixFloat values { LUABIND_RETURN(FloatGPUMirroredMemoryBlock, obj->getRawValuesAccess()); } //BIND_END //BIND_METHOD SparseMatrixFloat indices { LUABIND_RETURN(Int32GPUMirroredMemoryBlock, obj->getRawIndicesAccess()); } //BIND_END //BIND_METHOD SparseMatrixFloat first_index { LUABIND_RETURN(Int32GPUMirroredMemoryBlock, obj->getRawFirstIndexAccess()); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME DOKBuilderSparseMatrixFloat matrix.sparse.builders.dok //BIND_CPP_CLASS DOKBuilderSparseMatrixFloat //BIND_CONSTRUCTOR DOKBuilderSparseMatrixFloat { LUABIND_RETURN(DOKBuilderSparseMatrixFloat, new DOKBuilderSparseMatrixFloat()); } //BIND_END //BIND_METHOD DOKBuilderSparseMatrixFloat set { unsigned int row, col; float value; LUABIND_GET_PARAMETER(1, uint, row); LUABIND_GET_PARAMETER(2, uint, col); LUABIND_GET_PARAMETER(3, float, value); if (row == 0 || col == 0) LUABIND_ERROR("Indices should be > 0"); obj->insert(row-1, col-1, value); LUABIND_RETURN(DOKBuilderSparseMatrixFloat, obj); } //BIND_END //BIND_METHOD DOKBuilderSparseMatrixFloat build { unsigned int d0, d1; SPARSE_FORMAT format = CSR_FORMAT; const char *sparse; LUABIND_GET_OPTIONAL_PARAMETER(1, uint, d0, 0); LUABIND_GET_OPTIONAL_PARAMETER(2, uint, d1, 0); LUABIND_GET_OPTIONAL_PARAMETER(3, string, sparse, 0); if (sparse != 0) { if (strcmp(sparse, "csc") == 0) { format = CSC_FORMAT; } else if (strcmp(sparse, "csr") != 0) { LUABIND_FERROR1("Incorrect sparse format string %s", sparse); } } LUABIND_RETURN(SparseMatrixFloat, obj->build(d0, d1, format)); } //BIND_END ////////////////////////////////////////////////////////////////////////////// april-ann-0.4.1/packages/basics/matrix/binding/bind_sparse_matrix_complex_float.lua.cc000066400000000000000000000500231263004425400312150ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include // para isfinite #include "april_assert.h" #include "bind_april_io.h" #include "bind_complex.h" #include "bind_matrix.h" #include "bind_matrix_int32.h" #include "bind_matrix_complex_float.h" #include "bind_mathcore.h" #include "cmath_overloads.h" #include "luabindmacros.h" // for lua_pushComplexF and lua_pushint #include "luabindutil.h" // for lua_pushComplexF and lua_pushint #include "matrix_ext.h" using AprilMath::ComplexF; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Boolean; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilMath::MatrixExt::Misc; using namespace AprilMath::MatrixExt::LAPACK; using namespace AprilMath::MatrixExt::Operations; using namespace AprilMath::MatrixExt::Reductions; IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(SparseMatrixComplexF); namespace Basics { int sparseMatrixComplexFIteratorFunction(lua_State *L) { SparseMatrixComplexFIterator *obj = lua_toSparseMatrixComplexFIterator(L,1); if (obj->it == obj->m->end()) { lua_pushnil(L); return 1; } int c0=0,c1=0; obj->it.getCoords(c0,c1); lua_pushComplexF(L,*(obj->it)); lua_pushint(L,c0+1); lua_pushint(L,c1+1); ++(obj->it); return 3; } } //BIND_END //BIND_HEADER_H #include // para isfinite #include "complex_number.h" #include "bind_april_io.h" #include "referenced.h" #include "sparse_matrixComplexF.h" #include "utilLua.h" namespace Basics { class SparseMatrixComplexFIterator : public Referenced { public: SparseMatrixComplexF *m; SparseMatrixComplexF::iterator it; // SparseMatrixComplexFIterator(SparseMatrixComplexF *m) : m(m), it(m->begin()) { IncRef(m); } virtual ~SparseMatrixComplexFIterator() { DecRef(m); } }; #define MAKE_READ_SPARSE_MATRIX_LUA_METHOD(MatrixType, Type) do { \ MatrixType *obj = readSparse(L); \ if (obj == 0) { \ luaL_error(L, "Error happens reading from file stream"); \ } \ else { \ lua_push##MatrixType(L, obj); \ } \ } while(false) template SparseMatrix *readSparse(lua_State *L) { AprilIO::StreamInterface *stream = lua_toAuxStreamInterface(L,1); AprilUtils::SharedPtr ptr(stream); if (stream == 0) { luaL_error(L, "Needs a stream as 1st argument"); return 0; } AprilUtils::LuaTable options(L,2); return SparseMatrix::read(ptr.get(), options); } } // namespace Basics using namespace Basics; //BIND_END //BIND_LUACLASSNAME SparseMatrixComplexFIterator matrixComplex.sparse.iterator //BIND_CPP_CLASS SparseMatrixComplexFIterator //BIND_CONSTRUCTOR SparseMatrixComplexFIterator { LUABIND_ERROR("Use iterate() method in matrixComplex.sparse object"); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME SparseMatrixComplexF matrixComplex.sparse //BIND_CPP_CLASS SparseMatrixComplexF //BIND_LUACLASSNAME Serializable aprilio.serializable //BIND_SUBCLASS_OF SparseMatrixComplexF Serializable //BIND_CONSTRUCTOR SparseMatrixComplexF { if (lua_isMatrixComplexF(L,1)) { ComplexF near_zero; MatrixComplexF *m; LUABIND_GET_PARAMETER(1, MatrixComplexF, m); LUABIND_GET_OPTIONAL_PARAMETER(2, ComplexF, near_zero, NEAR_ZERO); obj = SparseMatrixComplexF::fromDenseMatrix(m, CSR_FORMAT, near_zero); } else { int rows,cols; ComplexFGPUMirroredMemoryBlock *values; Int32GPUMirroredMemoryBlock *indices; Int32GPUMirroredMemoryBlock *first_index; bool sort; LUABIND_GET_PARAMETER(1, int, rows); if (lua_isComplexFGPUMirroredMemoryBlock(L,2)) { cols = rows; rows = 1; LUABIND_GET_PARAMETER(2, ComplexFGPUMirroredMemoryBlock, values); LUABIND_GET_PARAMETER(3, Int32GPUMirroredMemoryBlock, indices); LUABIND_GET_OPTIONAL_PARAMETER(4, Int32GPUMirroredMemoryBlock, first_index, 0); LUABIND_GET_OPTIONAL_PARAMETER(5, boolean, sort, false); } else { LUABIND_GET_PARAMETER(2, int, cols); LUABIND_GET_PARAMETER(3, ComplexFGPUMirroredMemoryBlock, values); LUABIND_GET_PARAMETER(4, Int32GPUMirroredMemoryBlock, indices); LUABIND_GET_OPTIONAL_PARAMETER(5, Int32GPUMirroredMemoryBlock, first_index, 0); LUABIND_GET_OPTIONAL_PARAMETER(6, boolean, sort, false); } obj = new SparseMatrixComplexF(rows, cols, values, indices, first_index, CSR_FORMAT, sort); } LUABIND_RETURN(SparseMatrixComplexF,obj); } //BIND_END //BIND_CLASS_METHOD SparseMatrixComplexF csc { SparseMatrixComplexF *obj; if (lua_isMatrixComplexF(L,1)) { MatrixComplexF *m; ComplexF near_zero; LUABIND_GET_PARAMETER(1, MatrixComplexF, m); LUABIND_GET_OPTIONAL_PARAMETER(2, ComplexF, near_zero, NEAR_ZERO); obj = SparseMatrixComplexF::fromDenseMatrix(m, CSC_FORMAT, near_zero); } else { int rows,cols; ComplexFGPUMirroredMemoryBlock *values; Int32GPUMirroredMemoryBlock *indices; Int32GPUMirroredMemoryBlock *first_index; bool sort; LUABIND_GET_PARAMETER(1, int, rows); if (lua_isComplexFGPUMirroredMemoryBlock(L,2)) { cols = 1; LUABIND_GET_PARAMETER(2, ComplexFGPUMirroredMemoryBlock, values); LUABIND_GET_PARAMETER(3, Int32GPUMirroredMemoryBlock, indices); LUABIND_GET_OPTIONAL_PARAMETER(4, Int32GPUMirroredMemoryBlock, first_index, 0); LUABIND_GET_OPTIONAL_PARAMETER(5, boolean, sort, false); } else { LUABIND_GET_PARAMETER(2, int, cols); LUABIND_GET_PARAMETER(3, ComplexFGPUMirroredMemoryBlock, values); LUABIND_GET_PARAMETER(4, Int32GPUMirroredMemoryBlock, indices); LUABIND_GET_OPTIONAL_PARAMETER(5, Int32GPUMirroredMemoryBlock, first_index, 0); LUABIND_GET_OPTIONAL_PARAMETER(6, boolean, sort, false); } obj = new SparseMatrixComplexF(rows, cols, values, indices, first_index, CSC_FORMAT, sort); } LUABIND_RETURN(SparseMatrixComplexF,obj); } //BIND_END //BIND_METHOD SparseMatrixComplexF size { LUABIND_RETURN(int, obj->size()); } //BIND_END //BIND_METHOD SparseMatrixComplexF non_zero_size { LUABIND_RETURN(int, obj->nonZeroSize()); } //BIND_END //BIND_METHOD SparseMatrixComplexF get_reference_string { char buff[128]; sprintf(buff,"%p data= %p %p %p", (void*)obj, (void*)obj->getRawValuesAccess(), (void*)obj->getRawIndicesAccess(), (void*)obj->getRawFirstIndexAccess()); LUABIND_RETURN(string, buff); } //BIND_END //BIND_CLASS_METHOD SparseMatrixComplexF fromMMap { LUABIND_CHECK_ARGN(>=, 1); LUABIND_CHECK_ARGN(<=, 3); LUABIND_CHECK_PARAMETER(1, string); const char *filename; bool write, shared; LUABIND_GET_PARAMETER(1,string,filename); LUABIND_GET_OPTIONAL_PARAMETER(2,bool,write,true); LUABIND_GET_OPTIONAL_PARAMETER(3,bool,shared,true); AprilUtils::MMappedDataReader *mmapped_data; mmapped_data = new AprilUtils::MMappedDataReader(filename,write,shared); IncRef(mmapped_data); SparseMatrixComplexF *obj = SparseMatrixComplexF::fromMMappedDataReader(mmapped_data); DecRef(mmapped_data); LUABIND_RETURN(SparseMatrixComplexF,obj); } //BIND_END //BIND_METHOD SparseMatrixComplexF toMMap { LUABIND_CHECK_ARGN(==, 1); const char *filename; LUABIND_GET_PARAMETER(1, string, filename); AprilUtils::MMappedDataWriter *mmapped_data; mmapped_data = new AprilUtils::MMappedDataWriter(filename); IncRef(mmapped_data); obj->toMMappedDataWriter(mmapped_data); DecRef(mmapped_data); } //BIND_END //BIND_METHOD SparseMatrixComplexF get { int row,col; LUABIND_GET_PARAMETER(1, int, row); LUABIND_GET_PARAMETER(2, int, col); ComplexF v = (*obj)(row-1,col-1); LUABIND_RETURN(ComplexF, v); } //BIND_END //BIND_METHOD SparseMatrixComplexF raw_get { int idx; LUABIND_GET_PARAMETER(1, int, idx); if (idx < 1 || idx > obj->nonZeroSize()) LUABIND_FERROR2("Index out-of-bounds [%d,%d]", 1, obj->nonZeroSize()); SparseMatrixComplexF::const_iterator it(obj->iteratorAtRawIndex(idx-1)); LUABIND_RETURN(ComplexF, *it); int c0=0,c1=0; it.getCoords(c0,c1); LUABIND_RETURN(ComplexF, *it); LUABIND_RETURN(int, c0+1); LUABIND_RETURN(int, c1+1); } //BIND_END //BIND_METHOD SparseMatrixComplexF raw_set { ComplexF value; int idx; LUABIND_GET_PARAMETER(1, int, idx); LUABIND_GET_PARAMETER(2, ComplexF, value); if (idx < 1 || idx > obj->nonZeroSize()) LUABIND_FERROR2("Index out-of-bounds [%d,%d]", 1, obj->nonZeroSize()); (*obj)[idx] = value; LUABIND_RETURN(SparseMatrixComplexF, obj); } //BIND_END //BIND_METHOD SparseMatrixComplexF iterate { LUABIND_CHECK_ARGN(==, 0); LUABIND_RETURN(cfunction,sparseMatrixComplexFIteratorFunction); LUABIND_RETURN(SparseMatrixComplexFIterator,new SparseMatrixComplexFIterator(obj)); } //BIND_END //BIND_METHOD SparseMatrixComplexF fill { LUABIND_CHECK_ARGN(==, 1); ComplexF value; if (lua_isSparseMatrixComplexF(L, 1)) { SparseMatrixComplexF *aux; LUABIND_GET_PARAMETER(1,SparseMatrixComplexF,aux); for (int i=0; igetNumDim(); ++i) if (aux->getDimSize(i) != 1) LUABIND_ERROR("Needs a ComplexF or a matrix with only one element\n"); value = *(aux->begin()); } else { LUABIND_CHECK_PARAMETER(1, ComplexF); LUABIND_GET_PARAMETER(1,ComplexF,value); } LUABIND_RETURN(SparseMatrixComplexF, matFill(obj,value)); } //BIND_END //BIND_METHOD SparseMatrixComplexF zeros //DOC_BEGIN // void zeros(ComplexF value) /// Permite poner todos los valores de la matriz a un mismo valor. //DOC_END { LUABIND_RETURN(SparseMatrixComplexF, matZeros(obj)); } //BIND_END //BIND_METHOD SparseMatrixComplexF ones //DOC_BEGIN // void onex(ComplexF value) /// Permite poner todos los valores de la matriz a un mismo valor. //DOC_END { LUABIND_RETURN(SparseMatrixComplexF, matOnes(obj)); } //BIND_END //BIND_METHOD SparseMatrixComplexF get_use_cuda { LUABIND_RETURN(bool, obj->getCudaFlag()); } //BIND_END //BIND_METHOD SparseMatrixComplexF to_dense { LUABIND_RETURN(MatrixComplexF, obj->toDense()); } //BIND_END //BIND_METHOD SparseMatrixComplexF set_use_cuda { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, bool); bool v; LUABIND_GET_PARAMETER(1,bool, v); obj->setUseCuda(v); LUABIND_RETURN(SparseMatrixComplexF, obj); } //BIND_END //BIND_METHOD SparseMatrixComplexF get_sparse_format { if (obj->getSparseFormat() == CSR_FORMAT) LUABIND_RETURN(string, "csr"); else LUABIND_RETURN(string, "csc"); } //BIND_END //BIND_METHOD SparseMatrixComplexF dim { LUABIND_CHECK_ARGN(>=, 0); LUABIND_CHECK_ARGN(<=, 1); int pos; const int *d=obj->getDimPtr(); LUABIND_GET_OPTIONAL_PARAMETER(1, int, pos, -1); if (pos < 1) { LUABIND_VECTOR_TO_NEW_TABLE(int, d, obj->getNumDim()); LUABIND_RETURN_FROM_STACK(-1); } else LUABIND_RETURN(int, d[pos-1]); } //BIND_END //BIND_METHOD SparseMatrixComplexF slice { LUABIND_CHECK_ARGN(>=,2); LUABIND_CHECK_ARGN(<=,3); LUABIND_CHECK_PARAMETER(1, table); LUABIND_CHECK_PARAMETER(2, table); int *coords, *sizes, coords_len, sizes_len; bool clone; LUABIND_TABLE_GETN(1, coords_len); LUABIND_TABLE_GETN(2, sizes_len); if (coords_len != sizes_len || coords_len != obj->getNumDim()) LUABIND_FERROR3("Incorrect number of dimensions, expected %d, " "found %d and %d\n", obj->getNumDim(), coords_len, sizes_len); coords = new int[coords_len]; sizes = new int[sizes_len]; LUABIND_TABLE_TO_VECTOR_SUB1(1, int, coords, coords_len); LUABIND_TABLE_TO_VECTOR(2, int, sizes, sizes_len); LUABIND_GET_OPTIONAL_PARAMETER(3, bool, clone, false); for (int i=0; i obj->getDimSize(i)) LUABIND_FERROR1("Incorrect size or coord at position %d\n", i+1); SparseMatrixComplexF *obj2 = new SparseMatrixComplexF(obj, coords, sizes, clone); LUABIND_RETURN(SparseMatrixComplexF, obj2); delete[] coords; delete[] sizes; } //BIND_END //BIND_METHOD SparseMatrixComplexF clone { LUABIND_CHECK_ARGN(>=, 0); LUABIND_CHECK_ARGN(<=, 1); int argn; argn = lua_gettop(L); // number of arguments SparseMatrixComplexF *obj2; if (argn == 0) obj2 = obj->clone(); else { const char *sparse; LUABIND_GET_PARAMETER(1, string, sparse); SPARSE_FORMAT format = CSC_FORMAT; if (strcmp(sparse, "csr") == 0) format = CSR_FORMAT; else if (strcmp(sparse, "csc") != 0) LUABIND_FERROR1("Incorrect sparse format string %s", sparse); obj2 = obj->clone(format); } LUABIND_RETURN(SparseMatrixComplexF,obj2); } //BIND_END //BIND_METHOD SparseMatrixComplexF transpose { LUABIND_RETURN(SparseMatrixComplexF, obj->transpose()); } //BIND_END //BIND_METHOD SparseMatrixComplexF isfinite { LUABIND_CHECK_ARGN(==, 0); bool resul=true; for (SparseMatrixComplexF::iterator it(obj->begin()); resul && it!=obj->end(); ++it) //if (!isfinite(obj->data[i])) resul = 0; if ((*it) - (*it) != AprilMath::Limits::zero()) resul = false; LUABIND_RETURN(boolean,resul); } //BIND_END //BIND_CLASS_METHOD SparseMatrixComplexF diag { SparseMatrixComplexF *obj; int argn = lua_gettop(L); // number of arguments if (lua_isMatrixComplexF(L,1)) { MatrixComplexF *m; LUABIND_GET_PARAMETER(1, MatrixComplexF, m); const char *sparse; LUABIND_GET_OPTIONAL_PARAMETER(2, string, sparse, "csr"); SPARSE_FORMAT format = CSR_FORMAT; if (strcmp(sparse, "csc") == 0) format = CSC_FORMAT; else if (strcmp(sparse, "csr") != 0) LUABIND_FERROR1("Incorrect sparse format string %s", sparse); obj = SparseMatrixComplexF::diag(m,format); } else if (lua_isComplexFGPUMirroredMemoryBlock(L,1)) { ComplexFGPUMirroredMemoryBlock *block; LUABIND_GET_PARAMETER(1, ComplexFGPUMirroredMemoryBlock, block); const char *sparse; LUABIND_GET_OPTIONAL_PARAMETER(2, string, sparse, "csr"); SPARSE_FORMAT format = CSR_FORMAT; if (strcmp(sparse, "csc") == 0) format = CSC_FORMAT; else if (strcmp(sparse, "csr") != 0) LUABIND_FERROR1("Incorrect sparse format string %s", sparse); obj = SparseMatrixComplexF::diag(block,format); } else if (lua_istable(L,1)) { int N; LUABIND_TABLE_GETN(1, N); ComplexFGPUMirroredMemoryBlock *block = new ComplexFGPUMirroredMemoryBlock(N); const char *sparse; LUABIND_GET_OPTIONAL_PARAMETER(2, string, sparse, "csr"); SPARSE_FORMAT format = CSR_FORMAT; if (strcmp(sparse, "csc") == 0) format = CSC_FORMAT; else if (strcmp(sparse, "csr") != 0) LUABIND_FERROR1("Incorrect sparse format string %s", sparse); ComplexF *mem = block->getPPALForWrite(); lua_pushnil(L); int i=0; while(lua_next(L, 1) != 0) { mem[i++] = lua_toComplexF(L, -1); lua_pop(L, 1); } obj = SparseMatrixComplexF::diag(block,format); } else { int N; ComplexF v; LUABIND_GET_PARAMETER(1, int, N); LUABIND_GET_PARAMETER(2, ComplexF, v); const char *sparse; LUABIND_GET_OPTIONAL_PARAMETER(3, string, sparse, "csr"); SPARSE_FORMAT format = CSR_FORMAT; if (strcmp(sparse, "csc") == 0) format = CSC_FORMAT; else if (strcmp(sparse, "csr") != 0) LUABIND_FERROR1("Incorrect sparse format string %s", sparse); obj = SparseMatrixComplexF::diag(N,v,format); } LUABIND_RETURN(SparseMatrixComplexF, obj); } //BIND_END //BIND_METHOD SparseMatrixComplexF equals { SparseMatrixComplexF *other; float epsilon; LUABIND_GET_PARAMETER(1, SparseMatrixComplexF, other); LUABIND_GET_OPTIONAL_PARAMETER(2, float, epsilon, 1e-04f); LUABIND_RETURN(boolean, matEquals(obj, other, epsilon)); } //BIND_END //BIND_METHOD SparseMatrixComplexF copy { int argn; LUABIND_CHECK_ARGN(==, 1); SparseMatrixComplexF *mat; LUABIND_GET_PARAMETER(1, SparseMatrixComplexF, mat); LUABIND_RETURN(SparseMatrixComplexF, matCopy(obj, mat)); } //BIND_END //BIND_METHOD SparseMatrixComplexF scal { LUABIND_CHECK_ARGN(==, 1); ComplexF value; LUABIND_GET_PARAMETER(1, ComplexF, value); LUABIND_RETURN(SparseMatrixComplexF, matScal(obj, value)); } //BIND_END //BIND_METHOD SparseMatrixComplexF get_shared_count { LUABIND_RETURN(uint, obj->getSharedCount()); } //BIND_END //BIND_METHOD SparseMatrixComplexF reset_shared_count { obj->resetSharedCount(); LUABIND_RETURN(SparseMatrixComplexF, obj); } //BIND_END //BIND_METHOD SparseMatrixComplexF add_to_shared_count { unsigned int count; LUABIND_GET_PARAMETER(1,uint,count); obj->addToSharedCount(count); } //BIND_END //BIND_METHOD SparseMatrixComplexF prune_subnormal_and_check_normal { obj->pruneSubnormalAndCheckNormal(); } //BIND_END //BIND_METHOD SparseMatrixComplexF as_vector { LUABIND_RETURN(SparseMatrixComplexF, obj->asVector()); } //BIND_END //BIND_METHOD SparseMatrixComplexF is_diagonal { LUABIND_RETURN(bool, obj->isDiagonal()); } //BIND_END //// MATRIX SERIALIZATION //// //BIND_CLASS_METHOD SparseMatrixComplexF read { MAKE_READ_SPARSE_MATRIX_LUA_METHOD(SparseMatrixComplexF, ComplexF); LUABIND_INCREASE_NUM_RETURNS(1); } //BIND_END //BIND_METHOD SparseMatrixComplexF num_dim { LUABIND_RETURN(int, 2); } //BIND_END //BIND_METHOD SparseMatrixComplexF select { LUABIND_ERROR("Not implemented method in sparse matrix instances"); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_METHOD SparseMatrixComplexF values { LUABIND_RETURN(ComplexFGPUMirroredMemoryBlock, obj->getRawValuesAccess()); } //BIND_END //BIND_METHOD SparseMatrixComplexF indices { LUABIND_RETURN(Int32GPUMirroredMemoryBlock, obj->getRawIndicesAccess()); } //BIND_END //BIND_METHOD SparseMatrixComplexF first_index { LUABIND_RETURN(Int32GPUMirroredMemoryBlock, obj->getRawFirstIndexAccess()); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME DOKBuilderSparseMatrixComplexF matrixComplex.sparse.builders.dok //BIND_CPP_CLASS DOKBuilderSparseMatrixComplexF //BIND_CONSTRUCTOR DOKBuilderSparseMatrixComplexF { LUABIND_RETURN(DOKBuilderSparseMatrixComplexF, new DOKBuilderSparseMatrixComplexF()); } //BIND_END //BIND_METHOD DOKBuilderSparseMatrixComplexF set { unsigned int row, col; ComplexF value; LUABIND_GET_PARAMETER(1, uint, row); LUABIND_GET_PARAMETER(2, uint, col); LUABIND_GET_PARAMETER(3, ComplexF, value); if (row == 0 || col == 0) LUABIND_ERROR("Indices should be > 0"); obj->insert(row-1, col-1, value); LUABIND_RETURN(DOKBuilderSparseMatrixComplexF, obj); } //BIND_END //BIND_METHOD DOKBuilderSparseMatrixComplexF build { unsigned int d0, d1; SPARSE_FORMAT format = CSR_FORMAT; const char *sparse; LUABIND_GET_OPTIONAL_PARAMETER(1, uint, d0, 0); LUABIND_GET_OPTIONAL_PARAMETER(2, uint, d1, 0); LUABIND_GET_OPTIONAL_PARAMETER(3, string, sparse, 0); if (sparse != 0) { if (strcmp(sparse, "csc") == 0) { format = CSC_FORMAT; } else if (strcmp(sparse, "csr") != 0) { LUABIND_FERROR1("Incorrect sparse format string %s", sparse); } } LUABIND_RETURN(SparseMatrixComplexF, obj->build(d0, d1, format)); } //BIND_END ////////////////////////////////////////////////////////////////////////////// april-ann-0.4.1/packages/basics/matrix/binding/bind_sparse_matrix_double.lua.cc000066400000000000000000000604751263004425400276470ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include // para isfinite #include "april_assert.h" #include "bind_april_io.h" #include "bind_matrix.h" #include "bind_matrix_int32.h" #include "bind_matrix_double.h" #include "bind_mathcore.h" #include "cmath_overloads.h" #include "luabindmacros.h" // for lua_pushdouble and lua_pushint #include "luabindutil.h" // for lua_pushdouble and lua_pushint #include "matrix_ext.h" using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Boolean; using namespace AprilMath::MatrixExt::Initializers; using namespace AprilMath::MatrixExt::Misc; using namespace AprilMath::MatrixExt::LAPACK; using namespace AprilMath::MatrixExt::Operations; using namespace AprilMath::MatrixExt::Reductions; IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(SparseMatrixDouble); namespace Basics { int sparseMatrixDoubleIteratorFunction(lua_State *L) { SparseMatrixDoubleIterator *obj = lua_toSparseMatrixDoubleIterator(L,1); if (obj->it == obj->m->end()) { lua_pushnil(L); return 1; } int c0=0,c1=0; obj->it.getCoords(c0,c1); lua_pushdouble(L,*(obj->it)); lua_pushint(L,c0+1); lua_pushint(L,c1+1); ++(obj->it); return 3; } } //BIND_END //BIND_HEADER_H #include // para isfinite #include "bind_april_io.h" #include "referenced.h" #include "sparse_matrixDouble.h" #include "utilLua.h" namespace Basics { class SparseMatrixDoubleIterator : public Referenced { public: SparseMatrixDouble *m; SparseMatrixDouble::iterator it; // SparseMatrixDoubleIterator(SparseMatrixDouble *m) : m(m), it(m->begin()) { IncRef(m); } virtual ~SparseMatrixDoubleIterator() { DecRef(m); } }; #define MAKE_READ_SPARSE_MATRIX_LUA_METHOD(MatrixType, Type) do { \ MatrixType *obj = readSparse(L); \ if (obj == 0) { \ luaL_error(L, "Error happens reading from file stream"); \ } \ else { \ lua_push##MatrixType(L, obj); \ } \ } while(false) template SparseMatrix *readSparse(lua_State *L) { AprilIO::StreamInterface *stream = lua_toAuxStreamInterface(L,1); AprilUtils::SharedPtr ptr(stream); if (stream == 0) { luaL_error(L, "Needs a stream as 1st argument"); return 0; } AprilUtils::LuaTable options(L,2); return SparseMatrix::read(ptr.get(), options); } } // namespace Basics using namespace Basics; //BIND_END //BIND_LUACLASSNAME SparseMatrixDoubleIterator matrixDouble.sparse.iterator //BIND_CPP_CLASS SparseMatrixDoubleIterator //BIND_CONSTRUCTOR SparseMatrixDoubleIterator { LUABIND_ERROR("Use iterate() method in matrixDouble.sparse object"); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME SparseMatrixDouble matrixDouble.sparse //BIND_CPP_CLASS SparseMatrixDouble //BIND_LUACLASSNAME Serializable aprilio.serializable //BIND_SUBCLASS_OF SparseMatrixDouble Serializable //BIND_CONSTRUCTOR SparseMatrixDouble { if (lua_isMatrixDouble(L,1)) { double near_zero; MatrixDouble *m; LUABIND_GET_PARAMETER(1, MatrixDouble, m); LUABIND_GET_OPTIONAL_PARAMETER(2, double, near_zero, NEAR_ZERO); obj = SparseMatrixDouble::fromDenseMatrix(m, CSR_FORMAT, near_zero); } else { int rows,cols; DoubleGPUMirroredMemoryBlock *values; Int32GPUMirroredMemoryBlock *indices; Int32GPUMirroredMemoryBlock *first_index; bool sort; LUABIND_GET_PARAMETER(1, int, rows); if (lua_isDoubleGPUMirroredMemoryBlock(L,2)) { cols = rows; rows = 1; LUABIND_GET_PARAMETER(2, DoubleGPUMirroredMemoryBlock, values); LUABIND_GET_PARAMETER(3, Int32GPUMirroredMemoryBlock, indices); LUABIND_GET_OPTIONAL_PARAMETER(4, Int32GPUMirroredMemoryBlock, first_index, 0); LUABIND_GET_OPTIONAL_PARAMETER(5, boolean, sort, false); } else { LUABIND_GET_PARAMETER(2, int, cols); LUABIND_GET_PARAMETER(3, DoubleGPUMirroredMemoryBlock, values); LUABIND_GET_PARAMETER(4, Int32GPUMirroredMemoryBlock, indices); LUABIND_GET_OPTIONAL_PARAMETER(5, Int32GPUMirroredMemoryBlock, first_index, 0); LUABIND_GET_OPTIONAL_PARAMETER(6, boolean, sort, false); } obj = new SparseMatrixDouble(rows, cols, values, indices, first_index, CSR_FORMAT, sort); } LUABIND_RETURN(SparseMatrixDouble,obj); } //BIND_END //BIND_CLASS_METHOD SparseMatrixDouble csc { SparseMatrixDouble *obj; if (lua_isMatrixDouble(L,1)) { MatrixDouble *m; double near_zero; LUABIND_GET_PARAMETER(1, MatrixDouble, m); LUABIND_GET_OPTIONAL_PARAMETER(2, double, near_zero, NEAR_ZERO); obj = SparseMatrixDouble::fromDenseMatrix(m, CSC_FORMAT, near_zero); } else { int rows,cols; DoubleGPUMirroredMemoryBlock *values; Int32GPUMirroredMemoryBlock *indices; Int32GPUMirroredMemoryBlock *first_index; bool sort; LUABIND_GET_PARAMETER(1, int, rows); if (lua_isDoubleGPUMirroredMemoryBlock(L,2)) { cols = 1; LUABIND_GET_PARAMETER(2, DoubleGPUMirroredMemoryBlock, values); LUABIND_GET_PARAMETER(3, Int32GPUMirroredMemoryBlock, indices); LUABIND_GET_OPTIONAL_PARAMETER(4, Int32GPUMirroredMemoryBlock, first_index, 0); LUABIND_GET_OPTIONAL_PARAMETER(5, boolean, sort, false); } else { LUABIND_GET_PARAMETER(2, int, cols); LUABIND_GET_PARAMETER(3, DoubleGPUMirroredMemoryBlock, values); LUABIND_GET_PARAMETER(4, Int32GPUMirroredMemoryBlock, indices); LUABIND_GET_OPTIONAL_PARAMETER(5, Int32GPUMirroredMemoryBlock, first_index, 0); LUABIND_GET_OPTIONAL_PARAMETER(6, boolean, sort, false); } obj = new SparseMatrixDouble(rows, cols, values, indices, first_index, CSC_FORMAT, sort); } LUABIND_RETURN(SparseMatrixDouble,obj); } //BIND_END //BIND_METHOD SparseMatrixDouble size { LUABIND_RETURN(int, obj->size()); } //BIND_END //BIND_METHOD SparseMatrixDouble non_zero_size { LUABIND_RETURN(int, obj->nonZeroSize()); } //BIND_END //BIND_METHOD SparseMatrixDouble get_reference_string { char buff[128]; sprintf(buff,"%p data= %p %p %p", (void*)obj, (void*)obj->getRawValuesAccess(), (void*)obj->getRawIndicesAccess(), (void*)obj->getRawFirstIndexAccess()); LUABIND_RETURN(string, buff); } //BIND_END //BIND_CLASS_METHOD SparseMatrixDouble fromMMap { LUABIND_CHECK_ARGN(>=, 1); LUABIND_CHECK_ARGN(<=, 3); LUABIND_CHECK_PARAMETER(1, string); const char *filename; bool write, shared; LUABIND_GET_PARAMETER(1,string,filename); LUABIND_GET_OPTIONAL_PARAMETER(2,bool,write,true); LUABIND_GET_OPTIONAL_PARAMETER(3,bool,shared,true); AprilUtils::MMappedDataReader *mmapped_data; mmapped_data = new AprilUtils::MMappedDataReader(filename,write,shared); IncRef(mmapped_data); SparseMatrixDouble *obj = SparseMatrixDouble::fromMMappedDataReader(mmapped_data); DecRef(mmapped_data); LUABIND_RETURN(SparseMatrixDouble,obj); } //BIND_END //BIND_METHOD SparseMatrixDouble toMMap { LUABIND_CHECK_ARGN(==, 1); const char *filename; LUABIND_GET_PARAMETER(1, string, filename); AprilUtils::MMappedDataWriter *mmapped_data; mmapped_data = new AprilUtils::MMappedDataWriter(filename); IncRef(mmapped_data); obj->toMMappedDataWriter(mmapped_data); DecRef(mmapped_data); } //BIND_END //BIND_METHOD SparseMatrixDouble get { int row,col; LUABIND_GET_PARAMETER(1, int, row); LUABIND_GET_PARAMETER(2, int, col); double v = (*obj)(row-1,col-1); LUABIND_RETURN(double, v); } //BIND_END //BIND_METHOD SparseMatrixDouble raw_get { int idx; LUABIND_GET_PARAMETER(1, int, idx); if (idx < 1 || idx > obj->nonZeroSize()) LUABIND_FERROR2("Index out-of-bounds [%d,%d]", 1, obj->nonZeroSize()); SparseMatrixDouble::const_iterator it(obj->iteratorAtRawIndex(idx-1)); LUABIND_RETURN(double, *it); int c0=0,c1=0; it.getCoords(c0,c1); LUABIND_RETURN(double, *it); LUABIND_RETURN(int, c0+1); LUABIND_RETURN(int, c1+1); } //BIND_END //BIND_METHOD SparseMatrixDouble raw_set { double value; int idx; LUABIND_GET_PARAMETER(1, int, idx); LUABIND_GET_PARAMETER(2, double, value); if (idx < 1 || idx > obj->nonZeroSize()) LUABIND_FERROR2("Index out-of-bounds [%d,%d]", 1, obj->nonZeroSize()); (*obj)[idx] = value; LUABIND_RETURN(SparseMatrixDouble, obj); } //BIND_END //BIND_METHOD SparseMatrixDouble iterate { LUABIND_CHECK_ARGN(==, 0); LUABIND_RETURN(cfunction,sparseMatrixDoubleIteratorFunction); LUABIND_RETURN(SparseMatrixDoubleIterator,new SparseMatrixDoubleIterator(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble fill { LUABIND_CHECK_ARGN(==, 1); double value; if (lua_isSparseMatrixDouble(L, 1)) { SparseMatrixDouble *aux; LUABIND_GET_PARAMETER(1,SparseMatrixDouble,aux); for (int i=0; igetNumDim(); ++i) if (aux->getDimSize(i) != 1) LUABIND_ERROR("Needs a double or a matrix with only one element\n"); value = *(aux->begin()); } else { LUABIND_CHECK_PARAMETER(1, double); LUABIND_GET_PARAMETER(1,double,value); } LUABIND_RETURN(SparseMatrixDouble, matFill(obj,value)); } //BIND_END //BIND_METHOD SparseMatrixDouble zeros //DOC_BEGIN // void zeros(double value) /// Permite poner todos los valores de la matriz a un mismo valor. //DOC_END { LUABIND_RETURN(SparseMatrixDouble, matZeros(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble ones //DOC_BEGIN // void onex(double value) /// Permite poner todos los valores de la matriz a un mismo valor. //DOC_END { LUABIND_RETURN(SparseMatrixDouble, matOnes(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble get_use_cuda { LUABIND_RETURN(bool, obj->getCudaFlag()); } //BIND_END //BIND_METHOD SparseMatrixDouble to_dense { LUABIND_RETURN(MatrixDouble, obj->toDense()); } //BIND_END //BIND_METHOD SparseMatrixDouble set_use_cuda { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, bool); bool v; LUABIND_GET_PARAMETER(1,bool, v); obj->setUseCuda(v); LUABIND_RETURN(SparseMatrixDouble, obj); } //BIND_END //BIND_METHOD SparseMatrixDouble get_sparse_format { if (obj->getSparseFormat() == CSR_FORMAT) LUABIND_RETURN(string, "csr"); else LUABIND_RETURN(string, "csc"); } //BIND_END //BIND_METHOD SparseMatrixDouble dim { LUABIND_CHECK_ARGN(>=, 0); LUABIND_CHECK_ARGN(<=, 1); int pos; const int *d=obj->getDimPtr(); LUABIND_GET_OPTIONAL_PARAMETER(1, int, pos, -1); if (pos < 1) { LUABIND_VECTOR_TO_NEW_TABLE(int, d, obj->getNumDim()); LUABIND_RETURN_FROM_STACK(-1); } else LUABIND_RETURN(int, d[pos-1]); } //BIND_END //BIND_METHOD SparseMatrixDouble slice { LUABIND_CHECK_ARGN(>=,2); LUABIND_CHECK_ARGN(<=,3); LUABIND_CHECK_PARAMETER(1, table); LUABIND_CHECK_PARAMETER(2, table); int *coords, *sizes, coords_len, sizes_len; bool clone; LUABIND_TABLE_GETN(1, coords_len); LUABIND_TABLE_GETN(2, sizes_len); if (coords_len != sizes_len || coords_len != obj->getNumDim()) LUABIND_FERROR3("Incorrect number of dimensions, expected %d, " "found %d and %d\n", obj->getNumDim(), coords_len, sizes_len); coords = new int[coords_len]; sizes = new int[sizes_len]; LUABIND_TABLE_TO_VECTOR_SUB1(1, int, coords, coords_len); LUABIND_TABLE_TO_VECTOR(2, int, sizes, sizes_len); LUABIND_GET_OPTIONAL_PARAMETER(3, bool, clone, false); for (int i=0; i obj->getDimSize(i)) LUABIND_FERROR1("Incorrect size or coord at position %d\n", i+1); SparseMatrixDouble *obj2 = new SparseMatrixDouble(obj, coords, sizes, clone); LUABIND_RETURN(SparseMatrixDouble, obj2); delete[] coords; delete[] sizes; } //BIND_END //BIND_METHOD SparseMatrixDouble clone { LUABIND_CHECK_ARGN(>=, 0); LUABIND_CHECK_ARGN(<=, 1); int argn; argn = lua_gettop(L); // number of arguments SparseMatrixDouble *obj2; if (argn == 0) obj2 = obj->clone(); else { const char *sparse; LUABIND_GET_PARAMETER(1, string, sparse); SPARSE_FORMAT format = CSC_FORMAT; if (strcmp(sparse, "csr") == 0) format = CSR_FORMAT; else if (strcmp(sparse, "csc") != 0) LUABIND_FERROR1("Incorrect sparse format string %s", sparse); obj2 = obj->clone(format); } LUABIND_RETURN(SparseMatrixDouble,obj2); } //BIND_END //BIND_METHOD SparseMatrixDouble transpose { LUABIND_RETURN(SparseMatrixDouble, obj->transpose()); } //BIND_END //BIND_METHOD SparseMatrixDouble isfinite { LUABIND_CHECK_ARGN(==, 0); bool resul=true; for (SparseMatrixDouble::iterator it(obj->begin()); resul && it!=obj->end(); ++it) //if (!isfinite(obj->data[i])) resul = 0; if ((*it) - (*it) != 0.0f) resul = false; LUABIND_RETURN(boolean,resul); } //BIND_END //BIND_CLASS_METHOD SparseMatrixDouble diag { SparseMatrixDouble *obj; int argn = lua_gettop(L); // number of arguments if (lua_isMatrixDouble(L,1)) { MatrixDouble *m; LUABIND_GET_PARAMETER(1, MatrixDouble, m); const char *sparse; LUABIND_GET_OPTIONAL_PARAMETER(2, string, sparse, "csr"); SPARSE_FORMAT format = CSR_FORMAT; if (strcmp(sparse, "csc") == 0) format = CSC_FORMAT; else if (strcmp(sparse, "csr") != 0) LUABIND_FERROR1("Incorrect sparse format string %s", sparse); obj = SparseMatrixDouble::diag(m,format); } else if (lua_isDoubleGPUMirroredMemoryBlock(L,1)) { DoubleGPUMirroredMemoryBlock *block; LUABIND_GET_PARAMETER(1, DoubleGPUMirroredMemoryBlock, block); const char *sparse; LUABIND_GET_OPTIONAL_PARAMETER(2, string, sparse, "csr"); SPARSE_FORMAT format = CSR_FORMAT; if (strcmp(sparse, "csc") == 0) format = CSC_FORMAT; else if (strcmp(sparse, "csr") != 0) LUABIND_FERROR1("Incorrect sparse format string %s", sparse); obj = SparseMatrixDouble::diag(block,format); } else if (lua_istable(L,1)) { int N; LUABIND_TABLE_GETN(1, N); DoubleGPUMirroredMemoryBlock *block = new DoubleGPUMirroredMemoryBlock(N); const char *sparse; LUABIND_GET_OPTIONAL_PARAMETER(2, string, sparse, "csr"); SPARSE_FORMAT format = CSR_FORMAT; if (strcmp(sparse, "csc") == 0) format = CSC_FORMAT; else if (strcmp(sparse, "csr") != 0) LUABIND_FERROR1("Incorrect sparse format string %s", sparse); double *mem = block->getPPALForWrite(); lua_pushnil(L); int i=0; while(lua_next(L, 1) != 0) { mem[i++] = lua_todouble(L, -1); lua_pop(L, 1); } obj = SparseMatrixDouble::diag(block,format); } else { int N; double v; LUABIND_GET_PARAMETER(1, int, N); LUABIND_GET_PARAMETER(2, double, v); const char *sparse; LUABIND_GET_OPTIONAL_PARAMETER(3, string, sparse, "csr"); SPARSE_FORMAT format = CSR_FORMAT; if (strcmp(sparse, "csc") == 0) format = CSC_FORMAT; else if (strcmp(sparse, "csr") != 0) LUABIND_FERROR1("Incorrect sparse format string %s", sparse); obj = SparseMatrixDouble::diag(N,v,format); } LUABIND_RETURN(SparseMatrixDouble, obj); } //BIND_END //BIND_METHOD SparseMatrixDouble min { LUABIND_CHECK_ARGN(>=,0); LUABIND_CHECK_ARGN(<=,3); int argn = lua_gettop(L); if (argn > 0) { int dim; MatrixDouble *dest; MatrixInt32 *argmin; LUABIND_GET_PARAMETER(1, int, dim); LUABIND_GET_OPTIONAL_PARAMETER(2, MatrixDouble, dest, 0); LUABIND_GET_OPTIONAL_PARAMETER(3, MatrixInt32, argmin, 0); int *aux = 0; if (argmin == 0) { aux = new int[obj->getNumDim()]; for (int i=0; igetNumDim(); ++i) aux[i] = obj->getDimSize(i); aux[dim-1] = 1; argmin = new MatrixInt32(obj->getNumDim(), aux); } IncRef(argmin); if (dim < 1 || dim > obj->getNumDim()) LUABIND_FERROR2("Incorrect dimension, found %d, expect in [1,%d]", dim, obj->getNumDim()); LUABIND_RETURN(MatrixDouble, matMin(obj, dim-1, dest, argmin)); LUABIND_RETURN(MatrixInt32, argmin); DecRef(argmin); delete[] aux; } else { int c0, c1; LUABIND_RETURN(double, matMin(obj, c0, c1)); LUABIND_RETURN(int, c0+1); LUABIND_RETURN(int, c1+1); } } //BIND_END //BIND_METHOD SparseMatrixDouble max { LUABIND_CHECK_ARGN(>=,0); LUABIND_CHECK_ARGN(<=,3); int argn = lua_gettop(L); if (argn > 0) { int dim; MatrixDouble *dest; MatrixInt32 *argmax; LUABIND_GET_PARAMETER(1, int, dim); LUABIND_GET_OPTIONAL_PARAMETER(2, MatrixDouble, dest, 0); LUABIND_GET_OPTIONAL_PARAMETER(3, MatrixInt32, argmax, 0); int *aux = 0; if (argmax == 0) { aux = new int[obj->getNumDim()]; for (int i=0; igetNumDim(); ++i) aux[i] = obj->getDimSize(i); aux[dim-1] = 1; argmax = new MatrixInt32(obj->getNumDim(), aux); } IncRef(argmax); if (dim < 1 || dim > obj->getNumDim()) LUABIND_FERROR2("Incorrect dimension, found %d, expect in [1,%d]", dim, obj->getNumDim()); LUABIND_RETURN(MatrixDouble, matMax(obj, dim-1, dest, argmax)); LUABIND_RETURN(MatrixInt32, argmax); DecRef(argmax); delete[] aux; } else { int c0, c1; LUABIND_RETURN(double, matMax(obj, c0, c1)); LUABIND_RETURN(int, c0+1); LUABIND_RETURN(int, c1+1); } } //BIND_END //BIND_METHOD SparseMatrixDouble equals { SparseMatrixDouble *other; float epsilon; LUABIND_GET_PARAMETER(1, SparseMatrixDouble, other); LUABIND_GET_OPTIONAL_PARAMETER(2, float, epsilon, 1e-04f); LUABIND_RETURN(boolean, matEquals(obj, other, epsilon)); } //BIND_END //BIND_METHOD SparseMatrixDouble sqrt { LUABIND_RETURN(SparseMatrixDouble, matSqrt(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble pow { double value; LUABIND_CHECK_ARGN(==,1); LUABIND_GET_PARAMETER(1, double, value); LUABIND_RETURN(SparseMatrixDouble, matPow(obj,value)); } //BIND_END //BIND_METHOD SparseMatrixDouble tan { LUABIND_RETURN(SparseMatrixDouble, matTan(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble tanh { LUABIND_RETURN(SparseMatrixDouble, matTanh(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble atan { LUABIND_RETURN(SparseMatrixDouble, matAtan(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble atanh { LUABIND_RETURN(SparseMatrixDouble, matAtanh(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble sin { LUABIND_RETURN(SparseMatrixDouble, matSin(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble sinh { LUABIND_RETURN(SparseMatrixDouble, matSinh(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble asin { LUABIND_RETURN(SparseMatrixDouble, matAsin(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble asinh { LUABIND_RETURN(SparseMatrixDouble, matAsinh(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble abs { LUABIND_RETURN(SparseMatrixDouble, matAbs(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble sign { LUABIND_RETURN(SparseMatrixDouble, matSign(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble sum { LUABIND_CHECK_ARGN(>=, 0); LUABIND_CHECK_ARGN(<=, 2); int argn = lua_gettop(L); // number of arguments if (argn >= 1 && !lua_isnil(L,1)) { int dim; MatrixDouble *dest; LUABIND_GET_PARAMETER(1, int, dim); LUABIND_GET_OPTIONAL_PARAMETER(2, MatrixDouble, dest, 0); if (dim < 1 || dim > obj->getNumDim()) LUABIND_FERROR2("Incorrect dimension, found %d, expect in [1,%d]", dim, obj->getNumDim()); LUABIND_RETURN(MatrixDouble, matSum(obj, dim-1, dest)); } else LUABIND_RETURN(double, matSum(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble copy { int argn; LUABIND_CHECK_ARGN(==, 1); SparseMatrixDouble *mat; LUABIND_GET_PARAMETER(1, SparseMatrixDouble, mat); LUABIND_RETURN(SparseMatrixDouble, matCopy(obj, mat)); } //BIND_END //BIND_METHOD SparseMatrixDouble scal { LUABIND_CHECK_ARGN(==, 1); double value; LUABIND_GET_PARAMETER(1, double, value); LUABIND_RETURN(SparseMatrixDouble, matScal(obj, value)); } //BIND_END //BIND_METHOD SparseMatrixDouble div { LUABIND_CHECK_ARGN(==, 1); double value; LUABIND_GET_PARAMETER(1, double, value); LUABIND_RETURN(SparseMatrixDouble, matDiv(obj, value)); } //BIND_END //BIND_METHOD SparseMatrixDouble norm2 { LUABIND_RETURN(double, matNorm2(obj)); } //BIND_END //BIND_METHOD SparseMatrixDouble get_shared_count { LUABIND_RETURN(uint, obj->getSharedCount()); } //BIND_END //BIND_METHOD SparseMatrixDouble reset_shared_count { obj->resetSharedCount(); LUABIND_RETURN(SparseMatrixDouble, obj); } //BIND_END //BIND_METHOD SparseMatrixDouble add_to_shared_count { unsigned int count; LUABIND_GET_PARAMETER(1,uint,count); obj->addToSharedCount(count); } //BIND_END //BIND_METHOD SparseMatrixDouble prune_subnormal_and_check_normal { obj->pruneSubnormalAndCheckNormal(); } //BIND_END //BIND_METHOD SparseMatrixDouble as_vector { LUABIND_RETURN(SparseMatrixDouble, obj->asVector()); } //BIND_END //BIND_METHOD SparseMatrixDouble is_diagonal { LUABIND_RETURN(bool, obj->isDiagonal()); } //BIND_END //// MATRIX SERIALIZATION //// //BIND_CLASS_METHOD SparseMatrixDouble read { MAKE_READ_SPARSE_MATRIX_LUA_METHOD(SparseMatrixDouble, double); LUABIND_INCREASE_NUM_RETURNS(1); } //BIND_END //BIND_METHOD SparseMatrixDouble num_dim { LUABIND_RETURN(int, 2); } //BIND_END //BIND_METHOD SparseMatrixDouble select { LUABIND_ERROR("Not implemented method in sparse matrix instances"); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_METHOD SparseMatrixDouble values { LUABIND_RETURN(DoubleGPUMirroredMemoryBlock, obj->getRawValuesAccess()); } //BIND_END //BIND_METHOD SparseMatrixDouble indices { LUABIND_RETURN(Int32GPUMirroredMemoryBlock, obj->getRawIndicesAccess()); } //BIND_END //BIND_METHOD SparseMatrixDouble first_index { LUABIND_RETURN(Int32GPUMirroredMemoryBlock, obj->getRawFirstIndexAccess()); } //BIND_END //////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME DOKBuilderSparseMatrixDouble matrixDouble.sparse.builders.dok //BIND_CPP_CLASS DOKBuilderSparseMatrixDouble //BIND_CONSTRUCTOR DOKBuilderSparseMatrixDouble { LUABIND_RETURN(DOKBuilderSparseMatrixDouble, new DOKBuilderSparseMatrixDouble()); } //BIND_END //BIND_METHOD DOKBuilderSparseMatrixDouble set { unsigned int row, col; double value; LUABIND_GET_PARAMETER(1, uint, row); LUABIND_GET_PARAMETER(2, uint, col); LUABIND_GET_PARAMETER(3, double, value); if (row == 0 || col == 0) LUABIND_ERROR("Indices should be > 0"); obj->insert(row-1, col-1, value); LUABIND_RETURN(DOKBuilderSparseMatrixDouble, obj); } //BIND_END //BIND_METHOD DOKBuilderSparseMatrixDouble build { unsigned int d0, d1; SPARSE_FORMAT format = CSR_FORMAT; const char *sparse; LUABIND_GET_OPTIONAL_PARAMETER(1, uint, d0, 0); LUABIND_GET_OPTIONAL_PARAMETER(2, uint, d1, 0); LUABIND_GET_OPTIONAL_PARAMETER(3, string, sparse, 0); if (sparse != 0) { if (strcmp(sparse, "csc") == 0) { format = CSC_FORMAT; } else if (strcmp(sparse, "csr") != 0) { LUABIND_FERROR1("Incorrect sparse format string %s", sparse); } } LUABIND_RETURN(SparseMatrixDouble, obj->build(d0, d1, format)); } //BIND_END ////////////////////////////////////////////////////////////////////////////// april-ann-0.4.1/packages/basics/matrix/binding/generate_matrix_binding.lua000066400000000000000000000232431263004425400267140ustar00rootroot00000000000000function dirname(path_with_filename, sep) local sep=sep or'/' return path_with_filename:match("(.*"..sep..")") or "./" end function basename(path) local name = string.match(path, "([^/]+)$") return name end local root = dirname(arg[0]) local function get_timestamp(filename) local f = io.popen(table.concat{"find ", root, filename, " -printf '%h/%f %T@\n' 2> /dev/null ", "| cut -d' ' -f 2" }) return tonumber(f:read("*l")) or 0 end local script_timestamp = get_timestamp(basename(arg[0])) local matrix_methods = { float = { "size", "rewrap", "squeeze", "get_reference_string", "copy_from_table", "get", "set", "offset", "raw_get", "raw_set", "get_use_cuda", "same_dim", "set_use_cuda", "dim", "num_dim", "stride", "slice", "select", "clone", "transpose", "isfinite", "toTable", "contiguous", "map", "diagonalize", "get_shared_count", "reset_shared_count", "add_to_shared_count", "sync", "padding_all", "padding", "uniform", "uniformf", "linspace", "logspace", "linear", "sliding_window", "is_contiguous", "prune_subnormal_and_check_normal", "adjust_range", "diag", "fill", "zeros", "ones", "min", "max", "equals", "clamp", "add", "scalar_add", "sub", "mul", "cmul", "plogp", "log", "log1p", "exp", "expm1", "sqrt", "pow", "tan", "tanh", "atan", "atanh", "sin", "sinh", "asin", "asinh", "cos", "cosh", "acos", "acosh", "abs", "complement", "sign", "sum", "copy", "axpy", "prod", "cumsum", "cumprod", "gemm", "sparse_mm", "gemv", "ger", "dot", "scal", "cinv", "masked_fill", "masked_copy", "div", "norm2", "inv", "logdet", "det", "cholesky", "svd", "lt", "gt", "eq", "neq", "toMMap", "data", "order", "order_rank", "convert_to", "index", "indexed_fill", "indexed_copy", "ceil", "floor", "round", "left_inflate", "right_inflate", "count_eq", "count_neq", }, double = { "size", "rewrap", "squeeze", "get_reference_string", "copy_from_table", "get", "set", "offset", "raw_get", "raw_set", "get_use_cuda", "same_dim", "set_use_cuda", "dim", "num_dim", "stride", "slice", "select", "clone", "transpose", "isfinite", "toTable", "contiguous", "map", "diagonalize", "get_shared_count", "reset_shared_count", "add_to_shared_count", "sync", "padding_all", "padding", "uniform", "uniformf", "linspace", "logspace", "linear", "sliding_window", "is_contiguous", "prune_subnormal_and_check_normal", "adjust_range", "diag", "fill", "zeros", "ones", "min", "max", "equals", "clamp", "add", "scalar_add", "sub", "mul", "cmul", "plogp", "log", "log1p", "exp", "expm1", "sqrt", "pow", "tan", "tanh", "atan", "atanh", "sin", "sinh", "asin", "asinh", "cos", "cosh", "acos", "acosh", "abs", "complement", "sign", "sum", "copy", "axpy", "prod", "cumsum", "cumprod", "gemm", "gemv", "ger", "dot", "scal", "cinv", "masked_fill", "masked_copy", "div", "norm2", "lt", "gt", "eq", "neq", "toMMap", "data", "order", "order_rank", "convert_to", "index", "indexed_fill", "indexed_copy", "ceil", "floor", "round", "left_inflate", "right_inflate", "count_eq", "count_neq", }, int32_t = { "size", "rewrap", "squeeze", "get_reference_string", "copy_from_table", "get", "set", "offset", "raw_get", "raw_set", "get_use_cuda", "same_dim", "set_use_cuda", "dim", "num_dim", "stride", "slice", "select", "clone", "transpose", "toTable", "contiguous", "map", "diagonalize", "get_shared_count", "reset_shared_count", "add_to_shared_count", "sync", "padding_all", "padding", "uniform", "linspace", "linear", "sliding_window", "is_contiguous", "diag", "fill", "zeros", "ones", "min", "max", "equals", "clamp", "add", "scalar_add", "sub", "cmul", "scal", "sum", "copy", "axpy", "prod", "cumsum", "cumprod", "masked_fill", "masked_copy", "idiv", "mod", "lt", "gt", "eq", "neq", "toMMap", "data", "order", "order_rank", "convert_to", "index", "indexed_fill", "indexed_copy", "left_inflate", "right_inflate", "count_eq", "count_neq", }, ComplexF = { "size", "rewrap", "squeeze", "get_reference_string", "copy_from_table", "get", "set", "offset", "raw_get", "raw_set", "get_use_cuda", "same_dim", "set_use_cuda", "dim", "num_dim", "stride", "slice", "select", "clone", "transpose", "isfinite", "toTable", "contiguous", "map", "diagonalize", "get_shared_count", "reset_shared_count", "add_to_shared_count", "sync", "padding_all", "padding", "linear", "sliding_window", "is_contiguous", "prune_subnormal_and_check_normal", "diag", "fill", "zeros", "ones", "equals", "add", "scalar_add", "sub", "mul", "cmul", "sum", "copy", "axpy", "prod", "cumsum", "cumprod", "gemm", "gemv", "ger", "dot", "scal", "cinv", "masked_fill", "masked_copy", "div", "norm2", "toMMap", "data", "convert_to", "index", "indexed_fill", "indexed_copy", "ceil", "floor", "round", "left_inflate", "right_inflate", "count_eq", "count_neq", }, char = { "size", "rewrap", "squeeze", "get_reference_string", "copy_from_table", "get", "set", "offset", "raw_get", "raw_set", "get_use_cuda", "same_dim", "set_use_cuda", "dim", "num_dim", "stride", "slice", "select", "clone", "transpose", "toTable", "contiguous", "map", "diagonalize", "get_shared_count", "reset_shared_count", "add_to_shared_count", "sync", "padding_all", "padding", "sliding_window", "is_contiguous", "diag", "fill", "zeros", "ones", "equals", "copy", "toMMap", "data", "convert_to", "index", "indexed_fill", "indexed_copy", "stringfy", "left_inflate", "right_inflate", "count_eq", "count_neq", }, bool = { "size", "rewrap", "squeeze", "get_reference_string", "copy_from_table", "get", "set", "offset", "raw_get", "raw_set", "get_use_cuda", "same_dim", "set_use_cuda", "dim", "num_dim", "stride", "slice", "select", "clone", "transpose", "toTable", "contiguous", "map", "diagonalize", "get_shared_count", "reset_shared_count", "add_to_shared_count", "sync", "padding_all", "padding", "sliding_window", "is_contiguous", "diag", "fill", "zeros", "ones", "equals", "copy", "toMMap", "data", "convert_to", "index", "indexed_fill", "indexed_copy", "to_index", "left_inflate", "right_inflate", }, } local matrix_class_methods = { float = { "as", "deserialize", "read", "fromMMap", "__broadcast__", "__call_function__", "__newindex_function__", "__index_function__", }, double = { "as", "deserialize", "read", "fromMMap", "__broadcast__", "__call_function__", "__newindex_function__", "__index_function__", }, char = { "as", "deserialize", "read", "fromMMap", "__broadcast__", "__call_function__", "__newindex_function__", "__index_function__", }, int32_t = { "as", "deserialize", "read", "fromMMap", "__broadcast__", "__call_function__", "__newindex_function__", "__index_function__", }, ComplexF = { "as", "deserialize", "read", "fromMMap", "__broadcast__", "__call_function__", "__newindex_function__", "__index_function__", }, bool = { "as", "deserialize", "read", "fromMMap", "__broadcast__", "__call_function__", "__newindex_function__", "__index_function__", }, } local matrix_class_method_binding = [[ //BIND_CLASS_METHOD %s %s { LUABIND_INCREASE_NUM_RETURNS(MatrixBindings<%s>::%s(L)); } //BIND_END ]] local matrix_method_binding = [[ //BIND_METHOD %s %s { LUABIND_INCREASE_NUM_RETURNS(MatrixBindings<%s>::%s(L,obj)); } //BIND_END ]] local function generate_binding(data, class_methods, methods, class_method_binding, method_binding) for _,arg in ipairs(data) do local T = arg[1] local MATRIX_T = arg[2] local MATRIX_Lua = arg[3] local input = arg[4] local output = arg[5] local input_timestamp = get_timestamp(input) local output_timestamp = get_timestamp(output) if input_timestamp > output_timestamp or script_timestamp > output_timestamp then local template = io.open(root .. input):read("*a") local f = io.open(root .. output, "w") f:write((template:gsub("%$%$([^$]+)%$%$", { T = T, MATRIX_T = MATRIX_T, MATRIX_Lua = MATRIX_Lua, }))) local generated = {} for _,name in ipairs(class_methods[T] or {}) do assert(not generated[name]) f:write((class_method_binding:format(MATRIX_T, name, T, name))) generated[name] = true end f:write("///////////////////////////////////////////////////////////\n\n") for _,name in ipairs(methods[T] or {}) do assert(not generated[name], string.format("Duplicated entry %s.%s", MATRIX_Lua, name)) f:write((method_binding:format(MATRIX_T, name, T, name))) generated[name] = true end f:close() end end end local matrix_binding_data = { { "float", "MatrixFloat", "matrix", "matrix_template.lua.cc", "bind_matrix.lua.cc" }, { "double", "MatrixDouble", "matrixDouble", "matrix_template.lua.cc", "bind_matrix_double.lua.cc" }, { "int32_t", "MatrixInt32", "matrixInt32", "matrix_template.lua.cc", "bind_matrix_int32.lua.cc" }, { "char", "MatrixChar", "matrixChar", "matrix_template.lua.cc", "bind_matrix_char.lua.cc" }, { "ComplexF", "MatrixComplexF", "matrixComplex", "matrix_template.lua.cc", "bind_matrix_complex_float.lua.cc" }, { "bool", "MatrixBool", "matrixBool", "matrix_template.lua.cc", "bind_matrix_bool.lua.cc" }, } generate_binding(matrix_binding_data, matrix_class_methods, matrix_methods, matrix_class_method_binding, matrix_method_binding) april-ann-0.4.1/packages/basics/matrix/binding/matrix_binding.h000066400000000000000000002077621263004425400245220ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIX_BINDING_H #define MATRIX_BINDING_H extern "C" { #include #include } #include #include "complex_number.h" #include "bind_april_io.h" #include "bind_mtrand.h" #include "gpu_mirrored_memory_block.h" #include "matrixFloat.h" #include "mystring.h" #include "luabindmacros.h" #include "luabindutil.h" #include "utilLua.h" namespace Basics { /// Implements binding functions reusable in different Matrix flavors. template class MatrixBindings { static void parse_slice(const char *slice, int &a, int &b, const int min, const int max) { /* Impmentation in C of: a = slice:match("^([+-]?%d+)%:.*$") or min b = slice:match("^.*%:([+-]?%d+)$") or max */ bool neg_a = false, neg_b = false; // ^[+-]? if ( *slice == '+' || *slice == '-') { if ( *slice == '-') neg_a = true; ++slice; } // ^: if ( *slice == ':') { a = min; ++slice; } else { // %d+: const char *next = strchr(slice, ':'); if (next == NULL) ERROR_EXIT(256, "Unable to locate ':' character\n"); a = atoi(slice); slice = next+1; } // [+-]? if ( *slice == '+' || *slice == '-') { if ( *slice == '-' ) neg_b = true; ++slice; } // empty string if ( *slice == '\0' ) { b = max; } // %d+ else { b = atoi(slice); } if (neg_a) a = -a; if (neg_b) b = -b; } static void extract_range(lua_State *L, const int n, const int k, int &a, int &b, const int min, const int max) { int tt = lua_type(L, n); if (tt == LUA_TTABLE) { const int len = lua_rawlen(L, n); if (len == 0) { a = min; b = max; } else if (len == 2) { lua_rawgeti(L, n, 1); a = lua_toint(L, -1); lua_pop(L, 1); lua_rawgeti(L, n, 2); b = lua_toint(L, -1); lua_pop(L, 1); } else { ERROR_EXIT1(256, "The table for dimension %d must contain two numbers or none\n", k+1); } } // if (tt == LUA_TTABLE) else if (tt == LUA_TNUMBER) { a = b = lua_toint(L, n); } else if (tt == LUA_TSTRING) { const char *slice = lua_tostring(L, n); MatrixBindings::parse_slice(slice, a, b, min, max); } else { // not a table, not a number and neither a string :S ERROR_EXIT1(256, "The argument %d is not a table neither a string or a number\n", k+1); } if (a < 0) a = max + a + 1; if (b < 0) b = max + b + 1; if (a < min || a > max) { ERROR_EXIT2(256, "Range limit %d out of bounds for dim %d\n", a, k+1); } if (b < min || b > max) { ERROR_EXIT2(256, "Range limit %d out of bounds for dim %d\n", b, k+1); } if (a > b) { ERROR_EXIT(256, "Expecting an increasing range\n"); } } static Matrix *buildMatrixSliceFromTable(lua_State *L, const int n, Matrix *obj) { const int len = lua_rawlen(L, n); if (len == 0) return obj; const int ndims = obj->getNumDim(); const int *dims = obj->getDimPtr(); if (len > ndims) { ERROR_EXIT(128, "Number of dimensions out-of-bounds\n"); } AprilUtils::UniquePtr coords = new int[ndims]; AprilUtils::UniquePtr sizes = new int[ndims]; int a=0, b=0; for (int i=1, k=0; i<=len; ++i, ++k) { lua_rawgeti(L, n, i); MatrixBindings::extract_range(L, -1, k, a, b, 1, dims[k]); coords[k] = a - 1; // -1 because in C we start at 0 sizes[k] = b - a + 1; lua_pop(L, 1); } // for (int i=2, k=0; i<=n; ++i, ++k) for (int k=len; k(obj, coords.get(), sizes.get(), false); } static Matrix *buildMatrixSliceFromArgs(lua_State *L, const int first, Matrix *obj) { const int n = lua_gettop(L); const int given_ndims = n - first + 1; if (given_ndims == 0) return obj; const int ndims = obj->getNumDim(); const int *dims = obj->getDimPtr(); if (given_ndims > ndims) { ERROR_EXIT(128, "Number of dimensions out-of-bounds\n"); } AprilUtils::UniquePtr coords = new int[ndims]; AprilUtils::UniquePtr sizes = new int[ndims]; int a=0, b=0; for (int i=first, k=0; i<=n; ++i, ++k) { MatrixBindings::extract_range(L, i, k, a, b, 1, dims[k]); coords[k] = a - 1; // -1 because in C we start at 0 sizes[k] = b - a + 1; } // for (int i=2, k=0; i<=n; ++i, ++k) for (int k=given_ndims; k(obj, coords.get(), sizes.get(), false); } class LuaFunctionWrapper { public: LuaFunctionWrapper(lua_State *L, int n) : L(L), n(n) {} Matrix *operator()(Matrix *a, const Matrix *b) const { lua_pushvalue(L,n); lua_push(L,a); lua_push(L,const_cast*>(b)); if (lua_pcall(L, 2, 1, 0) != LUA_OK) { AprilUtils::string str(lua_tostring(L,-1)); lua_pop(L,1); ERROR_EXIT1(128, "%s", str.c_str()); } AprilUtils::SharedPtr< Matrix > c = lua_to*>(L,-1); lua_pop(L,1); return c.weakRelease(); } private: mutable lua_State *L; const int n; // position at Lua stack }; template static K lua_rawto(lua_State *L, int n) { return AprilUtils::LuaTable::lua_rawgetudata(L,n); } template static bool lua_is(lua_State *L, int n) { return AprilUtils::LuaTable::checkType(L,n); } template static K lua_to(lua_State *L, int n) { if (!lua_is(L,n)) { ERROR_EXIT1(128, "Incorrect argument type at position %d\n", n); } return AprilUtils::LuaTable::convertTo(L, n); } template static K lua_opt(lua_State *L, int n, K default_value) { if (lua_isnil(L, n) || lua_type(L, n) == LUA_TNONE) return default_value; else return lua_to(L,n); } template static void lua_push(lua_State *L, K obj) { AprilUtils::LuaTable::pushInto(L, obj); } #define FUNCTION_NAME "read_vector" template static K *read_vector(lua_State *L, const char *key, int num_dim, K add) { AprilUtils::UniquePtr v; lua_getfield(L, 1, key); if (!lua_isnil(L, -1)) { LUABIND_CHECK_PARAMETER(-1, table); int table_len; LUABIND_TABLE_GETN(-1, table_len); if (table_len != num_dim) LUABIND_FERROR3("Table '%s' with incorrect size, expected %d, found %d", key, num_dim, table_len); v = new K[num_dim]; for(int i=0; i < num_dim; i++) { lua_rawgeti(L, -1, i+1); v[i] = lua_to(L,-1) + add; lua_pop(L,1); } } lua_pop(L, 1); return v.release(); } #undef FUNCTION_NAME static int sliding_window_iterator_function(lua_State *L) { typename Matrix::sliding_window *obj = lua_to::sliding_window*>(L,1); if (obj->isEnd()) { lua_pushnil(L); return 1; } Matrix *mat = obj->getMatrix(); lua_push(L, mat); obj->next(); return 1; } public: #define BEGIN_METHOD(name) static int name(lua_State *L, Matrix *obj) #define BEGIN_CLASS_METHOD(name) static int name(lua_State *L) #define BEGIN_SW_METHOD(name) static int name(lua_State *L, typename Matrix::sliding_window *obj) ////////////////////////////////////////////////////////////////////////// #define FUNCTION_NAME "sliding_window binding" BEGIN_SW_METHOD(get_matrix) { lua_push(L, obj->getMatrix(lua_opt*>(L, 1, 0))); return 1; } BEGIN_SW_METHOD(next) { lua_push(L, obj->next()); return 1; } BEGIN_SW_METHOD(set_at_window) { int windex; LUABIND_CHECK_ARGN(==,1); LUABIND_GET_PARAMETER(1, int, windex); if (windex < 1) LUABIND_ERROR("Index must be >= 1\n"); obj->setAtWindow(windex-1); lua_push(L, obj); return 1; } BEGIN_SW_METHOD(num_windows) { lua_push(L, obj->numWindows()); return 1; } BEGIN_SW_METHOD(coords) { LUABIND_VECTOR_TO_NEW_TABLE(int, obj->getCoords(), obj->getNumDim()); return 1; } BEGIN_SW_METHOD(is_end) { lua_push(L, obj->isEnd()); return 1; } BEGIN_SW_METHOD(iterate) { LUABIND_CHECK_ARGN(==, 0); lua_pushcfunction(L, MatrixBindings::sliding_window_iterator_function); lua_push(L, obj); return 2; } #undef FUNCTION_NAME ////////////////////////////////////////////////////////////////////////// #define FUNCTION_NAME "matrix binding" BEGIN_CLASS_METHOD(MMapped) { bool aux = AprilMath::GPUMirroredMemoryBlockBase::getUseMMapAllocation(); AprilMath::GPUMirroredMemoryBlockBase::setUseMMapAllocation(true); int n = MatrixBindings::constructor(L); AprilMath::GPUMirroredMemoryBlockBase::setUseMMapAllocation(aux); return n; } BEGIN_CLASS_METHOD(constructor) { if (typeid(T) == typeid(char) && lua_type(L,1) == LUA_TSTRING) { // for matrixChar case int len = luaL_len(L,1); const char *data = lua_tostring(L,1); AprilUtils::UniquePtr dim = new int[1]; dim[0] = len; AprilUtils::SharedPtr > obj = new Matrix(1, dim.get()); for (typename Matrix::iterator it(obj->begin()); it != obj->end(); ++it, ++data) { april_assert(data != '\0'); *it = static_cast(*data); } lua_push(L, obj.get()); } else { int i,argn; argn = lua_gettop(L); // number of arguments LUABIND_CHECK_ARGN(>=, 1); int ndims = (!lua_isnumber(L,argn)) ? argn-1 : argn; AprilUtils::UniquePtr dim; if (ndims == 0) { // caso matrix{valores} o matrix(block) ndims = 1; dim = new int[ndims]; dim[0] = -1; } else { dim = new int[ndims]; for (i=1; i <= ndims; i++) { if (!lua_isnumber(L,i)) // TODO: Este mensaje de error parece que no es correcto... y no se todavia por que!!! LUABIND_FERROR2("incorrect argument to matrix dimension (arg %d must" " be a number and is a %s)", i, lua_typename(L,i)); dim[i-1] = (int)lua_tonumber(L,i); if (dim[i-1] <= 0) LUABIND_FERROR1("incorrect argument to matrix dimension (arg %d must be >0)",i); } } AprilUtils::SharedPtr< Matrix > obj; if (lua_is*>(L,argn)) { AprilUtils::SharedPtr< AprilMath::GPUMirroredMemoryBlock > block; block = lua_to*>(L, argn); if (dim[0] == -1) dim[0] = block->getSize(); obj = new Matrix(ndims, dim.get(), block.get()); } else { if (lua_istable(L,argn)) { if (dim[0] == -1) LUABIND_TABLE_GETN(1, dim[0]); obj = new Matrix(ndims, dim.get()); int i=1; int len; LUABIND_TABLE_GETN(argn, len); if (len != obj->size()) { LUABIND_FERROR2("Incorrect number of elements at the given table, " "found %d, expected %d", len, obj->size()); } for (typename Matrix::iterator it(obj->begin()); it != obj->end(); ++it, ++i) { lua_rawgeti(L,argn,i); /* if (!check_number(L,-1,*it)) */ if (!lua_is(L, -1)) { LUABIND_FERROR1("The given table has an invalid value at position" " %d, check table size and its content", i); } *it = lua_to(L, -1); lua_remove(L,-1); } // for each matrix position } // if lua_istable(L,argn) else { if (ndims == 1 && dim[0] == -1) { LUABIND_ERROR("Incorrect matrix dimensions"); } obj = new Matrix(ndims, dim.get()); if (typeid(T) == typeid(char) && lua_type(L,argn) == LUA_TSTRING) { // for matrixChar case int len = luaL_len(L,argn); if (len != obj->size()) { LUABIND_ERROR("Not matching sizes"); } const char *data = lua_tostring(L,argn); for (typename Matrix::iterator it(obj->begin()); it != obj->end(); ++it, ++data) { april_assert(data != '\0'); *it = static_cast(*data); } } } } // else { !lua_is(L,argn) } lua_push(L, obj.get()); } return 1; } BEGIN_METHOD(convert_to) { LUABIND_CHECK_ARGN(==,1); const char *type; LUABIND_GET_PARAMETER(1, string, type); if (!strcmp(type,"float")) { Matrix *obj2 = AprilMath::MatrixExt::Misc:: matConvertTo(obj); lua_push(L, obj2); } else if (!strcmp(type,"bool")) { Matrix *obj2 = AprilMath::MatrixExt::Misc:: matConvertTo(obj); lua_push(L, obj2); } else if (!strcmp(type,"int32")) { Matrix *obj2 = AprilMath::MatrixExt::Misc:: matConvertTo(obj); lua_push(L, obj2); } else if (!strcmp(type,"double")) { Matrix *obj2 = AprilMath::MatrixExt::Misc:: matConvertTo(obj); lua_push(L, obj2); } else if (!strcmp(type,"char")) { Matrix *obj2 = AprilMath::MatrixExt::Misc:: matConvertTo(obj); lua_push(L, obj2); } else if (!strcmp(type,"complex")) { Matrix *obj2 = AprilMath::MatrixExt::Misc:: matConvertTo(obj); lua_push(L, obj2); } else { LUABIND_FERROR1("Not implemented casting for type %s", type); } return 1; } BEGIN_METHOD(rewrap) { LUABIND_CHECK_ARGN(>=, 1); int ndims; ndims = lua_gettop(L); // number of dimensions bool clone_if_not_contiguous = false; if (lua_isboolean(L, ndims)) { LUABIND_GET_PARAMETER(ndims, boolean, clone_if_not_contiguous); --ndims; } AprilUtils::UniquePtr dims( new int[ndims] ); for (int i=1; i <= ndims; i++) { LUABIND_GET_PARAMETER(i, int, dims[i-1]); if (dims[i-1] <= 0) { LUABIND_FERROR1("incorrect argument to matrix dimension " "(arg %d must be >0)",i); } } Matrix *new_obj = obj->rewrap(dims.get(), ndims, clone_if_not_contiguous); lua_push(L, new_obj); return 1; } BEGIN_METHOD(get_reference_string) { char buff[128]; sprintf(buff,"%p data= %p", (void*)obj, (void*)obj->getRawDataAccess()); lua_pushstring(L, buff); return 1; } BEGIN_METHOD(copy_from_table) { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); int veclen; LUABIND_TABLE_GETN(1, veclen); if (veclen != obj->size()) LUABIND_FERROR2("wrong size %d instead of %d",veclen,obj->size()); int i=1; for (typename Matrix::iterator it(obj->begin()); it != obj->end(); ++it, ++i) { lua_rawgeti(L,1,i); if (!lua_is(L,-1)) { LUABIND_FERROR1("The given table has a no number value at position %d, " "the table could be smaller than matrix size", i); } *it = lua_to(L,-1); lua_remove(L,-1); } lua_push(L, obj); return 1; } BEGIN_METHOD(get) { const Matrix *cobj = obj; int argn = lua_gettop(L); // number of arguments if (argn != cobj->getNumDim()) LUABIND_FERROR2("wrong size %d instead of %d",argn,cobj->getNumDim()); T ret; if (cobj->getNumDim() == 1) { int v1; LUABIND_GET_PARAMETER(1,int,v1); if (v1<1 || v1 > cobj->getDimSize(0)) { LUABIND_FERROR2("wrong index parameter 1, %d is not <= %d", v1, cobj->getDimSize(0)); } ret = (*cobj)(v1-1); } else if (cobj->getNumDim() == 2) { int v1, v2; LUABIND_GET_PARAMETER(1,int,v1); LUABIND_GET_PARAMETER(2,int,v2); if (v1<1 || v1 > cobj->getDimSize(0)) { LUABIND_FERROR2("wrong index parameter 1, %d is not <= %d or is not >= 1", v1, cobj->getDimSize(0)); } if (v2<1 || v2 > cobj->getDimSize(1)) { LUABIND_FERROR2("wrong index parameter 2, %d is not <= %d or is not >= 1", v2, cobj->getDimSize(1)); } ret = (*cobj)(v1-1, v2-1); } else { AprilUtils::UniquePtr coords( new int[cobj->getNumDim()] ); for (int i=0; igetNumDim(); ++i) { LUABIND_GET_PARAMETER(i+1,int,coords[i]); if (coords[i]<1 || coords[i] > cobj->getDimSize(i)) { LUABIND_FERROR2("wrong index parameter %d, %d is not <= %d or is not >= 1", coords[i], cobj->getDimSize(i)); } coords[i]--; } ret = (*cobj)(coords.get(), cobj->getNumDim()); } lua_push(L, ret); return 1; } BEGIN_METHOD(set) { int argn = lua_gettop(L); // number of arguments if (argn != obj->getNumDim()+1) LUABIND_FERROR2("wrong size %d instead of %d",argn,obj->getNumDim()+1); T f; if (obj->getNumDim() == 1) { int v1; LUABIND_GET_PARAMETER(1,int,v1); if (v1<1 || v1 > obj->getDimSize(0)) { LUABIND_FERROR2("wrong index parameter: 1 <= %d <= %d is incorrect", v1, obj->getDimSize(0)); } f = lua_to(L, obj->getNumDim()+1); (*obj)(v1-1) = f; } else if (obj->getNumDim() == 2) { int v1, v2; LUABIND_GET_PARAMETER(1,int,v1); LUABIND_GET_PARAMETER(2,int,v2); if (v1<1 || v1 > obj->getDimSize(0)) { LUABIND_FERROR2("wrong index parameter: 1 <= %d <= %d is incorrect", v1, obj->getDimSize(0)); } if (v2<1 || v2 > obj->getDimSize(1)) { LUABIND_FERROR2("wrong index parameter: 2 <= %d <= %d is incorrect", v2, obj->getDimSize(1)); } f = lua_to(L, obj->getNumDim()+1); (*obj)(v1-1, v2-1) = f; } else { AprilUtils::UniquePtr coords( new int[obj->getNumDim()] ); for (int i=0; igetNumDim(); ++i) { LUABIND_GET_PARAMETER(i+1,int,coords[i]); if (coords[i]<1 || coords[i] > obj->getDimSize(i)) { LUABIND_FERROR2("wrong index parameter: 1 <= %d <= %d is incorrect", coords[i], obj->getDimSize(i)); } coords[i]--; } f = lua_to(L, obj->getNumDim()+1); (*obj)(coords.get(), obj->getNumDim()) = f; } lua_push(L, obj); return 1; } BEGIN_METHOD(raw_get) { int raw_pos; LUABIND_GET_PARAMETER(1, int, raw_pos); lua_push(L, (*obj)[raw_pos]); return 1; } BEGIN_METHOD(raw_set) { int raw_pos; LUABIND_GET_PARAMETER(1, int, raw_pos); T value = lua_to(L, 2); (*obj)[raw_pos] = value; lua_push(L, obj); return 1; } BEGIN_METHOD(set_use_cuda) { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, bool); bool v; LUABIND_GET_PARAMETER(1,bool, v); obj->setUseCuda(v); lua_push(L, obj); return 1; } BEGIN_METHOD(dim) { LUABIND_CHECK_ARGN(>=, 0); LUABIND_CHECK_ARGN(<=, 1); int pos; const int *d=obj->getDimPtr(); LUABIND_GET_OPTIONAL_PARAMETER(1, int, pos, -1); if (pos < 1) { AprilUtils::LuaTable vec(d, obj->getNumDim(), L); vec.pushTable(L); } else { lua_pushint(L, d[pos-1]); } return 1; } BEGIN_METHOD(stride) { LUABIND_CHECK_ARGN(>=, 0); LUABIND_CHECK_ARGN(<=, 1); int pos; const int *s=obj->getStridePtr(); LUABIND_GET_OPTIONAL_PARAMETER(1, int, pos, -1); if (pos < 1) { AprilUtils::LuaTable vec(s, obj->getNumDim(), L); vec.pushTable(L); } else { lua_pushint(L, s[pos-1]); } return 1; } BEGIN_METHOD(slice) { LUABIND_CHECK_ARGN(>=,2); LUABIND_CHECK_ARGN(<=,3); LUABIND_CHECK_PARAMETER(1, table); LUABIND_CHECK_PARAMETER(2, table); AprilUtils::UniquePtr coords, sizes; int coords_len, sizes_len; bool clone; LUABIND_TABLE_GETN(1, coords_len); LUABIND_TABLE_GETN(2, sizes_len); if (coords_len != sizes_len || coords_len != obj->getNumDim()) LUABIND_FERROR3("Incorrect number of dimensions, expected %d, " "found %d and %d\n", obj->getNumDim(), coords_len, sizes_len); coords = new int[coords_len]; sizes = new int[sizes_len]; LUABIND_TABLE_TO_VECTOR_SUB1(1, int, coords, coords_len); LUABIND_TABLE_TO_VECTOR(2, int, sizes, sizes_len); LUABIND_GET_OPTIONAL_PARAMETER(3, bool, clone, false); for (int i=0; i obj->getDimSize(i)) { LUABIND_FERROR1("Incorrect size or coord at position %d\n", i+1); } } Matrix *obj2 = new Matrix(obj, coords.get(), sizes.get(), clone); lua_push(L, obj2); return 1; } BEGIN_METHOD(select) { LUABIND_CHECK_ARGN(>=,2); LUABIND_CHECK_ARGN(<=,3); LUABIND_CHECK_PARAMETER(1, int); LUABIND_CHECK_PARAMETER(2, int); int dim, index; LUABIND_GET_PARAMETER(1, int, dim); LUABIND_GET_PARAMETER(2, int, index); Matrix *dest = lua_opt*>(L, 3, 0); Matrix *obj2 = obj->select(dim-1, index-1, dest); lua_push(L, obj2); return 1; } BEGIN_CLASS_METHOD(as) { LUABIND_CHECK_ARGN(==, 1); Matrix *m; m = lua_to*>(L, 1); lua_push(L, m->cloneOnlyDims()); return 1; } BEGIN_METHOD(transpose) { int argn; argn = lua_gettop(L); if (argn == 0) { lua_push(L, obj->transpose()); } else { int d1,d2; LUABIND_GET_PARAMETER(1, int, d1); LUABIND_GET_PARAMETER(2, int, d2); lua_push(L, obj->transpose(d1-1, d2-1)); } return 1; } BEGIN_CLASS_METHOD(deserialize) { check_table_fields(L, 1, "stride", "sizes", "data", "offset", (const char *)0); int offset; AprilUtils::UniquePtr sizes; AprilUtils::UniquePtr stride; AprilMath::GPUMirroredMemoryBlock *data; lua_getfield(L, 1, "data"); data = lua_to*>(L, -1); lua_pop(L, 1); lua_getfield(L, 1, "offset"); offset = lua_toint(L, -1); lua_pop(L, 1); lua_getfield(L, 1, "sizes"); int len = luaL_len(L, -1); sizes = new int[len]; stride = new int[len]; for (int i=0; i *obj; obj = new Matrix(len, sizes.get(), data, offset, stride.get()); lua_push*>(L, obj); return 1; } BEGIN_CLASS_METHOD(read) { AprilIO::StreamInterface *stream = lua_toAuxStreamInterface(L,1); if (!stream) LUABIND_ERROR("Needs a stream as first argument"); AprilUtils::SharedPtr ptr(stream); AprilUtils::LuaTable options(L,2); Matrix *obj = Matrix::read(ptr.get(), options); if (!obj) { LUABIND_ERROR("Error happens reading from file stream"); } else { lua_push*>(L, obj); } return 1; } BEGIN_CLASS_METHOD(fromMMap) { LUABIND_CHECK_ARGN(>=, 1); LUABIND_CHECK_ARGN(<=, 3); LUABIND_CHECK_PARAMETER(1, string); const char *filename; bool write, shared; LUABIND_GET_PARAMETER(1,string,filename); LUABIND_GET_OPTIONAL_PARAMETER(2,bool,write,true); LUABIND_GET_OPTIONAL_PARAMETER(3,bool,shared,true); AprilUtils::SharedPtr mmapped_data; mmapped_data = new AprilUtils::MMappedDataReader(filename,write,shared); Matrix *obj = Matrix::fromMMappedDataReader(mmapped_data.get()); lua_push*>(L, obj); return 1; } BEGIN_METHOD(toMMap) { LUABIND_CHECK_ARGN(==, 1); const char *filename; LUABIND_GET_PARAMETER(1, string, filename); AprilUtils::SharedPtr mmapped_data; mmapped_data = new AprilUtils::MMappedDataWriter(filename); obj->toMMappedDataWriter(mmapped_data.get()); return 0; } BEGIN_METHOD(map) { int argn; int N; argn = lua_gettop(L); // number of arguments N = argn-1; AprilUtils::UniquePtr* []> v; AprilUtils::UniquePtr::const_iterator []> list_it; if (N > 0) { v = new Matrix*[N]; list_it = new typename Matrix::const_iterator[N]; } for (int i=0; i*>(L, i+1)) { LUABIND_FERROR1("Expected a matrix at position: ", i+1); } v[i] = lua_rawto*>(L, i+1); if (!v[i]->sameDim(obj)) { LUABIND_ERROR("The given matrices must have the same dimension sizes\n"); } list_it[i] = v[i]->begin(); } LUABIND_CHECK_PARAMETER(argn, function); for (typename Matrix::iterator it(obj->begin()); it!=obj->end(); ++it) { // copy the Lua function, lua_call will pop this copy lua_pushvalue(L, argn); // push the self matrix value lua_push(L, *it); // push the value of the rest of given matrices for (int j=0; j(L, -1)) { LUABIND_ERROR("Incorrect returned value type"); } *it = lua_to(L, -1); } lua_pop(L, 1); } lua_push(L, obj); return 1; } BEGIN_METHOD(num_dim) { lua_push(L, obj->getNumDim()); return 1; } BEGIN_METHOD(to_index) { MatrixInt32 *m = AprilMath::MatrixExt::Misc::matNonZeroIndices(obj); lua_push(L, m); return 1; } BEGIN_METHOD(equals) { Matrix *other; float epsilon; other = lua_to*>(L,1); LUABIND_GET_OPTIONAL_PARAMETER(2, float, epsilon, 0.05f); // 5% error #ifdef USE_CUDA obj->sync(); other->sync(); #endif if (AprilMath::MatrixExt::Reductions::matEquals(obj, other, epsilon)) { lua_pushboolean(L, true); } else { lua_pushboolean(L, false); } return 1; } BEGIN_METHOD(add_to_shared_count) { unsigned int count; LUABIND_GET_PARAMETER(1,uint,count); obj->addToSharedCount(count); lua_push(L, obj); return 1; } BEGIN_METHOD(padding_all) { int padding; LUABIND_GET_PARAMETER(1, int, padding); T default_value = lua_opt(L, 2, AprilMath::Limits::zero()); Matrix *result = obj->padding(padding, default_value); lua_push(L, result); return 1; } BEGIN_METHOD(padding) { AprilUtils::UniquePtr begin_padding, end_padding; LUABIND_CHECK_ARGN(>=,obj->getNumDim()*2); LUABIND_CHECK_ARGN(<=,obj->getNumDim()*2 + 1); begin_padding = new int[obj->getNumDim()]; end_padding = new int[obj->getNumDim()]; int j=1; for (int i=0; igetNumDim(); ++i, j+=2) { LUABIND_GET_PARAMETER(j, int, begin_padding[i]); LUABIND_GET_PARAMETER(j+1, int, end_padding[i]); } T default_value = lua_opt(L, j, AprilMath::Limits::zero()); Matrix *result = obj->padding(begin_padding.get(), end_padding.get(), default_value); lua_push(L, result); return 1; } BEGIN_METHOD(uniform) { int lower, upper; AprilUtils::SharedPtr random; LUABIND_GET_PARAMETER(1, int, lower); LUABIND_GET_PARAMETER(2, int, upper); LUABIND_GET_OPTIONAL_PARAMETER(3, MTRand, random, 0); if (lower > upper) { LUABIND_ERROR("First argument must be <= second argument"); } if (!random) random = new Basics::MTRand(); for (typename Matrix::iterator it(obj->begin()); it != obj->end(); ++it) { *it = T(random->randInt(upper - lower)) + lower; } lua_push(L, obj); return 1; } BEGIN_METHOD(uniformf) { T lower = AprilMath::Limits::zero(), upper = AprilMath::Limits::one(); AprilUtils::SharedPtr random; LUABIND_GET_OPTIONAL_PARAMETER(1, float, lower, 0.0f); LUABIND_GET_OPTIONAL_PARAMETER(2, float, upper, 1.0f); LUABIND_GET_OPTIONAL_PARAMETER(3, MTRand, random, 0); if (lower > upper) { LUABIND_ERROR("First argument must be <= second argument"); } if (!random) random = new Basics::MTRand(); for (typename Matrix::iterator it(obj->begin()); it != obj->end(); ++it) { *it = T(random->rand(upper - lower) + lower); } lua_push(L, obj); return 1; } BEGIN_METHOD(linspace) { int size_1 = obj->size()-1; T inf = lua_opt(L, 1, AprilMath::Limits::one()); T sup = lua_opt(L, 2, static_cast(size_1+1)); int i = 0; T diff = sup-inf; if (diff == size_1) { i = static_cast(inf); for (typename Matrix::iterator it(obj->begin()); it!=obj->end(); ++it, ++i) { april_assert(i <= static_cast(sup)); *it = static_cast(i); } } else { for (typename Matrix::iterator it(obj->begin()); it!=obj->end(); ++it, ++i) { *it = (diff*i)/size_1 + inf; } } lua_push(L, obj); return 1; } BEGIN_METHOD(logspace) { int size = obj->size()-1; T inf = lua_opt(L, 1, T(1.0f)); T sup = lua_opt(L, 2, T(size+1)); T base = lua_opt(L, 3, T(10.0f)); int i=0; inf = AprilMath::m_log(inf)/AprilMath::m_log(base); sup = AprilMath::m_log(sup)/AprilMath::m_log(base); T diff = sup-inf; for (typename Matrix::iterator it(obj->begin()); it!=obj->end(); ++it, ++i) { *it = AprilMath::m_pow(base, (diff*i)/size + inf); } lua_push(L, obj); return 1; } BEGIN_METHOD(linear) { int lower, step; LUABIND_GET_OPTIONAL_PARAMETER(1, int, lower, 0); LUABIND_GET_OPTIONAL_PARAMETER(2, int, step, 1); int k=lower; for (typename Matrix::iterator it(obj->begin()); it != obj->end(); ++it, k+=step) { *it = T(k); } lua_push(L, obj); return 1; } BEGIN_METHOD(sliding_window) { AprilUtils::UniquePtr sub_matrix_size, offset, step, num_steps, order_step; int argn = lua_gettop(L); // number of arguments const int num_dim = obj->getNumDim(); if (argn > 1) { LUABIND_ERROR("incorrect number of arguments"); } if (argn == 1) { LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L, 1, "offset", "size", "step", "numSteps", "orderStep", (const char*)0); offset = read_vector(L, "offset", num_dim, 0); sub_matrix_size = read_vector(L, "size", num_dim, 0); step = read_vector(L, "step", num_dim, 0); num_steps = read_vector(L, "numSteps", num_dim, 0); order_step = read_vector(L, "orderStep", num_dim, -1); } typename Matrix::sliding_window *window = new typename Matrix::sliding_window(obj, sub_matrix_size.get(), offset.get(), step.get(), num_steps.get(), order_step.get()); lua_push(L, window); return 1; } BEGIN_METHOD(adjust_range) { T rmin = lua_to(L,1); T rmax = lua_to(L,2); lua_push(L, AprilMath::MatrixExt::Operations:: matAdjustRange(obj, rmin, rmax)); return 1; } BEGIN_METHOD(size) { lua_push(L, obj->size()); return 1; } BEGIN_METHOD(squeeze) { lua_push(L, obj->squeeze()); return 1; } BEGIN_METHOD(left_inflate) { lua_push(L, obj->leftInflate(luaL_optint(L,1,1))); return 1; } BEGIN_METHOD(right_inflate) { lua_push(L, obj->rightInflate(luaL_optint(L,1,1))); return 1; } BEGIN_METHOD(offset) { lua_push(L, obj->getOffset()); return 1; } BEGIN_METHOD(get_use_cuda) { lua_push(L, obj->getCudaFlag()); return 1; } BEGIN_METHOD(clone) { lua_push(L, obj->clone()); return 1; } BEGIN_METHOD(isfinite) { lua_push(L, AprilMath::MatrixExt::Reductions::matIsFinite(obj)); return 1; } BEGIN_METHOD(toTable) { AprilUtils::LuaTable t(L); int i=1; for(typename Matrix::const_iterator it = obj->begin(); it != obj->end(); ++it, ++i) { t[i] = *it; } t.pushTable(L); return 1; } BEGIN_METHOD(contiguous) { lua_push(L, obj->getIsContiguous() ? obj : obj->clone()); return 1; } BEGIN_METHOD(diagonalize) { lua_push(L, obj->diagonalize()); return 1; } BEGIN_METHOD(get_shared_count) { lua_push(L, obj->getSharedCount()); return 1; } BEGIN_METHOD(reset_shared_count) { obj->resetSharedCount(); lua_push(L, obj); return 1; } BEGIN_METHOD(sync) { obj->sync(); lua_push(L, obj); return 1; } BEGIN_METHOD(is_contiguous) { lua_push(L, obj->getIsContiguous()); return 1; } BEGIN_METHOD(prune_subnormal_and_check_normal) { obj->pruneSubnormalAndCheckNormal(); lua_push(L, obj); return 1; } BEGIN_METHOD(diag) { LUABIND_CHECK_ARGN(==,1); T v = lua_to(L,1); AprilMath::MatrixExt::Initializers::matDiag(obj, v); lua_push(L, obj); return 1; } BEGIN_METHOD(fill) { LUABIND_CHECK_ARGN(==, 1); T value; if (lua_is*>(L,1)) { Matrix *aux = lua_rawto*>(L,1); for (int i=0; igetNumDim(); ++i) { if (aux->getDimSize(i) != 1) { LUABIND_ERROR("Needs a number or a matrix with only one element\n"); } } value = *(aux->begin()); } else { value = lua_to(L,1); } lua_push(L, AprilMath::MatrixExt::Initializers::matFill(obj,value)); return 1; } BEGIN_METHOD(zeros) { lua_push(L, AprilMath::MatrixExt::Initializers::matZeros(obj)); return 1; } BEGIN_METHOD(ones) { lua_push(L, AprilMath::MatrixExt::Initializers::matOnes(obj)); return 1; } BEGIN_METHOD(min) { #ifdef USE_CUDA obj->sync(); #endif LUABIND_CHECK_ARGN(>=,0); LUABIND_CHECK_ARGN(<=,3); int argn = lua_gettop(L); if (argn > 0) { // case over a dimension int dim; LUABIND_GET_PARAMETER(1, int, dim); AprilUtils::SharedPtr > dest; AprilUtils::SharedPtr > argmin; dest = lua_opt*>(L,2,0); argmin = lua_opt(L,3,0); AprilUtils::UniquePtr aux; if (!argmin) { aux = new int[obj->getNumDim()]; for (int i=0; igetNumDim(); ++i) aux[i] = obj->getDimSize(i); aux[dim-1] = 1; argmin = new Matrix(obj->getNumDim(), aux.get()); } if (dim < 1 || dim > obj->getNumDim()) { LUABIND_FERROR2("Incorrect dimension, found %d, expect in [1,%d]", dim, obj->getNumDim()); } lua_push(L, AprilMath::MatrixExt::Reductions:: matMin(obj, dim-1, dest.get(), argmin.get())); lua_push(L, argmin.get()); } else { // case over whole matrix int arg_min, raw_pos; lua_push(L, AprilMath::MatrixExt::Reductions:: matMin(obj, arg_min, raw_pos)); lua_push(L, arg_min+1); } return 2; } BEGIN_METHOD(max) { #ifdef USE_CUDA obj->sync(); #endif LUABIND_CHECK_ARGN(>=,0); LUABIND_CHECK_ARGN(<=,3); int argn = lua_gettop(L); if (argn > 0) { // case over a dimension int dim; LUABIND_GET_PARAMETER(1, int, dim); AprilUtils::SharedPtr > dest; AprilUtils::SharedPtr > argmax; dest = lua_opt*>(L,2,0); argmax = lua_opt(L,3,0); AprilUtils::UniquePtr aux; if (!argmax) { aux = new int[obj->getNumDim()]; for (int i=0; igetNumDim(); ++i) aux[i] = obj->getDimSize(i); aux[dim-1] = 1; argmax = new Matrix(obj->getNumDim(), aux.get()); } if (dim < 1 || dim > obj->getNumDim()) { LUABIND_FERROR2("Incorrect dimension, found %d, expect in [1,%d]", dim, obj->getNumDim()); } lua_push(L, AprilMath::MatrixExt::Reductions:: matMax(obj, dim-1, dest.get(), argmax.get())); lua_push(L, argmax.get()); } else { // case over whole matrix int arg_max, raw_pos; lua_push(L, AprilMath::MatrixExt::Reductions:: matMax(obj, arg_max, raw_pos)); lua_push(L, arg_max+1); } return 2; } BEGIN_METHOD(clamp) { LUABIND_CHECK_ARGN(==, 2); T lower = lua_to(L,1), upper = lua_to(L,2); lua_push(L, AprilMath::MatrixExt::Operations:: matClamp(obj, lower, upper)); return 1; } BEGIN_METHOD(floor) { lua_push(L, AprilMath::MatrixExt::Operations:: matFloor(obj)); return 1; } BEGIN_METHOD(ceil) { lua_push(L, AprilMath::MatrixExt::Operations:: matCeil(obj)); return 1; } BEGIN_METHOD(round) { lua_push(L, AprilMath::MatrixExt::Operations:: matRound(obj)); return 1; } BEGIN_METHOD(add) { int argn; argn = lua_gettop(L); // number of arguments LUABIND_CHECK_ARGN(==, 1); Matrix *mat = lua_to*>(L,1); if (!obj->sameDim(mat)) { LUABIND_ERROR("matrix add wrong dimensions"); } #ifdef USE_CUDA mat->sync(); #endif lua_push(L, AprilMath::MatrixExt::Misc:: matAddition(obj, mat)); return 1; } BEGIN_METHOD(scalar_add) { int argn; argn = lua_gettop(L); // number of arguments LUABIND_CHECK_ARGN(==, 1); T scalar = lua_to(L, 1); lua_push(L, AprilMath::MatrixExt::Operations:: matScalarAdd(obj, scalar)); return 1; } BEGIN_METHOD(sub) { LUABIND_CHECK_ARGN(==, 1); Matrix *mat = lua_to*>(L, 1); if (!obj->sameDim(mat)) { LUABIND_ERROR("incompatible dimensions"); } #ifdef USE_CUDA mat->sync(); #endif lua_push(L, AprilMath::MatrixExt::Misc:: matSubstraction(obj, mat)); return 1; } BEGIN_METHOD(mul) { LUABIND_CHECK_ARGN(==, 1); Matrix *mat = lua_to*>(L, 1); #ifdef USE_CUDA mat->sync(); #endif lua_push(L, AprilMath::MatrixExt::Misc:: matMultiply(obj, mat)); return 1; } BEGIN_METHOD(cmul) { LUABIND_CHECK_ARGN(==, 1); Matrix *mat = lua_to*>(L, 1); #ifdef USE_CUDA mat->sync(); #endif lua_push(L, AprilMath::MatrixExt::Operations:: matCmul(obj, mat)); return 1; } BEGIN_METHOD(plogp) { lua_push(L, AprilMath::MatrixExt::Operations::matPlogp(obj)); return 1; } BEGIN_METHOD(log) { lua_push(L, AprilMath::MatrixExt::Operations::matLog(obj)); return 1; } BEGIN_METHOD(log1p) { lua_push(L, AprilMath::MatrixExt::Operations::matLog1p(obj)); return 1; } BEGIN_METHOD(exp) { lua_push(L, AprilMath::MatrixExt::Operations::matExp(obj)); return 1; } BEGIN_METHOD(expm1) { lua_push(L, AprilMath::MatrixExt::Operations::matExpm1(obj)); return 1; } BEGIN_METHOD(sqrt) { lua_push(L, AprilMath::MatrixExt::Operations::matSqrt(obj)); return 1; } BEGIN_METHOD(pow) { T value = lua_to(L, 1); lua_push(L, AprilMath::MatrixExt::Operations::matPow(obj, value)); return 1; } BEGIN_METHOD(tan) { lua_push(L, AprilMath::MatrixExt::Operations::matTan(obj)); return 1; } BEGIN_METHOD(tanh) { lua_push(L, AprilMath::MatrixExt::Operations::matTanh(obj)); return 1; } BEGIN_METHOD(atan) { lua_push(L, AprilMath::MatrixExt::Operations::matAtan(obj)); return 1; } BEGIN_METHOD(atanh) { lua_push(L, AprilMath::MatrixExt::Operations::matAtanh(obj)); return 1; } BEGIN_METHOD(sin) { lua_push(L, AprilMath::MatrixExt::Operations::matSin(obj)); return 1; } BEGIN_METHOD(sinh) { lua_push(L, AprilMath::MatrixExt::Operations::matSinh(obj)); return 1; } BEGIN_METHOD(asin) { lua_push(L, AprilMath::MatrixExt::Operations::matAsin(obj)); return 1; } BEGIN_METHOD(asinh) { lua_push(L, AprilMath::MatrixExt::Operations::matAsinh(obj)); return 1; } BEGIN_METHOD(cos) { lua_push(L, AprilMath::MatrixExt::Operations::matCos(obj)); return 1; } BEGIN_METHOD(cosh) { lua_push(L, AprilMath::MatrixExt::Operations::matCosh(obj)); return 1; } BEGIN_METHOD(acos) { lua_push(L, AprilMath::MatrixExt::Operations::matAcos(obj)); return 1; } BEGIN_METHOD(acosh) { lua_push(L, AprilMath::MatrixExt::Operations::matAcosh(obj)); return 1; } BEGIN_METHOD(abs) { lua_push(L, AprilMath::MatrixExt::Operations::matAbs(obj)); return 1; } BEGIN_METHOD(complement) { lua_push(L, AprilMath::MatrixExt::Operations::matComplement(obj)); return 1; } BEGIN_METHOD(cinv) { lua_push(L, AprilMath::MatrixExt::Operations:: matDiv(obj, AprilMath::Limits::one())); return 1; } BEGIN_METHOD(sign) { lua_push(L, AprilMath::MatrixExt::Operations::matSign(obj)); return 1; } BEGIN_METHOD(sum) { #ifdef USE_CUDA obj->sync(); #endif LUABIND_CHECK_ARGN(>=, 0); LUABIND_CHECK_ARGN(<=, 2); int argn = lua_gettop(L); // number of arguments if (argn > 0 && !lua_isnil(L,1)) { int dim; LUABIND_GET_PARAMETER(1, int, dim); Matrix *dest = lua_opt*>(L, 2, 0); if (dim < 1 || dim > obj->getNumDim()) { LUABIND_FERROR2("Incorrect dimension, found %d, expect in [1,%d]", dim, obj->getNumDim()); } lua_push(L, AprilMath::MatrixExt::Reductions:: matSum(obj, dim-1, dest)); } else { lua_push(L, AprilMath::MatrixExt::Reductions:: matSum(obj)); } return 1; } BEGIN_METHOD(prod) { #ifdef USE_CUDA obj->sync(); #endif LUABIND_CHECK_ARGN(>=, 0); LUABIND_CHECK_ARGN(<=, 2); int argn = lua_gettop(L); // number of arguments if (argn > 0 && !lua_isnil(L,1)) { int dim; LUABIND_GET_PARAMETER(1, int, dim); Matrix *dest = lua_opt*>(L, 2, 0); if (dim < 1 || dim > obj->getNumDim()) { LUABIND_FERROR2("Incorrect dimension, found %d, expect in [1,%d]", dim, obj->getNumDim()); } lua_push(L, AprilMath::MatrixExt::Reductions:: matProd(obj, dim-1, dest)); } else { lua_push(L, AprilMath::MatrixExt::Reductions:: matProd(obj)); } return 1; } BEGIN_METHOD(cumsum) { #ifdef USE_CUDA obj->sync(); #endif LUABIND_CHECK_ARGN(>=, 0); LUABIND_CHECK_ARGN(<=, 2); int dim; LUABIND_GET_OPTIONAL_PARAMETER(1, int, dim, 1); Matrix *dest = lua_opt*>(L, 2, 0); if (dim < 1 || dim > obj->getNumDim()) { LUABIND_FERROR2("Incorrect dimension, found %d, expect in [1,%d]", dim, obj->getNumDim()); } lua_push(L, AprilMath::MatrixExt::Reductions:: matCumSum(obj, dim-1, dest)); return 1; } BEGIN_METHOD(cumprod) { #ifdef USE_CUDA obj->sync(); #endif LUABIND_CHECK_ARGN(>=, 0); LUABIND_CHECK_ARGN(<=, 2); int dim; LUABIND_GET_OPTIONAL_PARAMETER(1, int, dim, 1); Matrix *dest = lua_opt*>(L, 2, 0); if (dim < 1 || dim > obj->getNumDim()) { LUABIND_FERROR2("Incorrect dimension, found %d, expect in [1,%d]", dim, obj->getNumDim()); } lua_push(L, AprilMath::MatrixExt::Reductions:: matCumProd(obj, dim-1, dest)); return 1; } BEGIN_METHOD(copy) { int argn; LUABIND_CHECK_ARGN(==, 1); Matrix *mat = lua_to*>(L, 1); #ifdef USE_CUDA mat->sync(); #endif lua_push(L, AprilMath::MatrixExt::BLAS::matCopy(obj,mat)); return 1; } BEGIN_METHOD(axpy) { int argn; LUABIND_CHECK_ARGN(==, 2); T alpha = lua_to(L, 1); if (lua_is*>(L, 2)) { Matrix *mat = lua_rawto*>(L, 2); #ifdef USE_CUDA mat->sync(); #endif lua_push(L, AprilMath::MatrixExt::BLAS::matAxpy(obj, alpha, mat)); } else if (lua_is*>(L, 2)) { SparseMatrix *mat = lua_to*>(L, 2); lua_push(L, AprilMath::MatrixExt::BLAS::matAxpy(obj, alpha, mat)); } else { LUABIND_ERROR("Expected matrix or sparse matrix as 2nd argument"); } return 1; } BEGIN_METHOD(gemm) { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L,1, "trans_A", "trans_B", "alpha", "A", "B", "beta", (const char *)0); bool trans_A, trans_B; LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, trans_A, bool, trans_A, false); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, trans_B, bool, trans_B, false); AprilUtils::LuaTable t(L, 1); T alpha = t["alpha"].opt( AprilMath::Limits::one() ); T beta = t["beta"].opt( AprilMath::Limits::one() ); Matrix *matA = t["A"].get*>(); Matrix *matB = t["B"].get*>(); #ifdef USE_CUDA matA->sync(); matB->sync(); #endif lua_push(L, AprilMath::MatrixExt::BLAS:: matGemm(obj, trans_A ? CblasTrans : CblasNoTrans, trans_B ? CblasTrans : CblasNoTrans, alpha, matA, matB, beta)); return 1; } BEGIN_METHOD(sparse_mm) { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L,1, "trans_A", "trans_B", "alpha", "A", "B", "beta", (const char *)0); bool trans_A, trans_B; LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, trans_A, bool, trans_A, false); LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, trans_B, bool, trans_B, false); AprilUtils::LuaTable t(L, 1); T alpha = t["alpha"].opt( AprilMath::Limits::one() ); T beta = t["beta"].opt( AprilMath::Limits::one() ); SparseMatrix *matA = t["A"].get*>(); Matrix *matB = t["B"].get*>(); lua_push(L, AprilMath::MatrixExt::BLAS:: matSparseMM(obj, trans_A ? CblasTrans : CblasNoTrans, trans_B ? CblasTrans : CblasNoTrans, alpha, matA, matB, beta)); return 1; } BEGIN_METHOD(gemv) { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L,1, "trans_A", "alpha", "A", "X", "beta", (const char *)0); bool trans_A; LUABIND_GET_TABLE_OPTIONAL_PARAMETER(1, trans_A, bool, trans_A, false); AprilUtils::LuaTable t(L, 1); T alpha = t["alpha"].opt( AprilMath::Limits::one() ); T beta = t["beta"].opt( AprilMath::Limits::one() ); Matrix *matX = t["X"].get*>(); lua_getfield(L, 1, "A"); if (lua_is*>(L,-1)) { Matrix *matA = lua_rawto*>(L,-1); lua_pop(L,1); #ifdef USE_CUDA matA->sync(); matX->sync(); #endif lua_push(L, AprilMath::MatrixExt::BLAS:: matGemv(obj, trans_A ? CblasTrans : CblasNoTrans, alpha, matA, matX, beta)); } else { SparseMatrix *matA = lua_to*>(L,-1); lua_pop(L,1); lua_push(L, AprilMath::MatrixExt::BLAS:: matGemv(obj, trans_A ? CblasTrans : CblasNoTrans, alpha, matA, matX, beta)); } return 1; } BEGIN_METHOD(ger) { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); check_table_fields(L,1, "alpha", "X", "Y", (const char *)0); AprilUtils::LuaTable t(L,1); T alpha = t["alpha"].opt( AprilMath::Limits::one() ); Matrix *matX = t["X"].get*>(); Matrix *matY = t["Y"].get*>(); #ifdef USE_CUDA matX->sync(); matY->sync(); #endif lua_push(L, AprilMath::MatrixExt::BLAS:: matGer(obj, alpha, matX, matY)); return 1; } BEGIN_METHOD(dot) { LUABIND_CHECK_ARGN(==, 1); if (lua_is*>(L, 1)) { Matrix *matX = lua_rawto*>(L, 1); #ifdef USE_CUDA obj->sync(); matX->sync(); #endif lua_push(L, AprilMath::MatrixExt::BLAS:: matDot(obj, matX)); } else if (lua_is*>(L, 2)) { SparseMatrix *matX = lua_to*>(L, 1); #ifdef USE_CUDA obj->sync(); matX->sync(); #endif lua_push(L, AprilMath::MatrixExt::BLAS:: matDot(obj, matX)); } return 1; } BEGIN_METHOD(scal) { LUABIND_CHECK_ARGN(==, 1); T value = lua_to(L, 1); lua_push(L, AprilMath::MatrixExt::Operations:: matScal(obj, value)); return 1; } BEGIN_METHOD(masked_fill) { MatrixBool *mask = lua_to(L, 1); T value = lua_to(L, 2); Matrix *dest = lua_opt*>(L, 3, 0); lua_push(L, AprilMath::MatrixExt::Operations:: matMaskedFill(obj, mask, value, dest)); return 1; } BEGIN_METHOD(masked_copy) { MatrixBool *mask = lua_to(L, 1); Matrix *value = lua_to*>(L, 2); Matrix *dest = lua_opt*>(L, 3, 0); lua_push(L, AprilMath::MatrixExt::Operations:: matMaskedCopy(obj, mask, value, dest)); return 1; } BEGIN_METHOD(div) { LUABIND_CHECK_ARGN(==, 1); if (lua_is*>(L, 1)) { Matrix *other = lua_rawto*>(L, 1); lua_push(L, AprilMath::MatrixExt::Operations:: matDiv(obj, other)); } else { T value = lua_to(L, 1); lua_push(L, AprilMath::MatrixExt::Operations:: matDiv(obj, value)); } return 1; } BEGIN_METHOD(idiv) { LUABIND_CHECK_ARGN(==, 1); if (lua_is*>(L, 1)) { Matrix *other = lua_rawto*>(L, 1); lua_push(L, AprilMath::MatrixExt::Operations:: matDiv(obj, other)); } else { T value = lua_to(L, 1); lua_push(L, AprilMath::MatrixExt::Operations:: matIDiv(obj, value)); } return 1; } BEGIN_METHOD(mod) { LUABIND_CHECK_ARGN(==, 1); if (lua_is*>(L, 1)) { Matrix *other = lua_rawto*>(L, 1); lua_push(L, AprilMath::MatrixExt::Operations:: matMod(obj, other)); } else { T value = lua_to(L, 1); lua_push(L, AprilMath::MatrixExt::Operations:: matMod(obj, value)); } return 1; } BEGIN_METHOD(norm2) { #ifdef USE_CUDA obj->sync(); #endif lua_push(L, AprilMath::MatrixExt::BLAS:: matNorm2(obj)); return 1; } BEGIN_METHOD(inv) { lua_push(L, AprilMath::MatrixExt::LAPACK:: matInv(obj)); return 1; } BEGIN_METHOD(logdet) { T sign; lua_push(L, AprilMath::MatrixExt::LAPACK:: matLogDeterminant(obj, sign).log()); lua_push(L, sign); return 2; } BEGIN_METHOD(det) { lua_push(L, AprilMath::MatrixExt::LAPACK:: matDeterminant(obj)); return 1; } BEGIN_METHOD(cholesky) { char uplo; LUABIND_GET_OPTIONAL_PARAMETER(1, char, uplo, 'U'); uplo = toupper(uplo); if (uplo != 'U' && uplo != 'L') { LUABIND_ERROR("Incorrect argument, expected character L or U"); } lua_push(L, AprilMath::MatrixExt::LAPACK:: matCholesky(obj, uplo)); return 1; } BEGIN_METHOD(svd) { Matrix *U,*V; SparseMatrix *S; AprilMath::MatrixExt::LAPACK::matSVD(obj, &U, &S, &V); lua_push(L, U); lua_push(L, S); lua_push(L, V); return 3; } BEGIN_METHOD(lt) { if (lua_is*>(L, 1)) { Matrix *value = lua_rawto*>(L, 1); lua_push(L, AprilMath::MatrixExt::Boolean::matLT(obj, value)); } else { T value = lua_to(L, 1); lua_push(L, AprilMath::MatrixExt::Boolean::matLT(obj, value)); } return 1; } BEGIN_METHOD(gt) { if (lua_is*>(L, 1)) { Matrix *value = lua_rawto*>(L, 1); lua_push(L, AprilMath::MatrixExt::Boolean::matGT(obj, value)); } else { T value = lua_to(L, 1); lua_push(L, AprilMath::MatrixExt::Boolean::matGT(obj, value)); } return 1; } BEGIN_METHOD(eq) { if (lua_is*>(L, 1)) { Matrix *value = lua_rawto*>(L, 1); lua_push(L, AprilMath::MatrixExt::Boolean::matEQ(obj, value)); } else { T value = lua_to(L, 1); lua_push(L, AprilMath::MatrixExt::Boolean::matEQ(obj, value)); } return 1; } BEGIN_METHOD(neq) { if (lua_is*>(L, 1)) { Matrix *value = lua_rawto*>(L, 1); lua_push(L, AprilMath::MatrixExt::Boolean::matNEQ(obj, value)); } else { T value = lua_to(L, 1); lua_push(L, AprilMath::MatrixExt::Boolean::matNEQ(obj, value)); } return 1; } BEGIN_METHOD(data) { lua_push(L, obj->getRawDataAccess()); return 1; } BEGIN_METHOD(order) { MatrixInt32 *dest = lua_opt(L, 1, 0); dest = AprilMath::MatrixExt::Misc::matOrder(obj, dest); lua_push(L, dest); return 1; } BEGIN_METHOD(order_rank) { MatrixInt32 *dest = lua_opt(L, 1, 0); dest = AprilMath::MatrixExt::Misc::matOrderRank(obj, dest); lua_push(L, dest); return 1; } BEGIN_METHOD(stringfy) { OutputLuaStringStream stream(L); for (typename Matrix::const_iterator it = obj->begin(); it != obj->end(); ++it) { const T *str = &(*it); stream.put(str, sizeof(*it)); } stream.push(L); return 1; } BEGIN_METHOD(same_dim) { if (lua_is*>(L,1)) { Matrix *other = lua_rawto*>(L,1); lua_pushboolean(L, obj->sameDim(other)); return 1; } else { if (!lua_istable(L,1)) { LUABIND_ERROR("Expecting a matrix or a table as argument"); } bool result=true; int len = luaL_len(L,1); if (len != obj->getNumDim()) LUABIND_ERROR("Incorrect number of dimensions"); const int *dims = obj->getDimPtr(); for (int i=1; i<=len && result; ++i) { lua_rawgeti(L, 1, i); int j = lua_toint(L, -1); lua_pop(L, 1); if (j != dims[i-1]) result=false; } lua_pushboolean(L, result); return 1; } } BEGIN_METHOD(index) { Matrix *result; int dim = lua_to(L,1); if (lua_is*>(L,2)) { Matrix *idx = lua_rawto*>(L,2); result = AprilMath::MatrixExt::Misc:: matIndex(obj, dim-1, idx); // WARNING!!! -1 } else { AprilUtils::SharedPtr< Matrix > idx; if (lua_istable(L,2)) { lua_getglobal(L, "matrixInt32"); // dim table ... matrixInt32 lua_pushvalue(L, 2); // dim table ... matrixInt32 table if (lua_pcall(L, 1, 1, 0) != LUA_OK) { // dim table ... object AprilUtils::string str(lua_tostring(L,-1)); lua_pop(L,1); ERROR_EXIT1(128, "%s", str.c_str()); } idx = lua_rawto*>(L,-1); lua_pop(L,1); } else { if (!lua_is*>(L,2)) { ERROR_EXIT(128, "Expecting matrixInt32 as second argument\n"); } idx = lua_rawto*>(L,2); } result = AprilMath::MatrixExt::Misc:: matIndex(obj, dim-1, idx.get()); // WARNING!!! -1 } lua_push(L, result); return 1; } BEGIN_METHOD(indexed_fill) { Matrix *result; int dim = lua_to(L,1); T val = lua_to(L,3); if (lua_is*>(L,2)) { Matrix *idx = lua_rawto*>(L,2); result = AprilMath::MatrixExt::Misc:: matIndexedFill(obj, dim-1, idx, val); // WARNING!!! -1 } else { AprilUtils::SharedPtr< Matrix > idx; if (lua_istable(L,2)) { lua_getglobal(L, "matrixInt32"); // dim table ... matrixInt32 lua_pushvalue(L, 2); // dim table ... matrixInt32 table if (lua_pcall(L, 1, 1, 0) != LUA_OK) { // dim table ... object AprilUtils::string str(lua_tostring(L,-1)); lua_pop(L,1); ERROR_EXIT1(128, "%s", str.c_str()); } idx = lua_rawto*>(L,-1); lua_pop(L,1); } else { idx = lua_to*>(L,2); } result = AprilMath::MatrixExt::Misc:: matIndexedFill(obj, dim-1, idx.get(), val); // WARNING!!! -1 } lua_push(L, result); return 1; } BEGIN_METHOD(indexed_copy) { Matrix *result; int dim = lua_to(L,1); Matrix *other = lua_rawto*>(L,3); if (lua_is*>(L,2)) { Matrix *idx = lua_rawto*>(L,2); result = AprilMath::MatrixExt::Misc:: matIndexedCopy(obj, dim-1, idx, other); // WARNING!!! -1 } else { AprilUtils::SharedPtr< Matrix > idx; if (lua_istable(L,2)) { lua_getglobal(L, "matrixInt32"); // dim table ... matrixInt32 lua_pushvalue(L, 2); // dim table ... matrixInt32 table if (lua_pcall(L, 1, 1, 0) != LUA_OK) { // dim table ... object AprilUtils::string str(lua_tostring(L,-1)); lua_pop(L,1); ERROR_EXIT1(128, "%s", str.c_str()); } idx = lua_rawto*>(L,-1); lua_pop(L,1); } else { idx = lua_to*>(L,2); } result = AprilMath::MatrixExt::Misc:: matIndexedCopy(obj, dim-1, idx.get(), other); // WARNING!!! -1 } lua_push(L, result); return 1; } BEGIN_METHOD(count_eq) { lua_push(L, AprilMath::MatrixExt::Misc::matCountEq(obj, lua_to(L,1))); return 1; } BEGIN_METHOD(count_neq) { lua_push(L, AprilMath::MatrixExt::Misc::matCountNeq(obj, lua_to(L,1))); return 1; } BEGIN_CLASS_METHOD(__broadcast__) { Matrix *a = lua_to*>(L,2); Matrix *b = lua_to*>(L,3); Matrix *aux = lua_opt*>(L,4,0); AprilUtils::SharedPtr< Matrix > result = aux; if (lua_isfunction(L,1)) { result.reset( AprilMath::MatrixExt::Misc:: matBroadcast(LuaFunctionWrapper(L,1), a, b, result.get()) ); } else if (luaL_getmetafield(L,1,"__call")) { result.reset( AprilMath::MatrixExt::Misc:: matBroadcast(LuaFunctionWrapper(L,lua_absindex(L,-1)), a, b, result.get()) ); lua_pop(L,1); } else { LUABIND_ERROR("Needs a function as first argument"); } lua_push(L, result.get()); return 1; } BEGIN_CLASS_METHOD(__call_function__) { AprilUtils::SharedPtr< Matrix > obj = lua_rawto*>(L, 1); obj = buildMatrixSliceFromArgs(L, 2, obj.get()); lua_push(L, obj.get()); return 1; } BEGIN_CLASS_METHOD(__index_function__) { int tt = lua_type(L,2); if (tt == LUA_TNUMBER) { const Matrix *cobj = lua_rawto*>(L, 1); const int key = lua_toint(L,2) - 1; // -1 because we start at 0 in C if (cobj->getNumDim() > 1) { lua_push(L, cobj->select(0, key)); } else { lua_push(L, (*cobj)(key)); } return 1; } else if (tt == LUA_TTABLE) { AprilUtils::SharedPtr< Matrix >obj = lua_rawto*>(L, 1); obj = buildMatrixSliceFromTable(L, 2, obj.get()); lua_push(L, obj); return 1; } return 0; } BEGIN_CLASS_METHOD(__newindex_function__) { AprilUtils::SharedPtr< Matrix > obj = lua_rawto*>(L, 1); int tk = lua_type(L, 2); // specialization for case m[k] = v with k and v being of type T if (obj->getNumDim() == 1 && tk == LUA_TNUMBER && lua_is(L, 3)) { // because we start at 0 in C) (*obj)(lua_toint(L, 2) - 1) = lua_to(L, 3); return 0; // early stop here } else if (tk != LUA_TNUMBER && tk != LUA_TTABLE) { // it should be a MatrixBool if (!lua_is(L,2)) { ERROR_EXIT(128, "Needs a table, a number or a matrixBool as key\n"); } lua_remove(L, 1); if (lua_is(L, 2)) { MatrixBindings::masked_fill(L, obj.get()); } else { MatrixBindings::masked_copy(L, obj.get()); } } // if (lua_is(L, 2)) else { // not a MatrixBool if (tk == LUA_TNUMBER) { const int key = lua_toint(L, 2) - 1; // because we start at 0 in C if (obj->getNumDim() > 1) { obj = obj->select(0, key); } else { if (lua_is(L, 3)) { (*obj)(key) = lua_to(L, 3); } else if (lua_is*>(L, 3)) { Matrix *other = lua_rawto*>(L, 3); if (other->size() != 1) { ERROR_EXIT(128, "Expecting a one element matrix\n"); } (*obj)(key) = *(other->begin()); } else { ERROR_EXIT(128, "Found incorrect type as value"); } return 0; // early return here } } else if (tk == LUA_TTABLE) { obj = buildMatrixSliceFromTable(L, 2, obj.get()); if (obj->size() == 1) { if (lua_is(L, 3)) { *(obj->begin()) = lua_to(L, 3); } else if (lua_is*>(L, 3)) { Matrix *other = lua_rawto*>(L, 3); if (other->size() != 1) { ERROR_EXIT(128, "Expecting a one element matrix\n"); } *(obj->begin()) = *(other->begin()); } else { ERROR_EXIT(128, "Found incorrect type as value"); } return 0; // early return here } } else { ERROR_EXIT(128, "Needs a table, a number or a matrixBool as key\n"); } if (lua_is(L, 3)) { T value = lua_to(L, 3); AprilMath::MatrixExt::Initializers::matFill(obj.get(), value); } else if (lua_is*>(L, 3)) { Matrix *other = lua_rawto*>(L, 3); AprilMath::MatrixExt::BLAS::matCopy(obj.get(), other); } else { ERROR_EXIT(128, "Found incorrect type as value"); } } // if key is not a MatrixBool return 0; } // __newindex_function__ }; #undef FUNCTION_NAME #undef BEGIN_METHOD #undef BEGIN_CLASS_METHOD } #endif // MATRIX_BINDING_H april-ann-0.4.1/packages/basics/matrix/binding/matrix_template.lua.cc000066400000000000000000000064721263004425400256340ustar00rootroot00000000000000//BIND_HEADER_C extern "C" { #include } #include "bind_april_io.h" #include "bind_mathcore.h" #include "bind_mtrand.h" #include "bind_matrix_bool.h" #include "bind_matrix_char.h" #include "bind_matrix_complex_float.h" #include "bind_matrix_double.h" #include "bind_matrix_int32.h" #include "bind_sparse_matrix.h" #include "luabindutil.h" #include "luabindmacros.h" #include "lua_string.h" #include "matrix_ext.h" #include "mystring.h" #include "smart_ptr.h" #include "sparse_matrixFloat.h" #include "utilMatrixChar.h" #include "utilMatrixComplexF.h" #include "utilMatrixDouble.h" #include "utilMatrixFloat.h" #include "utilMatrixInt32.h" IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION($$MATRIX_T$$); IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(SlidingWindow$$MATRIX_T$$); //BIND_END //BIND_HEADER_H #include "complex_number.h" #include "bind_april_io.h" #include "bind_mtrand.h" #include "gpu_mirrored_memory_block.h" #include "matrixBool.h" #include "matrixChar.h" #include "matrixComplexF.h" #include "matrixInt32.h" #include "matrixFloat.h" #include "luabindmacros.h" #include "luabindutil.h" #include "utilLua.h" using namespace Basics; typedef $$MATRIX_T$$::sliding_window SlidingWindow$$MATRIX_T$$; DECLARE_LUA_TABLE_BIND_SPECIALIZATION(SlidingWindow$$MATRIX_T$$); #include "matrix_binding.h" //BIND_END //BIND_LUACLASSNAME $$MATRIX_T$$ $$MATRIX_Lua$$ //BIND_CPP_CLASS $$MATRIX_T$$ //BIND_LUACLASSNAME Serializable aprilio.serializable //BIND_SUBCLASS_OF $$MATRIX_T$$ Serializable //BIND_LUACLASSNAME SlidingWindow$$MATRIX_T$$ $$MATRIX_Lua$$.__sliding_window__ //BIND_CPP_CLASS SlidingWindow$$MATRIX_T$$ //BIND_CONSTRUCTOR SlidingWindow$$MATRIX_T$$ { LUABIND_ERROR("Use matrix.sliding_window"); } //BIND_END //BIND_METHOD SlidingWindow$$MATRIX_T$$ get_matrix { LUABIND_INCREASE_NUM_RETURNS(MatrixBindings<$$T$$>::get_matrix(L, obj)); } //BIND_END //BIND_METHOD SlidingWindow$$MATRIX_T$$ next { LUABIND_INCREASE_NUM_RETURNS(MatrixBindings<$$T$$>::next(L, obj)); } //BIND_END //BIND_METHOD SlidingWindow$$MATRIX_T$$ set_at_window { LUABIND_INCREASE_NUM_RETURNS(MatrixBindings<$$T$$>::set_at_window(L, obj)); } //BIND_END //BIND_METHOD SlidingWindow$$MATRIX_T$$ num_windows { LUABIND_INCREASE_NUM_RETURNS(MatrixBindings<$$T$$>::num_windows(L, obj)); } //BIND_END //BIND_METHOD SlidingWindow$$MATRIX_T$$ coords { LUABIND_INCREASE_NUM_RETURNS(MatrixBindings<$$T$$>::coords(L, obj)); } //BIND_END //BIND_METHOD SlidingWindow$$MATRIX_T$$ is_end { LUABIND_INCREASE_NUM_RETURNS(MatrixBindings<$$T$$>::is_end(L, obj)); } //BIND_END //BIND_METHOD SlidingWindow$$MATRIX_T$$ iterate { LUABIND_INCREASE_NUM_RETURNS(MatrixBindings<$$T$$>::iterate(L, obj)); } //BIND_END ////////////////////////////////////////////////////////////////////// //BIND_CONSTRUCTOR $$MATRIX_T$$ //DOC_BEGIN // $$MATRIX_Lua$$(int dim1, int dim2, ..., table mat=nil) /// Constructor con una secuencia de valores que son las dimensiones de /// la matriz el ultimo argumento puede ser una tabla, en cuyo caso /// contiene los valores adecuadamente serializados, si solamente /// aparece la matriz, se trata de un vector cuya longitud viene dada /// implicitamente. //DOC_END { LUABIND_INCREASE_NUM_RETURNS(MatrixBindings<$$T$$>::constructor(L)); } //BIND_END //BIND_CLASS_METHOD $$MATRIX_T$$ MMapped { LUABIND_INCREASE_NUM_RETURNS(MatrixBindings<$$T$$>::MMapped(L)); } //BIND_END april-ann-0.4.1/packages/basics/matrix/c_src/000077500000000000000000000000001263004425400210145ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/matrix/c_src/map_matrix.h000066400000000000000000000277611263004425400233430ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MAP_MATRIX_H #define MAP_MATRIX_H #include "mathcore.h" #define DEFAULT_N_TH 100 #define DEFAULT_SIZE_TH 100u namespace Basics { // forward declaration template class Matrix; // forward declaration template class SparseMatrix; } namespace AprilMath { namespace MatrixExt { /** * @brief Applies a span-based unary MAP operation. * * The MAP operation must be a functor with the following header: * * - O functor(unsigned int N, const GPUMirroredMemoryBlock *input, unsigned int input_stride, unsigned int input_shift, GPUMirroredMemoryBlock *output, unsigned int output_stride, unsigned int output_shift, bool use_cuda); * * @tparam T - The type of input Basics::Matrix. * * @tparam O - The type of output Basics::Matrix. * * @tparam OP - The type of the functor operator, normally it can be derived * from the given functor parameter. * * @param input - The input Basics::Matrix from where input spans will be * taken. * * @param functor - The functor which computes the MAP operation over a span. * * @param dest - The output Basics::Matrix. * * @note It is possible that @c input=dest and the computation will be done * in-place. * * @note Uses OMP, if available, to improve the performance. */ template Basics::Matrix *MatrixSpanMap1(const Basics::Matrix *input, const OP &functor, Basics::Matrix *dest, const int N_th = DEFAULT_N_TH, const unsigned int SIZE_th = DEFAULT_SIZE_TH); /** * @brief Applies a scalar-based unary MAP operation. * * The MAP operation must be a functor with the following header: * * - O functor(const T &v); * * @tparam T - The type of input Basics::Matrix. * * @tparam O - The type of output Basics::Matrix. * * @tparam OP - The type of the functor operator, normally it can be derived * from the given functor parameter. * * @param input - The input Basics::Matrix. * * @param functor - The functor which computes the MAP operation over scalars. * * @param dest - The output Basics::Matrix. * * @note It is possible that @c input=dest and the computation will be done * in-place. * * @note This function is a wrapper over MatrixSpanMap1 which converts a * scalar functor into span functor using ScalarToSpanMap1 struct. * * @note Uses OMP, if available, to improve the performance. */ template Basics::Matrix *MatrixScalarMap1(const Basics::Matrix *input, const OP &functor, Basics::Matrix *dest, const int N_th = DEFAULT_N_TH, const unsigned int SIZE_th = DEFAULT_SIZE_TH); /** * @brief Applies a span-based binary MAP operation. * * The MAP operation must be a functor with the following header: * * - O functor(unsigned int N, const GPUMirroredMemoryBlock *input1, unsigned int input1_stride, unsigned int input1_shift, const GPUMirroredMemoryBlock *input2, unsigned int input2_stride, unsigned int input2_shift, GPUMirroredMemoryBlock *output, unsigned int output_stride, unsigned int output_shift, bool use_cuda); * * @tparam T1 - The type of input1 Basics::Matrix. * * @tparam T2 - The type of input2 Basics::Matrix. * * @tparam O - The type of output Basics::Matrix. * * @tparam OP - The type of the functor operator, normally it can be derived * from the given functor parameter. * * @param input1 - The input1 Basics::Matrix from where input spans will be * taken. * * @param input2 - The input2 Basics::Matrix from where input spans will be * taken. * * @param functor - The functor which computes the MAP operation over a span. * * @param dest - The output Basics::Matrix. * * @note It is possible that @c input1=dest or @c input2=dest and the * computation will be done in-place. * * @note Uses OMP, if available, to improve the performance. */ template Basics::Matrix *MatrixSpanMap2(const Basics::Matrix *input1, const Basics::Matrix *input2, const OP &functor, Basics::Matrix *dest, const int N_th = DEFAULT_N_TH, const unsigned int SIZE_th = DEFAULT_SIZE_TH); /** * @brief Applies a span-based ternary MAP operation. * * The MAP operation must be a functor with the following header: * * - O functor(unsigned int N, const GPUMirroredMemoryBlock *input1, unsigned int input1_stride, unsigned int input1_shift, const GPUMirroredMemoryBlock *input2, unsigned int input2_stride, unsigned int input2_shift, const GPUMirroredMemoryBlock *input3, unsigned int input3_stride, unsigned int input3_shift, GPUMirroredMemoryBlock *output, unsigned int output_stride, unsigned int output_shift, bool use_cuda); * * @tparam T1 - The type of input1 Basics::Matrix. * * @tparam T2 - The type of input2 Basics::Matrix. * * @tparam T3 - The type of input3 Basics::Matrix. * * @tparam O - The type of output Basics::Matrix. * * @tparam OP - The type of the functor operator, normally it can be derived * from the given functor parameter. * * @param input1 - The input1 Basics::Matrix from where input spans will be * taken. * * @param input2 - The input2 Basics::Matrix from where input spans will be * taken. * * @param input3 - The input3 Basics::Matrix from where input spans will be * taken. * * @param functor - The functor which computes the MAP operation over a span. * * @param dest - The output Basics::Matrix. * * @note It is possible that @c input1=dest or @c input2=dest or @c * input3=dest and the computation will be done in-place. * * @note Uses OMP, if available, to improve the performance. */ template Basics::Matrix *MatrixSpanMap3(const Basics::Matrix *input1, const Basics::Matrix *input2, const Basics::Matrix *input3, const OP &functor, Basics::Matrix *dest, const int N_th = DEFAULT_N_TH, const unsigned int SIZE_th = DEFAULT_SIZE_TH); /** * @brief Applies a scalar-based binary MAP operation. * * The MAP operation must be a functor with the following header: * * - O functor(const T1 &a, const T2 &b); * * @tparam T1 - The type of input1 Basics::Matrix. * * @tparam T2 - The type of input2 Basics::Matrix. * * @tparam O - The type of output Basics::Matrix. * * @tparam OP - The type of the functor operator, normally it can be derived * from the given functor parameter. * * @param input1 - The input1 Basics::Matrix. * * @param input2 - The input2 Basics::Matrix. * * @param functor - The functor which computes the MAP operation over scalars. * * @param dest - The output Basics::Matrix. * * @note It is possible that @c input1=dest or @c input2=dest and the * computation will be done in-place. * * @note This function is a wrapper over MatrixSpanMap2 which converts a * scalar functor into span functor using ScalarToSpanMap2 struct. * * @note Uses OMP, if available, to improve the performance. */ template Basics::Matrix *MatrixScalarMap2(const Basics::Matrix *input1, const Basics::Matrix *input2, const OP &functor, Basics::Matrix *dest, const int N_th = DEFAULT_N_TH, const unsigned int SIZE_th = DEFAULT_SIZE_TH); /** * @brief Applies a scalar-based binary MAP operation with a sparse matrix. */ template Basics::Matrix *MatrixScalarMap2(const Basics::Matrix *input1, const Basics::SparseMatrix *input2, const OP &functor, Basics::Matrix *dest, const int N_th = DEFAULT_SIZE_TH, const unsigned int SIZE_th = DEFAULT_SIZE_TH); /** * @brief Applies a scalar-based ternary MAP operation. * * The MAP operation must be a functor with the following header: * * - O functor(const T1 &a, const T2 &b, const T3 &c); * * @tparam T1 - The type of input1 Basics::Matrix. * * @tparam T2 - The type of input2 Basics::Matrix. * * @tparam T3 - The type of input3 Basics::Matrix. * * @tparam O - The type of output Basics::Matrix. * * @tparam OP - The type of the functor operator, normally it can be derived * from the given functor parameter. * * @param input1 - The input1 Basics::Matrix. * * @param input2 - The input2 Basics::Matrix. * * @param input3 - The input3 Basics::Matrix. * * @param functor - The functor which computes the MAP operation over scalars. * * @param dest - The output Basics::Matrix. * * @note It is possible that @c input1=dest or @c input2=dest or @c * input3=dest and the computation will be done in-place. * * @note This function is a wrapper over MatrixSpanMap3 which converts a * scalar functor into span functor using ScalarToSpanMap3 struct. * * @note Uses OMP, if available, to improve the performance. */ template Basics::Matrix *MatrixScalarMap3(const Basics::Matrix *input1, const Basics::Matrix *input2, const Basics::Matrix *input3, const OP &functor, Basics::Matrix *dest, const int N_th = DEFAULT_N_TH, const unsigned int SIZE_th = DEFAULT_SIZE_TH); } // namespace MatrixExt } // namespace AprilMath #undef DEFAULT_N_TH #undef DEFAULT_SIZE_TH #include "map_matrix.impl.h" #endif // MAP_MATRIX_H april-ann-0.4.1/packages/basics/matrix/c_src/map_matrix.impl.h000066400000000000000000000547301263004425400242770ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MAP_MATRIX_IMPL_H #define MAP_MATRIX_IMPL_H // It must be defined here. #include "matrix.h" #include "map_matrix.h" #include "map_template.h" #include "omp_utils.h" namespace AprilMath { namespace MatrixExt { template Basics::Matrix *MatrixScalarMap1(const Basics::Matrix *input, const OP &functor, Basics::Matrix *dest, const int N_th, const unsigned int SIZE_th) { ScalarToSpanMap1 span_functor(functor); return MatrixSpanMap1(input, span_functor, dest, N_th, SIZE_th); } template Basics::Matrix *MatrixScalarMap2(const Basics::Matrix *input1, const Basics::Matrix *input2, const OP &functor, Basics::Matrix *dest, const int N_th, const unsigned int SIZE_th) { ScalarToSpanMap2 span_functor(functor); return MatrixSpanMap2(input1, input2, span_functor, dest, N_th, SIZE_th); } template Basics::Matrix *MatrixScalarMap2(const Basics::Matrix *input1, const Basics::SparseMatrix *input2, const OP &functor, Basics::Matrix *dest, const int N_th, const unsigned int SIZE_th) { // TODO: Implement using a CPU/CUDA wrapper UNUSED_VARIABLE(N_th); UNUSED_VARIABLE(SIZE_th); april_assert(input1 != 0 && input2 != 0 && dest != 0); if (input1->getNumDim() != 2) { ERROR_EXIT(256, "Needs 2-dimensional matrices\n"); } if (!input2->sameDim(input1)) { ERROR_EXIT(256, "Incompatible matrix sizes\n"); } if (input2->getSparseFormat() != CSR_FORMAT) { ERROR_EXIT(256, "Needs a CSR sparse matrix\n"); } int input2_i, input2_j=0; typename Basics::Matrix::iterator dest_it = dest->begin(); typename Basics::Matrix::const_iterator input1_it = input1->begin(); typename Basics::SparseMatrix::const_iterator input2_it = input2->begin(); for (int i=0; igetDimSize(0); ++i) { april_assert(input1_it != input1->end()); april_assert(dest_it != dest->end()); for (int j=0; jgetDimSize(1); ++j) { bool input2_end = (input2_it == input2->end()); if (!input2_end) input2_it.getCoords(input2_i, input2_j); else input2_i = input1->getDimSize(0); T2 input2; if (input2_i == i && input2_j == j) { // non-zero input2 input2 = *input2_it; ++input2_it; } else { input2 = T2(0.0f); } *dest_it = functor(*input1_it, input2); // ++input1_it; ++dest_it; } } return dest; } template Basics::Matrix *MatrixScalarMap3(const Basics::Matrix *input1, const Basics::Matrix *input2, const Basics::Matrix *input3, const OP &functor, Basics::Matrix *dest, const int N_th, const unsigned int SIZE_th) { ScalarToSpanMap3 span_functor(functor); return MatrixSpanMap3(input1, input2, input3, span_functor, dest, N_th, SIZE_th); } template Basics::Matrix *MatrixSpanMap1(const Basics::Matrix *input, const OP &functor, Basics::Matrix *dest, const int N_th, const unsigned int SIZE_th) { april_assert(input != 0 && dest != 0); if (input->size() != dest->size()) { ERROR_EXIT(128, "Incompatible matrix sizes or dimensions\n"); } #ifdef NO_OMP UNUSED_VARIABLE(N_th); UNUSED_VARIABLE(SIZE_th); #endif bool cuda_flag = input->getCudaFlag() || dest->getCudaFlag(); // Contiguous memory block or one dimension. if ( (input->getIsContiguous() || input->getNumDim() == 1) && (dest->getIsContiguous() || dest->getNumDim() == 1) ) { unsigned int size = input->size(); unsigned int input_stride, input_offset = input->getOffset(); unsigned int dest_stride, dest_offset = dest->getOffset(); if (input->getIsContiguous()) input_stride = 1u; else input_stride = input->getStrideSize(0); if (dest->getIsContiguous()) dest_stride = 1u; else dest_stride = dest->getStrideSize(0); functor(size, input->getRawDataAccess(), input_stride, input_offset, dest->getRawDataAccess(), dest_stride, dest_offset, cuda_flag); } // General case. else { if (!input->sameDim(dest)) { ERROR_EXIT(128, "Incompatible matrix sizes or dimensions\n"); } typename Basics::Matrix::span_iterator input_span_it(input); typename Basics::Matrix::span_iterator dest_span_it(dest, input_span_it.getDimOrder()); const int N = input_span_it.numberOfIterations(); april_assert(N == dest_span_it.numberOfIterations()); const unsigned int size = static_cast(input_span_it.getSize()); const unsigned int input_stride = static_cast(input_span_it.getStride()); const unsigned int dest_stride = static_cast(dest_span_it.getStride()); april_assert(size == static_cast(dest_span_it.getSize())); #ifdef USE_CUDA // Forces execution of memory copy from GPU to PPAL or viceversa (if // needed), avoiding race conditions on the following. input->getRawDataAccess()->forceSync(cuda_flag); #endif #ifndef NO_OMP // This if controls the execution using OMP only when the number of threads // is more than 1 and the iterator size is large enough. if (OMPUtils::get_num_threads() > 1 && N > N_th && size > SIZE_th) { #pragma omp parallel for firstprivate(input_span_it) firstprivate(dest_span_it) for (int i=0; igetRawDataAccess(), input_stride, static_cast(input_span_it.getOffset()), dest->getRawDataAccess(), dest_stride, static_cast(dest_span_it.getOffset()), cuda_flag); } // for every possible span } // if num_threads>1 and large enough computation else { #endif // sequential code, with less overhead when updating iterator for (int i=0; iend_span_iterator()); april_assert(dest_span_it != dest->end_span_iterator()); functor(size, input->getRawDataAccess(), input_stride, static_cast(input_span_it.getOffset()), dest->getRawDataAccess(), dest_stride, static_cast(dest_span_it.getOffset()), cuda_flag); // ++input_span_it; ++dest_span_it; } // for every possible span april_assert(input_span_it == input->end_span_iterator()); april_assert(dest_span_it == dest->end_span_iterator()); #ifndef NO_OMP } // else (num_threads==1 or not large enough computation) #endif } // General case. return dest; } // MatrixMap1 function template Basics::Matrix *MatrixSpanMap2(const Basics::Matrix *input1, const Basics::Matrix *input2, const OP &functor, Basics::Matrix *dest, const int N_th, const unsigned int SIZE_th) { april_assert(input1 != 0 && input2 != 0 && dest != 0); if (input1->size() != dest->size() || input2->size() != dest->size()) { ERROR_EXIT(128, "Incompatible matrix sizes or dimensions\n"); } #ifdef NO_OMP UNUSED_VARIABLE(N_th); UNUSED_VARIABLE(SIZE_th); #endif bool cuda_flag = input1->getCudaFlag() || input2->getCudaFlag() || dest->getCudaFlag(); // Contiguous memory block or one dimension. if ( (input1->getIsContiguous() || input1->getNumDim() == 1) && (input2->getIsContiguous() || input2->getNumDim() == 1) && (dest->getIsContiguous() || dest->getNumDim() == 1) ) { unsigned int size = input1->size(); unsigned int input1_stride, input1_offset = input1->getOffset(); unsigned int input2_stride, input2_offset = input2->getOffset(); unsigned int dest_stride, dest_offset = dest->getOffset(); if (input1->getIsContiguous()) input1_stride = 1u; else input1_stride = input1->getStrideSize(0); if (input2->getIsContiguous()) input2_stride = 1u; else input2_stride = input2->getStrideSize(0); if (dest->getIsContiguous()) dest_stride = 1u; else dest_stride = dest->getStrideSize(0); functor(size, input1->getRawDataAccess(), input1_stride, input1_offset, input2->getRawDataAccess(), input2_stride, input2_offset, dest->getRawDataAccess(), dest_stride, dest_offset, cuda_flag); } // General case. else { if (!input1->sameDim(dest) || !input2->sameDim(dest)) { ERROR_EXIT(128, "Incompatible matrix sizes or dimensions\n"); } typename Basics::Matrix::span_iterator input1_span_it(input1); typename Basics::Matrix::span_iterator input2_span_it(input2); typename Basics::Matrix::span_iterator dest_span_it(dest, input1_span_it.getDimOrder()); const int N = input1_span_it.numberOfIterations(); april_assert(N == dest_span_it.numberOfIterations()); april_assert(N == input2_span_it.numberOfIterations()); const unsigned int size = static_cast(input1_span_it.getSize()); const unsigned int input1_stride = static_cast(input1_span_it.getStride()); const unsigned int input2_stride = static_cast(input2_span_it.getStride()); const unsigned int dest_stride = static_cast(dest_span_it.getStride()); april_assert(size == static_cast(input2_span_it.getSize())); april_assert(size == static_cast(dest_span_it.getSize())); #ifdef USE_CUDA // Forces execution of memory copy from GPU to PPAL or viceversa (if // needed), avoiding race conditions on the following. input1->getRawDataAccess()->forceSync(cuda_flag); input2->getRawDataAccess()->forceSync(cuda_flag); #endif #ifndef NO_OMP // This if controls the execution using OMP only when the number of threads // is more than 1 and the iterator size is large enough. if (OMPUtils::get_num_threads() > 1 && N > N_th && size > SIZE_th) { #pragma omp parallel for firstprivate(input1_span_it) firstprivate(input2_span_it) firstprivate(dest_span_it) for (int i=0; igetRawDataAccess(), input1_stride, static_cast(input1_span_it.getOffset()), input2->getRawDataAccess(), input2_stride, static_cast(input2_span_it.getOffset()), dest->getRawDataAccess(), dest_stride, static_cast(dest_span_it.getOffset()), cuda_flag); } // for every possible span } // if num_threads>1 and large enough computation else { #endif // sequential code, with less overhead when updating iterator for (int i=0; iend_span_iterator()); april_assert(input2_span_it != input2->end_span_iterator()); april_assert(dest_span_it != dest->end_span_iterator()); functor(size, input1->getRawDataAccess(), input1_stride, static_cast(input1_span_it.getOffset()), input2->getRawDataAccess(), input2_stride, static_cast(input2_span_it.getOffset()), dest->getRawDataAccess(), dest_stride, static_cast(dest_span_it.getOffset()), cuda_flag); // ++input1_span_it; ++input2_span_it; ++dest_span_it; } // for every possible span april_assert(input1_span_it == input1->end_span_iterator()); april_assert(input2_span_it == input2->end_span_iterator()); april_assert(dest_span_it == dest->end_span_iterator()); #ifndef NO_OMP } // else (num_threads==1 or not large enough computation) #endif } // General case. return dest; } // MatrixMap2 function template Basics::Matrix *MatrixSpanMap3(const Basics::Matrix *input1, const Basics::Matrix *input2, const Basics::Matrix *input3, const OP &functor, Basics::Matrix *dest, const int N_th, const unsigned int SIZE_th) { april_assert(input1 != 0 && input2 != 0 && input3 != 0 && dest != 0); if (input1->size() != dest->size() || input2->size() != dest->size() || input3->size() != dest->size()) { ERROR_EXIT(128, "Incompatible matrix sizes or dimensions\n"); } #ifdef NO_OMP UNUSED_VARIABLE(N_th); UNUSED_VARIABLE(SIZE_th); #endif bool cuda_flag = input1->getCudaFlag() || input2->getCudaFlag() || input3->getCudaFlag() || dest->getCudaFlag(); // Contiguous memory block or one dimension. if ( (input1->getIsContiguous() || input1->getNumDim() == 1) && (input2->getIsContiguous() || input2->getNumDim() == 1) && (input3->getIsContiguous() || input3->getNumDim() == 1) && (dest->getIsContiguous() || dest->getNumDim() == 1) ) { unsigned int size = input1->size(); unsigned int input1_stride, input1_offset = input1->getOffset(); unsigned int input2_stride, input2_offset = input2->getOffset(); unsigned int input3_stride, input3_offset = input3->getOffset(); unsigned int dest_stride, dest_offset = dest->getOffset(); if (input1->getIsContiguous()) input1_stride = 1u; else input1_stride = input1->getStrideSize(0); if (input2->getIsContiguous()) input2_stride = 1u; else input2_stride = input2->getStrideSize(0); if (input3->getIsContiguous()) input3_stride = 1u; else input3_stride = input3->getStrideSize(0); if (dest->getIsContiguous()) dest_stride = 1u; else dest_stride = dest->getStrideSize(0); functor(size, input1->getRawDataAccess(), input1_stride, input1_offset, input2->getRawDataAccess(), input2_stride, input2_offset, input3->getRawDataAccess(), input3_stride, input3_offset, dest->getRawDataAccess(), dest_stride, dest_offset, cuda_flag); } // General case. else { if (!input1->sameDim(dest) || !input2->sameDim(dest) || !input3->sameDim(dest)) { ERROR_EXIT(128, "Incompatible matrix sizes or dimensions\n"); } typename Basics::Matrix::span_iterator input1_span_it(input1); typename Basics::Matrix::span_iterator input2_span_it(input2); typename Basics::Matrix::span_iterator input3_span_it(input3); typename Basics::Matrix::span_iterator dest_span_it(dest, input1_span_it.getDimOrder()); const int N = input1_span_it.numberOfIterations(); april_assert(N == dest_span_it.numberOfIterations()); april_assert(N == input2_span_it.numberOfIterations()); april_assert(N == input3_span_it.numberOfIterations()); const unsigned int size = static_cast(input1_span_it.getSize()); const unsigned int input1_stride = static_cast(input1_span_it.getStride()); const unsigned int input2_stride = static_cast(input2_span_it.getStride()); const unsigned int input3_stride = static_cast(input3_span_it.getStride()); const unsigned int dest_stride = static_cast(dest_span_it.getStride()); april_assert(size == static_cast(input2_span_it.getSize())); april_assert(size == static_cast(input3_span_it.getSize())); april_assert(size == static_cast(dest_span_it.getSize())); #ifdef USE_CUDA // Forces execution of memory copy from GPU to PPAL or viceversa (if // needed), avoiding race conditions on the following. input1->getRawDataAccess()->forceSync(cuda_flag); input2->getRawDataAccess()->forceSync(cuda_flag); input3->getRawDataAccess()->forceSync(cuda_flag); #endif #ifndef NO_OMP // This if controls the execution using OMP only when the number of threads // is more than 1 and the iterator size is large enough. if (OMPUtils::get_num_threads() > 1 && N > N_th && size > SIZE_th) { #pragma omp parallel for firstprivate(input1_span_it) firstprivate(input2_span_it) firstprivate(input3_span_it) firstprivate(dest_span_it) for (int i=0; igetRawDataAccess(), input1_stride, static_cast(input1_span_it.getOffset()), input2->getRawDataAccess(), input2_stride, static_cast(input2_span_it.getOffset()), input3->getRawDataAccess(), input3_stride, static_cast(input3_span_it.getOffset()), dest->getRawDataAccess(), dest_stride, static_cast(dest_span_it.getOffset()), cuda_flag); } // for every possible span } // if num_threads>1 and large enough computation else { #endif // sequential code, with less overhead when updating iterator for (int i=0; iend_span_iterator()); april_assert(input2_span_it != input2->end_span_iterator()); april_assert(input3_span_it != input3->end_span_iterator()); april_assert(dest_span_it != dest->end_span_iterator()); functor(size, input1->getRawDataAccess(), input1_stride, static_cast(input1_span_it.getOffset()), input2->getRawDataAccess(), input2_stride, static_cast(input2_span_it.getOffset()), input3->getRawDataAccess(), input3_stride, static_cast(input3_span_it.getOffset()), dest->getRawDataAccess(), dest_stride, static_cast(dest_span_it.getOffset()), cuda_flag); // ++input1_span_it; ++input2_span_it; ++input3_span_it; ++dest_span_it; } // for every possible span april_assert(input1_span_it == input1->end_span_iterator()); april_assert(input2_span_it == input2->end_span_iterator()); april_assert(input3_span_it == input3->end_span_iterator()); april_assert(dest_span_it == dest->end_span_iterator()); #ifndef NO_OMP } // else (num_threads==1 or not large enough computation) #endif } // General case. return dest; } // MatrixMap2 function } // namespace MatrixExt } // namespace AprilMath #endif // MAP_MATRIX_IMPL_H april-ann-0.4.1/packages/basics/matrix/c_src/map_sparse_matrix.h000066400000000000000000000034601263004425400247060ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MAP_SPARSE_MATRIX_H #define MAP_SPARSE_MATRIX_H namespace Basics { // forward declaration template class SparseMatrix; } namespace AprilMath { namespace MatrixExt { template Basics::SparseMatrix *SparseMatrixScalarMap1(const Basics::SparseMatrix *input, const OP &functor, Basics::SparseMatrix *dest = 0); template Basics::SparseMatrix *SparseMatrixScalarMap2(const Basics::SparseMatrix *input1, const Basics::SparseMatrix *input2, const OP &functor, Basics::SparseMatrix *dest = 0); } // namespace MatrixExt } // namespace AprilMath #include "map_sparse_matrix.impl.h" #endif // MAP_SPARSE_MATRIX_H april-ann-0.4.1/packages/basics/matrix/c_src/map_sparse_matrix.impl.h000066400000000000000000000060071263004425400256460ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MAP_SPARSE_MATRIX_IMPL_H #define MAP_SPARSE_MATRIX_IMPL_H // must be defined here #include "matrix.h" #include "map_sparse_matrix.h" #include "map_template.h" namespace AprilMath { namespace MatrixExt { template Basics::SparseMatrix *SparseMatrixScalarMap1(const Basics::SparseMatrix *input, const OP &functor, Basics::SparseMatrix *dest) { if (dest == 0) dest = input->clone(); april_assert(input != 0 && dest != 0); // TODO: check coordinates if (input->size() != dest->size() || !input->sameDim(dest) || input->nonZeroSize() != dest->nonZeroSize()) { ERROR_EXIT(128, "Incorrect matrix sizes or dimensions\n"); } genericMap1Call(input->nonZeroSize(), input->getRawValuesAccess(), 1u, 0u, dest->getRawValuesAccess(), 1u, 0u, input->getCudaFlag(), functor); return dest; } template Basics::SparseMatrix *SparseMatrixScalarMap2(const Basics::SparseMatrix *input1, const Basics::SparseMatrix *input2, const OP &functor, Basics::SparseMatrix *dest) { if (dest == 0) dest = input1->clone(); // TODO: check coordinates if (input1->size() != dest->size() || !input1->sameDim(dest) || input1->nonZeroSize() != dest->nonZeroSize() || input2->size() != dest->size() || !input2->sameDim(dest)) { ERROR_EXIT(128, "Incorrect matrix sizes or dimensions\n"); } genericMap2Call(input1->nonZeroSize(), input1->getRawValuesAccess(), 1u, 0u, input2->getRawValuesAccess(), 1u, 0u, dest->getRawValuesAccess(), 1u, 0u, input1->getCudaFlag(), functor); return dest; } } // namespace MatrixExt } // namespace AprilMath #endif // MAP_SPARSE_MATRIX_IMPL_H april-ann-0.4.1/packages/basics/matrix/c_src/matrix-conv.impl.h000066400000000000000000000653371263004425400244120ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIX_CONV_IMPL_H #define MATRIX_CONV_IMPL_H #include "matrix.h" #include "smart_ptr.h" namespace AprilMath { namespace MatrixExt { namespace Misc { namespace ConvolutionUtils { template typename Basics::Matrix::sliding_window * prepareMatrixSlideWindowConvolution(int D, Basics::Matrix *mat, // step is an array with D size const int *step, // kernel is an array with D+2 size const int *kernel) { typename Basics::Matrix::sliding_window *mat_sw=0; int numDim = mat->getNumDim(); AprilUtils::UniquePtr aux_step, order_step; if (step != 0) { aux_step = new int[D+2]; aux_step[0] = aux_step[1] = 1; for (int i=0; i:: sliding_window(mat, kernel+2, (step != 0) ? (aux_step.get()+2) : 0, 0, 0, order_step.get()); break; case 1: // numDim == D+1 // KxPxN1xN2x...xNd kernel :: PxM1xM2x...xMd matrix if (kernel[1] != mat->getDimSize(0)) { ERROR_EXIT2(128, "Incorrect kernel size at 2nd dimension, " "expected %d, found %d\n", mat->getDimSize(0), kernel[1]); } mat_sw = new typename Basics::Matrix:: sliding_window(mat, kernel+1, (step != 0) ? (aux_step.get()+1) : 0, 0, 0, order_step.get()); break; case 0: // numDim == D+2 { // KxPxN1xN2x...xNd kernel :: BxPxM1xM2x...xMd matrix if (kernel[1] != mat->getDimSize(1)) { ERROR_EXIT2(128, "Incorrect kernel size at 2nd dimension, " "expected %d, found %d\n", mat->getDimSize(1), kernel[1]); } AprilUtils::UniquePtr aux_kernel(new int[numDim]); aux_kernel[0] = 1; // mat->getDimSize(0); for (int i=1; i:: sliding_window(mat, aux_kernel.get(), aux_step.get(), 0, 0, order_step.get()); } break; default: ERROR_EXIT4(128, "Incorrect number of dimensions, expected " "%d or %d or %d, found %d\n", D, D+1, D+2, numDim); } return mat_sw; } // Traverses mat using a sliding_window configured to fit the given convolution // kernel, and copies every window into an unrolled matrix. template Basics::Matrix *unrollSourceMatrixForConvolution(int D, Basics::Matrix *mat, const int *step, const int *kernel, int bunch_size) { AprilUtils::SharedPtr< typename Basics::Matrix::sliding_window > mat_sw( prepareMatrixSlideWindowConvolution(D, mat, step, kernel) ); AprilUtils::SharedPtr< Basics::Matrix > mat_slice = mat_sw->getMatrix(); AprilUtils::SharedPtr< Basics::Matrix > unrolled_slice; // allocate unrolled matrix int dims[3] = { bunch_size, mat_sw->numWindows()/bunch_size, mat_slice->size() }; Basics::Matrix *unrolled_mat = new Basics::Matrix(3, dims); AprilUtils::UniquePtr aux_dims(new int[mat_slice->getNumDim()+2]); aux_dims[0] = dims[0]; aux_dims[1] = dims[1]; for (int i=0; igetNumDim(); ++i) { aux_dims[i+2] = mat_slice->getDimSize(i); } AprilUtils::SharedPtr< Basics::Matrix > unrolled_mat_rewrapped( unrolled_mat->rewrap(aux_dims.get(), mat_slice->getNumDim()+2) ); aux_dims[0] = 1; aux_dims[1] = 1; AprilUtils::UniquePtr order_step; AprilUtils::SharedPtr< typename Basics::Matrix::sliding_window > unrolled_sw( new typename Basics::Matrix:: sliding_window(unrolled_mat_rewrapped.get(), aux_dims.get(), 0, 0, 0, order_step.get()) ); if (unrolled_sw->numWindows() != mat_sw->numWindows()) { ERROR_EXIT(128, "Incorrect size in input matrix\n"); } // copy all the slices while(!mat_sw->isEnd()) { april_assert( !mat_sw->isEnd() && !unrolled_sw->isEnd() ); mat_slice = mat_sw->getMatrix(mat_slice.get()); unrolled_slice = unrolled_sw->getMatrix(unrolled_slice.get()); // AprilUtils::SharedPtr< Basics::Matrix > rewrapped_mat_slice( mat_slice->rewrap(unrolled_slice->getDimPtr(), unrolled_slice->getNumDim(), // clone in case it is not contiguous true) ); AprilMath::MatrixExt::BLAS::matCopy(unrolled_slice.get(), rewrapped_mat_slice.get()); // mat_sw->next(); unrolled_sw->next(); } return unrolled_mat; } template Basics::Matrix *unrollKernelForConvolution(int D, Basics::Matrix *kernel, int *&kernel_sizes) { int dims[2]; kernel_sizes = 0; switch(D+2 - kernel->getNumDim()) { case 0: // kernel->getNumDim() == D+2 dims[0] = kernel->getDimSize(0); break; case 1: // kernel->getNumDim() == D+1 kernel_sizes = new int[D+2]; dims[0] = kernel_sizes[0] = 1; for (int i=0; igetDimSize(i); break; case 2: // kernel->getNumDim() == D kernel_sizes = new int[D+2]; dims[0] = kernel_sizes[0] = kernel_sizes[1] = 1; for (int i=0; igetDimSize(i); break; default: ERROR_EXIT4(128, "Incorrect kernel numDim, expected %d or %d or %d, given %d\n", D, D+1, D+2, kernel->getNumDim()); } dims[1] = kernel->size() / dims[0]; Basics::Matrix *unrolled_kernel = kernel->rewrap(dims, 2); return unrolled_kernel; } template Basics::Matrix *allocateResultMatrix(int D, int bunch_size, Basics::Matrix *mat, const int *kernel_sizes, const int *step, Basics::Matrix *result) { // compute result_sizes AprilUtils::UniquePtr result_sizes(new int[D+2]); result_sizes[0] = bunch_size; result_sizes[1] = kernel_sizes[0]; int j = mat->getNumDim() - D; // first mat dimension if (step != 0) { // with a given step array for (int i=0; igetDimSize(j+i) - kernel_sizes[i+2])/step[i] + 1; } } else { // without a given step array, assumed as step[i]=1 for (int i=0; igetDimSize(j+i) - kernel_sizes[i+2]) + 1; } } // allocate new result matrix if not given if (result == 0) { result = new Basics::Matrix(D+2, result_sizes.get()); } // check result matrix sizes (includes number of planes = number of kernels) else { if (!result->getIsContiguous()) { ERROR_EXIT(128, "Needs contiguous matrices\n"); } if (!result->sameDim(result_sizes.get(), D+2)) { ERROR_EXIT(128, "Incorrect result matrix sizes\n"); } } return result; } } // namespace ConvolutionUtils // The matrix must be of BxPxM1xM2x...xMd sizes, where B is the bunch_size, P // the number of planes. The kernel is matrix of KxPxN1xN2x...xNd sizes, where K // is the number of kernels, P the number of planes at input matrix. In both // cases, the left-most dimensions can be removed in order and them will be // taken as 1, that is, it is possible to remove B and P (or K and P), or to // remove only B (or K). In any case, the resulting matrix will be of // BxKxR1xR2x...xRd, and if given, it can ignore the two left-most dimensions. template Basics::Matrix *matConvolution(Basics::Matrix *obj, int D, const int *step, Basics::Matrix *kernel, Basics::Matrix *result=0) { /* Matrix **given_unrolled_kernel, Matrix **given_unrolled_input) { */ // check kernel matrix is contiguous if (!kernel->getIsContiguous()) { ERROR_EXIT(128, "Needs a contiguous kernel matrix\n"); } int bunch_size = (D+2 == obj->getNumDim()) ? obj->getDimSize(0) : 1; // compute kernel sizes and unroll kernel matrix int *kernel_sizes; AprilUtils::SharedPtr< Basics::Matrix > unrolled_kernel; unrolled_kernel = ConvolutionUtils::unrollKernelForConvolution(D, kernel, kernel_sizes); // allocate result to properly fit the convolution result = ConvolutionUtils::allocateResultMatrix(D, bunch_size, obj, (kernel_sizes == 0) ? kernel->getDimPtr() : kernel_sizes, step, result); // unroll all convolutions in one matrix, so the whole convolution will be // performed as a matrix-matrix multiplication AprilUtils::SharedPtr< Basics::Matrix > unrolled_this( ConvolutionUtils:: unrollSourceMatrixForConvolution(D, obj, step, (kernel_sizes == 0) ? kernel->getDimPtr() : kernel_sizes, bunch_size) ); // unroll the result matrix int dims[3] = { bunch_size, unrolled_kernel->getDimSize(0), unrolled_this->getDimSize(1) }; AprilUtils::SharedPtr< Basics::Matrix > unrolled_result; unrolled_result = result->rewrap(dims, 3); // AprilUtils::SharedPtr< Basics::Matrix > source_pattern, result_pattern; source_pattern = unrolled_this->select(0, 0); result_pattern = unrolled_result->select(0, 0); AprilUtils::SharedPtr< Basics::Matrix > contiguous_source_pattern, contiguous_result_pattern; contiguous_source_pattern = ( (source_pattern->getIsContiguous()) ? source_pattern : source_pattern->clone() ); contiguous_result_pattern = ( (result_pattern->getIsContiguous()) ? result_pattern : result_pattern->clone() ); // compute convolution by using CBLAS GEMM AprilMath::MatrixExt::BLAS::matGemm(contiguous_result_pattern.get(), CblasNoTrans, CblasTrans, AprilMath::Limits::one(), unrolled_kernel.get(), contiguous_source_pattern.get(), AprilMath::Limits::zero()); AprilMath::MatrixExt::BLAS::matCopy(result_pattern.get(), contiguous_result_pattern.get()); for (int j=1; jselect(0, j, source_pattern.get()); result_pattern = unrolled_result->select(0, j, result_pattern.get()); AprilMath::MatrixExt::BLAS::matCopy(contiguous_source_pattern.get(), source_pattern.get()); // compute convolution by using CBLAS GEMM AprilMath::MatrixExt::BLAS::matGemm(contiguous_result_pattern.get(), CblasNoTrans, CblasTrans, AprilMath::Limits::one(), unrolled_kernel.get(), contiguous_source_pattern.get(), AprilMath::Limits::zero()); AprilMath::MatrixExt::BLAS::matCopy(result_pattern.get(), contiguous_result_pattern.get()); } delete[] kernel_sizes; return result; } // TODO: FINISH THE FOLLOWING EXPERIMENTAL IMPLEMENTATION /* template typename Matrix::sliding_window* prepareMatrixSlideWindowConvolution(int D, Matrix *mat, // step is an array with D size const int *step, // kernel is an array with D+2 size const int *kernel) { typename Matrix::sliding_window *mat_sw; int numDim = mat->getNumDim(); int *aux_step = 0; int *order_step = 0; if (step != 0) { aux_step = new int[D+2]; aux_step[0] = aux_step[1] = 1; for (int i=0; igetMajorOrder() == CblasColMajor) { //order_step = new int[numDim]; //for (int i=0; i::sliding_window(mat, kernel+2, (step != 0) ? (aux_step+2) : 0, 0, 0, order_step); break; case 1: // numDim == D+1 // KxPxN1xN2x...xNd kernel :: PxM1xM2x...xMd matrix if (kernel[1] != mat->getDimSize(0)) { ERROR_EXIT2(128, "Incorrect kernel size at 2nd dimension, " "expected %d, found %d\n", mat->getDimSize(0), kernel[1]); } mat_sw = new typename Matrix::sliding_window(mat, kernel+1, (step != 0) ? (aux_step+1) : 0, 0, 0, order_step); break; case 0: // numDim == D+2 { // KxPxN1xN2x...xNd kernel :: BxPxM1xM2x...xMd matrix if (kernel[1] != mat->getDimSize(1)) { ERROR_EXIT2(128, "Incorrect kernel size at 2nd dimension, " "expected %d, found %d\n", mat->getDimSize(1), kernel[1]); } int *aux_kernel = new int[numDim]; aux_kernel[0] = 1; // mat->getDimSize(0); for (int i=1; i::sliding_window(mat, aux_kernel, aux_step, 0, 0, order_step); delete[] aux_kernel; } break; default: mat_sw = 0; ERROR_EXIT4(128, "Incorrect number of dimensions, expected " "%d or %d or %d, found %d\n", D, D+1, D+2, numDim); } delete[] aux_step; delete[] order_step; return mat_sw; } // Traverses mat using a sliding_window configured to fit the given convolution // kernel, and copies every window into an unrolled matrix. template Matrix *unrollSourceMatrixForConvolution(int D, Matrix *mat, const int *step, const int *kernel) { typename Matrix::sliding_window *mat_sw = prepareMatrixSlideWindowConvolution(D, mat, step, kernel); Matrix *mat_slice = mat_sw->getMatrix(); IncRef(mat_slice); Matrix *unrolled_slice = 0; // allocate unrolled matrix int dims[2] = { mat_sw->numWindows(), mat_slice->size() }; Matrix *unrolled_mat = new Matrix(2, dims, mat->getMajorOrder()); unrolled_mat->zeros(); int *aux_dims = new int[mat_slice->getNumDim()+1]; aux_dims[0] = dims[0]; for (int i=0; igetNumDim(); ++i) { aux_dims[i+1] = mat_slice->getDimSize(i); } Matrix *unrolled_mat_rewrapped = unrolled_mat->rewrap(aux_dims, mat_slice->getNumDim()+1); IncRef(unrolled_mat_rewrapped); aux_dims[0] = 1; int *order_step = 0; if (mat->getMajorOrder() == CblasColMajor) { order_step = new int[mat_slice->getNumDim()+1]; for (int i=0; igetNumDim()+1; ++i) order_step[i] = i; } typename Matrix::sliding_window *unrolled_sw = new typename Matrix::sliding_window(unrolled_mat_rewrapped, aux_dims, 0, 0, 0, order_step); delete[] aux_dims; delete[] order_step; if (unrolled_sw->numWindows() != mat_sw->numWindows()) { ERROR_EXIT(128, "Incorrect size in input matrix\n"); } // copy all the slices while(!mat_sw->isEnd()) { april_assert( !mat_sw->isEnd() && !unrolled_sw->isEnd() ); mat_slice = mat_sw->getMatrix(mat_slice); unrolled_slice = unrolled_sw->getMatrix(unrolled_slice); // Matrix *rewrapped_mat_slice = mat_slice->rewrap(unrolled_slice->getDimPtr(), unrolled_slice->getNumDim(), // clone in case it is not contiguous true); IncRef(rewrapped_mat_slice); unrolled_slice->copy(rewrapped_mat_slice); //rewrapped_mat_slice->print(); //unrolled_slice->print(); //unrolled_mat_rewrapped->print(); //unrolled_mat->print(); //printf("========================================================\n"); DecRef(rewrapped_mat_slice); // mat_sw->next(); unrolled_sw->next(); } delete unrolled_slice; delete unrolled_sw; DecRef(unrolled_mat_rewrapped); DecRef(mat_slice); delete mat_sw; //unrolled_mat->print(); return unrolled_mat; } template Matrix *unrollKernelForConvolution(int D, Matrix *kernel, int *&kernel_sizes) { int dims[2]; kernel_sizes = 0; switch(D+2 - kernel->getNumDim()) { case 0: // kernel->getNumDim() == D+2 dims[0] = kernel->getDimSize(0); break; case 1: // kernel->getNumDim() == D+1 kernel_sizes = new int[D+2]; dims[0] = kernel_sizes[0] = 1; for (int i=0; igetDimSize(i); break; case 2: // kernel->getNumDim() == D kernel_sizes = new int[D+2]; dims[0] = kernel_sizes[0] = kernel_sizes[1] = 1; for (int i=0; igetDimSize(i); break; default: ERROR_EXIT4(128, "Incorrect kernel numDim, expected %d or %d or %d, given %d\n", D, D+1, D+2, kernel->getNumDim()); } dims[1] = kernel->size() / dims[0]; Matrix *unrolled_kernel = kernel->rewrap(dims, 2); return unrolled_kernel; } template Matrix *allocateResultMatrix(int D, int bunch_size, Matrix *mat, const int *kernel_sizes, const int *step, Matrix *result) { // compute result_sizes int *result_sizes = new int[D+2]; result_sizes[0] = bunch_size; result_sizes[1] = kernel_sizes[0]; int j = mat->getNumDim() - D; // first mat dimension if (step != 0) { // with a given step array for (int i=0; igetDimSize(j+i) - kernel_sizes[i+2])/step[i] + 1; } } else { // without a given step array, assumed as step[i]=1 for (int i=0; igetDimSize(j+i) - kernel_sizes[i+2]) + 1; } } // allocate new result matrix if not given if (result == 0) { result = new Matrix(D+2, result_sizes, mat->getMajorOrder()); } // check result matrix sizes (includes number of planes = number of kernels) else { if (!result->getIsContiguous()) { ERROR_EXIT(128, "Needs contiguous matrices\n"); } if (!result->sameDim(result_sizes, D+1)) { ERROR_EXIT(128, "Incorrect result matrix sizes\n"); } } delete[] result_sizes; return result; } // The matrix must be of BxPxM1xM2x...xMd sizes, where B is the bunch_size, P // the number of planes. The kernel is matrix of KxPxN1xN2x...xNd sizes, where K // is the number of kernels, P the number of planes at input matrix. In both // cases, the left-most dimensions can be removed in order and them will be // taken as 1, that is, it is possible to remove B and P (or K and P), or to // remove only B (or K). In any case, the resulting matrix will be of // BxKxR1xR2x...xRd, and if given, it can ignore the two left-most dimensions. template Matrix *Matrix::convolution(int D, const int *step, Matrix *kernel, Matrix *result) { // TODO: make it work for CblasColMajor order if (getMajorOrder() == CblasColMajor) { ERROR_EXIT(128, "Not implemented for col_major matrices\n"); } // Matrix **given_unrolled_kernel, // Matrix **given_unrolled_input) { // check kernel matrix is contiguous if (!kernel->getIsContiguous()) { ERROR_EXIT(128, "Needs a contiguous kernel matrix\n"); } int bunch_size = (D+2 == getNumDim()) ? getDimSize(0) : 1; // compute kernel sizes and unroll kernel matrix int *kernel_sizes; Matrix *unrolled_kernel = unrollKernelForConvolution(D, kernel, kernel_sizes); IncRef(unrolled_kernel); // allocate result to properly fit the convolution result = allocateResultMatrix(D, bunch_size, this, (kernel_sizes == 0) ? kernel->getDimPtr() : kernel_sizes, step, result); // unroll all convolutions in one matrix, so the whole convolution will be // performed as a matrix-matrix multiplication Matrix *unrolled_input = unrollSourceMatrixForConvolution(D, this, step, (kernel_sizes == 0) ? kernel->getDimPtr() : kernel_sizes); IncRef(unrolled_input); // unroll the result matrix int dims[2]; dims[0] = result->getDimSize(0) * result->getDimSize(1); dims[1] = result->size() / dims[0]; Matrix *unrolled_result = result->rewrap(dims, 2); IncRef(unrolled_result); // int sizes[2]; sizes[0] = unrolled_input->getDimSize(0)/bunch_size; sizes[1] = unrolled_input->getDimSize(1); Matrix::sliding_window source_sw(unrolled_input, sizes, 0, sizes); sizes[0] = unrolled_kernel->getDimSize(0); sizes[1] = unrolled_result->getDimSize(1); Matrix::sliding_window result_sw(unrolled_result, sizes, 0, sizes); // sanity check april_assert(source_sw.numWindows() == bunch_size); april_assert(result_sw.numWindows() == bunch_size); // Matrix *source_pattern = 0, *result_pattern = 0; source_pattern = source_sw.getMatrix(); result_pattern = result_sw.getMatrix(); IncRef(source_pattern); IncRef(result_pattern); // AprilUtils::aprilPrint(0, source_sw.isEnd(), "\n"); while(!source_sw.isEnd()) { source_pattern = source_sw.getMatrix(source_pattern); result_pattern = result_sw.getMatrix(result_pattern); // compute convolution by using CBLAS GEMM result_pattern->gemm(CblasNoTrans, CblasTrans, T(1.0f), unrolled_kernel, source_pattern, T(0.0f)); // //source_pattern->print(); //result_pattern->print(); //printf("========================================================\n"); source_sw.next(); result_sw.next(); } DecRef(source_pattern); DecRef(result_pattern); DecRef(unrolled_input); DecRef(unrolled_result); DecRef(unrolled_kernel); delete[] kernel_sizes; return result; } */ } // namespace Misc } // namespace MatrixExt } // namespace Basics #endif // MATRIX_CONV_IMPL_H april-ann-0.4.1/packages/basics/matrix/c_src/matrix-iterators.impl.h000066400000000000000000000604101263004425400254440ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIX_ITERATORS_IMPL_H #define MATRIX_ITERATORS_IMPL_H #include "matrix.h" #include "unused_variable.h" namespace Basics { /***** ITERATORS *****/ template Matrix::iterator::iterator(Matrix *m) : m(m), idx(0), raw_pos(0) { if (!m->getIsContiguous()) { coords = new int[m->getNumDim()]; for (int i=0; igetNumDim(); ++i) coords[i] = 0; } else coords = 0; raw_pos = m->getOffset(); data = m->getData(); } template Matrix::iterator::iterator(Matrix *m, int raw_pos) : m(m), idx(0), raw_pos(raw_pos) { if (!m->getIsContiguous()) { coords = new int[m->getNumDim()]; m->computeCoords(raw_pos, coords); } else coords = 0; data = m->getData(); } template Matrix::iterator::iterator(Matrix *m, int raw_pos, int *coords) : m(m), idx(0), raw_pos(raw_pos) { if (!m->getIsContiguous()) { this->coords = new int[m->getNumDim()]; for (int i=0; igetNumDim(); ++i) this->coords[i] = coords[i]; } else this->coords = 0; data = m->getData(); } template Matrix::iterator::iterator() : m(0), idx(0), raw_pos(0), coords(0) { } template Matrix::iterator::iterator(const iterator &other) : m(other.m), idx(other.idx), raw_pos(other.raw_pos) { if (other.coords != 0) { coords = new int[m->getNumDim()]; for (int i=0; igetNumDim(); ++i) coords[i] = other.coords[i]; } else coords = 0; data = m->getData(); } template Matrix::iterator:: ~iterator() { delete[] coords; } template typename Matrix::iterator &Matrix::iterator:: operator=(const Matrix::iterator &other) { m = other.m; idx = other.idx; raw_pos = other.raw_pos; data = m->getData(); if (other.coords != 0) { if (coords==0 || m->numDim != other.m->numDim) { delete[] coords; coords = new int[other.m->getNumDim()]; } for (int i=0; igetNumDim(); ++i) coords[i] = other.coords[i]; } else { delete[] coords; coords = 0; } return *this; } template bool Matrix::iterator::operator==(const Matrix::iterator &other) const { return m==other.m && raw_pos == other.raw_pos; } template bool Matrix::iterator::operator!=(const Matrix::iterator &other) const { return !( (*this) == other ); } template typename Matrix::iterator &Matrix::iterator::operator++() { ++idx; if (coords != 0) m->nextCoordVectorRowOrder(coords, raw_pos); else ++raw_pos; return *this; } template T &Matrix::iterator::operator*() { return data[raw_pos]; } template T *Matrix::iterator::operator->() { return &data[raw_pos]; } template int Matrix::iterator::getRawPos() const { return raw_pos; } /*******************************************************************/ template Matrix::const_iterator::const_iterator(const Matrix *m) : m(m), idx(0), raw_pos(0) { if (!m->getIsContiguous()) { coords = new int[m->getNumDim()]; for (int i=0; igetNumDim(); ++i) coords[i] = 0; } else coords = 0; raw_pos = m->getOffset(); data = m->getData(); } template Matrix::const_iterator::const_iterator(const Matrix *m, int raw_pos) : m(m), idx(0), raw_pos(raw_pos) { if (!m->getIsContiguous()) { coords = new int[m->getNumDim()]; m->computeCoords(raw_pos, coords); } else coords = 0; data = m->getData(); } template Matrix::const_iterator::const_iterator(const Matrix *m, int raw_pos, int *coords) : m(m), idx(0), raw_pos(raw_pos) { if (!m->getIsContiguous()) { this->coords = new int[m->getNumDim()]; for (int i=0; igetNumDim(); ++i) this->coords[i] = coords[i]; } else this->coords = 0; data = m->getData(); } template Matrix::const_iterator::const_iterator() : m(0), idx(0), raw_pos(0), coords(0) { } template Matrix::const_iterator::const_iterator(const Matrix::const_iterator &other) : m(other.m), idx(other.idx), raw_pos(other.raw_pos) { if (other.coords != 0) { coords = new int[m->getNumDim()]; for (int i=0; igetNumDim(); ++i) coords[i] = other.coords[i]; } else coords = 0; data = m->getData(); } template Matrix::const_iterator::const_iterator(const Matrix::iterator &other) : m(other.m), idx(other.idx), raw_pos(other.raw_pos) { if (other.coords != 0) { coords = new int[m->getNumDim()]; for (int i=0; igetNumDim(); ++i) coords[i] = other.coords[i]; } else coords = 0; data = m->getData(); } template Matrix::const_iterator::~const_iterator() { delete[] coords; } template typename Matrix::const_iterator &Matrix::const_iterator::operator=(const typename Matrix::const_iterator &other) { m = other.m; idx = other.idx; raw_pos = other.raw_pos; data = m->getData(); if (other.coords != 0) { if (coords==0 || m->numDim != other.m->numDim) { delete[] coords; coords = new int[other.m->getNumDim()]; } for (int i=0; igetNumDim(); ++i) coords[i] = other.coords[i]; } else { delete[] coords; coords = 0; } return *this; } template typename Matrix::const_iterator &Matrix::const_iterator::operator=(const typename Matrix::iterator &other) { m = other.m; idx = other.idx; raw_pos = other.raw_pos; data = m->getData(); if (other.coords != 0) { if (coords==0 || m->numDim != other.m->numDim) { delete[] coords; coords = new int[other.m->getNumDim()]; } for (int i=0; igetNumDim(); ++i) coords[i] = other.coords[i]; } else { delete[] coords; coords = 0; } return *this; } template bool Matrix::const_iterator::operator==(const Matrix::const_iterator &other) const { return m==other.m && raw_pos == other.raw_pos; } template bool Matrix::const_iterator::operator==(const Matrix::iterator &other) const { return m==other.m && raw_pos == other.raw_pos; } template bool Matrix::const_iterator::operator!=(const Matrix::const_iterator &other) const { return !( (*this) == other ); } template bool Matrix::const_iterator::operator!=(const Matrix::iterator &other) const { return !( (*this) == other ); } template typename Matrix::const_iterator &Matrix::const_iterator::operator++() { ++idx; if (coords != 0) m->nextCoordVectorRowOrder(coords, raw_pos); else ++raw_pos; return *this; } template const T &Matrix::const_iterator::operator*() const { return data[raw_pos]; } template const T *Matrix::const_iterator::operator->() const { return &data[raw_pos]; } template int Matrix::const_iterator::getRawPos() const { return raw_pos; } /*******************************************************************/ template void Matrix::span_iterator::initialize(const Matrix *m, int raw_pos, int dim) { if (dim < -2 || dim >= m->numDim) { ERROR_EXIT2(128, "Dimension out of bounds, given %d, expected [-1,%d]\n", dim, m->numDim-1); } this->m = m; this->raw_pos = raw_pos; coords = new int[m->numDim]; order = new int[m->numDim]; switch(m->numDim) { case 1: order[0] = 0; coords[0] = 0; num_iterations = 1; break; case 2: coords[0] = 0; coords[1] = 0; if (dim == -1) { if (m->matrixSize[0] > m->matrixSize[1]) { order[0] = 0; order[1] = 1; } else if (m->matrixSize[1] > m->matrixSize[0]) { order[0] = 1; order[1] = 0; } else { // CUATION: this conditions are critical to work with transposed // matrices, in order to ensure the iterator to traverse equally two // matrices with different transposition. order[0] = 1; order[1] = 0; } } else { order[0] = dim; order[1] = 1-dim; } num_iterations = m->matrixSize[order[1]]; break; default: if (dim == -1) { // compute the best dimension for (int i=0; inumDim; ++i) { coords[i] = 0; order[i] = i; } AprilUtils::Sort(order, 0, m->numDim-1, inverse_sort_compare(m)); } else { // take given dim as the best and sort other dimensions for (int i=0; inumDim; ++i) { coords[i] = 0; order[i] = i; } AprilUtils::Sort(order, 1, m->numDim-1, inverse_sort_compare(m)); coords[0] = 0; order[0] = dim; } num_iterations = 1; for (int i=1; inumDim; ++i) { num_iterations *= m->matrixSize[order[i]]; } } } template Matrix::span_iterator::span_iterator(const Matrix *m, const int *order) { this->m = m; this->raw_pos = m->offset; this->coords = new int[m->numDim]; this->order = new int[m->numDim]; for (int i=0; inumDim; ++i) { this->order[i] = order[i]; this->coords[i] = 0; } this->num_iterations = 1; for (int i=1; inumDim; ++i) { this->num_iterations *= m->matrixSize[order[i]]; } } template Matrix::span_iterator:: span_iterator(const Matrix *m, int raw_pos, int dim) { initialize(m, raw_pos, dim); m->computeCoords(raw_pos, coords); } template Matrix::span_iterator::span_iterator(const Matrix *m, int dim) { initialize(m, m->offset, dim); } template Matrix::span_iterator:: span_iterator(const span_iterator &other) : m(other.m), raw_pos(other.raw_pos), num_iterations(other.num_iterations) { coords = new int[m->getNumDim()]; order = new int[m->getNumDim()]; for (int i=0; igetNumDim(); ++i) { coords[i] = other.coords[i]; order[i] = other.order[i]; } } template Matrix::span_iterator::span_iterator(): m(0),coords(0),order(0) { } template Matrix::span_iterator::~span_iterator() { delete[] order; delete[] coords; } template int Matrix::span_iterator::getOffset() const { return raw_pos; } template int Matrix::span_iterator::getStride() const { return m->stride[order[0]]; } template int Matrix::span_iterator::getSize() const { return m->matrixSize[order[0]]; } template typename Matrix::span_iterator &Matrix::span_iterator:: operator=(const Matrix::span_iterator &other) { if (m==0 || m->numDim != other.m->numDim) { delete[] coords; delete[] order; coords = new int[other.m->getNumDim()]; order = new int[other.m->getNumDim()]; } m = other.m; raw_pos = other.raw_pos; for (int i=0; igetNumDim(); ++i) { coords[i] = other.coords[i]; order[i] = other.order[i]; } num_iterations = other.num_iterations; return *this; } template bool Matrix::span_iterator:: operator==(const Matrix::span_iterator &other) const { return m==other.m && raw_pos==other.raw_pos; } template bool Matrix::span_iterator:: operator!=(const Matrix::span_iterator &other) const { return !((*this)==other); } template typename Matrix::span_iterator &Matrix::span_iterator:: operator++() { switch(m->numDim) { case 1: raw_pos = m->last_raw_pos+1; break; case 2: { int j = order[1]; coords[j] = (coords[j]+1) % m->matrixSize[j]; if (coords[j] > 0) raw_pos += m->stride[j]; else raw_pos = m->last_raw_pos+1; break; } default: { int j = 1, pos; do { pos = order[j++]; coords[pos] = (coords[pos]+1) % m->matrixSize[pos]; } while(jnumDim && coords[pos] == 0); if (j == m->numDim && coords[pos] == 0) raw_pos = m->last_raw_pos+1; else raw_pos = m->computeRawPos(coords); } } return *this; } template int Matrix::span_iterator::numberOfIterations() const { return num_iterations; } template void Matrix::span_iterator::setAtIteration(int idx) { if (idx < num_iterations) { raw_pos = m->offset; coords[order[0]] = 0; for (int i=1; i < m->getNumDim(); i++) { int j = order[i]; coords[j] = idx % m->matrixSize[j]; idx = idx / m->matrixSize[j];; raw_pos += m->stride[j]*coords[j]; } } else raw_pos = m->last_raw_pos+1; } ///////////////////////////////////////////////////////////////////////////// template Matrix::pos_iterator::pos_iterator(const Matrix *m) : m(m), idx(0), raw_pos(0) { if (!m->getIsContiguous()) { coords = new int[m->getNumDim()]; for (int i=0; igetNumDim(); ++i) coords[i] = 0; } else coords = 0; raw_pos = m->getOffset(); } template Matrix::pos_iterator::pos_iterator() : m(0), idx(0), raw_pos(0), coords(0) { } template Matrix::pos_iterator::~pos_iterator() { delete[] coords; } template typename Matrix::pos_iterator &Matrix::pos_iterator:: operator=(const Matrix::pos_iterator &other) { m = other.m; idx = other.idx; raw_pos = other.raw_pos; if (other.coords != 0) { if (coords==0 || m->numDim != other.m->numDim) { delete[] coords; coords = new int[other.m->getNumDim()]; } for (int i=0; igetNumDim(); ++i) coords[i] = other.coords[i]; } else { delete[] coords; coords = 0; } return *this; } template bool Matrix::pos_iterator::operator==(const Matrix::pos_iterator &other) const { return m==other.m && raw_pos == other.raw_pos; } template bool Matrix::pos_iterator::operator!=(const Matrix::pos_iterator &other) const { return !( (*this) == other ); } template typename Matrix::pos_iterator &Matrix::pos_iterator::operator++() { ++idx; if (coords != 0) m->nextCoordVectorRowOrder(coords, raw_pos); else ++raw_pos; return *this; } /*******************************************************************/ template Matrix::sliding_window::sliding_window() : Referenced(), m(0), offset(0), sub_matrix_size(0), step(0), num_steps(0), order_step(0), coords(0), raw_pos(0), num_windows(0) { } template Matrix::sliding_window::sliding_window(Matrix *m, const int *sub_matrix_size, const int *offset, const int *step, const int *num_steps, const int *order_step) : Referenced(), m(m), offset(new int[m->numDim]), sub_matrix_size(new int[m->numDim]), step(new int[m->numDim]), num_steps(new int[m->numDim]), order_step(new int[m->numDim]), coords(new int[m->numDim]), raw_pos(m->offset), finished(false), offset_plus_num_step_by_step(new int[m->numDim]), num_windows(1) { if (offset != 0) { for (int i=0; inumDim; ++i) { this->raw_pos += offset[i]*m->stride[i]; this->coords[i] = this->offset[i] = offset[i]; } } else { for (int i=0; inumDim; ++i) this->coords[i] = this->offset[i] = 0; } // default values for arrays if necessary if (sub_matrix_size == 0) { for (int i=0; inumDim; ++i) { this->sub_matrix_size[i] = m->matrixSize[i]; } this->sub_matrix_size[0] = 1; } else { for (int i=0; inumDim; ++i) { this->sub_matrix_size[i] = sub_matrix_size[i]; } } // if (step == 0) { for (int i=0; inumDim; ++i) { this->step[i] = 1; } } else { for (int i=0; inumDim; ++i) { this->step[i] = step[i]; } } // if (num_steps == 0) { for (int i=0; inumDim; ++i) { this->num_steps[i] = (m->matrixSize[i] - this->sub_matrix_size[i])/this->step[i] + 1; } } else { for (int i=0; inumDim; ++i) { this->num_steps[i] = num_steps[i]; } } // if (order_step == 0) { for (int i=0; inumDim; ++i) { this->order_step[i] = (m->numDim - (i + 1)); } } else { for (int i=0; inumDim; ++i) { this->order_step[i] = order_step[i]; } } // last_raw_pos is 0 instead of m->offset because at getMatrix method the // resulting matrix last_raw_pos is the addition between current window // raw_pos (with m->offset) plus the following last_raw_pos computation last_raw_pos = 0; total_size = 1; for (int i=0; inumDim; ++i) { total_size = this->sub_matrix_size[i]*total_size; last_raw_pos += (this->sub_matrix_size[i]-1)*m->stride[i]; } // Final sanity check and initialization of auxiliary data structures for (int i=0; inumDim; ++i) { if (this->step[i] < 1) { ERROR_EXIT2(128, "Unexpected step value of %d at coordinate %d," " it must be > 0\n", this->step[i], i); } if (this->num_steps[i] < 1) { ERROR_EXIT2(128, "Unexpected num_steps value of %d at coordinate %d," " it must be > 0\n", this->num_steps[i], i); } if (this->offset[i] < 0) { ERROR_EXIT1(128, "Unexpected offset value at coordinate %d\n", i); } if (this->sub_matrix_size[i] < 0) { ERROR_EXIT1(128, "Unexpected sub_matrix_size value at coordinate %d\n", i); } int last = ( this->offset[i] + this->step[i]*(this->num_steps[i]-1) + this->sub_matrix_size[i]); if (last > m->matrixSize[i]) { ERROR_EXIT1(128, "Overflow at sliding window dimension %d!!!\n", i); } offset_plus_num_step_by_step[i] = this->offset[i] + this->num_steps[i] * this->step[i]; num_windows *= this->num_steps[i]; } } template Matrix::sliding_window::sliding_window(const sliding_window &other) : Referenced(), m(other.m), offset(new int[m->numDim]), sub_matrix_size(new int[m->numDim]), step(new int[m->numDim]), num_steps(new int[m->numDim]), order_step(new int[m->numDim]), coords(new int[m->numDim]), raw_pos(other.raw_pos), total_size(other.total_size), last_raw_pos(other.last_raw_pos), finished(other.finished), offset_plus_num_step_by_step(new int[m->numDim]), num_windows(other.num_windows) { for (int i=0; inumDim; ++i) { sub_matrix_size[i] = other.sub_matrix_size[i]; step[i] = other.step[i]; num_steps[i] = other.num_steps[i]; order_step[i] = other.order_step[i]; coords[i] = other.coords[i]; offset[i] = other.offset[i]; offset_plus_num_step_by_step[i] = other.offset_plus_num_step_by_step[i]; } } template Matrix::sliding_window::~sliding_window() { delete[] sub_matrix_size; delete[] step; delete[] num_steps; delete[] order_step; delete[] coords; delete[] offset; delete[] offset_plus_num_step_by_step; } template typename Matrix::sliding_window::sliding_window &Matrix::sliding_window:: operator=(const sliding_window &other) { if (m.empty() || m->numDim != other.m->numDim) { delete[] sub_matrix_size; delete[] step; delete[] num_steps; delete[] order_step; delete[] coords; delete[] offset; delete[] offset_plus_num_step_by_step; sub_matrix_size = new int[other.m->numDim]; step = new int[other.m->numDim]; num_steps = new int[other.m->numDim]; order_step = new int[other.m->numDim]; coords = new int[other.m->numDim]; offset = new int[other.m->numDim]; offset_plus_num_step_by_step = new int[other.m->numDim]; } m = other.m; offset = other.offset; raw_pos = other.raw_pos; total_size = other.total_size; last_raw_pos = other.last_raw_pos; finished = other.finished; num_windows = other.num_windows; for (int i=0; inumDim; ++i) { sub_matrix_size[i] = other.sub_matrix_size[i]; step[i] = other.step[i]; num_steps[i] = other.num_steps[i]; order_step[i] = other.order_step[i]; coords[i] = other.coords[i]; offset[i] = other.offset[i]; offset_plus_num_step_by_step[i] = other.offset_plus_num_step_by_step[i]; } return *this; } template typename Matrix::sliding_window::sliding_window *Matrix::sliding_window:: next() { int j = 0; bool overflow; do { int pos = order_step[j]; int prev = coords[pos]; coords[pos] += step[pos]; if (coords[pos] >= offset_plus_num_step_by_step[pos]) { coords[pos] = offset[pos]; raw_pos -= m->stride[pos]*(prev + offset[pos]); overflow = true; } else { raw_pos += m->stride[pos]*step[pos]; overflow = false; } } while(overflow && ++jnumDim); if (j == m->numDim && overflow) finished = true; return this; } template Matrix *Matrix::sliding_window::getMatrix(Matrix *dest) { if (finished) return dest; if (dest == 0) { return new Matrix(m->numDim, m->stride, raw_pos, sub_matrix_size, total_size, last_raw_pos + raw_pos, m->data.get(), m->use_cuda); } else { april_assert(dest->getRawDataAccess() == m->getRawDataAccess()); dest->changeSubMatrixData(raw_pos, last_raw_pos + raw_pos); return dest; } // this line is unreachable } template int Matrix::sliding_window::numWindows() const { return num_windows; } template void Matrix::sliding_window::setAtWindow(int windex) { if (windex < num_windows) { raw_pos = m->offset; for (int i=0; i < m->getNumDim();i++) { int j = order_step[i]; coords[j] = offset[j] + (windex % num_steps[j])*step[j]; windex = windex / num_steps[j]; raw_pos += m->stride[j]*coords[j]; } } else finished = true; } template const int *Matrix::sliding_window::getCoords() const { return coords; } template int Matrix::sliding_window::getNumDim() const { return m->getNumDim(); } } // namespace Basics #endif // MATRIX_ITERATORS_IMPL_H april-ann-0.4.1/packages/basics/matrix/c_src/matrix-serialization.impl.h000066400000000000000000000346251263004425400263160ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIX_SERIALIZATION_H #define MATRIX_SERIALIZATION_H #include #include #include #include "constString.h" #include "c_string.h" #include "error_print.h" #include "matrix.h" #include "matrix_serialization_utils.h" #include "smart_ptr.h" #include "stream.h" namespace Basics { /****************************************************************************/ template Matrix* Matrix::read(AprilIO::StreamInterface *stream, const AprilUtils::LuaTable &options) { if (options.opt(MatrixIO::TAB_OPTION, false)) { return readTab(stream, options); } else { return readNormal(stream, options); } } template Matrix* Matrix::readNormal(AprilIO::StreamInterface *stream, const AprilUtils::LuaTable &options) { UNUSED_VARIABLE(options); // MatrixIO::AsciiExtractor ascii_extractor; MatrixIO::BinaryExtractor bin_extractor; if (!stream->good()) { ERROR_PRINT("The stream is not prepared, it is empty, or EOF\n"); return 0; } AprilUtils::SharedPtr c_str(new AprilIO::CStringStream());; april_assert(!c_str.empty()); AprilUtils::constString line,format,token; // First we read the matrix dimensions line = readULine(stream, c_str.get()); if (!line) { ERROR_PRINT("empty file!!!\n"); return 0; } static const int maxdim=100; int dims[maxdim]; int n=0, pos_comodin=-1; while (n > mat; // Now we read the type of the format line = readULine(stream, c_str.get()); format = line.extract_token(); if (!format) { ERROR_PRINT("impossible to read format token\n"); return 0; } // legacy major order string // order = line.extract_token(); // if (given_order != 0) order = given_order; if (pos_comodin == -1) { // Normal version mat = new Matrix(n,dims); typename Matrix::iterator data_it(mat->begin()); if (format == "ascii") { while (data_it!=mat->end() && (line=readULine(stream, c_str.get()))) { while (data_it!=mat->end() && ascii_extractor(line, *data_it)) { ++data_it; } } } else { // binary while (data_it!=mat->end() && (line=readULine(stream, c_str.get()))) { while (data_it!=mat->end() && bin_extractor(line, *data_it)) { ++data_it; } } } if (data_it!=mat->end()) { ERROR_PRINT("Impossible to fill all the matrix components\n"); mat.reset(); return 0; } } else { // version with comodin int size=0,maxsize=4096; AprilUtils::UniquePtr data = new T[maxsize]; if (format == "ascii") { while ( (line=readULine(stream, c_str.get())) ) { while (ascii_extractor(line, data[size])) { size++; if (size == maxsize) { // resize data vector T *aux = new T[2*maxsize]; for (int a=0;a(n,dims); int i=0; for (typename Matrix::iterator it(mat->begin()); it!=mat->end(); ++it,++i) *it = data[i]; data.reset(); } return mat.weakRelease(); } template void Matrix::write(AprilIO::StreamInterface *stream, const AprilUtils::LuaTable &options) { bool is_tab = options.opt(MatrixIO::TAB_OPTION, false); if (is_tab) writeTab(stream, options); else writeNormal(stream, options); } template void Matrix::writeNormal(AprilIO::StreamInterface *stream, const AprilUtils::LuaTable &options) { bool is_ascii = options.opt(MatrixIO::ASCII_OPTION, false); // MatrixIO::AsciiCoder ascii_coder; MatrixIO::BinaryCoder bin_coder; /* Legacy code MatrixIO::AsciiSizer ascii_sizer; MatrixIO::BinarySizer bin_sizer; int sizedata,sizeheader; sizeheader = this->getNumDim()*10+10+10; // FIXME: To put adequate values // sizedata contains the memory used by T in ascii including spaces, // new lines, etc... if (is_ascii) sizedata = ascii_sizer(this); else sizedata = bin_sizer(this); // size_t expected_size = static_cast(sizedata+sizeheader+1); UNUSED_VARIABLE(sizedata); UNUSED_VARIABLE(sizeheader); */ if (!stream->isOpened()) { ERROR_EXIT(256, "The stream is not prepared\n"); } for (int i=0;igetNumDim()-1;i++) { stream->printf("%d ",this->getDimSize(i)); } stream->printf("%d\n",this->getDimSize(this->getNumDim()-1)); if (is_ascii) { const int columns = 9; stream->printf("ascii"); /* legacy major order string if (this->getMajorOrder() == CblasColMajor) { stream->printf(" col_major"); } else { stream->printf(" row_major"); } */ stream->printf("\n"); int i=0; for(typename Matrix::const_iterator it(this->begin()); it!=this->end();++it,++i) { ascii_coder(*it, stream); stream->printf("%c", ((((i+1) % columns) == 0) ? '\n' : ' ')); } if ((i % columns) != 0) { stream->printf("\n"); } } else { // binary const int columns = 16; stream->printf("binary"); /* legacy major order string if (this->getMajorOrder() == CblasColMajor) { stream->printf(" col_major"); } else { stream->printf(" row_major"); } */ stream->printf("\n"); // We substract 1 so the final '\0' is not considered int i=0; for(typename Matrix::const_iterator it(this->begin()); it!=this->end(); ++it,++i) { bin_coder(*it, stream); /* char b[5]; binarizer::code_float(*it, b); fprintf(f, "%c%c%c%c%c", b[0], b[1], b[2], b[3], b[4]); */ if ((i+1) % columns == 0) stream->printf("\n"); } if ((i % columns) != 0) stream->printf("\n"); } } /****************************************************************/ template Matrix* Matrix::readTab(AprilIO::StreamInterface *stream, const AprilUtils::LuaTable &options) { const char *delim = options.opt(MatrixIO::DELIM_OPTION, "\n\r\t,; "); bool read_empty = options.opt(MatrixIO::EMPTY_OPTION, false); T default_value = options.opt(MatrixIO::DEFAULT_OPTION, T()); int ncols = options.opt(MatrixIO::NCOLS_OPTION, 0); int nrows = options.opt(MatrixIO::NROWS_OPTION, 0); const AprilUtils::LuaTable &map = options.opt(MatrixIO::MAP_OPTION, AprilUtils::LuaTable()); // MatrixIO::AsciiExtractor ascii_extractor; if (!stream->good()) { ERROR_PRINT("The stream is not prepared, it is empty, or EOF\n"); return 0; } AprilUtils::SharedPtr c_str; c_str = new AprilIO::CStringStream(); april_assert(!c_str.empty()); AprilUtils::constString line(""); if (ncols == 0 || nrows == 0) { off_t first_pos = stream->seek(); if (nrows == 0) { while (!stream->eof()) { line = readULine(stream, c_str.get(), read_empty); if (line.len() > 0) { if (ncols == 0) { while(line.extract_token(delim, read_empty)) ++ncols; // while(ascii_extractor(line,value)) ++ncols; } ++nrows; } } } else { line = readULine(stream, c_str.get(), read_empty); if (line.len() > 0) { if (ncols == 0) { while(line.extract_token(delim, read_empty)) ++ncols; // while(ascii_extractor(line,value)) ++ncols; } } } if (nrows <= 0 || ncols <= 0) ERROR_EXIT(256, "Found 0 rows or 0 cols\n"); stream->seek(SEEK_SET, first_pos); if (stream->hasError()) { ERROR_PRINT1("Impossible to rewind the stream: %s\n", stream->getErrorMsg()); return 0; } if (!stream->good()) { ERROR_PRINT("The stream is not prepared, it is empty, or EOF\n"); return 0; } } AprilUtils::constString token; int dims[2] = { nrows, ncols }; AprilUtils::SharedPtr< Matrix > mat; mat = new Matrix(2,dims); int i=0; typename Matrix::iterator data_it(mat->begin()); bool use_map = !map.empty(); if (read_empty) { // Allows delim at end of the token and therefore empty fields can be // identified and assigned to default_value. while (data_it!=mat->end() && (line=readULine(stream, c_str.get(), true))) { int num_cols_size_count = 0; while (data_it!=mat->end()) { token = line.extract_token(delim, read_empty); if (!token) break; if ( read_empty && token.len() == 1 && ( strchr(delim, token[0]) || strchr("\r\n", token[0]) ) ) { *data_it = default_value; } else { char back = token[token.len()-1]; if (!ascii_extractor(token, *data_it)) { if (use_map) { size_t len = token.len(); if (read_empty && (strchr(delim, back) || strchr("\r\n", back))) { april_assert(token.len() > 1u); len -= 1u; } *data_it = map.opt((const char *)(token), len, default_value); } // if (use_map) else { // not use_map break; } } } ++data_it; ++num_cols_size_count; } if (num_cols_size_count != ncols) { mat.reset(); ERROR_EXIT3(128, "Incorrect number of elements at line %d, " "expected %d, found %d\n", i, ncols, num_cols_size_count); } ++i; } } else { // Doesn't allow delim at end of the token and empty fields are forbidden while (data_it!=mat->end() && (line=readULine(stream, c_str.get()))) { int num_cols_size_count = 0; while (data_it!=mat->end()) { token = line.extract_token(delim, read_empty); if (!token) break; if (!ascii_extractor(token, *data_it)) { if (!use_map || map.checkNil((const char *)token)) break; *data_it = map.get((const char *)(token), token.len()); } ++data_it; ++num_cols_size_count; } if (num_cols_size_count != ncols) { mat.reset(); ERROR_EXIT3(128, "Incorrect number of elements at line %d, " "expected %d, found %d\n", i, ncols, num_cols_size_count); } ++i; } } if (data_it!=mat->end()) { ERROR_PRINT("Impossible to fill all the matrix components\n"); mat.reset(); } return mat.weakRelease(); } template void Matrix::writeTab(AprilIO::StreamInterface *stream, const AprilUtils::LuaTable &options) { const char *delim = options.opt(MatrixIO::DELIM_OPTION, " "); MatrixIO::AsciiCoder ascii_coder; if (this->getNumDim() != 2) { ERROR_EXIT(128, "Needs a matrix with 2 dimensions"); } /* Legacy code MatrixIO::AsciiSizer ascii_sizer; int sizedata; sizedata = ascii_sizer(this); size_t expected_size = static_cast(sizedata+1); UNUSED_VARIABLE(expected_size); */ if (!stream->isOpened()) { ERROR_EXIT(256, "The stream is not prepared\n"); } const int columns = this->getDimSize(1); int i=0; for(typename Matrix::const_iterator it(this->begin()); it!=this->end();++it,++i) { ascii_coder(*it, stream); stream->printf("%c", ((((i+1) % columns) == 0) ? '\n' : delim[0])); } if ((i % columns) != 0) { stream->printf("\n"); } } } // namespace Basics #endif // MATRIX_SERIALIZATION april-ann-0.4.1/packages/basics/matrix/c_src/matrix.h000066400000000000000000000771311263004425400225020ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIX_H #define MATRIX_H #include #include #include // surprisingly, placement new doesn't work without this #include "aligned_memory.h" #include "april_assert.h" #include "c_string.h" #include "cblas_headers.h" #include "cmath_overloads.h" #include "clamp.h" #include "disallow_class_methods.h" #include "gpu_mirrored_memory_block.h" #include "maxmin.h" #include "mmapped_data.h" #include "logbase.h" #include "qsort.h" #include "serializable.h" #include "smart_ptr.h" #include "swap.h" #include "unused_variable.h" #include "mathcore.h" namespace Basics { namespace MatrixIO { /// Boolean option key for read/write using tabulated format. const char * const TAB_OPTION = "tab"; /// Boolean option key for read/write using ascii format. const char * const ASCII_OPTION = "ascii"; /// String option key with a delimitiers list. const char * const DELIM_OPTION = "delim"; /// Boolean option key indicating if empty fields are allowed during read. const char * const EMPTY_OPTION = "read_empty"; /// T option key indicating the default value for empty fields. const char * const DEFAULT_OPTION = "default"; /// T option key indicating the expected number of columns. const char * const NCOLS_OPTION = "ncols"; /// T option key indicating the expected number of rows. const char * const NROWS_OPTION = "nrows"; /// T option key indicating a map of strings into T values. const char * const MAP_OPTION = "map"; } // forward declaration template class SparseMatrix; /** * @brief Multidimensional matrix class. * * It implements basic tensor operations. */ template class Matrix : public AprilIO::Serializable { APRIL_DISALLOW_ASSIGN(Matrix); // friend class SparseMatrix; const static unsigned int MATRIX_BINARY_VERSION; enum matrix_contiguous_enum_t { NONE=0, CONTIGUOUS=1, NONCONTIGUOUS=2 }; // Auxiliary count variable where the user could store the number of times // this object is shared in a computation (like in ANN components sharing // weight matrices) unsigned int shared_count; protected: /// Number of dimensions int numDim; /// Size of each dimension int *stride; /// Offset for sub-matrix int offset; /// Sub-matrix size of each dimension int *matrixSize; /// Total size of the matrix (number of elements) int total_size; int last_raw_pos; /// Pointer to data AprilUtils::SharedPtr< AprilMath::GPUMirroredMemoryBlock > data; AprilUtils::SharedPtr< AprilUtils::MMappedDataReader > mmapped_data; /// For CUDA purposes bool use_cuda; /// To know if it is contiguous mutable matrix_contiguous_enum_t is_contiguous; /// Returns the data pointer for read and write T *getData() { return data->getPPALForReadAndWrite(); } /// Returns the data pointer for read const T *getData() const { return data->getPPALForRead(); } int getLastRawPos() const { return last_raw_pos; } public: class sliding_window; friend class sliding_window; /// Returns if the matrix is a vector bool isVector() const { return (numDim==1 || (numDim==2 && ( (matrixSize[0]==1) || (matrixSize[1]==1) ))); } bool isColVector() const { return (numDim==2 && matrixSize[1]==1); } /// Returns the stride of the vector, the stride whom coordinate is different /// of 1. It only works if the matrix is a vector (precondition). int getVectorStride() const { return (numDim == 1) ? stride[0] : ( (matrixSize[0]!=1) ? (stride[0]) : (stride[1]) ); } /// Computes the position at data array given it coordinates int computeRawPos(const int *coords) const; /// Computes the position at data array given it coordinates int computeRawPos(const int *coords, const int *offset) const; /// Computes the coordinates given the raw data position void computeCoords(const int raw_pos, int *coords) const; /// Updates with the following coordinates vector bool nextCoordVectorRowOrder(int *coords, int &raw_pos) const; bool nextCoordVectorColOrder(int *coords, int &raw_pos) const; bool nextCoordVectorRowOrder(int *coords) const; bool nextCoordVectorColOrder(int *coords) const; static bool nextCoordVectorRowOrder(int *coords, const int *sizes, const int numDim); static bool nextCoordVectorColOrder(int *coords, const int *sizes, const int numDim); static bool nextCoordVectorRowOrder(int *coords, int &raw_pos, const int *sizes, const int *strides, const int numDim, const int last_raw_pos); static bool nextCoordVectorColOrder(int *coords, int &raw_pos, const int *sizes, const int *strides, const int numDim, const int last_raw_pos); /********* Iterators for Matrix traversal *********/ /** * @brief This iterator only traverses the Matrix positions, but doesn't * have access to the memory. * * @todo Implement other iterators as wrappers or derived class from * pos_iterator, allowing to share a lot of code. */ class pos_iterator { friend class Matrix; const Matrix *m; ///< A weak reference. int idx; int raw_pos; /// The coords array is only used when the matrix is not congiuous, /// otherwise it is NULL int *coords; public: pos_iterator(const Matrix *m); pos_iterator(); ~pos_iterator(); inline pos_iterator &operator=(const pos_iterator &other); inline bool operator==(const pos_iterator &other) const; inline bool operator!=(const pos_iterator &other) const; inline pos_iterator &operator++(); int getRawPos() const { return raw_pos; } int getIdx() const { return idx; } bool isEnd() const { return raw_pos == m->last_raw_pos+1; } }; // forward declaration class const_iterator; class iterator { friend class const_iterator; friend class Matrix; Matrix *m; ///< A weak reference. int idx; int raw_pos; /// The coords array is only used when the matrix is not congiuous, /// otherwise it is NULL int *coords; T *data; iterator(Matrix *m); iterator(Matrix *m, int raw_pos); iterator(Matrix *m, int raw_pos, int *coords); public: iterator(); iterator(const iterator &other); ~iterator(); inline iterator &operator=(const iterator &other); inline bool operator==(const iterator &other) const; inline bool operator!=(const iterator &other) const; inline iterator &operator++(); inline T &operator*(); inline T *operator->(); int getRawPos() const; int getIdx() const { return idx; } }; /*******************************************************/ class const_iterator { friend class Matrix; const Matrix *m; ///< A weak reference. int idx; int raw_pos; /// The coords array is only used when the matrix is not congiuous, /// otherwise it is NULL int *coords; const T *data; const_iterator(const Matrix *m); const_iterator(const Matrix *m, int raw_pos); const_iterator(const Matrix *m, int raw_pos, int *coords); public: const_iterator(); const_iterator(const const_iterator &other); const_iterator(const iterator &other); /*const_iterator(const iterator &other);*/ ~const_iterator(); inline const_iterator &operator=(const const_iterator &other); inline const_iterator &operator=(const iterator &other); inline bool operator==(const const_iterator &other) const; inline bool operator==(const iterator &other) const; inline bool operator!=(const const_iterator &other) const; inline bool operator!=(const iterator &other) const; inline const_iterator &operator++(); inline const T &operator*() const; inline const T *operator->() const; int getRawPos() const; int getIdx() const { return idx; } }; /********************************************************/ /** * The sliding is a kind of iterator which traverses the matrix producing * sub-matrices following a sliding window similar to dataset.matrix. This * iterator couldn't account for CIRCULAR and OUTSIDE values. This objects * IncRefs the given reference, so be careful to check not 0 references in * the given matrix object. */ class sliding_window : public Referenced { /// A reference to the matrix AprilUtils::SharedPtr< Matrix > m; /// Offset coordinates int *offset; /// subPattern size. int *sub_matrix_size; /// Step of each dimension for the sliding window. int *step; /// Number of movements on each dimension (number of steps). int *num_steps; /// Order of movement for each dimension. int *order_step; /// Coordinate position of the first component int *coords; /// Current position at the matrix of the first component int raw_pos; /// int total_size, last_raw_pos; bool finished; /// auxiliary computation int *offset_plus_num_step_by_step; /// Number of windows generated by the iterator int num_windows; public: sliding_window(); sliding_window(Matrix *m, const int *sub_matrix_size=0, const int *offset=0, const int *step=0, const int *num_steps=0, const int *order_step=0); sliding_window(const sliding_window &other); ~sliding_window(); inline sliding_window &operator=(const sliding_window &other); inline sliding_window *next(); /// This method returns the matrix at the current window position. If a /// matrix is given, it must be created before using previous execution of /// getMatrix method. WARNING, the matrix is not check to be correct, so be /// careful. inline Matrix *getMatrix(Matrix *dest=0); inline bool isEnd() const { return finished; } inline int numWindows() const; inline void setAtWindow(int windex); inline const int *getCoords() const; inline int getNumDim() const; }; /********************************************************/ /** * The span iterator traverses the matrix allowing to do a linear traversal of * a given dimension. The class allows to generate offset, stride and size * values which given the Matrix base pointer could be used to access to any * position in a given dimension span. */ class span_iterator { friend class Matrix; const Matrix *m; ///< A weak reference. int raw_pos; int *coords, *order; int num_iterations; struct inverse_sort_compare { const Matrix *m; inverse_sort_compare(const Matrix *m) : m(m) { } bool operator()(const int &a, const int &b) const { const int a_sz = m->matrixSize[a]; const int b_sz = m->matrixSize[b]; if (a_sz == b_sz) { return b < a; } // Don't use a trade-off between size and stride, it will be unsafe with // transposed matrices else { return a_sz > b_sz; } } }; // void initialize(const Matrix *m, int raw_pos, int dim); // span_iterator(const Matrix *m, int raw_pos, int dim); public: span_iterator(const Matrix *m, const int *order); span_iterator(const Matrix *m, int dim = -1); span_iterator(); span_iterator(const span_iterator &other); ~span_iterator(); inline int getOffset() const; inline int getStride() const; inline int getSize() const; inline span_iterator &operator=(const span_iterator &other); inline bool operator==(const span_iterator &other) const; inline bool operator!=(const span_iterator &other) const; inline span_iterator &operator++(); inline int numberOfIterations() const; inline void setAtIteration(int idx); const int *getDimOrder() const { return order; } const int *getCoordinates() const { return coords; } }; /********************************************************/ /** * The random access iterator allows to retain the memory pointer, forcing an * update between host and device (GPU) memory, and allows to access any * position of the matrix given its coordinates. */ class random_access_iterator { Matrix *m; ///< A weak reference. T *memory; int *coords; public: random_access_iterator(Matrix *m) : m(m), memory(m->getRawDataAccess()->getPPALForReadAndWrite()), coords(new int[m->numDim]) { } ~random_access_iterator() { delete[] coords; } /// Raw access operation, CAUTION it is dangerous T& operator[] (int raw_pos) { return memory[raw_pos]; } /// Acces for uni-dimensional matrices T& operator() (int i) { april_assert(m->numDim == 1); int raw_pos = m->computeRawPos(&i); return memory[raw_pos]; } /// Acces for bi-dimensional matrices T& operator() (int row, int col) { april_assert(m->numDim == 2); coords[0] = row; coords[1] = col; int raw_pos = m->computeRawPos(coords); return memory[raw_pos]; } /// Acces for N-dimensional matrices T& operator() (int coord0, int coord1, int coord2, ...) { april_assert(m->numDim >= 3); coords[0] = coord0; coords[1] = coord1; coords[2] = coord2; va_list ap; va_start(ap, coord2); for(int i=3; inumDim; i++) { int coordn = va_arg(ap, int); coords[i] = coordn; } va_end(ap); int raw_pos = m->computeRawPos(coords); return memory[raw_pos]; } /// Acces for N-dimensional by using a vector of coordinates T& operator() (int *coords, int sz) { UNUSED_VARIABLE(sz); april_assert(m->numDim == sz); int raw_pos = m->computeRawPos(coords); return memory[raw_pos]; } }; /** * The const random access iterator allows to retain the memory pointer, * forcing an update between host and device (GPU) memory, and allows to * access any position of the matrix given its coordinates. It is a read-only * iterator. */ class const_random_access_iterator { const Matrix *m; ///< A weak reference. const T *memory; int *coords; public: const_random_access_iterator(const Matrix *m) : m(m), memory(m->getRawDataAccess()->getPPALForRead()), coords(new int[m->numDim]) { } ~const_random_access_iterator() { delete[] coords; } /// Raw access operation, CAUTION it is dangerous const T& operator[] (int raw_pos) const { return memory[raw_pos]; } const T& operator() (int i) const { april_assert(m->numDim == 1); int raw_pos = m->computeRawPos(&i); return memory[raw_pos]; } const T& operator() (int row, int col) const { april_assert(m->numDim == 2); coords[0] = row; coords[1] = col; int raw_pos = m->computeRawPos(coords); return memory[raw_pos]; } const T& operator() (int coord0, int coord1, int coord2, ...) const { april_assert(m->numDim >= 3); coords[0] = coord0; coords[1] = coord1; coords[2] = coord2; va_list ap; va_start(ap, coord2); for(int i=3; inumDim; i++) { int coordn = va_arg(ap, int); coords[i] = coordn; } va_end(ap); int raw_pos = m->computeRawPos(coords); return memory[raw_pos]; } const T& operator() (int *coords, int sz) const { UNUSED_VARIABLE(sz); april_assert(m->numDim == sz); int raw_pos = m->computeRawPos(coords); return memory[raw_pos]; } }; private: // const version of iterators, for fast end() iterator calls. They are // allocated on-demand, so if end() methods are never executed, they // don't waste memory space mutable iterator end_iterator; mutable const_iterator end_const_iterator; mutable span_iterator end_span_iterator_; // NULL constructor Matrix() : is_contiguous(NONE), end_iterator(), end_const_iterator(), end_span_iterator_() { } /** * @note This constructor allocates memory for stride and matrixSize only if * both arrays are given. Otherwise matrixSize and stride will be set to * NULL. */ Matrix(int numDim, const int *stride, const int offset, const int *matrixSize, const int total_size, const int last_raw_pos, AprilMath::GPUMirroredMemoryBlock *data, const bool use_cuda, AprilUtils::MMappedDataReader *mmapped_data = 0); /// Modifies the offset of the matrix. WARNING, this method doesn't check the /// new data position, so be sure that it fits in the data pointer size void changeSubMatrixData(const int new_offset, const int new_last_raw_pos) { offset = new_offset; last_raw_pos = new_last_raw_pos; end_iterator.m = 0; end_const_iterator.m = 0; end_span_iterator_.m = 0; } public: /********** Constructors ***********/ /// Full constructor given numDim, dim, data, offset, stride Matrix(int numDim, const int* dim, AprilMath::GPUMirroredMemoryBlock *data = 0, int offset = 0, const int* stride = 0); /// Constructor with variadic arguments. explicit Matrix(int numDim, int d1, ...); /// Constructor given other matrix, it does a shallow or deep copy (clone). By /// default is a deep copy, some code pieces expect this behavior, don't /// change it. Matrix(Matrix *other, bool clone=true); /// Sub-matrix constructor Matrix(Matrix *other, const int* coords, const int *sizes, bool clone=true); /// Sub-matrix constructor of a const matrix. WARNING, this matrices don't /// allow writes if clone=false explicit Matrix(const Matrix *other, const int* coords, const int *sizes, bool clone=true); /// Destructor virtual ~Matrix(); /// Constructor from a MMAP file static Matrix *fromMMappedDataReader(AprilUtils::MMappedDataReader *mmapped_data); /// Writes to a file void toMMappedDataWriter(AprilUtils::MMappedDataWriter *mmapped_data) const; /// For DEBUG purposes void print() const; /// Modify sizes of matrix, returns this if rewrap is not necessary Matrix *rewrap(const int *new_dims, int len, bool clone_if_not_contiguous=false); /// Modify sizes of matrix, returns always a new instance Matrix *constRewrap(const int *new_dims, int len, bool clone_if_not_contiguous=false) const; /// Add singleton dimensions at left Matrix *leftInflate(int n) const; /// Add singleton dimensions at right Matrix *rightInflate(int n) const; /// Removes all singleton dimensions, always returns a new instance Matrix *constSqueeze() const; /// Removes all singleton dimensions, returns this when fails squeezing Matrix *squeeze(); /* Getters and setters */ int getNumDim() const { return numDim; } const int *getDimPtr() const { return matrixSize; } const int *getStridePtr() const { return stride; } int getDimSize(int i) const { return matrixSize[i]; } int getStrideSize(int i) const { return stride[i]; } int size() const { return total_size; } void setUseCuda(bool v) { use_cuda = v; #ifdef USE_CUDA if (use_cuda) data->updateMemGPU(); #endif } bool getCudaFlag() const { return use_cuda; } bool isSimple() const { return (getIsContiguous()); } /// Indicates if it is a contiguous matrix bool getIsContiguous() const; /// Returns the offset of first data value (sub-matrix) int getOffset() const { return offset; } /**********************/ iterator begin() { return iterator(this); } iterator iteratorAt(int c0) { april_assert(numDim==1); return iterator(this, computeRawPos(&c0), &c0); } iterator iteratorAt(int c0, int c1) { april_assert(numDim==2); int aux[2]={c0,c1}; return iterator(this, computeRawPos(aux), aux); } iterator iteratorAt(int *coords, int len) { UNUSED_VARIABLE(len); april_assert(numDim==len); return iterator(this, computeRawPos(coords), coords); } const iterator &end() { if (end_iterator.m == 0) end_iterator = iterator(this, last_raw_pos+1); return end_iterator; } const span_iterator &end_span_iterator() const { if (end_span_iterator_.m == 0) end_span_iterator_ = span_iterator(this, last_raw_pos+1, -1); return end_span_iterator_; } /************************/ const_iterator begin() const { return const_iterator(this); } const_iterator iteratorAt(int c0) const { april_assert(numDim==1); return const_iterator(this, computeRawPos(&c0), &c0); } const_iterator iteratorAt(int c0, int c1) const { april_assert(numDim==2); int aux[2]={c0,c1}; return const_iterator(this, computeRawPos(aux), aux); } const_iterator iteratorAt(int *coords, int len) const { UNUSED_VARIABLE(len); april_assert(numDim==len); return const_iterator(this, computeRawPos(coords), coords); } const const_iterator &end() const { if (end_const_iterator.m == 0) end_const_iterator = const_iterator(this, last_raw_pos+1); return end_const_iterator; } /// Symbolic transposition, changes strides order Matrix* transpose(); /// Symbolic transposition, changes strides order Matrix* transpose(int dim1, int dim2); /// Copy only sizes, but not data Matrix* cloneOnlyDims() const; /// Deep copy Matrix* clone() const; /// Shallow copy Matrix* shallowCopy(); /// Number values check void pruneSubnormalAndCheckNormal(); /// This method sets to zero the shared counter void resetSharedCount() { shared_count = 0; } /// This method adds counts to the shared counter void addToSharedCount(unsigned int count=1) { shared_count += count; } /// Getter of the shared count value unsigned int getSharedCount() const { return shared_count; } /// Raw access operator [] T& operator[] (int i); const T& operator[] (int i) const; // Access to independent elements, one and two dimensions are special cases T& operator() (int i); T& operator() (int row, int col); T& operator() (int coord0, int coord1, int coord2, ...); T& operator() (int *coords, int sz); const T& operator() (int i) const; const T& operator() (int row, int col) const; const T& operator() (int coord0, int coord1, int coord2, ...) const; const T& operator() (int *coords, int sz) const; /// Function to obtain RAW access to data pointer. Be careful with it, you /// are losing sub-matrix abstraction. AprilMath::GPUMirroredMemoryBlock *getRawDataAccess() { return data.get(); } const AprilMath::GPUMirroredMemoryBlock *getRawDataAccess() const { return data.get(); } bool getCol(int col, T* vec, int vecsize); bool putCol(int col, T *vec, int vecsize); bool putSubCol(int col, int first_row, T *vec, int vecsize); /// Returns true if they have the same dimension template bool sameDim(const Matrix *other) const; bool sameDim(const int *dims, const int len) const; /** * @brief Returns a matrix of one less dimension, with the elements selected * for the given dimension at the given index. * * If @c dest matrix is given, it should be created using a previous * execution of select method over the same dimension, otherwise, the * behavior of select is undefined. * * @note WARNING, @c dest matrix correctness is not checked, so, be * careful. * * @code * // A tipical use case for a efficient select use with a matAxpy operation * // Let A a Basics::Matrix of NxM * // Let B a Basics::Matrix of Nx1 * AprilUtils::SharedPtr< Basics::Matrix > col; * for (int i=0; igetDimSize(1); ++i) { * // The first iteration, col=0 and select initialize the col matrix, * // the following iterations the same col matrix will be reused. * col = A->select(1, i, col.get()); * matAxpy(col.get(), 1.0, B); * } * @endcode */ Matrix *select(int dim, int index, Matrix *dest=0) const; // Expands current matrix to a diagonal matrix Matrix *diagonalize() const; /**** LAPACK OPERATIONS ****/ // SYNC GPU OR PPAL IF NEEDED void sync() { #ifdef USE_CUDA data->forceSync(use_cuda); #endif } void sync() const { #ifdef USE_CUDA data->forceSync(use_cuda); #endif } /*Matrix **unrolled_kernel=0, Matrix **unrolled_this=0);*/ Matrix *padding(int *begin_padding, int *end_padding, T default_value=T()) const; Matrix *padding(int pad_value, T default_value=T()) const; // SERIALIZATION virtual const char *luaCtorName() const { ERROR_EXIT(128, "Serialization not implemented\n"); return 0; } virtual int exportParamsToLua(lua_State *L) { AprilUtils::LuaTable t(L); AprilUtils::LuaTable sizes(L); AprilUtils::LuaTable stride(L); for (int i=0; i *read(AprilIO::StreamInterface *stream, const AprilUtils::LuaTable &options); private: void allocate_memory(int size); void release_memory(); void initialize(const int *dim, int offset=0, const int *stride=0); static AprilUtils::constString readULine(AprilIO::StreamInterface *stream, AprilIO::CStringStream *dest, bool read_empty = false) { // Not needed, it is done in extractULineFromStream: dest->clear(); extractULineFromStream(stream, dest, read_empty); return dest->getConstString(); } void writeNormal(AprilIO::StreamInterface *stream, const AprilUtils::LuaTable &options); void writeTab(AprilIO::StreamInterface *stream, const AprilUtils::LuaTable &options); static Matrix *readNormal(AprilIO::StreamInterface *stream, const AprilUtils::LuaTable &options); static Matrix *readTab(AprilIO::StreamInterface *stream, const AprilUtils::LuaTable &options); }; } // namespace Basics #include "sparse_matrix.h" // must be defined here #include "matrix_ext.h" #include "matrix.impl.h" #include "matrix-iterators.impl.h" #include "matrix-serialization.impl.h" #include "matrixFloat.h" #include "matrixDouble.h" #include "matrixComplexF.h" #include "matrixInt32.h" #include "matrixChar.h" #include "matrixBool.h" #endif // MATRIX_H april-ann-0.4.1/packages/basics/matrix/c_src/matrix.impl.h000066400000000000000000001144731263004425400234430ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIX_IMPL_H #define MATRIX_IMPL_H #include #include #include #include #include #include "april_print.h" #include "cmath_overloads.h" #include "error_print.h" #include "ignore_result.h" #include "matrix.h" #include "omp_utils.h" // Must be defined in this order. #include "matrix_ext.h" namespace Basics { template const unsigned int Matrix::MATRIX_BINARY_VERSION = 0x00000001; template void Matrix::initialize(const int *dim, int offset, const int *_stride) { last_raw_pos = offset; total_size=1; for(int i=numDim-1; i>=0; --i) { stride[i] = (_stride == 0) ? total_size : _stride[i]; total_size *= dim[i]; matrixSize[i] = dim[i]; april_assert(matrixSize[i] > 0); last_raw_pos += stride[i] * (dim[i]-1); } } /// Allocation of memory for data pointer. It is Referenced for sharing. template void Matrix::allocate_memory(int size) { data.reset( new AprilMath::GPUMirroredMemoryBlock(static_cast(size)) ); } /// Release of the memory allocated for data pointer. template void Matrix::release_memory() { data.reset(); } /// Null constructor template Matrix::Matrix(int numDim, const int *stride, const int offset, const int *matrixSize, const int total_size, const int last_raw_pos, AprilMath::GPUMirroredMemoryBlock *data, const bool use_cuda, AprilUtils::MMappedDataReader *mmapped_data) : AprilIO::Serializable(), shared_count(0), numDim(numDim), stride(NULL), offset(offset), matrixSize(NULL), total_size(total_size), last_raw_pos(last_raw_pos), data(data), mmapped_data(mmapped_data), use_cuda(use_cuda), is_contiguous(NONE), end_iterator(), end_const_iterator(), end_span_iterator_() { if (stride && matrixSize) { this->matrixSize = new int[numDim]; this->stride = new int[numDim]; for (int i=0; istride[i] = stride[i]; this->matrixSize[i] = matrixSize[i]; } } else if (stride || matrixSize) { ERROR_EXIT(128, "Improper call, stride=0 XOR matrixSize==0 is not true\n"); } april_assert(offset >= 0); } /// Default constructor template Matrix::Matrix(int numDim, const int* dim, AprilMath::GPUMirroredMemoryBlock *data, int offset, const int* _stride) : AprilIO::Serializable(), shared_count(0), numDim(numDim), offset(offset), data(data), use_cuda(AprilMath::GPUMirroredMemoryBlockBase::USE_CUDA_DEFAULT), is_contiguous(NONE), end_iterator(), end_const_iterator(), end_span_iterator_() { stride = new int[numDim]; matrixSize = new int[numDim]; initialize(dim, offset, _stride); april_assert(total_size <= last_raw_pos+1); if (this->data.empty()) allocate_memory(last_raw_pos + 1); else { if (static_cast(this->data->getSize()) <= last_raw_pos) ERROR_EXIT2(128, "Data pointer size doesn't fit, expected %d, found %d\n", last_raw_pos+1, data->getSize()); } april_assert(offset >= 0); } /// Constructor for sub-matrix building template Matrix::Matrix(Matrix *other, const int* coords, const int *sizes, bool clone) : AprilIO::Serializable(), shared_count(0), numDim(other->numDim), offset(0), use_cuda(other->use_cuda), is_contiguous(NONE), end_iterator(), end_const_iterator(), end_span_iterator_() { for (int i=0; i other->matrixSize[i]) ERROR_EXIT3(128, "Size+coordinates are out of dimension size: %d+%d>%d\n", sizes[i], coords[i], other->matrixSize[i]); } stride = new int[numDim]; matrixSize = new int[numDim]; if (clone) { initialize(sizes); allocate_memory(total_size); span_iterator it(this); const int *dims_order = it.getDimOrder(); const int first_dim = dims_order[0]; const int this_stride = it.getStride(); const int other_stride = other->getStrideSize(first_dim); const int N = it.numberOfIterations(); for (int i=0; iend_span_iterator()); const int other_raw_pos = other->computeRawPos(it.getCoordinates(), coords); doCopy(it.getSize(), other->data.get(), other_stride, other_raw_pos, this->data.get(), this_stride, it.getOffset(), this->getCudaFlag()); ++it; } april_assert(it == this->end_span_iterator()); } // if (clone) else { // !clone AprilUtils::UniquePtr aux_coords( new int[numDim] ); total_size = 1; for (int i=0; istride[i]; matrixSize[i] = sizes[i]; total_size = total_size * sizes[i]; aux_coords[i] = sizes[i]-1; } offset = other->computeRawPos(coords); data = other->data; last_raw_pos = computeRawPos(aux_coords.get()); } // !clone april_assert(offset >= 0); } // Constructor for sub-matrix building from a CONST matrix template Matrix::Matrix(const Matrix *other, const int* coords, const int *sizes, bool clone) : AprilIO::Serializable(), shared_count(0), numDim(other->numDim), offset(0), use_cuda(other->use_cuda), is_contiguous(NONE), end_iterator(), end_const_iterator(), end_span_iterator_() { for (int i=0; i other->matrixSize[i]) ERROR_EXIT3(128, "Size+coordinates are out of dimension size: %d+%d>%d\n", sizes[i], coords[i], other->matrixSize[i]); } stride = new int[numDim]; matrixSize = new int[numDim]; if (clone) { initialize(sizes); allocate_memory(total_size); span_iterator it(this), it_other(other, it.getDimOrder()); const int *dims_order = it_other.getDimOrder(); const int first_dim = dims_order[0]; int diff_raw_pos = other->getStrideSize(first_dim) * coords[first_dim]; int other_first_iteration = 0; if (numDim > 1) { // compute it_other traversal length until the coordinates of the slice // (except first_dim) AprilUtils::UniquePtr aux_stride( new int[numDim] ); aux_stride[dims_order[0]] = 1; aux_stride[dims_order[1]] = 1; for (int i=2; imatrixSize[i-1]; } other_first_iteration = 0; for (int i=1; i OMPUtils::get_num_threads()) { #pragma omp parallel for firstprivate(it) firstprivate(it_other) for (int i=0; iend_span_iterator()); april_assert(it_other != other->end_span_iterator()); doCopy(it.getSize(), other->data.get(), it_other.getStride(), diff_raw_pos + it_other.getOffset(), this->data.get(), it.getStride(), it.getOffset(), this->getCudaFlag()); } } else { #else it_other.setAtIteration(other_first_iteration); for (int i=0; iend_span_iterator()); april_assert(it_other != other->end_span_iterator()); doCopy(it.getSize(), other->data.get(), it_other.getStride(), diff_raw_pos + it_other.getOffset(), this->data.get(), it.getStride(), it.getOffset(), this->getCudaFlag()); ++it; ++it_other; } #endif #ifndef NO_OMP } #endif } else { int *aux_coords = new int[numDim]; total_size = 1; for (int i=0; istride[i]; matrixSize[i] = sizes[i]; total_size = total_size * sizes[i]; aux_coords[i] = sizes[i]-1; } offset = other->computeRawPos(coords); data.reset( new AprilMath:: GPUMirroredMemoryBlock(other->size(), other->data->getPPALForRead()) ); last_raw_pos = computeRawPos(aux_coords); delete[] aux_coords; } april_assert(offset >= 0); } /// Constructor with variable arguments template Matrix::Matrix(int numDim, int d1, ...) : AprilIO::Serializable(), shared_count(0), numDim(numDim), offset(0), use_cuda(AprilMath::GPUMirroredMemoryBlockBase::USE_CUDA_DEFAULT), is_contiguous(NONE), end_iterator(), end_const_iterator(), end_span_iterator_() { int *dim = new int[numDim]; stride = new int[numDim]; matrixSize = new int[numDim]; va_list ap; va_start(ap, d1); dim[0]=d1; for (int i=1; i Matrix::Matrix(Matrix *other, bool clone) : AprilIO::Serializable(), shared_count(0), numDim(other->numDim), offset(0), use_cuda(other->use_cuda), is_contiguous(NONE), end_iterator(), end_const_iterator(), end_span_iterator_() { stride = new int[numDim]; matrixSize = new int[numDim]; total_size = other->total_size; last_raw_pos = other->last_raw_pos; if (clone) { initialize(other->matrixSize); allocate_memory(total_size); AprilMath::MatrixExt::BLAS::matCopy(this, other); } else { offset = other->offset; data = other->data; for (int i=0; istride[i]; matrixSize[i] = other->matrixSize[i]; } } april_assert(offset >= 0); } template Matrix *Matrix::fromMMappedDataReader(AprilUtils::MMappedDataReader *mmapped_data) { Matrix *obj = new Matrix(); // obj->data.reset( AprilMath::GPUMirroredMemoryBlock:: fromMMappedDataReader(mmapped_data) ); // unsigned int binary_version = *(mmapped_data->get()); if (binary_version != MATRIX_BINARY_VERSION) ERROR_EXIT1(128, "Incorrect binary matrix version from commit number %d\n", mmapped_data->getCommitNumber()); int N = *(mmapped_data->get()); obj->numDim = N; obj->stride = mmapped_data->get(N); obj->offset = *(mmapped_data->get()); obj->matrixSize = mmapped_data->get(N); obj->total_size = *(mmapped_data->get()); obj->last_raw_pos = *(mmapped_data->get()); CBLAS_ORDER dummy1 = *(mmapped_data->get()); bool dummy2 = *(mmapped_data->get()); // legacy transposed flag UNUSED_VARIABLE(dummy1); UNUSED_VARIABLE(dummy2); // NON MAPPED DATA obj->use_cuda = AprilMath::GPUMirroredMemoryBlockBase::USE_CUDA_DEFAULT; obj->shared_count = 0; obj->is_contiguous = NONE; // THE MMAP POINTER obj->mmapped_data.reset( mmapped_data ); // april_assert(obj->offset >= 0); return obj; } template void Matrix::toMMappedDataWriter(AprilUtils::MMappedDataWriter *mmapped_data) const { data->toMMappedDataWriter(mmapped_data); mmapped_data->put(&MATRIX_BINARY_VERSION); mmapped_data->put(&numDim); mmapped_data->put(stride, numDim); mmapped_data->put(&offset); mmapped_data->put(matrixSize, numDim); mmapped_data->put(&total_size); mmapped_data->put(&last_raw_pos); CBLAS_ORDER dummy1=CblasRowMajor; mmapped_data->put(&dummy1); bool dummy2=false; // legacy transposed flag mmapped_data->put(&dummy2); } template Matrix::~Matrix() { release_memory(); if (mmapped_data.empty()) { delete[] stride; delete[] matrixSize; } } template void Matrix::print() const { for (Matrix::const_iterator it(begin()); it != end(); ++it) { AprilUtils::aprilPrint(*it); printf(" "); } printf("\n"); } template Matrix *Matrix::rewrap(const int *new_dims, int len, bool clone_if_not_contiguous) { bool need_clone = false; AprilUtils::SharedPtr< Matrix > obj; if (!getIsContiguous()) { if (!clone_if_not_contiguous) { ERROR_EXIT(128, "Impossible to re-wrap non contiguous matrix, " "clone it first\n"); } else { need_clone = true; } } bool equal = true; int new_size = 1; for (int i=0; i=numDim || new_dims[i] != matrixSize[i]) equal=false; new_size *= new_dims[i]; } if (len==numDim && equal) return this; if (new_size != size()) { ERROR_EXIT2(128, "Incorrect size, expected %d, and found %d\n", size(), new_size); } if (need_clone) { AprilMath::GPUMirroredMemoryBlock *new_data = new AprilMath::GPUMirroredMemoryBlock(new_size); obj = new Matrix(len, new_dims, new_data); AprilUtils::SharedPtr< Matrix > aux( obj->rewrap(this->getDimPtr(), this->getNumDim()) ); AprilMath::MatrixExt::BLAS::matCopy(aux.get(),this); } else { obj = new Matrix(len, new_dims, data.get(), offset); } #ifdef USE_CUDA obj->setUseCuda(use_cuda); #endif return obj.weakRelease(); } template Matrix *Matrix::constRewrap(const int *new_dims, int len, bool clone_if_not_contiguous) const { bool need_clone = false; AprilUtils::SharedPtr< Matrix > obj; if (!getIsContiguous()) { if (!clone_if_not_contiguous) { ERROR_EXIT(128, "Impossible to re-wrap non contiguous matrix, " "clone it first\n"); } else { need_clone = true; } } int new_size = 1; for (int i=0; i *new_data = new AprilMath::GPUMirroredMemoryBlock(new_size); obj = new Matrix(len, new_dims, new_data); AprilUtils::SharedPtr< Matrix > aux( obj->rewrap(this->getDimPtr(), this->getNumDim()) ); AprilMath::MatrixExt::BLAS::matCopy(aux.get(),this); } else { obj = new Matrix(len, new_dims, const_cast*>(data.get()), offset); } #ifdef USE_CUDA obj->setUseCuda(use_cuda); #endif return obj.weakRelease(); } template Matrix *Matrix::constSqueeze() const { int len = 0; AprilUtils::UniquePtr sizes(new int[getNumDim()]); AprilUtils::UniquePtr strides(new int[getNumDim()]); for (int i=0; i 1) { strides[len] = getStrideSize(i); sizes[len++] = sz; } } // matrices with 1x1x1x...x1 dimensions need the following sanity check if (len == 0) { strides[len] = 1; sizes[len++] = 1; } AprilUtils::SharedPtr< Matrix > obj = new Matrix(len, NULL, getOffset(), NULL, size(), last_raw_pos, const_cast< AprilMath::GPUMirroredMemoryBlock*>(data.get()), use_cuda, const_cast< AprilUtils::MMappedDataReader*>(mmapped_data.get())); obj->matrixSize = sizes.release(); obj->stride = strides.release(); return obj.weakRelease(); } template Matrix *Matrix::squeeze() { int len = 0; AprilUtils::UniquePtr sizes(new int[getNumDim()]); AprilUtils::UniquePtr strides(new int[getNumDim()]); for (int i=0; i 1) { strides[len] = getStrideSize(i); sizes[len++] = sz; } } // matrices with 1x1x1x...x1 dimensions need the following sanity check if (len == 0) { strides[len] = 1; sizes[len++] = 1; } // return this in case len==numDim, rewrap in other case AprilUtils::SharedPtr< Matrix > obj = (len==numDim) ? this : new Matrix(len, NULL, getOffset(), NULL, size(), last_raw_pos, data.get(), use_cuda, mmapped_data.get()); obj->matrixSize = sizes.release(); obj->stride = strides.release(); return obj.weakRelease(); } template Matrix *Matrix::transpose() { Matrix *result; if (this->numDim > 1) { result = this->shallowCopy(); for (int i=0,j=numDim-1; istride[j] = this->stride[i]; result->matrixSize[j] = this->matrixSize[i]; } result->is_contiguous = NONE; } else result = this; return result; } /// Symbolic transposition, changes strides order template Matrix* Matrix::transpose(int dim1, int dim2) { if (dim1 == dim2) return this; if (dim1 < 0 || dim1 >= numDim || dim2 < 0 || dim2 >= numDim) { ERROR_EXIT4(128, "Incorrect dimensions, exepected to be " "in range [%d,%d], given dim1=%d, dim2=%d\n", 0, numDim-1, dim1, dim2); } Matrix *result; result = this->shallowCopy(); AprilUtils::swap(result->stride[dim1], result->stride[dim2]); AprilUtils::swap(result->matrixSize[dim1], result->matrixSize[dim2]); return result; } template Matrix* Matrix::cloneOnlyDims() const { Matrix *obj = new Matrix(numDim, matrixSize); #ifdef USE_CUDA obj->setUseCuda(use_cuda); #endif return obj; } template Matrix* Matrix::clone() const { Matrix *result = this->cloneOnlyDims(); AprilMath::MatrixExt::BLAS::matCopy(result,this); return result; } template Matrix* Matrix::shallowCopy() { return new Matrix(this,false); } template T& Matrix::operator[] (int i) { return data->get(static_cast(i)); } template const T& Matrix::operator[] (int i) const { return data->get(static_cast(i)); } template T& Matrix::operator() (int i) { april_assert(numDim == 1); int raw_pos = computeRawPos(&i); return data->get(static_cast(raw_pos)); } template T& Matrix::operator() (int row, int col) { april_assert(numDim == 2); int pos[2]={row,col}; int raw_pos = computeRawPos(pos); return data->get(static_cast(raw_pos)); } template T& Matrix::operator() (int coord0, int coord1, int coord2, ...) { april_assert(numDim >= 3); int *aux_coords = new int[numDim]; aux_coords[0] = coord0; aux_coords[1] = coord1; aux_coords[2] = coord2; va_list ap; va_start(ap, coord2); for(int i=3; iget(static_cast(raw_pos)); } template T& Matrix::operator() (int *coords, int sz) { UNUSED_VARIABLE(sz); april_assert(numDim == sz); int raw_pos = computeRawPos(coords); return data->get(static_cast(raw_pos)); } template const T& Matrix::operator() (int i) const { april_assert(numDim == 1); int raw_pos = computeRawPos(&i); return data->get(static_cast(raw_pos)); } template const T& Matrix::operator() (int row, int col) const { april_assert(numDim == 2); int pos[2]={row,col}; int raw_pos = computeRawPos(pos); return data->get(static_cast(raw_pos)); } template const T& Matrix::operator() (int coord0, int coord1, int coord2, ...) const { april_assert(numDim >= 3); int *aux_coords = new int[numDim]; aux_coords[0] = coord0; aux_coords[1] = coord1; aux_coords[2] = coord2; va_list ap; va_start(ap, coord2); for(int i=3; iget(static_cast(raw_pos)); } template const T& Matrix::operator() (int *coords, int sz) const { UNUSED_VARIABLE(sz); april_assert(numDim == sz); int raw_pos = computeRawPos(coords); return data->get(static_cast(raw_pos)); } template bool Matrix::getCol(int col, T* vec, int vecsize) { // If it is not a 2D matrix, error if (numDim != 2) return false; // If the column is out of range, error if ((col < 0) || (col >= matrixSize[1])) return false; // If the array length is different to the size of the matrix columns, error if (vecsize != matrixSize[0]) return false; const T *d = data->getPPALForRead(); for (int row = 0; row < matrixSize[0]; row++) { int coords[2] = { row, col }; vec[row] = d[computeRawPos(coords)]; } return true; } template bool Matrix::putCol(int col, T* vec, int vecsize) { // If it is not a 2D matrix, error if (numDim != 2) return false; // If the column is out of range, error if ((col < 0) || (col >= matrixSize[1])) return false; // If the array length is different to the size of the matrix columns, error if (vecsize != matrixSize[0]) return false; T *d = data->getPPALForWrite(); for (int row = 0; row < matrixSize[0]; row++) { int coords[2] = { row, col }; d[computeRawPos(coords)] = vec[row]; } return true; } template bool Matrix::putSubCol(int col, int first_row, T* vec, int vecsize) { // If it is not a 2D matrix, error if (numDim != 2) return false; // If the column is out of range, error if ((col < 0) || (col >= matrixSize[1])) return false; // If the first row is out of range, error if ((first_row < 0) || (first_row >= matrixSize[0])) return false; // If the array is out of range, error if ((first_row < 0) || (first_row+vecsize > matrixSize[0])) return false; T *d = data->getPPALForWrite(); for (int row = first_row; row < first_row+vecsize; row++) { int coords[2] = { row, col }; d[computeRawPos(coords)] = vec[row]; } return true; } template template bool Matrix::sameDim(const Matrix *other) const { return sameDim(other->getDimPtr(), other->getNumDim()); } template bool Matrix::sameDim(const int *dims, const int len) const { if (numDim != len) return false; switch(numDim) { default: for (int i=0; i Matrix *Matrix::select(int dim, int index, Matrix *dest) const { if (numDim == 1) ERROR_EXIT(128, "Not possible to execute select for numDim=1\n"); if (dim >= numDim) ERROR_EXIT(128, "Select for a dimension which doesn't exists\n"); if (index >= matrixSize[dim]) ERROR_EXIT(128, "Select for an index out of the matrix\n"); Matrix *result; if (dest == 0) { result = new Matrix(); int d = numDim - 1; // Data initialization result->use_cuda = use_cuda; result->numDim = d; result->matrixSize = new int[d]; result->stride = new int[d]; result->offset = offset + index*stride[dim]; // the select implies an offset result->last_raw_pos = result->offset; result->data = const_cast*>(data.get()); // Not needed: result->mmapped_data = 0; for(int i=0; istride[i] = stride[i]; result->matrixSize[i] = matrixSize[i]; result->last_raw_pos += (matrixSize[i]-1)*stride[i]; } for(int i=dim+1; istride[i-1] = stride[i]; result->matrixSize[i-1] = matrixSize[i]; result->last_raw_pos += (matrixSize[i]-1)*stride[i]; } result->total_size = total_size/matrixSize[dim]; } else { // april_assert(dest->total_size == total_size/matrixSize[dim]); april_assert(dest->numDim == numDim-1); // int dest_offset = offset + index*stride[dim]; int dest_last_raw_pos = dest_offset; for(int i=0; ichangeSubMatrixData(dest_offset, dest_last_raw_pos); // result = dest; } april_assert(result->offset >= 0); return result; } /***** COORDINATES METHODS *****/ template bool Matrix::nextCoordVectorRowOrder(int *coords, int &raw_pos) const { return nextCoordVectorRowOrder(coords, raw_pos, matrixSize, stride, numDim, last_raw_pos); } template bool Matrix::nextCoordVectorColOrder(int *coords, int &raw_pos) const { return nextCoordVectorColOrder(coords, raw_pos, matrixSize, stride, numDim, last_raw_pos); } template bool Matrix::nextCoordVectorRowOrder(int *coords, int &raw_pos, const int *sizes, const int *strides, const int numDim, const int last_raw_pos) { bool ret = true; switch(numDim) { case 1: coords[0] = (coords[0]+1) % sizes[0]; if (coords[0] == 0) { raw_pos = last_raw_pos + 1; ret = false; } else raw_pos += strides[0]; break; case 2: coords[1] = (coords[1]+1) % sizes[1]; if (coords[1] == 0) { coords[0] = (coords[0]+1) % sizes[0]; if (coords[0] == 0) { raw_pos = last_raw_pos + 1; ret = false; } else raw_pos += strides[0] - (sizes[1]-1)*strides[1]; } else raw_pos += strides[1]; break; default: int j = numDim; do { --j; coords[j] = (coords[j]+1) % sizes[j]; if (coords[j] == 0) raw_pos -= (sizes[j]-1) * strides[j]; else raw_pos += strides[j]; } while(j>0 && coords[j] == 0); if (j == 0 && coords[0] == 0) { raw_pos = last_raw_pos + 1; ret = false; } } return ret; } template bool Matrix::nextCoordVectorColOrder(int *coords, int &raw_pos, const int *sizes, const int *strides, const int numDim, const int last_raw_pos) { bool ret = true; switch(numDim) { case 1: coords[0] = (coords[0]+1) % sizes[0]; if (coords[0] == 0) { raw_pos = last_raw_pos + 1; ret = false; } else raw_pos += strides[0]; break; case 2: coords[0] = (coords[0]+1) % sizes[0]; if (coords[0] == 0) { coords[1] = (coords[1]+1) % sizes[1]; if (coords[1] == 0) { raw_pos = last_raw_pos + 1; ret = false; } else raw_pos += strides[1] - (sizes[0]-1)*strides[0]; } else raw_pos += strides[0]; break; default: int j = 0; do { coords[j] = (coords[j]+1) % sizes[j]; if (coords[j] == 0) { if (sizes[j] > 1) raw_pos -= (sizes[j]-1) * strides[j]; } else raw_pos += strides[j]; } while(coords[j++] == 0 && j bool Matrix::nextCoordVectorRowOrder(int *coords) const { return nextCoordVectorRowOrder(coords, matrixSize, numDim); } template bool Matrix::nextCoordVectorColOrder(int *coords) const { return nextCoordVectorColOrder(coords, matrixSize, numDim); } template bool Matrix::nextCoordVectorRowOrder(int *coords, const int *sizes, int numDim) { int j = numDim; do { --j; coords[j] = (coords[j]+1) % sizes[j]; } while(j>0 && coords[j] == 0); if (j == 0 && coords[0] == 0) return false; return true; } template bool Matrix::nextCoordVectorColOrder(int *coords, const int *sizes, int numDim) { int j = 0; do { coords[j] = (coords[j]+1) % sizes[j]; } while(coords[j++] == 0 && j int Matrix::computeRawPos(const int *coords) const { int raw_pos; switch(numDim) { case 1: april_assert(coords[0] < matrixSize[0]); raw_pos = coords[0]*stride[0]; break; case 2: april_assert(coords[0] < matrixSize[0]); april_assert(coords[1] < matrixSize[1]); raw_pos = coords[0]*stride[0]+coords[1]*stride[1]; break; default: raw_pos=0; for(int i=0; i int Matrix::computeRawPos(const int *coords, const int *offset) const { int raw_pos; switch(numDim) { case 1: april_assert(coords[0]+offset[0] < matrixSize[0]); raw_pos = (coords[0]+offset[0])*stride[0]; break; case 2: april_assert(coords[0]+offset[0] < matrixSize[0]); april_assert(coords[1]+offset[1] < matrixSize[1]); raw_pos = (coords[0]+offset[0])*stride[0]+(coords[1]+offset[1])*stride[1]; break; default: raw_pos=0; for(int i=0; ioffset; } /// FIXME: Change it to compute coords traversing strides in descending order? template void Matrix::computeCoords(const int raw_pos, int *coords) const { int R = raw_pos - offset; switch(numDim) { case 1: coords[0] = R / stride[0]; break; case 2: coords[0] = R / stride[0]; coords[1] = (R % stride[0]) / stride[1]; break; default: for (int i=0; i bool Matrix::getIsContiguous() const { if (is_contiguous != NONE) return (is_contiguous==CONTIGUOUS); int aux = 1; for (int i=numDim-1; i>=0; --i) { if(stride[i] != aux && matrixSize[i] != 1) { is_contiguous = NONCONTIGUOUS; return false; } else { aux *= matrixSize[i]; } } is_contiguous = CONTIGUOUS; return true; } // expands current matrix to a diagonal matrix template Matrix *Matrix::diagonalize() const { if (numDim != 1) ERROR_EXIT(128, "Only one-dimensional matrix is allowed\n"); const int dims[2] = { matrixSize[0], matrixSize[0] }; AprilUtils::SharedPtr< Matrix > resul = new Matrix(2, dims); // resul_diag is a submatrix of resul, build to do a diagonal traverse const int stride = matrixSize[0] + 1; AprilUtils::SharedPtr< Matrix > resul_diag = new Matrix(1, &stride, 0, dims, dims[0], resul->last_raw_pos, resul->data.get(), resul->use_cuda); AprilMath::MatrixExt::Initializers::matZeros(resul.get()); AprilMath::MatrixExt::BLAS::matCopy(resul_diag.get(), this); resul_diag.reset(); return resul.weakRelease(); } template void Matrix::pruneSubnormalAndCheckNormal() { ERROR_EXIT(128, "NOT IMPLEMENTED!!!\n"); } template Matrix *Matrix::padding(int *begin_padding, int *end_padding, T default_value) const { AprilUtils::UniquePtr result_sizes = new int[getNumDim()]; AprilUtils::UniquePtr matrix_pos = new int[getNumDim()]; for (int i=0; i > result = new Matrix(getNumDim(), result_sizes.get()); // FIXME: implement fill by several submatrices for large matrix sizes with // small padding sizes AprilMath::MatrixExt::Initializers::matFill(result.get(), default_value); // take submatrix where data will be located AprilUtils::SharedPtr< Matrix > result_data = new Matrix(result.get(), matrix_pos.get(), getDimPtr(), false); // copy data to the submatrix AprilMath::MatrixExt::BLAS::matCopy(result_data.get(), this); // result_data.reset(); return result.weakRelease(); } template Matrix *Matrix::padding(int pad_value, T default_value) const { AprilUtils::UniquePtr result_sizes = new int[getNumDim()]; AprilUtils::UniquePtr matrix_pos = new int[getNumDim()]; for (int i=0; i > result = new Matrix(getNumDim(), result_sizes.get()); // FIXME: implement fill by several submatrices for large matrix sizes with // small padding sizes AprilMath::MatrixExt::Initializers::matFill(result.get(), default_value); // take submatrix where data will be located AprilUtils::SharedPtr< Matrix > result_data = new Matrix(result.get(), matrix_pos.get(), getDimPtr(), false); // copy data to the submatrix AprilMath::MatrixExt::BLAS::matCopy(result_data.get(), this); // result_data.reset(); return result.weakRelease(); } /// Add singleton dimensions at left template Matrix *Matrix::leftInflate(int n) const { const int RESULT_NUM_DIM = n + getNumDim(); AprilUtils::UniquePtr sizes(new int[RESULT_NUM_DIM]); AprilUtils::UniquePtr strides(new int[RESULT_NUM_DIM]); int k; // fill with 1s for (k=0; k *obj = // giving 0 at size and stride vectors, they are given below new Matrix(RESULT_NUM_DIM, NULL, getOffset(), NULL, size(), last_raw_pos, const_cast< AprilMath::GPUMirroredMemoryBlock*>(data.get()), use_cuda, const_cast< AprilUtils::MMappedDataReader*>(mmapped_data.get())); obj->matrixSize = sizes.release(); obj->stride = strides.release(); return obj; } /// Add singleton dimensions at right template Matrix *Matrix::rightInflate(int n) const { const int RESULT_NUM_DIM = n + getNumDim(); AprilUtils::UniquePtr sizes(new int[RESULT_NUM_DIM]); AprilUtils::UniquePtr strides(new int[RESULT_NUM_DIM]); int k=0; // copy matrix shape for (int i=0; i *obj = // giving 0 at size and stride vectors, they are given below new Matrix(RESULT_NUM_DIM, NULL, getOffset(), NULL, size(), last_raw_pos, const_cast< AprilMath::GPUMirroredMemoryBlock*>(data.get()), use_cuda, const_cast< AprilUtils::MMappedDataReader*>(mmapped_data.get())); obj->matrixSize = sizes.release(); obj->stride = strides.release(); return obj; } } // namespace Basics #endif // MATRIX_IMPL_H april-ann-0.4.1/packages/basics/matrix/c_src/matrixBool.cc000066400000000000000000000052241263004425400234460ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "matrixBool.h" namespace Basics { namespace MatrixIO { ///////////////////////////////////////////////////////////////////////// template<> bool AsciiExtractor::operator()(AprilUtils::constString &line, bool &destination) { char aux; if (!line.extract_char(&aux)) return false; destination = (aux == '1'); return true; } template<> bool BinaryExtractor::operator()(AprilUtils::constString &line, bool &destination) { UNUSED_VARIABLE(line); UNUSED_VARIABLE(destination); ERROR_EXIT(128, "Bool type has not binary option\n"); return false; } template<> int AsciiSizer::operator()(const Matrix *mat) { return mat->size()*2; } template<> int BinarySizer::operator()(const Matrix *mat) { UNUSED_VARIABLE(mat); ERROR_EXIT(128, "Bool type has not binary option\n"); return 0; } template<> void AsciiCoder::operator()(const bool &value, AprilIO::StreamInterface *stream) { stream->printf("%c", (value) ? ('1') : ('0')); } template<> void BinaryCoder::operator()(const bool &value, AprilIO::StreamInterface *stream) { UNUSED_VARIABLE(value); UNUSED_VARIABLE(stream); ERROR_EXIT(128, "Bool type has not binary option\n"); } ///////////////////////////////////////////////////////////////////////////// } // namespace MatrixIO template<> const char *Matrix::luaCtorName() const { return "matrixBool.deserialize"; } /////////////////////////////////////////////////////////////////////////////// template class Matrix; } // namespace Basics april-ann-0.4.1/packages/basics/matrix/c_src/matrixBool.h000066400000000000000000000042101263004425400233020ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIX_BOOL_H #define MATRIX_BOOL_H #include "matrix.h" namespace Basics { namespace MatrixIO { /* Especialization of MatrixBool ascii and binary extractors, sizers and coders */ template<> bool AsciiExtractor::operator()(AprilUtils::constString &line, bool &destination); template<> bool BinaryExtractor::operator()(AprilUtils::constString &line, bool &destination); template<> int AsciiSizer::operator()(const Matrix *mat); template<> int BinarySizer::operator()(const Matrix *mat); template<> void AsciiCoder::operator()(const bool &value, AprilIO::StreamInterface *stream); template<> void BinaryCoder::operator()(const bool &value, AprilIO::StreamInterface *stream); } // namespace MatrixIO template<> const char *Matrix::luaCtorName() const; /////////////////////////////////////////////////////////////////////////////// typedef Matrix MatrixBool; } // namespace Basics //////////////////////////////////////////////////////////////////////////// DECLARE_LUA_TABLE_BIND_SPECIALIZATION(Basics::MatrixBool); #endif // MATRIX_BOOL_H april-ann-0.4.1/packages/basics/matrix/c_src/matrixChar.cc000066400000000000000000000052341263004425400234310ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "matrixChar.h" namespace Basics { namespace MatrixIO { ///////////////////////////////////////////////////////////////////////// template<> bool AsciiExtractor::operator()(AprilUtils::constString &line, char &destination) { if (!line.extract_char(&destination)) return false; return true; } template<> bool BinaryExtractor::operator()(AprilUtils::constString &line, char &destination) { UNUSED_VARIABLE(line); UNUSED_VARIABLE(destination); ERROR_EXIT(128, "Char type has not binary option\n"); return false; } template<> int AsciiSizer::operator()(const Matrix *mat) { return mat->size()*2; } template<> int BinarySizer::operator()(const Matrix *mat) { UNUSED_VARIABLE(mat); ERROR_EXIT(128, "Char type has not binary option\n"); return 0; } template<> void AsciiCoder::operator()(const char &value, AprilIO::StreamInterface *stream) { stream->printf("%c", value); } template<> void BinaryCoder::operator()(const char &value, AprilIO::StreamInterface *stream) { UNUSED_VARIABLE(value); UNUSED_VARIABLE(stream); ERROR_EXIT(128, "Char type has not binary option\n"); } ///////////////////////////////////////////////////////////////////////////// } // namespace MatrixIO template<> int Matrix::exportParamsToLua(lua_State *L) { UNUSED_VARIABLE(L); ERROR_EXIT(128, "Serialization of matrixChar not implemented\n"); return 0; } /////////////////////////////////////////////////////////////////////////////// template class Matrix; } // namespace Basics april-ann-0.4.1/packages/basics/matrix/c_src/matrixChar.h000066400000000000000000000046261263004425400232770ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIX_CHAR_H #define MATRIX_CHAR_H #include "matrix.h" namespace Basics { namespace MatrixIO { /* Especialization of MatrixChar ascii and binary extractors, sizers and coders */ template<> bool AsciiExtractor::operator()(AprilUtils::constString &line, char &destination); template<> bool BinaryExtractor::operator()(AprilUtils::constString &line, char &destination); template<> int AsciiSizer::operator()(const Matrix *mat); template<> int BinarySizer::operator()(const Matrix *mat); template<> void AsciiCoder::operator()(const char &value, AprilIO::StreamInterface *stream); template<> void BinaryCoder::operator()(const char &value, AprilIO::StreamInterface *stream); } // namespace MatrixIO template<> int Matrix::exportParamsToLua(lua_State *L); /////////////////////////////////////////////////////////////////////////////// typedef Matrix MatrixChar; } // namespace Basics //////////////////////////////////////////////////////////////////////////// namespace AprilUtils { template<> Basics::MatrixChar *LuaTable:: convertTo(lua_State *L, int idx); template<> void LuaTable:: pushInto(lua_State *L, Basics::MatrixChar *value); template<> bool LuaTable:: checkType(lua_State *L, int idx); } #endif // MATRIX_CHAR_H april-ann-0.4.1/packages/basics/matrix/c_src/matrixComplexF.cc000066400000000000000000000060721263004425400242720ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "matrix.h" #include "matrixComplexF.h" // WARNING: ALL THE METHODS IMPLEMENTED HERE ARE SPECIALIZED TO COMPLEXF VERSION namespace Basics { typedef AprilMath::ComplexF ComplexF; namespace MatrixIO { ///////////////////////////////////////////////////////////////////////// template<> bool AsciiExtractor::operator()(AprilUtils::constString &line, ComplexF &destination) { if (!line.extract_float(&destination.real())) return false; if (!line.extract_float(&destination.img())) return false; char ch; if (!line.extract_char(&ch)) return false; if (ch != 'i') return false; return true; } template<> bool BinaryExtractor::operator()(AprilUtils::constString &line, ComplexF &destination) { if (!line.extract_float_binary(&destination.real())) return false; if (!line.extract_float_binary(&destination.img())) return false; return true; } template<> int AsciiSizer::operator()(const Matrix *mat) { return mat->size()*26; // 12*2+2 } template<> int BinarySizer::operator()(const Matrix *mat) { return AprilUtils::binarizer::buffer_size_32(mat->size()<<1); // mat->size() * 2 } template<> void AsciiCoder::operator()(const ComplexF &value, AprilIO::StreamInterface *stream) { stream->printf("%.5g%+.5gi", value.real(), value.img()); } template<> void BinaryCoder::operator()(const ComplexF &value, AprilIO::StreamInterface *stream) { char b[10]; AprilUtils::binarizer::code_float(value.real(), b); AprilUtils::binarizer::code_float(value.img(), b+5); stream->put(b, sizeof(char)*10); } ///////////////////////////////////////////////////////////////////////////// } // namespace MatrixIO ///////////////////////////////////////////////////////////////////////////// template<> const char *Matrix::luaCtorName() const { return "matrixComplex.deserialize"; } template class Matrix; } // namespace Basics april-ann-0.4.1/packages/basics/matrix/c_src/matrixComplexF.h000066400000000000000000000047151263004425400241360ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIXCOMPLEXF_H #define MATRIXCOMPLEXF_H #include "complex_number.h" #include "matrix.h" namespace Basics { namespace MatrixIO { /* Especialization of MatrixComplexF ascii and binary extractors, sizers and coders */ template<> bool AsciiExtractor::operator()(AprilUtils::constString &line, AprilMath::ComplexF &destination); template<> bool BinaryExtractor::operator()(AprilUtils::constString &line, AprilMath::ComplexF &destination); template<> int AsciiSizer::operator()(const Matrix *mat); template<> int BinarySizer::operator()(const Matrix *mat); template<> void AsciiCoder::operator()(const AprilMath::ComplexF &value, AprilIO::StreamInterface *stream); template<> void BinaryCoder::operator()(const AprilMath::ComplexF &value, AprilIO::StreamInterface *stream); } // namespace MatrixIO ////////////////////////////////////////////////////////////////////////////// template<> const char *Matrix::luaCtorName() const; typedef Matrix MatrixComplexF; } // namespace Basics //////////////////////////////////////////////////////////////////////////// DECLARE_LUA_TABLE_BIND_SPECIALIZATION(Basics::MatrixComplexF); #endif // MATRIXCOMPLEXF_H april-ann-0.4.1/packages/basics/matrix/c_src/matrixDouble.cc000066400000000000000000000047761263004425400240000ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "matrixDouble.h" namespace Basics { namespace MatrixIO { ///////////////////////////////////////////////////////////////////////// template<> bool AsciiExtractor::operator()(AprilUtils::constString &line, double &destination) { if (!line.extract_double(&destination)) return false; return true; } template<> bool BinaryExtractor::operator()(AprilUtils::constString &line, double &destination) { if (!line.extract_double_binary(&destination)) return false; return true; } template<> int AsciiSizer::operator()(const Matrix *mat) { return mat->size()*12; } template<> int BinarySizer::operator()(const Matrix *mat) { return AprilUtils::binarizer::buffer_size_64(mat->size()); } template<> void AsciiCoder::operator()(const double &value, AprilIO::StreamInterface *stream) { stream->printf("%.5g", value); } template<> void BinaryCoder::operator()(const double &value, AprilIO::StreamInterface *stream) { char b[10]; AprilUtils::binarizer::code_double(value, b); stream->put(b, sizeof(char)*10); } ///////////////////////////////////////////////////////////////////////////// } // namespace MatrixIO template<> const char *Matrix::luaCtorName() const { return "matrixDouble.deserialize"; } ///////////////////////////////////////////////////////////////////////// template class Matrix; } april-ann-0.4.1/packages/basics/matrix/c_src/matrixDouble.h000066400000000000000000000041261263004425400236270ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIX_DOUBLE_H #define MATRIX_DOUBLE_H #include "matrix.h" namespace Basics { typedef Matrix MatrixDouble; namespace MatrixIO { /* Especialization of MatrixDouble ascii and binary extractors, sizers and coders */ template<> bool AsciiExtractor::operator()(AprilUtils::constString &line, double &destination); template<> bool BinaryExtractor::operator()(AprilUtils::constString &line, double &destination); template<> int AsciiSizer::operator()(const Matrix *mat); template<> int BinarySizer::operator()(const Matrix *mat); template<> void AsciiCoder::operator()(const double &value, AprilIO::StreamInterface *stream); template<> void BinaryCoder::operator()(const double &value, AprilIO::StreamInterface *stream); } // namespace MatrixIO template<> const char *Matrix::luaCtorName() const; } //////////////////////////////////////////////////////////////////////////// DECLARE_LUA_TABLE_BIND_SPECIALIZATION(Basics::MatrixDouble); #endif // MATRIX_DOUBLE_H april-ann-0.4.1/packages/basics/matrix/c_src/matrixFloat.cc000066400000000000000000000062671263004425400236300ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include "binarizer.h" #include "check_floats.h" #include "constString.h" #include "matrix.h" #include "matrixFloat.h" // WARNING: ALL THE METHODS IMPLEMENTED HERE ARE SPECIALIZED TO FLOAT VERSION using AprilUtils::constString; namespace Basics { namespace MatrixIO { ///////////////////////////////////////////////////////////////////////// template<> bool AsciiExtractor::operator()(constString &line, float &destination) { bool result = line.extract_float(&destination); if (!result) return false; return true; } template<> bool BinaryExtractor::operator()(constString &line, float &destination) { if (!line.extract_float_binary(&destination)) return false; return true; } template<> int AsciiSizer::operator()(const Matrix *mat) { return mat->size()*12; } template<> int BinarySizer::operator()(const Matrix *mat) { return AprilUtils::binarizer::buffer_size_32(mat->size()); } template<> void AsciiCoder::operator()(const float &value, AprilIO::StreamInterface *stream) { if (value <= 16777216.0f && value >= -16777216.0f && static_cast(static_cast(value)) == value) { stream->printf("%d", static_cast(value)); } else { stream->printf("%.5g", value); } } template<> void BinaryCoder::operator()(const float &value, AprilIO::StreamInterface *stream) { char b[5]; AprilUtils::binarizer::code_float(value, b); stream->put(b, sizeof(char)*5); } ///////////////////////////////////////////////////////////////////////////// } // namespace MatrixIO template<> const char *Matrix::luaCtorName() const { return "matrix.deserialize"; } template <> void Matrix::pruneSubnormalAndCheckNormal() { float *data = getRawDataAccess()->getPPALForReadAndWrite(); if (!AprilUtils::check_floats(data, size())) ERROR_EXIT(128, "No finite numbers at weights matrix!!!\n"); } /////////////////////////////////////////////////////////////////////////////// template class Matrix; } // namespace Basics april-ann-0.4.1/packages/basics/matrix/c_src/matrixFloat.h000066400000000000000000000046161263004425400234660ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIXFLOAT_H #define MATRIXFLOAT_H #include "lua_table.h" #include "matrix.h" namespace Basics { namespace MatrixIO { /* Especialization of MatrixFloat ascii and binary extractors, sizers and coders */ template<> bool AsciiExtractor::operator()(AprilUtils::constString &line, float &destination); template<> bool BinaryExtractor::operator()(AprilUtils::constString &line, float &destination); template<> int AsciiSizer::operator()(const Matrix *mat); template<> int BinarySizer::operator()(const Matrix *mat); template<> void AsciiCoder::operator()(const float &value, AprilIO::StreamInterface *stream); template<> void BinaryCoder::operator()(const float &value, AprilIO::StreamInterface *stream); /**************************************************************************/ } // namespace MatrixIO ////////////////////////////////////////////////////////////////////////// template<> const char *Matrix::luaCtorName() const; template <> void Matrix::pruneSubnormalAndCheckNormal(); //////////////////////////////////////////////////////////////////////////// typedef Matrix MatrixFloat; } //////////////////////////////////////////////////////////////////////////// DECLARE_LUA_TABLE_BIND_SPECIALIZATION(Basics::MatrixFloat); #endif // MATRIXFLOAT_H april-ann-0.4.1/packages/basics/matrix/c_src/matrixInt32.cc000066400000000000000000000050531263004425400234520ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include "matrixInt32.h" namespace Basics { namespace MatrixIO { ///////////////////////////////////////////////////////////////////////// template<> bool AsciiExtractor::operator()(AprilUtils::constString &line, int32_t &destination) { if (!line.extract_int(&destination)) return false; return true; } template<> bool BinaryExtractor::operator()(AprilUtils::constString &line, int32_t &destination) { if (!line.extract_int32_binary(&destination)) return false; return true; } template<> int AsciiSizer::operator()(const Matrix *mat) { return mat->size()*12; } template<> int BinarySizer::operator()(const Matrix *mat) { return AprilUtils::binarizer::buffer_size_32(mat->size()); } template<> void AsciiCoder::operator()(const int32_t &value, AprilIO::StreamInterface *stream) { stream->printf("%d", value); } template<> void BinaryCoder::operator()(const int32_t &value, AprilIO::StreamInterface *stream) { char b[5]; AprilUtils::binarizer::code_int32(value, b); stream->put(b, sizeof(char)*5); } ///////////////////////////////////////////////////////////////////////// } // namespace MatrixIO template<> const char *Matrix::luaCtorName() const { return "matrixInt32.deserialize"; } ///////////////////////////////////////////////////////////////////////////// template class Matrix; } // namespace Basics april-ann-0.4.1/packages/basics/matrix/c_src/matrixInt32.h000066400000000000000000000043041263004425400233120ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIX_INT32_H #define MATRIX_INT32_H #include "matrix.h" namespace Basics { namespace MatrixIO { /* Especialization of MatrixInt32 ascii and binary extractors, sizers and coders */ template<> bool AsciiExtractor::operator()(AprilUtils::constString &line, int32_t &destination); template<> bool BinaryExtractor::operator()(AprilUtils::constString &line, int32_t &destination); template<> int AsciiSizer::operator()(const Matrix *mat); template<> int BinarySizer::operator()(const Matrix *mat); template<> void AsciiCoder::operator()(const int32_t &value, AprilIO::StreamInterface *stream); template<> void BinaryCoder::operator()(const int32_t &value, AprilIO::StreamInterface *stream); } // namespace MatrixIO ////////////////////////////////////////////////////////////////////////////// template<> const char *Matrix::luaCtorName() const; typedef Matrix MatrixInt32; } // namespace Basics //////////////////////////////////////////////////////////////////////////// DECLARE_LUA_TABLE_BIND_SPECIALIZATION(Basics::MatrixInt32); #endif // MATRIX_INT_H april-ann-0.4.1/packages/basics/matrix/c_src/matrix_ext.h000066400000000000000000000030011263004425400233430ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIX_H #include "matrix.h" #include "sparse_matrix.h" #endif #ifndef MATRIX_EXT_H #define MATRIX_EXT_H #include "matrix_ext_blas.h" #include "matrix_ext_boolean.h" #include "matrix_ext_initializers.h" #include "matrix_ext_lapack.h" #include "matrix_ext_misc.h" #include "matrix_ext_operations.h" #include "matrix_ext_reductions.h" namespace AprilMath { /** * @brief Linear algebra routines and other math operations for matrices. * * @note AprilMath::Limits will be used to give default values (as zero, * one, etc.). */ namespace MatrixExt { // Just for documentation } } #endif // MATRIX_EXT_H april-ann-0.4.1/packages/basics/matrix/c_src/matrix_ext_blas.cu000066400000000000000000000726251263004425400245460ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "cmath_overloads.h" #include "mathcore.h" #include "matrix.h" #include "maxmin.h" #include "realfftwithhamming.h" #include "smart_ptr.h" #include "sparse_matrix.h" // Must be defined in this order. #include "matrix_ext_blas.h" // Must to be defined here. #include "map_matrix.h" #include "map_sparse_matrix.h" // Must to be defined here. #include "reduce_matrix.h" #include "reduce_sparse_matrix.h" using Basics::Matrix; using Basics::SparseMatrix; namespace AprilMath { namespace MatrixExt { /// Useful functors for Matrix operations. namespace Functors { template struct MatrixNorm2Reductor { void operator()(float &acc, const T &b) const { float b_abs = AprilMath::m_abs(b); acc = AprilMath::m_sqrt(acc*acc + b_abs*b_abs); } }; } // namespace Functors namespace BLAS { //////////////////// CBLAS MATH OPERATIONS //////////////////// // SCOPY BLAS operation this = other template Matrix *matCopy(Matrix *obj, const Matrix *other) { return MatrixSpanMap1(other, doCopy, obj); } // SCOPY BLAS operation this = other template SparseMatrix *matCopy(SparseMatrix *obj, const SparseMatrix *other) { return SparseMatrixScalarMap1(other, AprilMath::Functors::m_identity(), obj); } // AXPY BLAS operation this = this + alpha * other template Matrix *matAxpy(Matrix *obj, const T alpha, const Matrix *other) { if (obj->size() != other->size()) { ERROR_EXIT2(128, "Incorrect matrices sizes: %d != %d\n", obj->size(), other->size()); } #ifdef USE_MKL return MatrixSpanMap1(other, CurriedAxpy(alpha), obj, obj->size(), obj->size()); #else return MatrixSpanMap1(other, CurriedAxpy(alpha), obj); #endif } template Matrix *matAxpy(Matrix *obj, T alpha, const SparseMatrix *other) { if (obj->size() != other->size()) { ERROR_EXIT2(128, "Incorrect matrices sizes: %d != %d\n", obj->size(), other->size()); } if ( (other->getSparseFormat() == CSR_FORMAT && other->getDimSize(0) != 1) || (other->getSparseFormat() == CSC_FORMAT && other->getDimSize(1) != 1) ) { // bi-dimensional case if (other->getDimSize(0) != obj->getDimSize(0) || other->getDimSize(1) != obj->getDimSize(1)) { ERROR_EXIT4(128, "Incompatible matrix sizes, sparse is %dx%d, " "dense is %dx%d\n", other->getDimSize(0), other->getDimSize(1), obj->getDimSize(0), obj->getDimSize(1)); } bool cuda_flag = obj->getCudaFlag() || other->getCudaFlag(); const GPUMirroredMemoryBlock *values = other->getRawValuesAccess(); const Int32GPUMirroredMemoryBlock *indices = other->getRawIndicesAccess(); const int32_t *first_index = other->getRawFirstIndexAccess()->getPPALForRead();; AprilUtils::SharedPtr< Matrix > slice; unsigned int dim = (other->getSparseFormat() == CSR_FORMAT) ? 0 : 1; for (int i=0; igetDimSize(dim); ++i) { slice = obj->select(dim, i, slice.get()); doSparseAxpy(first_index[i+1] - first_index[i], alpha, values, indices, slice->getRawDataAccess(), first_index[i], static_cast(slice->getOffset()), static_cast(slice->getStrideSize(0)), cuda_flag); } } else { // vector case if (!obj->isVector()) { ERROR_EXIT(128, "sparse AXPY only works with vectors\n"); } doSparseAxpy(other->nonZeroSize(), alpha, other->getRawValuesAccess(), other->getRawIndicesAccess(), obj->getRawDataAccess(), 0, static_cast(obj->getOffset()), static_cast(obj->getVectorStride()), obj->getCudaFlag() || other->getCudaFlag()); } return obj; } // GEMM BLAS operation C = alpha * op(A)*op(B) + beta*C template Matrix *matGemm(Matrix *C, CBLAS_TRANSPOSE trans_A, CBLAS_TRANSPOSE trans_B, const T alpha, const Matrix *otherA, const Matrix *otherB, T beta) { int aux_A_stride[2], aux_B_stride[2], aux_C_stride[2]; // CBLAS_ORDER order = CblasRowMajor; if (C == otherA || C == otherB) { ERROR_EXIT(128, "GEMM method cannot receive as A or B argument " "the C argument\n"); } if (C->getNumDim() != 2 || otherA->getNumDim() != 2 || otherB->getNumDim() != 2) { ERROR_EXIT(128,"Incorrect number of dimensions, only allowed for numDim=2\n"); } int row_idx_A = 0, col_idx_A = 1; int row_idx_B = 0, col_idx_B = 1; // const int *A_stride = otherA->getStridePtr(); const int *B_stride = otherB->getStridePtr(); const int *C_stride = C->getStridePtr(); const int *A_dim = otherA->getDimPtr(); const int *B_dim = otherB->getDimPtr(); const int *C_dim = C->getDimPtr(); // case of transposed matrix if (C_stride[1] != 1) { order = CblasColMajor; } else { // case of transposed col vector if (C_stride[0] == C_stride[1] && C_dim[1] != 1) { C_stride = aux_C_stride; aux_C_stride[0] = C_dim[1]; aux_C_stride[1] = 1; } } if (A_stride[0] == A_stride[1] && A_stride[0] == 1 && A_dim[1] != 1) { A_stride = aux_A_stride; aux_A_stride[0] = A_dim[1]; aux_A_stride[1] = 1; } if (B_stride[0] == B_stride[1] && B_stride[0] == 1 && B_dim[1] != 1) { B_stride = aux_B_stride; aux_B_stride[0] = B_dim[1]; aux_B_stride[1] = 1; } // int lda = AprilUtils::max(A_stride[0], A_stride[1]); int ldb = AprilUtils::max(B_stride[0], B_stride[1]); int ldc = AprilUtils::max(C_stride[0], C_stride[1]); if (A_stride[0] + A_stride[1] != lda+1 || B_stride[0] + B_stride[1] != ldb+1 || C_stride[0] + C_stride[1] != ldc+1) { ERROR_EXIT(128, "Only allowed with contiguous matrices in leading dimension\n"); } // if (trans_A == CblasTrans) AprilUtils::swap(row_idx_A, col_idx_A); if (trans_B == CblasTrans) AprilUtils::swap(row_idx_B, col_idx_B); if (C_dim[0] != A_dim[row_idx_A] || C_dim[1] != B_dim[col_idx_B] || A_dim[col_idx_A] != B_dim[row_idx_B]) { ERROR_EXIT6(128, "Incorrect matrixes dimensions: %dx%d + %dx%d * %dx%d\n", C_dim[0], C_dim[1], A_dim[row_idx_A], A_dim[col_idx_A], B_dim[row_idx_B], B_dim[col_idx_B]); } int M = C_dim[0], N=C_dim[1]; int K = A_dim[col_idx_A]; if (order == CblasRowMajor) { if (A_stride[1] != 1) { trans_A = NEGATE_CBLAS_TRANSPOSE(trans_A); } if (B_stride[1] != 1) { trans_B = NEGATE_CBLAS_TRANSPOSE(trans_B); } } else { if (A_stride[0] != 1) { trans_A = NEGATE_CBLAS_TRANSPOSE(trans_A); } if (B_stride[0] != 1) { trans_B = NEGATE_CBLAS_TRANSPOSE(trans_B); } } // doGemm(order, trans_A, trans_B, M, N, K, alpha, otherA->getRawDataAccess(), lda, otherB->getRawDataAccess(), ldb, beta, C->getRawDataAccess(), ldc, otherA->getOffset(), otherB->getOffset(), C->getOffset(), C->getCudaFlag() || otherA->getCudaFlag() || otherB->getCudaFlag()); return C; } // MM Sparse BLAS operation C = alpha * op(A)*op(B) + beta*op(C) template Matrix *matSparseMM(Matrix *C, CBLAS_TRANSPOSE trans_A, CBLAS_TRANSPOSE trans_B, const T alpha, const SparseMatrix *otherA, const Matrix *otherB, T beta) { int aux_B_stride[2], aux_C_stride[2]; // CBLAS_ORDER order = CblasRowMajor; if (C == otherB) { ERROR_EXIT(128, "Sparse GEMM method couldn't receive as A or B argument " "the C argument\n"); } if (C->getNumDim() != 2 || otherA->getNumDim() != 2 || otherB->getNumDim() != 2) { ERROR_EXIT(128,"Incorrect number of dimensions, only allowed for numDim=2\n"); } int row_idx_A = 0, col_idx_A = 1; int row_idx_B = 0, col_idx_B = 1; // const int *B_stride = otherB->getStridePtr(); const int *C_stride = C->getStridePtr(); const int *A_dim = otherA->getDimPtr(); const int *B_dim = otherB->getDimPtr(); const int *C_dim = C->getDimPtr(); // case of transposed matrix if (C_stride[1] != 1) { order = CblasColMajor; } else { // case of transposed col vector if (C_stride[0] == C_stride[1] && C_dim[1] != 1) { C_stride = aux_C_stride; aux_C_stride[0] = C_dim[1]; aux_C_stride[1] = 1; } } if (B_stride[0] == B_stride[1] && B_stride[0] == 1 && B_dim[1] != 1) { B_stride = aux_B_stride; aux_B_stride[0] = B_dim[1]; aux_B_stride[1] = 1; } // int ldb = AprilUtils::max(B_stride[0], B_stride[1]); int ldc = AprilUtils::max(C_stride[0], C_stride[1]); if (B_stride[0] + B_stride[1] != ldb+1 || C_stride[0] + C_stride[1] != ldc+1) { ERROR_EXIT(128, "Only allowed with contiguous matrices in leading dimension\n"); } // if (trans_A == CblasTrans) AprilUtils::swap(row_idx_A, col_idx_A); if (trans_B == CblasTrans) AprilUtils::swap(row_idx_B, col_idx_B); // if (C_dim[0] != A_dim[row_idx_A] || C_dim[1] != B_dim[col_idx_B] || A_dim[col_idx_A] != B_dim[row_idx_B]) { ERROR_EXIT6(128, "Incorrect matrixes dimensions: %dx%d + %dx%d * %dx%d\n", C_dim[0], C_dim[1], A_dim[row_idx_A], A_dim[col_idx_A], B_dim[row_idx_B], B_dim[col_idx_B]); } int M=C_dim[0], N=C_dim[1]; int K=B_dim[row_idx_B]; if (order == CblasRowMajor) { if (B_stride[1] != 1) trans_B = NEGATE_CBLAS_TRANSPOSE(trans_B); } else { if (B_stride[0] != 1) trans_B = NEGATE_CBLAS_TRANSPOSE(trans_B); } // doSparseMM(order, otherA->getSparseFormat(), trans_A, trans_B, M, N, K, alpha, otherA->getRawValuesAccess(), otherA->getRawIndicesAccess(), otherA->getRawFirstIndexAccess(), otherB->getRawDataAccess(), ldb, beta, C->getRawDataAccess(), ldc, otherB->getOffset(), C->getOffset(), C->getCudaFlag() || otherA->getCudaFlag() || otherB->getCudaFlag()); return C; } // GEMV BLAS operation Y = alpha * op(A)*X + beta*Y template Matrix *matGemv(Matrix *Y, CBLAS_TRANSPOSE trans_A, const T alpha, const Matrix *otherA, const Matrix *otherX, const T beta) { CBLAS_ORDER order = CblasRowMajor; if (!Y->isVector() || !otherX->isVector() || otherA->getNumDim() != 2) { ERROR_EXIT(128,"Incorrect number of dimensions\n"); } int M, N; const int *A_stride = otherA->getStridePtr(); int lda = AprilUtils::max(A_stride[0],A_stride[1]); if (A_stride[0]+A_stride[1] != lda+1) { ERROR_EXIT(128, "Only allowed with contiguous matrices in leading dimension\n"); } if (A_stride[1] != 1) order = CblasColMajor; M = otherA->getDimSize(0); N = otherA->getDimSize(1); // SANITY CHECK if (trans_A == CblasTrans) { if (N != Y->size() || M != otherX->size()) { ERROR_EXIT4(128, "Incorrect matrixes dimensions: %dx1 + %dx%d * %dx1\n", Y->size(), N, M, otherX->size()); } } else { if (M != Y->size() || N != otherX->size()) { ERROR_EXIT4(128, "Incorrect matrixes dimensions: %dx1 + %dx%d * %dx1\n", Y->size(), M, N, otherX->size()); } } // int ldx=otherX->getVectorStride(); int ldy=Y->getVectorStride(); doGemv(order, trans_A, M, N, alpha, otherA->getRawDataAccess(), lda, otherX->getRawDataAccess(), ldx, beta, Y->getRawDataAccess(), ldy, otherA->getOffset(), otherX->getOffset(), Y->getOffset(), Y->getCudaFlag() || otherX->getCudaFlag() || otherA->getCudaFlag()); return Y; } // GEMV Sparse BLAS operation this = alpha * op(A)*X + beta*this template Matrix *matGemv(Matrix *Y, CBLAS_TRANSPOSE trans_A, const T alpha, const SparseMatrix *otherA, const Matrix *otherX, const T beta) { if (!Y->isVector() || !otherX->isVector()) { ERROR_EXIT(128,"Incorrect number of dimensions\n"); } int M,N; M=otherA->getDimSize(0); N=otherA->getDimSize(1); // SANITY CHECK if (trans_A == CblasNoTrans) { if (M != Y->size() || N != otherX->size()) { ERROR_EXIT4(128, "Incorrect matrixes dimensions: %dx1 + %dx%d * %dx1\n", Y->size(), M, N, otherX->size()); } } else { if (N != Y->size() || M != otherX->size()) { ERROR_EXIT4(128, "Incorrect matrixes dimensions: %dx1 + %dx%d * %dx1\n", Y->size(), N, M, otherX->size()); } } // int ldx=otherX->getVectorStride(); int ldy=Y->getVectorStride(); doSparseGemv(otherA->getSparseFormat(), trans_A, M, N, alpha, otherA->getRawValuesAccess(), otherA->getRawIndicesAccess(), otherA->getRawFirstIndexAccess(), otherX->getRawDataAccess(), ldx, beta, Y->getRawDataAccess(), ldy, otherX->getOffset(), Y->getOffset(), Y->getCudaFlag() || otherX->getCudaFlag() || otherA->getCudaFlag()); return Y; } // GER BLAS operation A = alpha * X*Y' + A template Matrix *matGer(Matrix *A, const T alpha, const Matrix *otherX, const Matrix *otherY) { CBLAS_ORDER order = CblasRowMajor; if (!otherX->isVector() || !otherY->isVector() || A->getNumDim()!=2) { ERROR_EXIT(128,"Incorrect number of dimensions\n"); } const int *A_stride = A->getStridePtr(); int lda = AprilUtils::max(A_stride[0],A_stride[1]); if (A->getStrideSize(1) != 1) order = CblasColMajor; int M=otherX->size(), N=otherY->size(); if (A->getDimSize(0) != M || A->getDimSize(1) != N) { ERROR_EXIT4(128, "Incorrect matrixes dimensions: %dx%d + %dx1 * 1x%d\n", A->getDimSize(0), A->getDimSize(1), M, N); } int ldx=otherX->getVectorStride(); int ldy=otherY->getVectorStride(); doGer(order, M, N, alpha, otherX->getRawDataAccess(), otherX->getOffset(), ldx, otherY->getRawDataAccess(), otherY->getOffset(), ldy, A->getRawDataAccess(), A->getOffset(), lda, A->getCudaFlag() || otherX->getCudaFlag() || otherY->getCudaFlag()); return A; } // DOT BLAS operation value = dot(X, Y) template T matDot(const Matrix *X, const Matrix *Y) { if (X->size() != Y->size()) { ERROR_EXIT2(128, "Incorrect dimensions: %d dot %d\n", X->size(), Y->size()); } return MatrixSpanReduce2(X, Y, doDot< T, AprilMath::Functors::r_add >, AprilMath::Functors::r_add(), T(0.0f)); } // DOT Sparse BLAS operation value = dot(this, other) template T matDot(const Matrix *X, const SparseMatrix *Y) { if (!X->isVector() || !Y->isVector()) { ERROR_EXIT(128,"Incorrect number of dimensions\n"); } if (X->size() != Y->size()) { ERROR_EXIT2(128, "Incorrect dimensions: %d dot %d\n", X->size(), Y->size()); } if (Y->getDenseCoordinateSize() != 1) { ERROR_EXIT(128, "DOT operation only allowed with sparse matrices with " "dense coordinate size of 1, please, change the sparse " "format\n"); } T ret = doSparseDot(Y->nonZeroSize(), Y->getRawValuesAccess(), Y->getRawIndicesAccess(), X->getRawDataAccess(), X->getOffset(), X->getVectorStride(), X->getCudaFlag() || Y->getCudaFlag()); return ret; } template float matNorm2(Matrix *obj) { return MatrixSpanReduce1(obj, doNrm2< T, Functors::MatrixNorm2Reductor >, Functors::MatrixNorm2Reductor(), float(0.0f)); } // FIXME: implement using a wrapper template float matNorm2(SparseMatrix *obj) { float result = 0.0f; for (typename SparseMatrix::const_iterator it(obj->begin()); it != obj->end(); ++it) { result += (*it) * (*it); } return AprilMath::m_sqrt(result); } ///// INTEGER VERSIONS ///// template <> Matrix *matAxpy(Matrix *obj, int32_t alpha, const SparseMatrix *other) { UNUSED_VARIABLE(obj); UNUSED_VARIABLE(alpha); UNUSED_VARIABLE(other); ERROR_EXIT(128, "Not implemented for sparse int32 matrices\n"); return 0; } template struct GenericAxpyFunctor { T alpha; GenericAxpyFunctor(const T &alpha) : alpha(alpha) {} APRIL_CUDA_EXPORT T operator()(const T &x, const T &y) { return alpha*x + y; } }; // AXPY integer operation this = this + alpha * other template <> Matrix *matAxpy(Matrix *obj, const int32_t alpha, const Matrix *other) { if (obj->size() != other->size()) { ERROR_EXIT2(128, "Incorrect matrices sizes: %d != %d\n", obj->size(), other->size()); } if (alpha != 1) { return MatrixScalarMap2(other, obj, GenericAxpyFunctor(alpha), obj); } else { return MatrixScalarMap2(other, obj, AprilMath::Functors::m_add(), obj); } } /////////////////////////// template Matrix *matCopy(Matrix *, const Matrix *); template Matrix *matAxpy(Matrix *, const float, const Matrix *); template Matrix *matAxpy(Matrix *, const float, const SparseMatrix *); template Matrix *matGemm(Matrix *, CBLAS_TRANSPOSE, CBLAS_TRANSPOSE, const float, const Matrix *otherA, const Matrix *otherB, float beta); template Matrix *matSparseMM(Matrix *, CBLAS_TRANSPOSE, CBLAS_TRANSPOSE, const float, const SparseMatrix *, const Matrix *, float); template Matrix *matGemv(Matrix *Y, CBLAS_TRANSPOSE, const float, const Matrix *, const Matrix *, const float); template Matrix *matGemv(Matrix *Y, CBLAS_TRANSPOSE, const float, const SparseMatrix *, const Matrix *, const float); template Matrix *matGer(Matrix *, const float, const Matrix *, const Matrix *); template float matDot(const Matrix *, const Matrix *); template float matDot(const Matrix *, const SparseMatrix *); template float matNorm2(Matrix *); template Matrix *matCopy(Matrix *, const Matrix *); template Matrix *matAxpy(Matrix *, const double, const Matrix *); template Matrix *matAxpy(Matrix *, const double, const SparseMatrix *); template Matrix *matGemm(Matrix *, CBLAS_TRANSPOSE, CBLAS_TRANSPOSE, const double, const Matrix *otherA, const Matrix *otherB, double beta); template Matrix *matSparseMM(Matrix *, CBLAS_TRANSPOSE, CBLAS_TRANSPOSE, const double, const SparseMatrix *, const Matrix *, double); template Matrix *matGemv(Matrix *Y, CBLAS_TRANSPOSE, const double, const Matrix *, const Matrix *, const double); template Matrix *matGemv(Matrix *Y, CBLAS_TRANSPOSE, const double, const SparseMatrix *, const Matrix *, const double); template Matrix *matGer(Matrix *, const double, const Matrix *, const Matrix *); template double matDot(const Matrix *, const Matrix *); template double matDot(const Matrix *, const SparseMatrix *); template float matNorm2(Matrix *); template Matrix *matCopy(Matrix *, const Matrix *); template Matrix *matAxpy(Matrix *, const ComplexF, const Matrix *); template Matrix *matAxpy(Matrix *, const ComplexF, const SparseMatrix *); template Matrix *matGemm(Matrix *, CBLAS_TRANSPOSE, CBLAS_TRANSPOSE, const ComplexF, const Matrix *otherA, const Matrix *otherB, ComplexF beta); template Matrix *matSparseMM(Matrix *, CBLAS_TRANSPOSE, CBLAS_TRANSPOSE, const ComplexF, const SparseMatrix *, const Matrix *, ComplexF); template Matrix *matGemv(Matrix *Y, CBLAS_TRANSPOSE, const ComplexF, const Matrix *, const Matrix *, const ComplexF); template Matrix *matGemv(Matrix *Y, CBLAS_TRANSPOSE, const ComplexF, const SparseMatrix *, const Matrix *, const ComplexF); template Matrix *matGer(Matrix *, const ComplexF, const Matrix *, const Matrix *); template ComplexF matDot(const Matrix *, const Matrix *); template ComplexF matDot(const Matrix *, const SparseMatrix *); template float matNorm2(Matrix *); template Matrix *matCopy(Matrix *, const Matrix *); template Matrix *matCopy(Matrix *, const Matrix *); template Matrix *matCopy(Matrix *, const Matrix *); template SparseMatrix *matCopy(SparseMatrix *, const SparseMatrix *); template float matNorm2(SparseMatrix *); template float matNorm2(SparseMatrix *); template SparseMatrix *matCopy(SparseMatrix *, const SparseMatrix *); template SparseMatrix *matCopy(SparseMatrix *, const SparseMatrix *); } // namespace BLAS } // namespace MatrixExt } // namespace AprilMath april-ann-0.4.1/packages/basics/matrix/c_src/matrix_ext_blas.h000066400000000000000000000130721263004425400243550ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "matrix_ext.h" #ifndef MATRIX_EXT_BLAS_H #define MATRIX_EXT_BLAS_H namespace AprilMath { namespace MatrixExt { /** * @brief BLAS operations over Matrix instances. * * This operations have been implemented following CBLAS interface, they are * computed in-place receiving as first argument the destination * Basics::Matrix object. * * @see AprilMath::MatrixExt */ namespace BLAS { //////////////////// CBLAS MATH OPERATIONS //////////////////// /// SCOPY BLAS operation template Basics::Matrix *matCopy(Basics::Matrix *obj, const Basics::Matrix *other); /// SCOPY BLAS operation template Basics::SparseMatrix *matCopy(Basics::SparseMatrix *obj, const Basics::SparseMatrix *other); /// AXPY BLAS operation \f$ y = y + \alpha x \f$ being y=other and x=obj. template Basics::Matrix *matAxpy(Basics::Matrix *obj, const T alpha, const Basics::Matrix *other); /// AXPY BLAS operation \f$ y = y + \alpha x \f$ being y=other and x=obj. template Basics::Matrix *matAxpy(Basics::Matrix *obj, T alpha, const Basics::SparseMatrix *other); template <> Basics::Matrix *matAxpy(Basics::Matrix *obj, const int32_t alpha, const Basics::Matrix *other); template <> Basics::Matrix *matAxpy(Basics::Matrix *obj, int32_t alpha, const Basics::SparseMatrix *other); /// GEMM BLAS operation \f$ C = \alpha \text{op}(A) \times \text{op}(B) + \beta C \f$ template Basics::Matrix *matGemm(Basics::Matrix *C, CBLAS_TRANSPOSE trans_A, CBLAS_TRANSPOSE trans_B, const T alpha, const Basics::Matrix *otherA, const Basics::Matrix *otherB, T beta); /// MM Sparse BLAS operation \f$ C = \alpha \text{op}(A) \times \text{op}(B) + \beta C \f$ template Basics::Matrix *matSparseMM(Basics::Matrix *C, CBLAS_TRANSPOSE trans_A, CBLAS_TRANSPOSE trans_B, const T alpha, const Basics::SparseMatrix *otherA, const Basics::Matrix *otherB, T beta); /// GEMV BLAS operation \f$ Y = \alpha \text{op}(A) \times X + \beta Y \f$ template Basics::Matrix *matGemv(Basics::Matrix *Y, CBLAS_TRANSPOSE trans_A, const T alpha, const Basics::Matrix *otherA, const Basics::Matrix *otherX, const T beta); /// GEMV Sparse BLAS operation \f$ Y = \alpha \text{op}(A) \times X + \beta Y \f$ template Basics::Matrix *matGemv(Basics::Matrix *Y, CBLAS_TRANSPOSE trans_A, const T alpha, const Basics::SparseMatrix *otherA, const Basics::Matrix *otherX, const T beta); /// GER BLAS operation \f$ A = \alpha X \otimes Y + A \f$ (outer product) template Basics::Matrix *matGer(Basics::Matrix *A, const T alpha, const Basics::Matrix *otherX, const Basics::Matrix *otherY); /// DOT product BLAS operation \f$ X \circ Y \f$ template T matDot(const Basics::Matrix *X, const Basics::Matrix *Y); /// DOT product Sparse BLAS operation \f$ X \circ Y \f$ template T matDot(const Basics::Matrix *X, const Basics::SparseMatrix *Y); /// CBLAS norm2 operation \f$ ||A||_2 \f$ template float matNorm2(Basics::Matrix *obj); /// CBLAS norm2 operation \f$ ||A||_2 \f$ template float matNorm2(Basics::SparseMatrix *obj); } // namespace BLAS } // namespace MatrixExt } // namespace AprilMath #endif // MATRIX_EXT_BLAS_H april-ann-0.4.1/packages/basics/matrix/c_src/matrix_ext_boolean.cu000066400000000000000000000224571263004425400252420ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "cmath_overloads.h" #include "mathcore.h" #include "matrix.h" #include "maxmin.h" #include "realfftwithhamming.h" #include "smart_ptr.h" #include "sparse_matrix.h" // Must be defined in this order. #include "matrix_ext_boolean.h" // Must to be defined here. #include "map_matrix.h" #include "map_sparse_matrix.h" // Must to be defined here. #include "reduce_matrix.h" #include "reduce_sparse_matrix.h" using Basics::Matrix; using Basics::SparseMatrix; namespace AprilMath { namespace MatrixExt { namespace Boolean { //////////////////// BOOLEAN CONDITIONS //////////////////// /* BOOLEAN CONDITIONS: this methods transforms the given matrix in a ZERO/ONE matrix, depending in the truth of the given condition */ template Matrix *matLT(const Matrix *obj, const T &value, Matrix *dest) { AprilUtils::SharedPtr< Matrix > aux; if (dest == 0) { aux = dest = new Matrix(obj->getNumDim(), obj->getDimPtr()); } dest = MatrixScalarMap1(obj, m_curried_lt(value), dest); aux.weakRelease(); return dest; } template Matrix *matLT(const Matrix *obj, const Matrix *other, Matrix *dest) { AprilUtils::SharedPtr< Matrix > aux; if (dest == 0) { aux = dest = new Matrix(obj->getNumDim(), obj->getDimPtr()); } dest = MatrixScalarMap2(obj, other, AprilMath::Functors::m_lt(), dest); aux.weakRelease(); return dest; } template Matrix *matGT(const Matrix *obj, const T &value, Matrix *dest) { AprilUtils::SharedPtr< Matrix > aux; if (dest == 0) { aux = dest = new Matrix(obj->getNumDim(), obj->getDimPtr()); } dest = MatrixScalarMap1(obj, m_curried_gt(value), dest); aux.weakRelease(); return dest; } template Matrix *matGT(const Matrix *obj, const Matrix *other, Matrix *dest) { AprilUtils::SharedPtr< Matrix > aux; if (dest == 0) { aux = dest = new Matrix(obj->getNumDim(), obj->getDimPtr()); } dest = MatrixScalarMap2(obj, other, AprilMath::Functors::m_gt(), dest); aux.weakRelease(); return dest; } template Matrix *matEQ(const Matrix *obj, const T &value, Matrix *dest) { AprilUtils::SharedPtr< Matrix > aux; if (dest == 0) { aux = dest = new Matrix(obj->getNumDim(), obj->getDimPtr()); } if (m_isnan(value)) { dest = MatrixScalarMap1(obj, m_curried_eq_nan(), dest); } else { dest =MatrixScalarMap1(obj, m_curried_eq(value), dest); } aux.weakRelease(); return dest; } template Matrix *matEQ(const Matrix *obj, const Matrix *other, Matrix *dest) { AprilUtils::SharedPtr< Matrix > aux; if (dest == 0) { aux = dest = new Matrix(obj->getNumDim(), obj->getDimPtr()); } dest = MatrixScalarMap2(obj, other, AprilMath::Functors::m_eq(), dest); aux.weakRelease(); return dest; } template Matrix *matNEQ(const Matrix *obj, const T &value, Matrix *dest) { AprilUtils::SharedPtr< Matrix > aux; if (dest == 0) { aux = dest = new Matrix(obj->getNumDim(), obj->getDimPtr()); } if (m_isnan(value)) { dest = MatrixScalarMap1(obj, m_curried_neq_nan(), dest); } else { dest = MatrixScalarMap1(obj, m_curried_neq(value), dest); } aux.weakRelease(); return dest; } template Matrix *matNEQ(const Matrix *obj, const Matrix *other, Matrix *dest) { AprilUtils::SharedPtr< Matrix > aux; if (dest == 0) { aux = dest = new Matrix(obj->getNumDim(), obj->getDimPtr()); } dest = MatrixScalarMap2(obj, other, AprilMath::Functors::m_neq(), dest); aux.weakRelease(); return dest; } template Matrix *matLT(const Matrix *, const float &, Matrix *); template Matrix *matLT(const Matrix *, const Matrix *, Matrix *); template Matrix *matGT(const Matrix *, const float &, Matrix *); template Matrix *matGT(const Matrix *, const Matrix *, Matrix *); template Matrix *matEQ(const Matrix *, const float &, Matrix *); template Matrix *matEQ(const Matrix *, const Matrix *, Matrix *); template Matrix *matNEQ(const Matrix *, const float &, Matrix *); template Matrix *matNEQ(const Matrix *, const Matrix *, Matrix *); template Matrix *matLT(const Matrix *, const double &, Matrix *); template Matrix *matLT(const Matrix *, const Matrix *, Matrix *); template Matrix *matGT(const Matrix *, const double &, Matrix *); template Matrix *matGT(const Matrix *, const Matrix *, Matrix *); template Matrix *matEQ(const Matrix *, const double &, Matrix *); template Matrix *matEQ(const Matrix *, const Matrix *, Matrix *); template Matrix *matNEQ(const Matrix *, const double &, Matrix *); template Matrix *matNEQ(const Matrix *, const Matrix *, Matrix *); template Matrix *matLT(const Matrix *, const int32_t &, Matrix *); template Matrix *matLT(const Matrix *, const Matrix *, Matrix *); template Matrix *matGT(const Matrix *, const int32_t &, Matrix *); template Matrix *matGT(const Matrix *, const Matrix *, Matrix *); template Matrix *matEQ(const Matrix *, const int32_t &, Matrix *); template Matrix *matEQ(const Matrix *, const Matrix *, Matrix *); template Matrix *matNEQ(const Matrix *, const int32_t &, Matrix *); template Matrix *matNEQ(const Matrix *, const Matrix *, Matrix *); } // namespace Boolean } // namespace MatrixExt } // namespace AprilMath april-ann-0.4.1/packages/basics/matrix/c_src/matrix_ext_boolean.h000066400000000000000000000137101263004425400250520ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "matrix_ext.h" #ifndef MATRIX_EXT_BOOLEAN_H #define MATRIX_EXT_BOOLEAN_H namespace AprilMath { namespace MatrixExt { /** * @brief Boolean operations over Matrix instances. * * This operations transform the given matrix in a Basics::MatrixBool * instance with True/False depending in the given condition. All the * functions receive as first argument the target Basics::Matrix and as last * argument an optional destination Basics::MatrixBool. In case of not given * last argument, a new Basics::MatrixBool will be allocated. * * @see AprilMath::MatrixExt */ namespace Boolean { //////////////////// BOOLEAN CONDITIONS //////////////////// /* BOOLEAN CONDITIONS: this methods transforms the given matrix in a ZERO/ONE matrix, depending in the truth of the given condition */ /** * @brief Compares every matrix element with the given value and updates * returned @c dest matrix with @c true or @c false depending in the * condition \f$ x < v \f$ * * @note If the given @c dest argument is 0, this operation allocates a * new destination matrix. */ template Basics::Matrix *matLT(const Basics::Matrix *obj, const T &value, Basics::Matrix *dest=0); /** * @brief Compares two matrices in a component-wise fashion, updates * returned @c dest matrix with @c true or @c false depending in the * condition \f$ x < v \f$ * * @note If the given @c dest argument is 0, this operation allocates a * new destination matrix. */ template Basics::Matrix *matLT(const Basics::Matrix *obj, const Basics::Matrix *other, Basics::Matrix *dest=0); /** * @brief Compares every matrix element with the given value and updates * returned @c dest matrix with @c true or @c false depending in the * condition \f$ x > v \f$ * * @note If the given @c dest argument is 0, this operation allocates a * new destination matrix. */ template Basics::Matrix *matGT(const Basics::Matrix *obj, const T &value, Basics::Matrix *dest=0); /** * @brief Compares two matrices in a component-wise fashion, updates * returned @c dest matrix with @c true or @c false depending in the * condition \f$ x > v \f$ * * @note If the given @c dest argument is 0, this operation allocates a * new destination matrix. */ template Basics::Matrix *matGT(const Basics::Matrix *obj, const Basics::Matrix *other, Basics::Matrix *dest=0); /** * @brief Compares every matrix element with the given value and updates * returned @c dest matrix with @c true or @c false depending in the * condition \f$ x = v \f$ * * @note If the given @c dest argument is 0, this operation allocates a * new destination matrix. */ template Basics::Matrix *matEQ(const Basics::Matrix *obj, const T &value, Basics::Matrix *dest=0); /** * @brief Compares two matrices in a component-wise fashion, updates * returned @c dest matrix with @c true or @c false depending in the * condition \f$ x = v \f$ * * @note If the given @c dest argument is 0, this operation allocates a * new destination matrix. */ template Basics::Matrix *matEQ(const Basics::Matrix *obj, const Basics::Matrix *other, Basics::Matrix *dest=0); /** * @brief Compares every matrix element with the given value and updates * returned @c dest matrix with @c true or @c false depending in the * condition \f$ x \neq v \f$ * * @note If the given @c dest argument is 0, this operation allocates a * new destination matrix. */ template Basics::Matrix *matNEQ(const Basics::Matrix *obj, const T &value, Basics::Matrix *dest=0); /** * @brief Compares two matrices in a component-wise fashion, updates * returned @c dest matrix with @c true or @c false depending in the * condition \f$ x \neq v \f$ * * @note If the given @c dest argument is 0, this operation allocates a * new destination matrix. */ template Basics::Matrix *matNEQ(const Basics::Matrix *obj, const Basics::Matrix *other, Basics::Matrix *dest=0); } // namespace Boolean } // namespace MatrixExt } // namespace AprilMath #endif // MATRIX_EXT_BOOLEAN_H april-ann-0.4.1/packages/basics/matrix/c_src/matrix_ext_initializers.cu000066400000000000000000000126031263004425400263210ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "cmath_overloads.h" #include "mathcore.h" #include "matrix.h" #include "maxmin.h" #include "realfftwithhamming.h" #include "smart_ptr.h" #include "sparse_matrix.h" // Must be defined in this order. #include "matrix_ext_initializers.h" // Must to be defined here. #include "map_matrix.h" #include "map_sparse_matrix.h" // Must to be defined here. #include "reduce_matrix.h" #include "reduce_sparse_matrix.h" using Basics::Matrix; using Basics::SparseMatrix; namespace AprilMath { namespace MatrixExt { namespace Initializers { template Matrix *matFill(Matrix *obj, const T value) { return MatrixScalarMap1(obj, m_curried_fill(value), obj); } template SparseMatrix *matFill(SparseMatrix *obj, const T value) { return SparseMatrixScalarMap1(obj, m_curried_fill(value), obj); } template Matrix *matZeros(Matrix *obj) { return matFill(obj, AprilMath::Limits::zero()); } template SparseMatrix *matZeros(SparseMatrix *obj) { return matFill(obj, AprilMath::Limits::zero()); } template Matrix *matOnes(Matrix *obj) { return matFill(obj, AprilMath::Limits::one()); } template SparseMatrix *matOnes(SparseMatrix *obj) { return matFill(obj, AprilMath::Limits::one()); } template Matrix *matDiag(Matrix *obj, const T value) { if (obj->getCudaFlag()) { ERROR_PRINT("WARNING! DIAG OPERATION NOT IMPLENTED FOR CUDA\n"); } for (int i=1; igetNumDim(); ++i) { if (obj->getDimSize(i) != obj->getDimSize(i-1)) { ERROR_EXIT(128, "Only allowed for squared matrices\n"); } } typename Matrix::random_access_iterator it(obj); AprilUtils::UniquePtr aux_coords(new int[obj->getNumDim()]); for (int i=0; igetDimSize(0); ++i) { for (int j=0; jgetNumDim(); ++j) aux_coords[j] = i; it(aux_coords.get(), obj->getNumDim()) = value; } return obj; } template Matrix *matFill(Matrix *, const float); template Matrix *matZeros(Matrix *); template Matrix *matOnes(Matrix *); template Matrix *matDiag(Matrix *, const float); template Matrix *matFill(Matrix *, const double); template Matrix *matZeros(Matrix *); template Matrix *matOnes(Matrix *); template Matrix *matDiag(Matrix *, const double); template Matrix *matFill(Matrix *, const ComplexF); template Matrix *matZeros(Matrix *); template Matrix *matOnes(Matrix *); template Matrix *matDiag(Matrix *, const ComplexF); template Matrix *matFill(Matrix *, const char); template Matrix *matZeros(Matrix *); template Matrix *matOnes(Matrix *); template Matrix *matDiag(Matrix *, const char); template Matrix *matFill(Matrix *, const bool); template Matrix *matZeros(Matrix *); template Matrix *matOnes(Matrix *); template Matrix *matDiag(Matrix *, const bool); template Matrix *matFill(Matrix *, const int32_t); template Matrix *matZeros(Matrix *); template Matrix *matOnes(Matrix *); template Matrix *matDiag(Matrix *, const int32_t); template SparseMatrix *matFill(SparseMatrix *, const float ); template SparseMatrix *matZeros(Basics::SparseMatrix *); template SparseMatrix *matOnes(SparseMatrix *); template SparseMatrix *matFill(SparseMatrix *, const double ); template SparseMatrix *matZeros(Basics::SparseMatrix *); template SparseMatrix *matOnes(SparseMatrix *); template SparseMatrix *matFill(SparseMatrix *, const ComplexF ); template SparseMatrix *matZeros(Basics::SparseMatrix *); template SparseMatrix *matOnes(SparseMatrix *); } // namespace Initializers } // namespace MatrixExt } // namespace AprilMath april-ann-0.4.1/packages/basics/matrix/c_src/matrix_ext_initializers.h000066400000000000000000000047471263004425400261530ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIX_H #include "matrix.h" #include "sparse_matrix.h" #endif #ifndef MATRIX_OPERATIONS_H #define MATRIX_OPERATIONS_H namespace AprilMath { namespace MatrixExt { /** * @brief Initializers for Matrix instances. * * This operations initialize the given Basics::Matrix changing it * in-place. * * @see AprilMath::MatrixExt */ namespace Initializers { /// Initialize all the matrix elements to the given value. template Basics::Matrix *matFill(Basics::Matrix *obj, const T value); /// Initialize all the matrix elements to the given value. template Basics::SparseMatrix *matFill(Basics::SparseMatrix *obj, const T value); /// Initialize all the matrix elements to zero. template Basics::Matrix *matZeros(Basics::Matrix *obj); /// Initialize all the matrix elements to zero. template Basics::SparseMatrix *matZeros(Basics::SparseMatrix *obj); /// Initialize all the matrix elements to one. template Basics::Matrix *matOnes(Basics::Matrix *obj); /// Initialize all the matrix elements to one. template Basics::SparseMatrix *matOnes(Basics::SparseMatrix *obj); /// Initialize the matrix diagonal elements to the given value. template Basics::Matrix *matDiag(Basics::Matrix *obj, const T value); } // namespace Initializers } // namespace MatrixExt } // namespace AprilMath #endif // MATRIX_OPERATIONS_H april-ann-0.4.1/packages/basics/matrix/c_src/matrix_ext_lapack.cu000066400000000000000000000233721263004425400250530ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "cmath_overloads.h" #include "mathcore.h" #include "matrix.h" #include "maxmin.h" #include "realfftwithhamming.h" #include "smart_ptr.h" #include "sparse_matrix.h" // Must be defined in this order. #include "matrix_ext_lapack.h" // Must to be defined here. #include "map_matrix.h" #include "map_sparse_matrix.h" // Must to be defined here. #include "reduce_matrix.h" #include "reduce_sparse_matrix.h" using Basics::Matrix; using Basics::SparseMatrix; namespace AprilMath { namespace MatrixExt { namespace LAPACK { Matrix *matInv(const Matrix *obj) { if (obj->getNumDim() != 2 || obj->getDimSize(0) != obj->getDimSize(1)) { ERROR_EXIT(128, "Only squared bi-dimensional matrices are allowed\n"); } Matrix *A = obj->clone(); AprilUtils::UniquePtr IPIV( new int[obj->getDimSize(0)] ); int INFO; INFO = clapack_sgetrf(CblasRowMajor, A->getDimSize(0), A->getDimSize(1), A->getRawDataAccess()->getPPALForReadAndWrite(), A->getStrideSize(0), IPIV.get()); checkLapackInfo(INFO); INFO = clapack_sgetri(CblasRowMajor, A->getDimSize(0), A->getRawDataAccess()->getPPALForReadAndWrite(), A->getStrideSize(0), IPIV.get()); checkLapackInfo(INFO); return A; } void matSVD(const Matrix *obj, Matrix **U, SparseMatrix **S, Matrix **VT) { if (obj->getNumDim() != 2) { ERROR_EXIT(128, "Only bi-dimensional matrices are allowed\n"); } AprilUtils::SharedPtr< Matrix > A( obj->clone() ); AprilUtils::SharedPtr< Matrix > AT( A->transpose() ); int INFO; const int m = A->getDimSize(0); // cols const int n = A->getDimSize(1); // rows const int numSV = (m *S_values = new GPUMirroredMemoryBlock(numSV); GPUMirroredMemoryBlock *S_indices = new GPUMirroredMemoryBlock(numSV); GPUMirroredMemoryBlock *S_first = new GPUMirroredMemoryBlock(m+1); for (int i=0; i > sU; AprilUtils::SharedPtr< SparseMatrix > sS; AprilUtils::SharedPtr< Matrix > sVT; sU = new Matrix(2, dimsU); sS = new SparseMatrix(m,n,S_values,S_indices,S_first); sVT = new Matrix(2, dimsVT); AprilUtils::SharedPtr< Matrix > UT( sVT->transpose() ); AprilUtils::SharedPtr< Matrix > V( sU->transpose() ); // m,n are changed by n,m because the tranposition of the matrices INFO = clapack_sgesdd(CblasColMajor, n, m, AT->getStrideSize(1), AT->getRawDataAccess()->getPPALForReadAndWrite(), UT->getRawDataAccess()->getPPALForWrite(), S_values->getPPALForWrite(), V->getRawDataAccess()->getPPALForWrite()); checkLapackInfo(INFO); *U = sU.weakRelease(); *S = sS.weakRelease(); *VT = sVT.weakRelease(); } // FROM: http://www.r-bloggers.com/matrix-determinant-with-the-lapack-routine-dspsv/ AprilUtils::log_float matLogDeterminant(const Matrix *obj, float &sign) { if (obj->getNumDim() != 2 || obj->getDimSize(0) != obj->getDimSize(1)) { ERROR_EXIT(128, "Only squared bi-dimensional matrices are allowed\n"); } AprilUtils::SharedPtr< Matrix > A( obj->clone() ); AprilUtils::SharedPtr< Matrix > AT( A->transpose() ); // in col major AprilUtils::UniquePtr IPIV( new int[A->getDimSize(0)] ); int INFO; INFO = clapack_sgetrf(CblasColMajor, AT->getDimSize(0), AT->getDimSize(1), AT->getRawDataAccess()->getPPALForReadAndWrite(), AT->getStrideSize(1), IPIV.get()); checkLapackInfo(INFO); Matrix::const_random_access_iterator it(A.get()); AprilUtils::log_float det = AprilUtils::log_float::from_float(it(0,0)); int row_changes = 0; #if defined(USE_MKL) || defined(USE_XCODE) // in MKL and XCODE the permutation IPIV is one-based if (IPIV[0] != 1) ++row_changes; #else // in atlas_lapack IPIV is zero-based if (IPIV[0] != 0) ++row_changes; #endif for (int i=1; igetDimSize(0); ++i) { const float &v = it(i,i); if (v < 0.0f) { ERROR_EXIT(128, "Impossible to compute logDeterminant over " "non-positive matrix\n"); } det *= AprilUtils::log_float::from_float(v); #if defined(USE_MKL) || defined(USE_XCODE) // in MKL and XCODE the permutation IPIV is one-based if (IPIV[i] != (i+1)) ++row_changes; #else // in atlas_lapack IPIV is zero-based if (IPIV[i] != i) ++row_changes; #endif } if ( (row_changes & 1) == 0 ) sign = 1.0f; else sign = -1.0f; return det; } // FROM: http://www.r-bloggers.com/matrix-determinant-with-the-lapack-routine-dspsv/ double matDeterminant(const Matrix *obj) { if (obj->getNumDim() != 2 || obj->getDimSize(0) != obj->getDimSize(1)) { ERROR_EXIT(128, "Only squared bi-dimensional matrices are allowed\n"); } AprilUtils::SharedPtr< Matrix > A( obj->clone() ); AprilUtils::SharedPtr< Matrix > AT( A->transpose() ); // in col major AprilUtils::UniquePtr IPIV( new int[A->getDimSize(0)] ); int INFO; INFO = clapack_sgetrf(CblasColMajor, AT->getDimSize(0), AT->getDimSize(1), AT->getRawDataAccess()->getPPALForReadAndWrite(), AT->getStrideSize(1), IPIV.get()); checkLapackInfo(INFO); Matrix::const_random_access_iterator it(A.get()); double det = 1.0f; int row_changes = 0; for (int i=0; igetDimSize(0); ++i) { const float &v = it(i,i); det *= v; #if defined(USE_MKL) || defined(USE_XCODE) // in MKL and XCODE the permutation IPIV is one-based if (IPIV[i] != (i+1)) ++row_changes; #else // in atlas_lapack IPIV is zero-based if (IPIV[i] != i) ++row_changes; #endif } double sign; if ( (row_changes & 1) == 0 ) sign = 1.0f; else sign = -1.0f; return sign*det; } /** * @brief Compute the Cholesky factorization of a real symmetric positive * definite matrix A. * * The factorization has the form: * A = U**T * U, if UPLO = 'U', or * A = L * L**T, if UPLO = 'L', * where U is an upper triangular matrix and L is lower triangular. * * @param obj - The input matrix. * * @param uplo - A char with 'U' or 'L'. */ Matrix *matCholesky(const Matrix *obj, char uplo) { if (obj->getNumDim() != 2 || obj->getDimSize(0) != obj->getDimSize(1)) { ERROR_EXIT(128, "Only squared bi-dimensional matrices are allowed\n"); } Matrix *A = obj->clone(); int INFO = clapack_spotrf(CblasRowMajor, (uplo == 'U') ? CblasUpper : CblasLower, A->getDimSize(0), A->getRawDataAccess()->getPPALForReadAndWrite(), A->getStrideSize(0)); checkLapackInfo(INFO); switch(uplo) { case 'U': { Matrix::random_access_iterator it(A); for (int i=0; igetDimSize(0); ++i) { for (int j=0; j::random_access_iterator it(A); for (int i=0; igetDimSize(0); ++i) { for (int j=i+1; jgetDimSize(0); ++j) { it(i,j) = 0.0f; } } } } return A; } } // namespace LAPACK } // namespace MatrixExt } // namespace AprilMath april-ann-0.4.1/packages/basics/matrix/c_src/matrix_ext_lapack.h000066400000000000000000000057721263004425400246770ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "matrix_ext.h" #ifndef MATRIX_EXT_LAPACK_H #define MATRIX_EXT_LAPACK_H namespace AprilMath { namespace MatrixExt { /** * @brief LAPACK operations over Matrix instances. * * This operations have been implemented using LAPACK functions. All of * these functions return its result or a new allocated matrix. * * @see AprilMath::MatrixExt */ namespace LAPACK { //////////////////// LAPACK MATH OPERATIONS //////////////////// // FIXME: using WRAPPER for generalized CULA, LAPACK, float and complex // numbers /// Inverts the given matrix. Basics::Matrix *matInv(const Basics::Matrix *obj); /// Computes SVD decomposition of the given matrix. S, U, VT are given by reference. void matSVD(const Basics::Matrix *obj, Basics::Matrix **U, Basics::SparseMatrix **S, Basics::Matrix **VT); // FROM: http://www.r-bloggers.com/matrix-determinant-with-the-lapack-routine-dspsv/ /// Computes the logarithm of the determinant. The sign is returned by reference. AprilUtils::log_float matLogDeterminant(const Basics::Matrix *obj, float &sign); // FROM: http://www.r-bloggers.com/matrix-determinant-with-the-lapack-routine-dspsv/ /// Computes the determinant. double matDeterminant(const Basics::Matrix *obj); /** * @brief Compute the Cholesky factorization of a real symmetric positive * definite matrix A. * * The factorization has the form: * A = U**T * U, if UPLO = 'U', or * A = L * L**T, if UPLO = 'L', * where U is an upper triangular matrix and L is lower triangular. * * @param obj - The input matrix. * * @param uplo - A char with 'U' or 'L'. */ Basics::Matrix * matCholesky(const Basics::Matrix *obj, char uplo); } // namespace LAPACK } // namespace MatrixExt } // namespace AprilMath #endif // MATRIX_EXT_LAPACK_H april-ann-0.4.1/packages/basics/matrix/c_src/matrix_ext_misc.cu000066400000000000000000001227171263004425400245560ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "cmath_overloads.h" #include "mathcore.h" #include "matrix.h" #include "maxmin.h" #include "realfftwithhamming.h" #include "smart_ptr.h" #include "sparse_matrix.h" // Must be defined in this order. #include "matrix_ext_misc.h" // Must to be defined here. #include "map_matrix.h" #include "map_sparse_matrix.h" // Must to be defined here. #include "reduce_matrix.h" #include "reduce_sparse_matrix.h" // Must to be defined here. #include "cuda_utils.h" #include "matrix_ext_blas.h" #include "omp_utils.h" using Basics::Matrix; using Basics::SparseMatrix; #ifdef USE_CUDA using namespace AprilMath::CUDA; #endif namespace AprilMath { namespace MatrixExt { namespace Misc { //////////////////// OTHER MATH OPERATIONS //////////////////// #ifdef USE_CUDA template __global__ void indexVectorKernel(const T *m_ptr, const int m_stride, const int32_t *idx_ptr, const int idx_stride, T *dest_ptr, const int dest_stride, const int N) { for ( int i = blockIdx.x*blockDim.x + threadIdx.x; i < N; i += blockDim.x*gridDim.x ) { // WARNING: idx counts from 1, instead of 0 dest_ptr[ i*dest_stride ] = m_ptr[ m_stride * (idx_ptr[i*idx_stride]-1) ]; } } template __global__ void indexedFillVectorKernel(T *m_ptr, const int m_stride, const int32_t *idx_ptr, const int idx_stride, const int N, const T val) { for ( int i = blockIdx.x*blockDim.x + threadIdx.x; i < N; i += blockDim.x*gridDim.x ) { // WARNING: idx counts from 1, instead of 0 m_ptr[ m_stride * (idx_ptr[i*idx_stride]-1) ] = val; } } template __global__ void indexedCopyVectorKernel(T *m_ptr, const int m_stride, const int32_t *idx_ptr, const int idx_stride, const T *other_ptr, const int other_stride, const int N) { for ( int i = blockIdx.x*blockDim.x + threadIdx.x; i < N; i += blockDim.x*gridDim.x ) { // WARNING: idx counts from 1, instead of 0 m_ptr[ m_stride * (idx_ptr[i*idx_stride]-1) ] = other_ptr[ i*other_stride ]; } } #endif template void indexVectorWrapper(Matrix *m, Matrix *idx, Matrix *dest) { const int N = idx->size(); const int m_offset = m->getOffset(); const int idx_offset = idx->getOffset(); const int dest_offset = dest->getOffset(); const int m_stride = m->getStrideSize(0); const int idx_stride = idx->getStrideSize(0); const int dest_stride = dest->getStrideSize(0); #ifdef USE_CUDA bool cuda_flag = m->getCudaFlag() || idx->getCudaFlag() || dest->getCudaFlag(); if (cuda_flag) { const T *m_ptr = m->getRawDataAccess()->getGPUForRead() + m_offset; const int32_t *idx_ptr = idx->getRawDataAccess()->getGPUForRead() + idx_offset; T *dest_ptr = dest->getRawDataAccess()->getGPUForWrite() + dest_offset; // Number of threads on each block dimension int num_threads, num_blocks; computeBlockAndGridSizesForArray(N, num_threads, num_blocks); indexVectorKernel<<>> (m_ptr, m_stride, idx_ptr, idx_stride, dest_ptr, dest_stride, N); } else { #endif const T *m_ptr = m->getRawDataAccess()->getPPALForRead() + m_offset; const int32_t *idx_ptr = idx->getRawDataAccess()->getPPALForRead() + idx_offset; T *dest_ptr = dest->getRawDataAccess()->getPPALForWrite() + dest_offset; for(int i=0; i void indexedFillVectorWrapper(Matrix *m, Matrix *idx, T val) { const int N = idx->size(); const int m_offset = m->getOffset(); const int idx_offset = idx->getOffset(); const int m_stride = m->getStrideSize(0); const int idx_stride = idx->getStrideSize(0); #ifdef USE_CUDA bool cuda_flag = m->getCudaFlag() || idx->getCudaFlag(); if (cuda_flag) { T *m_ptr = m->getRawDataAccess()->getGPUForWrite() + m_offset; const int32_t *idx_ptr = idx->getRawDataAccess()->getGPUForRead() + idx_offset; // Number of threads on each block dimension int num_threads, num_blocks; computeBlockAndGridSizesForArray(N, num_threads, num_blocks); indexedFillVectorKernel<<>> (m_ptr, m_stride, idx_ptr, idx_stride, N, val); } else { #endif T *m_ptr = m->getRawDataAccess()->getPPALForWrite() + m_offset; const int32_t *idx_ptr = idx->getRawDataAccess()->getPPALForRead() + idx_offset; for(int i=0; i void indexedCopyVectorWrapper(Matrix *m, Matrix *idx, Matrix *other) { const int N = idx->size(); const int m_offset = m->getOffset(); const int idx_offset = idx->getOffset(); const int other_offset = other->getOffset(); const int m_stride = m->getStrideSize(0); const int idx_stride = idx->getStrideSize(0); const int other_stride = other->getStrideSize(0); #ifdef USE_CUDA bool cuda_flag = m->getCudaFlag() || idx->getCudaFlag() || other->getCudaFlag(); if (cuda_flag) { T *m_ptr = m->getRawDataAccess()->getGPUForWrite() + m_offset; const int32_t *idx_ptr = idx->getRawDataAccess()->getGPUForRead() + idx_offset; const T *other_ptr = other->getRawDataAccess()->getGPUForRead() + other_offset; // Number of threads on each block dimension int num_threads, num_blocks; computeBlockAndGridSizesForArray(N, num_threads, num_blocks); indexedCopyVectorKernel<<>> (m_ptr, m_stride, idx_ptr, idx_stride, other_ptr, other_stride, N); } else { #endif T *m_ptr = m->getRawDataAccess()->getPPALForWrite() + m_offset; const int32_t *idx_ptr = idx->getRawDataAccess()->getPPALForRead() + idx_offset; const T *other_ptr = other->getRawDataAccess()->getPPALForRead() + other_offset; for(int i=0; i struct MatOrderCompare { typename Matrix::const_random_access_iterator data; MatOrderCompare(Matrix *m) : data(m) {} bool operator()(const int32_t &a, const int32_t &b) const { return data(a-1) < data(b-1); } }; template Matrix *matOrder(const Matrix *m, Matrix *dest) { AprilUtils::SharedPtr< Matrix > aux; AprilUtils::SharedPtr< Matrix > squeezed(m->constSqueeze()); if (squeezed->getNumDim() > 1) { ERROR_EXIT(128, "Needs a rank 1 matrix object\n"); } if (dest == 0) { aux = dest = new Matrix(1, squeezed->size()); } else { if (squeezed->size() != dest->size()) { ERROR_EXIT(128, "Incorrect destination size\n"); } if (!squeezed->getIsContiguous()) { ERROR_EXIT(128, "Destination matrix should be contiguous\n"); } } int i=1; // WARNING: we start counting at 1, instead of 0 for (Matrix::iterator it = dest->begin(); it!=dest->end(); ++it) { *it = i++; } int32_t *ptr = dest->getRawDataAccess()->getPPALForReadAndWrite(); MatOrderCompare cmp(squeezed.get()); AprilUtils::Sort(ptr, 0, dest->size()-1, cmp); aux.weakRelease(); return dest; } template Matrix *matOrderRank(const Matrix *m, Matrix *dest) { AprilUtils::SharedPtr< Matrix > aux = matOrder(m); AprilUtils::SharedPtr< Matrix > aux2; if (dest == 0) { aux2 = dest = new Matrix(1, aux->size()); } else { if (aux->size() != dest->size()) { ERROR_EXIT(128, "Incorrect destination size\n"); } } Matrix::random_access_iterator dst_it(dest); int i=1; // WARNING: we start counting at 1, instead of 0 for (Matrix::const_iterator src_it = aux->begin(); src_it != aux->end(); ++src_it) { dst_it( *src_it - 1 ) = i++; } aux2.weakRelease(); return dest; } template Matrix *matIndex(const Matrix *m, int dim, const Matrix *idx) { AprilUtils::SharedPtr< Matrix > sq_idx = idx->constSqueeze(); if (sq_idx->getNumDim() != 1) { ERROR_EXIT(128, "Needs a rank 1 tensor as second argument (index)\n"); } if (dim < 0 || dim >= m->getNumDim()) { ERROR_EXIT(128, "Dimension argument out-of-bounds"); } const int D = m->getNumDim(); // copy m->dims into a new array AprilUtils::UniquePtr dims = new int[D]; for (int i=0; igetDimSize(i); // take the given dimension size and change it to fit the result matrix int dim_limit = dims[dim]; dims[dim] = idx->size(); // allocate memory for the resulting matrix AprilUtils::SharedPtr< Matrix > result; result = new Matrix(m->getNumDim(), dims.get()); #ifdef USE_CUDA result->setUseCuda(m->getCudaFlag()); #endif if (m->size() == dim_limit) { // vector version, ad-hoc implementation AprilUtils::SharedPtr< Matrix > sq_m = m->constSqueeze(); AprilUtils::SharedPtr< Matrix > sq_r = result->squeeze(); indexVectorWrapper(sq_m.get(), sq_idx.get(), sq_r.get()); } else { // matrix version, ad-hoc general implementation using select AprilUtils::SharedPtr< Matrix > m_slice, r_slice; typename Matrix::const_iterator it = idx->begin(); // traverse all given indices copying submatrices for (int i=0; isize(); ++i, ++it) { april_assert(it != idx->end()); april_assert(i < result->getDimSize(dim)); // WARNING: idx counts from 1, instead of 0 const int p = *it - 1; april_assert(p < m->getDimSize(dim)); // take submatrices m_slice = m->select(dim, p, m_slice.get()); r_slice = result->select(dim, i, r_slice.get()); // copy them AprilMath::MatrixExt::BLAS::matCopy(r_slice.get(), m_slice.get()); } } return result.weakRelease(); } template Matrix *matIndexedFill(Matrix *m, int dim, const Matrix *idx, T val) { AprilUtils::SharedPtr< Matrix > m_ref = m; // IncRef m AprilUtils::SharedPtr< Matrix > sq_idx = idx->constSqueeze(); if (sq_idx->getNumDim() != 1) { ERROR_EXIT(128, "Needs a rank 1 tensor as second argument (index)\n"); } if (dim < 0 || dim >= m->getNumDim()) { ERROR_EXIT(128, "Dimension argument out-of-bounds"); } const int dim_limit = m->getDimSize(dim); if (m->size() == dim_limit) { // vector version, ad-hoc implementation AprilUtils::SharedPtr< Matrix > sq_m = m->squeeze(); indexedFillVectorWrapper(sq_m.get(), sq_idx.get(), val); } else { // matrix version, ad-hoc general implementation using select AprilUtils::SharedPtr< Matrix > m_slice; typename Matrix::const_iterator it = idx->begin(); // traverse all given indices copying submatrices for (int i=0; isize(); ++i, ++it) { april_assert(it != idx->end()); // WARNING: idx counts from 1, instead of 0 const int p = *it - 1; april_assert(p < m->getDimSize(dim)); // take submatrix m_slice = m->select(dim, p, m_slice.get()); // fill it with val constant AprilMath::MatrixExt::Initializers::matFill(m_slice.get(), val); } } return m; } template Matrix *matIndexedCopy(Matrix *m, int dim, const Matrix *idx, const Matrix *other) { AprilUtils::SharedPtr< Matrix > sq_idx = idx->constSqueeze(); if (sq_idx->getNumDim() != 1) { ERROR_EXIT(128, "Needs a rank 1 tensor as second argument (index)\n"); } if (dim < 0 || dim >= m->getNumDim()) { ERROR_EXIT(128, "Dimension argument out-of-bounds\n"); } const int D = m->getNumDim(); // copy m->dims into a new array AprilUtils::UniquePtr dims = new int[D]; for (int i=0; igetDimSize(i); const int dim_limit = dims[dim]; dims[dim] = idx->size(); if (!other->sameDim(dims.get(), D)) { ERROR_EXIT(128, "Incompatible matrix sizes\n"); } if (m->size() == dim_limit) { // vector version, ad-hoc implementation AprilUtils::SharedPtr< Matrix > sq_m = m->squeeze(); AprilUtils::SharedPtr< Matrix > sq_o = other->constSqueeze(); indexedCopyVectorWrapper(sq_m.get(), sq_idx.get(), sq_o.get()); } else { // matrix version, ad-hoc general implementation using select AprilUtils::SharedPtr< Matrix > m_slice, o_slice; typename Matrix::const_iterator it = idx->begin(); // traverse all given indices copying submatrices for (int i=0; isize(); ++i, ++it) { april_assert(it != idx->end()); april_assert(i < other->getDimSize(dim)); // WARNING: idx counts from 1, instead of 0 const int p = *it - 1; april_assert(p < m->getDimSize(dim)); // take submatrices m_slice = m->select(dim, p, m_slice.get()); o_slice = other->select(dim, i, o_slice.get()); // fill it with val constant AprilMath::MatrixExt::BLAS::matCopy(m_slice.get(), o_slice.get()); } } return m; } template Matrix *matIndex(const Matrix *m, int dim, const Matrix *mask) { AprilUtils::SharedPtr< Matrix > idx; idx = matNonZeroIndices(mask); return matIndex(m, dim, idx.get()); } template Matrix *matIndexedFill(Matrix *m, int dim, const Matrix *mask, T val) { AprilUtils::SharedPtr< Matrix > idx; idx = matNonZeroIndices(mask); return matIndexedFill(m, dim, idx.get(), val); } template Matrix *matIndexedCopy(Matrix *m, int dim, const Matrix *mask, const Matrix *other) { AprilUtils::SharedPtr< Matrix > idx; idx = matNonZeroIndices(mask); return matIndexedCopy(m, dim, idx.get(), other); } template Matrix *matAddition(const Matrix *a, const Matrix *b, Matrix *c) { AprilUtils::SharedPtr< Matrix > aux; if (c == 0) aux = c = a->clone(); c = AprilMath::MatrixExt::BLAS:: matAxpy(c, AprilMath::Limits::one(), b); aux.weakRelease(); return c; } template Matrix *matSubstraction(const Matrix *a, const Matrix *b, Matrix *c) { AprilUtils::SharedPtr< Matrix > aux; if (c == 0) aux = c = a->clone(); c = AprilMath::MatrixExt::BLAS:: matAxpy(c, -AprilMath::Limits::one(), b); aux.weakRelease(); return c; } template Matrix *matMultiply(const Matrix *a, const Matrix *b, Matrix *c) { AprilUtils::SharedPtr< Matrix > aux; if (b->isVector()) { if (a->isColVector()) { // OUTER product int dim[2] = {a->size(),b->size()}; if (c == 0) { aux = c = new Matrix(2, dim); #ifdef USE_CUDA c->setUseCuda(a->getCudaFlag() || b->getCudaFlag()); #endif } else if (!c->sameDim(dim, 2)) { ERROR_EXIT2(128, "Incorrect matrix sizes, expected %dx%d\n", dim[0], dim[1]); } AprilMath::MatrixExt::BLAS:: matGer(AprilMath::MatrixExt::Initializers::matZeros(c), AprilMath::Limits::one(), a, b); } else if (!a->isVector()) { // Matrix-Vector product int dim[2] = {a->getDimSize(0),1}; if (c == 0) { aux = c = new Matrix(b->getNumDim(), dim); #ifdef USE_CUDA c->setUseCuda(a->getCudaFlag() || b->getCudaFlag()); #endif } else if (!c->sameDim(dim, b->getNumDim())) { ERROR_EXIT2(128, "Incorrect matrix sizes, expected %dx%d\n", dim[0], dim[1]); } AprilMath::MatrixExt::BLAS:: matGemv(AprilMath::MatrixExt::Initializers::matZeros(c), CblasNoTrans, AprilMath::Limits::one(), a, b, AprilMath::Limits::zero()); } else { // DOT product int dim[2] = {1,1}; if (c == 0) { aux = c = new Matrix(a->getNumDim(), dim); #ifdef USE_CUDA c->setUseCuda(a->getCudaFlag() || b->getCudaFlag()); #endif } else if (!c->sameDim(dim, a->getNumDim())) { ERROR_EXIT2(128, "Incorrect matrix sizes, expected %dx%d\n", dim[0], dim[1]); } c->getRawDataAccess()->putValue( c->getOffset(), AprilMath::MatrixExt::BLAS:: matDot(a, b) ); } } else if (a->getNumDim() == 2 && b->getNumDim() == 2 && a->getDimSize(1) == b->getDimSize(0)) { // Matrix-Matrix product int dim[2] = {a->getDimSize(0), b->getDimSize(1)}; if (c == 0) { aux = c = new Matrix(2,dim); #ifdef USE_CUDA c->setUseCuda(a->getCudaFlag() || b->getCudaFlag()); #endif } else if (!c->sameDim(dim,2)) { ERROR_EXIT2(128, "Incorrect matrix sizes, expected %dx%d\n", dim[0], dim[1]); } AprilMath::MatrixExt::BLAS:: matGemm(AprilMath::MatrixExt::Initializers::matZeros(c), CblasNoTrans, CblasNoTrans, AprilMath::Limits::one(), a, b, AprilMath::Limits::zero()); } else { ERROR_EXIT(128, "Incompatible matrix sizes\n"); } aux.weakRelease(); return c; } Basics::Matrix *matRealFFTwithHamming(Basics::Matrix *obj, int wsize, int wadvance, Basics::Matrix *dest) { AprilUtils::SharedPtr< Matrix > aux; const int N = obj->getNumDim(); if (N != 1) ERROR_EXIT(128, "Only valid for numDim=1\n"); if (wsize > obj->size() || wadvance > obj->size()) { ERROR_EXIT(128, "Incompatible wsize or wadvance value\n"); } AprilMath::RealFFTwithHamming real_fft(wsize); const int M = real_fft.getOutputSize(); AprilUtils::UniquePtr dest_size(new int[N+1]); dest_size[0] = (obj->getDimSize(0) - wsize)/wadvance + 1; dest_size[1] = M; if (dest != 0) { if (!dest->sameDim(dest_size.get(), N+1)) { ERROR_EXIT(128, "Incompatible dest matrix\n"); } } else { aux = dest = new Matrix(N+1, dest_size.get()); #ifdef USE_CUDA dest->setUseCuda(obj->getCudaFlag()); #endif } AprilUtils::UniquePtr input(new double[wsize]); AprilUtils::UniquePtr output(new double[M]); // Basics::Matrix::sliding_window swindow(obj, &wsize, 0, // offset &wadvance); AprilUtils::SharedPtr< Matrix > input_slice; AprilUtils::SharedPtr< Matrix > output_slice; int i=0, j; while(!swindow.isEnd()) { april_assert(i < dest_size[0]); input_slice = swindow.getMatrix(input_slice.get()); output_slice = dest->select(0, i); j=0; for (Basics::Matrix::const_iterator it(input_slice->begin()); it != input_slice->end(); ++it, ++j) { april_assert(j(*it); } april_assert(j==wsize); real_fft(input.get(), output.get()); j=0; for (Basics::Matrix::iterator it(output_slice->begin()); it != output_slice->end(); ++it, ++j) { april_assert(j(output[j]); } april_assert(j==M); ++i; swindow.next(); } april_assert(i == dest_size[0]); aux.weakRelease(); return dest; } template Basics::Matrix *matConvertTo(const Basics::Matrix *input, Basics::Matrix *dest) { AprilUtils::SharedPtr< Matrix > aux; if (dest != 0) { if (!dest->sameDim(input)) { ERROR_EXIT(256, "Incompatible matrix sizes\n"); } } else { aux = dest = new Basics::Matrix(input->getNumDim(), input->getDimPtr()); } dest = MatrixScalarMap1(input, AprilMath::Functors::m_cast(), dest); aux.weakRelease(); return dest; } template int matCountEq(const Basics::Matrix *input, T value) { return MatrixScalarReduce1(input, AprilMath::make_r_map1 (AprilMath::m_curried_eq(value), AprilMath::Functors::r_add()), AprilMath::Functors::r_add(), 0); } template int matCountNeq(const Basics::Matrix *input, T value) { return MatrixScalarReduce1(input, AprilMath::make_r_map1 (AprilMath::m_curried_neq(value), AprilMath::Functors::r_add()), AprilMath::Functors::r_add(), 0); } template Basics::Matrix *matNonZeroIndices(const Basics::Matrix *input, Basics::Matrix *dest) { AprilUtils::SharedPtr > aux; AprilUtils::SharedPtr > sq_input = input->constSqueeze(); if (sq_input->getNumDim() != 1) { ERROR_EXIT(128, "Needs a rank 1 matrix\n"); } int non_zeros = sq_input->size() - matCountEq(sq_input.get(), AprilMath::Limits::zero()); if (non_zeros == 0) { ERROR_EXIT(128, "Unable to handle the given input matrix, it looks like an all false/zero matrix\n"); } if (dest != 0) { if (dest->size() != non_zeros) { ERROR_EXIT(256, "Incompatible matrix sizes\n"); } } else { aux = dest = new Basics::Matrix(1, &non_zeros); } int k=0; Basics::Matrix::iterator dest_it = dest->begin(); for (typename Basics::Matrix::const_iterator it = sq_input->begin(); it != sq_input->end(); ++it) { ++k; // first index is 1, to be compatible with Lua if (*it != AprilMath::Limits::zero()) { april_assert(dest_it != dest->end()); *dest_it = k; ++dest_it; } } april_assert(dest_it == dest->end()); aux.weakRelease(); return dest; } template Matrix *matOrder(const Matrix *, Matrix *); template Matrix *matOrderRank(const Matrix *, Matrix *); template Matrix *matIndex(const Matrix *, int, const Matrix *); template Matrix *matIndex(const Matrix *, int, const Matrix *); template Matrix *matIndexedFill(Matrix *, int, const Matrix *, float); template Matrix *matIndexedFill(Matrix *, int, const Matrix *, float); template Matrix *matIndexedCopy(Matrix *, int, const Matrix *, const Matrix *); template Matrix *matIndexedCopy(Matrix *, int, const Matrix *, const Matrix *); template Matrix *matAddition(const Matrix *, const Matrix *, Matrix *); template Matrix *matSubstraction(const Matrix *, const Matrix *, Matrix *); template Matrix *matMultiply(const Matrix *, const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matNonZeroIndices(const Matrix *input, Basics::Matrix *dest); template int matCountEq(const Matrix *, float); template int matCountNeq(const Matrix *, float); template Matrix *matOrder(const Matrix *, Matrix *); template Matrix *matOrderRank(const Matrix *, Matrix *); template Matrix *matIndex(const Matrix *, int, const Matrix *); template Matrix *matIndex(const Matrix *, int, const Matrix *); template Matrix *matIndexedFill(Matrix *, int, const Matrix *, double); template Matrix *matIndexedFill(Matrix *, int, const Matrix *, double); template Matrix *matIndexedCopy(Matrix *, int, const Matrix *, const Matrix *); template Matrix *matIndexedCopy(Matrix *, int, const Matrix *, const Matrix *); template Matrix *matAddition(const Matrix *, const Matrix *, Matrix *); template Matrix *matSubstraction(const Matrix *, const Matrix *, Matrix *); template Matrix *matMultiply(const Matrix *, const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matNonZeroIndices(const Matrix *input, Basics::Matrix *dest); template int matCountEq(const Matrix *, double); template int matCountNeq(const Matrix *, double); template Matrix *matIndex(const Matrix *, int, const Matrix *); template Matrix *matIndex(const Matrix *, int, const Matrix *); template Matrix *matIndexedFill(Matrix *, int, const Matrix *, ComplexF); template Matrix *matIndexedFill(Matrix *, int, const Matrix *, ComplexF); template Matrix *matIndexedCopy(Matrix *, int, const Matrix *, const Matrix *); template Matrix *matIndexedCopy(Matrix *, int, const Matrix *, const Matrix *); template Matrix *matAddition(const Matrix *, const Matrix *, Matrix *); template Matrix *matSubstraction(const Matrix *, const Matrix *, Matrix *); template Matrix *matMultiply(const Matrix *, const Matrix *, Matrix *); template Matrix *matNonZeroIndices(const Matrix *input, Basics::Matrix *dest); template int matCountEq(const Matrix *, ComplexF); template int matCountNeq(const Matrix *, ComplexF); template Matrix *matIndex(const Matrix *, int, const Matrix *); template Matrix *matIndex(const Matrix *, int, const Matrix *); template Matrix *matIndexedFill(Matrix *, int, const Matrix *, char); template Matrix *matIndexedFill(Matrix *, int, const Matrix *, char); template Matrix *matIndexedCopy(Matrix *, int, const Matrix *, const Matrix *); template Matrix *matIndexedCopy(Matrix *, int, const Matrix *, const Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matNonZeroIndices(const Matrix *input, Basics::Matrix *dest); template int matCountEq(const Matrix *, char); template int matCountNeq(const Matrix *, char); template Matrix *matIndex(const Matrix *, int, const Matrix *); template Matrix *matIndex(const Matrix *, int, const Matrix *); template Matrix *matIndexedFill(Matrix *, int, const Matrix *, int32_t); template Matrix *matIndexedFill(Matrix *, int, const Matrix *, int32_t); template Matrix *matIndexedCopy(Matrix *, int, const Matrix *, const Matrix *); template Matrix *matIndexedCopy(Matrix *, int, const Matrix *, const Matrix *); template Matrix *matOrder(const Matrix *, Matrix *); template Matrix *matOrderRank(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matNonZeroIndices(const Matrix *input, Basics::Matrix *dest); template Matrix *matAddition(const Matrix *, const Matrix *, Matrix *); template Matrix *matSubstraction(const Matrix *, const Matrix *, Matrix *); template int matCountEq(const Matrix *, int32_t); template int matCountNeq(const Matrix *, int32_t); template Matrix *matIndex(const Matrix *, int, const Matrix *); template Matrix *matIndex(const Matrix *, int, const Matrix *); template Matrix *matIndexedFill(Matrix *, int, const Matrix *, bool); template Matrix *matIndexedFill(Matrix *, int, const Matrix *, bool); template Matrix *matIndexedCopy(Matrix *, int, const Matrix *, const Matrix *); template Matrix *matIndexedCopy(Matrix *, int, const Matrix *, const Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matNonZeroIndices(const Matrix *input, Basics::Matrix *dest); template int matCountEq(const Matrix *, bool); template int matCountNeq(const Matrix *, bool); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); template Matrix *matConvertTo(const Matrix *, Matrix *); } // namespace Misc } // namespace MatrixExt } // namespace AprilMath april-ann-0.4.1/packages/basics/matrix/c_src/matrix_ext_misc.h000066400000000000000000000311351263004425400243670ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "matrix_ext.h" #include "swap.h" #ifndef MATRIX_EXT_MISC_H #define MATRIX_EXT_MISC_H namespace AprilMath { namespace MatrixExt { /** * @brief Miscellaneous operations for Matrix instances. * * This operations have been implemented using other matrix operations or * ad-hoc implementations. They are wrappers to perform usual computations. * * @see AprilMath::MatrixExt */ namespace Misc { //////////////////// OTHER MATH OPERATIONS //////////////////// /// To be called from Lua. Indices start at 1 instead of 0. template Basics::Matrix *matOrder(const Basics::Matrix *m, Basics::Matrix *dest = 0); /// To be called from Lua. Indices start at 1 instead of 0. template Basics::Matrix *matOrderRank(const Basics::Matrix *m, Basics::Matrix *dest = 0); /// Changes the order of matrix data over a given dimension. Returns a new allocated matrix. template Basics::Matrix *matIndex(const Basics::Matrix *m, int dim, const Basics::Matrix *idx); /// Changes the order of matrix data over a given dimension. Returns a new allocated matrix. template Basics::Matrix *matIndex(const Basics::Matrix *m, int dim, const Basics::Matrix *mask); /// Fills the given indices at the given dimension. Returns m. template Basics::Matrix *matIndexedFill(Basics::Matrix *m, int dim, const Basics::Matrix *idx, T val); /// Fills the given indices at the given dimension. Returns m. template Basics::Matrix *matIndexedFill(Basics::Matrix *m, int dim, const Basics::Matrix *mask, T val); /// Copies the given indices at the given dimension. Returns m. template Basics::Matrix *matIndexedCopy(Basics::Matrix *m, int dim, const Basics::Matrix *idx, const Basics::Matrix *other); /// Copies the given indices at the given dimension. Returns m. template Basics::Matrix *matIndexedCopy(Basics::Matrix *m, int dim, const Basics::Matrix *mask, const Basics::Matrix *other); /** * @brief Returns the result of \f$ C = A + B \f$ * * @note If the given @c c argument is 0, this operation allocates a * new destination matrix, otherwise uses the given matrix. */ template Basics::Matrix *matAddition(const Basics::Matrix *a, const Basics::Matrix *b, Basics::Matrix *c = 0); /** * @brief Returns the result of \f$ C = A - B \f$ * * @note If the given @c c argument is 0, this operation allocates a * new destination matrix, otherwise uses the given matrix. */ template Basics::Matrix *matSubstraction(const Basics::Matrix *a, const Basics::Matrix *b, Basics::Matrix *c = 0); /** * @brief Returns the result of \f$ C = A \times B \f$ * * This operation implements a generic multiplication which result * depends in the rank and shape of the given matrices. So, if * a vector and a column vector are given, the operation implements * an outer product. If two row vectors are given, the operation * implements inner product. If a vector and a matrix is given, it * implements matrix-vector product. If two matrices are given, the * operation implements matrix-matrix product. * * @note If the given @c c argument is 0, this operation allocates a * new destination matrix, otherwise uses the given matrix. */ template Basics::Matrix *matMultiply(const Basics::Matrix *a, const Basics::Matrix *b, Basics::Matrix *c = 0); /** * @brief Computes real FFT with Hamming window using a sliding window. * * This function uses the given @c wsize and @c wadvance parameters to * traverse the given matrix with a sliding window, and for every window * applies the Hamming filter and computes real FFT. The result is a * matrix with as many columns as FFT bins, and as many rows as windows. * * @param obj - the source matrix. * @param wsize - the source matrix. * @param wadvance - the source matrix. * @param obj - the source matrix. * * @result The given @c dest argument or a new allocated matrix if @c * dest=0 * * @see AprilMath::RealFFTwithHamming class. */ Basics::Matrix *matRealFFTwithHamming(Basics::Matrix *obj, int wsize, int wadvance, Basics::Matrix *dest=0); ///////////////////////////////////////////////////////////////////////// class BroadcastHelper { /// Computes the shape of the broadcast result matrix. static AprilUtils::UniquePtr resultShape(const int *a_dim, int Na, const int *b_dim, int Nb) { if (Na > Nb) { // make sure Na < Nb AprilUtils::swap(a_dim,b_dim); AprilUtils::swap(Na,Nb); } const int d = Nb - Na; // Na < Nb always here AprilUtils::UniquePtr shape = new int[Nb]; for (int i=0; i static void oneWayBroadcast(const OP &func, AprilUtils::SharedPtr > dest, const Basics::Matrix *other) { if (dest->sameDim(other)) { // particular case AprilUtils::SharedPtr< Basics::Matrix > out = func(dest.get(), other); if (out != dest) { BLAS::matCopy(dest.get(), out.get()); } } else { // general case AprilUtils::SharedPtr< Basics::Matrix > other_inflated; AprilUtils::SharedPtr< Basics::Matrix > dest_slice; if (dest->getNumDim() != other->getNumDim()) { // We need to leftInflate 'other' matrix and change other ptr other_inflated = other->leftInflate(dest->getNumDim() - other->getNumDim()); other = other_inflated.get(); } const int *other_dim = other->getDimPtr(); typename Basics::Matrix::sliding_window dest_sw(dest.get(), other_dim, // sub_matrix_size 0, // offset other_dim); // step while(!dest_sw.isEnd()) { dest_slice = dest_sw.getMatrix(dest_slice.get()); AprilUtils::SharedPtr< Basics::Matrix > out = func(dest_slice.get(), other); if (out.get() != dest_slice.get()) { BLAS::matCopy(dest_slice.get(), out.get()); } dest_sw.next(); } } // general case } template struct copyFunctor { Basics::Matrix *operator()(Basics::Matrix *dest, const Basics::Matrix *source) const { return BLAS::matCopy(dest, source); } }; public: /** * @see AprilMath::MatrixExt::Misc::matBroadcast */ template static AprilUtils::SharedPtr< Basics::Matrix > execute(const OP &func, const Basics::Matrix *a, const Basics::Matrix *b, AprilUtils::SharedPtr< Basics::Matrix > result = 0) { const int *a_dim = a->getDimPtr(), *b_dim = b->getDimPtr(); const int Na = a->getNumDim(), Nb = b->getNumDim(); const int N = AprilUtils::max(Na, Nb); AprilUtils::UniquePtr shape = resultShape(a_dim, Na, b_dim, Nb); if (result.empty()) { result = new Basics::Matrix(N, shape.get()); } else { if (!result->sameDim(shape.get(), N)) { ERROR_EXIT(128, "Incompatible shape in result matrix\n"); } } if (result == b) { oneWayBroadcast(func, result, a); } else if (result == a) { oneWayBroadcast(func, result, b); } else { oneWayBroadcast(copyFunctor(), result, a); oneWayBroadcast(func, result, b); } return result; } }; /** * @brief Similar to broadcasting in SciPy: * http://wiki.scipy.org/EricsBroadcastingDoc * * The operator is called as: @c out=func(a,b) where 'a' can be input and * output at the same time (no const), 'b' is always input data (const). * * @note Matrix *func(Matrix *a, const Matrix *b); */ template Basics::Matrix *matBroadcast(const OP &func, const Basics::Matrix *a, const Basics::Matrix *b, Basics::Matrix *result = 0) { AprilUtils::SharedPtr< Basics::Matrix > result_ref(result); result_ref = BroadcastHelper::execute(func, a, b, result_ref); return result_ref.weakRelease(); } /** * @brief Changes the type of a matrix instance. */ template Basics::Matrix *matConvertTo(const Basics::Matrix *input, Basics::Matrix *dest=0); /** * @brief Counts the number of values equals to the given parameter. */ template int matCountEq(const Basics::Matrix *input, T value); /** * @brief Counts the number of values not equals to the given parameter. */ template int matCountNeq(const Basics::Matrix *input, T value); /** * @brief Converts into MatrixInt32 with all non-zero indices. Indices * start a 1 instead of 0. */ template Basics::Matrix *matNonZeroIndices(const Basics::Matrix *input, Basics::Matrix *dest=0); } // namespace Misc } // namespace MatrixExt } // namespace AprilMath #include "matrix-conv.impl.h" #endif // MATRIX_EXT_MISC_H april-ann-0.4.1/packages/basics/matrix/c_src/matrix_ext_operations.cu000066400000000000000000001315771263004425400260120ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "cmath_overloads.h" #include "mathcore.h" #include "matrix.h" #include "maxmin.h" #include "realfftwithhamming.h" #include "smart_ptr.h" #include "sparse_matrix.h" // Must be defined in this order. #include "matrix_ext_operations.h" // Must to be defined here. #include "map_matrix.h" #include "map_sparse_matrix.h" // Must to be defined here. #include "reduce_matrix.h" #include "reduce_sparse_matrix.h" using Basics::Matrix; using Basics::SparseMatrix; namespace AprilMath { namespace MatrixExt { namespace Operations { template Matrix *matPlogp(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1 (obj, AprilMath::Functors::m_plogp(), dest); } template Matrix *matLog(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_log(), dest); } template Matrix *matLog1p(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_log1p(), dest); } template Matrix *matExp(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_exp(), dest); } template Matrix *matExpm1(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_expm1(), dest); } template Matrix *matSqrt(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_sqrt(), dest); } template SparseMatrix *matSqrt(const SparseMatrix *obj, SparseMatrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return SparseMatrixScalarMap1(obj, AprilMath::Functors::m_sqrt(), dest); } template Matrix *matPow(const Matrix *obj, const T &value, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, m_curried_pow(value), dest); } template SparseMatrix *matPow(const SparseMatrix *obj, const T &value, SparseMatrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return SparseMatrixScalarMap1(obj, m_curried_pow(value), dest); } template Matrix *matTan(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_tan(), dest); } template SparseMatrix *matTan(const SparseMatrix *obj, SparseMatrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return SparseMatrixScalarMap1(obj, AprilMath::Functors::m_tan(), dest); } template Matrix *matTanh(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_tanh(), dest); } template SparseMatrix *matTanh(const SparseMatrix *obj, SparseMatrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return SparseMatrixScalarMap1(obj, AprilMath::Functors::m_tanh(), dest); } template Matrix *matAtan(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_atan(), dest); } template SparseMatrix *matAtan(const SparseMatrix *obj, SparseMatrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return SparseMatrixScalarMap1(obj, AprilMath::Functors::m_atan(), dest); } template Matrix *matAtanh(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_atanh(), dest); } template SparseMatrix *matAtanh(const SparseMatrix *obj, SparseMatrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return SparseMatrixScalarMap1(obj, AprilMath::Functors::m_atanh(), dest); } template Matrix *matSin(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_sin(), dest); } template SparseMatrix *matSin(const SparseMatrix *obj, SparseMatrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return SparseMatrixScalarMap1(obj, AprilMath::Functors::m_sin(), dest); } template Matrix *matSinh(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_sinh(), dest); } template SparseMatrix *matSinh(const SparseMatrix *obj, SparseMatrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return SparseMatrixScalarMap1(obj, AprilMath::Functors::m_sinh(), dest); } template Matrix *matAsin(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_asin(), dest); } template SparseMatrix *matAsin(const SparseMatrix *obj, SparseMatrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return SparseMatrixScalarMap1(obj, AprilMath::Functors::m_asin(), dest); } template Matrix *matAsinh(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_asinh(), dest); } template SparseMatrix *matAsinh(const SparseMatrix *obj, SparseMatrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return SparseMatrixScalarMap1(obj, AprilMath::Functors::m_asinh(), dest); } template Matrix *matCos(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_cos(), dest); } template Matrix *matCosh(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_cosh(), dest); } template Matrix *matAcos(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_acos(), dest); } template Matrix *matAcosh(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_acosh(), dest); } template Matrix *matAbs(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_abs(), dest); } template SparseMatrix *matAbs(const SparseMatrix *obj, SparseMatrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return SparseMatrixScalarMap1(obj, AprilMath::Functors::m_abs(), dest); } template Matrix *matComplement(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_complement(), dest); } template Matrix *matSign(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_sign(), dest); } template SparseMatrix *matSign(const SparseMatrix *obj, SparseMatrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return SparseMatrixScalarMap1(obj, AprilMath::Functors::m_sign(), dest); } ////////////////// OTHER MAP FUNCTIONS ////////////////// /// Performs a clamp operation, in-place operation if @c dest=0, otherwise, /// the result will be computed at the given @c dest Matrix. template Matrix *matClamp(const Matrix *obj, const T lower, const T upper, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, m_curried_clamp(lower,upper), dest); } /// Performs a floor operation, in-place operation if @c dest=0, otherwise, /// the result will be computed at the given @c dest Matrix. template Matrix *matFloor(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_floor(), dest); } /// Performs a ceil operation, in-place operation if @c dest=0, otherwise, /// the result will be computed at the given @c dest Matrix. template Matrix *matCeil(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_ceil(), dest); } /// Performs a round operation, in-place operation if @c dest=0, otherwise, /// the result will be computed at the given @c dest Matrix. template Matrix *matRound(const Matrix *obj, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::Functors::m_round(), dest); } template Matrix *matScal(const Matrix *obj, const T value, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixSpanMap1(obj, CurriedScal(value), dest); } template SparseMatrix *matScal(const SparseMatrix *obj, const T value, SparseMatrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return SparseMatrixScalarMap1(obj, m_curried_mul(value), dest); } template Matrix *matCmul(const Matrix *obj, const Matrix *other, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap2(obj, other, AprilMath::Functors::m_mul(), dest); } template Matrix *matScalarAdd(const Matrix *obj, const T &v, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, m_curried_add(v), dest); } template Matrix *matAdjustRange(const Matrix *obj, const T &rmin, const T &rmax, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); T mmin, mmax; AprilMath::MatrixExt::Reductions::matMinAndMax(obj, mmin, mmax); // especial case, set all values to rmin if (mmax - mmin == T()) { AprilMath::MatrixExt::Initializers::matFill(dest, rmin); } else { const T ratio = (rmax-rmin)/(mmax-mmin); if (mmin > AprilMath::Limits::zero() || mmin < AprilMath::Limits::zero()) { matScalarAdd(obj, -mmin, dest); } AprilMath::MatrixExt::Operations::matScal(dest, ratio); if (rmin > AprilMath::Limits::zero() || rmin < AprilMath::Limits::zero()) { matScalarAdd(dest, rmin); } } return dest; } template Matrix *matDiv(const Matrix *obj, const T &value, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, m_curried_div(value), dest); } template Matrix *matIDiv(const Matrix *obj, const T &value, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, m_curried_idiv(value), dest); } template Basics::Matrix *matDiv(const Basics::Matrix *obj, const Basics::Matrix *other, Basics::Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap2(obj, other, AprilMath::Functors::m_div(), dest); } template SparseMatrix *matDiv(const SparseMatrix *obj, const T &value, SparseMatrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return SparseMatrixScalarMap1(obj, m_curried_div(value), dest); } template Matrix *matMod(const Matrix *obj, const T &value, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap1(obj, AprilMath::m_curried_mod(value), dest); } template Matrix *matMod(const Matrix *obj, const Basics::Matrix *other, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap2(obj, other, AprilMath::Functors::m_mod(), dest); } /// Curried masked fill operator. template struct maskedFillOp { const T value; ///< fill value. /// The constructor stores inf and sup values. maskedFillOp(const T &value) : value(value) { } /** * @brief Returns b ? value : a */ APRIL_CUDA_EXPORT T operator()(const T &a, const bool &b) const { return (b) ? (value) : (a); } }; template Matrix *matMaskedFill(const Matrix *obj, const Matrix *mask, const T &value, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap2(obj, mask, maskedFillOp(value), dest); } /// Curried masked copy operator. template struct maskedCopyOp { maskedCopyOp() { } /** * @brief Returns b ? c : a */ APRIL_CUDA_EXPORT T operator()(const T &a, const bool &b, const T &c) const { return (b) ? (c) : (a); } }; template Matrix *matMaskedCopy(const Matrix *obj1, const Matrix *mask, const Matrix *obj2, Matrix *dest) { april_assert( dest != 0 ); // TODO: sanity check, to be removed after checking all the code has // been updated with commit performed 2015/10/26 around 13:00 if (dest == 0) ERROR_EXIT(128, "Given a NULL destination matrix"); return MatrixScalarMap3(obj1, mask, obj2, maskedCopyOp(), dest); } //////////////// integer versions /////////////////// template <> Matrix *matScal(const Matrix *obj, const int32_t value, Matrix *dest) { april_assert( dest != 0 ); return MatrixScalarMap1(obj, AprilMath:: m_curried_mul(value), dest); } //////////////////////////////////////////////////// template Matrix *matPlogp(const Matrix *, Matrix *); template Matrix *matLog(const Matrix *, Matrix *); template Matrix *matLog1p(const Matrix *, Matrix *); template Matrix *matExp(const Matrix *, Matrix *); template Matrix *matExpm1(const Matrix *, Matrix *); template Matrix *matSqrt(const Matrix *, Matrix *); template Matrix *matPow(const Matrix *, const float &, Matrix *); template Matrix *matTan(const Matrix *, Matrix *); template Matrix *matTanh(const Matrix *, Matrix *); template Matrix *matAtan(const Matrix *, Matrix *); template Matrix *matAtanh(const Matrix *, Matrix *); template Matrix *matSin(const Matrix *, Matrix *); template Matrix *matSinh(const Matrix *, Matrix *); template Matrix *matAsin(const Matrix *, Matrix *); template Matrix *matAsinh(const Matrix *, Matrix *); template Matrix *matCos(const Matrix *, Matrix *); template Matrix *matCosh(const Matrix *, Matrix *); template Matrix *matAcos(const Matrix *, Matrix *); template Matrix *matAcosh(const Matrix *, Matrix *); template Matrix *matAbs(const Matrix *, Matrix *); template Matrix *matComplement(const Matrix *, Matrix *); template Matrix *matSign(const Matrix *, Matrix *); template Matrix *matClamp(const Matrix *, const float, const float, Matrix *); template Matrix *matFloor(const Matrix *, Matrix *); template Matrix *matCeil(const Matrix *, Matrix *); template Matrix *matRound(const Matrix *, Matrix *); template Matrix *matScal(const Matrix *, const float, Matrix *); template Matrix *matCmul(const Matrix *, const Matrix *, Matrix *); template Matrix *matScalarAdd(const Matrix *, const float &, Matrix *); template Matrix *matAdjustRange(const Matrix *, const float &, const float &, Matrix *); template Matrix *matDiv(const Matrix *, const float &, Matrix *); template Matrix *matDiv(const Matrix *, const Matrix *, Matrix *); template Matrix *matMaskedFill(const Matrix *, const Matrix *, const float &, Matrix *); template Matrix *matMaskedCopy(const Matrix *, const Matrix *, const Matrix *, Matrix *); template Matrix *matPlogp(const Matrix *, Matrix *); template Matrix *matLog(const Matrix *, Matrix *); template Matrix *matLog1p(const Matrix *, Matrix *); template Matrix *matExp(const Matrix *, Matrix *); template Matrix *matExpm1(const Matrix *, Matrix *); template Matrix *matSqrt(const Matrix *, Matrix *); template Matrix *matPow(const Matrix *, const double &, Matrix *); template Matrix *matTan(const Matrix *, Matrix *); template Matrix *matTanh(const Matrix *, Matrix *); template Matrix *matAtan(const Matrix *, Matrix *); template Matrix *matAtanh(const Matrix *, Matrix *); template Matrix *matSin(const Matrix *, Matrix *); template Matrix *matSinh(const Matrix *, Matrix *); template Matrix *matAsin(const Matrix *, Matrix *); template Matrix *matAsinh(const Matrix *, Matrix *); template Matrix *matCos(const Matrix *, Matrix *); template Matrix *matCosh(const Matrix *, Matrix *); template Matrix *matAcos(const Matrix *, Matrix *); template Matrix *matAcosh(const Matrix *, Matrix *); template Matrix *matAbs(const Matrix *, Matrix *); template Matrix *matComplement(const Matrix *, Matrix *); template Matrix *matSign(const Matrix *, Matrix *); template Matrix *matClamp(const Matrix *, const double, const double, Matrix *); template Matrix *matFloor(const Matrix *, Matrix *); template Matrix *matCeil(const Matrix *, Matrix *); template Matrix *matRound(const Matrix *, Matrix *); template Matrix *matScal(const Matrix *, const double, Matrix *); template Matrix *matCmul(const Matrix *, const Matrix *, Matrix *); template Matrix *matScalarAdd(const Matrix *, const double &, Matrix *); template Matrix *matAdjustRange(const Matrix *, const double &, const double &, Matrix *); template Matrix *matDiv(const Matrix *, const double &, Matrix *); template Matrix *matDiv(const Matrix *, const Matrix *, Matrix *); template Matrix *matMaskedFill(const Matrix *, const Matrix *, const double &, Matrix *); template Matrix *matMaskedCopy(const Matrix *, const Matrix *, const Matrix *, Matrix *); template Matrix *matScal(const Matrix *, const int32_t, Matrix *); template Matrix *matCmul(const Matrix *, const Matrix *, Matrix *); template Matrix *matClamp(const Matrix *, const int32_t, const int32_t, Matrix *); template Matrix *matScalarAdd(const Matrix *, const int32_t &, Matrix *); template Matrix *matIDiv(const Matrix *, const int32_t &, Matrix *); template Matrix *matDiv(const Matrix *, const Matrix *, Matrix *); template Matrix *matMod(const Matrix *, const Matrix *, Matrix *); template Matrix *matMod(const Matrix *, const int32_t &, Matrix *); template Matrix *matMaskedFill(const Matrix *, const Matrix *, const int32_t &, Matrix *); template Matrix *matMaskedCopy(const Matrix *, const Matrix *, const Matrix *, Matrix *); template Matrix *matMaskedFill(const Matrix *, const Matrix *, const char &, Matrix *); template Matrix *matMaskedCopy(const Matrix *, const Matrix *, const Matrix *, Matrix *); template Matrix *matMaskedFill(const Matrix *, const Matrix *, const bool &, Matrix *); template Matrix *matMaskedCopy(const Matrix *, const Matrix *, const Matrix *, Matrix *); template Matrix *matFloor(const Matrix *, Matrix *); template Matrix *matCeil(const Matrix *, Matrix *); template Matrix *matRound(const Matrix *, Matrix *); template Matrix *matScal(const Matrix *, const ComplexF, Matrix *); template Matrix *matCmul(const Matrix *, const Matrix *, Matrix *); template Matrix *matScalarAdd(const Matrix *, const ComplexF &, Matrix *); template Matrix *matDiv(const Matrix *, const ComplexF &, Matrix *); template Matrix *matDiv(const Matrix *, const Matrix *, Matrix *); template Matrix *matMaskedFill(const Matrix *, const Matrix *, const ComplexF &, Matrix *); template Matrix *matMaskedCopy(const Matrix *, const Matrix *, const Matrix *, Matrix *); template SparseMatrix *matSqrt(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matPow(const SparseMatrix *, const float &, SparseMatrix *); template SparseMatrix *matTan(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matAtan(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matTanh(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matAtanh(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matSin(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matAsin(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matSinh(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matAsinh(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matAbs(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matSign(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matScal(const SparseMatrix *, const float, SparseMatrix *); template SparseMatrix *matDiv(const SparseMatrix *, const float &, SparseMatrix *); template SparseMatrix *matScal(const SparseMatrix *, const ComplexF, SparseMatrix *); template SparseMatrix *matSqrt(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matPow(const SparseMatrix *, const double &, SparseMatrix *); template SparseMatrix *matTan(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matAtan(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matTanh(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matAtanh(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matSin(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matAsin(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matSinh(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matAsinh(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matAbs(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matSign(const SparseMatrix *, SparseMatrix *); template SparseMatrix *matScal(const SparseMatrix *, const double, SparseMatrix *); template SparseMatrix *matDiv(const SparseMatrix *, const double &, SparseMatrix *); } // namespace Operations } // namespace MatrixExt } // namespace AprilMath april-ann-0.4.1/packages/basics/matrix/c_src/matrix_ext_operations.h000066400000000000000000000573151263004425400256270ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "matrix_ext.h" #ifndef MATRIX_EXT_OPERATIONS_H #define MATRIX_EXT_OPERATIONS_H namespace AprilMath { namespace MatrixExt { ///////// BASIC MAP FUNCTIONS ///////// /** * @brief Valid operations over Matrix instances. They are wrappers over * generic functions defined at AprilMath::MatrixExt for map or reduce * operations using Matrix instances. * * This operations have been overloaded to be **in-place** or over a given * @c dest matrix. When given a destination matrix, it should be != 0. In * all cases, @c dest matrix is expected to be compatible with shape of @c * obj matrix. * * @note Most of these operations have been implemented using functions * defined in AprilMath and AprilMath::Functors. * * @see AprilMath::MatrixExt */ namespace Operations { /** * @brief Computes \f$ p \log p \f$ for every element of the given matrix. * * This function takes the values of the given matrix as probabilities, * so they have to be in the range \f$ [0,1] \f$. * * @note This operation has been optimized considering properly the case * of \f$ p=0 \f$. * * @see Operations namespace. */ template Basics::Matrix *matPlogp(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matPlogp(Basics::Matrix *obj) { return matPlogp(obj, obj); } /** * @brief Computes \f$ \log x \f$ for every element of the given matrix. */ template Basics::Matrix *matLog(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matLog(Basics::Matrix *obj) { return matLog(obj, obj); } /** * @brief Computes \f$ \log (1 + x) \f$ for every element of the given * matrix. */ template Basics::Matrix *matLog1p(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matLog1p(Basics::Matrix *obj) { return matLog1p(obj, obj); } /** * @brief Computes \f$ \exp x \f$ for every element of the given matrix. */ template Basics::Matrix *matExp(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matExp(Basics::Matrix *obj) { return matExp(obj, obj); } /** * @brief Computes \f$ \exp (x) - 1 \f$ for every element of the given * matrix. */ template Basics::Matrix *matExpm1(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matExpm1(Basics::Matrix *obj) { return matExpm1(obj, obj); } /** * @brief Computes \f$ \sqrt x \f$ for every element of the given matrix. */ template Basics::Matrix *matSqrt(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matSqrt(Basics::Matrix *obj) { return matSqrt(obj, obj); } /** * @brief Computes \f$ \sqrt x \f$ for every element of the given matrix. */ template Basics::SparseMatrix *matSqrt(const Basics::SparseMatrix *obj, Basics::SparseMatrix *dest); template Basics::SparseMatrix *matSqrt(Basics::SparseMatrix *obj) { return matSqrt(obj, obj); } /** * @brief Computes \f$ x^v \f$ for every element of the given matrix. */ template Basics::Matrix *matPow(const Basics::Matrix *obj, const T &value, Basics::Matrix *dest); template Basics::Matrix *matPow(Basics::Matrix *obj, const T &value) { return matPow(obj, value, obj); } /** * @brief Computes \f$ x^y \f$ for every element of the given matrix. */ template Basics::SparseMatrix *matPow(const Basics::SparseMatrix *obj, const T &value, Basics::SparseMatrix *dest); template Basics::SparseMatrix *matPow(Basics::SparseMatrix *obj, const T &value) { return matPow(obj, value, obj); } /** * @brief Computes \f$ tan(x) \f$ for every element of the given matrix. */ template Basics::Matrix *matTan(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matTan(Basics::Matrix *obj) { return matTan(obj, obj); } /** * @brief Computes \f$ tan(x) \f$ for every element of the given matrix. */ template Basics::SparseMatrix *matTan(const Basics::SparseMatrix *obj, Basics::SparseMatrix *dest); template Basics::SparseMatrix *matTan(Basics::SparseMatrix *obj) { return matTan(obj, obj); } /** * @brief Computes \f$ tanh(x) \f$ for every element of the given matrix. */ template Basics::Matrix *matTanh(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matTanh(Basics::Matrix *obj) { return matTanh(obj, obj); } /** * @brief Computes \f$ tanh(x) \f$ for every element of the given matrix. */ template Basics::SparseMatrix *matTanh(const Basics::SparseMatrix *obj, Basics::SparseMatrix *dest); template Basics::SparseMatrix *matTanh(Basics::SparseMatrix *obj) { return matTanh(obj, obj); } /** * @brief Computes \f$ atan(x) \f$ for every element of the given matrix. */ template Basics::Matrix *matAtan(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matAtan(Basics::Matrix *obj) { return matAtan(obj, obj); } /** * @brief Computes \f$ atan(x) \f$ for every element of the given matrix. */ template Basics::SparseMatrix *matAtan(const Basics::SparseMatrix *obj, Basics::SparseMatrix *dest); template Basics::SparseMatrix *matAtan(Basics::SparseMatrix *obj) { return matAtan(obj, obj); } /** * @brief Computes \f$ atanh(x) \f$ for every element of the given matrix. */ template Basics::Matrix *matAtanh(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matAtanh(Basics::Matrix *obj) { return matAtanh(obj, obj); } /** * @brief Computes \f$ atanh(x) \f$ for every element of the given matrix. */ template Basics::SparseMatrix *matAtanh(const Basics::SparseMatrix *obj, Basics::SparseMatrix *dest); template Basics::SparseMatrix *matAtanh(Basics::SparseMatrix *obj) { return matAtanh(obj, obj); } /** * @brief Computes \f$ sin(x) \f$ for every element of the given matrix. */ template Basics::Matrix *matSin(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matSin(Basics::Matrix *obj) { return matSin(obj, obj); } /** * @brief Computes \f$ sin(x) \f$ for every element of the given matrix. */ template Basics::SparseMatrix *matSin(const Basics::SparseMatrix *obj, Basics::SparseMatrix *dest); template Basics::SparseMatrix *matSin(Basics::SparseMatrix *obj) { return matSin(obj, obj); } /** * @brief Computes \f$ sinh(x) \f$ for every element of the given matrix. */ template Basics::Matrix *matSinh(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matSinh(Basics::Matrix *obj) { return matSinh(obj, obj); } /** * @brief Computes \f$ sinh(x) \f$ for every element of the given matrix. */ template Basics::SparseMatrix *matSinh(const Basics::SparseMatrix *obj, Basics::SparseMatrix *dest); template Basics::SparseMatrix *matSinh(Basics::SparseMatrix *obj) { return matSinh(obj, obj); } /** * @brief Computes \f$ asin(x) \f$ for every element of the given matrix. */ template Basics::Matrix *matAsin(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matAsin(Basics::Matrix *obj) { return matAsin(obj, obj); } /** * @brief Computes \f$ asin(x) \f$ for every element of the given matrix. */ template Basics::SparseMatrix *matAsin(const Basics::SparseMatrix *obj, Basics::SparseMatrix *dest); template Basics::SparseMatrix *matAsin(Basics::SparseMatrix *obj) { return matAsin(obj, obj); } /** * @brief Computes \f$ asinh(x) \f$ for every element of the given matrix. */ template Basics::Matrix *matAsinh(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matAsinh(Basics::Matrix *obj) { return matAsinh(obj, obj); } /** * @brief Computes \f$ asinh(x) \f$ for every element of the given matrix. */ template Basics::SparseMatrix *matAsinh(const Basics::SparseMatrix *obj, Basics::SparseMatrix *dest); template Basics::SparseMatrix *matAsinh(Basics::SparseMatrix *obj) { return matAsinh(obj, obj); } /** * @brief Computes \f$ cos(x) \f$ for every element of the given matrix. */ template Basics::Matrix *matCos(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matCos(Basics::Matrix *obj) { return matCos(obj, obj); } /** * @brief Computes \f$ cosh(x) \f$ for every element of the given matrix. */ template Basics::Matrix *matCosh(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matCosh(Basics::Matrix *obj) { return matCosh(obj, obj); } /** * @brief Computes \f$ acos(x) \f$ for every element of the given matrix. */ template Basics::Matrix *matAcos(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matAcos(Basics::Matrix *obj) { return matAcos(obj, obj); } /** * @brief Computes \f$ acosh(x) \f$ for every element of the given matrix. */ template Basics::Matrix *matAcosh(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matAcosh(Basics::Matrix *obj) { return matAcosh(obj, obj); } /** * @brief Computes \f$ abs(x) \f$ for every element of the given matrix. */ template Basics::Matrix *matAbs(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matAbs(Basics::Matrix *obj) { return matAbs(obj, obj); } /** * @brief Computes \f$ abs(x) \f$ for every element of the given matrix. */ template Basics::SparseMatrix *matAbs(const Basics::SparseMatrix *obj, Basics::SparseMatrix *dest); template Basics::SparseMatrix *matAbs(Basics::SparseMatrix *obj) { return matAbs(obj, obj); } /** * @brief Computes \f$ 1 - x \f$ for every element of the given matrix. */ template Basics::Matrix *matComplement(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matComplement(Basics::Matrix *obj) { return matComplement(obj, obj); } /** * @brief Computes \f$ \frac{x}{|x|} \f$ for every element of the given matrix. */ template Basics::Matrix *matSign(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matSign(Basics::Matrix *obj) { return matSign(obj, obj); } /** * @brief Computes \f$ \frac{x}{|x|} \f$ for every element of the given matrix. */ template Basics::SparseMatrix *matSign(const Basics::SparseMatrix *obj, Basics::SparseMatrix *dest); template Basics::SparseMatrix *matSign(Basics::SparseMatrix *obj) { return matSign(obj, obj); } ////////////////// OTHER MAP FUNCTIONS ////////////////// /** * @brief Computes \f$ \max(l, \min(u, x)) \f$ for every element of the * given matrix. */ template Basics::Matrix *matClamp(const Basics::Matrix *obj, const T lower, const T upper, Basics::Matrix *dest); template Basics::Matrix *matClamp(Basics::Matrix *obj, const T lower, const T upper) { return matClamp(obj, lower, upper, obj); } /** * @brief Computes \f$ floor(x) \f$ for every element of the * given matrix. */ template Basics::Matrix *matFloor(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matFloor(Basics::Matrix *obj) { return matFloor(obj, obj); } /** * @brief Computes \f$ ceil(x) \f$ for every element of the * given matrix. */ template Basics::Matrix *matCeil(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matCeil(Basics::Matrix *obj) { return matCeil(obj, obj); } /** * @brief Computes \f$ round(x) \f$ for every element of the * given matrix. */ template Basics::Matrix *matRound(const Basics::Matrix *obj, Basics::Matrix *dest); template Basics::Matrix *matRound(Basics::Matrix *obj) { return matRound(obj, obj); } /** * @brief Computes \f$ v \cdot x \f$ for every element of the given matrix. */ template Basics::Matrix *matScal(const Basics::Matrix *obj, const T value, Basics::Matrix *dest); template <> Basics::Matrix *matScal(const Basics::Matrix *obj, const int32_t value, Basics::Matrix *dest); template Basics::Matrix *matScal(Basics::Matrix *obj, const T value) { return matScal(obj, value, obj); } /** * @brief Computes \f$ v \cdot x \f$ for every element of the given matrix. */ template Basics::SparseMatrix *matScal(const Basics::SparseMatrix *obj, const T value, Basics::SparseMatrix *dest); template Basics::SparseMatrix *matScal(Basics::SparseMatrix *obj, const T value) { return matScal(obj, value, obj); } /** * @brief Computes component-wise multiplication of two matrices. */ template Basics::Matrix *matCmul(const Basics::Matrix *obj, const Basics::Matrix *other, Basics::Matrix *dest); template Basics::Matrix *matCmul(Basics::Matrix *obj, const Basics::Matrix *other) { return matCmul(obj, other, obj); } /** * @brief Computes \f$ x + v \f$ for every matrix element. */ template Basics::Matrix *matScalarAdd(const Basics::Matrix *obj, const T &v, Basics::Matrix *dest); template Basics::Matrix *matScalarAdd(Basics::Matrix *obj, const T &v) { return matScalarAdd(obj, v, obj); } /** * @brief Adjust linearly to a given range the values of the matrix. */ template Basics::Matrix *matAdjustRange(const Basics::Matrix *obj, const T &rmin, const T &rmax, Basics::Matrix *dest); template Basics::Matrix *matAdjustRange(Basics::Matrix *obj, const T &rmin, const T &rmax) { return matAdjustRange(obj, rmin, rmax, obj); } /** * @brief Computes \f$ \frac{v}{x} \f$ for every element x in the matrix. */ template Basics::Matrix *matDiv(const Basics::Matrix *obj, const T &value, Basics::Matrix *dest); template Basics::Matrix *matDiv(Basics::Matrix *obj, const T &value) { return matDiv(obj, value, obj); } /** * @brief Computes \f$ \frac{x}{v} \f$ for every element x in the matrix. */ template Basics::Matrix *matIDiv(const Basics::Matrix *obj, const T &value, Basics::Matrix *dest); template Basics::Matrix *matIDiv(Basics::Matrix *obj, const T &value) { return matIDiv(obj, value, obj); } /** * @brief Computes a component-wise division of two matrices. */ template Basics::Matrix *matDiv(const Basics::Matrix *obj, const Basics::Matrix *other, Basics::Matrix *dest); template Basics::Matrix *matDiv(Basics::Matrix *obj, const Basics::Matrix *other) { return matDiv(obj, other, obj); } /** * @brief Computes \f$ \frac{v}{x} \f$ for every element x in the matrix. */ template Basics::SparseMatrix *matDiv(const Basics::SparseMatrix *obj, const T &value, Basics::SparseMatrix *dest); template Basics::SparseMatrix *matDiv(Basics::SparseMatrix *obj, const T &value) { return matDiv(obj, value, obj); } /** * @brief Computes a component-wise mod operation of two matrices. */ template Basics::Matrix *matMod(const Basics::Matrix *obj, const Basics::Matrix *other, Basics::Matrix *dest); template Basics::Matrix *matMod(Basics::Matrix *obj, const Basics::Matrix *other) { return matMod(obj, other, obj); } /** * @brief Computes \f$ x % v \f$ for every element x in the matrix. */ template Basics::Matrix *matMod(const Basics::Matrix *obj, const T &value, Basics::Matrix *dest); template Basics::Matrix *matMod(Basics::Matrix *obj, const T &value) { return matMod(obj, value, obj); } /** * @brief Computes matrix fill using a given mask matrix. */ template Basics::Matrix *matMaskedFill(const Basics::Matrix *obj, const Basics::Matrix *mask, const T &value, Basics::Matrix *dest); template Basics::Matrix *matMaskedFill(Basics::Matrix *obj, const Basics::Matrix *mask, const T &value) { return matMaskedFill(obj, mask, value, obj); } /** * @brief Computes matrix copy using a given mask matrix. */ template Basics::Matrix *matMaskedCopy(const Basics::Matrix *obj1, const Basics::Matrix *mask, const Basics::Matrix *obj2, Basics::Matrix *dest); template Basics::Matrix *matMaskedCopy(Basics::Matrix *obj1, const Basics::Matrix *mask, const Basics::Matrix *obj2) { return matMaskedCopy(obj1, mask, obj2, obj1); } } // namespace Operations } // namespace MatrixExt } // namespace AprilMath #endif // MATRIX_EXT_OPERATIONS_H april-ann-0.4.1/packages/basics/matrix/c_src/matrix_ext_reductions.cu000066400000000000000000001033111263004425400257670ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "cmath_overloads.h" #include "mathcore.h" #include "matrix.h" #include "maxmin.h" #include "realfftwithhamming.h" #include "smart_ptr.h" #include "sparse_matrix.h" // Must be defined in this order. #include "matrix_ext_reductions.h" // Must to be defined here. #include "map_matrix.h" #include "map_sparse_matrix.h" // Must to be defined here. #include "reduce_matrix.h" #include "reduce_sparse_matrix.h" using Basics::Matrix; using Basics::SparseMatrix; namespace AprilMath { namespace MatrixExt { namespace Reductions { /////////////////// MAX MIN REDUCTIONS /////////////////// // Min and max over given dimension, be careful, argmin and argmax matrices // contains the min/max index at the given dimension, but starting in 1 (not // in 0) template Matrix *matMin(const Matrix *obj, int dim, Matrix *dest, Matrix *argmin) { if (argmin == 0) { return MatrixScalarReduce1OverDimension(obj, dim, AprilMath::Functors::r_min(), AprilMath::Functors::r_min(), Limits::infinity(), dest); } else { return MatrixScalarReduceMinMaxOverDimension(obj, dim, AprilMath::Functors::r_min2(), Limits::infinity(), argmin, dest); } } // TODO: use a wrapper for GPU/CPU template Matrix *matMin(const SparseMatrix *obj, int dim, Matrix *dest, Matrix *argmin) { AprilUtils::SharedPtr< Matrix > aux; if (dim != 0 && dim != 1) { ERROR_EXIT1(128, "Incorrect given dimension %d\n", dim); } int ndim = (dim==0)?(1):(0); if (dest) { if (dest->getDimSize(dim) != 1 || dest->getDimSize(ndim) != obj->getDimSize(ndim)) { ERROR_EXIT(128, "Incorrect matrix sizes\n"); } } else { int result_dims[2] = { obj->getDimSize(0), obj->getDimSize(1) }; result_dims[dim] = 1; aux = dest = new Matrix(1, result_dims); } if (argmin) { if (argmin->getDimSize(dim) != 1 || argmin->getDimSize(ndim) != obj->getDimSize(ndim)) { ERROR_EXIT(128, "Incorrect matrix sizes\n"); } AprilMath::MatrixExt::Initializers::matZeros(argmin); } AprilMath::MatrixExt::Initializers::matZeros(dest); typename Matrix::random_access_iterator dest_it(dest); int aux_dims[2] = { 0, 0 }; if (argmin == 0) { for (typename SparseMatrix::const_iterator it(obj->begin()); it!=obj->end(); ++it) { int coords[2]; it.getCoords(coords[0],coords[1]); aux_dims[ndim] = coords[ndim]; dest_it(aux_dims[0],aux_dims[1]) = AprilUtils::min(dest_it(aux_dims[0],aux_dims[1]),(*it)); } } else { typename Matrix::random_access_iterator argmin_it(argmin); for (typename SparseMatrix::const_iterator it(obj->begin()); it!=obj->end(); ++it) { int coords[2]; it.getCoords(coords[0],coords[1]); aux_dims[ndim] = coords[ndim]; if (*it < dest_it(aux_dims[0],aux_dims[1])) { dest_it(aux_dims[0],aux_dims[1]) = *it; argmin_it(aux_dims[0],aux_dims[1]) = aux_dims[ndim]; } } } aux.weakRelease(); return dest; } template Matrix *matMax(const Matrix *obj, int dim, Matrix *dest, Matrix *argmax) { if (argmax == 0) { return MatrixScalarReduce1OverDimension(obj, dim, AprilMath::Functors::r_max(), AprilMath::Functors::r_max(), -Limits::infinity(), dest); } else { return MatrixScalarReduceMinMaxOverDimension(obj, dim, AprilMath::Functors::r_max2(), -Limits::infinity(), argmax, dest); } } // TODO: use a wrapper for GPU/CPU template Matrix *matMax(const SparseMatrix *obj, int dim, Matrix *dest, Matrix *argmax) { AprilUtils::SharedPtr< Matrix > aux; if (dim != 0 && dim != 1) { ERROR_EXIT1(128, "Incorrect given dimension %d\n", dim); } int ndim = (dim==0)?(1):(0); if (dest) { if (dest->getDimSize(dim) != 1 || dest->getDimSize(ndim) != obj->getDimSize(ndim)) { ERROR_EXIT(128, "Incorrect matrix sizes\n"); } } else { int result_dims[2] = { obj->getDimSize(0), obj->getDimSize(1) }; result_dims[dim] = 1; aux = dest = new Matrix(1, result_dims); } if (argmax) { if (argmax->getDimSize(dim) != 1 || argmax->getDimSize(ndim) != obj->getDimSize(ndim)) { ERROR_EXIT(128, "Incorrect matrix sizes\n"); } AprilMath::MatrixExt::Initializers::matZeros(argmax); } AprilMath::MatrixExt::Initializers::matZeros(dest); typename Matrix::random_access_iterator dest_it(dest); int aux_dims[2] = { 0, 0 }; if (argmax == 0) { for (typename SparseMatrix::const_iterator it(obj->begin()); it!=obj->end(); ++it) { int coords[2]; it.getCoords(coords[0],coords[1]); aux_dims[ndim] = coords[ndim]; dest_it(aux_dims[0],aux_dims[1]) = AprilUtils::max(dest_it(aux_dims[0],aux_dims[1]),(*it)); } } else { typename Matrix::random_access_iterator argmax_it(argmax); for (typename SparseMatrix::const_iterator it(obj->begin()); it!=obj->end(); ++it) { int coords[2]; it.getCoords(coords[0],coords[1]); aux_dims[ndim] = coords[ndim]; if (dest_it(aux_dims[0],aux_dims[1]) < *it) { dest_it(aux_dims[0],aux_dims[1]) = *it; argmax_it(aux_dims[0],aux_dims[1]) = aux_dims[ndim]; } } } aux.weakRelease(); return dest; } // FIXME: using WRAPPER template T matMin(const Matrix *obj, int &arg_min, int &arg_min_raw_pos) { typename Matrix::const_iterator it(obj->begin()); typename Matrix::const_iterator result = AprilUtils::argmin(it, typename Matrix::const_iterator(obj->end())); arg_min = result.getIdx(); arg_min_raw_pos = result.getRawPos(); return *result; } // FIXME: using WRAPPER template T matMin(const SparseMatrix *obj, int &c0, int &c1) { typename SparseMatrix::const_iterator it = AprilUtils::argmin(obj->begin(),obj->end()); it.getCoords(c0,c1); return *it; } // FIXME: using WRAPPER template T matMax(const Matrix *obj, int &arg_max, int &arg_max_raw_pos) { typename Matrix::const_iterator it(obj->begin()); typename Matrix::const_iterator result = AprilUtils::argmax(it, typename Matrix::const_iterator(obj->end())); arg_max = result.getIdx(); arg_max_raw_pos = result.getRawPos(); return *result; } // FIXME: using WRAPPER template T matMax(const SparseMatrix *obj, int &c0, int &c1) { typename SparseMatrix::const_iterator it = AprilUtils::argmax(obj->begin(),obj->end()); it.getCoords(c0,c1); return *it; } // FIXME: using WRAPPER template void matMinAndMax(const Matrix *obj, T &min, T &max) { typename Matrix::const_iterator it(obj->begin()); min = *it; max = *it; for (; it!=obj->end(); ++it) { if (*it < min) min = *it; if (*it > max) max = *it; } } template void matMinAndMax(const SparseMatrix *obj, T &min, T &max) { typename SparseMatrix::const_iterator it(obj->begin()); min = max = *it; ++it; for (; it != obj->end(); ++it) { if ( max < (*it) ) max = *it; else if ( (*it) < min ) min = *it; } } template Matrix *matMaxSelDim(const Matrix *obj, const int dim, Int32GPUMirroredMemoryBlock *raw_positions, const int shift, Matrix *result) { AprilUtils::SharedPtr< Matrix > aux; if (dim < 0 || dim > obj->getNumDim()) { ERROR_EXIT2(128, "Incorrect dimension %d, numDim=%d\n", dim, obj->getNumDim()); } if (result == 0) { aux = result = new Matrix(1, obj->getDimSize(dim)); } else { if (result->size()!=obj->getDimSize(dim) || result->getNumDim()!=1) { ERROR_EXIT1(128, "Incorrect result matrix size, " "expected unidimensional matrix with size %d\n", obj->getDimSize(dim)); } } #ifdef USE_CUDA result->setUseCuda(obj->getCudaFlag()); #endif int *argmax = 0; if (raw_positions != 0) { argmax = raw_positions->getPPALForWrite() + shift; } switch(obj->getNumDim()) { case 1: ERROR_EXIT(128, "Impossible to compute maxSelDim when numDim=1\n"); break; case 2: { const int other_dim = 1 - dim; T *res_ptr = result->getRawDataAccess()->getPPALForWrite(); const T *src_ptr = obj->getRawDataAccess()->getPPALForRead(); for (int i=0; igetDimSize(dim); ++i, ++res_ptr) { int current_raw_pos = obj->getOffset() + i*obj->getStrideSize(dim); int raw_pos_max = current_raw_pos; *res_ptr = src_ptr[current_raw_pos]; current_raw_pos += obj->getStrideSize(other_dim); for (int j=1; jgetDimSize(other_dim); ++j, current_raw_pos += obj->getStrideSize(other_dim)) { if (src_ptr[current_raw_pos] > *res_ptr) { *res_ptr = src_ptr[current_raw_pos]; raw_pos_max = current_raw_pos; } } if (argmax) argmax[i] = raw_pos_max; } break; } case 3: { int other_dim1 = (dim+1)%3; int other_dim2 = (dim+2)%3; if (other_dim2 < other_dim1) { AprilUtils::swap(other_dim1, other_dim2); } T *res_ptr = result->getRawDataAccess()->getPPALForWrite(); const T *src_ptr = obj->getRawDataAccess()->getPPALForRead(); for (int i=0; igetDimSize(dim); ++i, ++res_ptr) { int raw_pos_max = i*obj->getStrideSize(dim) + obj->getOffset(); *res_ptr = src_ptr[raw_pos_max]; for (int j=0; jgetDimSize(other_dim1); ++j) { int current_raw_pos = obj->getOffset() + i*obj->getStrideSize(dim) + j*obj->getStrideSize(other_dim1); for (int k=0; kgetDimSize(other_dim2); ++k, current_raw_pos += obj->getStrideSize(other_dim2)) { if (src_ptr[current_raw_pos] > *res_ptr) { *res_ptr = src_ptr[current_raw_pos]; raw_pos_max = current_raw_pos; } } } if (argmax) argmax[i] = raw_pos_max; } break; } case 4: { int other_dim1 = (dim+1)%4; int other_dim2 = (dim+2)%4; int other_dim3 = (dim+3)%4; if (other_dim1 > other_dim2) AprilUtils::swap(other_dim1, other_dim2); if (other_dim2 > other_dim3) { AprilUtils::swap(other_dim2, other_dim3); if (other_dim1 > other_dim2) AprilUtils::swap(other_dim1, other_dim2); } T *res_ptr = result->getRawDataAccess()->getPPALForWrite(); const T *src_ptr = obj->getRawDataAccess()->getPPALForRead(); for (int i=0; igetDimSize(dim); ++i, ++res_ptr) { int raw_pos_max = i*obj->getStrideSize(dim) + obj->getOffset(); *res_ptr = src_ptr[raw_pos_max]; for (int j=0; jgetDimSize(other_dim1); ++j) { for (int k=0; kgetDimSize(other_dim2); ++k) { int current_raw_pos=obj->getOffset()+i*obj->getStrideSize(dim)+j*obj->getStrideSize(other_dim1)+k*obj->getStrideSize(other_dim2); for (int k2=0; k2getDimSize(other_dim3); ++k2, current_raw_pos += obj->getStrideSize(other_dim3)) { if (src_ptr[current_raw_pos] > *res_ptr) { *res_ptr = src_ptr[current_raw_pos]; raw_pos_max = current_raw_pos; } } } } if (argmax) argmax[i] = raw_pos_max; } break; } default: { T *res_ptr = result->getRawDataAccess()->getPPALForWrite(); for (int i=0; igetDimSize(dim); ++i, ++res_ptr) { int aux, argmax_raw_pos; AprilUtils::SharedPtr< Matrix > current( const_cast*>(obj)->select(dim, i) ); matMax(current.get(), aux, argmax_raw_pos); if (argmax) argmax[i] = argmax_raw_pos; } } } aux.weakRelease(); return result; } template T matSum(const Matrix *obj) { return MatrixSpanSumReduce1(obj, ScalarToSpanReduce1< T, T, AprilMath::Functors::r_add > (AprilMath::Functors::r_add())); } template <> ComplexF matSum(const Matrix *obj) { return MatrixScalarReduce1(obj, AprilMath::Functors::r_add(), AprilMath::Functors::r_add(), ComplexF(0.0f,0.0f)); } template T matSum(const SparseMatrix *obj) { return SparseMatrixScalarReduce1(obj, AprilMath::Functors::r_add(), AprilMath::Limits::zero()); } template Matrix *matSum(Matrix *obj, int dim, Matrix *dest, bool accumulated) { return MatrixScalarReduce1OverDimension(obj, dim, AprilMath::Functors::r_add(), AprilMath::Functors::r_add(), AprilMath::Limits::zero(), dest, !accumulated); } // TODO: Implement using a wrapper for GPU/CPU computation. template Matrix *matSum(const SparseMatrix *obj, int dim, Matrix *dest, bool accumulated) { AprilUtils::SharedPtr< Matrix > aux; if (dim != 0 && dim != 1) { ERROR_EXIT1(128, "Incorrect given dimension %d\n", dim); } int ndim = (dim==0)?(1):(0); if (dest) { if (dest->getDimSize(dim) != 1 || dest->getDimSize(ndim) != obj->getDimSize(ndim)) { ERROR_EXIT(128, "Incorrect matrix sizes\n"); } if (!accumulated) { AprilMath::MatrixExt::Initializers::matZeros(dest); } } else { int result_dims[2] = { obj->getDimSize(0), obj->getDimSize(1) }; result_dims[dim] = 1; aux = dest = new Matrix(1, result_dims); AprilMath::MatrixExt::Initializers::matZeros(dest); } typename Matrix::random_access_iterator dest_it(dest); int aux_dims[2] = { 0, 0 }; for (typename SparseMatrix::const_iterator it(obj->begin()); it!=obj->end(); ++it) { int coords[2]; it.getCoords(coords[0],coords[1]); aux_dims[ndim] = coords[ndim]; dest_it(aux_dims[0],aux_dims[1]) += (*it); } aux.weakRelease(); return dest; } template T matProd(const Matrix *obj) { return MatrixSpanProdReduce1(obj, ScalarToSpanReduce1< T, T, AprilMath::Functors::r_mul > (AprilMath::Functors::r_mul())); } template <> ComplexF matProd(const Matrix *obj) { return MatrixScalarReduce1(obj, AprilMath::Functors::r_mul(), AprilMath::Functors::r_mul(), AprilMath::Limits::one()); } template Matrix *matProd(Matrix *obj, int dim, Matrix *dest) { return MatrixScalarReduce1OverDimension(obj, dim, AprilMath::Functors::r_mul(), AprilMath::Functors::r_mul(), AprilMath::Limits::one(), dest, true); } template Basics::Matrix *matCumSum(Basics::Matrix *obj, int dim, Basics::Matrix *dest) { AprilUtils::SharedPtr< Matrix > aux; if (dest) { if (!dest->sameDim(obj)) ERROR_EXIT(128, "Incorrect matrix sizes\n"); } else { aux = dest = obj->cloneOnlyDims(); } if (obj->getNumDim() == 1) { T agg = AprilMath::Limits::zero(); typename Matrix::const_iterator obj_it = obj->begin(); typename Matrix::iterator dst_it = dest->begin(); while(obj_it != obj->end()) { april_assert( dst_it != dest->end() ); agg += *obj_it; *dst_it = agg; ++obj_it; ++dst_it; } } else { AprilUtils::SharedPtr< Matrix > obj_slice, dst_slice; AprilUtils::SharedPtr< Matrix > agg = obj->select(dim, 0); agg = AprilMath::MatrixExt::Initializers::matZeros(agg->cloneOnlyDims()); for (int i=0; igetDimSize(dim); ++i) { obj_slice = obj->select(dim, i, obj_slice.get()); dst_slice = dest->select(dim, i, dst_slice.get()); AprilMath::MatrixExt::BLAS:: matAxpy(agg.get(), AprilMath::Limits::one(), obj_slice.get()); AprilMath::MatrixExt::BLAS:: matCopy(dst_slice.get(), agg.get()); } } aux.weakRelease(); return dest; } template Basics::Matrix *matCumProd(Basics::Matrix *obj, int dim, Basics::Matrix *dest) { AprilUtils::SharedPtr< Matrix > aux; if (dest) { if (!dest->sameDim(obj)) ERROR_EXIT(128, "Incorrect matrix sizes\n"); } else { aux = dest = obj->cloneOnlyDims(); } if (obj->getNumDim() == 1) { T agg = AprilMath::Limits::one(); typename Matrix::const_iterator obj_it = obj->begin(); typename Matrix::iterator dst_it = dest->begin(); while(obj_it != obj->end()) { april_assert( dst_it != dest->end() ); agg *= *obj_it; *dst_it = agg; ++obj_it; ++dst_it; } } else { AprilUtils::SharedPtr< Matrix > obj_slice, dst_slice; AprilUtils::SharedPtr< Matrix > agg = obj->select(dim, 0); agg = AprilMath::MatrixExt::Initializers::matOnes(agg->cloneOnlyDims()); for (int i=0; igetDimSize(dim); ++i) { obj_slice = obj->select(dim, i, obj_slice.get()); dst_slice = dest->select(dim, i, dst_slice.get()); AprilMath::MatrixExt::Operations:: matCmul(agg.get(), obj_slice.get()); AprilMath::MatrixExt::BLAS:: matCopy(dst_slice.get(), agg.get()); } } aux.weakRelease(); return dest; } /**** COMPONENT WISE OPERATIONS ****/ template bool matEquals(const Matrix *a, const Matrix *b, float epsilon) { if (!a->sameDim(b)) return false; typename Matrix::const_iterator a_it(a->begin()); typename Matrix::const_iterator b_it(b->begin()); while(a_it != a->end() && b_it != b->end()) { if (!m_relative_equals(*a_it, *b_it, epsilon)) { return false; } ++a_it; ++b_it; } if (a_it == a->end() && b_it == b->end()) { return true; } else { return false; } } template bool matEquals(const SparseMatrix *a, const SparseMatrix *b, float epsilon) { if (!a->sameDim(b)) return false; typename SparseMatrix::const_iterator a_it(a->begin()); typename SparseMatrix::const_iterator b_it(b->begin()); while(a_it != a->end() && b_it != b->end()) { int a_c0, a_c1, b_c0, b_c1; a_it.getCoords(a_c0, a_c1); b_it.getCoords(b_c0, b_c1); if (a_c0 != b_c0 || a_c1 != b_c1 || !m_relative_equals(*a_it, *b_it, epsilon)) return false; ++a_it; ++b_it; } if (a_it != a->end() || b_it != b->end()) return false; return true; } template bool matIsFinite(const Matrix *obj) { return MatrixScalarReduce1(obj, AprilMath::make_r_map1 (AprilMath::Functors::m_is_finite(), AprilMath::Functors::r_and()), AprilMath::Functors::r_and(), true); } template Matrix *matMin(const Matrix *, int, Matrix *, Matrix *); template Matrix *matMax(const Matrix *, int, Matrix *, Matrix *); template float matMin(const Matrix *, int &, int &); template float matMax(const Matrix *, int &, int &); template void matMinAndMax(const Matrix *, float &, float &); template Matrix *matMaxSelDim(const Matrix *, const int, Int32GPUMirroredMemoryBlock *, const int, Basics::Matrix *); template float matSum(const Matrix *); template Matrix *matSum(Matrix *, int, Matrix *, bool); template float matProd(const Matrix *); template Matrix *matProd(Matrix *, int, Matrix *); template Matrix *matCumSum(Matrix *, int, Matrix *); template Matrix *matCumProd(Matrix *, int, Matrix *); template bool matEquals(const Matrix *, const Matrix *, float); template bool matIsFinite(const Matrix *); template Matrix *matMin(const Matrix *, int, Matrix *, Matrix *); template Matrix *matMax(const Matrix *, int, Matrix *, Matrix *); template double matMin(const Matrix *, int &, int &); template double matMax(const Matrix *, int &, int &); template void matMinAndMax(const Matrix *, double &, double &); template Matrix *matMaxSelDim(const Matrix *, const int, Int32GPUMirroredMemoryBlock *, const int, Basics::Matrix *); template double matSum(const Matrix *); template Matrix *matSum(Matrix *, int, Matrix *, bool); template double matProd(const Matrix *); template Matrix *matProd(Matrix *, int, Matrix *); template Matrix *matCumSum(Matrix *, int, Matrix *); template Matrix *matCumProd(Matrix *, int, Matrix *); template bool matEquals(const Matrix *, const Matrix *, float); template bool matIsFinite(const Matrix *); template Matrix *matMin(const SparseMatrix *, int , Matrix *, Matrix *); template Matrix *matMax(const SparseMatrix *, int, Matrix *, Matrix *); template float matMin(const SparseMatrix *, int &, int &); template float matMax(const SparseMatrix *, int &, int &); template void matMinAndMax(const SparseMatrix *, float &, float &); template float matSum(const SparseMatrix *); template Matrix *matSum(const SparseMatrix *, int, Matrix *, bool); template bool matEquals(const SparseMatrix *, const SparseMatrix *, float); template bool matEquals(const SparseMatrix *, const SparseMatrix *, float); template Matrix *matMin(const SparseMatrix *, int , Matrix *, Matrix *); template Matrix *matMax(const SparseMatrix *, int, Matrix *, Matrix *); template double matMin(const SparseMatrix *, int &, int &); template double matMax(const SparseMatrix *, int &, int &); template void matMinAndMax(const SparseMatrix *, double &, double &); template double matSum(const SparseMatrix *); template Matrix *matSum(const SparseMatrix *, int, Matrix *, bool); template bool matEquals(const SparseMatrix *, const SparseMatrix *, float); template ComplexF matSum(const Matrix *); template Matrix *matSum(Matrix *, int, Matrix *, bool); template ComplexF matProd(const Matrix *); template Matrix *matProd(Matrix *, int, Matrix *); template Matrix *matCumSum(Matrix *, int, Matrix *); template Matrix *matCumProd(Matrix *, int, Matrix *); template bool matEquals(const Matrix *, const Matrix *, float); template bool matIsFinite(const Matrix *); template Matrix *matMin(const SparseMatrix *, int , Matrix *, Matrix *); template Matrix *matMax(const SparseMatrix *, int, Matrix *, Matrix *); template int32_t matMin(const SparseMatrix *, int &, int &); template int32_t matMax(const SparseMatrix *, int &, int &); template Matrix *matMin(const Matrix *, int, Matrix *, Matrix *); template Matrix *matMax(const Matrix *, int, Matrix *, Matrix *); template int32_t matMin(const Matrix *, int &, int &); template int32_t matMax(const Matrix *, int &, int &); template void matMinAndMax(const Matrix *, int32_t &, int32_t &); template Matrix *matMaxSelDim(const Matrix *, const int, Int32GPUMirroredMemoryBlock *, const int, Basics::Matrix *); template int32_t matSum(const Matrix *); template Matrix *matSum(Matrix *, int, Matrix *, bool); template int32_t matProd(const Matrix *); template Matrix *matProd(Matrix *, int, Matrix *); template Matrix *matCumSum(Matrix *, int, Matrix *); template Matrix *matCumProd(Matrix *, int, Matrix *); template bool matEquals(const Matrix *, const Matrix *, float); template bool matEquals(const Matrix *, const Matrix *, float); template bool matEquals(const Matrix *, const Matrix *, float); } // namespace Reductions } // namespace MatrixExt } // namespace AprilMath april-ann-0.4.1/packages/basics/matrix/c_src/matrix_ext_reductions.h000066400000000000000000000262371263004425400256220ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "matrix_ext.h" #ifndef MATRIX_EXT_REDUCTIONS_H #define MATRIX_EXT_REDUCTIONS_H namespace AprilMath { namespace MatrixExt { /** * @brief Reduction operations for Matrix instances. * * @see AprilMath::MatrixExt */ namespace Reductions { /////////////////// MAX MIN REDUCTIONS /////////////////// // Min and max over given dimension, be careful, argmin and argmax matrices // contains the min/max index at the given dimension, but starting in 1 (not // in 0) /** * @brief Min reduction over a given dimension number. * * @param obj - The source matrix object. * @param dim - The dimension (a value between 0 and @c obj->getNumDim() * @param dest - The destination matrix, if it is 0, a new matrix would be allocated. * @param argmin - A matrix with the position of the minimums, if not given, it won't be used. * * @result The given @c dest argument or a new allocated matrix with the min values. */ template Basics::Matrix *matMin(const Basics::Matrix *obj, int dim, Basics::Matrix *dest=0, Basics::Matrix *argmin=0); // TODO: use a wrapper for GPU/CPU /** * @brief Min reduction over a given dimension number. * * @param obj - The source matrix object. * @param dim - The dimension (a value between 0 and @c obj->getNumDim() * @param dest - The destination matrix, if it is 0, a new matrix would be allocated. * @param argmin - A matrix with the position of the minimums, if not given, it won't be used. * * @result The given @c dest argument or a new allocated matrix with the min values. */ template Basics::Matrix *matMin(const Basics::SparseMatrix *obj, int dim, Basics::Matrix *dest=0, Basics::Matrix *argmin=0); /** * @brief Max reduction over a given dimension number. * * @param obj - The source matrix object. * @param dim - The dimension (a value between 0 and @c obj->getNumDim() * @param dest - The destination matrix, if it is 0, a new matrix would be allocated. * @param argmax - A matrix with the position of the maximums, if not given, it won't be used. * * @result The given @c dest argument or a new allocated matrix with the min values. */ template Basics::Matrix *matMax(const Basics::Matrix *obj, int dim, Basics::Matrix *dest=0, Basics::Matrix *argmax=0); // TODO: use a wrapper for GPU/CPU /** * @brief Max reduction over a given dimension number. * * @param obj - The source matrix object. * @param dim - The dimension (a value between 0 and @c obj->getNumDim() * @param dest - The destination matrix, if it is 0, a new matrix would be allocated. * @param argmax - A matrix with the position of the maximums, if not given, it won't be used. * * @result The given @c dest argument or a new allocated matrix with the min values. */ template Basics::Matrix *matMax(const Basics::SparseMatrix *obj, int dim, Basics::Matrix *dest=0, Basics::Matrix *argmax=0); // FIXME: using WRAPPER template T matMin(const Basics::Matrix *obj, int &arg_min, int &arg_min_raw_pos); // FIXME: using WRAPPER template T matMin(const Basics::SparseMatrix *obj, int &c0, int &c1); // FIXME: using WRAPPER /** * @brief Max reduction over the whole matrix. * * @param obj - The source matrix object. * @param arg_max - The index value of the element in the matrix. * @param arg_max_raw_pos - The index value of the element in the memory block. * * @result The max value. */ template T matMax(const Basics::Matrix *obj, int &arg_max, int &arg_max_raw_pos); // FIXME: using WRAPPER /** * @brief Max reduction over the whole matrix. * * @param obj - The source matrix object. * @param c0 - The index in dimension 0. * @param c1 - The index in dimension 1. * * @result The max value. */ template T matMax(const Basics::SparseMatrix *obj, int &c0, int &c1); // FIXME: using WRAPPER template void matMinAndMax(const Basics::Matrix *obj, T &min, T &max); template void matMinAndMax(const Basics::SparseMatrix *obj, T &min, T &max); template Basics::Matrix *matMaxSelDim(const Basics::Matrix *obj, const int dim, Int32GPUMirroredMemoryBlock *raw_positions, const int shift, Basics::Matrix *result=0); /// Returns the sum of all the elements of the given matrix. template T matSum(const Basics::Matrix *obj); /// Returns the sum of all the elements of the given matrix. template <> ComplexF matSum(const Basics::Matrix *obj); /// Returns the sum of all the elements of the given matrix. template T matSum(const Basics::SparseMatrix *obj); /** * @brief Sum reduction over a given dimension number. * * @param obj - The source matrix object. * @param dim - The dimension (a value between 0 and @c obj->getNumDim() * @param dest - The destination matrix, if it is 0, a new matrix would be allocated. * @param accumulated - Indicates if the sum has to be accumulated to dest. * * @result The given @c dest argument or a new allocated matrix with the sum values. */ template Basics::Matrix *matSum(Basics::Matrix *obj, int dim, Basics::Matrix *dest=0, bool accumulated=false); // TODO: Implement using a wrapper for GPU/CPU computation. /** * @brief Sum reduction over a given dimension number. * * @param obj - The source matrix object. * @param dim - The dimension (a value between 0 and @c obj->getNumDim() * @param dest - The destination matrix, if it is 0, a new matrix would be allocated. * @param accumulated - Indicates if the sum has to be accumulated to dest. * * @result The given @c dest argument or a new allocated matrix with the sum values. */ template Basics::Matrix *matSum(const Basics::SparseMatrix *obj, int dim, Basics::Matrix *dest=0, bool accumulated=false); /// Returns the product of all the elements of the given matrix. template T matProd(const Basics::Matrix *obj); /// Returns the product of all the elements of the given matrix. template <> ComplexF matProd(const Basics::Matrix *obj); /** * @brief Product reduction over a given dimension number. * * @param obj - The source matrix object. * @param dim - The dimension (a value between 0 and @c obj->getNumDim() * @param dest - The destination matrix, if it is 0, a new matrix would be allocated. * * @result The given @c dest argument or a new allocated matrix with the product values. */ template Basics::Matrix *matProd(Basics::Matrix *obj, int dim, Basics::Matrix *dest=0); // TODO: Implement using a wrapper for GPU/CPU computation. /** * @brief Cumulative sum reduction over a given dimension number. * * @param obj - The source matrix object. * @param dim - The dimension (a value between 0 and @c obj->getNumDim() * @param dest - The destination matrix, if it is 0, a new matrix would be allocated. * * @result The given @c dest argument or a new allocated matrix with the cumulative sum values. */ template Basics::Matrix *matCumSum(Basics::Matrix *obj, int dim, Basics::Matrix *dest=0); // TODO: Implement using a wrapper for GPU/CPU computation. /** * @brief Cumulative prod reduction over a given dimension number. * * @param obj - The source matrix object. * @param dim - The dimension (a value between 0 and @c obj->getNumDim() * @param dest - The destination matrix, if it is 0, a new matrix would be allocated. * * @result The given @c dest argument or a new allocated matrix with the cumulative prod values. */ template Basics::Matrix *matCumProd(Basics::Matrix *obj, int dim, Basics::Matrix *dest=0); /**** COMPONENT WISE OPERATIONS ****/ /// Returns true if \f$ A = B \f$ using the given \f$ \epsilon \f$ as relative error threshold. template bool matEquals(const Basics::Matrix *a, const Basics::Matrix *b, float epsilon); /// Returns true if \f$ A = B \f$ using the given \f$ \epsilon \f$ as relative error threshold. template bool matEquals(const Basics::SparseMatrix *a, const Basics::SparseMatrix *b, float epsilon); /** * @brief Indicates if the matrix numbers are finite or note. */ template bool matIsFinite(const Basics::Matrix *obj); } // namespace Reductions } // namespace MatrixExt } // namespace AprilMath #endif // MATRIX_EXT_REDUCTIONS_H april-ann-0.4.1/packages/basics/matrix/c_src/matrix_serialization_utils.h000066400000000000000000000116061263004425400266520ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef MATRIX_SERIALIZATION_UTILS_H #define MATRIX_SERIALIZATION_UTILS_H #include "constString.h" #include "error_print.h" #include "stream.h" #include "unused_variable.h" namespace Basics { template class Matrix; // forward declaration template class SparseMatrix; // forward declaration namespace MatrixIO { /* Templates for ascii and binary extractors, sizers and coders */ /** * Template for AsciiExtractor implementations, it needs to be specialized * depending in the Matrix type T. */ template struct AsciiExtractor { // returns true if success, false otherwise bool operator()(AprilUtils::constString &line, T &destination) { UNUSED_VARIABLE(line); UNUSED_VARIABLE(destination); ERROR_EXIT(128, "NOT IMPLEMENTED\n"); return false; } }; /** * Template for BinaryExtractor implementations, it needs to be specialized * depending in the Matrix type T. */ template struct BinaryExtractor { // returns true if success, false otherwise bool operator()(AprilUtils::constString &line, T &destination) { UNUSED_VARIABLE(line); UNUSED_VARIABLE(destination); ERROR_EXIT(128, "NOT IMPLEMENTED\n"); return false; } }; /** * Template for AsciiSizer implementations, it needs to be specialized * depending in the Matrix type T. */ template struct AsciiSizer { // returns the number of bytes needed for all matrix data (plus spaces) int operator()(const Matrix *mat) { UNUSED_VARIABLE(mat); ERROR_EXIT(128, "NOT IMPLEMENTED\n"); return -1; } }; /** * Template for BinarySizer implementations, it needs to be specialized * depending in the Matrix type T. */ template struct BinarySizer { // returns the number of bytes needed for all matrix data (plus spaces) int operator()(const Matrix *mat) { UNUSED_VARIABLE(mat); ERROR_EXIT(128, "NOT IMPLEMENTED\n"); return -1; } }; /** * Template for AsciiCoder implementations, it needs to be specialized * depending in the Matrix type T. */ template struct AsciiCoder { // puts to the stream the given value void operator()(const T &value, AprilIO::StreamInterface *stream) { UNUSED_VARIABLE(value); UNUSED_VARIABLE(stream); ERROR_EXIT(128, "NOT IMPLEMENTED\n"); } }; /** * Template for BinaryCoder implementations, it needs to be specialized * depending in the Matrix type T. */ template struct BinaryCoder { // puts to the stream the given value void operator()(const T &value, AprilIO::StreamInterface *stream) { UNUSED_VARIABLE(value); UNUSED_VARIABLE(stream); ERROR_EXIT(128, "NOT IMPLEMENTED\n"); } }; /****************************************************************************/ /** * Template for SparseAsciiSizer implementations, it needs to be specialized * depending in the SparseMatrix type T. */ template struct SparseAsciiSizer { // returns the number of bytes needed for all matrix data (plus spaces) int operator()(const SparseMatrix *mat) { UNUSED_VARIABLE(mat); ERROR_EXIT(128, "NOT IMPLEMENTED\n"); return -1; } }; /** * Template for SparseBinarySizer implementations, it needs to be specialized * depending in the SparseMatrix type T. */ template struct SparseBinarySizer { // returns the number of bytes needed for all matrix data (plus spaces) int operator()(const SparseMatrix *mat) { UNUSED_VARIABLE(mat); ERROR_EXIT(128, "NOT IMPLEMENTED\n"); return -1; } }; } // namespace MatrixIO } // namespace Basics #endif // MATRIX_SERIALIZATION_UTILS_H april-ann-0.4.1/packages/basics/matrix/c_src/reduce_matrix.h000066400000000000000000000345761263004425400240370ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef REDUCE_MATRIX_H #define REDUCE_MATRIX_H #include "cmath_overloads.h" #include "mathcore.h" #define DEFAULT_N_TH 100 #define DEFAULT_SIZE_TH 100u namespace Basics { // forward declaration template class Matrix; } namespace AprilMath { namespace MatrixExt { template Basics::Matrix * MatrixScalarReduce1OverDimension(const Basics::Matrix *input, int dim, const OP1 &scalar_red_functor, const OP2 &partials_red_functor, const O &zero, Basics::Matrix *dest=0, bool set_dest_to_zero=true); template Basics::Matrix * MatrixSpanReduce1OverDimension(const Basics::Matrix *input, int dim, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero, Basics::Matrix *dest=0, bool set_dest_to_zero=true); template Basics::Matrix * MatrixScalarReduce2OverDimension(const Basics::Matrix *input1, const Basics::Matrix *input2, int dim, const OP1 &scalar_red_functor, const OP2 &partials_red_functor, const O &zero, Basics::Matrix *dest=0, bool set_dest_to_zero=true); template Basics::Matrix * MatrixSpanReduce2OverDimension(const Basics::Matrix *input1, const Basics::Matrix *input2, int dim, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero, Basics::Matrix *dest=0, bool set_dest_to_zero=true); template Basics::Matrix * MatrixScalarReduceMinMaxOverDimension(const Basics::Matrix *input, int dim, const OP &scalar_red_functor, const T &zero, Basics::Matrix *which=0, Basics::Matrix *dest=0, bool set_dest_to_zero=true); template Basics::Matrix * MatrixSpanReduceMinMaxOverDimension(const Basics::Matrix *input, int dim, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const T &zero, Basics::Matrix *which=0, Basics::Matrix *dest=0, bool set_dest_to_zero=true); template void MatrixScalarReduce1(const Basics::Matrix *input, const OP1 &scalar_red_functor, const OP2 &partials_red_functor, const O &zero, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos=0, bool set_dest_to_zero=true); /** * @brief Reduces all the elements of a given Basics::Matrix @c input storing * the result in the given @c dest_raw_pos position of @c dest * AprilMath::GPUMirroredMemoryBlock. * * @tparam T - The reduction input type. * @tparam O - The reduction output type. * @tparam OP1 - The functor for reduction of input values. It has to implement * the APRIL_CUDA_EXPORT void operator()(O &acc, const T &b) const which * reduces the given reduction output accumulator @c acc with the given input * value @c b and stores the result in @c acc. * @tparam Op2 - The functor for reduction of intermediate output values. It * has to implement the APRIL_CUDA_EXPORT void operator()(O &acc, const O &b) const * which reduces a given reduction output accumulator @c acc with the given output * reduction value @c b, storing its result in @c acc. * * @param input - * @param scalar_red_functor - * @param partials_red_functor - * @param zero - * @param set_dest_to_zero - * * @return The output reduction value. * * @note This function is a wrapper over * AprilMath::MatrixExt::MatrixScalarReduce1 passing @c dest parameter as a * new allocated AprilMath::GPUMirroredMemoryBlock and @c dest_raw_pos=0 . * * @code * // The example uses the AprilMath::Function::r_add reduction, which uses * // operator+= to reduce two values, the input type T and the reduction type O. * #include "reduce_matrix.h" * namespace MyNameSpace { * struct MeanReduceResult { * float sum; * int N; * MeanReduceResult() : sum(0.0f), N(0) { } * float getMean() const { return sum/N; } * // Called from AprilMath::Functors::r_add, * APRIL_CUDA_EXPORT MeanReduceResult &operator+=(const float &b) const { * acc.N++; * acc.sum += b; * return *this; * } * // Called from AprilMath::Functors::r_add * APRIL_CUDA_EXPORT MeanReduceResult &operator+=(const MeanReduceResult &b) const { * acc.sum += b.sum; * acc.N += b.N; * return *this; * } * }; * } * SPECIALIZE_CUDA_SHARED_MEMORY(MyNameSpace::MeanReduceResult,MeanReduceResult); * // a matrix of 1 dimension and 1 element * MyNameSpace::MeanReduceResult result = * MatrixScalarReduce1(my_matrix_float, // a pointer to a MatrixFloat instance * AprilMath::Functors::r_add, * AprilMath::Functors::r_add, * MyNameSpace::MeanReduceResult()); * printf("Mean result: %f\n", result.getMean()); * @endcode */ template O MatrixScalarReduce1(const Basics::Matrix *input, const OP1 &scalar_red_functor, const OP2 &partials_red_functor, const O &zero); template void MatrixSpanReduce1(const Basics::Matrix *input, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos=0, bool set_dest_to_zero=true); template O MatrixSpanReduce1(const Basics::Matrix *input, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero); template void MatrixSpanReduceMinMax(const Basics::Matrix *input, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero, AprilMath::GPUMirroredMemoryBlock *which, unsigned int which_raw_pos, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos=0, bool set_dest_to_zero=true); template void MatrixSpanReduce2(const Basics::Matrix *input1, const Basics::Matrix *input2, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos=0, bool set_dest_to_zero=true); template O MatrixSpanReduce2(const Basics::Matrix *input1, const Basics::Matrix *input2, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero); template void MatrixScalarReduce2(const Basics::Matrix *input1, const Basics::Matrix *input2, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos=0, bool set_dest_to_zero=true); template O MatrixScalarReduce2(const Basics::Matrix *input1, const Basics::Matrix *input2, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero); template void MatrixScalarSumReduce1(const Basics::Matrix *input, const OP &scalar_red_functor, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos=0, bool set_dest_to_zero=true, int N_th = DEFAULT_N_TH, unsigned int SIZE_th = DEFAULT_SIZE_TH); template void MatrixSpanSumReduce1(const Basics::Matrix *input, const OP &inter_span_red_functor, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos=0, bool set_dest_to_zero=true, int N_th = DEFAULT_N_TH, unsigned int SIZE_th = DEFAULT_N_TH); template T MatrixSpanSumReduce1(const Basics::Matrix *input, const OP &inter_span_red_functor); template void MatrixScalarProdReduce1(const Basics::Matrix *input, const OP &scalar_red_functor, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos=0, bool set_dest_to_one=true, int N_th = DEFAULT_N_TH, unsigned int SIZE_th = DEFAULT_SIZE_TH); template void MatrixSpanProdReduce1(const Basics::Matrix *input, const OP &inter_span_red_functor, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos=0, bool set_dest_to_one=true, int N_th = DEFAULT_N_TH, unsigned int SIZE_th = DEFAULT_N_TH); template T MatrixSpanProdReduce1(const Basics::Matrix *input, const OP &inter_span_red_functor); } // namespace MatrixExt } // namespace AprilMath #undef DEFAULT_N_TH #undef DEFAULT_SIZE_TH #include "reduce_matrix.impl.h" #endif // MAP_MATRIX_H april-ann-0.4.1/packages/basics/matrix/c_src/reduce_matrix.impl.h000066400000000000000000001155651263004425400247750ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef REDUCE_MATRIX_IMPL_H #define REDUCE_MATRIX_IMPL_H // Must be defined here. #include "matrix.h" #include "april_assert.h" #include "omp_utils.h" #include "reduce_matrix.h" #include "reduce_template.h" #include "smart_ptr.h" namespace AprilMath { namespace MatrixExt { template Basics::Matrix * MatrixScalarReduceMinMaxOverDimension(const Basics::Matrix *input, int dim, const OP &scalar_red_functor, const T &zero, Basics::Matrix *which, Basics::Matrix *dest, bool set_dest_to_zero) { ScalarToSpanReduceMinMax span_functor(scalar_red_functor); return MatrixSpanReduceMinMaxOverDimension(input, dim, span_functor, scalar_red_functor, zero, which, dest, set_dest_to_zero); } template void MatrixSpanReduceMinMax(const Basics::Matrix *input, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero, AprilMath::GPUMirroredMemoryBlock *which, unsigned int which_raw_pos, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos, bool set_dest_to_zero) { april_assert(input != 0); if (dest == 0) ERROR_EXIT(128, "Expected a non-NULL dest pointer\n"); if (which == 0) ERROR_EXIT(128, "Expected a non-NULL which pointer\n"); bool cuda_flag = input->getCudaFlag(); // This specialization has a problem to compute the argmin or argmax when // matrices are in col_major // // Contiguous memory block // if (input->getIsContiguous()) { // inter_span_red_functor(static_cast(input->size()), // input->getRawDataAccess(), 1u, // static_cast(input->getOffset()), // input->getCudaFlag(), // zero, // intra_span_red_functor, // which, // which_raw_pos, // dest, // dest_raw_pos, // set_dest_to_zero); // } // One dimension if (input->getNumDim() == 1) { inter_span_red_functor(static_cast(input->size()), input->getRawDataAccess(), static_cast(input->getStrideSize(0)), static_cast(input->getOffset()), cuda_flag, zero, intra_span_red_functor, which, which_raw_pos, dest, dest_raw_pos, set_dest_to_zero); } // This specialization has a problem to compute the argmin or argmax when // matrices are in col_major // General case else { ERROR_EXIT(128, "NOT IMPLEMENTED\n"); /* typename Basics::Matrix::span_iterator span_it(input); unsigned int size = static_cast(span_it.getSize()); unsigned int stride = static_cast(span_it.getStride()); const int N = span_it.numberOfIterations(); for (int i=0; iend_span_iterator()); inter_span_red_functor(size, input->getRawDataAccess(), stride, span_it.getOffset(), input->getCudaFlag(), zero, intra_span_red_functor, which, which_raw_pos, dest, dest_raw_pos, set_dest_to_zero); set_dest_to_zero = false; // only use it in the first iteration ++span_it; } april_assert(span_it == input->end_span_iterator()); */ } } // function MatrixSpanReduceMinMax template Basics::Matrix * MatrixSpanReduceMinMaxOverDimension(const Basics::Matrix *input, int dim, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const T &zero, Basics::Matrix *which, Basics::Matrix *dest, bool set_dest_to_zero) { april_assert(input != 0); bool cuda_flag = input->getCudaFlag() || (dest && dest->getCudaFlag()) || (which && which->getCudaFlag()); const int numDim = input->getNumDim(); const int *matrixSize = input->getDimPtr(); AprilUtils::UniquePtr result_dims( new int[numDim] ); /**** INPUT span ****/ AprilUtils::UniquePtr span_order( new int[numDim] ); span_order[0] = dim; int result_size=1; for (int i=0; i > result = dest; AprilUtils::SharedPtr< Basics::Matrix > aux_which; Basics::Matrix *result2 = which; if (result.empty()) { result = new Basics::Matrix(numDim, result_dims.get()); set_dest_to_zero = true; } if (result2 == 0) { aux_which = result2 = new Basics::Matrix(numDim, result_dims.get()); set_dest_to_zero = true; } #ifdef USE_CUDA result->setUseCuda(cuda_flag); result2->setUseCuda(cuda_flag); #endif if (result->size() != result_size || result2->size() != result_size) { // else if (!result->sameDim(result_dims, numDim)) ERROR_EXIT2(256, "Incorrect size at the given dest matrtix, " "expected %d, found %d\n", result_size, result->size()); } typename Basics::Matrix::span_iterator span_it(input, span_order.get()); typename Basics::Matrix::pos_iterator it2(result2); unsigned int span_size = static_cast(span_it.getSize()); unsigned int span_stride = static_cast(span_it.getStride()); april_assert(span_it.numberOfIterations() == result->size()); // traverse in row major order for (typename Basics::Matrix::pos_iterator it(result.get()); !it.isEnd(); ++it, ++it2, ++span_it) { april_assert(span_it != input->end_span_iterator()); april_assert(!it2.isEnd()); inter_span_red_functor(span_size, input->getRawDataAccess(), span_stride, static_cast(span_it.getOffset()), cuda_flag, zero, intra_span_red_functor, result2->getRawDataAccess(), it2.getRawPos(), result->getRawDataAccess(), it.getRawPos(), set_dest_to_zero); } april_assert(span_it == input->end_span_iterator()); april_assert(it2.isEnd()); return result.weakRelease(); } template Basics::Matrix * MatrixScalarReduce1OverDimension(const Basics::Matrix *input, int dim, const OP1 &scalar_red_functor, const OP2 &partials_red_functor, const O &zero, Basics::Matrix *dest, bool set_dest_to_zero) { ScalarToSpanReduce1 span_functor(scalar_red_functor); return MatrixSpanReduce1OverDimension(input, dim, span_functor, partials_red_functor, zero, dest, set_dest_to_zero); } template Basics::Matrix * MatrixSpanReduce1OverDimension(const Basics::Matrix *input, int dim, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero, Basics::Matrix *dest, bool set_dest_to_zero) { april_assert(input != 0); bool cuda_flag = input->getCudaFlag() || (dest && dest->getCudaFlag()); const int numDim = input->getNumDim(); const int *matrixSize = input->getDimPtr(); AprilUtils::UniquePtr result_dims( new int[numDim] ); /**** INPUT span ****/ AprilUtils::UniquePtr span_order( new int[numDim] ); span_order[0] = dim; int result_size=1; for (int i=0; i > result = dest; if (result.empty()) { result = new Basics::Matrix(numDim, result_dims.get()); set_dest_to_zero = true; } else if (result->size() != result_size) { // else if (!result->sameDim(result_dims, numDim)) ERROR_EXIT2(256, "Incorrect size at the given dest matrix, " "expected %d, found %d\n", result_size, result->size()); #ifdef USE_CUDA result->setUseCuda(cuda_flag); #endif } typename Basics::Matrix::span_iterator span_it(input, span_order.get()); unsigned int span_size = static_cast(span_it.getSize()); unsigned int span_stride = static_cast(span_it.getStride()); april_assert(span_it.numberOfIterations() == result->size()); // traverse in row major order for (typename Basics::Matrix::pos_iterator it(result.get()); !it.isEnd(); ++it, ++span_it) { april_assert(span_it != input->end_span_iterator()); inter_span_red_functor(span_size, input->getRawDataAccess(), span_stride, static_cast(span_it.getOffset()), cuda_flag, zero, intra_span_red_functor, result->getRawDataAccess(), it.getRawPos(), set_dest_to_zero); } april_assert(span_it == input->end_span_iterator()); return result.weakRelease(); } template void MatrixScalarSumReduce1(const Basics::Matrix *input, const OP &scalar_red_functor, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos, bool set_dest_to_zero, int N_th, unsigned int SIZE_th) { ScalarToSpanReduce1 span_functor(scalar_red_functor); MatrixSpanSumReduce1(input, span_functor, dest, dest_raw_pos, N_th, SIZE_th, set_dest_to_zero); } template void MatrixScalarProdReduce1(const Basics::Matrix *input, const OP &scalar_red_functor, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos, bool set_dest_to_one, int N_th, unsigned int SIZE_th) { ScalarToSpanReduce1 span_functor(scalar_red_functor); MatrixSpanProdReduce1(input, span_functor, dest, dest_raw_pos, N_th, SIZE_th, set_dest_to_one); } template O MatrixSpanReduce1(const Basics::Matrix *input, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero) { AprilUtils::SharedPtr< AprilMath::GPUMirroredMemoryBlock > dest( new AprilMath::GPUMirroredMemoryBlock(1u) ); MatrixSpanReduce1(input, inter_span_red_functor, intra_span_red_functor, zero, dest.get(), 0u, true); return dest->get(0); } template void MatrixSpanReduce1(const Basics::Matrix *input, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos, bool set_dest_to_zero) { april_assert(input != 0); if (dest == 0) ERROR_EXIT(128, "Expected a non-NULL dest pointer\n"); bool cuda_flag = input->getCudaFlag(); // Contiguous memory block or one dimension. if (input->getIsContiguous() || input->getNumDim() == 1) { unsigned int size = static_cast(input->size()); unsigned int input_offset = static_cast(input->getOffset()); unsigned int input_stride; if (input->getIsContiguous()) { // Contiguous. input_stride = 1u; } else { // One dimension. input_stride = static_cast(input->getStrideSize(0)); } inter_span_red_functor(size, input->getRawDataAccess(), input_stride, input_offset, cuda_flag, zero, intra_span_red_functor, dest, dest_raw_pos, set_dest_to_zero); } // General case else { typename Basics::Matrix::span_iterator span_it(input); unsigned int size = static_cast(span_it.getSize()); unsigned int stride = static_cast(span_it.getStride()); const int N = span_it.numberOfIterations(); for (int i=0; iend_span_iterator()); inter_span_red_functor(size, input->getRawDataAccess(), stride, span_it.getOffset(), cuda_flag, zero, intra_span_red_functor, dest, dest_raw_pos, set_dest_to_zero); set_dest_to_zero = false; // use only in the first iteration ++span_it; } april_assert(span_it == input->end_span_iterator()); } } // function MatrixSpanReduce1 template O MatrixScalarReduce1(const Basics::Matrix *input, const OP1 &scalar_red_functor, const OP2 &partials_red_functor, const O &zero) { AprilUtils::SharedPtr< AprilMath::GPUMirroredMemoryBlock > dest( new AprilMath::GPUMirroredMemoryBlock(1) ); MatrixScalarReduce1(input, scalar_red_functor, partials_red_functor, zero, dest.get(), 0u, true); return dest->get(0); } template void MatrixScalarReduce1(const Basics::Matrix *input, const OP1 &scalar_red_functor, const OP2 &partials_red_functor, const O &zero, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos, bool set_dest_to_zero) { ScalarToSpanReduce1 span_functor(scalar_red_functor); MatrixSpanReduce1(input, span_functor, partials_red_functor, zero, dest, dest_raw_pos, set_dest_to_zero); } template T MatrixSpanSumReduce1(const Basics::Matrix *input, const OP &inter_span_red_functor) { AprilUtils::SharedPtr< AprilMath::GPUMirroredMemoryBlock > dest( new AprilMath::GPUMirroredMemoryBlock(1) ); MatrixSpanSumReduce1(input, inter_span_red_functor, dest.get(), 0u, true); return dest->get(0); } template T MatrixSpanProdReduce1(const Basics::Matrix *input, const OP &inter_span_red_functor) { AprilUtils::SharedPtr< AprilMath::GPUMirroredMemoryBlock > dest( new AprilMath::GPUMirroredMemoryBlock(1) ); MatrixSpanProdReduce1(input, inter_span_red_functor, dest.get(), 0u, true); return dest->get(0); } template void MatrixSpanSumReduce1(const Basics::Matrix *input, const OP &inter_span_red_functor, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos, bool set_dest_to_zero, int N_th, unsigned int SIZE_th) { april_assert(input != 0); if (dest == 0) ERROR_EXIT(128, "Expected a non-NULL dest pointer\n"); #ifdef NO_OMP UNUSED_VARIABLE(N_th); UNUSED_VARIABLE(SIZE_th); #endif bool cuda_flag = input->getCudaFlag(); // Contiguous memory block or one dimension. if (input->getIsContiguous() || input->getNumDim() == 1) { unsigned int size = static_cast(input->size()); unsigned int input_offset = static_cast(input->getOffset()); unsigned int input_stride; if (input->getIsContiguous()) { // Contiguous. input_stride = 1u; } else { // One dimension. input_stride = static_cast(input->getStrideSize(0)); } inter_span_red_functor(size, input->getRawDataAccess(), input_stride, input_offset, cuda_flag, AprilMath::Limits::zero(), AprilMath::Functors::r_add(), dest, dest_raw_pos, set_dest_to_zero); } // General case else { typename Basics::Matrix::span_iterator span_it(input); unsigned int size = static_cast(span_it.getSize()); unsigned int stride = static_cast(span_it.getStride()); const int N = span_it.numberOfIterations(); #ifndef NO_OMP // this if controls the execution using OMP only when the number of threads // is more than 1 and the iterator size is big enough if (OMPUtils::get_num_threads() > 1 && N > N_th && size > SIZE_th) { T result; if (set_dest_to_zero) result = AprilMath::Limits::zero(); else dest->getValue(dest_raw_pos, result); GPUMirroredMemoryBlock aux(1); T partial; #ifdef USE_CUDA // Forces execution of memory copy from GPU to PPAL or viceversa (if // needed), avoiding race conditions on the following. input->getRawDataAccess()->forceSync(cuda_flag); #endif #pragma omp parallel for reduction(+:result) firstprivate(span_it) for (int i=0; igetRawDataAccess(), stride, span_it.getOffset(), cuda_flag, AprilMath::Limits::zero(), AprilMath::Functors::r_add(), &aux, 0, true); aux.getValue(0, partial); result += partial; } dest->putValue(dest_raw_pos, result); } else { #endif for (int i=0; iend_span_iterator()); inter_span_red_functor(size, input->getRawDataAccess(), stride, span_it.getOffset(), cuda_flag, AprilMath::Limits::zero(), AprilMath::Functors::r_add(), dest, dest_raw_pos, set_dest_to_zero); set_dest_to_zero = false; // use only in the first iteration ++span_it; } april_assert(span_it == input->end_span_iterator()); #ifndef NO_OMP } #endif } // General case } // function MatrixSpanSumReduce1 template void MatrixSpanProdReduce1(const Basics::Matrix *input, const OP &inter_span_red_functor, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos, bool set_dest_to_one, int N_th, unsigned int SIZE_th) { april_assert(input != 0); if (dest == 0) ERROR_EXIT(128, "Expected a non-NULL dest pointer\n"); #ifdef NO_OMP UNUSED_VARIABLE(N_th); UNUSED_VARIABLE(SIZE_th); #endif bool cuda_flag = input->getCudaFlag(); // Contiguous memory block or one dimension. if (input->getIsContiguous() || input->getNumDim() == 1) { unsigned int size = static_cast(input->size()); unsigned int input_offset = static_cast(input->getOffset()); unsigned int input_stride; if (input->getIsContiguous()) { // Contiguous. input_stride = 1u; } else { // One dimension. input_stride = static_cast(input->getStrideSize(0)); } inter_span_red_functor(size, input->getRawDataAccess(), input_stride, input_offset, cuda_flag, AprilMath::Limits::one(), AprilMath::Functors::r_mul(), dest, dest_raw_pos, set_dest_to_one); } // General case else { typename Basics::Matrix::span_iterator span_it(input); unsigned int size = static_cast(span_it.getSize()); unsigned int stride = static_cast(span_it.getStride()); const int N = span_it.numberOfIterations(); #ifndef NO_OMP // this if controls the execution using OMP only when the number of threads // is more than 1 and the iterator size is big enough if (OMPUtils::get_num_threads() > 1 && N > N_th && size > SIZE_th) { T result; if (set_dest_to_one) result = AprilMath::Limits::one(); else dest->getValue(dest_raw_pos, result); GPUMirroredMemoryBlock aux(1); T partial; #ifdef USE_CUDA // Forces execution of memory copy from GPU to PPAL or viceversa (if // needed), avoiding race conditions on the following. input->getRawDataAccess()->forceSync(cuda_flag); #endif #pragma omp parallel for reduction(*:result) firstprivate(span_it) for (int i=0; igetRawDataAccess(), stride, span_it.getOffset(), cuda_flag, AprilMath::Limits::one(), AprilMath::Functors::r_mul(), &aux, 0, true); aux.getValue(0, partial); result *= partial; } dest->putValue(dest_raw_pos, result); } else { #endif for (int i=0; iend_span_iterator()); inter_span_red_functor(size, input->getRawDataAccess(), stride, span_it.getOffset(), cuda_flag, AprilMath::Limits::one(), AprilMath::Functors::r_mul(), dest, dest_raw_pos, set_dest_to_one); set_dest_to_one = false; // use only in the first iteration ++span_it; } april_assert(span_it == input->end_span_iterator()); #ifndef NO_OMP } #endif } // General case } // function MatrixSpanProdReduce1 template O MatrixSpanReduce2(const Basics::Matrix *input1, const Basics::Matrix *input2, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero) { AprilUtils::SharedPtr< AprilMath::GPUMirroredMemoryBlock > dest( new AprilMath::GPUMirroredMemoryBlock(1) ); MatrixSpanReduce2(input1, input2, inter_span_red_functor, intra_span_red_functor, zero, dest.get(), 0u, true); return dest->get(0); } template void MatrixSpanReduce2(const Basics::Matrix *input1, const Basics::Matrix *input2, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos, bool set_dest_to_zero) { april_assert(input1 != 0 && input2 != 0); if (dest == 0) ERROR_EXIT(128, "Expected a non-NULL dest pointer\n"); if (input1->size() != input2->size()) { ERROR_EXIT(128, "Incompatible matrix sizes\n"); } bool cuda_flag = input1->getCudaFlag() || input2->getCudaFlag(); // Contiguous memory block or one dimension. if ( (input1->getIsContiguous() || input1->getNumDim() == 1) && (input2->getIsContiguous() || input2->getNumDim() == 1) ) { unsigned int size = static_cast(input1->size()); unsigned int input1_offset = static_cast(input1->getOffset()); unsigned int input2_offset = static_cast(input2->getOffset()); unsigned int input1_stride, input2_stride; if (input1->getIsContiguous()) { // Contiguous. input1_stride = 1u; } else { // One dimension. input1_stride = static_cast(input1->getStrideSize(0)); } if (input2->getIsContiguous()) { // Contiguous. input2_stride = 1u; } else { // One dimension. input2_stride = static_cast(input2->getStrideSize(0)); } inter_span_red_functor(size, input1->getRawDataAccess(), input1_stride, input1_offset, input2->getRawDataAccess(), input2_stride, input2_offset, cuda_flag, zero, intra_span_red_functor, dest, dest_raw_pos, set_dest_to_zero); } // General case else { typename Basics::Matrix::span_iterator input1_span_it(input1); typename Basics::Matrix::span_iterator input2_span_it(input2); const int N = input1_span_it.numberOfIterations(); april_assert(N == input2_span_it.numberOfIterations()); const unsigned int size = static_cast(input1_span_it.getSize()); const unsigned int input1_stride = static_cast(input1_span_it.getStride()); const unsigned int input2_stride = static_cast(input2_span_it.getStride()); april_assert(size == static_cast(input2_span_it.getSize())); for (int i=0; iend_span_iterator()); april_assert(input2_span_it != input2->end_span_iterator()); inter_span_red_functor(size, input1->getRawDataAccess(), input1_stride, input1_span_it.getOffset(), input2->getRawDataAccess(), input2_stride, input2_span_it.getOffset(), cuda_flag, zero, intra_span_red_functor, dest, dest_raw_pos, set_dest_to_zero); set_dest_to_zero = false; // use only in the first iteration ++input1_span_it; ++input2_span_it; } april_assert(input1_span_it == input1->end_span_iterator()); april_assert(input2_span_it == input2->end_span_iterator()); } } // function MatrixSpanReduce2 template void MatrixScalarReduce2(const Basics::Matrix *input1, const Basics::Matrix *input2, const OP1 &scalar_red_functor, const OP2 &partials_red_functor, const O &zero, AprilMath::GPUMirroredMemoryBlock *dest, unsigned int dest_raw_pos, bool set_dest_to_zero) { ScalarToSpanReduce2 span_functor(scalar_red_functor); MatrixSpanReduce2(input1, input2, span_functor, partials_red_functor, zero, dest, dest_raw_pos, set_dest_to_zero); } template O MatrixScalarReduce2(const Basics::Matrix *input1, const Basics::Matrix *input2, const OP1 &scalar_red_functor, const OP2 &partials_red_functor, const O &zero) { AprilUtils::SharedPtr< AprilMath::GPUMirroredMemoryBlock > dest( new AprilMath::GPUMirroredMemoryBlock(1) ); MatrixScalarReduce2(input1, input2, scalar_red_functor, partials_red_functor, zero, dest.get(), 0u, true); return dest->get(0); } template Basics::Matrix * MatrixScalarReduce2OverDimension(const Basics::Matrix *input1, const Basics::Matrix *input2, int dim, const OP1 &scalar_red_functor, const OP2 &partials_red_functor, const O &zero, Basics::Matrix *dest, bool set_dest_to_zero) { ScalarToSpanReduce2 span_functor(scalar_red_functor); return MatrixSpanReduce2OverDimension(input1, input2, dim, span_functor, partials_red_functor, zero, dest, set_dest_to_zero); } template Basics::Matrix * MatrixSpanReduce2OverDimension(const Basics::Matrix *input1, const Basics::Matrix *input2, int dim, const OP1 &inter_span_red_functor, const OP2 &intra_span_red_functor, const O &zero, Basics::Matrix *dest, bool set_dest_to_zero) { april_assert(input1 != 0 && input2 != 0); if (input1->size() != input2->size()) { ERROR_EXIT(128, "Incompatible matrix sizes\n"); } bool cuda_flag = input1->getCudaFlag() || input2->getCudaFlag() || (dest && dest->getCudaFlag()); const int numDim = input1->getNumDim(); const int *matrixSize = input1->getDimPtr(); AprilUtils::UniquePtr result_dims( new int[numDim] ); /**** INPUT span ****/ AprilUtils::UniquePtr span_order( new int[numDim] ); span_order[0] = dim; int result_size=1; for (int i=0; i > result = dest; if (result.empty()) { result = new Basics::Matrix(numDim, result_dims.get()); set_dest_to_zero = true; } else if (result->size() != result_size) { // else if (!result->sameDim(result_dims, numDim)) ERROR_EXIT2(256, "Incorrect size at the given dest matrix, " "expected %d, found %d\n", result_size, result->size()); #ifdef USE_CUDA result->setUseCuda(cuda_flag); #endif } typename Basics::Matrix::span_iterator span1_it(input1, span_order.get()); typename Basics::Matrix::span_iterator span2_it(input2, span_order.get()); unsigned int span_size = static_cast(span1_it.getSize()); unsigned int span1_stride = static_cast(span1_it.getStride()); unsigned int span2_stride = static_cast(span2_it.getStride()); april_assert(span1_it.numberOfIterations() == result->size()); april_assert(span2_it.getSize() == span1_it.getSize()); april_assert(span2_it.numberOfIterations() == span1_it.numberOfIterations()); // traverse in row major order for (typename Basics::Matrix::pos_iterator it(result.get()); !it.isEnd(); ++it, ++span1_it, ++span2_it) { april_assert(span1_it != input1->end_span_iterator()); april_assert(span2_it != input2->end_span_iterator()); inter_span_red_functor(span_size, input1->getRawDataAccess(), span1_stride, static_cast(span1_it.getOffset()), input2->getRawDataAccess(), span2_stride, static_cast(span2_it.getOffset()), cuda_flag, zero, intra_span_red_functor, result->getRawDataAccess(), it.getRawPos(), set_dest_to_zero); } april_assert(span1_it == input1->end_span_iterator()); april_assert(span2_it == input2->end_span_iterator()); return result.weakRelease(); } } // namespace MatrixExt } // namespace AprilMath #endif // REDUCE_MATRIX_IMPL_H april-ann-0.4.1/packages/basics/matrix/c_src/reduce_sparse_matrix.h000066400000000000000000000025441263004425400254020ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef REDUCE_SPARSE_MATRIX_H #define REDUCE_SPARSE_MATRIX_H namespace Basics { // forward declaration template class SparseMatrix; } namespace AprilMath { namespace MatrixExt { template T SparseMatrixScalarReduce1(const Basics::SparseMatrix *input, const OP &scalar_red_functor, const T &zero); } // namespace MatrixExt } // namespace AprilMath #include "reduce_sparse_matrix.impl.h" #endif // REDUCE_SPARSE_MATRIX_H april-ann-0.4.1/packages/basics/matrix/c_src/reduce_sparse_matrix.impl.h000066400000000000000000000033551263004425400263430ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef REDUCE_SPARSE_MATRIX_IMPL_H #define REDUCE_SPARSE_MATRIX_IMPL_H #include "matrix.h" #include "reduce_sparse_matrix.h" #include "reduce_template.h" namespace AprilMath { namespace MatrixExt { template T SparseMatrixScalarReduce1(const Basics::SparseMatrix *input, const OP &scalar_red_functor, const T &zero) { GPUMirroredMemoryBlock result(1u); result.putValue(0u, zero); genericReduce1Call(input->nonZeroSize(), input->getRawValuesAccess(), 1u, 0u, input->getCudaFlag(), zero, scalar_red_functor, scalar_red_functor, &result, 0u, true); return result.get(0); } } // namespace MatrixExt } // namespace AprilMath #endif // REDUCE_SPARSE_MATRIX_H april-ann-0.4.1/packages/basics/matrix/c_src/referenced_vector.h000066400000000000000000000031571263004425400246570ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef REFERENCED_VECTOR_H #define REFERENCED_VECTOR_H #include #include "referenced.h" #include "vector.h" namespace AprilUtils { template class ReferencedVector : public Referenced, public vector { public: ReferencedVector(size_t n=0) : Referenced(), vector(n) { } // Destructor... virtual ~ReferencedVector() { } T* release_internal_vector() { // :'( he perdido una hora para averiguar que peta si no se pone el this-> // http://www.cplusplus.com/forum/general/6798 T *returned = this->vec; this->used_size = this->vector_size = 0; this->vec = 0; return returned; } }; typedef ReferencedVector ReferencedVectorFloat; typedef ReferencedVector ReferencedVectorUint; } // namespace #endif april-ann-0.4.1/packages/basics/matrix/c_src/sparse_matrix-iterators.impl.h000066400000000000000000000170001263004425400270160ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SPARSE_MATRIX_ITERATORS_IMPL_H #define SPARSE_MATRIX_ITERATORS_IMPL_H #include "sparse_matrix.h" #include "unused_variable.h" namespace Basics { /***** ITERATORS *****/ template SparseMatrix::iterator::iterator(SparseMatrix *m, int idx) : m(m), idx(idx), first_index_pos(0) { values = m->values->getPPALForReadAndWrite(); indices = m->indices->getPPALForReadAndWrite(); first_index = m->first_index->getPPALForReadAndWrite(); } template SparseMatrix::iterator::iterator() : m(0), idx(0), values(0), indices(0), first_index(0), first_index_pos(0) { } template SparseMatrix::iterator::iterator(const iterator &other) : m(other.m), idx(other.idx), first_index_pos(other.first_index_pos) { values = m->values->getPPALForReadAndWrite(); indices = m->indices->getPPALForReadAndWrite(); first_index = other.first_index; while(first_index[first_index_pos] == first_index[first_index_pos+1] && first_index_pos < m->getDenseCoordinateSize()) { ++first_index_pos; } } template SparseMatrix::iterator::~iterator() { } template typename SparseMatrix::iterator &SparseMatrix::iterator:: operator=(const SparseMatrix::iterator &other) { m = other.m; idx = other.idx; values = m->values->getPPALForReadAndWrite(); indices = m->indices->getPPALForReadAndWrite(); first_index = other.first_index; first_index_pos = other.first_index_pos; return *this; } template bool SparseMatrix::iterator::operator==(const SparseMatrix::iterator &other) const { return m==other.m && idx == other.idx; } template bool SparseMatrix::iterator::operator!=(const SparseMatrix::iterator &other) const { return !( (*this) == other ); } template typename SparseMatrix::iterator &SparseMatrix::iterator::operator++() { ++idx; if (idx < m->nonZeroSize()) { while(first_index[first_index_pos+1] <= idx) ++first_index_pos; } return *this; } template T &SparseMatrix::iterator::operator*() { return values[idx]; } template T *SparseMatrix::iterator::operator->() { return &values[idx]; } template void SparseMatrix::iterator::getCoords(int &x0, int &x1) const { switch(m->sparse_format) { case CSC_FORMAT: x0 = indices[idx]; x1 = first_index_pos; break; case CSR_FORMAT: x0 = first_index_pos; x1 = indices[idx]; break; default: x0=-1; x1=-1; } } /*******************************************************************/ template SparseMatrix::const_iterator::const_iterator(const SparseMatrix *m, int idx) : m(m), idx(idx), first_index_pos(0) { values = m->values->getPPALForRead(); indices = m->indices->getPPALForRead(); first_index = m->first_index->getPPALForRead(); while(first_index[first_index_pos] == first_index[first_index_pos+1] && first_index_pos < m->getDenseCoordinateSize()) { ++first_index_pos; } } template SparseMatrix::const_iterator::const_iterator() : m(0), idx(0), values(0), indices(0), first_index(0), first_index_pos(0) { } template SparseMatrix::const_iterator::const_iterator(const const_iterator &other) : m(other.m), idx(other.idx), first_index_pos(other.first_index_pos) { values = m->values->getPPALForRead(); indices = m->indices->getPPALForRead(); first_index = other.first_index; } template SparseMatrix::const_iterator::const_iterator(const iterator &other) : m(other.m), idx(other.idx), first_index_pos(other.first_index_pos) { values = m->values->getPPALForRead(); indices = m->indices->getPPALForRead(); first_index = other.first_index; } template SparseMatrix::const_iterator::~const_iterator() { } template typename SparseMatrix::const_iterator &SparseMatrix::const_iterator:: operator=(const SparseMatrix::const_iterator &other) { m = other.m; idx = other.idx; values = m->values->getPPALForRead(); indices = m->indices->getPPALForRead(); first_index = other.first_index; first_index_pos = other.first_index_pos; return *this; } template typename SparseMatrix::const_iterator &SparseMatrix::const_iterator:: operator=(const SparseMatrix::iterator &other) { m = other.m; idx = other.idx; values = m->values->getPPALForRead(); indices = m->indices->getPPALForRead(); first_index = other.first_index; first_index_pos = other.first_index_pos; return *this; } template bool SparseMatrix::const_iterator::operator==(const SparseMatrix::const_iterator &other) const { return m==other.m && idx == other.idx; } template bool SparseMatrix::const_iterator::operator==(const SparseMatrix::iterator &other) const { return m==other.m && idx == other.idx; } template bool SparseMatrix::const_iterator::operator!=(const SparseMatrix::const_iterator &other) const { return !( (*this) == other ); } template bool SparseMatrix::const_iterator::operator!=(const SparseMatrix::iterator &other) const { return !( (*this) == other ); } template typename SparseMatrix::const_iterator &SparseMatrix::const_iterator::operator++() { ++idx; if (idx < m->nonZeroSize()) { while(first_index[first_index_pos+1] <= idx) ++first_index_pos; } return *this; } template const T &SparseMatrix::const_iterator::operator*() const { return values[idx]; } template const T *SparseMatrix::const_iterator::operator->() const { return &values[idx]; } template void SparseMatrix::const_iterator::getCoords(int &x0, int &x1) const { switch(m->sparse_format) { case CSC_FORMAT: x0 = indices[idx]; x1 = first_index_pos; break; case CSR_FORMAT: x0 = first_index_pos; x1 = indices[idx]; break; default: x0=-1; x1=-1; } } } // namespace Basics #endif // SPARSE_MATRIX_ITERATORS_IMPL_H april-ann-0.4.1/packages/basics/matrix/c_src/sparse_matrix-serialization.impl.h000066400000000000000000000222661263004425400276710ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SPARSE_MATRIX_SERIALIZATION_H #define SPARSE_MATRIX_SERIALIZATION_H #include #include #include #include "binarizer.h" #include "constString.h" #include "c_string.h" #include "error_print.h" #include "matrix.h" #include "matrix_serialization_utils.h" #include "smart_ptr.h" #include "stream.h" namespace Basics { ///////////////////////////////////////////////////////////////////////////// // SPARSE template SparseMatrix* SparseMatrix::read(AprilIO::StreamInterface *stream, const AprilUtils::LuaTable &options) { UNUSED_VARIABLE(options); MatrixIO::AsciiExtractor ascii_extractor; MatrixIO::BinaryExtractor bin_extractor; if (!stream->good()) { ERROR_PRINT("The stream is not prepared, it is empty, or EOF\n"); return 0; } AprilUtils::SharedPtr c_str(new AprilIO::CStringStream()); april_assert(!c_str.empty()); AprilUtils::constString line,format,sparse,token; // First we read the matrix dimensions line = readULine(stream, c_str.get()); if (!line) { ERROR_PRINT("empty file!!!\n"); return 0; } int dims[2], n=0, NZ; for (int i=0; i<2; ++i, ++n) { if (!line.extract_int(&dims[i])) { ERROR_PRINT1("incorrect dimension %d type, expected a integer\n", n); return 0; } n++; } if (!line.extract_int(&NZ)) { ERROR_PRINT("impossible to read the number of non-zero elements\n"); return 0; } SparseMatrix *mat = 0; // Now we read the type of the format line = readULine(stream, c_str.get()); format = line.extract_token(); if (!format) { ERROR_PRINT("impossible to read format token\n"); return 0; } sparse = line.extract_token(); AprilUtils::SharedPtr > values = new AprilMath::GPUMirroredMemoryBlock(NZ); AprilUtils::SharedPtr indices = new AprilMath::Int32GPUMirroredMemoryBlock(NZ); AprilUtils::SharedPtr first_index; SPARSE_FORMAT sparse_format; if (!sparse || sparse=="csr") { first_index = new AprilMath::Int32GPUMirroredMemoryBlock(dims[0]+1); sparse_format = CSR_FORMAT; } else if (sparse=="csc") { first_index = new AprilMath::Int32GPUMirroredMemoryBlock(dims[1]+1); sparse_format = CSC_FORMAT; } else { ERROR_PRINT("Impossible to determine the sparse format\n"); return 0; } T *values_ptr = values->getPPALForWrite(); int32_t *indices_ptr = indices->getPPALForWrite(); int32_t *first_index_ptr = first_index->getPPALForWrite(); if (format == "ascii") { int i=0; while(i(first_index->getSize())) { if (! (line=readULine(stream, c_str.get())) ) { ERROR_EXIT(128, "Incorrect sparse matrix format\n"); } while(i(first_index->getSize()) && line.extract_int(&first_index_ptr[i])) { ++i; } } } else { // binary int i=0; while(i(first_index->getSize())) { if (! (line=readULine(stream, c_str.get())) ) { ERROR_EXIT(128, "Incorrect sparse matrix format\n"); } while(i(first_index->getSize()) && line.extract_int32_binary(&first_index_ptr[i])) { ++i; } } } mat = new SparseMatrix(dims[0],dims[1], values.get(),indices.get(),first_index.get(), sparse_format); return mat; } template void SparseMatrix::write(AprilIO::StreamInterface *stream, const AprilUtils::LuaTable &options) { bool is_ascii = options.opt(MatrixIO::ASCII_OPTION, false); // MatrixIO::AsciiCoder ascii_coder; MatrixIO::BinaryCoder bin_coder; /* Legacy code MatrixIO::SparseAsciiSizer ascii_sizer; MatrixIO::SparseBinarySizer bin_sizer; int sizedata,sizeheader; sizeheader = (this->getNumDim()+1)*10+10+10; // FIXME: To put adequate values // sizedata contains the memory used by T in ascii including spaces, // new lines, etc... if (is_ascii) { sizedata = ascii_sizer(this) + this->nonZeroSize()*12 + this->getDenseCoordinateSize()*12 + 3; } else { sizedata = bin_sizer(this) + AprilUtils::binarizer::buffer_size_32(this->nonZeroSize()) + AprilUtils::binarizer::buffer_size_32(this->getDenseCoordinateSize()) + 3; } // size_t expected_size = static_cast(sizedata+sizeheader+1); // UNUSED_VARIABLE(expected_size); */ if (!stream->isOpened()) { ERROR_EXIT(256, "The stream is not prepared\n"); } stream->printf("%d ",this->getDimSize(0)); stream->printf("%d ",this->getDimSize(1)); stream->printf("%d\n",this->nonZeroSize()); const T *values_ptr = this->getRawValuesAccess()->getPPALForRead(); const int32_t *indices_ptr = this->getRawIndicesAccess()->getPPALForRead(); const int32_t *first_index_ptr = this->getRawFirstIndexAccess()->getPPALForRead(); if (is_ascii) { const int columns = 9; stream->printf("ascii"); if (this->getSparseFormat() == CSR_FORMAT) stream->printf(" csr"); else stream->printf(" csc"); stream->printf("\n"); int i; for (i=0; inonZeroSize(); ++i) { ascii_coder(values_ptr[i], stream); stream->printf("%c", ((((i+1) % columns) == 0) ? '\n' : ' ')); } if ((i % columns) != 0) { stream->printf("\n"); } for (i=0; inonZeroSize(); ++i) { stream->printf("%d", indices_ptr[i]); stream->printf("%c", ((((i+1) % columns) == 0) ? '\n' : ' ')); } if ((i % columns) != 0) { stream->printf("\n"); } for (i=0; i<=this->getDenseCoordinateSize(); ++i) { stream->printf("%d", first_index_ptr[i]); stream->printf("%c", ((((i+1) % columns) == 0) ? '\n' : ' ')); } if ((i % columns) != 0) stream->printf("\n"); } else { // binary const int columns = 16; stream->printf("binary"); if (this->getSparseFormat() == CSR_FORMAT) stream->printf(" csr"); else stream->printf(" csc"); stream->printf("\n"); int i=0; char b[5]; for (i=0; inonZeroSize(); ++i) { bin_coder(values_ptr[i], stream); if ((i+1) % columns == 0) stream->printf("\n"); } if ((i % columns) != 0) stream->printf("\n"); for (i=0; inonZeroSize(); ++i) { AprilUtils::binarizer::code_int32(indices_ptr[i], b); stream->printf("%c%c%c%c%c", b[0],b[1],b[2],b[3],b[4]); if ((i+1) % columns == 0) stream->printf("\n"); } if ((i % columns) != 0) stream->printf("\n"); for (i=0; i<=this->getDenseCoordinateSize(); ++i) { AprilUtils::binarizer::code_int32(first_index_ptr[i], b); stream->printf("%c%c%c%c%c", b[0],b[1],b[2],b[3],b[4]); if ((i+1) % columns == 0) stream->printf("\n"); } if ((i % columns) != 0) stream->printf("\n"); } } } // namespace Basics #endif // SPARSE_MATRIX_SERIALIZATION_H april-ann-0.4.1/packages/basics/matrix/c_src/sparse_matrix.h000066400000000000000000000571161263004425400240600ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SPARSE_MATRIX_H #define SPARSE_MATRIX_H #include #include #include // surprisingly, placement new doesn't work without this #include "aligned_memory.h" #include "april_assert.h" #include "aux_hash_table.h" #include "cblas_headers.h" #include "disallow_class_methods.h" #include "error_print.h" #include "gpu_mirrored_memory_block.h" #include "hash_table.h" #include "mathcore.h" #include "matrix.h" #include "maxmin.h" #include "mmapped_data.h" #include "qsort.h" #include "serializable.h" #include "swap.h" #include "unused_variable.h" namespace Basics { // CSC or CSR format explained at MKL "Sparse Matrix Storage Formats": // http://software.intel.com/sites/products/documentation/hpc/mkl/mklman/GUID-9FCEB1C4-670D-4738-81D2-F378013412B0.htm /// The SparseMatrix class represents bi-dimensional sparse matrices, stored as /// CSC or CSR format, using zero-based indexing (as in Lua). The structure of /// the matrices is resized dynamically. It is not possible to share internal /// memory pointers between different matrices, unless transposition operator /// which shared the data pointers. template class SparseMatrix : public AprilIO::Serializable { APRIL_DISALLOW_ASSIGN(SparseMatrix); friend class Matrix; const static unsigned int MATRIX_BINARY_VERSION; // Auxiliary count variable where the user could store the number of times // this object is shared in a computation (like in ANN components sharing // weight matrices) unsigned int shared_count; protected: /// Number of dimensions (always 2) static const int numDim = 2; /// size of each dimension int matrixSize[2]; /// Total size of the matrix (number of elements) int total_size; // Pointers to data: values,indices,first_index /// non-zero values AprilUtils::SharedPtr< AprilMath::GPUMirroredMemoryBlock > values; /// indices for rows (CSC) or columns (CSR) AprilUtils::SharedPtr< AprilMath::Int32GPUMirroredMemoryBlock > indices; /// size(values) + 1 AprilUtils::SharedPtr< AprilMath::Int32GPUMirroredMemoryBlock > first_index; /// For mmapped matrices AprilUtils::SharedPtr< AprilUtils::MMappedDataReader > mmapped_data; /// Format type (CSC or CSR) SPARSE_FORMAT sparse_format; /// For CUDA purposes bool use_cuda; int searchIndexOf(const int c0, const int c1) const; int searchIndexOfFirst(const int c0, const int c1) const; public: ////////////////////////////////////////////////////////////////////////// /** * @brief Builds a sparse matrix from a Dictionary Of Keys (DOK) format * https://en.wikipedia.org/wiki/Sparse_matrix#Dictionary_of_keys_.28DOK.29 */ class DOKBuilder : public Referenced { typedef AprilUtils::uint_pair Key; typedef AprilUtils::hash DictType; public: DOKBuilder() : Referenced(), max_row_index(0), max_col_index(0) { } ~DOKBuilder() { } void insert(const Key &coords, const T &value) { if (coords.first > max_row_index) max_row_index = coords.first; if (coords.second > max_col_index) max_col_index = coords.second; data.insert(coords, value); } void insert(unsigned int row, unsigned int col, const T &value) { insert(Key(row,col), value); } /** * @brief Builds a sparse matrix by sorting all the coordinates and * declaring the CSR/CSC vectors: values, indices and first_index. */ SparseMatrix *build(unsigned int d0=0, unsigned int d1=0, SPARSE_FORMAT format = CSR_FORMAT) const { if (d0 == 0) d0 = max_row_index+1; if (d1 == 0) d1 = max_col_index+1; if (d0 <= max_row_index) { ERROR_EXIT2(128, "Improper number of rows expected > %u, given %u\n", max_row_index, d0); } if (d1 <= max_col_index) { ERROR_EXIT2(128, "Improper number of columns expected > %d, given %u\n", max_col_index, d1); } // const Key sizes(d0, d1); // put all coordinates of the dictionary into a vector, it will be // sorted after to build the sparse matrix object AprilUtils::vector coordinates(data.size()); unsigned int i=0; for (typename DictType::const_iterator it = data.begin(); it != data.end(); ++it) { if (it->second != AprilMath::Limits::zero() && it->second != -AprilMath::Limits::zero()) { coordinates[i++] = it->first; } } coordinates.resize(i); const unsigned int NNZ = coordinates.size(); // depending in the format, the privateBuild template receives // CSRCompare() or CSCCompare() if (format == CSR_FORMAT) { return privateBuild(sizes, NNZ, coordinates, CSRCompare()); } else if (format == CSC_FORMAT) { return privateBuild(sizes, NNZ, coordinates, CSCCompare()); } else { ERROR_EXIT1(128, "Not recognized sparse format: %d\n", format); } return 0; } private: DictType data; unsigned int max_row_index, max_col_index; struct CSRCompare { unsigned int getDense(const Key &k) const { return k.first; } unsigned int getSparse(const Key &k) const { return k.second; } SPARSE_FORMAT getFormat() const { return CSR_FORMAT; } bool operator()(const Key &a, const Key &b) const { if (a.first < b.first) return true; else if (a.first > b.first) return false; else return a.second < b.second; } }; struct CSCCompare { unsigned int getDense(const Key &k) const { return k.second; } unsigned int getSparse(const Key &k) const { return k.first; } SPARSE_FORMAT getFormat() const { return CSC_FORMAT; } bool operator()(const Key &a, const Key &b) const { if (a.second < b.second) return true; else if (a.second > b.second) return false; else return a.first < b.first; } }; /** * @brief This private build template allows to factorize code between * both CSR and CSC formats. * * It receives a CMP type which is an instance of CSRCompare or CSCCompare * classes. */ template SparseMatrix *privateBuild(const Key &sizes, const unsigned int NNZ, AprilUtils::vector &coordinates, CMP compare) const { AprilMath::GPUMirroredMemoryBlock *values = new AprilMath::GPUMirroredMemoryBlock(NNZ); AprilMath::Int32GPUMirroredMemoryBlock *indices = new AprilMath::Int32GPUMirroredMemoryBlock(NNZ); AprilMath::Int32GPUMirroredMemoryBlock *first_index = new AprilMath::Int32GPUMirroredMemoryBlock(compare.getDense(sizes)+1); // build the matrix by sorting the coordinates (CSR or CSC order) and // filling values, indices and first_index memory blocks (*first_index)[0] = 0; AprilUtils::Sort(coordinates.begin(), coordinates.size(), compare); unsigned int j=0; for (unsigned int i=0; i(compare.getSparse(k)); } // process all remaining empty runs while(j < compare.getDense(sizes)) { ++j; (*first_index)[j] = NNZ; } return new SparseMatrix(static_cast(sizes.first), static_cast(sizes.second), values, indices, first_index, compare.getFormat()); } }; // class DOKBuilder ////////////////////////////////////////////////////////////////////////// /// Returns if the matrix is a vector bool isVector() const { return ( (matrixSize[0]==1) || (matrixSize[1]==1) ); } bool isColVector() const { return matrixSize[1]==1; } /********* Iterators for Matrix traversal *********/ // forward declaration class const_iterator; class iterator { friend class const_iterator; friend class SparseMatrix; SparseMatrix *m; // A weak reference. int idx; // T *values; int *indices; int *first_index; int first_index_pos; iterator(SparseMatrix *m, int idx=0); public: iterator(); iterator(const iterator &other); ~iterator(); iterator &operator=(const iterator &other); bool operator==(const iterator &other) const; bool operator!=(const iterator &other) const; iterator &operator++(); T &operator*(); T *operator->(); int getIdx() const { return idx; } void getCoords(int &x0, int &x1) const; }; /*******************************************************/ class const_iterator { friend class SparseMatrix; const SparseMatrix *m; // A weak reference. int idx; // const T *values; const int *indices; const int *first_index; int first_index_pos; const_iterator(const SparseMatrix *m, int idx=0); public: const_iterator(); const_iterator(const const_iterator &other); const_iterator(const iterator &other); /*const_iterator(const iterator &other);*/ ~const_iterator(); const_iterator &operator=(const const_iterator &other); const_iterator &operator=(const iterator &other); bool operator==(const const_iterator &other) const; bool operator==(const iterator &other) const; bool operator!=(const const_iterator &other) const; bool operator!=(const iterator &other) const; const_iterator &operator++(); const T &operator*() const; const T *operator->() const; int getIdx() const { return idx; } void getCoords(int &x0, int &x1) const; }; /*******************************************************/ private: // const version of iterators, for fast end() iterator calls. They are // allocated on-demand, so if end() methods are never executed, they // nerver will be initialized. mutable iterator end_iterator; mutable const_iterator end_const_iterator; SparseMatrix() : end_iterator(), end_const_iterator() { } void checkSortedIndices(bool sort=false); public: /********** Constructors ***********/ /// Constructor SparseMatrix(const int d0, const int d1, AprilMath::GPUMirroredMemoryBlock *values, AprilMath::Int32GPUMirroredMemoryBlock *indices, AprilMath::Int32GPUMirroredMemoryBlock *first_index, const SPARSE_FORMAT sparse_format = CSR_FORMAT, bool sort=false); /// Constructor given other matrix, it does a deep copy (clone). SparseMatrix(const SparseMatrix *other, SPARSE_FORMAT sparse_format = NONE_FORMAT); /// Sub-matrix constructor, makes a deep copy of the given matrix slice SparseMatrix(const SparseMatrix *other, const int *coords, const int *sizes, bool clone=true); /// Destructor virtual ~SparseMatrix(); /// Constructor given a dense Matrix, it returns a SparseMatrix static SparseMatrix *fromDenseMatrix(const Matrix *other, const SPARSE_FORMAT sparse_format = CSR_FORMAT, const T zero = T()); /// Constructor from a MMAP file static SparseMatrix *fromMMappedDataReader(AprilUtils::MMappedDataReader *mmapped_data); /// Writes to a file void toMMappedDataWriter(AprilUtils::MMappedDataWriter *mmapped_data) const; /* Getters and setters */ int getNumDim() const { return numDim; } const int *getDimPtr() const { return matrixSize; } int getDimSize(int i) const { return matrixSize[i]; } int size() const { return total_size; } // FIXME: use an attribute to improve the efficiency of this call /// Returns the Number of Non-Zero elements. int nonZeroSize() const { return static_cast(values->getSize()); } int getDenseCoordinateSize() const { if (sparse_format == CSR_FORMAT) return matrixSize[0]; else return matrixSize[1]; } int getCompressedCoordinateSize() const { if (sparse_format == CSR_FORMAT) return matrixSize[1]; else return matrixSize[0]; } SPARSE_FORMAT getSparseFormat() const { return sparse_format; } bool getIsDataRowOrdered() const { return sparse_format == CSR_FORMAT; } // UPDATE GPU OR PPAL IF NEEDED void sync() { #ifdef USE_CUDA values->forceSync(use_cuda); indices->forceSync(use_cuda); first_index->forceSync(use_cuda); #endif } void setUseCuda(bool v) { use_cuda = v; #ifdef USE_CUDA if (use_cuda) { values->updateMemGPU(); indices->updateMemGPU(); first_index->updateMemGPU(); } #endif } bool getCudaFlag() const { return use_cuda; } /**********************/ iterator begin() { return iterator(this); } iterator iteratorAt(int c0, int c1) { int idx = searchIndexOf(c0, c1); if (idx == -1) ERROR_EXIT2(128,"Incorrect given position (%d,%d)\n",c0,c1); return iterator(this, idx); } iterator iteratorAtFirst(int c0, int c1) { int idx = searchIndexOfFirst(c0, c1); return iterator(this, idx); } iterator iteratorAtRawIndex(int i) { return iterator(this,i); } const iterator &end() { if (end_iterator.m == 0) end_iterator = iterator(this, nonZeroSize()); return end_iterator; } /************************/ const_iterator begin() const { return const_iterator(this); } const_iterator iteratorAt(int c0, int c1) const { int idx = searchIndexOf(c0, c1); if (idx == -1) ERROR_EXIT2(128,"Incorrect given position (%d,%d)\n",c0,c1); return const_iterator(this, idx); } const_iterator iteratorAtFirst(int c0, int c1) const { int idx = searchIndexOfFirst(c0, c1); return const_iterator(this, idx); } const_iterator iteratorAtRawIndex(int i) const { return const_iterator(this,i); } const const_iterator &end() const { if (end_const_iterator.m == 0) end_const_iterator = const_iterator(this, nonZeroSize()); return end_const_iterator; } /// Symbolic transposition, changes the sparse format SparseMatrix* transpose(); /// Deep copy with different sparse format SparseMatrix *clone(SPARSE_FORMAT sparse_format = NONE_FORMAT) const; /// Returns an equivalent dense matrix Matrix *toDense() const; /// Number values check void pruneSubnormalAndCheckNormal(); /// This method sets to zero the shared counter void resetSharedCount() { shared_count = 0; } /// This method adds counts to the shared counter void addToSharedCount(unsigned int count=1) { shared_count += count; } /// Getter of the shared count value unsigned int getSharedCount() const { return shared_count; } /// Raw access operator [], access by index position T& operator[] (int i); const T& operator[] (int i) const; /// Access to independent elements // T& operator() (int row, int col); const T operator() (int row, int col) const; /// Function to obtain RAW access to data pointer. Be careful with it, because /// you are losing sub-matrix abstraction. AprilMath::GPUMirroredMemoryBlock *getRawValuesAccess() { return values.get(); } AprilMath::Int32GPUMirroredMemoryBlock *getRawIndicesAccess() { return indices.get(); } AprilMath::Int32GPUMirroredMemoryBlock *getRawFirstIndexAccess() { return first_index.get(); } const AprilMath::GPUMirroredMemoryBlock *getRawValuesAccess() const { return values.get(); } const AprilMath::Int32GPUMirroredMemoryBlock *getRawIndicesAccess() const { return indices.get(); } const AprilMath::Int32GPUMirroredMemoryBlock *getRawFirstIndexAccess() const { return first_index.get(); } /// Returns true if they have the same dimension template bool sameDim(const SparseMatrix *other) const; template bool sameDim(const Matrix *other) const; bool sameDim(const int d0, const int d1) const; //////////////////////////////////////////////////////////////////////////// bool isDiagonal() const { if (matrixSize[0] != matrixSize[1] || matrixSize[0] != nonZeroSize()) return false; for(const_iterator it(begin()); it!=end(); ++it) { int c0,c1; it.getCoords(c0,c1); if (c0 != c1) return false; } return true; } static SparseMatrix *diag(int N, T value=T(), SPARSE_FORMAT sparse_format = CSR_FORMAT) { unsigned int uN = static_cast(N); SparseMatrix *result; AprilMath::GPUMirroredMemoryBlock *values = new AprilMath::GPUMirroredMemoryBlock(uN); AprilMath::Int32GPUMirroredMemoryBlock *indices = new AprilMath::Int32GPUMirroredMemoryBlock(uN); AprilMath::Int32GPUMirroredMemoryBlock *first_index = new AprilMath::Int32GPUMirroredMemoryBlock(uN+1); T *values_ptr = values->getPPALForWrite(); int *indices_ptr = indices->getPPALForWrite(); int *first_index_ptr = first_index->getPPALForWrite(); first_index_ptr[0] = 0; for (unsigned int i=0; i(N, N, values, indices, first_index, sparse_format); return result; } static SparseMatrix *diag(Matrix *m, SPARSE_FORMAT sparse_format = CSR_FORMAT) { if (m->getNumDim() != 1) ERROR_EXIT(128, "Expected uni-dimensional matrix\n"); int N = m->getDimSize(0); unsigned int uN = static_cast(N); SparseMatrix *result; AprilMath::GPUMirroredMemoryBlock *values = new AprilMath::GPUMirroredMemoryBlock(uN); AprilMath::Int32GPUMirroredMemoryBlock *indices = new AprilMath::Int32GPUMirroredMemoryBlock(uN); AprilMath::Int32GPUMirroredMemoryBlock *first_index = new AprilMath::Int32GPUMirroredMemoryBlock(uN+1); T *values_ptr = values->getPPALForWrite(); int *indices_ptr = indices->getPPALForWrite(); int *first_index_ptr = first_index->getPPALForWrite(); first_index_ptr[0] = 0; typename Matrix::const_iterator it(m->begin()); for (unsigned int i=0; iend()); values_ptr[i] = *it; indices_ptr[i] = i; first_index_ptr[i+1] = i+1; } result = new SparseMatrix(N, N, values, indices, first_index, sparse_format); return result; } static SparseMatrix *diag(AprilMath::GPUMirroredMemoryBlock *values, SPARSE_FORMAT sparse_format = CSR_FORMAT) { unsigned int uN = values->getSize(); int N = static_cast(uN); SparseMatrix *result; AprilMath::Int32GPUMirroredMemoryBlock *indices = new AprilMath::Int32GPUMirroredMemoryBlock(uN); AprilMath::Int32GPUMirroredMemoryBlock *first_index = new AprilMath::Int32GPUMirroredMemoryBlock(uN+1); int *indices_ptr = indices->getPPALForWrite(); int *first_index_ptr = first_index->getPPALForWrite(); first_index_ptr[0] = 0; for (unsigned int i=0; i(N, N, values, indices, first_index, sparse_format); return result; } /// This method converts the caller SparseMatrix in a vector, unrolling the /// dimensions in row-major order. If the SparseMatrix is in CSR format, the /// resulting vector is a row vector, otherwise, it is a column vector. SparseMatrix *asVector() const; // SERIALIZATION virtual const char *luaCtorName() const { if (sparse_format == CSR_FORMAT) return "matrix.sparse.csr"; else return "matrix.sparse.csc"; } virtual int exportParamsToLua(lua_State *L) { lua_pushnumber(L, matrixSize[0]); lua_pushnumber(L, matrixSize[1]); AprilUtils::LuaTable:: pushInto*>(L, values.get()); AprilUtils::LuaTable:: pushInto(L, indices.get()); AprilUtils::LuaTable:: pushInto(L, first_index.get()); return 5; } /** * @brief Reads the SparseMatrix from a stream. * * Any key/value in @c options dictionary will be ignored. */ static SparseMatrix *read(AprilIO::StreamInterface *stream, const AprilUtils::LuaTable &options); /** * @brief Writes the SparseMatrix into a stream. * * The @c options dictionary can contain the following keys: * * - MatrixIO::ASCII_OPTION key contains a bool value indicating if the data * has to be binary or not. It uses AprilUtils::binarizer for * binarization purposes. By default it is true. */ virtual void write(AprilIO::StreamInterface *stream, const AprilUtils::LuaTable &options); private: void allocate_memory(int size); void release_memory(); void initialize(int d0, int d1); static AprilUtils::constString readULine(AprilIO::StreamInterface *stream, AprilIO::CStringStream *dest) { // Not needed, it is done in extractULineFromStream: dest->clear(); extractULineFromStream(stream, dest); return dest->getConstString(); } }; } // namespace Basics // must be defined here #include "matrix_ext.h" #include "sparse_matrix.impl.h" #include "sparse_matrix-iterators.impl.h" #include "sparse_matrix-serialization.impl.h" #include "sparse_matrixFloat.h" #include "sparse_matrixDouble.h" #include "sparse_matrixComplexF.h" #endif // SPARSE_MATRIX_H april-ann-0.4.1/packages/basics/matrix/c_src/sparse_matrix.impl.h000066400000000000000000000443741263004425400250220ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SPARSE_MATRIX_IMPL_H #define SPARSE_MATRIX_IMPL_H #include #include #include #include #include "error_print.h" #include "ignore_result.h" #include "pair.h" #include "qsort.h" #include "sparse_matrix.h" #include "swap.h" #include "vector.h" // Must be defined in this order. #include "matrix_ext.h" namespace Basics { template const unsigned int SparseMatrix::MATRIX_BINARY_VERSION = 0x00000001; template int SparseMatrix::searchIndexOf(const int c0, const int c1) const { int idx; switch(sparse_format) { case CSC_FORMAT: if (c1 >= matrixSize[1]) idx = nonZeroSize()+1; else idx = doSearchCSCSparseIndexOf(indices.get(), first_index.get(), c0, c1, use_cuda); break; case CSR_FORMAT: if (c0 >= matrixSize[0]) idx = nonZeroSize()+1; else idx = doSearchCSRSparseIndexOf(indices.get(), first_index.get(), c0, c1, use_cuda); break; default: ERROR_EXIT1(128, "Unrecognized format %d\n", sparse_format); idx=-1; } return idx; } template int SparseMatrix::searchIndexOfFirst(const int c0, const int c1) const { int idx; switch(sparse_format) { case CSC_FORMAT: if (c1 >= matrixSize[1]) idx = nonZeroSize()+1; else idx = doSearchCSCSparseIndexOfFirst(indices.get(), first_index.get(), c0, c1, use_cuda); break; case CSR_FORMAT: if (c0 >= matrixSize[0]) idx = nonZeroSize()+1; else idx = doSearchCSRSparseIndexOfFirst(indices.get(), first_index.get(), c0, c1, use_cuda); break; default: ERROR_EXIT1(128, "Unrecognized format %d\n", sparse_format); idx=-1; } return idx; } template struct SparseMatrixIndicesCmp { bool operator()(const AprilUtils::pair &a, const AprilUtils::pair &b) const { return a.first < b.first; } }; template void SparseMatrix::checkSortedIndices(bool sort) { const int dense_size = getDenseCoordinateSize(); const int compressed_size = getCompressedCoordinateSize(); // for index sort algorithm if (indices->getSize() != values->getSize()) ERROR_EXIT(256, "Different block sizes found in indices and values\n"); if (static_cast(first_index->getSize()) != dense_size+1) ERROR_EXIT1(256, "First index block size must be %d\n", dense_size+1); const int *indices_ptr = indices->getPPALForRead(); const int *first_index_ptr = first_index->getPPALForRead(); if (first_index_ptr[dense_size] != static_cast(values->getSize())) ERROR_EXIT2(256, "Incorrect last value of first_index block, " "found %d, expected %u\n", first_index_ptr[dense_size], values->getSize()); AprilUtils::vector< AprilUtils::pair > aux_index_sorted; for (int i=0; i= compressed_size)) ERROR_EXIT2(256, "Index out-of-bounds [%d] = %d\n", first_index_ptr[i], indices_ptr[first_index_ptr[i]]); for (int j=first_index_ptr[i]+1; j= indices_ptr[j]) need_sort = true; if (indices_ptr[j] < 0 || indices_ptr[j] >= compressed_size) ERROR_EXIT2(256, "Index out-of-bounds [%d] = %d\n", j, indices_ptr[j]); } if (need_sort) { if (!sort) ERROR_EXIT(256, "Found incorrect index order\n"); aux_index_sorted.clear(); T *values_ptr = values->getPPALForReadAndWrite(); int *indices_ptr = indices->getPPALForReadAndWrite(); for (int j=first_index_ptr[i]; j 0); AprilUtils::Sort(aux_index_sorted.begin(), 0, static_cast(aux_index_sorted.size())-1, SparseMatrixIndicesCmp()); int k=0; for (int j=first_index_ptr[i]; j void SparseMatrix::initialize(int d0, int d1) { if (d0 != 1 || d1 != 1) { if (d1 == 1 && sparse_format == CSR_FORMAT) { ERROR_EXIT(128, "Column vector unable with CSR format\n"); } else if (d0 == 1 && sparse_format == CSC_FORMAT) { ERROR_EXIT(128, "Row vector unable with CSC format\n"); } } total_size = d0*d1; matrixSize[0] = d0; matrixSize[1] = d1; } /// Allocation of memory for data pointer. template void SparseMatrix::allocate_memory(int size) { unsigned int sz = static_cast(size); values = new AprilMath::GPUMirroredMemoryBlock(sz); indices = new AprilMath::Int32GPUMirroredMemoryBlock(sz); first_index = new AprilMath::Int32GPUMirroredMemoryBlock(static_cast(getDenseCoordinateSize())+1); } /// Release of the memory allocated for data pointer. template void SparseMatrix::release_memory() { } /// Default constructor template SparseMatrix::SparseMatrix(const int d0, const int d1, AprilMath::GPUMirroredMemoryBlock *values, AprilMath::Int32GPUMirroredMemoryBlock *indices, AprilMath::Int32GPUMirroredMemoryBlock *first_index, const SPARSE_FORMAT sparse_format, bool sort) : AprilIO::Serializable(), shared_count(0), values(values), indices(indices), first_index(first_index), mmapped_data(0), sparse_format(sparse_format), use_cuda(false), end_iterator(), end_const_iterator() { initialize(d0, d1); if (this->first_index.empty()) { if ( (d1 == 1 && sparse_format == CSC_FORMAT) || (d0 == 1 && sparse_format == CSR_FORMAT) ) { this->first_index = new AprilMath::Int32GPUMirroredMemoryBlock(2); int *first_index_ptr = this->first_index->getPPALForWrite(); first_index_ptr[0] = 0; first_index_ptr[1] = static_cast(values->getSize()); } else { ERROR_EXIT(128, "NULL first_index block only allowed for " "column or row vectors, not matrices\n"); } } checkSortedIndices(sort); } #define NOT_IS_ZERO(it,zero) (zero) < (*it) || (*it) < -(zero) template SparseMatrix *SparseMatrix::fromDenseMatrix(const Matrix *dense, const SPARSE_FORMAT sparse_format, const T zero) { if (dense->getNumDim() != 2) { ERROR_EXIT(128, "Only allowed for bi-dimensional matrices\n"); } AprilUtils::UniquePtr< DOKBuilder > builder( new DOKBuilder() ); typename Matrix::const_iterator it(dense->begin()); for (int d0=0; d0getDimSize(0); ++d0) { for (int d1=0; d1getDimSize(1); ++d1, ++it) { assert(it != dense->end()); if (NOT_IS_ZERO(it, zero)) { builder->insert(d0, d1, *it); } } } return builder->build(dense->getDimSize(0), dense->getDimSize(1), sparse_format); } #undef NOT_IS_ZERO /// Constructor given other matrix, it does a deep copy (clone). template SparseMatrix::SparseMatrix(const SparseMatrix *other, SPARSE_FORMAT sparse_format) : AprilIO::Serializable(), shared_count(other->shared_count), mmapped_data(0), use_cuda(other->use_cuda), end_iterator(), end_const_iterator() { if (sparse_format == NONE_FORMAT) this->sparse_format = other->sparse_format; else this->sparse_format = sparse_format; initialize(other->matrixSize[0], other->matrixSize[1]); allocate_memory(static_cast(other->values->getSize())); if (this->sparse_format == other->sparse_format) { values->copyFromBlock(0u, other->values.get(), 0u, other->values->getSize()); indices->copyFromBlock(0u, other->indices.get(), 0u, other->indices->getSize()); first_index->copyFromBlock(0u, other->first_index.get(), 0, other->first_index->getSize()); } else { // Transformation between compressed sparse formats ERROR_EXIT(256, "Not implemented!!!\n"); } } /// Constructor for sub-matrix building template SparseMatrix::SparseMatrix(const SparseMatrix *other, const int *coords, const int *sizes, bool clone) : AprilIO::Serializable(), shared_count(0), mmapped_data(0), sparse_format(other->sparse_format), use_cuda(other->use_cuda), end_iterator(), end_const_iterator() { UNUSED_VARIABLE(clone); if (sizes[0] + coords[0] > other->matrixSize[0]) ERROR_EXIT3(128, "Size+coordinates are out of dimension size: %d+%d>%d\n", sizes[0], coords[0], other->matrixSize[0]); if (sizes[1] + coords[1] > other->matrixSize[1]) ERROR_EXIT3(128, "Size+coordinates are out of dimension size: %d+%d>%d\n", sizes[1], coords[1], other->matrixSize[1]); initialize(sizes[0], sizes[1]); int non_zero_size = 0; int x0=0, x1=0; for (const_iterator it(other->begin()); it != other->end(); ++it) { it.getCoords(x0,x1); if (x0 >= coords[0] && x0 < coords[0]+sizes[0] && x1 >= coords[1] && x1 < coords[1]+sizes[1]) ++non_zero_size; } allocate_memory(non_zero_size); T *values_ptr = values->getPPALForWrite(); int *indices_ptr = indices->getPPALForWrite(); int *first_index_ptr = first_index->getPPALForWrite(); int current=0; first_index_ptr[0] = 0; switch(sparse_format) { case CSC_FORMAT: { int x0=0, x1=0; for (const_iterator it(other->begin()); it != other->end(); ++it) { it.getCoords(x0,x1); if (coords[0] <= x0 && x0 < coords[0]+sizes[0] && coords[1] <= x1 && x1 < coords[1]+sizes[1]) { values_ptr[current] = *it; indices_ptr[current] = x0-coords[0]; ++current; first_index_ptr[x1-coords[1]+1] = current; } } } break; case CSR_FORMAT: { int x0=0, x1=0; for (const_iterator it(other->begin()); it != other->end(); ++it) { it.getCoords(x0,x1); if (coords[0] <= x0 && x0 < coords[0]+sizes[0] && coords[1] <= x1 && x1 < coords[1]+sizes[1]) { values_ptr[current] = *it; indices_ptr[current] = x1-coords[1]; ++current; first_index_ptr[x0-coords[0]+1] = current; } } } break; default: ERROR_EXIT1(128, "Unrecognized format %d\n", sparse_format); } } template SparseMatrix *SparseMatrix:: fromMMappedDataReader(AprilUtils::MMappedDataReader *mmapped_data) { AprilUtils::SharedPtr< SparseMatrix > obj = new SparseMatrix(); // obj->values = AprilMath::GPUMirroredMemoryBlock::fromMMappedDataReader(mmapped_data); obj->indices = AprilMath::Int32GPUMirroredMemoryBlock::fromMMappedDataReader(mmapped_data); obj->first_index = AprilMath::Int32GPUMirroredMemoryBlock::fromMMappedDataReader(mmapped_data); // unsigned int binary_version = *(mmapped_data->get()); if (binary_version != MATRIX_BINARY_VERSION) ERROR_EXIT1(128, "Incorrect binary matrix version from commit number %d\n", mmapped_data->getCommitNumber()); int *aux_size = mmapped_data->get(2); obj->matrixSize[0] = aux_size[0]; obj->matrixSize[1] = aux_size[1]; obj->total_size = *(mmapped_data->get()); obj->sparse_format = *(mmapped_data->get()); // NON MAPPED DATA obj->use_cuda = false; obj->shared_count = 0; // THE MMAP POINTER obj->mmapped_data = mmapped_data; // return obj.weakRelease(); } template void SparseMatrix::toMMappedDataWriter(AprilUtils::MMappedDataWriter *mmapped_data) const { values->toMMappedDataWriter(mmapped_data); indices->toMMappedDataWriter(mmapped_data); first_index->toMMappedDataWriter(mmapped_data); mmapped_data->put(&MATRIX_BINARY_VERSION); mmapped_data->put(matrixSize, 2); mmapped_data->put(&total_size); mmapped_data->put(&sparse_format); } template SparseMatrix::~SparseMatrix() { release_memory(); } template SparseMatrix *SparseMatrix::transpose() { SparseMatrix *result = new SparseMatrix(matrixSize[1], matrixSize[0], values.get(), indices.get(), first_index.get(), (sparse_format == CSR_FORMAT) ? CSC_FORMAT : CSR_FORMAT, false); return result; } template SparseMatrix *SparseMatrix::clone(SPARSE_FORMAT sparse_format) const { return new SparseMatrix(this, sparse_format); } template T& SparseMatrix::operator[] (int i) { return values->get(static_cast(i)); } template const T& SparseMatrix::operator[] (int i) const { return values->get(static_cast(i)); } template const T SparseMatrix::operator() (int row, int col) const { int idx = searchIndexOf(row,col); if (idx < 0) return T(); return (*values)[idx]; } template template bool SparseMatrix::sameDim(const SparseMatrix *other) const { return ( sparse_format == other->sparse_format && sameDim(other->getDimSize(0), other->getDimSize(1)) ); } template template bool SparseMatrix::sameDim(const Matrix *other) const { return ( other->getNumDim() == 2 && sameDim(other->getDimSize(0), other->getDimSize(1)) ); } template bool SparseMatrix::sameDim(const int row, const int col) const { return (row == matrixSize[0]) && (col == matrixSize[1]); } template void SparseMatrix::pruneSubnormalAndCheckNormal() { ERROR_EXIT(128, "NOT IMPLEMENTED!!!\n"); } template Matrix *SparseMatrix::toDense() const { AprilUtils::SharedPtr< Matrix > result = new Matrix(2, matrixSize); typename Matrix::random_access_iterator result_it(result.get()); AprilMath::MatrixExt::Initializers::matZeros(result.get()); int x0=0,x1=0; for (const_iterator it(begin()); it != end(); ++it) { it.getCoords(x0,x1); result_it(x0,x1) = *it; } return result.weakRelease(); } template SparseMatrix *SparseMatrix::asVector() const { int sz = matrixSize[0]*matrixSize[1]; const int *this_indices_ptr = indices->getPPALForRead(); const int *this_first_index_ptr = first_index->getPPALForRead(); // bool sort=false; AprilMath::GPUMirroredMemoryBlock *result_values = values->clone(); AprilMath::Int32GPUMirroredMemoryBlock *result_indices = new AprilMath::Int32GPUMirroredMemoryBlock(nonZeroSize()); AprilMath::Int32GPUMirroredMemoryBlock *result_first_index = new AprilMath::Int32GPUMirroredMemoryBlock(2); // int *result_indices_ptr = result_indices->getPPALForWrite(); int *result_first_index_ptr = result_first_index->getPPALForWrite(); result_first_index_ptr[0] = 0; result_first_index_ptr[1] = nonZeroSize(); // int d0,d1; switch(sparse_format) { case CSR_FORMAT: d0=1; d1=sz; for (int row=0; row *result = new SparseMatrix(d0, d1, result_values, result_indices, result_first_index, sparse_format, sort); return result; } } // namespace Basics #endif // SPARSE_MATRIX_IMPL_H april-ann-0.4.1/packages/basics/matrix/c_src/sparse_matrixComplexF.cc000066400000000000000000000027311263004425400256450ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include "sparse_matrixComplexF.h" using AprilMath::ComplexF; /////////////////////////////////////////////////////////////////////////////// namespace Basics { namespace MatrixIO { template<> int SparseAsciiSizer::operator()(const SparseMatrix *mat) { return mat->nonZeroSize()*26; } template<> int SparseBinarySizer::operator()(const SparseMatrix *mat) { return AprilUtils::binarizer::buffer_size_32(mat->nonZeroSize()<<1); } } ////////////////////////////////////////////////////////////////////////// template class SparseMatrix; } april-ann-0.4.1/packages/basics/matrix/c_src/sparse_matrixComplexF.h000066400000000000000000000034101263004425400255020ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SPARSEMATRIXCOMPLEX_H #define SPARSEMATRIXCOMPLEX_H #include "matrixComplexF.h" /////////////////////////////////////////////////////////////////////////////// namespace Basics { namespace MatrixIO { /* Especialization of SparseMatrixComplexF ascii and binary sizers */ template<> int SparseAsciiSizer::operator()(const SparseMatrix *mat); template<> int SparseBinarySizer::operator()(const SparseMatrix *mat); } ///////////////////////////////////////////////////////////////////////// typedef SparseMatrix SparseMatrixComplexF; typedef SparseMatrix::DOKBuilder DOKBuilderSparseMatrixComplexF; } //////////////////////////////////////////////////////////////////////////// DECLARE_LUA_TABLE_BIND_SPECIALIZATION(Basics::SparseMatrixComplexF); #endif // SPARSEMATRIXCOMPLEXF_H april-ann-0.4.1/packages/basics/matrix/c_src/sparse_matrixDouble.cc000066400000000000000000000026561263004425400253500ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include "sparse_matrixDouble.h" /////////////////////////////////////////////////////////////////////////////// namespace Basics { namespace MatrixIO { template<> int SparseAsciiSizer::operator()(const SparseMatrix *mat) { return mat->nonZeroSize()*12; } template<> int SparseBinarySizer::operator()(const SparseMatrix *mat) { return AprilUtils::binarizer::buffer_size_64(mat->nonZeroSize()); } } ////////////////////////////////////////////////////////////////////////// template class SparseMatrix; } april-ann-0.4.1/packages/basics/matrix/c_src/sparse_matrixDouble.h000066400000000000000000000032541263004425400252050ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SPARSEMATRIXDOUBLE_H #define SPARSEMATRIXDOUBLE_H #include "matrixDouble.h" /////////////////////////////////////////////////////////////////////////////// namespace Basics { namespace MatrixIO { /* Especialization of SparseMatrixDouble ascii and binary sizers */ template<> int SparseAsciiSizer::operator()(const SparseMatrix *mat); template<> int SparseBinarySizer::operator()(const SparseMatrix *mat); } ///////////////////////////////////////////////////////////////////////// typedef SparseMatrix SparseMatrixDouble; typedef SparseMatrix::DOKBuilder DOKBuilderSparseMatrixDouble; } //////////////////////////////////////////////////////////////////////////// DECLARE_LUA_TABLE_BIND_SPECIALIZATION(Basics::SparseMatrixDouble); #endif // SPARSEMATRIXDOUBLE_H april-ann-0.4.1/packages/basics/matrix/c_src/sparse_matrixFloat.cc000066400000000000000000000026501263004425400251750ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include "sparse_matrixFloat.h" /////////////////////////////////////////////////////////////////////////////// namespace Basics { namespace MatrixIO { template<> int SparseAsciiSizer::operator()(const SparseMatrix *mat) { return mat->nonZeroSize()*12; } template<> int SparseBinarySizer::operator()(const SparseMatrix *mat) { return AprilUtils::binarizer::buffer_size_32(mat->nonZeroSize()); } } ////////////////////////////////////////////////////////////////////////// template class SparseMatrix; } april-ann-0.4.1/packages/basics/matrix/c_src/sparse_matrixFloat.h000066400000000000000000000032361263004425400250400ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2014, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef SPARSEMATRIXFLOAT_H #define SPARSEMATRIXFLOAT_H #include "matrixFloat.h" /////////////////////////////////////////////////////////////////////////////// namespace Basics { namespace MatrixIO { /* Especialization of SparseMatrixFloat ascii and binary sizers */ template<> int SparseAsciiSizer::operator()(const SparseMatrix *mat); template<> int SparseBinarySizer::operator()(const SparseMatrix *mat); } ///////////////////////////////////////////////////////////////////////// typedef SparseMatrix SparseMatrixFloat; typedef SparseMatrix::DOKBuilder DOKBuilderSparseMatrixFloat; } //////////////////////////////////////////////////////////////////////////// DECLARE_LUA_TABLE_BIND_SPECIALIZATION(Basics::SparseMatrixFloat); #endif // SPARSEMATRIXFLOAT_H april-ann-0.4.1/packages/basics/matrix/c_src/utilMatrixChar.cc000066400000000000000000000016001263004425400242600ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "utilMatrixChar.h" namespace Basics { } // namespace Basics april-ann-0.4.1/packages/basics/matrix/c_src/utilMatrixChar.h000066400000000000000000000017121263004425400241260ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef UTILMATRIXCHAR_H #define UTILMATRIXCHAR_H #include "matrixChar.h" namespace Basics { } // namespace Basics #endif // UTILMATRIXCHAR_H april-ann-0.4.1/packages/basics/matrix/c_src/utilMatrixComplexF.cc000066400000000000000000000073441263004425400251330ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "ignore_result.h" #include "utilMatrixComplexF.h" using AprilMath::ComplexF; namespace Basics { MatrixFloat *convertFromMatrixComplexFToMatrixFloat(MatrixComplexF *mat) { MatrixFloat *new_mat; int N = mat->getNumDim(); int *dims = new int[N+1]; // the real and imaginary part are the last dimension (they are stored // together in row major) for (int i=0; igetDimPtr()[i]; dims[N] = 2; AprilMath::FloatGPUMirroredMemoryBlock *new_mat_memory; new_mat_memory = mat->getRawDataAccess()->reinterpretAs(); new_mat=new MatrixFloat(N+1, dims, new_mat_memory); #ifdef USE_CUDA new_mat->setUseCuda(mat->getCudaFlag()); #endif delete[] dims; return new_mat; } void applyConjugateInPlace(MatrixComplexF *mat) { for (MatrixComplexF::iterator it(mat->begin()); it != mat->end(); ++it) { it->conj(); } } MatrixFloat *realPartFromMatrixComplexFToMatrixFloat(MatrixComplexF *mat) { MatrixFloat *new_mat = new MatrixFloat(mat->getNumDim(), mat->getDimPtr()); #ifdef USE_CUDA new_mat->setUseCuda(mat->getCudaFlag()); #endif MatrixComplexF::const_iterator orig_it(mat->begin()); MatrixFloat::iterator dest_it(new_mat->begin()); while(orig_it != mat->end()) { *dest_it = orig_it->real(); ++orig_it; ++dest_it; } return new_mat; } MatrixFloat *imgPartFromMatrixComplexFToMatrixFloat(MatrixComplexF *mat) { MatrixFloat *new_mat = new MatrixFloat(mat->getNumDim(), mat->getDimPtr()); #ifdef USE_CUDA new_mat->setUseCuda(mat->getCudaFlag()); #endif MatrixComplexF::const_iterator orig_it(mat->begin()); MatrixFloat::iterator dest_it(new_mat->begin()); while(orig_it != mat->end()) { *dest_it = orig_it->img(); ++orig_it; ++dest_it; } return new_mat; } MatrixFloat *absFromMatrixComplexFToMatrixFloat(MatrixComplexF *mat) { MatrixFloat *new_mat = new MatrixFloat(mat->getNumDim(), mat->getDimPtr()); #ifdef USE_CUDA new_mat->setUseCuda(mat->getCudaFlag()); #endif MatrixComplexF::const_iterator orig_it(mat->begin()); MatrixFloat::iterator dest_it(new_mat->begin()); while(orig_it != mat->end()) { *dest_it = orig_it->abs(); ++orig_it; ++dest_it; } return new_mat; } MatrixFloat *angleFromMatrixComplexFToMatrixFloat(MatrixComplexF *mat) { MatrixFloat *new_mat = new MatrixFloat(mat->getNumDim(), mat->getDimPtr()); #ifdef USE_CUDA new_mat->setUseCuda(mat->getCudaFlag()); #endif MatrixComplexF::const_iterator orig_it(mat->begin()); MatrixFloat::iterator dest_it(new_mat->begin()); while(orig_it != mat->end()) { *dest_it = orig_it->angle(); ++orig_it; ++dest_it; } return new_mat; } } // namespace Basics april-ann-0.4.1/packages/basics/matrix/c_src/utilMatrixComplexF.h000066400000000000000000000026721263004425400247740ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef UTILMATRIXCOMPLEXF_H #define UTILMATRIXCOMPLEXF_H #include "complex_number.h" #include "matrixComplexF.h" #include "matrixFloat.h" namespace Basics { MatrixFloat *convertFromMatrixComplexFToMatrixFloat(MatrixComplexF *mat); void applyConjugateInPlace(MatrixComplexF *mat); MatrixFloat *realPartFromMatrixComplexFToMatrixFloat(MatrixComplexF *mat); MatrixFloat *imgPartFromMatrixComplexFToMatrixFloat(MatrixComplexF *mat); MatrixFloat *absFromMatrixComplexFToMatrixFloat(MatrixComplexF *mat); MatrixFloat *angleFromMatrixComplexFToMatrixFloat(MatrixComplexF *mat); } // namespace Basics #endif // UTILMATRIXCOMPLEXF_H april-ann-0.4.1/packages/basics/matrix/c_src/utilMatrixDouble.cc000066400000000000000000000016611263004425400246240ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "constString.h" #include "error_print.h" #include "utilMatrixDouble.h" namespace Basics { } // namespace Basics april-ann-0.4.1/packages/basics/matrix/c_src/utilMatrixDouble.h000066400000000000000000000017511263004425400244660ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef UTILMATRIXDOUBLE_H #define UTILMATRIXDOUBLE_H #include "matrixFloat.h" #include "matrixDouble.h" namespace Basics { } // namespace Basics #endif // UTILMATRIXDOUBLE_H april-ann-0.4.1/packages/basics/matrix/c_src/utilMatrixFloat.cc000066400000000000000000000167551263004425400244710ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Salvador España-Boquera, Francisco Zamora-Martinez * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include #include #include "clamp.h" #include "constString.h" #include "utilMatrixFloat.h" using AprilUtils::clamp; using AprilUtils::constString; namespace Basics { inline int hexdigit(char c) { if ('0'<=c && c<='9') return c-'0'; if ('A'<=c && c<='F') return c-'A'+10; else return c-'a'+10; } MatrixFloat* readMatrixFloatHEX(int width, int height, constString cs) { float normaliza = 1.0/255; int dims[2]; // dims[0] is height, dims[1] is width dims[1] = width; dims[0] = height; MatrixFloat *mat = new MatrixFloat(2,dims); MatrixFloat::iterator it(mat->begin()); int size2 = 2*width*height; for (int i=0; i> 3)) return 0; mat = new MatrixFloat(2,dims); MatrixFloat::iterator it(mat->begin()); const char *b = cs; int k=0; int vector_pos = 0; for (int row=0; row> (7-vector_offset)) & 0x01); *it = clamp(CTENEGRO + (CTEBLANCO-CTENEGRO)*brillo,CTEBLANCO,CTENEGRO); if (vector_offset == 7) { if (col+1 != dims[0]) vector_pos = vector_pos + 1; } vector_offset = (vector_offset + 1) % 8; } vector_pos = vector_pos + 1; } } else if (formato == "P5") { // PGM BINARY if (!linea.extract_int(&maxval)) return 0; float normaliza = 1.0/maxval; if (cs.len() < npixels) return 0; if (forcecolor) { // We make the 3 values to be equal mat = new MatrixFloat(3,dims); MatrixFloat::iterator it(mat->begin()); const char *b = cs; for (unsigned int i=0;ibegin()); const char *b = cs; for (unsigned int i=0;ibegin()); const char *b = cs; // gray = .3 * red + .59 * green + .11 * blue normaliza *= 0.01; for (unsigned int i=0;ibegin()); const char *b = cs; // This loop does not work because in both cases we have 3-tuples // with values of the same pixel npixels *= 3; for (unsigned int i=0;igetNumDim() < 2) || (mat->getNumDim() > 3)) { *buffer = 0; return 0; } int i,ancho,alto,prof,sizedata,sizeheader = 100; ancho = mat->getDimSize(1); alto = mat->getDimSize(0); prof = (mat->getNumDim() == 3) ? mat->getDimSize(2) : 1; if (prof != 1 && prof != 3) { *buffer = 0; return 0; } sizedata = ancho*alto*prof; char *r,*b; r = b = new char[sizedata+sizeheader]; r += sprintf(r,"%s\n%d %d\n255\n", ((prof == 1) ? "P5" : "P6"),ancho,alto); float f; MatrixFloat::const_iterator it(mat->begin()); for (i=0;igetNumDim() != 2) { *buffer = 0; return 0; } int i,ancho,alto,sizedata,sizedata2; ancho = mat->getDimSize(1); alto = mat->getDimSize(0); sizedata = ancho*alto; sizedata2 = 2*ancho*alto; char *r,*b; r = b = new char[sizedata2+1]; float f; MatrixFloat::const_iterator it(mat->begin()); for (i=0;i* readMatrixFloatHEX(int width, int height, AprilUtils::constString cs); const float CTENEGRO = 1.0f; const float CTEBLANCO = 0.0f; Matrix* readMatrixFloatPNM(AprilUtils::constString cs, bool forcecolor=false, bool forcegray=false); int saveMatrixFloatPNM(Matrix *mat, char **buffer); int saveMatrixFloatHEX(Matrix *mat, char **buffer, int *width, int *height); ////////////////////////////////////////////////////////////////////////////// } // namespace Basics #endif // UTILMATRIXFLOAT_H april-ann-0.4.1/packages/basics/matrix/c_src/utilMatrixInt32.cc000066400000000000000000000015761263004425400243160ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "utilMatrixInt32.h" namespace Basics { } // namespace Basics april-ann-0.4.1/packages/basics/matrix/c_src/utilMatrixInt32.h000066400000000000000000000017471263004425400241600ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2013, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef UTILMATRIXINT32_H #define UTILMATRIXINT32_H #include "matrixInt32.h" #include "matrixFloat.h" namespace Basics { } // namespace Basics #endif // UTILMATRIXINT32_H april-ann-0.4.1/packages/basics/matrix/doc/000077500000000000000000000000001263004425400204705ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/matrix/doc/matrix_user.dox000066400000000000000000000043161263004425400235520ustar00rootroot00000000000000/** \page matrix Matrix Muchos algoritmos que requieren trabajar con conjuntos de datos requieren muestras con el mismo número de elementos. Así, parece muy natural utilizar una matriz donde cada fila es una muestra. El número de filas coincide con el número de muestras a presentar al algoritmo. El número de columnas correspondería con el tamaño de cada patrón. april permite definir matrices de varias maneras utilizando la clase matrix, la forma más sencilla es mediante matrix.fromString, por ejemplo: \verbatim xor_in = matrix.fromString[[ # podemos añadir lineas de comentarios cuando queramos # basta con situar un '#' al principio de la linea # la primera linea contiene el numero de componentes en cada dimension 4 2 # el numero de dimensiones se obtiene implicitamente # la siguiente linea contiene el tipo de representacion, ascii o binary ascii # luego vienen los valores propiamente dichos separados por espacio, # tabulador, enter, coma, punto y coma 0 0 0 1 1 0 1 1 ]] xor_out = matrix.fromString"4 1\nascii\n0 1 1 0" -- o incluso asi \endverbatim De manera que están definidas las siguientes funciones para cargar y salvar matrices: \verbatim function matrix.loadfile(filename) local f = io.open(filename,"r") local b = f:read("*a") f:close() return matrix.fromString(b) end \endverbatim \verbatim function matrix.savefile(matrix,filename,format) local f = io.open(filename,"w") f:write(matrix:toString(format)) f:close() end \endverbatim Podemos consultar las dimensiones de una matrix utilizando el método dim que devuelve una tabla con el tamaño de cada dimensión de la manera siguiente: \verbatim print("La matriz xor_in tiene dimensiones {".. table.concat(m_in:dim(),",").."}") --> La matriz xor_in tiene dimensiones {4,2} \endverbatim \verbatim m1 = matrix(2,3) --> matrix de 2x3 m2 = matrix(2,2,{1,2,3,4}) --> el último argumento puede ser --> una tabla con los valores m3 = matrix(unpack(m1:dim())) --> matriz del mismo tamaño que m1 m3:fill(2) --> rellenar la matriz con un valor m4 = matrix(3) m4:set{1,2,3} --> dar valores a una matriz ya creada \endverbatim */ april-ann-0.4.1/packages/basics/matrix/lua_src/000077500000000000000000000000001263004425400213535ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/matrix/lua_src/generic_call.lua000066400000000000000000000016441263004425400244720ustar00rootroot00000000000000-- GENERIC __CALL METAMETHOD matrix.__generic__ = matrix.__generic__ or {} matrix.__generic__.__make_generic_call__ = function(matrix_class) assert(matrix_class and class.is_class(matrix_class), "__make_generic_call__: Needs a class table as argument") class.extend_metamethod(matrix_class, "__call", matrix_class.__call_function__) end matrix.__generic__.__make_generic_index__ = function(matrix_class) assert(matrix_class and class.is_class(matrix_class), "__make_generic_index__: Needs a class table as argument") class.declare_functional_index(matrix_class, matrix_class.__index_function__) end matrix.__generic__.__make_generic_newindex__ = function(matrix_class) assert(matrix_class and class.is_class(matrix_class), "__make_generic_newindex__: Needs a class table as argument") return matrix_class.__newindex_function__ end april-ann-0.4.1/packages/basics/matrix/lua_src/generic_index_methods.lua000066400000000000000000000144631263004425400264140ustar00rootroot00000000000000matrix = matrix or {} matrix.__generic__ = matrix.__generic__ or {} local function old_index(self,dim,idx) assert(type(dim) == "number", "Needs a number as first argument") if type(idx) == "table" then idx = matrixInt32(idx) elseif class.is_a(idx, matrixBool) then idx = idx:to_index() end if not idx then return nil end assert(class.is_a(idx, matrixInt32), "Needs a matrixInt32 second argument (index)") local idx = idx:squeeze() assert(#idx:dim() == 1, "Needs a rank 1 tensor as second argument (index)") local d = self:dim() assert(dim >= 1 and dim <= #d, "Dimension argument out-of-bounds") local dim_bound = d[dim] d[dim] = idx:size() local ctor = class.of(self) local result = ctor(table.unpack(d)) if self:size() == dim_bound then local self = self:squeeze() local result = result:squeeze() for i=1,#idx do local p = idx[i] april_assert(p >= 1 and p <= dim_bound, "Index number %d out-of-bounds", i) result[i] = self[p] end else d[dim] = 1 local self_sw = self:sliding_window{ size=d, step=d } local dest_sw = result:sliding_window{ size=d, step=d } local result_submat,self_submat for i=1,#idx do local p = idx[i] april_assert(p >= 1 and p <= dim_bound, "Index number %d out-of-bounds", p) assert(not dest_sw:is_end()) self_sw:set_at_window(p) result_submat = dest_sw:get_matrix(result_submat) self_submat = self_sw:get_matrix(self_submat) result_submat:copy(self_submat) dest_sw:next() end end return result end local function old_index_fill_function(self,dim,idx,val) assert(type(dim) == "number", "Needs a number as first argument") if type(idx) == "table" then idx = matrixInt32(idx) elseif class.is_a(idx, matrixBool) then idx = idx:to_index() end if not idx then return self end assert(class.is_a(idx, matrixInt32), "Needs a matrixInt32 second argument (index)") local idx = idx:squeeze() assert(#idx:dim() == 1, "Needs a rank 1 tensor as second argument (index)") local d = self:dim() assert(dim >= 1 and dim <= #d,"Dimension argument out-of-bounds") local dim_bound = d[dim] if dim_bound == self:size() then local self = self:squeeze() for i=1,#idx do local p = idx[i] april_assert(p >= 1 and p <= dim_bound, "Index number %d out-of-bounds", i) self[p] = val end else d[dim] = 1 local sw = self:sliding_window{ size=d, step=d } local mat for i=1,#idx do local p = idx[i] april_assert(p >= 1 and p <= dim_bound, "Index number %d out-of-bounds", i) sw:set_at_window(p) mat = sw:get_matrix(mat) mat:fill(val) end end return self end local function old_index_copy_function(self,dim,idx,other) assert(type(dim) == "number", "Needs a number as first argument") if type(idx) == "table" then idx = matrixInt32(idx) elseif class.is_a(idx, matrixBool) then idx = idx:to_index() end if not idx then return self end assert(class.is_a(idx, matrixInt32), "Needs a matrixInt32 second argument (index)") assert(class.of(self) == class.of(other), "Self and other must be same matrix type") local idx = idx:squeeze() assert(#idx:dim() == 1, "Needs a rank 1 tensor as second argument (index)") local d = self:dim() assert(dim >= 1 and dim <= #d,"Dimension argument out-of-bounds") local dim_bound = d[dim] local d2 = self:dim() d2[dim] = #idx assert(other:same_dim(d2), "Incompatible matrix sizes") if dim_bound == self:size() then local self = self:squeeze() local other = other:squeeze() for i=1,#idx do local p = idx[i] april_assert(p >= 1 and p <= dim_bound, "Index number %d out-of-bounds", i) self[p] = other[i] end else d[dim] = 1 local other_sw = other:sliding_window{ size=d, step=d } local self_sw = self:sliding_window{ size=d, step=d } local other_submat,self_submat for i=1,#idx do local p = idx[i] april_assert(p >= 1 and p <= dim_bound, "Index number %d out-of-bounds", i) assert(not other_sw:is_end()) self_sw:set_at_window(p) other_submat = other_sw:get_matrix(other_submat) self_submat = self_sw:get_matrix(self_submat) self_submat:copy(other_submat) other_sw:next() end end return self end function matrix.__generic__.__make_index_methods__(cls) april_set_doc(cls .. "index", { class = "method", summary = { "Returns new allocated matrix filtered by the given dim and", "index matrix parameters.", }, params = { "A dimension number", { "A table, matrixBool or matrixInt32 indicating which", "indices will be taken." }, }, outputs = { { "A new allocated matrix instance, or nil if 2nd argument", "has zero selected components", }, }, }) april_set_doc(cls .. "indexed_fill", { class = "method", summary = { "Fills the indexed dim,index components of the caller matrix.", }, params = { "A dimension number", { "A table, matrixBool or matrixInt32 indicating which", "indices will be taken." }, "A number value for filling.", }, outputs = { "The caller matrix.", }, }) april_set_doc(cls .. "indexed_copy", { class = "method", summary = { "Copies a matrix into the indexed dim,index components of the caller matrix.", }, params = { "A dimension number", { "A table, matrixBool or matrixInt32 indicating which", "indices will be taken." }, "A matrix with data to be copied.", }, outputs = { "The caller matrix.", }, }) end april-ann-0.4.1/packages/basics/matrix/lua_src/generic_join.lua000066400000000000000000000032371263004425400245160ustar00rootroot00000000000000-- GENERIC JOIN FUNCTION matrix.__generic__ = matrix.__generic__ or {} matrix.__generic__.__make_generic_join__ = function() return function(dim, ...) local arg = table.pack(...) if type(arg[1]) == "table" then assert(#arg == 1, "Use one table argument or multiple matrix arguments") arg = arg[1] end assert(#arg > 0, "At least one matrix is needed") local ctor = class.of(arg[1]) local size = arg[1]:dim() if dim == 0 then local new_arg = {} for i=1,#arg do new_arg[i] = arg[i]:left_inflate() end arg, dim, size = new_arg, 1, new_arg[1]:dim() elseif dim == #size+1 then local new_arg = {} for i=1,#arg do new_arg[i] = arg[i]:right_inflate() end arg, dim, size = new_arg, #size+1, new_arg[1]:dim() else -- ERROR CHECK assert(dim >= 1 and dim <= #size, "Incorrect given dimension number, or incorrect first matrix size") end size[dim] = 0 for i=1,#arg do local m = arg[i] local d = m:dim() assert(#d == #size, "All the matrices must have the same number of dimensions") size[dim] = size[dim] + d[dim] for j=1,dim-1 do assert(size[j] == d[j], "Incorrect dimension size") end for j=dim+1,#size do assert(size[j] == d[j], "Incorrect dimension size") end end -- JOIN local outm = ctor(table.unpack(size)) local first = iterator.duplicate(1):take(#size):table() for i=1,#arg do local m = arg[i] local d = m:dim() size[dim] = d[dim] local outm_slice = outm:slice(first, size) outm_slice:copy(m) first[dim] = first[dim] + size[dim] end return outm end end april-ann-0.4.1/packages/basics/matrix/lua_src/generic_print.lua000066400000000000000000000033751263004425400247160ustar00rootroot00000000000000-- GENERIC PRINT FUNCTION matrix.__generic__ = matrix.__generic__ or {} matrix.__generic__.__make_generic_print__ = function(name,getter) assert(name and getter) return function(self) local MAX_ROW_LEN,MAX_ROWS = 60,6 local dims = self:dim() local coords = {} local out = {} local row = {} local row_len = 0 for i=1,#dims do coords[i]=1 end for i=1,self:size() do if #dims > 2 and coords[#dims] == 1 and coords[#dims-1] == 1 then table.insert(out, string.format("\n# pos [%s]", table.concat(coords, ","))) end if not coords[#coords-1] or coords[#coords-1] < MAX_ROWS or coords[#coords-1] == dims[#coords-1] then if row_len < MAX_ROW_LEN or coords[#coords] == dims[#coords] then local str = getter(self:get(table.unpack(coords))) row_len = row_len + #str + 1 if row_len < MAX_ROW_LEN or coords[#coords] == dims[#coords] then table.insert(row, str) else table.insert(row, "...") end end elseif coords[#coords-1] == MAX_ROWS then row = { "..." } end local j=#dims+1 repeat j=j-1 coords[j] = coords[j] + 1 if coords[j] > dims[j] then coords[j] = 1 end until j==1 or coords[j] ~= 1 if coords[#coords] == 1 then if #row > 0 then table.insert(out, table.concat(row, " ")) row={} row_len = 0 end end end table.insert(out, string.format("# %s of size [%s] stride [%s] ref [%s]\n", name, table.concat(dims, ","), table.concat(self:stride(), ","), self:get_reference_string())) return table.concat(out, "\n") end end april-ann-0.4.1/packages/basics/matrix/lua_src/generic_serialization.lua000066400000000000000000000150601263004425400264310ustar00rootroot00000000000000local function archive_wrapper(s) if class.is_a(s, aprilio.package) then assert(s:number_of_files() == 1, "Expected only 1 file in the package") return s:open(1) else return s end end matrix.__generic__ = matrix.__generic__ or {} matrix.__generic__.__make_generic_to_lua_string__ = function(matrix_class, defmode) local name = matrix_class.meta_instance.id class.extend(matrix_class, "to_lua_string", function(self, format) return string.format("%s.fromString[[%s]]", name, self:toString(format or defmode)) end) end -- GENERIC FROM FILENAME matrix.__generic__.__make_generic_fromFilename__ = function(matrix_class) matrix_class.fromFilename = function(filename) local f = april_assert(io.open(filename), "Unable to open %s", filename) local ret = table.pack(matrix_class.read(archive_wrapper( f ))) f:close() return table.unpack(ret) end end -- GENERIC FROM TAB FILENAME matrix.__generic__.__make_generic_fromTabFilename__ = function(matrix_class) matrix_class.fromTabFilename = function(filename) local f = april_assert(io.open(filename), "Unable to open %s", filename) local ret = table.pack(matrix_class.read(archive_wrapper( f ), { [matrix.options.tab] = true })) f:close() return table.unpack(ret) end end matrix.__generic__.__make_generic_fromCSVFilename__ = function(matrix_class) matrix_class.fromCSVFilename = function(filename,args) local args = get_table_fields({ [matrix.options.delim] = { mandatory=true, type_match="string", default="," }, [matrix.options.default] = { mandatory=false }, header = { type_match="boolean" }, [matrix.options.map] = { mandatory=false, type_match="table", }, }, args) local header = args.header args.header = nil args[matrix.options.empty] = true args[matrix.options.tab] = true local f = april_assert(io.open(filename), "Unable to open %s", filename) local f = archive_wrapper( f ) if header then header = string.tokenize(f:read("*l"), args[matrix.options.delim]) end local ret = table.pack(matrix_class.read(f, args)) f:close() if header then table.insert(ret, header) end return table.unpack(ret) end end -- GENERIC FROM STRING matrix.__generic__.__make_generic_fromString__ = function(matrix_class) matrix_class.fromString = function(str) return matrix_class.read(aprilio.stream.input_lua_string(str)) end end -- GENERIC TO FILENAME matrix.__generic__.__make_generic_toFilename__ = function(matrix_class, defmode) class.extend(matrix_class, "toFilename", function(self,filename,mode) local mode = mode or defmode local f = april_assert(io.open(filename,"w"), "Unable to open %s", filename) local ret = table.pack(self:write(f, { [matrix.options.ascii] = (mode=="ascii") })) f:close() return table.unpack(ret) end) end -- GENERIC TO TAB FILENAME matrix.__generic__.__make_generic_toTabFilename__ = function(matrix_class) class.extend(matrix_class, "toTabFilename", function(self,filename,mode) local f = april_assert(io.open(filename,"w"), "Unable to open %s", filename) local ret = table.pack(self:write(f, { [matrix.options.ascii] = (mode=="ascii"), [matrix.options.tab] = true })) f:close() return table.unpack(ret) end) end matrix.__generic__.__make_generic_toCSVFilename__ = function(matrix_class) class.extend(matrix_class, "toCSVFilename", function(self,filename,args) local args = get_table_fields({ [matrix.options.delim] = { mandatory=true, type_match="string", default="," }, header = { type_match="table" }, }, args) local delim = args[matrix.options.delim] assert(#delim == 1, "delim should be a 1 character string") local header = args.header args.header = nil local f = april_assert(io.open(filename,"w"), "Unable to open %s", filename) if header then f:write(table.concat(header, delim)) f:write("\n") end local ret = table.pack(self:write(f, { [matrix.options.ascii] = true, [matrix.options.delim] = delim, [matrix.options.tab] = true })) f:close() return table.unpack(ret) end) end -- GENERIC TO STRING matrix.__generic__.__make_generic_toString__ = function(matrix_class, defmode) class.extend(matrix_class, "toString", function(self,mode) local mode = mode or defmode return self:write({ [matrix.options.ascii] = (mode=="ascii") }) end) end function matrix.__generic__.__make_all_serialization_methods__(matrix_class, defmode) local defmode = defmode or "binary" matrix.__generic__.__make_generic_fromFilename__(matrix_class) matrix.__generic__.__make_generic_fromTabFilename__(matrix_class) matrix.__generic__.__make_generic_fromString__(matrix_class) matrix.__generic__.__make_generic_fromCSVFilename__(matrix_class) matrix.__generic__.__make_generic_toFilename__(matrix_class, defmode) matrix.__generic__.__make_generic_toTabFilename__(matrix_class) matrix.__generic__.__make_generic_toString__(matrix_class, defmode) matrix.__generic__.__make_generic_to_lua_string__(matrix_class, defmode) matrix.__generic__.__make_generic_toCSVFilename__(matrix_class) class.extend_metamethod(matrix_class, "ipylua_toseries", function(self) local self = self:squeeze() assert(self:num_dim() == 1, "Needs a rank one matrix") return self end ) end april-ann-0.4.1/packages/basics/matrix/lua_src/matrix.lua000066400000000000000000001255351263004425400233750ustar00rootroot00000000000000do local _,vector_methods = class.find("mathcore.vector") local matrix_ctor = { float = matrix, double = matrixDouble, complex = matrixComplex, char = matrixChar, bool = matrixBool, int32 = matrixInt32, } -- not guaranteed to reuse the underlying block, it can be a copy vector_methods.to_matrix = april_doc{ class="method", summary="Converts the vector into a matrix", description="Be careful, the underlying memory block is not guaranteed to be newly allocated", params={ "First dimension size [optional]", "Second dimension size [optional]", "...", "Last dimension size [optional]", }, outputs={ "A matrix instance", }, } .. function(self, ...) local block = self:to_block() local args = table.pack(...) table.insert(args, block) local m = matrix_ctor[self.dtype](table.unpack(args)) assert(#m == #block, "Incompatible matrix sizes") return m end end class.extend_metamethod(matrix, "__len", function(self) return self:dim(1) end) class.extend_metamethod(matrix, "__ipairs", function(self) return function(self,i) i = i+1 if i <= #self then return i,self[i] end end, self, 0 end) class.extend(matrix, "t", matrix.."transpose") -- serialization matrix.__generic__.__make_all_serialization_methods__(matrix) matrix.join = matrix.__generic__.__make_generic_join__(matrix) class.extend(matrix, "flatten", function(self) return self:rewrap(self:size()) end) -- ADDING PSEUDO-INVERSE METHODcond class.extend(matrix, "pinv", function(self) local u,s,vt = self:svd() for aux,i in s:iterate() do u:select(2,i):scal(((math.abs(aux)>1e-07) and 1/aux) or 0.0) end return matrix.as(self): gemm{ A = vt, B = u, trans_A = true, trans_B = true, alpha = 1.0, beta = 0.0, } end) matrix.ext.iterate = april_doc{ class = "function", summary = "Returns an iterator which traverses a dimension", description = { "The iterator uses m:select() method to traverse the given", "dimension number. The iterator returns the pair pos,slice", "where pos is the position inside the dimension and slice", "is a matrix with the result of m:select(dim,pos).", "Note that slice is reused between different iterations.", "Note that slice is a reference to the original matrix, any", "change to slice will be reflected into m." }, params = { "A matrix instance (any kind of matrix type)", "A dimension number [optional], by default it is 1 (row traversal)", "Step [optional], by default it is 1. It can be negative", }, outputs = { "An instance of iterator class", }, } .. function(self,dim,step) local dim = dim or 1 local step = step or 1 assert(step ~= 0, "Unable to iterate with step=0") local d = self:dim() assert(dim > 0 and dim <= #d, "Out-of-bounds dimension number") local slice return iterator(function(state,pos) local self,slice,dim,sz = table.unpack(state) pos = pos + step if pos <= d[dim] and pos >= 1 then slice = self:select(dim,pos,slice) return pos,slice end end, {self,slice,dim,d[dim]}, step>0 and 0 or d[dim]+1) end matrix.ext.broadcast = april_doc{ class = "function", summary = "Broadcasts an operation over two matrices", description = { "Similar to scipy broadcasting: http://wiki.scipy.org/EricsBroadcastingDoc ", "The operator is called as: func(a,b,...) where 'a' and 'b' are slices", "of the given input matrices, and '...' is the given optional variadic", "list of arguments.", }, params = { "A binary operator which receives two matrices, called as func(a,b,...)", "A matrix", "Another matrix", "A destination matrix [optional], nil by default", "Extra arguments to the binary operator [optional]", }, outputs = { {"The given destination matrix or a new allocated", "matrix with the result of the broadcast"} }, } .. function(func, a, b, result, ...) if ... then local args = table.pack(...) func = function(a,b) return func(a,b,table.unpack(args)) end end return class.of(a).__broadcast__(func,a,b,result) end matrix.__generic__.__make_index_methods__(matrix) -- static methods which return a new matrix instead of operate in-place matrix.op = {} for _,method in ipairs{"adjust_range", "clamp", "cmul", "cinv", "idiv", "plogp", "log", "log1p", "exp", "sqrt", "pow", "tan", "tanh", "atan", "sin", "sinh", "asin", "asinh", "cos", "cosh", "acos", "acosh", "abs", "complement", "sign", "scal", "div" } do matrix.op[method] = function(self,...) local clone = self:clone() return clone[method](clone,...) end end function matrix.ext.repmat(x, ...) local arg = table.pack(...) local dim = x:dim() local result_dim = {} assert(#arg >= #dim, "Underflow given number of dimensions") for i=1,#arg do dim[i] = dim[i] or 1 result_dim[i] = dim[i] * arg[i] end local x = x:rewrap(table.unpack(dim)) local ctor = class.of(x) local result = ctor(table.unpack(result_dim)) local result_sw = result:sliding_window{ size=dim, step=dim } local mat while not result_sw:is_end() do mat = result_sw:get_matrix(mat) mat:copy(x) result_sw:next() end return result end matrix.ext.diag = april_doc{ class = "function", summary = "Returns a matrix with diagonal elements of the given matrix", params = { "A 2D matrix", "The k-th diagonal number [optional], by default k=0", }, outputs = { "A new matrix instance", } } .. function(m,k) local k=k or 0 local dim = m:dim() assert(#dim == 2, "Needs a 2D matrix") local N = dim[1] assert(dim[2] == N, "Needs a square matrix") local get_map if k == 0 then get_map = function(i) return m:get(i,i) end elseif k>0 then assert(k < N, "Out-of-bounds k argument") get_map = function(i) return m:get(i,i+k) end else -- k<0 assert(k > -N, "Out-of-bounds k argument") get_map = function(i) return m:get(i-k,i) end end local ctor = class.of(m) if rawequal(ctor,matrix.sparse) then ctor = matrix end return ctor(N-math.abs(k)):linspace():map(get_map) end matrix.ext.triu = april_doc{ class = "function", summary = "Returns uppper triangular matrix taken from given matrix", params = { "A 2D matrix", "The start k-th diagonal number [optional], by default k=0", }, outputs = { "A new matrix instance", } } .. function(m,k) local k=k or 0 local dim = m:dim() local N = dim[1] assert(#dim == 2, "Needs a 2D matrix") assert(dim[2] == N, "Needs a square matrix") assert(k <= 0 or k < N, "Out-of-bounds k argument") assert(k >= 0 or k > -N, "Out-of-bounds k argument") local ctor = class.of(m) local triu = ctor(table.unpack(dim)):zeros() -- for each row for i=1,math.min(N,N-k) do local cols = { math.max(1,i+k), N } triu[{ i, cols }] = m(i, cols) end return triu end matrix.ext.tril = april_doc{ class = "function", summary = "Returns lower triangular matrix taken from given matrix", params = { "A 2D matrix", "The start k-th diagonal number [optional], by default k=0", }, outputs = { "A new matrix instance", } } .. function(m,k) local k=k or 0 local dim = m:dim() local N = dim[1] assert(#dim == 2, "Needs a 2D matrix") assert(dim[2] == N, "Needs a square matrix") assert(k <= 0 or k < N, "Out-of-bounds k argument") assert(k >= 0 or k > -N, "Out-of-bounds k argument") local ctor = class.of(m) local triu = ctor(table.unpack(dim)):zeros() local j=math.max(1,k+1) -- col number -- for each row for i=math.max(1,-k+1),N do local cols = { 1, math.min(N,j) } j=j+1 triu[{ i, cols }] = m(i, cols) end return triu end -- IMAGE function matrix.loadImage(filename,format) fprintf(io.stderr, "WARNING: matrix.loadImage is deprecated\n") local f -- si la imagen esta en formato netpbm no hace falta convert: if string.match(filename,".*%.p[gnp]m$") then f = io.open(filename,"r") else local dest_format = "pnm" if format == "gray" then dest_format = "pgm" end f = io.popen(string.format("convert %s %s:-",filename,dest_format)) end if not f then error(string.format("Error loading image %s'", filename)) end local b = f:read("*a") f:close() return matrix.fromPNM(b,format) end function matrix.saveImage(matrix,filename) local f = io.open(filename,"w") or error("Unable to open " .. filename) f:write(matrix:toPNM()) f:close() end function matrix.loadfile() error("Deprecated, use fromFilename method") end function matrix.savefile() error("Deprecated, use toFilename method") end -- RAW (ASCII) -- TODO: MEter esta funcion como parametro format de matrix:toString function matrix.saveRAW(matrix,filename) local f = io.open(filename,"w") or error("Unable to open " .. filename) local t = matrix:toTable() for i=1,table.getn(t) do f:write(t[i] .. "\n") end f:close() end ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- matrix.dict = matrix.dict or {} setmetatable(matrix.dict, { __call = function(self,v) if v then return type(v) == "table" and v or {v} else return {} end end }) local mmap = function(tbl,func,...) if type(tbl) == "table" then for name,w in pairs(tbl) do func(w,...) end else func(tbl,...) end return tbl end local mreduce = function(tbl,func,start,...) if type(tbl) == "table" then local acc = start for name,w in pairs(tbl) do acc = func(acc,w,...) end return acc else return func(start,w,...) end end matrix.dict.iterator = function(tbl,name_match) if type(tbl) == "table" then local name_match = name_match or ".*" return iterator(pairs(tbl)): filter(function(name,w) return name:find(name_match) end) else assert("Needs a table") end end for _,name in ipairs{ "scal", "fill", "scalar_add", "pow", "clamp", "idiv", "cinv", "zeros", "ones", "plogp", "log", "log1p", "exp", "sqrt", "tan", "tanh", "atan", "atanh", "cos", "cosh", "acos", "acosh", "sin", "sinh", "asin", "asinh", "abs", "complement", "sign", "inv", "prune_subnormal_and_check_normal", } do matrix.dict[name] = function(tbl,...) return mmap(tbl, function(w, name, ...) w[name](w,...) end, name, ...) end end matrix.dict.replace = function(tbl1, tbl2) assert(type(tbl1) == "table", "Needs a table as 1st argument") assert(type(tbl2) == "table", "Needs a table as 2nd argument") for name,w1 in pairs(tbl1) do local w2 = tbl2[name] if w2 then tbl1[name] = w2 end end return tbl1 end matrix.dict.clone = function(tbl) if type(tbl) == "table" then return iterator(pairs(tbl)): map(function(name,w) return name,w:clone() end):table() else return tbl:clone() end end matrix.dict.clone_only_dims = function(tbl) if type(tbl) == "table" then return iterator(pairs(tbl)): map(function(name,w) return name,matrix.as(w) end): table() else return matrix.as(tbl) end end matrix.dict.axpy = function(tbl1,value,tbl2) assert(type(value) == "number", "Needs a number as 2nd argument") if type(tbl1) == "table" and type(tbl2) == "table" then for name,w1 in pairs(tbl1) do local w2 = april_assert(tbl2[name], "Unable to find key %s", name) w1:axpy(value,w2) end else tbl1:axpy(value, tbl2) end return tbl1 end matrix.dict.copy = function(tbl1,tbl2) if type(tbl1) == "table" and type(tbl2) == "table" then for name,w1 in pairs(tbl1) do local w2 = april_assert(tbl2[name], "Unable to find key %s", name) w1:copy(w2) end else tbl1:copy(tbl2) end return tbl1 end matrix.dict.cmul = function(tbl1,tbl2) if type(tbl1) == "table" and type(tbl2) == "table" then for name,w1 in pairs(tbl1) do local w2 = april_assert(tbl2[name], "Unable to find key %s", name) w1:cmul(w2) end else tbl1:cmul(tbl2) end return tbl1 end matrix.dict.norm2 = function(tbl) if type(tbl) == "table" then local n2 = mreduce(tbl, function(acc,w) return acc + w:norm2()^2 end, 0) return math.sqrt(n2) else return tbl:norm2() end end matrix.dict.size = function(tbl) return mreduce(tbl, function(acc,w) return acc + w:size() end, 0) end matrix.dict.dot = function(tbl1,tbl2) if type(tbl1) == "table" and type(tbl2) == "table" then local dot=0 for name,w1 in pairs(tbl1) do local w2 = april_assert(tbl2[name], "Unable to find %s key", name) dot = dot + w1:dot(w2) end return dot else return tbl1:dot(tbl2) end end ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- ----------------------------------------------------------------------------- util.vector_uint.meta_instance.__tostring = function(self) local out = {} local sz = self:size() local NCOLS = 9 for i=1,sz do if i%NCOLS == 0 then table.insert(out, "\n") end table.insert(out, string.format("%8d ",self:get(i))) end table.insert(out, string.format("\n# vector_uint of size %d", self:size())) return table.concat(out, "") end util.vector_float.meta_instance.__tostring = function(self) local out = {} local sz = self:size() local NCOLS = 9 for i=1,sz do if i%NCOLS == 0 then table.insert(out, "\n") end table.insert(out, string.format("% -13.8g ",self:get(i))) end table.insert(out, string.format("\n# vector_float of size %d", self:size())) return table.concat(out, " ") end --------------------------- -- BINDING DOCUMENTATION -- --------------------------- april_set_doc(matrix, { class = "class", summary = "Multidimensional matrix objects", description ={ "This class represent multidimensional matrices.", "They are used for build datasets and train machine", "learning models.", "Mathematical operations are allowed (*, -, +).", "Specific BLAS methods are binding to Lua to ensure", "efficiency." }, }) april_set_doc(matrix, { class = "method", summary = "Matrix constructor", description ={ "Constructor of a multidimensional matrix.", "The data is stored at row_major order", }, params = { "First dimension size", "Second dimension size", "...", "ith dimension size", "...", "nth dimension size", { "A table with values [optional]. The values must be", "in row major order", }, }, outputs = { "A matrix instantiated object" }, }) april_set_doc(matrix.read, { class = "method", summary = "It allows to read a matrix from a stream.", description ={ "It allows to read a matrix from a stream.", "It uses the format of write function.", }, params = { "A aprilio.stream instance.", "A lua table with options", }, }) april_set_doc(matrix.fromMMap, { class = "function", summary = "Matrix fromMMap constructor", description ={ "Loads a matrix from a mmaped filename.", }, params = { "A filename path.", { "A boolean indicating if writing is allowed [optional].", "By default it is true", }, { "A boolean indicating if memory map is shared [optional].", "By default it is true", }, }, outputs = { "A matrix instantiated object" }, }) april_set_doc(matrix.."toMMap", { class = "method", summary = "It allows to store a matrix in a mmapped file.", description ={ "It allows to store a matrix in a mmapped file.", "It uses the format expected by fromMMap function.", }, params = { "A filename path.", }, }) april_set_doc(matrix.loadImage, { class = "function", summary = "Matrix loadImage constructor", description ={ "Loads a matrix from a image filename.", }, params = { "A filename path.", }, outputs = { "A matrix instantiated object" }, }) april_set_doc(matrix.saveImage, { class = "function", summary = "It allows to store a matrix in a image file.", description ={ "It allows to store a matrix in a file.", }, params = { "A matrix object.", "A filename path.", }, }) april_set_doc(matrix.fromString, { class = "function", summary = "Matrix fromString constructor", description ={ "Loads a matrix from a Lua string.", }, params = { "A Lua string.", }, outputs = { "A matrix instantiated object" }, }) april_set_doc(matrix.."toString", { class = "method", summary = "It returns a Lua string which stores the matrix.", description ={ "It returns a Lua string which stores the matrix.", "It uses the format expected by fromString function.", }, outputs = { "A Lua string" }, }) april_set_doc(matrix.."to_lua_string", { class = "method", summary = "It returns a Lua chunk string which is loadable.", params = { "The format [optional]. By default is binary." }, outputs = { "A Lua string" }, }) april_set_doc(matrix.fromPNM, { class = "function", summary = "Matrix fromPNM constructor", description ={ "Loads a matrix from a PNM image stored at a Lua string.", }, params = { "A Lua string.", }, outputs = { "A matrix instantiated object" }, }) april_set_doc(matrix.."toPNM", { class = "method", summary = "It stores the matrix as a PNM image Lua string.", description ={ "It stores the matrix as a PNM image Lua string.", }, outputs = { "A Lua string" }, }) april_set_doc(matrix.."copy_from_table", { class = "method", summary = "Copies the table values to the matrix.", params = { "A lua table with data numbers in row_major order", }, }) april_set_doc(matrix.."get", { class = "method", summary = "Returns the value stored at a given position.", params = { "First dimension position", "Second dimension position", "...", "ith dimension position", "...", "nth dimension position", }, outputs = { "A number", }, }) april_set_doc(matrix.."sum", { class="method", summary="Computes the sum of all the elements.", outputs={"A number"}, }) april_set_doc(matrix.."sum", { class="method", summary="Computes the sum of all the elements over the given dimension.", params={ "A number, the dimension", "A matrix where to store the result [optional]", }, outputs={"A matrix with the result"}, }) april_set_doc(matrix.."set", { class = "method", summary = "Sets the value of a given position.", params = { "First dimension position", "Second dimension position", "...", "ith dimension position", "...", "nth dimension position", "A number with the value to be set", }, outputs = { "The caller matrix" }, }) april_set_doc(matrix.."raw_get", { class = "method", summary = "Returns the value stored at a given RAW position.", params = { "RAW position", }, outputs = { "A number", }, }) april_set_doc(matrix.."raw_set", { class = "method", summary = "Sets the value of a given RAW position.", params = { "RAW position", }, outputs = { "The caller matrix" }, }) april_set_doc(matrix.."offset", { class = "method", summary = "Returns the RAW offset position of matrix data.", outputs = { "A number with the RAW offset position", }, }) april_set_doc(matrix.."fill", { class = "method", summary = "Sets all values to a given number.", description = { "Sets all values to a given number.", "This method modifies the object IN-PLACE.", }, params = { "A number", }, outputs = { "The caller object (itself)", }, }) april_set_doc(matrix.."set_use_cuda", { class = "method", summary = "Indicates if use or not CUDA for math operations.", params = { "A boolean", }, outputs = { "The caller object (itself)", }, }) april_set_doc(matrix.."dim", { class = "method", summary = "Returns a table with the size of each dimension.", outputs = { "A table", }, }) april_set_doc(matrix.."dim", { class = "method", summary = "Returns the size of a given dimension number.", params = { "A number indicating the dimension, between 1 and num_dims", }, outputs = { "A number", }, }) april_set_doc(matrix.."stride", { class = "method", summary = "Returns a table with the stride size of each dimension.", outputs = { "A table", }, }) april_set_doc(matrix.."stride", { class = "method", summary = "Returns the stride size of a given dimension number.", params = { "A number indicating the dimension, between 1 and num_dims", }, outputs = { "A number", }, }) april_set_doc(matrix.."slice", { class = "method", summary = "Returns a sub-matrix that is a slice of caller matrix.", description = { "Returns a sub-matrix that is a slice of caller matrix.", "This method returns a sub-matrix which references the", "parent matrix (not copy the data). Optionally it is possible", "to do a deep copy (clone) of the data.", }, params = { "A table with the first position of the sub-matrix", "A table with the sizes of each dimension for the sub-matrix", { "A boolean indicating if do or not a clone [optional]. By", "default it is set to false", }, }, outputs = { "A matrix object (sub-matrix)", }, }) april_set_doc(matrix.."rewrap", { class = "method", summary = "Reinterprets the data as with other dimensions.", description = { "Returns a matrix which references to the caller, but", "reinterpreting the internal data with the given array of", "dimension sizes.", "The caller matrix must be a contiguous chunk of data.", }, params = { { "A table with the size of each dimension.", "The number of dimensions could be different of ", "caller matrix.", }, }, outputs = { "A matrix object (referencing the caller matrix)", }, }) april_set_doc(matrix.."select", { class = "method", summary = "Returns an slice result of select given dimension at given index.", description = { "Returns an slice result of select given dimension at given index.", "The matrix has one less dimension because the selected dimension", "is removed.", }, params = { { "A number with the selected dimension" }, { "A number with the selected index" }, }, outputs = { "A matrix object (referencing the caller matrix)", }, }) april_set_doc(matrix.join, { class = "function", summary = "Produce a matrix which is the join of a given set of matrices.", description = { "Joins a given set of matrices, given the dimension where they differ.", "Be careful, this method duplicates the memory needed, because all the", "matrices will be copied to the destination.", }, params = { { "A number with the dimension where matrices differ." }, { "The 1st matrix" }, { "The 2nd matrix" }, { "..." }, { "The Nth matrix" }, }, outputs = { "A new matrix object", }, }) april_set_doc(matrix.."clone", { class = "method", summary = "Returns a deep copy (clone) of the caller matrix.", outputs = { "A matrix object (cloned)", }, }) april_set_doc(matrix.."transpose", { class = "method", summary = "Returns transposition of the caller matrix.", description = { "Returns transposition of the caller matrix.", "The returned matrix is a reference to the original.", }, outputs = { "A matrix object (transposed)", }, }) april_set_doc(matrix.."transpose", { class = "method", summary = "Transposes two dimensions.", description = { "Transposes two dimensions of the caller matrix.", "The returned matrix is a reference to the original.", }, params = { "One dimension number", "Second dimension number", }, outputs = { "A matrix object (transposed)", }, }) april_set_doc(matrix.."adjust_range", { class = "method", summary = "Modifies the matrix values IN-PLACE to be at given range", params = { "The min value of the range", "The max value of the range" }, outputs = { "The caller matrix object (itself)", }, }) april_set_doc(matrix.."diag", { class = "method", summary = "Sets diagonal positions to a given number.", description = { "Sets diagonal positions to a tiven number value.", "This method modifies the object IN-PLACE.", }, params = { "A number", }, outputs = { "The caller object (itself)", }, }) april_set_doc(matrix.."toTable", { class = "method", summary = "Returns a Lua table with the data of the matrix.", description = { "Returns a Lua table with the data of the matrix.", "The table is a copy of the data in row_major order.", }, outputs = { "A Lua table", }, }) april_set_doc(matrix.."min", { class = "method", summary = "Returns the minimum value contained at the matrix.", outputs = { "A number", }, }) april_set_doc(matrix.."min", { class = "method", summary = "Returns a matrix with minimum values over given dimension.", params = { "A number with the dimension", "A matrix where to store the result [optional]", }, outputs = { "A matrix with the result", }, }) april_set_doc(matrix.."max", { class = "method", summary = "Returns the maximum value contained at the matrix.", outputs = { "A number", }, }) april_set_doc(matrix.."max", { class = "method", summary = "Returns a matrix with maximum values over given dimension.", params = { "A number with the dimension", "A matrix where to store the result [optional]", }, outputs = { "A matrix with the result", }, }) april_set_doc(matrix.."clamp", { class = "method", summary = "Clamp matrix values IN-PLACE to be in the given range.", params = { "The min value of the range", "The max value of the range", }, outputs = { "The caller matrix (itself)", }, }) april_set_doc(matrix.."add", { class = "method", summary = "Returns the addition of caller and other matrix.", description = { "Returns a new matrix which is addition of caller and other matrix.", "It uses BLAS operations.", }, params = { "Another matrix", }, outputs = { "A new matrix result of addition", }, }) april_set_doc(matrix.."sub", { class = "method", summary = "Returns the subtraction of caller and other matrix.", description = { "Returns a new matrix which is the subtraction of caller and other matrix.", "It uses BLAS operations.", }, params = { "Another matrix", }, outputs = { "A new matrix result of subtraction", }, }) april_set_doc(matrix.."mul", { class = "method", summary = "Returns the multiplication of caller and other matrix.", description = { "Returns a new matrix which is the multiplication of caller and other matrix.", "This method works with vector-vector, dot product,", "vector-matrix, and matrix-matrix multiplication, depending", "on the matrices dimensions.", "It uses BLAS operations.", }, params = { "Another matrix (2D matrix or a vector)", }, outputs = { "A new matrix result of multiplication", }, }) april_set_doc(matrix.."cmul", { class = "method", summary = "Computes IN-PLACE the component-wise multiplication of caller and other matrix.", params = { "Another matrix", }, outputs = { "The caller matrix", }, }) april_set_doc(matrix.."plogp", { class = "method", summary = "Component wise p*log(p) operation IN-PLACE: Y = Y*log(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."log", { class = "method", summary = "Component wise log operation IN-PLACE: Y = log(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."log1p", { class = "method", summary = "Component wise log1p operation IN-PLACE: Y = log1p(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."exp", { class = "method", summary = "Component wise exp operation IN-PLACE: Y = exp(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."tan", { class = "method", summary = "Component wise tanh operation IN-PLACE: Y = tan(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."tanh", { class = "method", summary = "Component wise tanh operation IN-PLACE: Y = tanh(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."atan", { class = "method", summary = "Component wise atanh operation IN-PLACE: Y = atan(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."atanh", { class = "method", summary = "Component wise atanh operation IN-PLACE: Y = atanh(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."sin", { class = "method", summary = "Component wise sin operation IN-PLACE: Y = sin(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."sinh", { class = "method", summary = "Component wise sinh operation IN-PLACE: Y = sinh(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."asin", { class = "method", summary = "Component wise asin operation IN-PLACE: Y = asin(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."asinh", { class = "method", summary = "Component wise asinh operation IN-PLACE: Y = asinh(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."cos", { class = "method", summary = "Component wise cos operation IN-PLACE: Y = cos(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."cosh", { class = "method", summary = "Component wise cosh operation IN-PLACE: Y = cosh(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."acos", { class = "method", summary = "Component wise acos operation IN-PLACE: Y = acos(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."acosh", { class = "method", summary = "Component wise acosh operation IN-PLACE: Y = acosh(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."abs", { class = "method", summary = "Component wise abs operation IN-PLACE: Y = abs(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."complement", { class = "method", summary = "Component wise complement operation IN-PLACE: Y = 1 - Y", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."sqrt", { class = "method", summary = "Component wise sqrt operation IN-PLACE: Y = sqrt(Y)", params = { }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."pow", { class = "method", summary = "Component wise pow operation IN-PLACE: Y = pow(Y,x)", params = { "A number (x)" }, outputs = { "The caller matrix, Y (itself)", }, }) april_set_doc(matrix.."axpy", { class = "method", summary = "BLAS AXPY operation IN-PLACE: Y = Y + alpha * X.", params = { "Alpha constant", "Another matrix, X", }, outputs = { "The caller matrix (a vector), Y (itself)", }, }) april_set_doc(matrix.."gemv", { class = "method", summary = "BLAS GEMV operation IN-PLACE: Y = beta * Y + alpha * A * X.", params = { ["alpha"] = "Alpha constant", ["beta"] = "Beta constant", ["trans_A"] = { "A boolean indicating if transpose or not matrix A.", "It is [optional], by default is false", }, ["A"] = "Another matrix, A (a 2D matrix)", ["X"] = "Another matrix, X (a vector)", }, outputs = { "The caller matrix (a vector), Y (itself)", }, }) april_set_doc(matrix.."gemm", { class = "method", summary = "BLAS GEMM operation IN-PLACE: C = beta * C + alpha * A * B.", params = { ["alpha"] = "Alpha constant", ["beta"] = "Beta constant", ["trans_A"] = { "A boolean indicating if transpose or not matrix A.", "It is [optional], by default is false", }, ["trans_B"] = { "A boolean indicating if transpose or not matrix B.", "It is [optional], by default is false", }, ["A"] = "Another matrix, A (a 2D matrix)", ["B"] = "Another matrix, B (a 2D matrix)", }, outputs = { "The caller matrix, C (itself)", }, }) april_set_doc(matrix.."ger", { class = "method", summary = "BLAS GER operation IN-PLACE: Z = Z + alpha * X * Y'.", params = { ["alpha"] = "Alpha constant", ["X"] = "Another matrix, X (a vector)", ["Y"] = "Another matrix, Y (a vector)", }, outputs = { "The caller matrix, Z (itself)", }, }) april_set_doc(matrix.."dot", { class = "method", summary = "BLAS DOT operation IN-PLACE: v = X dot Y", params = { "Another matrix, Y (a vector)", }, outputs = { "A number with the dot product", }, }) april_set_doc(matrix.."scal", { class = "method", summary = "BLAS SCAL operation IN-PLACE.", params = { "The scale factor", }, outputs = { "The caller matrix (itself)." }, }) april_set_doc(matrix.."div", { class = "method", summary = "Inverse to scal operation IN-PLACE, produces A = value/A.", params = { "The div factor", }, outputs = { "The caller matrix (itself)." }, }) april_set_doc(matrix.."norm2", { class = "method", summary = "BLAS NRM2 operation.", outputs = { "A number with the norm-2 of caller matrix." }, }) april_set_doc(matrix.."copy", { class = "method", summary = "Copy the values from another matrix using BLAS", params = { "A source matrix" }, outputs = { "The caller matrix instance" }, }) april_set_doc(matrix.."linear", { class = "method", summary = "Initializes with linear integers", params = { "First integer value [optional], by default 0", "Step value [optional], by default 1", }, outputs = { "The caller matrix instance" }, }) april_set_doc(matrix.."uniform", { class = "method", summary = "Initializes with random positive integers from range [a,b]", params = { "Lower range value", "Upper range value", "A random object instance [optional]" }, outputs = { "The caller matrix instance" }, }) april_set_doc(matrix.."uniformf", { class = "method", summary = "Initializes with random floats in range [a,b]", params = { "Lower range value", "Upper range value", "A random object instance [optional]" }, outputs = { "The caller matrix instance" }, }) april_set_doc(matrix.."is_contiguous", { class = "method", summary = "Returns true if the matrix data is contiguous at memory", outputs = { "A boolean" }, }) april_set_doc(matrix.."scalar_add", { class = "method", summary = "Adds a scalar IN-PLACE", params = { "A number" }, outputs = { "The caller matrix instance" }, }) april_set_doc(matrix.."inv", { class = "method", summary = "Computes the inverse of a matrix", description = { "This method computes the inverse of matrix.", "Check that your matrix is not singular, otherwise", "the returned matrix won't be correct.", }, outputs = { "The matrix inverse" }, }) april_set_doc(matrix.."svd", { class = "method", summary = "Computes the SVD of a matrix", description = { "This method computes the SVD of matrix.", "The computation returns three matrices", ", so A=U * S * V'.", }, outputs = { "The matrix U", "The sparse row vector S with the eigenvalues", "The matrix V', the transposed of V", }, }) april_set_doc(matrix.."diagonalize", { class = "method", summary = "Converts the given uni-dimensional matrix in a bi-dimensional diagonal dense matrix", outputs = { "A matrix which is the diagonalized version of the caller matrix", }, }) april_set_doc(matrix.."contiguous", { class = "method", summary = "Returns a contiguous version of the caller matrix", description = { "Returns a contiguous version of the caller matrix.", "If the matrix is contiguous, returns itself.", "Otherwise, returns a copy of the caller.", }, outputs = { "A matrix instance" }, }) april_set_doc(matrix.."map", { class = "method", summary = "Maps the matrix values by a given list of matrices and a Lua map function", description = { "Maps the matrix values by a given list of matrices", "and a Lua map function.", "The Lua function will be called for every possible", "matrix position. The Lua function receives the caller matrix", "value at the given position, the value of the second matrix,", "the value of the third matrix, and so on.", "The Lua function returns NIL or ONLY one value, which will be", "assigned to the caller matrix IN-PLACE.", "All the matrices must have the same dimension sizes.", "The number of given matrices could be >= 0", }, params = { "A second matrix", "A third matrix", "...", "A Nth matrix", "A Lua function which applies the map computation.", }, outputs = { "The caller matrix" }, }) april_set_doc(matrix.."lt", { class = "method", summary = "Returns a matrixBool with true where values are less than given param.", params = { "A matrix or a number", }, outputs = { "A matrixBool instance" }, }) april_set_doc(matrix.."gt", { class = "method", summary = "Returns a matrixBool with true where values are greater than given param.", params = { "A matrix or a number", }, outputs = { "A matrixBool instance" }, }) ------------------------------------------------------------------------- april_set_doc(matrix.."sliding_window", { class = "method", summary = "Returns a sliding window object", params = { offset = "Lua table [optional]", size = "Lua table [optional]", step = "Lua table [optional]", numSteps = "Lua table [optional]", orderStep = "Lua table [optional]", }, outputs = { "An instance of matrix.__sliding_window__" }, }) april_set_doc(matrix.__sliding_window__, { class = "class", summary = "Sliding window for matrix objects", }) april_set_doc(matrix.__sliding_window__.."get_matrix", { class = "method", summary = "Returns the matrix generated by the window", params = { {"A matrix [optional], to be used instead", "of alloc a new one"} }, outputs = { "A matrix instance" }, }) april_set_doc(matrix.__sliding_window__.."next", { class = "method", summary = "Moves the window to the next position", outputs = { "The caller sliding_window object" }, }) april_set_doc(matrix.__sliding_window__.."is_end", { class = "method", summary = "Returns true when it finishes", outputs = { "A boolean" }, }) april_set_doc(matrix.__sliding_window__.."iterate", { class = "method", summary = "Returns an iterator function: for mat in s:iterate() do ... end", outputs = { "An iterator function" }, }) ----------------------------- -- DEPRECATED CONSTRUCTORS -- matrix.row_major = make_deprecated_function("matrix.row_major", "matrix", matrix) matrix.col_major = make_deprecated_function("matrix.col_major", "matrix", matrix) class.extend(matrix, "get_major_order", make_deprecated_function("matrix.get_major_order", nil, function(self) return "row_major" end)) ----------------------------- -- other stuff matrix.__generic__.__make_generic_call__(matrix) -- define left side operator [] matrix.meta_instance.__newindex = matrix.__generic__.__make_generic_newindex__(matrix) -- define right side operator [] matrix.__generic__.__make_generic_index__(matrix) matrix.meta_instance.__tostring = matrix.__generic__.__make_generic_print__("Matrix", function(value) return string.format("% -13.6g", value) end) matrix.meta_instance.__eq = function(op1, op2) if type(op1) == "number" or type(op2) == "number" then return false end return op1:equals(op2) end matrix.meta_instance.__add = function(op1, op2) if not class.is_a(op1,matrix) then op1,op2=op2,op1 end if type(op2) == "number" then return op1:clone():scalar_add(op2) else return op1:add(op2) end end matrix.meta_instance.__sub = function(op1, op2) if class.is_a(op1,matrix) and class.is_a(op2,matrix) then return op1:sub(op2) elseif class.is_a(op1,matrix) then return op1:clone():scalar_add(-op2) elseif class.is_a(op2,matrix) then return op2:clone():scal(-1):scalar_add(op1) end end matrix.meta_instance.__mul = function(op1, op2) if class.is_a(op1,matrix.sparse) or class.is_a(op2,matrix.sparse) then if class.is_a(op2,matrix.sparse) then local res = matrix(op1:dim(1),op2:dim(2)) res:transpose():sparse_mm{ alpha=1.0, beta=0.0, A=op2, B=op1, trans_A=true, trans_B=true } return res else local res = matrix(op1:dim(1),op2:dim(2)) res:sparse_mm{ alpha=1.0, beta=0.0, A=op1, B=op2 } return res end else if not class.is_a(op1,matrix) then op1,op2=op2,op1 end if type(op2) == "number" then return op1:clone():scal(op2) else return op1:mul(op2) end end end matrix.meta_instance.__pow = function(op1, op2) local new_mat = op1:clone() return new_mat:pow(op2) end matrix.meta_instance.__div = function(op1, op2) if type(op2) == "number" then local new_mat = op1:clone() return new_mat:scal(1/op2) elseif type(op1) == "number" then local new_mat = op2:clone() return new_mat:div(op1) else assert(class.is_a(op1,matrix) and class.is_a(op2,matrix), "Expected a matrix and a number or two matrices") local new_mat1 = op1:clone() local new_mat2 = op2:clone():div(1) return new_mat1:cmul(new_mat2) end end matrix.meta_instance.__unm = function(op) local new_mat = op:clone() return new_mat:scal(-1) end april-ann-0.4.1/packages/basics/matrix/lua_src/matrixBool.lua000066400000000000000000000064711263004425400242060ustar00rootroot00000000000000class.extend_metamethod(matrixBool, "__len", function(self) return self:dim(1) end) class.extend_metamethod(matrixBool, "__ipairs", function(self) return function(self,i) i = i+1 if i <= #self then return i,self[i] end end, self, 0 end) class.extend(matrixBool, "t", matrixBool.."transpose") -- serialization matrix.__generic__.__make_all_serialization_methods__(matrixBool, "ascii") matrix.__generic__.__make_index_methods__(matrixBool) class.extend(matrixBool, "flatten", function(self) return self:rewrap(self:size()) end) april_set_doc(matrixBool.."to_index", { class = "method", summary = "Returns a matrixInt32 with the list of true indices", description = "Requires a rank 1 matrix", outputs = { "A matrixInt32 instance", }, }) class.extend(matrixBool, "land", april_doc{ class = "method", summary = "Computes component-wise AND operation IN-PLACE", params = {"Another matrixBool instance",}, outputs = {"The caller matrix",} } .. function(self,other) assert(class.is_a(other,matrixBool), "Needs a matrixBool as argument") self:map(other,function(x,y) return x and y end) return self end) class.extend(matrixBool, "lor", april_doc{ class = "method", summary = "Computes component-wise OR operation IN-PLACE", params = {"Another matrixBool instance",}, outputs = {"The caller matrix",} } .. function(self,other) assert(class.is_a(other,matrixBool), "Needs a matrixBool as argument") self:map(other,function(x,y) return x or y end) return self end) matrixBool.meta_instance.__unm = function(op) return op:clone():complement() end matrixBool.meta_instance.__add = function(op1, op2) assert(class.is_a(op1, matrixBool), "Needs two matrixBool arguments") assert(class.is_a(op2, matrixBool), "Needs two matrixBool arguments") return op1:clone():lor(op2) end matrixBool.meta_instance.__mul = function(op1, op2) assert(class.is_a(op1, matrixBool), "Needs two matrixBool arguments") assert(class.is_a(op2, matrixBool), "Needs two matrixBool arguments") return op1:clone():land(op2) end matrixBool.meta_instance.__eq = function(op1, op2) if type(op1) == "number" or type(op2) == "number" then return false end return op1:equals(op2) end matrix.__generic__.__make_generic_call__(matrixBool) matrixBool.meta_instance.__newindex = matrix.__generic__.__make_generic_newindex__(matrixBool) matrix.__generic__.__make_generic_index__(matrixBool) matrixBool.meta_instance.__tostring = matrix.__generic__.__make_generic_print__("MatrixBool", function(value) return string.format("%s", value and "T" or "F") end) matrixBool.join = matrix.__generic__.__make_generic_join__(matrixBool) april-ann-0.4.1/packages/basics/matrix/lua_src/matrixChar.lua000066400000000000000000000036631263004425400241700ustar00rootroot00000000000000class.extend_metamethod(matrixChar, "__len", function(self) return self:dim(1) end) class.extend_metamethod(matrixChar, "__ipairs", function(self) return function(self,i) i = i+1 if i <= #self then return i,self[i] end end, self, 0 end) class.extend(matrixChar, "t", matrixChar.."transpose") -- serialization matrix.__generic__.__make_all_serialization_methods__(matrixChar, "ascii") matrix.__generic__.__make_index_methods__(matrixChar) -- define right side operator [] matrix.__generic__.__make_generic_index__(matrixChar) -- define left side operator [] matrixChar.meta_instance.__newindex = matrix.__generic__.__make_generic_newindex__(matrixChar) matrix.__generic__.__make_generic_call__(matrixChar) matrixChar.meta_instance.__tostring = function(self) local dims = self:dim() local coords = {} local out = {} local row = {} local so_large = false for i=1,#dims do coords[i]=1 if coords[i] > 20 then so_large = true end end if not so_large then for i=1,self:size() do table.insert(out, string.format("[%s] = %s", table.concat(coords, ","), self:get(table.unpack(coords)))) local j=#dims+1 repeat j=j-1 coords[j] = (coords[j] % dims[j]) + 1 until j==1 or coords[j] ~= 1 end else table.insert(out, "Large matrix, not printed to display") end table.insert(out, string.format("# MatrixChar of size [%s] [%s]", table.concat(dims, ","), self:get_reference_string())) return table.concat(out, "\n") end function matrixChar.loadfile() error("Deprecated, use fromFilename method") end function matrixChar.savefile() error("Deprecated, use toFilename method") end matrixChar.meta_instance.__eq = function(op1, op2) if type(op1) == "number" or type(op2) == "number" then return false end return op1:equals(op2) end april-ann-0.4.1/packages/basics/matrix/lua_src/matrixComplex.lua000066400000000000000000000425051263004425400247200ustar00rootroot00000000000000class.extend_metamethod(matrixComplex, "__len", function(self) return self:dim(1) end) class.extend_metamethod(matrixComplex, "__ipairs", function(self) return function(self,i) i = i+1 if i <= #self then return i,self[i] end end, self, 0 end) class.extend(matrixComplex, "t", matrixComplex.."transpose") class.extend(matrixComplex, "flatten", function(self) return self:rewrap(self:size()) end) matrix.__generic__.__make_index_methods__(matrixComplex) -- serialization matrix.__generic__.__make_all_serialization_methods__(matrixComplex) matrixComplex.join = matrix.__generic__.__make_generic_join__(matrixComplex) matrixComplex.meta_instance.__eq = function(op1, op2) return op1:equals(op2) end matrixComplex.meta_instance.__add = function(op1, op2) if not class.is_a(op1,matrixComplex) then op1,op2=op2,op1 end if type(op2) == "number" then return op1:clone():scalar_add(op2) else return op1:add(op2) end end matrixComplex.meta_instance.__sub = function(op1, op2) if not class.is_a(op1,matrixComplex) then op1,op2=op2,op1 end return op1:sub(op2) end matrixComplex.meta_instance.__mul = function(op1, op2) if not class.is_a(op1,matrixComplex) then op1,op2=op2,op1 end if type(op2) == "number" then return op1:clone():scal(complex(op2,0)) elseif type(op2) == "string" then return op1:clone():scal(complex(op2)) elseif class.is_a(op2,complex) then return op1:clone():scal(op2) else return op1:mul(op2) end end matrixComplex.meta_instance.__div = function(op1, op2) assert(type(op2) == "number", "Expected a number as second argument") local new_mat = op1:clone() return new_mat:scal(1/op2) end matrixComplex.meta_instance.__unm = function(op) local new_mat = op:clone() return new_mat:scal(-1) end ----------------------------------------------------------------------------- --------------------------- -- BINDING DOCUMENTATION -- --------------------------- april_set_doc(matrixComplex, { class = "class", summary = "Multidimensional matrixComplex objects", description ={ "This class represent multidimensional matrices as matrix.", "But this is not available for build datasets and train machine", "learning models. In the last instance, you need always to", "transform this to a vanilla matrix.", "Mathematical operations are allowed (*, -, +).", "Specific BLAS methods are binding to Lua to ensure", "efficiency." }, }) april_set_doc(matrixComplex, { class = "method", summary = "Constructor", description ={ "Constructor of a multidimensional matrixComplex.", "The data is stored at row_major order", }, params = { "First dimension size", "Second dimension size", "...", "ith dimension size", "...", "nth dimension size", { "A table with values [optional]. The values must be", "in row major order. A valid value is a number, which is", "taken as real part only, a complex object instance, or a", "string with the complex number.", }, }, outputs = { "A matrixComplex instantiated object" }, }) april_set_doc(matrixComplex.."to_lua_string", { class = "method", summary = "It returns a Lua chunk string which is loadable.", params = { "The format [optional]. By default is binary." }, outputs = { "A Lua string" }, }) april_set_doc(matrixComplex.."copy_from_table", { class = "method", summary = "Copies the table values to the matrixComplex.", params = { "A lua table with data numbers in row_major order", }, }) april_set_doc(matrixComplex.."sum", { class="method", summary="Computes the sum of all the elements.", outputs={"A number"}, }) april_set_doc(matrixComplex.."sum", { class="method", summary="Computes the sum of all the elements over the given dimension.", params={"A number, the dimension"}, outputs={"A matrix"}, }) april_set_doc(matrixComplex.."get", { class = "method", summary = "Returns the value stored at a given position.", params = { "First dimension position", "Second dimension position", "...", "ith dimension position", "...", "nth dimension position", }, outputs = { "A number", }, }) april_set_doc(matrixComplex.."set", { class = "method", summary = "Sets the value of a given position.", params = { "First dimension position", "Second dimension position", "...", "ith dimension position", "...", "nth dimension position", "A number with the value to be set", }, outputs = { "The caller matrixComplex" }, }) april_set_doc(matrixComplex.."raw_get", { class = "method", summary = "Returns the value stored at a given RAW position.", params = { "RAW position", }, outputs = { "A number", }, }) april_set_doc(matrixComplex.."raw_set", { class = "method", summary = "Sets the value of a given RAW position.", params = { "RAW position", }, outputs = { "The caller matrixComplex" }, }) april_set_doc(matrixComplex.."offset", { class = "method", summary = "Returns the RAW offset position of matrixComplex data.", outputs = { "A number with the RAW offset position", }, }) april_set_doc(matrixComplex.."fill", { class = "method", summary = "Sets all values to a given number.", description = { "Sets all values to a given number.", "This method modifies the object IN-PLACE.", }, params = { "A number", }, outputs = { "The caller object (itself)", }, }) april_set_doc(matrixComplex.."set_use_cuda", { class = "method", summary = "Indicates if use or not CUDA for math operations.", params = { "A boolean", }, outputs = { "The caller object (itself)", }, }) april_set_doc(matrixComplex.."dim", { class = "method", summary = "Returns a table with the size of each dimension.", outputs = { "A table", }, }) april_set_doc(matrixComplex.."dim", { class = "method", summary = "Returns the size of a given dimension number.", params = { "A number indicating the dimension, between 1 and num_dims", }, outputs = { "A number", }, }) april_set_doc(matrixComplex.."stride", { class = "method", summary = "Returns a table with the stride size of each dimension.", outputs = { "A table", }, }) april_set_doc(matrixComplex.."stride", { class = "method", summary = "Returns the stride size of a given dimension number.", params = { "A number indicating the dimension, between 1 and num_dims", }, outputs = { "A number", }, }) april_set_doc(matrixComplex.."slice", { class = "method", summary = "Returns a sub-matrixComplex that is a slice of caller matrixComplex.", description = { "Returns a sub-matrixComplex that is a slice of caller matrixComplex.", "This method returns a sub-matrixComplex which references the", "parent matrixComplex (not copy the data). Optionally it is possible", "to do a deep copy (clone) of the data.", }, params = { "A table with the first position of the sub-matrixComplex", "A table with the sizes of each dimension for the sub-matrixComplex", { "A boolean indicating if do or not a clone [optional]. By", "default it is set to false", }, }, outputs = { "A matrixComplex object (sub-matrixComplex)", }, }) april_set_doc(matrixComplex.."rewrap", { class = "method", summary = "Reinterprets the data as with other dimensions.", description = { "Returns a matrixComplex which references to the caller, but", "reinterpreting the internal data with the given array of", "dimension sizes.", "The caller matrixComplex must be a contiguous chunk of data.", }, params = { { "A table with the size of each dimension.", "The number of dimensions could be different of ", "caller matrixComplex.", }, }, outputs = { "A matrixComplex object (referencing the caller matrixComplex)", }, }) april_set_doc(matrixComplex.."select", { class = "method", summary = "Returns an slice result of select given dimension at given index.", description = { "Returns an slice result of select given dimension at given index.", "The matrixComplex has one less dimension because the selected dimension", "is removed.", }, params = { { "A number with the selected dimension" }, { "A number with the selected index" }, }, outputs = { "A matrixComplex object (referencing the caller matrixComplex)", }, }) april_set_doc(matrixComplex.."clone", { class = "method", summary = "Returns a deep copy (clone) of the caller matrixComplex.", outputs = { "A matrixComplex object (cloned)", }, }) april_set_doc(matrixComplex.."transpose", { class = "method", summary = "Returns transposition of the caller matrixComplex.", description = { "Returns transposition of the caller matrixComplex.", "The returned matrixComplex references the original.", }, outputs = { "A matrixComplex object (transposed)", }, }) april_set_doc(matrixComplex.."diag", { class = "method", summary = "Sets diagonal positions to a given number.", description = { "Sets diagonal positions to a tiven number value.", "This method modifies the object IN-PLACE.", }, params = { "A number", }, outputs = { "The caller object (itself)", }, }) april_set_doc(matrixComplex.."toTable", { class = "method", summary = "Returns a Lua table with the data of the matrixComplex.", description = { "Returns a Lua table with the data of the matrixComplex.", "The table is a copy of the data in row_major order.", }, outputs = { "A Lua table", }, }) april_set_doc(matrixComplex.."add", { class = "method", summary = "Returns the addition of caller and other matrixComplex.", description = { "Returns a new matrixComplex which is addition of caller and other matrixComplex.", "It uses BLAS operations.", }, params = { "Another matrixComplex", }, outputs = { "A new matrixComplex result of addition", }, }) april_set_doc(matrixComplex.."sub", { class = "method", summary = "Returns the subtraction of caller and other matrixComplex.", description = { "Returns a new matrixComplex which is the subtraction of caller and other matrixComplex.", "It uses BLAS operations.", }, params = { "Another matrixComplex", }, outputs = { "A new matrixComplex result of subtraction", }, }) april_set_doc(matrixComplex.."mul", { class = "method", summary = "Returns the multiplication of caller and other matrixComplex.", description = { "Returns a new matrixComplex which is the multiplication of caller and other matrixComplex.", "This method works with vector-vector, dot product,", "vector-matrixComplex, and matrixComplex-matrixComplex multiplication, depending", "on the matrices dimensions.", "It uses BLAS operations.", }, params = { "Another matrixComplex (2D matrixComplex or a vector)", }, outputs = { "A new matrixComplex result of multiplication", }, }) april_set_doc(matrixComplex.."cmul", { class = "method", summary = "Computes IN-PLACE the component-wise multiplication of caller and other matrix.", params = { "Another matrix", }, outputs = { "The caller matrix", }, }) april_set_doc(matrixComplex.."axpy", { class = "method", summary = "BLAS AXPY operation IN-PLACE: Y = Y + alpha * X.", params = { "Alpha constant", "Another matrixComplex, X", }, outputs = { "The caller matrixComplex (a vector), Y (itself)", }, }) april_set_doc(matrixComplex.."gemv", { class = "method", summary = "BLAS GEMV operation IN-PLACE: Y = beta * Y + alpha * A * X.", params = { ["alpha"] = "Alpha constant", ["beta"] = "Beta constant", ["trans_A"] = { "A boolean indicating if transpose or not matrixComplex A.", "It is [optional], by default is false", }, ["A"] = "Another matrixComplex, A (a 2D matrixComplex)", ["X"] = "Another matrixComplex, X (a vector)", }, outputs = { "The caller matrixComplex (a vector), Y (itself)", }, }) april_set_doc(matrixComplex.."gemm", { class = "method", summary = "BLAS GEMM operation IN-PLACE: C = beta * C + alpha * A * B.", params = { ["alpha"] = "Alpha constant", ["beta"] = "Beta constant", ["trans_A"] = { "A boolean indicating if transpose or not matrixComplex A.", "It is [optional], by default is false", }, ["trans_B"] = { "A boolean indicating if transpose or not matrixComplex B.", "It is [optional], by default is false", }, ["A"] = "Another matrixComplex, A (a 2D matrixComplex)", ["B"] = "Another matrixComplex, B (a 2D matrixComplex)", }, outputs = { "The caller matrixComplex, C (itself)", }, }) april_set_doc(matrixComplex.."dot", { class = "method", summary = "BLAS DOT operation IN-PLACE: v = X dot Y", params = { "Another matrixComplex, Y (a vector)", }, outputs = { "A number with the dot product", }, }) april_set_doc(matrixComplex.."scal", { class = "method", summary = "BLAS SCAL operation IN-PLACE.", params = { "The scale factor", }, outputs = { "The caller matrixComplex (itself)." }, }) april_set_doc(matrixComplex.."norm2", { class = "method", summary = "BLAS NRM2 operation.", outputs = { "A number with the norm-2 of caller matrixComplex." }, }) april_set_doc(matrixComplex.."copy", { class = "method", summary = "Copy the values from another matrixComplex using BLAS", params = { "A source matrixComplex" }, outputs = { "The caller matrixComplex instance" }, }) april_set_doc(matrixComplex.."linear", { class = "method", summary = "Initializes with linear integers", params = { "First integer value [optional], by default 0", "Step value [optional], by default 1", }, outputs = { "The caller matrixComplex instance" }, }) april_set_doc(matrixComplex.."is_contiguous", { class = "method", summary = "Returns true if the matrixComplex data is contiguous at memory", outputs = { "A boolean" }, }) april_set_doc(matrixComplex.."scalar_add", { class = "method", summary = "Adds a scalar IN-PLACE", params = { "A number" }, outputs = { "The caller matrixComplex instance" }, }) april_set_doc(matrixComplex.."to_float", { class = "method", summary = "Returns a matrix (with float resolution)", description = { "Converts the given matrixComplex to a matrix (with float)", "with the one additional dimension of size two, where the", "real and imaginary part will be stored together.", "The extra dimension will be the last.", }, outputs = { "A matrix instance" }, }) april_set_doc(matrixComplex.."conj", { class = "method", summary = "Applies the conjugate of all the elements IN-PLACE", outputs = { "The caller matrixComplex instance" }, }) april_set_doc(matrixComplex.."real", { class = "method", summary = "Returns the real part of the caller matrix", outputs = { "A matrix instance" }, }) april_set_doc(matrixComplex.."img", { class = "method", summary = "Returns the imaginary part of the caller matrix", outputs = { "A matrix instance" }, }) april_set_doc(matrixComplex.."abs", { class = "method", summary = "Returns the abs of the polar representation", outputs = { "A matrix instance" }, }) april_set_doc(matrixComplex.."angle", { class = "method", summary = "Returns the angle of the polar representation", outputs = { "A matrix instance" }, }) april_set_doc(matrixComplex.."sliding_window", { class = "method", summary = "Returns a sliding window object", params = { offset = "Lua table [optional]", size = "Lua table [optional]", step = "Lua table [optional]", numSteps = "Lua table [optional]", orderStep = "Lua table [optional]", }, outputs = { "An instance of matrixComplex.__sliding_window__" }, }) april_set_doc(matrixComplex.__sliding_window__, { class = "class", summary = "Sliding window for matrixComplex objects", }) april_set_doc(matrixComplex.__sliding_window__.."get_matrix", { class = "method", summary = "Returns the matrixComplex generated by the window", params = { {"A matrixComplex [optional], to be used instead", "of alloc a new one"} }, outputs = { "A matrixComplex instance" }, }) april_set_doc(matrixComplex.__sliding_window__.."next", { class = "method", summary = "Moves the window to the next position", outputs = { "The caller sliding_window object" }, }) april_set_doc(matrixComplex.__sliding_window__.."is_end", { class = "method", summary = "Returns true when it finishes", outputs = { "A boolean" }, }) april_set_doc(matrixComplex.__sliding_window__.."iterate", { class = "method", summary = "Returns an iterator function: for mat in s:iterate() do ... end", outputs = { "An iterator function" }, }) matrix.__generic__.__make_generic_call__(matrixComplex) matrixComplex.meta_instance.__newindex = matrix.__generic__.__make_generic_newindex__(matrixComplex) matrix.__generic__.__make_generic_index__(matrixComplex) matrixComplex.meta_instance.__tostring = matrix.__generic__.__make_generic_print__("MatrixComplex", function(value) return string.format("%26s",tostring(value)) end) april-ann-0.4.1/packages/basics/matrix/lua_src/matrixDouble.lua000066400000000000000000000065201263004425400245200ustar00rootroot00000000000000class.extend_metamethod(matrixDouble, "__len", function(self) return self:dim(1) end) class.extend_metamethod(matrixDouble, "__ipairs", function(self) return function(self,i) i = i+1 if i <= #self then return i,self[i] end end, self, 0 end) class.extend(matrixDouble, "t", matrixDouble.."transpose") class.extend(matrixDouble, "flatten", function(self) return self:rewrap(self:size()) end) matrix.__generic__.__make_index_methods__(matrixDouble) -- serialization matrix.__generic__.__make_all_serialization_methods__(matrixDouble) matrix.__generic__.__make_generic_call__(matrixDouble) matrixDouble.meta_instance.__newindex = matrix.__generic__.__make_generic_newindex__(matrixDouble) matrix.__generic__.__make_generic_index__(matrixDouble) matrixDouble.meta_instance.__tostring = matrix.__generic__.__make_generic_print__("MatrixDouble", function(value) return string.format("% -15.6g", value) end) matrixDouble.join = matrix.__generic__.__make_generic_join__(matrixDouble) matrixDouble.meta_instance.__eq = function(op1, op2) if type(op1) == "number" or type(op2) == "number" then return false end return op1:equals(op2) end matrixDouble.meta_instance.__add = function(op1, op2) if not class.is_a(op1,matrixDouble) then op1,op2=op2,op1 end if type(op2) == "number" then return op1:clone():scalar_add(op2) else return op1:add(op2) end end matrixDouble.meta_instance.__sub = function(op1, op2) if class.is_a(op1,matrixDouble) and class.is_a(op2,matrixDouble) then return op1:sub(op2) elseif class.is_a(op1,matrixDouble) then return op1:clone():scalar_add(-op2) elseif class.is_a(op2,matrixDouble) then return op2:clone():scal(-1):scalar_add(op1) end end matrixDouble.meta_instance.__mul = function(op1, op2) if class.is_a(op1,matrixDouble.sparse) or class.is_a(op2,matrixDouble.sparse) then if class.is_a(op2,matrixDouble.sparse) then local res = matrixDouble(op1:dim(1),op2:dim(2)) res:transpose():sparse_mm{ alpha=1.0, beta=0.0, A=op2, B=op1, trans_A=true, trans_B=true } return res else local res = matrixDouble(op1:dim(1),op2:dim(2)) res:sparse_mm{ alpha=1.0, beta=0.0, A=op1, B=op2 } return res end else if not class.is_a(op1,matrixDouble) then op1,op2=op2,op1 end if type(op2) == "number" then return op1:clone():scal(op2) else return op1:mul(op2) end end end matrixDouble.meta_instance.__pow = function(op1, op2) local new_mat = op1:clone() return new_mat:pow(op2) end matrixDouble.meta_instance.__div = function(op1, op2) if type(op2) == "number" then local new_mat = op1:clone() return new_mat:scal(1/op2) elseif type(op1) == "number" then local new_mat = op2:clone() return new_mat:div(op1) else assert(class.is_a(op1,matrixDouble) and class.is_a(op2,matrixDouble), "Expected a matrixDouble and a number or two matrices") local new_mat1 = op1:clone() local new_mat2 = op2:clone():div(1) return new_mat1:cmul(new_mat2) end end matrixDouble.meta_instance.__unm = function(op) local new_mat = op:clone() return new_mat:scal(-1) end april-ann-0.4.1/packages/basics/matrix/lua_src/matrixInt32.lua000066400000000000000000000052741263004425400242120ustar00rootroot00000000000000class.extend_metamethod(matrixInt32, "__len", function(self) return self:dim(1) end) class.extend_metamethod(matrixInt32, "__ipairs", function(self) return function(self,i) i = i+1 if i <= #self then return i,self[i] end end, self, 0 end) class.extend(matrixInt32, "t", matrixInt32.."transpose") class.extend(matrixInt32, "flatten", function(self) return self:rewrap(self:size()) end) matrix.__generic__.__make_index_methods__(matrixInt32) -- serialization matrix.__generic__.__make_all_serialization_methods__(matrixInt32) matrix.__generic__.__make_generic_call__(matrixInt32) matrixInt32.meta_instance.__newindex = matrix.__generic__.__make_generic_newindex__(matrixInt32) matrix.__generic__.__make_generic_index__(matrixInt32) matrixInt32.meta_instance.__tostring = matrix.__generic__.__make_generic_print__("MatrixInt32", function(value) return string.format("% 11d", value) end) matrixInt32.join = matrix.__generic__.__make_generic_join__(matrixInt32) matrixInt32.meta_instance.__eq = function(op1, op2) if type(op1) == "number" or type(op2) == "number" then return false end return op1:equals(op2) end matrixInt32.meta_instance.__add = function(op1, op2) if not class.is_a(op1,matrixInt32) then op1,op2=op2,op1 end if type(op2) == "number" then return op1:clone():scalar_add(op2) else return op1:add(op2) end end matrixInt32.meta_instance.__sub = function(op1, op2) if class.is_a(op1,matrixInt32) and class.is_a(op2,matrixInt32) then return op1:sub(op2) elseif class.is_a(op1,matrixInt32) then return op1:clone():scalar_add(-op2) elseif class.is_a(op2,matrixInt32) then return op2:clone():scal(-1):scalar_add(op1) end end matrixInt32.meta_instance.__mul = function(op1, op2) if not class.is_a(op1,matrixInt32) then op1,op2=op2,op1 end if type(op2) == "number" then return op1:clone():scal(op2) else error("Not implemented matrix multiplication between matrixInt32 objects") end end matrixInt32.meta_instance.__div = function(op1, op2) if type(op2) == "number" then local new_mat = op1:clone() return new_mat:idiv(op2) elseif type(op1) == "number" then error("Unable to divide a number by a matrixInt32") else assert(class.is_a(op1,matrixInt32) and class.is_a(op2,matrixInt32), "Expected a matrixInt32 and a number or two matrices") return new_mat1:clone():idiv(new_mat2) end end matrixInt32.meta_instance.__unm = function(op) local new_mat = op:clone() return new_mat:scal(-1) end april-ann-0.4.1/packages/basics/matrix/lua_src/sparse_matrix.lua000066400000000000000000000103171263004425400247410ustar00rootroot00000000000000class.extend(matrix.sparse, "t", matrix.sparse .. "transpose") -- the constructor matrix.sparse.csr = matrix.sparse -- serialization matrix.__generic__.__make_generic_fromFilename__(matrix.sparse) matrix.__generic__.__make_generic_fromString__(matrix.sparse) matrix.__generic__.__make_generic_to_lua_string__(matrix.sparse) matrix.__generic__.__make_generic_toFilename__(matrix.sparse) matrix.__generic__.__make_generic_toString__(matrix.sparse) local function parse_slice(slice, max) if not slice then return 1,max end local a,b local tt = type(slice) if tt == "string" then a = slice:match("^(%d+)%:.*$") or 1 b = slice:match("^.*%:(%d+)$") or max elseif tt == "table" then a = slice[1] or 1 b = slice[2] or max elseif tt == "number" then a,b = slice,slice else error("Incorrect slice format, expecting a string, a table or a number") end a = tonumber(a) b = tonumber(b) if a < 0 then a = max + a end if b < 0 then b = max + b end assert(a >= 1 and a <= max) assert(b >= 1 and b <= max) assert(a <= b) return a,b end matrix.sparse.meta_instance.__call = function(self, x_slice, y_slice) local x_a,x_b = parse_slice(x_slice, self:dim(1)) local y_a,y_b = parse_slice(y_slice, self:dim(2)) local coords = { x_a, y_a } local sizes = { x_b - x_a + 1, y_b - y_a + 1 } return self:slice(coords, sizes, false) end -- define right side operator [] class.declare_functional_index ( matrix.sparse, function(self, key) local tt = type(key) if tt == "number" then return self:select(1, key) elseif tt == "table" then return self(key[1], key[2]) end end ) matrix.sparse.meta_instance.__newindex = function(self, key, value) error("Not implemented for sparse matrix instance") end matrix.sparse.meta_instance.__tostring = function(self) local out = {} local sparse = (self.get_sparse_format and self:get_sparse_format()) or "csr" local dims = self:dim() local so_large = false local getter = function(value) return string.format("% -11.6g", value) end -- for i=1,#dims do if dims[i] > 20 then so_large = true end end if not so_large then local aux = self:to_dense() local coords = {1,1} local row = {} for i=1,aux:size() do table.insert(row, getter(aux:get(table.unpack(coords)))) local j=#dims+1 repeat j=j-1 coords[j] = coords[j] + 1 if coords[j] > dims[j] then coords[j] = 1 end until j==1 or coords[j] ~= 1 if coords[#coords] == 1 then table.insert(out, table.concat(row, " ")) row={} end end else table.insert(out, "Large matrix, not printed to display") end table.insert(out, string.format("# SparseMatrix of size [%s] in %s [%s], %d non-zeros\n", table.concat(dims, ","), sparse, self:get_reference_string(), self:non_zero_size())) return table.concat(out, "\n") end matrix.sparse.meta_instance.__eq = function(op1, op2) if type(op1) == "number" or type(op2) == "number" then return false end return op1:equals(op2) end matrix.sparse.meta_instance.__mul = function(op1, op2) if type(op2) == "number" then return op1:clone():scal(op2) elseif type(op1) == "number" then return op2:clone():scal(op1) else if class.is_a(op1,matrix) then local res = matrix(op1:dim(1),op2:dim(2)) res:transpose():sparse_mm{ alpha=1.0, beta=0.0, A=op2, B=op1, trans_A=true, trans_B=true } return res elseif class.is_a(op2,matrix) then local res = matrix(op1:dim(1),op2:dim(2)) res:sparse_mm{ alpha=1.0, beta=0.0, A=op1, B=op2 } return res else error("matrix.sparse only could be multiplied by scalars or matrix") end end end matrix.sparse.meta_instance.__pow = function(op1, op2) local new_mat = op1:clone() return new_mat:pow(op2) end matrix.sparse.meta_instance.__div = function(op1, op2) if type(op2) == "number" then local new_mat = op1:clone() return new_mat:scal(1/op2) elseif type(op1) == "number" then local new_mat = op2:clone() return new_mat:div(op1) else error("matrix.sparse only could be divided by scalars") end end matrix.sparse.meta_instance.__unm = function(op) local new_mat = op:clone() return new_mat:scal(-1) end april-ann-0.4.1/packages/basics/matrix/package.lua000066400000000000000000000075201263004425400220250ustar00rootroot00000000000000 package{ name = "matrix", version = "1.0", depends = { "util", "mathcore", "random", "aprilio" }, keywords = { "matrix" }, description = "no description available", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "test", lua_unit_test{ file={ "test/test_ger.lua", "test/test_gemm.lua", "test/test_gemv.lua", "test/test_matrix_inv_solve.lua", "test/test_matrix_fft.lua", "test/test_matrix_math.lua", "test/test_sparse_matrix.lua", "test/test_convolution.lua", }, }, -- FIXME: make it compile -- c_unit_test{ -- file = { "test/test_matrix.cc" }, -- }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, exec{ command = [[lua binding/generate_matrix_binding.lua]] }, provide_bind{ file = "binding/bind_matrix.lua.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_matrix_complex_float.lua.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_matrix_double.lua.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_matrix_int32.lua.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_matrix_char.lua.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_matrix_bool.lua.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_referenced_vector.lua.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_sparse_matrix.lua.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_sparse_matrix_double.lua.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_sparse_matrix_complex_float.lua.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_matrix_options.lua.cc", dest_dir = "include" }, provide_bind{ file = "binding/bind_matrix_ext.lua.cc", dest_dir = "include" }, copy{ file= "binding/*.h", dest_dir = "include/binding" }, }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", include_dirs = "${include_dirs}", --flags = "-std=c99", not valid for c++!!! dest_dir = "build", }, object{ file = "c_src/*.cu", dest_dir = "build", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_matrix.lua.cc", dest_dir = "build", }, build_bind{ file = "binding/bind_matrix_complex_float.lua.cc", dest_dir = "build", }, build_bind{ file = "binding/bind_matrix_double.lua.cc", dest_dir = "build", }, build_bind{ file = "binding/bind_matrix_int32.lua.cc", dest_dir = "build", }, build_bind{ file = "binding/bind_matrix_char.lua.cc", dest_dir = "build", }, build_bind{ file = "binding/bind_matrix_bool.lua.cc", dest_dir = "build", }, build_bind{ file = "binding/bind_referenced_vector.lua.cc", dest_dir = "build", }, build_bind{ file = "binding/bind_sparse_matrix.lua.cc", dest_dir = "build", }, build_bind{ file = "binding/bind_sparse_matrix_double.lua.cc", dest_dir = "build", }, build_bind{ file = "binding/bind_sparse_matrix_complex_float.lua.cc", dest_dir = "build", }, build_bind{ file = "binding/bind_matrix_options.lua.cc", dest_dir = "build", }, build_bind{ file = "binding/bind_matrix_ext.lua.cc", dest_dir = "build", }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/matrix/test/000077500000000000000000000000001263004425400207025ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/matrix/test/test_convolution.lua000066400000000000000000000067471263004425400250410ustar00rootroot00000000000000local check = utest.check local T = utest.test local warning = utest.warning local aux = matrix(1,1,3,3):linear() --print(aux) local aux = matrix.join(1,aux,aux) local k = matrix(2,1,2,2):linear() local o = matrix.ext.convolution(aux, { kernel=k, D=2 }) local o2 = matrix.ext.convolution(aux:clone(), { kernel=k:clone(), D=2 }) --print(o) --print(o2) T("MatrixConvolutionBasicTest", function() -- from: http://hal.archives-ouvertes.fr/docs/00/11/26/31/PDF/p1038112283956.pdf -- High Performance Convolutional Neural Networks for Document Processing local m = matrix(1,3,3,3,{ 1,2,0, 1,1,3, 0,2,2, 0,2,1, 0,3,2, 1,1,0, 1,2,1, 0,1,3, 3,3,2 }) local k = matrix(2,3,2,2,{ 1,1, 2,2, 1,1, 1,1, 0,1, 1,0, 1,0, 0,1, 2,1, 2,1, 1,2, 2,0, }) local target_o = matrix(1,2,2,2,{ 14,20, 15,24, 12,24, 17,26, }) -- replicate the input and target matrices local m = matrix.join(1,m,m,m) local target_o = matrix.join(1, target_o, target_o, target_o) -- local o = matrix.ext.convolution(m, { kernel=k, D=2 }) -- --print(o) check.eq(o, target_o) end) T("MatrixConvolutionMediumTest", function() if not ann then warning("needs ann package\n") return true end local rnd = random(1234) local m = matrix(2,3,6,6):uniform(-10,10,rnd) local k = matrix(2,3,3,3):uniform(-1,1,rnd) local target_o = matrix(2,2,4,4, { -37, -9, -31, -3, -9, 0, 13, 13, -6, -38, 1, -25, 10, 14, 33, -11, -15, -23, 12, 19, -13, -8, -5, -28, 18, 4, -3, -11, 11, -35, -3, -6, 26, 17, 3, 42, -25, -22, 24, 40, -8, 29, -21, -55, -9, 24, 44, 20, -21, -22, -2, 44, 17, 32, -18, -32, -35, -15, 26, 0, -28, 3, -38, -11, }) ------------------------------------------------------------------------- local o = matrix.ext.convolution(m, { kernel=k, D=2 }) local c = ann.components.convolution{ kernel = { 3,3,3 }, n=2, weights = "w1" } c:build{ weights = { w1 = k:rewrap(2, k:size()/2) } } local cnn_o = c:forward(m) -- check.eq( o, target_o ) check.eq( cnn_o, target_o ) end) if #arg > 0 then T("MatrixConvolutionLenaTest", function() if not ann then warning("needs ann package\n") return true end local rnd=random(1234) local kx=17 local ky=17 local h=10 -- a matrix of ROWSxCOLUMNSx3 local m = ImageIO.read(string.get_path(arg[0]) .. "../../../ann/ann/test/photo.png"): matrix():transpose():clone() local m = m:padding(0,0,8,8,8,8) local k = matrix(h,3,kx,ky):uniformf(-0.1,0.1,rnd) local o = matrix.ext.convolution(m, { kernel=k, D=2 }):squeeze() local x,y = o:dim(2),o:dim(3) local o = o:rewrap(o:dim(1),x*y) local img = ann.connections.input_filters_image(o, {x,y}) ImageIO.write(img, "wop.png") check.TRUE( true ) end) end april-ann-0.4.1/packages/basics/matrix/test/test_gemm.lua000066400000000000000000000113251263004425400233730ustar00rootroot00000000000000local check=utest.check local T=utest.test function do_test() T("GEMMTest1", function() local a = matrix(2,1):linspace() -- matrix with strides = {1,1} local b = matrix(2,2):linspace() check.eq(a:t()*b, matrix(1,2,{ 1*1 + 2*3, 1*2 + 2*4 })) check.eq(matrix(1,2):gemm{ A=a, B=b, trans_A=true, alpha=1, beta=0 }, a:t()*b) check.eq(matrix(2,1):t():gemm{ A=a:t(), B=b, alpha=1, beta=0 }, a:t()*b ) check.eq(matrix(2,1):t():gemm{ A=a, B=b, trans_A=true, alpha=1, beta=0 }, a:t()*b ) -- local t1 = { 1, 2, 3, 4, 5, 6 } local t2 = { 3, 4, 1, 7, 9, 6 } local t1_t2 = matrix(2,2,{ 32, 36, 71, 87 }) local t2_t1 = matrix(3,3,{ 19, 26, 33, 29, 37, 45, 33, 48, 63 }) local t1p_t2p = matrix(3,3,{ 19, 29, 33, 26, 37, 48, 33, 45, 63 }) local t2p_t1p = matrix(2,2,{ 32, 71, 36, 87 }) local A = matrix(2,3,t1) local B = matrix(3,2,t2) check.eq(A*B, t1_t2) check.eq(B*A, t2_t1) check.eq(A:t()*B:t(), t1p_t2p) check.eq(B:t()*A:t(), t2p_t1p) check.eq(matrix(2,2):gemm{ A=A, B=B, alpha=1, beta=0 }, t1_t2) check.eq(matrix(3,3):gemm{ A=B, B=A, alpha=1, beta=0 }, t2_t1) check.eq(matrix(3,3):gemm{ A=A:t(), B=B:t(), alpha=1, beta=0 }, t1p_t2p) check.eq(matrix(2,2):gemm{ A=B:t(), B=A:t(), alpha=1, beta=0 }, t2p_t1p) check.eq(matrix(2,2):gemm{ A=A:t(), B=B:t(), trans_A=true, trans_B=true, alpha=1, beta=0 }, t1_t2) check.eq(matrix(3,3):gemm{ A=B:t(), B=A:t(), trans_A=true, trans_B=true, alpha=1, beta=0 }, t2_t1) check.eq(matrix(3,3):gemm{ A=A, B=B, trans_A=true, trans_B=true, alpha=1, beta=0 }, t1p_t2p) check.eq(matrix(2,2):gemm{ A=B, B=A, trans_A=true, trans_B=true, alpha=1, beta=0 }, t2p_t1p) check.eq(matrix(2,2):transpose():gemm{ A=A, B=B, alpha=1, beta=0 }, t1_t2) check.eq(matrix(3,3):transpose():gemm{ A=B, B=A, alpha=1, beta=0 }, t2_t1) check.eq(matrix(3,3):transpose():gemm{ A=A:t(), B=B:t(), alpha=1, beta=0 }, t1p_t2p) check.eq(matrix(2,2):transpose():gemm{ A=B:t(), B=A:t(), alpha=1, beta=0 }, t2p_t1p) check.eq(matrix(2,2):transpose():gemm{ A=A:t(), B=B:t(), trans_A=true, trans_B=true, alpha=1, beta=0 }, t1_t2) check.eq(matrix(3,3):transpose():gemm{ A=B:t(), B=A:t(), trans_A=true, trans_B=true, alpha=1, beta=0 }, t2_t1) check.eq(matrix(3,3):transpose():gemm{ A=A, B=B, trans_A=true, trans_B=true, alpha=1, beta=0 }, t1p_t2p) check.eq(matrix(2,2):transpose():gemm{ A=B, B=A, trans_A=true, trans_B=true, alpha=1, beta=0 }, t2p_t1p) check.errored(function() return A*A end) check.errored(function() return B*B end) end) T("GEMMTest2", function() local t1 = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 } local t2 = { 3, 4, 1, 7, 9, 6 } local t1_t2 = matrix(4,2,{ t1[1]*t2[1] + t1[2]*t2[3] + t1[3]*t2[5], t1[1]*t2[2] + t1[2]*t2[4] + t1[3]*t2[6], t1[4]*t2[1] + t1[5]*t2[3] + t1[6]*t2[5], t1[4]*t2[2] + t1[5]*t2[4] + t1[6]*t2[6], t1[7]*t2[1] + t1[8]*t2[3] + t1[9]*t2[5], t1[7]*t2[2] + t1[8]*t2[4] + t1[9]*t2[6], t1[10]*t2[1] + t1[11]*t2[3] + t1[12]*t2[5], t1[10]*t2[2] + t1[11]*t2[4] + t1[12]*t2[6], }) local t2p_t1p = matrix(2,4,{ t1[1]*t2[1] + t1[2]*t2[3] + t1[3]*t2[5], t1[4]*t2[1] + t1[5]*t2[3] + t1[6]*t2[5], t1[7]*t2[1] + t1[8]*t2[3] + t1[9]*t2[5], t1[10]*t2[1] + t1[11]*t2[3] + t1[12]*t2[5], t1[1]*t2[2] + t1[2]*t2[4] + t1[3]*t2[6], t1[4]*t2[2] + t1[5]*t2[4] + t1[6]*t2[6], t1[7]*t2[2] + t1[8]*t2[4] + t1[9]*t2[6], t1[10]*t2[2] + t1[11]*t2[4] + t1[12]*t2[6], }) local A = matrix(4,3,t1) local B = matrix(3,2,t2) check.eq(A*B, t1_t2) check.eq(B:t()*A:t(), t2p_t1p) end) end do_test() if util.is_cuda_available() then -- forces the use of CUDA mathcore.set_use_cuda_default(util.is_cuda_available()) do_test() end april-ann-0.4.1/packages/basics/matrix/test/test_gemv.lua000066400000000000000000000020361263004425400234030ustar00rootroot00000000000000local check=utest.check local T=utest.test function do_test() T("GEMVTest", function() local t1 = { 1, 2, 3, 4, 5, 6 } local t2 = { 3, 1, 9 } local t3 = { 9, 7 } local t1_t2 = matrix(2,{ 32, 71 }) local t1p_t3 = matrix(3,{ 37, 53, 69 }) local A = matrix(2,3,t1) local B = matrix(t2) local C = matrix(t3) check.eq(matrix(2):gemv{ A=A, X=B, alpha=1, beta=0 }, t1_t2) check.eq(matrix(3):gemv{ A=A:t(), X=C, alpha=1, beta=0 }, t1p_t3) check.eq(matrix(2):gemv{ A=A:t(), X=B, trans_A=true, alpha=1, beta=0 }, t1_t2) check.eq(matrix(3):gemv{ A=A, X=C, trans_A=true, alpha=1, beta=0 }, t1p_t3) check.errored(function() return matrix(3):gemv{ A=A:t(), X=C, trans_A=true, alpha=1, beta=0 } end) check.errored(function() return matrix(3):gemv{ A=A, X=C, alpha=1, beta=0 } end) end) end do_test() if util.is_cuda_available() then -- forces the use of CUDA mathcore.set_use_cuda_default(util.is_cuda_available()) do_test() end april-ann-0.4.1/packages/basics/matrix/test/test_ger.lua000066400000000000000000000016471263004425400232310ustar00rootroot00000000000000local check=utest.check local T=utest.test function do_test() T("GERTest", function() local t1 = { 3, 1, 9 } local t2 = { 9, 7, 10 } local t1_t2 = matrix(3,3,{ 3*9, 3*7, 3*10, 1*9, 1*7, 1*10, 9*9, 9*7, 9*10, }) local t2_t1 = matrix(3,3,{ 3*9, 9*1, 9*9, 3*7, 1*7, 9*7, 3*10, 1*10, 9*10 }) local X = matrix(t1) local Y = matrix(t2) check.eq(matrix(3,3):zeros():ger{ X=X, Y=Y, alpha=1 }, t1_t2) check.eq(matrix(3,3):zeros():ger{ X=Y, Y=X, alpha=1 }, t2_t1) check.errored(function() return check.eq(matrix(2,2):zeros():ger{ X=X, Y=Y, alpha=1 }, t1_t2) end) end) end do_test() if util.is_cuda_available() then -- forces the use of CUDA mathcore.set_use_cuda_default(util.is_cuda_available()) do_test() end april-ann-0.4.1/packages/basics/matrix/test/test_matrix.cc000066400000000000000000000024021263004425400235520ustar00rootroot00000000000000#include "gtest.h" #include "matrixFloat.h" #include "matrix_ext_blas.h" #include "matrix_ext_misc.h" #include "matrix_ext_reductions.h" #include "smart_ptr.h" using namespace Basics; using namespace AprilMath::MatrixExt::BLAS; using namespace AprilMath::MatrixExt::Misc; using namespace AprilMath::MatrixExt::Reductions; using namespace AprilUtils; MatrixFloat *floatAxpyOperator(MatrixFloat *X, const MatrixFloat *Y) { return matAxpy(X, 1.0f, Y); } namespace test_matrix { void check_int(int i) { EXPECT_TRUE( 0 <= i && i <= 9 ); } TEST(MatrixTest, Test1) { SharedPtr m1 = new MatrixFloat(10,20); SharedPtr m2 = new MatrixFloat(10,1); SharedPtr m3 = new MatrixFloat(10,20); for (int i=0; isize(); ++i) { (*m1)[i] = static_cast(i); } for (int i=0; isize(); ++i) { (*m2)[i] = static_cast(i); } for (int j=0,k=0; jgetDimSize(0); ++j) { for (int i=0; igetDimSize(1); ++i,++k) { (*m3)[k] = static_cast(k+j); } } SharedPtr out; out = matBroadcast(floatAxpyOperator, m1.get(), m2.get()); EXPECT_TRUE( matEquals(m3.get(), out.get(), 0.01) ); } } APRILANN_GTEST_MAIN(test_util) april-ann-0.4.1/packages/basics/matrix/test/test_matrix.lua000066400000000000000000000013771263004425400237600ustar00rootroot00000000000000 a = matrix.fromString[[ # primero vienen las dimensiones de la matriz 4 3 # y luego el tipo ascii # y los datos: 1 2 3,,,,, 4 5 6 7 8 9 10 11 12 ]] dims = a:dim() print(string.format("{%s}",table.concat(dims,','))) printf('En ascii: "%s"\n',a:toString()) printf('En binario: "%s"\n',a:toString("binary")) txt = a:toString("binary") c = matrix.fromString(txt) print('Leemos binario y lo volvemos a mostrar en ascii:\n"'..c:toString()..'"') x = matrix.fromString[[ 2 5 ascii 0 2 3 4 5 6 7 8 9 10 ]] print(x:toString()) print("ahora normalizamos entre 0 y 1") x:adjust_range(0,1) print(x:toString()) x = matrix.fromString[[ 2 5 ascii 1 1 1 1 1 1 1 1 1 1 ]] print(x:toString()) print("ahora normalizamos entre 0 y 1") x:adjust_range(0,1) print(x:toString()) april-ann-0.4.1/packages/basics/matrix/test/test_matrix_fft.lua000066400000000000000000000011201263004425400246010ustar00rootroot00000000000000local check = utest.check local T = utest.test T("FFTTest", function() local sin1 = matrix(512):linspace(0,1*math.pi):sin() local sin2 = matrix(512):linspace(0,2*math.pi):sin() local sin3 = matrix(512):linspace(0,3*math.pi):sin() local sin4 = matrix(512):linspace(0,4*math.pi):sin() local sin256 = matrix(512):linspace(0,512*math.pi):sin() local sum = (sin1 + sin2 + sin3 + sin4 + sin256)/5 local fft = matrix.ext.real_fftwh(sum, 512, 512):log():clamp(0,math.huge) local peaks = fft:gt(3):to_index() check.eq( peaks, matrixInt32{1, 2, 3, 4, 256} ) end) april-ann-0.4.1/packages/basics/matrix/test/test_matrix_get.lua000066400000000000000000000003041263004425400246040ustar00rootroot00000000000000m = matrix(3,4,5) local aux = {} for i=1,3*4*5 do table.insert(aux,i) end m:copy_from_table(aux) for i=1,3 do for j=1,4 do for k=1,5 do print(i,j,k,m:get(i,j,k)) end end end april-ann-0.4.1/packages/basics/matrix/test/test_matrix_inv_solve.lua000066400000000000000000000007561263004425400260440ustar00rootroot00000000000000mathcore.set_use_cuda_default(util.is_cuda_available()) -- local check = utest.check local T = utest.test T("InverseTest", function() -- inverse local M = matrix local m = M(2,2, { -2, 1, -1, 1, }) local b = M(2,1, { 4, 1 }) local c = m:inv()*b check.eq(c, M(2,1,{-3,-2}), "inverse") -- pseudo-inverse local c = m:pinv()*b check.eq(c, M(2,1,{-3,-2}), "pseudo-inverse") end) april-ann-0.4.1/packages/basics/matrix/test/test_matrix_math.lua000066400000000000000000000502621263004425400247660ustar00rootroot00000000000000-- TODO: implement unit tests for index, indexCopy, indexFill, operator [{}] local check = utest.check local T = utest.test -- function do_test() T("MathOpTest", function() local m = matrix(3,4,5):linspace() local m2 = m:t(1,2) local a = m2:select(1,1) local b = matrix(5,2):linspace() local c = a*b check.eq(c, matrix(3,2,{ 95, 110, 595, 710, 1095, 1310, })) local a = matrix(2,4,3,{ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, }) ca = a:select(2,2):complement() check.eq(ca, matrix(2,4,3,{ 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, }):select(2,2), "select") local a = matrix.fromString[[ 1 3 ascii 1 2 3 ]] local b = matrix.fromString[[ 3 1 ascii 1 4 7 ]] local c = a*b check.eq(c:get(1,1), 1*1+2*4+3*7, "dot product") check.eq(b*a, matrix(3,3,{ 1, 2, 3, 4, 8, 12, 7, 14, 21, }), "cross product") local d = matrix.fromString[[ 3 3 ascii 1 2 3 4 5 6 7 8 9 ]] check.eq(d:clone(), matrix(3,3,{ 1, 2, 3, 4, 5, 6, 7, 8, 9, }), "clone") check(d:transpose(), matrix(3,3,{ 1, 4, 7, 2, 5, 8, 3, 6, 9, }), "transpose") check(d:transpose():clone(), matrix(3,3,{ 1, 4, 7, 2, 5, 8, 3, 6, 9, }), "transpose clone") local e = d * d check(e, matrix(3,3,{ 30, 36, 42, 66, 81, 96, 102, 126, 150, }), "matrix mult *") local h = d:slice({2,2},{2,2}) check(h, matrix(2,2,{ 5, 6, 8, 9, }), "matrix slice") local h = d:slice({2,2},{2,2},true) check(h, matrix(2,2,{ 5, 6, 8, 9, }), "matrix slice clone") local e = h * h check(e, matrix(2,2,{ 73, 84, 112, 129, }), "matrix slice mul *") local l = matrix(2,2):fill(4) + h check(l, matrix(2,2,{ 9, 10, 12, 13, }), "matrix fill and slice add +") local g = matrix(3,2,{1,2, 3,4, 5,6}) check(g:transpose():clone(), matrix(2,3,{ 1, 3, 5, 2, 4, 6, }), "transpose + clone") check(g:transpose():clone():transpose():clone(), matrix(2,3,{ 1, 3, 5, 2, 4, 6, }), "transpose + clone + transpose + clone") check(g:transpose(), matrix(2,3,{ 1, 3, 5, 2, 4, 6, }), "transpose") check(g:transpose():clone(), matrix(2,3,{ 1, 3, 5, 2, 4, 6, }), "transpose clone") local h = matrix(table.unpack(g:transpose():dim())) check(h:copy(g:transpose()), matrix(2,3,{ 1, 3, 5, 2, 4, 6, }), "copy transposed") local j = g:transpose() * g check(j, matrix(2,2,{ 35, 44, 44, 56, }), "transpose mul *") local j = matrix(2,2):gemm{ trans_A=true, trans_B=false, alpha=1.0, A=g, B=g, beta=0.0 } check(j, matrix(2,2,{ 35, 44, 44, 56, }), "gemm") local j = matrix(2,2):transpose():gemm{ trans_A=true, trans_B=false, alpha=1.0, A=g, B=g, beta=0.0 } check(j, matrix(2,2,{ 35, 44, 44, 56, }), "gemm in col_major") end) --------------------------------------------------------------- --------------------------------------------------------------- --------------------------------------------------------------- T("SVDTest", function() local m = matrix(4,5,{1,0,0,0,2, 0,0,3,0,0, 0,0,0,0,0, 0,4,0,0,0}) local U,S,V = m:svd() check(U, matrix(4,4, { 0,0,1, 0, 0,1,0, 0, 0,0,0,-1, 1,0,0, 0, }), "SVD U matrix") check(S:to_dense(), matrix(4,{4,3,2.23607,0}):diagonalize(), "SVD S matrix") check(V, matrix(5,5, { 0,1,0,0,0, 0,0,1,0,0, 0.447214,0,0,0,0.894427, 0,0,0,1,0, -0.894427,0,0,0,0.447214, }), "SVD V matrix") end) --------------------------------------------------------------- --------------------------------------------------------------- --------------------------------------------------------------- T("SliceTest", function() local m = matrix(20,20):uniformf() local subm = m:slice({5,4},{6,9}) check.eq(subm, m("5:10","4:12"), "slice() 1") check.eq(subm, m({5,10},{4,12}), "slice() 2") local subm = m:slice({1,4},{6,m:dim(2)-3}) check.eq(subm, m(":6","4:"), "slice() 3") -- local m = matrix(1,4):transpose():linear() check.eq(m:slice({1,1},{2,1},true), matrix(2,1,{0,1}), "slice 4") check.eq(m:slice({3,1},{2,1},true), matrix(2,1,{2,3}), "slice 5") check.eq(m:slice({1,1},{2,1}), matrix(2,1,{0,1}), "slice 6") check.eq(m:slice({3,1},{2,1}), matrix(2,1,{2,3}), "slice 7") -- local m = matrix(1,4):linear() check.eq(m:slice({1,1},{1,2},true), matrix(1,2,{0,1}), "slice 8") check.eq(m:slice({1,3},{1,2},true), matrix(1,2,{2,3}), "slice 9") check.eq(m:slice({1,1},{1,2}), matrix(1,2,{0,1}), "slice 10") check.eq(m:slice({1,3},{1,2}), matrix(1,2,{2,3}), "slice 11") end) local function load_csv() local def = nan local m = matrix.read( aprilio.stream.input_lua_string"1,2,3,,4\n5,6,7,8,\n4,,,,5", { [matrix.options.delim]=",", [matrix.options.empty]=true, [matrix.options.default]=def, [matrix.options.tab]=true } ) return m end T("CSVTest", function() local m = load_csv() -- TODO: nan comparison returns always FALSE -- check.eq(m, matrix(3,5,{1,2,3,"-nan",4,5,6,7,8,"-nan",4,"-nan","-nan","-nan",5})) end) local tmpname = os.tmpname() T("SerializationTest", function() local m = matrix(10,20):uniformf() m:toFilename(tmpname) check.eq(matrix.fromFilename(tmpname), m, "toFilename/fromFilename") m:toFilename(tmpname, "ascii") check.eq(matrix.fromFilename(tmpname), m, "toFilename/fromFilename ascii") m:toFilename(tmpname, "binary") check.eq(matrix.fromFilename(tmpname), m, "toFilename/fromFilename binary") m:toTabFilename(tmpname) check.eq(matrix.fromTabFilename(tmpname), m, "toTabFilename/fromTabFilename") check.eq(matrix(10,20,m:toTable()), m) end) os.remove(tmpname) T("EQandNEQTest", function() local m = load_csv() local def = nan check.eq(m:eq(def), matrixBool(3,5,{0,0,0,1,0,0,0,0,0,1,0,1,1,1,0}), "NAN eq") check.eq(m:neq(def), matrixBool(3,5,{1,1,1,0,1,1,1,1,1,0,1,0,0,0,1}), "NAN neq") check.eq(m:eq(4), matrixBool(3,5,{0,0,0,0,1,0,0,0,0,0,1,0,0,0,0}), "4 eq") check.eq(m:neq(4), matrixBool(3,5,{1,1,1,1,0,1,1,1,1,1,0,1,1,1,1}), "4 neq") check.eq(m:eq(m), matrixBool(3,5):ones(), "eq m") check.eq(m:neq(m), matrixBool(3,5):zeros(), "neq m") end) T("SumTest", function() local m = matrix(2, 3, {1, 2, 3, 4, 5, 6}) check.eq(m:sum(), 1+2+3+4+5+6, "sum()") check.eq(m:sum(1), matrix(1, 3, {1+4, 2+5, 3+6}), "sum(1)") check.eq(m:sum(2), matrix(2, 1, {1+2+3, 4+5+6}), "sum(2)") local m = matrix(2, 4, 3, { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}) check.eq(m:sum(), 1+2+3+4+5+6+7+8+9+10+11+12+13+14+15+16+17+18+19+20+21+22+23+24, "sum() 2") check.eq(m:sum(1), matrix(1, 4, 3, { 1+13, 2+14, 3+15, 4+16, 5+17, 6+18, 7+19, 8+20, 9+21, 10+22, 11+23, 12+24}), "sum(1) 2") check.eq(m:sum(2), matrix(2, 1, 3, { 1+4+7+10, 2+5+8+11, 3+6+9+12, 13+16+19+22, 14+17+20+23, 15+18+21+24}), "sum(2) 2") check.eq(m:sum(3), matrix(2, 4, 1, { 1+2+3, 4+5+6, 7+8+9, 10+11+12, 13+14+15, 16+17+18, 19+20+21, 22+23+24}), "sum(3) 2") end) T("MaxTest", function() local m = matrix(2, 3, {1, 4, 2, 6, 3, 5}) check.eq(m:max(), 6, "max()") check.eq(m:max(1), matrix(1, 3, {6, 4, 5}), "max(1)") check.eq(m:max(2), matrix(2, 1, {4, 6}), "max(2)") local m = m - 10 check.eq(m:max(), -4, "max()") check.eq(m:max(1), matrix(1, 3, {-4, -6, -5}), "max(1)") check.eq(m:max(2), matrix(2, 1, {-6, -4}), "max(2)") local m = matrix(2, 4, 3, { 12, 14, 18, 8, 5, 6, 7, 16, 9, 10, 24, 1, 13, 2, 15, 4, 17, 3, 19, 20, 21, 22, 23, 11}) check.eq(m:max(), 24, "max() 2") local a,b = m:max(1) check.eq(a, matrix(1, 4, 3, { 13, 14, 18, 8, 17, 6, 19, 20, 21, 22, 24, 11 }), "max(1) a") check.eq(b:convert_to("float"), matrix(1, 4, 3, { 2, 1, 1, 1, 2, 1, 2, 2, 2, 2, 1, 2 }), "max(1) b") local a,b = m:max(2) check.eq(a, matrix(2, 1, 3, { 12, 24, 18, 22, 23, 21 }), "max(2) a") check.eq(b:convert_to("float"), matrix(2, 1, 3, { 1, 4, 1, 4, 4, 3 }), "max(2) b") local a,b = m:max(3) check.eq(a, matrix(2, 4, 1, { 18, 8, 16, 24, 15, 17, 21, 23 }), "max(3) a") check.eq(b:convert_to("float"), matrix(2, 4, 1, { 3, 1, 2, 2, 3, 2, 3, 2 }), "max(3) b") end) T("MinTest", function() local m = matrix(2, 3, {1, 4, 2, 6, 3, 5}) check.eq(m:min(), 1, "min()") check.eq(m:min(1), matrix(1, 3, {1, 3, 2}), "min(1)") check.eq(m:min(2), matrix(2, 1, {1, 3}), "min(2)") local m = m - 10 check.eq(m:min(), -9, "min()") check.eq(m:min(1), matrix(1, 3, {-9, -7, -8}), "min(1)") check.eq(m:min(2), matrix(2, 1, {-9, -7}), "min(2)") local m = matrix(2, 4, 3, { 12, 14, 18, 8, 5, 6, 7, 16, 9, 10, 24, 1, 13, 2, 15, 4, 17, 3, 19, 20, 21, 22, 23, 11}) check.eq(m:min(), 1, "min() 2") local a,b = m:min(1) check.eq(a, matrix(1, 4, 3, { 12, 2, 15, 4, 5, 3, 7, 16, 9, 10, 23, 1 }), "min(1) a") check.eq(b:convert_to("float"), matrix(1, 4, 3, { 1, 2, 2, 2, 1, 2, 1, 1, 1, 1, 2, 1 }), "min(1) b") local a,b = m:min(2) check.eq(a, matrix(2, 1, 3, { 7, 5, 1, 4, 2, 3 }), "min(2) a") check.eq(b:convert_to("float"), matrix(2, 1, 3, { 3, 2, 4, 2, 1, 2 }), "min(2) b") local a,b = m:min(3) check.eq(a, matrix(2, 4, 1, { 12, 5, 7, 1, 2, 3, 19, 11 }), "min(3) a") check.eq(b:convert_to("float"), matrix(2, 4, 1, { 1, 2, 1, 3, 2, 3, 1, 3 }), "min(3) b") end) T("BrodacastTest", function() local a = matrix(4,1,{0,10,20,30}) local b = matrix(3,{0,1,2}) local c = matrix.ext.broadcast(a.add, a, b) local d = matrix.ext.broadcast(a.add, a, b) local e = matrix(4,3,{0,1,2, 10,11,12, 20,21,22, 30,31,32}) check.eq(c,e) check.eq(d,e) -- local x = matrix(4):linear() local xx = x:rewrap(4,1) local y = matrix(5):ones() local z = matrix(3,4):ones() check.errored(function() matrix.ext.broadcast(x.add, x, y) end) check.eq(matrix.ext.broadcast(xx.add, xx, y), matrix(4,5,{1,1,1,1,1, 2,2,2,2,2, 3,3,3,3,3, 4,4,4,4,4,})) check.eq(matrix.ext.broadcast(x.add, x, z), matrix(3,4,{1,2,3,4, 1,2,3,4, 1,2,3,4})) end) T("IndexMetaMethods", function() local m1 = matrix(30,20,10):linspace() check.eq(m1:select(1,20), m1[20]) m1[10] = m1[25] check.eq(m1:select(1,10), m1:select(1,25)) m1[{10,20,10}] = 10 check.eq(m1[{10,20,10}], matrix(1,1,1,{10})) check.eq(m1(10,20,10), matrix(1,1,1,{10})) end) T("IndexMethods", function() local m = matrix(4,2, {1,2, 3,4, 5,6, 7,8}) local idx = matrixInt32{1,3} local m2 = m:index(1,idx) check.eq(m2, matrix(2,2,{1,2, 5,6})) check.eq(m:rewrap(8):index(1,idx), matrix{1,3}) check.eq(m:rewrap(8,1):index(1,idx), matrix(2,1,{1,3})) check.eq(m:rewrap(1,8,1,1):index(2,idx), matrix(1,2,1,1,{1,3})) -- local x = matrix.fromString[[5 5 ascii 0.8020 0.7246 0.1204 0.3419 0.4385 0.0369 0.4158 0.0985 0.3024 0.8186 0.2746 0.9362 0.2546 0.8586 0.6674 0.7473 0.9028 0.1046 0.9085 0.6622 0.1412 0.6784 0.1624 0.8113 0.3949 ]] local z = matrix(5,2) z:select(2,1):fill(-1) z:select(2,2):fill(-2) x:indexed_copy(2,matrixInt32{5,1},z) local y = matrix.fromString[[5 5 ascii -2.0000 0.7246 0.1204 0.3419 -1.0000 -2.0000 0.4158 0.0985 0.3024 -1.0000 -2.0000 0.9362 0.2546 0.8586 -1.0000 -2.0000 0.9028 0.1046 0.9085 -1.0000 -2.0000 0.6784 0.1624 0.8113 -1.0000 ]] check.eq(x, y) -- x:indexed_fill(2,matrixInt32{5,1},-3) local y = matrix.fromString[[5 5 ascii -3.0000 0.7246 0.1204 0.3419 -3.0000 -3.0000 0.4158 0.0985 0.3024 -3.0000 -3.0000 0.9362 0.2546 0.8586 -3.0000 -3.0000 0.9028 0.1046 0.9085 -3.0000 -3.0000 0.6784 0.1624 0.8113 -3.0000 ]] check.eq(x, y) -- local x = x:flatten() x:indexed_copy(1,matrixInt32{5,1},z[1]) local y = x:clone() y[5] = z[1][1] y[1] = z[1][2] check.eq(x, y) end) T("SqueezeAndRewrap", function() local m = matrix(2,3,1,2,1,3):linear():squeeze() check.eq(m, matrix(2,3,2,3):linear()) end) T("LargeMatrices", function() local m1 = matrix(300,200,100) local m2 = matrix(300,200,100) for i=1,m1:dim(3) do m1:select(3,i):fill(i) end for i=1,m2:dim(3) do m2(':',':',i):fill(i) end check.eq(m1, m2, "select and slice") m1,m2=nil,nil collectgarbage("collect") -- local m1 = matrix(300,200,100):fill(200) local eq = true for i=1,m1:size() do eq = eq and m1:raw_get(i-1) == 200 end check.TRUE(eq, "fill") -- m1:scalar_add(10) local eq = true for i=1,m1:size() do eq = eq and m1:raw_get(i-1) == 210 end check.TRUE(eq, "scalar_add") -- m1:scal(0.5) local eq = true for i=1,m1:size() do eq = eq and m1:raw_get(i-1) == 105 end check.TRUE(eq, "scalar") -- local aux = m1:sum(1):scal(1/300):sum(1):scal(1/200):sum()/100 check.number_eq(aux, 105) local aux = m1:select(3,1):sum(1):scal(1/300):sum()/200 check.number_eq(aux, 105) local m1 = nil collectgarbage("collect") -- local m1 = matrix(300,200,100):uniformf() m1:set(290,190,1, -20) check.eq(-20, (m1:min())) check.eq(-20, (m1:min(1):min(1):min())) check.eq(-20, (m1:select(3,1):min())) check.eq(-20, (m1:select(3,1):min(1):min())) end) T("MatrixCastingTest", function() local m = matrix.fromString[[4 5 ascii -0.61696 -0.0046727 0.24422 0.63568 -0.12454 0.22422 0.57072 0.54272 0.55995 0.72134 -0.45481 -0.69873 -0.44707 -0.60296 0.60374 0.63033 0.91628 -0.68237 0.75187 -0.76772 ]] local gt_0 = m:gt(0) for src in iterator{ "bool", "double", "float", "int32", "char" } do local gt_0 = gt_0:convert_to(src) check.eq(gt_0, gt_0:convert_to("double"):convert_to(src), "double->"..src) check.eq(gt_0, gt_0:convert_to("float"):convert_to(src), "float->"..src) check.eq(gt_0, gt_0:convert_to("int32"):convert_to(src), "int32->"..src) check.eq(gt_0, gt_0:convert_to("char"):convert_to(src), "char->"..src) check.eq(gt_0, gt_0:convert_to("bool"):convert_to(src), "bool->"..src) end local gt_idx = gt_0:flatten():to_index() check.eq(gt_idx, matrixInt32{3,4,6,7,8,9,10,15,16,17,19}, "to_index()") end) T("MatrixProdTest", function() local a = matrix(3,4,{ 0,1,2,3, 1,1,2,2, 1,0,1,1 }) check.eq( a:prod(), 0 ) check.eq( a:prod(1), matrix(1,4, {0,0,4,6}) ) check.eq( a:prod(2), matrix(3,1, {0, 4, 0}) ) end) T("MatrixCumOps", function() local x = matrix{1,2,3,4} local y = x:rewrap(2,2) check.eq(x:cumsum(), x:cumsum(1)) check.eq(x:cumsum(), matrix{1,3,6,10}) check.eq(y:cumsum(), y:cumsum(1)) check.eq(y:cumsum(), matrix(2,2,{1,2, 4,6})) check.eq(y:cumsum(2), matrix(2,2,{1,3, 3,7})) check.eq(x:cumprod(), x:cumprod(1)) check.eq(x:cumprod(), matrix{1,2,6,24}) check.eq(y:cumprod(), y:cumprod(1)) check.eq(y:cumprod(), matrix(2,2,{1,2, 3,8})) check.eq(y:cumprod(2), matrix(2,2,{1,2, 3,12})) end) end -- do_test() if util.is_cuda_available() then -- forces the use of CUDA mathcore.set_use_cuda_default(util.is_cuda_available()) do_test() end april-ann-0.4.1/packages/basics/matrix/test/test_referenced_vector.lua000066400000000000000000000005761263004425400261400ustar00rootroot00000000000000a = util.vector_float() for i = 1,50 do a:push_back(i) end m = a:toMatrix(false) -- do not reuse vector print(m) print("La longitud del vector es",a:size()) print("Tomamos el vector para la matriz") m = a:toMatrix() -- reuse vector print(m) print("La longitud del vector es",a:size()) a = util.vector_uint() for i = 1,10 do a:push_back(i) end print(a) print(a:toMatrix()) april-ann-0.4.1/packages/basics/matrix/test/test_sparse_matrix.lua000066400000000000000000000231161263004425400253300ustar00rootroot00000000000000local blockf = mathcore.block.float local blocki = mathcore.block.int32 -- local function dense(m) return (class.is_a(m,matrix.sparse) and m:to_dense()) or m end local make_eq = function(m1,m2) return function() local m1,m2=dense(m1),dense(m2) return m1:equals(m2) end end -- local check = utest.check local T = utest.test -- local a_dense = matrix(4,5,{ 1, 0, 0, -1, 2, 0, 0, 2, 1, 0, 0, 0, 0, 1, -2, -4, 0, 2, 0, 0, }) local a_sparse_csr,a_sparse_csc T("SparseConstructorsTest", function() a_sparse_csr = matrix.sparse.csr(4,5, blockf{1,-1,2,2,1,1,-2,-4,2}, blocki{0, 3,4,2,3,3, 4, 0,2}, blocki{0,3,5,7,9}) a_sparse_csc = matrix.sparse.csc(4,5, blockf{1,-4,2,2,-1,1,1,2,-2}, blocki{0, 3,1,3, 0,1,2,0, 2}, blocki{0,2,2,4,7,9}) check(make_eq(a_sparse_csr, a_dense), "CSR constructor from blocks") check(make_eq(a_sparse_csc, a_dense), "CSC constructor from blocks") a_sparse_csr = matrix.sparse.csr(a_dense) a_sparse_csc = matrix.sparse.csc(a_dense) check(make_eq(a_sparse_csr, a_dense), "CSR constructor from dense") check(make_eq(a_sparse_csc, a_dense), "CSC constructor from dense") local aux2 = matrix.sparse.diag(matrix(5,{1,2,3,4,5}),"csc") local aux3 = matrix.sparse.diag(blockf({1,2,3,4,5}),"csc") local aux4 = matrix.sparse.diag({1,2,3,4,5},"csc") check(make_eq(aux2, aux3), "diag CSC constructors 1") check(make_eq(aux2, aux4), "diag CSC constructors 2") local aux2 = matrix.sparse.diag(matrix(5,{1,2,3,4,5}),"csr") local aux3 = matrix.sparse.diag(blockf({1,2,3,4,5}),"csr") local aux4 = matrix.sparse.diag({1,2,3,4,5},"csr") check(make_eq(aux2, aux3), "diag CSR constructors 1") check(make_eq(aux2, aux4), "diag CSR constructors 2") end) T("SparseMaxTest", function() check(function() return a_sparse_csr:max() == 2 end, "CSR max") check(function() return a_sparse_csc:max() == 2 end, "CSC max") end) T("SparseAXPYTest", function() local m = matrix(9,1):linspace() local m2 = matrix.sparse.csc(3,3, blockf{10,-4}, blocki{1,0}, blocki{0,1,2,2}) local aux = m2:as_vector() check(function() return make_eq(m:clone():axpy(1.0,aux:to_dense()), m:clone():axpy(1.0,aux))() end) check(function() return make_eq(m:rewrap(3,3):clone():axpy(1.0,m2:to_dense()), m:rewrap(3,3):clone():axpy(1.0,m2))() end) check.errored(function() m:rewrap(3,3):clone():axpy(1.0,aux) end) check.errored(function() m:clone():axpy(1.0,m2) end) end) T("SparseSerializationTest", function() local b = matrix.sparse.csr(3,blockf{3},blocki{2}) local aux3 = matrix.sparse.diag(blockf({1,2,3,4,5}),"csr") local str = aux3:toString("ascii") check.eq(str, [[5 5 5 ascii csr 1 2 3 4 5 0 1 2 3 4 0 1 2 3 4 5 ]], "CSR serialization") local str = aux3:transpose():toString("ascii") check.eq(str, [[5 5 5 ascii csc 1 2 3 4 5 0 1 2 3 4 0 1 2 3 4 5 ]], "CSR transpose + CSC serialization") end) local a_csc = matrix.sparse.csc(matrix(3,4,{ 1, 2, 3, 0, 0, 0, 2, 0, 0, -1, 0, 1, })) local a_csr = matrix.sparse.csr(matrix(3,4,{ 1, 2, 3, 0, 0, 0, 2, 0, 0, -1, 0, 1, })) local b = matrix(4,2,{ 2, 1, 1, 0, -1, -2, 1, 2, }) T("SparseMMTesT", function() check(function() local c = matrix(3,2):zeros():sparse_mm({ trans_A=false, alpha=1.0, A=a_csc, B=b, beta=0.0, }) return make_eq(matrix(3,4,{ 1, 2, 3, 0, 0, 0, 2, 0, 0, -1, 0, 1, }) * b, c)() end, "CSC sparse_mm") check(function() local c = matrix(3,2):zeros():sparse_mm({ trans_A=false, alpha=1.0, A=a_csr, B=b, beta=0.0, }) return make_eq(matrix(3,4,{ 1, 2, 3, 0, 0, 0, 2, 0, 0, -1, 0, 1, }) * b, c)() end, "CSR sparse_mm") check(function() local c = matrix(3,2):zeros():sparse_mm({ trans_A=true, alpha=1.0, A=a_csc:transpose(), B=b, beta=0.0, }) return make_eq(matrix(3,4,{ 1, 2, 3, 0, 0, 0, 2, 0, 0, -1, 0, 1, }) * b, c)() end, "CSC + transpose sparse_mm") check(function() local c = matrix(3,2):zeros():sparse_mm({ trans_A=true, alpha=1.0, A=a_csr:transpose(), B=b, beta=0.0, }) return make_eq(matrix(3,4,{ 1, 2, 3, 0, 0, 0, 2, 0, 0, -1, 0, 1, }) * b, c)() end, "CSR + transpose sparse_mm") end) local x = matrix(4):linear() local y = matrix(3):zeros() T("SparseGEMVTest", function() check(function() y:gemv({ trans_A=false, alpha=1.0, A=a_csc, X=x, beta=0.0 }) return make_eq(a_csc:to_dense()*x, y)() end, "CSC GEMV") check(function() y:gemv({ trans_A=true, alpha=1.0, A=a_csc:transpose(), X=x, beta=0.0 }) return make_eq(a_csc:to_dense()*x, y)() end, "CSC transpose + CSR GEMV") check(function() y:gemv({ trans_A=false, alpha=1.0, A=a_csr, X=x, beta=0.0 }) return make_eq(a_csc:to_dense()*x, y)() end, "CSR GEMV") check(function() y:gemv({ trans_A=true, alpha=1.0, A=a_csr:transpose(), X=x, beta=0.0 }) return make_eq(a_csc:to_dense()*x, y)() end, "CSR + transpose + CSC GEMV") end) ---------------------------------------------------------------------------- T("SparseDotTest", function() local x = matrix(10,1):uniformf(-10,10,random(1234)) local y = matrix(1,10,{1,-1,4,0,0,2,0,0,0,-3}) local z = x:dot(y) local y_csr = matrix.sparse.csr(y) local y_csc = y:transpose() -- FIXME: this test is failing in travis :S -- check.eq(x:dot(y_csr),z) check.eq(x:dot(y_csc),z, "csc dot") end) T("SparseDOKBuilder", function() local d = matrix.sparse.builders.dok() d:set(1, 1, 1.0) d:set(2, 1, 1.0) d:set(1, 3, -1.0) d:set(3, 2, -1.0) check.eq(d:build(), matrix.sparse(matrix(3,3,{ 1.0, 0.0, -1.0, 1.0, 0.0, 0.0, 0.0, -1.0, 0.0, }))) check.eq(d:build(4,4), matrix.sparse(matrix(4,4,{ 1.0, 0.0, -1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, }))) check.eq(d:build(3,4), matrix.sparse(matrix(3,4,{ 1.0, 0.0, -1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, 0.0, }))) check.eq(d:build(4,3), matrix.sparse(matrix(4,3,{ 1.0, 0.0, -1.0, 1.0, 0.0, 0.0, 0.0, -1.0, 0.0, 0.0, 0.0, 0.0, }))) check.errored(function() d:build(2,3) end) check.errored(function() d:build(3,2) end) check.errored(function() d:set(0, 2, 1.0) end) check.errored(function() d:set(2, 0, 1.0) end) local d = matrix.sparse.builders.dok() d:set(2, 1, 4) d:set(2, 2, 0) d:set(3, 5, -1) d:set(3, 5, 0) -- remove previous value check.eq(d:build(), matrix.sparse(matrix(3,5,{ 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, }))) local d = matrix.sparse.builders.dok() d:set(2,2,-1) check.eq(d:build(), matrix.sparse(matrix(2,2,{0,0, 0,-1}))) end) april-ann-0.4.1/packages/basics/producer_fifo_wrapper/000077500000000000000000000000001263004425400230055ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/producer_fifo_wrapper/binding/000077500000000000000000000000001263004425400244175ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/producer_fifo_wrapper/binding/bind_producer_fifo_wrapper.lua.cc000066400000000000000000000033521263004425400330730ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C #include "bind_function_interface.h" //BIND_END //BIND_HEADER_H #include "producer_fifo_wrapper.h" //BIND_END //BIND_LUACLASSNAME ProducerFifoWrapper utils.producer_fifo_wrapper //BIND_CPP_CLASS ProducerFifoWrapper //BIND_LUACLASSNAME DoubleDataProducer __double_data_producer__ //BIND_SUBCLASS_OF ProducerFifoWrapper DoubleDataProducer //BIND_CONSTRUCTOR ProducerFifoWrapper { LUABIND_CHECK_ARGN(==, 0); LUABIND_RETURN(ProducerFifoWrapper, new ProducerFifoWrapper()); } //BIND_END //BIND_METHOD ProducerFifoWrapper put { LUABIND_CHECK_ARGN(==, 1); int vec_size = luaL_len(L, 1); double *vec = new double[vec_size]; LUABIND_TABLE_TO_VECTOR(1, double, vec, vec_size); obj->put(vec); } //BIND_END //BIND_METHOD ProducerFifoWrapper lock { LUABIND_CHECK_ARGN(==, 0); obj->lock(); } //BIND_END //BIND_METHOD ProducerFifoWrapper unlock { LUABIND_CHECK_ARGN(==, 0); obj->unlock(); } //BIND_END april-ann-0.4.1/packages/basics/producer_fifo_wrapper/c_src/000077500000000000000000000000001263004425400240765ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/producer_fifo_wrapper/c_src/producer_fifo_wrapper.cc000066400000000000000000000024361263004425400310000ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #include "producer_fifo_wrapper.h" ProducerFifoWrapper::ProducerFifoWrapper() { } ProducerFifoWrapper::~ProducerFifoWrapper() { } double* ProducerFifoWrapper::get() { return queue.get(); } void ProducerFifoWrapper::reset() { while (!queue.empty()) { double *aux = queue.get(); delete[] aux; } } void ProducerFifoWrapper::put(double *v) { queue.put(v); } void ProducerFifoWrapper::unlock() { queue.unlock(); } void ProducerFifoWrapper::lock() { queue.lock(); } april-ann-0.4.1/packages/basics/producer_fifo_wrapper/c_src/producer_fifo_wrapper.h000066400000000000000000000025671263004425400306470ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Francisco Zamora-Martinez * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ #ifndef PRODUCER_FIFO_WRAPPER_H #define PRODUCER_FIFO_WRAPPER_H #include "function_interface.h" #include "mutexed_fifo.h" using AprilThreadUtils::MutexedFIFO; using namespace Functions; class ProducerFifoWrapper : public DataProducer { MutexedFIFO queue; public: ProducerFifoWrapper(); ~ProducerFifoWrapper(); // metodos para dar cuenta de dataproducer double *get(); void reset(); // metodos wrapper de mutexedfifo void unlock(); void lock(); // metodo para bindear a lua: void put(double*); }; #endif // PRODUCER_FIFO_WRAPPER_H april-ann-0.4.1/packages/basics/producer_fifo_wrapper/package.lua000066400000000000000000000020471263004425400251060ustar00rootroot00000000000000package{ name = "producer_fifo_wrapper", version = "1.0", depends = { "util", "thread_utils", "function_interface" }, keywords = { }, description = "", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", copy{ file= "c_src/*.h", dest_dir = "include" }, provide_bind{ file = "binding/bind_producer_fifo_wrapper.lua.cc" , dest_dir = "include" }, }, target{ name = "build", depends = "provide", use_timestamp = true, object{ file = "c_src/*.cc", dest_dir = "build", -- flags = "-std=c99", }, luac{ orig_dir = "lua_src", dest_dir = "build", }, build_bind{ file = "binding/bind_producer_fifo_wrapper.lua.cc", dest_dir = "build" }, }, target{ name = "document", document_src{ }, document_bind{ }, }, } april-ann-0.4.1/packages/basics/profiler/000077500000000000000000000000001263004425400202415ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/profiler/lua_src/000077500000000000000000000000001263004425400216715ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/profiler/lua_src/profiler.lua000066400000000000000000000043121263004425400242160ustar00rootroot00000000000000profiler={} profiler.stopwatch = util.stopwatch() profiler.last_t = 0 profiler.total_time = 0 profiler.profile = {} function profiler.hook(event) profiler.stopwatch:stop() local t = profiler.stopwatch:read() local funcname = debug.getinfo(2, "n").name local last_func = debug.getinfo(3, "n").func local elapsed_time = t - profiler.last_t local info = debug.getinfo(2, "fnSlu") if event == "call" then --[[ if info.what == "Lua" then print ("call ->", info.name, info.what, info.namewhat, info.source, info.short_src, info.lastlinedefined) end --]] if funcname then if not profiler.profile[info.func] then profiler.profile[info.func] = info profiler.profile[info.func].call_count = 0 profiler.profile[info.func].time = 0 profiler.profile[info.func].line = info.currentline end profiler.profile[info.func].call_count = profiler.profile[info.func].call_count + 1 end if last_funcname then profiler.profile[last_func].time = profiler.profile[last_func].time + elapsed_time profiler.total_time = profiler.total_time + elapsed_time end elseif event == "return" or event == "tail return" then --print ("return ->", debug.getinfo(2,"n").name) if funcname and profiler.profile[info.func] then profiler.profile[info.func].time = profiler.profile[info.func].time + elapsed_time profiler.total_time = profiler.total_time + elapsed_time end end profiler.last_t = t profiler.stopwatch:go() end function profiler.start() profiler.stopwatch:go() debug.sethook(profiler.hook, "cr") end function profiler.stop() debug.sethook() profiler.stopwatch:stop() end function profiler.save(outfile) profile_list = {} for func, info in pairs(profiler.profile) do table.insert(profile_list, info) end table.sort(profile_list, function(a,b) return a.time > b.time end) fprintf(outfile, "Total time: %f\n", profiler.total_time) fprintf(outfile, "%58s\t%8s\t%s\t%s\n", "NAME", "TIME", "CALL_COUNT", "LINE") for i, info in ipairs(profile_list) do fprintf(outfile,"[%6s]%50s\t%8.2f\t%10d\t%d\n", info.what, string.format("%s@%s",info.name, info.source), info.time, info.call_count, info.line) end end april-ann-0.4.1/packages/basics/profiler/package.lua000066400000000000000000000012311263004425400223340ustar00rootroot00000000000000 package{ name = "profiler", version = "1.0", depends = { "util" }, keywords = { "profiler" }, description = "", -- targets como en ant target{ name = "init", mkdir{ dir = "build" }, mkdir{ dir = "include" }, }, target{ name = "clean", delete{ dir = "build" }, delete{ dir = "include" }, }, target{ name = "provide", depends = "init", }, target{ name = "build", depends = "provide", use_timestamp = true, luac{ orig_dir = "lua_src", dest_dir = "build", }, }, target{ name = "document", document_src{}, document_bind{}, }, } april-ann-0.4.1/packages/basics/profiler/test/000077500000000000000000000000001263004425400212205ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/profiler/test/profile.lua000066400000000000000000000002411263004425400233600ustar00rootroot00000000000000__profiled_program_name = arg[1] table.remove(arg,1) profiler.start() dofile(__profiled_program_name) profiler.stop() profiler.save(io.open("profile.out", "w")) april-ann-0.4.1/packages/basics/random/000077500000000000000000000000001263004425400176775ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/random/binding/000077500000000000000000000000001263004425400213115ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/random/binding/bind_mtrand.lua.cc000066400000000000000000000226241263004425400246670ustar00rootroot00000000000000/* * This file is part of APRIL-ANN toolkit (A * Pattern Recognizer In Lua with Artificial Neural Networks). * * Copyright 2012, Salvador España-Boquera * * The APRIL-ANN toolkit is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 3 as * published by the Free Software Foundation * * This library is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License * along with this library; if not, write to the Free Software Foundation, * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * */ //BIND_HEADER_C IMPLEMENT_LUA_TABLE_BIND_SPECIALIZATION(MTRand); //BIND_END //BIND_HEADER_H #include "bind_april_io.h" #include "MersenneTwister.h" #include "dice.h" #include "utilLua.h" using Basics::MTRand; using Basics::Dice; //BIND_END //BIND_LUACLASSNAME Serializable aprilio.serializable //BIND_LUACLASSNAME MTRand random //BIND_CPP_CLASS MTRand //BIND_SUBCLASS_OF MTRand Serializable //BIND_CONSTRUCTOR MTRand //DOC_BEGIN // random() //DOC_END //DOC_BEGIN // random(uint32_t n) /// @param n Valor de la semilla //DOC_END //DOC_BEGIN // random(uint32_t n[]) /// @param n[] Vector con semillas para inicializar //DOC_END { int argn = lua_gettop(L); /* number of arguments */ if ( argn == 0 || (argn == 1 && lua_isnil(L,1)) ) obj = new MTRand(); // auto-initialize with /dev/urandom or time() // and clock() else if (argn == 1) // initialize with a simple uint32 obj = new MTRand((uint32_t)luaL_checknumber(L, 1)); else { uint32_t *v = new uint32_t[argn]; int i; for (i=1; i <= argn; i++) { if (!lua_isnumber(L,i)) { delete[] v; lua_pushstring(L,"incorrect argument for mtrand initialization"); lua_error(L); } v[i-1] = (uint32_t)lua_tonumber(L,i); } obj = new MTRand(v, argn); delete[] v; } LUABIND_RETURN(MTRand, obj); } //BIND_END //BIND_DESTRUCTOR MTRand { } //BIND_END //BIND_METHOD MTRand rand //DOC_BEGIN // double rand() /** Genera un valor aleatorio del intervalo [0,n], donde * n es el argumento recibido. Si no se le da ningún valor se * considera n=1. */ //DOC_END //DOC_BEGIN // double rand(double n) /// Genera un valor aleatorio del intervalo [0,n], donde /// n es el argumento recibido. Si no se le da ningún valor se /// considera n=1. /// @param n Valor del intervalo [0,n] para generar el número aleatorio //DOC_END { LUABIND_CHECK_ARGN(<=, 1); double n; LUABIND_GET_OPTIONAL_PARAMETER(1,double,n,1); LUABIND_RETURN(number,obj->rand(n)); } //BIND_END //BIND_METHOD MTRand randExc //DOC_BEGIN // double randExc(double n = 1.0) /// Genera un valor aleatorio del intervalo [0,n), donde /// n es el argumento recibido. Si no se le da ningún valor se /// considera n=1. /// @param n Valor del intervalo [0,n) para generar el número aleatorio //DOC_END { LUABIND_CHECK_ARGN(<=, 1); double n; LUABIND_GET_OPTIONAL_PARAMETER(1,double,n,1); LUABIND_RETURN(number,obj->randExc(n)); } //BIND_END //BIND_METHOD MTRand randDblExc //DOC_BEGIN // double randDblExc(double n = 1.0) /// Genera un valor aleatorio del intervalo (0,n), donde /// n es el argumento recibido. Si no se le da ningún valor se /// considera n=1. /// @param n Valor del intervalo (0,n) para generar el número aleatorio //DOC_END { LUABIND_CHECK_ARGN(<=, 1); double n; LUABIND_GET_OPTIONAL_PARAMETER(1,double,n,1); LUABIND_RETURN(number,obj->randDblExc(n)); } //BIND_END //BIND_METHOD MTRand randInt // integer in [0,2^32-1] // integer in [0,x] if integer x is given // integer in [x,y] if integers x and y are given //DOC_BEGIN // uint32_t randInt(uint32_t ini = 0, uint32_t fin = 2^32 - 1) /// Genera un valor aleatorio del intervalo [ini, fin], donde /// x e y son los argumentos recibidos. Por defecto ini=0 y fin = 2^32 - 1. /// @param ini Punto inicial del intervalo /// @param fin Punto final del intervalo //DOC_END { LUABIND_CHECK_ARGN(<=, 2); int x,y,resul; // FIXME las hacemos uint32 ??? int argn = lua_gettop(L); /* number of arguments */ if (argn == 2) { LUABIND_GET_PARAMETER(1,int,x); // casting int a uint32 LUABIND_GET_PARAMETER(2,int,y); // casting int a uint32 if (y < x) LUABIND_ERROR("first argument must be <= second argument"); resul = x+obj->randInt(y-x); } else if (argn == 1) { LUABIND_GET_PARAMETER(1,int,x); // casting int a uint32 resul = obj->randInt(x); } else resul = obj->randInt(); LUABIND_RETURN(number,resul); } //BIND_END //BIND_METHOD MTRand shuffle //DOC_BEGIN // int[] shuffle(int size) /// @param size Tamaño de la secuencia que queremos desordenar //DOC_END //DOC_BEGIN // vector shuffle(vector) /// @param vector Vector a desordenar, devuelve OTRO vector desordenado //DOC_END { LUABIND_CHECK_ARGN(==, 1); int size = 0; // inicializamos para evitar warning int *vector = 0; bool is_number = true; if (lua_isnumber(L,1)) { // caso en que recibimos la talla de la tabla a generar LUABIND_GET_PARAMETER(1, int, size); if (size <= 0) LUABIND_ERROR("random shuffle: size must be >= 0"); } else if (lua_istable(L,1)) { // recibimos una tabla tipo vector y devolvemos otra con los // mismos elementos pero permutados size = luaL_len(L,1); is_number = false; } else LUABIND_ERROR("random shuffle: an int or a table expected"); vector = new int[size]; obj->shuffle(size,vector); // lua_createtable(L,narr,nrec) where narr array, nrec non-array lua_createtable(L, size, 0); // if (is_number) { // FIXME: USAR MACRO PARA CARGAR VECTOR??? for (int i=0; i < size; i++) { lua_pushnumber(L,vector[i]+1); lua_rawseti(L,2,i+1); } } else { for (int i=0; i < size; i++) { lua_rawgeti(L,1,vector[i]+1); lua_rawseti(L,2,i+1); } } delete[] vector; return 1; } //BIND_END //BIND_METHOD MTRand choose //DOC_BEGIN // element choose(vector) /// @param vector /// elige un elemento al azar del vector //DOC_END { LUABIND_CHECK_ARGN(==, 1); if (!lua_istable(L,1)) { LUABIND_ERROR("random choose: a table expected"); } int len = luaL_len(L,-1); if (len > 0) { int which = 1+obj->randInt(len-1); lua_rawgeti(L,-1,which); LUABIND_RETURN_FROM_STACK(-1); } } //BIND_END //BIND_METHOD MTRand randNorm //DOC_BEGIN // double randNorm(double mean, double variance) /// @param mean Media de la función gaussiana /// @param variance Varianza de la función gaussiana //DOC_END { double mean, variance; LUABIND_CHECK_ARGN(==, 2); LUABIND_GET_PARAMETER(1, double, mean); LUABIND_GET_PARAMETER(2, double, variance); LUABIND_RETURN(number,obj->randNorm(mean,variance)); } //BIND_END //BIND_METHOD MTRand seed //DOC_BEGIN // void seed() //DOC_END //DOC_BEGIN // void seed(uint32_t n) /// @param n Valor de la semilla inicial //DOC_END //DOC_BEGIN // void seed(uint32_t v[]) /// @param v[] Vector de semillas para inicializar el objeto //DOC_END { int argn = lua_gettop(L); /* number of arguments */ if (argn == 0) { obj->seed(); } else if (argn == 1) { obj->seed((uint32_t)luaL_checknumber(L, 1)); } else if (argn > 1) { uint32_t *v = new uint32_t[argn]; int i; for (i=1; i <= argn; i++) { v[i-1] = (uint32_t)luaL_checknumber(L, i); } obj->seed(v,argn); delete[] v; } } //BIND_END //BIND_METHOD MTRand clone //DOC_BEGIN // random *clone() //DOC_END { LUABIND_CHECK_ARGN(==, 0); MTRand *theclone = new MTRand(*obj); LUABIND_RETURN(MTRand,theclone); } //BIND_END //BIND_METHOD MTRand toTable //DOC_BEGIN // table toTable() //DOC_END { LUABIND_CHECK_ARGN(==, 0); uint32_t randState[ MTRand::SAVE ]; obj->save( randState ); lua_newtable(L); for (unsigned int i=0; i < MTRand::SAVE; i++) { lua_pushnumber(L,randState[i]); lua_rawseti(L,-2,i+1); } return 1; } //BIND_END //BIND_METHOD MTRand fromTable //DOC_BEGIN // void fromTable(table t) /// @param //DOC_END { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); uint32_t randState[ MTRand::SAVE ]; for (int i=1; i <= (int)MTRand::SAVE; i++) { lua_rawgeti(L,1,i); randState[i-1] = (uint32_t)luaL_checknumber(L, -1); lua_remove(L,-1); } obj->load( randState ); LUABIND_RETURN(MTRand,obj); } //BIND_END ///////////////////////////////////////////////////////////////////////////// //BIND_LUACLASSNAME Dice random.dice //BIND_CPP_CLASS Dice //BIND_CONSTRUCTOR Dice { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, table); // leer vector de doubles: double *v; int length = table_to_double_vector(L, &v); for (int i=0; igetOutcomes()); } //BIND_END //BIND_METHOD Dice thrown //DOC_BEGIN // int thrown(random *generator) //DOC_END { LUABIND_CHECK_ARGN(==, 1); LUABIND_CHECK_PARAMETER(1, MTRand); MTRand *generator = lua_toMTRand(L,1); LUABIND_RETURN(number,obj->thrown(generator)+1); } //BIND_END april-ann-0.4.1/packages/basics/random/c_src/000077500000000000000000000000001263004425400207705ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/000077500000000000000000000000001263004425400230415ustar00rootroot00000000000000april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/Makefile000066400000000000000000000020561263004425400245040ustar00rootroot00000000000000# Makefile for Wagner's Mersenne Twister class (MersenneTwister.h) # Define compiler and compilation options CC = g++ CFLAGS = -ansi -Wall COPTIM = -O3 # Compile example program .PHONY: all run test compare clean package all: example @ echo "Run the example program with './example'" @ echo "Or use 'make test' to test the output and speed of MersenneTwister.h" example: example.cpp MersenneTwister.h $(CC) $(CFLAGS) -o example example.cpp run: example ./example # Compile test suite test: @ $(MAKE) -C Test/ CC=$(CC) CFLAGS=$(CFLAGS) COPTIM=$(COPTIM) # Clean away executable and output files clean: @ rm -f example state.dat core @ $(MAKE) -C Test/ clean # Package files for distribution DIR = Mersenne-1.1 package: clean rm -rf $(DIR)/ mkdir $(DIR) cp README $(DIR)/ cp MersenneTwister.h $(DIR)/ cp example.cpp $(DIR)/ cp Makefile $(DIR)/ cp -R Test $(DIR)/ cat MersenneTwister.html | sed '/cutforpkg/,/cutforpkg/ s/.*//' > $(DIR)/MersenneTwister.html cp Random.jpg $(DIR)/ tar -zcvf $(DIR).tar.gz $(DIR)/ zip -r $(DIR).zip $(DIR)/ april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/MersenneTwister.h000066400000000000000000000361501263004425400263550ustar00rootroot00000000000000// MersenneTwister.h // Mersenne Twister random number generator -- a C++ class MTRand // Based on code by Makoto Matsumoto, Takuji Nishimura, and Shawn Cokus // Richard J. Wagner v1.1 28 September 2009 wagnerr@umich.edu // The Mersenne Twister is an algorithm for generating random numbers. It // was designed with consideration of the flaws in various other generators. // The period, 2^19937-1, and the order of equidistribution, 623 dimensions, // are far greater. The generator is also fast; it avoids multiplication and // division, and it benefits from caches and pipelines. For more information // see the inventors' web page at // http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html // Reference // M. Matsumoto and T. Nishimura, "Mersenne Twister: A 623-Dimensionally // Equidistributed Uniform Pseudo-Random Number Generator", ACM Transactions on // Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3-30. // Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura, // Copyright (C) 2000 - 2009, Richard J. Wagner // All rights reserved. // // Redistribution and use in source and binary forms, with or without // modification, are permitted provided that the following conditions // are met: // // 1. Redistributions of source code must retain the above copyright // notice, this list of conditions and the following disclaimer. // // 2. Redistributions in binary form must reproduce the above copyright // notice, this list of conditions and the following disclaimer in the // documentation and/or other materials provided with the distribution. // // 3. The names of its contributors may not be used to endorse or promote // products derived from this software without specific prior written // permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE // POSSIBILITY OF SUCH DAMAGE. // The original code included the following notice: // // When you use this, send an email to: m-mat@math.sci.hiroshima-u.ac.jp // with an appropriate reference to your work. // // It would be nice to CC: wagnerr@umich.edu and Cokus@math.washington.edu // when you write. #ifndef MERSENNETWISTER_H #define MERSENNETWISTER_H // Not thread safe (unless auto-initialization is avoided and each thread has // its own MTRand object) #include #include #include #include #include class MTRand { // Data public: typedef unsigned long uint32; // unsigned integer type, at least 32 bits enum { N = 624 }; // length of state vector enum { SAVE = N + 1 }; // length of array for save() protected: enum { M = 397 }; // period parameter uint32 state[N]; // internal state uint32 *pNext; // next value to get from state int left; // number of values left before reload needed // Methods public: MTRand( const uint32 oneSeed ); // initialize with a simple uint32 MTRand( uint32 *const bigSeed, uint32 const seedLength = N ); // or array MTRand(); // auto-initialize with /dev/urandom or time() and clock() MTRand( const MTRand& o ); // copy // Do NOT use for CRYPTOGRAPHY without securely hashing several returned // values together, otherwise the generator state can be learned after // reading 624 consecutive values. // Access to 32-bit random numbers uint32 randInt(); // integer in [0,2^32-1] uint32 randInt( const uint32 n ); // integer in [0,n] for n < 2^32 double rand(); // real number in [0,1] double rand( const double n ); // real number in [0,n] double randExc(); // real number in [0,1) double randExc( const double n ); // real number in [0,n) double randDblExc(); // real number in (0,1) double randDblExc( const double n ); // real number in (0,n) double operator()(); // same as rand() // Access to 53-bit random numbers (capacity of IEEE double precision) double rand53(); // real number in [0,1) // Access to nonuniform random number distributions double randNorm( const double mean = 0.0, const double stddev = 1.0 ); // Re-seeding functions with same behavior as initializers void seed( const uint32 oneSeed ); void seed( uint32 *const bigSeed, const uint32 seedLength = N ); void seed(); // Saving and loading generator state void save( uint32* saveArray ) const; // to array of size SAVE void load( uint32 *const loadArray ); // from such array friend std::ostream& operator<<( std::ostream& os, const MTRand& mtrand ); friend std::istream& operator>>( std::istream& is, MTRand& mtrand ); MTRand& operator=( const MTRand& o ); protected: void initialize( const uint32 oneSeed ); void reload(); uint32 hiBit( const uint32 u ) const { return u & 0x80000000UL; } uint32 loBit( const uint32 u ) const { return u & 0x00000001UL; } uint32 loBits( const uint32 u ) const { return u & 0x7fffffffUL; } uint32 mixBits( const uint32 u, const uint32 v ) const { return hiBit(u) | loBits(v); } uint32 magic( const uint32 u ) const { return loBit(u) ? 0x9908b0dfUL : 0x0UL; } uint32 twist( const uint32 m, const uint32 s0, const uint32 s1 ) const { return m ^ (mixBits(s0,s1)>>1) ^ magic(s1); } static uint32 hash( time_t t, clock_t c ); }; // Functions are defined in order of usage to assist inlining inline MTRand::uint32 MTRand::hash( time_t t, clock_t c ) { // Get a uint32 from t and c // Better than uint32(x) in case x is floating point in [0,1] // Based on code by Lawrence Kirby (fred@genesis.demon.co.uk) static uint32 differ = 0; // guarantee time-based seeds will change uint32 h1 = 0; unsigned char *p = (unsigned char *) &t; for( size_t i = 0; i < sizeof(t); ++i ) { h1 *= UCHAR_MAX + 2U; h1 += p[i]; } uint32 h2 = 0; p = (unsigned char *) &c; for( size_t j = 0; j < sizeof(c); ++j ) { h2 *= UCHAR_MAX + 2U; h2 += p[j]; } return ( h1 + differ++ ) ^ h2; } inline void MTRand::initialize( const uint32 seed ) { // Initialize generator state with seed // See Knuth TAOCP Vol 2, 3rd Ed, p.106 for multiplier. // In previous versions, most significant bits (MSBs) of the seed affect // only MSBs of the state array. Modified 9 Jan 2002 by Makoto Matsumoto. register uint32 *s = state; register uint32 *r = state; register int i = 1; *s++ = seed & 0xffffffffUL; for( ; i < N; ++i ) { *s++ = ( 1812433253UL * ( *r ^ (*r >> 30) ) + i ) & 0xffffffffUL; r++; } } inline void MTRand::reload() { // Generate N new values in state // Made clearer and faster by Matthew Bellew (matthew.bellew@home.com) static const int MmN = int(M) - int(N); // in case enums are unsigned register uint32 *p = state; register int i; for( i = N - M; i--; ++p ) *p = twist( p[M], p[0], p[1] ); for( i = M; --i; ++p ) *p = twist( p[MmN], p[0], p[1] ); *p = twist( p[MmN], p[0], state[0] ); left = N, pNext = state; } inline void MTRand::seed( const uint32 oneSeed ) { // Seed the generator with a simple uint32 initialize(oneSeed); reload(); } inline void MTRand::seed( uint32 *const bigSeed, const uint32 seedLength ) { // Seed the generator with an array of uint32's // There are 2^19937-1 possible initial states. This function allows // all of those to be accessed by providing at least 19937 bits (with a // default seed length of N = 624 uint32's). Any bits above the lower 32 // in each element are discarded. // Just call seed() if you want to get array from /dev/urandom initialize(19650218UL); register int i = 1; register uint32 j = 0; register int k = ( N > seedLength ? N : seedLength ); for( ; k; --k ) { state[i] = state[i] ^ ( (state[i-1] ^ (state[i-1] >> 30)) * 1664525UL ); state[i] += ( bigSeed[j] & 0xffffffffUL ) + j; state[i] &= 0xffffffffUL; ++i; ++j; if( i >= N ) { state[0] = state[N-1]; i = 1; } if( j >= seedLength ) j = 0; } for( k = N - 1; k; --k ) { state[i] = state[i] ^ ( (state[i-1] ^ (state[i-1] >> 30)) * 1566083941UL ); state[i] -= i; state[i] &= 0xffffffffUL; ++i; if( i >= N ) { state[0] = state[N-1]; i = 1; } } state[0] = 0x80000000UL; // MSB is 1, assuring non-zero initial array reload(); } inline void MTRand::seed() { // Seed the generator with an array from /dev/urandom if available // Otherwise use a hash of time() and clock() values // First try getting an array from /dev/urandom FILE* urandom = fopen( "/dev/urandom", "rb" ); if( urandom ) { uint32 bigSeed[N]; register uint32 *s = bigSeed; register int i = N; register bool success = true; while( success && i-- ) success = fread( s++, sizeof(uint32), 1, urandom ); fclose(urandom); if( success ) { seed( bigSeed, N ); return; } } // Was not successful, so use time() and clock() instead seed( hash( time(NULL), clock() ) ); } inline MTRand::MTRand( const uint32 oneSeed ) { seed(oneSeed); } inline MTRand::MTRand( uint32 *const bigSeed, const uint32 seedLength ) { seed(bigSeed,seedLength); } inline MTRand::MTRand() { seed(); } inline MTRand::MTRand( const MTRand& o ) { register const uint32 *t = o.state; register uint32 *s = state; register int i = N; for( ; i--; *s++ = *t++ ) {} left = o.left; pNext = &state[N-left]; } inline MTRand::uint32 MTRand::randInt() { // Pull a 32-bit integer from the generator state // Every other access function simply transforms the numbers extracted here if( left == 0 ) reload(); --left; register uint32 s1; s1 = *pNext++; s1 ^= (s1 >> 11); s1 ^= (s1 << 7) & 0x9d2c5680UL; s1 ^= (s1 << 15) & 0xefc60000UL; return ( s1 ^ (s1 >> 18) ); } inline MTRand::uint32 MTRand::randInt( const uint32 n ) { // Find which bits are used in n // Optimized by Magnus Jonsson (magnus@smartelectronix.com) uint32 used = n; used |= used >> 1; used |= used >> 2; used |= used >> 4; used |= used >> 8; used |= used >> 16; // Draw numbers until one is found in [0,n] uint32 i; do i = randInt() & used; // toss unused bits to shorten search while( i > n ); return i; } inline double MTRand::rand() { return double(randInt()) * (1.0/4294967295.0); } inline double MTRand::rand( const double n ) { return rand() * n; } inline double MTRand::randExc() { return double(randInt()) * (1.0/4294967296.0); } inline double MTRand::randExc( const double n ) { return randExc() * n; } inline double MTRand::randDblExc() { return ( double(randInt()) + 0.5 ) * (1.0/4294967296.0); } inline double MTRand::randDblExc( const double n ) { return randDblExc() * n; } inline double MTRand::rand53() { uint32 a = randInt() >> 5, b = randInt() >> 6; return ( a * 67108864.0 + b ) * (1.0/9007199254740992.0); // by Isaku Wada } inline double MTRand::randNorm( const double mean, const double stddev ) { // Return a real number from a normal (Gaussian) distribution with given // mean and standard deviation by polar form of Box-Muller transformation double x, y, r; do { x = 2.0 * rand() - 1.0; y = 2.0 * rand() - 1.0; r = x * x + y * y; } while ( r >= 1.0 || r == 0.0 ); double s = sqrt( -2.0 * log(r) / r ); return mean + x * s * stddev; } inline double MTRand::operator()() { return rand(); } inline void MTRand::save( uint32* saveArray ) const { register const uint32 *s = state; register uint32 *sa = saveArray; register int i = N; for( ; i--; *sa++ = *s++ ) {} *sa = left; } inline void MTRand::load( uint32 *const loadArray ) { register uint32 *s = state; register uint32 *la = loadArray; register int i = N; for( ; i--; *s++ = *la++ ) {} left = *la; pNext = &state[N-left]; } inline std::ostream& operator<<( std::ostream& os, const MTRand& mtrand ) { register const MTRand::uint32 *s = mtrand.state; register int i = mtrand.N; for( ; i--; os << *s++ << "\t" ) {} return os << mtrand.left; } inline std::istream& operator>>( std::istream& is, MTRand& mtrand ) { register MTRand::uint32 *s = mtrand.state; register int i = mtrand.N; for( ; i--; is >> *s++ ) {} is >> mtrand.left; mtrand.pNext = &mtrand.state[mtrand.N-mtrand.left]; return is; } inline MTRand& MTRand::operator=( const MTRand& o ) { if( this == &o ) return (*this); register const uint32 *t = o.state; register uint32 *s = state; register int i = N; for( ; i--; *s++ = *t++ ) {} left = o.left; pNext = &state[N-left]; return (*this); } #endif // MERSENNETWISTER_H // Change log: // // v0.1 - First release on 15 May 2000 // - Based on code by Makoto Matsumoto, Takuji Nishimura, and Shawn Cokus // - Translated from C to C++ // - Made completely ANSI compliant // - Designed convenient interface for initialization, seeding, and // obtaining numbers in default or user-defined ranges // - Added automatic seeding from /dev/urandom or time() and clock() // - Provided functions for saving and loading generator state // // v0.2 - Fixed bug which reloaded generator one step too late // // v0.3 - Switched to clearer, faster reload() code from Matthew Bellew // // v0.4 - Removed trailing newline in saved generator format to be consistent // with output format of built-in types // // v0.5 - Improved portability by replacing static const int's with enum's and // clarifying return values in seed(); suggested by Eric Heimburg // - Removed MAXINT constant; use 0xffffffffUL instead // // v0.6 - Eliminated seed overflow when uint32 is larger than 32 bits // - Changed integer [0,n] generator to give better uniformity // // v0.7 - Fixed operator precedence ambiguity in reload() // - Added access for real numbers in (0,1) and (0,n) // // v0.8 - Included time.h header to properly support time_t and clock_t // // v1.0 - Revised seeding to match 26 Jan 2002 update of Nishimura and Matsumoto // - Allowed for seeding with arrays of any length // - Added access for real numbers in [0,1) with 53-bit resolution // - Added access for real numbers from normal (Gaussian) distributions // - Increased overall speed by optimizing twist() // - Doubled speed of integer [0,n] generation // - Fixed out-of-range number generation on 64-bit machines // - Improved portability by substituting literal constants for long enum's // - Changed license from GNU LGPL to BSD // // v1.1 - Corrected parameter label in randNorm from "variance" to "stddev" // - Changed randNorm algorithm from basic to polar form for efficiency // - Updated includes from deprecated to standard forms // - Cleaned declarations and definitions to please Intel compiler // - Revised twist() operator to work on ones'-complement machines // - Fixed reload() function to work when N and M are unsigned // - Added copy constructor and copy operator from Salvador Espana april-ann-0.4.1/packages/basics/random/c_src/Mersenne-1.1/MersenneTwister.html000066400000000000000000000157241263004425400270760ustar00rootroot00000000000000 Mersenne Twister Random Number Generator