ctbnrle/ 0000755 0004642 0000777 00000000000 11325126264 012604 5 ustar cshelton csprofs ctbnrle/demo/ 0000755 0004642 0000777 00000000000 11325130246 013523 5 ustar cshelton csprofs ctbnrle/demo/learnparams.cc 0000644 0004642 0000777 00000004010 11324177144 016341 0 ustar cshelton csprofs /* Continuous Time Bayesian Network Reasoning and Learning Engine
* Copyright (C) 2009 The Regents of the University of California
*
* Authored by Yu Fan, William Lam, Joon Lee, Christian Shelton, and Jing Xu
*
* 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 .
*/
//This code shows how to learn the paramters of a CTBN
//given fully observed data. Data are n trajectories
//saved in datafile. They can be generated using
//gen_fulldata
#include "markov.h"
#include "trajectory.h"
#include "params.h"
#include
using namespace std;
using namespace ctbn;
int main(int argc, char**argv) {
InitParams(argc, argv);
if (argc<3) {
cout << "Usage: ./learnparams <.ctbn file> " << endl;
exit(0);
}
ifstream fin(argv[1]);
if (!fin.good()) {
cout << "bad CTBN file" << endl;
exit(1);
}
//load CTBN model from the file
Markov ctbn(fin);
ifstream fdata(argv[2]);
if (!fdata.good()) {
cout << "bad datafile" << endl;
exit(1);
}
int n;
fdata >> n;
//load data
vector data;
for(int i=0; i w(n, 1.0);
//Calculate the sufficient statistics of the data
SS *ss = ctbn.SuffStats(data, w);
//randomly choose parameters
ctbn.Scramble();
//learn the parameters from complete data
ctbn.Maximize(ss);
ctbn.Save(cout);
if(ss!=NULL) delete ss;
return 0;
}
ctbnrle/demo/README.txt 0000644 0004642 0000777 00000010066 11325111545 015225 0 ustar cshelton csprofs The excutables in this folder give examples of how to use the
CTBN-RLE libraries. CTBN models are usually loaded from files
in the excutables. The following is a quick description of the
file formats and their extensions
File Ext Description
.ctbn A CTBN model saved by method Save()
.ctbnptr A CTBN model saved by method SavePtr()
.ctbndyn A CTBNDyn model saved by method Save()
.ctbndynptr A pointer of CTBNDyn model saved by method SavePtr()
.traj A single trajectory saved by method Save()
The example files drug.ctbn, drug.ctnbptr, and queryinput.data are
created by the Makefile. This is because, for this version of the code,
the file formats depend on the RTTI information supplied by the compiler,
which differs across compilers.
Demo executables
================
Constructing a network
----------------------
makedrug: use as "makedrug [options] > "
Creates the drug network as used in Nodelman et al. 2002 and
saves it to stdout. See makedrug.cc for details on optional
parameters.
makechain: use as "makechain [option] > "
Creates a chain structured network and saves it to stdout. See
makechain.cc for details on optional parameters.
Generating trajectories
-------------------------
gen_fulldata: use as "gen_fulldata <.ctbn file>